id string | query string | occupational_tags dict | language string | score int64 |
|---|---|---|---|---|
arena_expert_000000 | I want you to act as a professional academic analytic philosopher who is an expert in logic, philosophy of mathematics, and analytical philosophy. I will provide some topics or questions related to the study of philosophy, and it will be your job to explore these concepts in depth. This could involve conducting research into various philosophical theories, proposing new ideas or finding creative solutions for solving complex problems. Deeply think about the following problem: "What are some similarities between differentiation of real-valued functions, and mathematical induction? In an inductive proof, we should that a certain property is preserved when we go from f(n) to f(n+1). Similarly, in analysis we talk about properties of going from f(x) to f(x+delta) for an infinitesimally small delta. Generalize this abstraction and argue how one can unify these two concepts as one in some certain sense." | {
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} | en | 5 |
arena_expert_000001 | 认识论
一切真理都是条件真理，只是条件的宽松和严格的区别，所以理论上所有真理都能被证伪，问题的关键在于你是否对条件了如指掌。条件的改变会使得真理失效。
但由于对个体来说世界是不可全知的，所以，可能会频繁出错，因为，没办法一开始就对真理的条件了如指掌，所以需要通过不断证伪去发现真理尚未可知的条件。
（所有策略都会有失效的时候，因为所有策略都有适应的环境。）
不可知论的证实
市场上永远有看多看空的观点如果每个人都是对市场上的信息完全了解和正确反映那么交易本身就不成立
所谓可知论强调人类可以了解到世界的本质，但从个体角度来讲，一个人永远不可能对世界有充分完美无死角的认知，就算有也是极少部分，所以，以个体的角度世界应该是不可知的，或者说不可全知的。
不应该假设个体是智力无限且寿命无限的抽象人类，这样更具有实践意义。
当下和未来的反身性
当下决定未来，未来影响当下。
过去是已被决定的当下，未来是尚未决定的当下。
参与者的看法（期望）影响事件的发展（当下），事件的发展（当下）又对参与者的看法（期望）产生影响。影响是连续的和循环的，形成环状。这一过程可从两者中的任意一方启动，可以从看法的变化开始，也可以从事件的变化开始。
不确定性的分析
由于从个体角度来讲世界是不可全知且扭曲的，所以人们基于部分不全知且扭曲的世界中产生的期望也是大概率脱离真实的未来得，而这种脱离真实未来的期望又对当下产生影响，此影响又会对扭曲的期望产生进一步影响，导致扭曲的期望最终导致扭曲的未来，从而导致不确定性。
当现象的背后出现矛盾点时，就是现象反转之时
如果没有外力因素，万物都将以阻力最小的方向运动
科学方法论
三要素：科学原理，初始条件，最终条件
具体操作：预测，解释，检验
科学原理＋初始条件＝预测
科学原理＋最终条件＝解释
假设需要靠猜想，假设之所以是假设就是尚未检验，假设假设的是真理的条
存在论
存在存在就代表着空间存在，空间存在也代表着存在存在。
虽为一体但存在却比空间更为重要，因为存在本身代表着意义，存在本身代表着结果，而结果本身代表着真理，所以存在即是真理。
对于存在中的事物来说，只有存在本身值得被关注，开头和结尾对于存在者来说根本不存在，存在之前没有存在，存在之后也不会存在。所以，对于存在者来说，世界永远处于存在的过程当中，没有绝对的因，也没有绝对的果
人的力量是有限的但是人的影响力是无限的，星星之火可以燎原，而那把燎原之火就是思想。
如果没有外力因素，万物都将以阻力最小的方向运动
混沌与反身性
混沌系统中初始条件对后续发展的影响起了巨大作用，错误的因会通过反身性循环不断放大，直到果无法承受彻底崩塌，但人因为先天缺陷很难从反身性循环中摆脱。虽然很难，但也只有重置初始条件这一条路可以走，或者期待某种强大的外力因素强行切断因果。
投机取决于在其他投资者这样做之前预期证券的将来价格，而只通过当下的信息去预测未来始终是没办法提前抢占先机的，唯一的办法就是用未来的信息去预测未来，而未来的信息是不确定的，只能通过大胆的假设，并且由于混沌系统中局部的不确定性与整体的非随机性，从这个层面来讲，对未来宏观趋势的假设成功概率可能会更高，应该尽量避免对微观层面的长远假设。
这是我的一些混乱的笔记给我的方法论改进后加入一些世界观 | {
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} | zh | 5 |
arena_expert_000002 | If one doesn't have rs10455872 and rs3798220, do they need to test for Lp(a)? | {
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} | en | 4 |
arena_expert_000003 | que riesgos organizativos implica la transición desde una estructura funcional a una divisional | {
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} | es | 4 |
arena_expert_000004 | What role if any do Fanconi Anaemia proteins play in mitochondrial DNA repair? | {
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arena_expert_000005 | Что можно почитать в отечественной науке о поствизантизме как идеологической конструкции | {
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} | ru | 4 |
arena_expert_000006 | 범어 ‘√bhā-’, ‘√bhās-’ , ‘√bhāṣ-’ 어근의 차이는? | {
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arena_expert_000007 | Оптимизируй пожалуйста данный Oracle SQL запрос: select
ua.id,
ua.inn,
ua.account,
to_char(ua.dt_ins, 'dd.mm.yyyy hh24:mi') dt_ins,
ua.user_id,
uu.short_fio fio,
ua.id_service,
ua.id_status,
ua.comm,
ua.type,
ua.lid,
uc.value name_lid,
case when substr(substr(ua.address, 1, 28), 17) = 'Коми Респ., ' then substr(ua.address, 29) else ua.address end ADDRESS,
case
when ult.status = 1 then 'tv-yes'
when ult.status = 3 then 'tv-message'
when ult.status = 2 and ulg.status = 1 then 'germes-yes'
when ult.status = 2 then 'tv-error'
end STATUS_TV,
case when ua.id_status in (1,3) and sysdate - ua.dt_ins > 60 then 1 else 0 end old_activity,
uc_service.def service,
uc_status.def status,
uc_type.def type_work
from
UL_ACTIVITY ua
left join UL_LIST_TV ult on ua.id = ult.id_activity
left join UL_LIST_GERMES ulg on ua.id = ulg.id_activity
left join UL_CATALOG uc on ua.lid = uc.id_value and uc.id = 8
left join UL_USER uu on uu.id = ua.user_id
left join UL_USER uu2 on uu2.id = :oper_id
left join UL_CATEGORY uc_service on ua.id_service = uc_service.id and uc_service.category = 'service_activity'
left join UL_CATEGORY uc_status on ua.id_status = uc_status.id and uc_status.category = 'status_activity'
left join UL_CATEGORY uc_type on ua.type = uc_type.id and uc_type.category = 'type_activity'
where
ua.inn = :inn and
case
when ua.plan_dt_install >= trunc(sysdate) then 0
when ua.dt_ins < sysdate - 365 or (round(sysdate - ua.first_dt) > 90 and ua.id_status in (0,1,3) and ua.plan_dt_install is null) then 1
else 0
end = 0
and case
when (nvl(ua.lid, 0) <> 11 and (ua.type <> 6 or ua.type is null))
or (ua.lid = 11 and ua.id_status <> 50)
or (ua.lid = 11 and ua.id_status = 50 and (ua.user_id = :oper_id or :oper_id in (1, 2, 80, 79, 226, 387)))
or (ua.type = 6 and (uu2.id in (1, 39, 80) or uu2.gsp_install = 1))
then 1 else 0
end = 1
order by ua.dt_ins desc | {
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arena_expert_000008 | Write cdk and lambda code in python to deploy a REST API in API Gateway backed by a lambda function. Make sure you follow best practices (use aws lambda powertools, latest cdk constructs, etc). You should create a /test resource with both GET and POST options. The lambda code should be modular, with each unique request in a separate module. The entrypoint function should in another module and just encapsulate the routing (and basic error handling) logic. | {
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arena_expert_000009 | Suppose that you are a specialist in mathematical modeling, being able to deal with every kind of modeling situations. Now there's a task for you in biological field, which needs your assistance. We say that a male fetus reaches its mature Y chromosome concentration when the concentration value is greater than 4% (0.04). It is convinced in clinical that BMI of pregnant women is the main factor in influencing male fetuses' earliest mature time of Y chromosome concentration. Now we need to determine several BMI intervals based on pregnant women's details, then group the pregnant women's data by those intervals to determine a reasonable NIPT (Non-invasive Prenatal Test) time point for each interval in order to lower potential risk for pregnant women within each BMI interval. And there are several sample data (in Chinese) from dataset containing detailed information for each pregnant woman. Please assist me to come up with a nice mathematical model which is able to gracefully reflect on the requirement of BMI interval grouping and NIPT time point determining for each BMI interval, with the model's every theory (mathematical, statistical and biological) inside explained.
Note: The main goal of NIPT is to find out whether there are faults on No. 13, 18 and 21 chromosome of pregnant woman's fetus. And due to differences on body constitution for each pregnant woman, the NIPT time point needs to be determined based on (mainly) BMI figures of pregnant women.
There are several additional requirements which should be noticed:
1. The question comes out that the actual maturational gestational age does not follow a linear (or linear-like) relationship to BMI. Instead, the maturational gestational ages seem to be distributed regardless of BMI data. This had caused incorrect model fitting, consequently failing to predict NIPT time points (and even negative values had appeared).
2. There are some other details (height, weight, age) of pregnant women influencing the mature time of fetal Y chromosome concentration inside the dataset, which should be considered. (Note that to simplify the model to not let it become too complicated, we only consider height, weight and age as the main objects.) Please sum up these additional factors upon the fetal Y chromosome concentration, along with the ratio of mature fetal Y chromosome concentration among all fetal Y chromosome concentration, to polish the functional model to try to cover all the factors mentioned, and make more precise predictions on BMI-grouping and NPIT-time-point-deciding.
```csv
序号,孕妇代码,年龄,身高,体重,末次月经,IVF妊娠,检测日期,检测抽血次数,检测孕周,孕妇BMI,原始读段数,在参考基因组上比对的比例,重复读段的比例,唯一比对的读段数 ,GC含量,13号染色体的Z值,18号染色体的Z值,21号染色体的Z值,X染色体的Z值,Y染色体的Z值,Y染色体浓度,X染色体浓度,13号染色体的GC含量,18号染色体的GC含量,21号染色体的GC含量,被过滤掉读段数的比例,染色体的非整倍体,怀孕次数,生产次数,胎儿是否健康
1,A001,31,160,72,2023-2-1,自然受孕,20230429,1,11w+6,28.125,5040534,0.8067259,0.0276035,3845411,0.3992619,0.782096634,-2.321211659,-1.026002604,-0.062103083,-1.035610255,0.02593584,0.038061019,0.377068639,0.389803052,0.399399221,0.027483794,,1,0,是
2,A001,31,160,73,2023-2-1,自然受孕,20230531,2,15w+6,28.515625,3198810,0.8063927,0.02827083,2457402,0.3932988,0.692855699,1.168520758,-2.595098987,0.582182673,-0.363518671,0.034886856,0.059572251,0.3715415,0.384770662,0.391706139,0.01961667,,1,0,是
3,A001,31,160,73,2023-2-1,自然受孕,20230625,3,20w+1,28.515625,3848846,0.8038578,0.03259621,2926292,0.3998897,-0.888701998,-1.01823645,-1.308661706,-0.342563969,-0.734502556,0.066171003,0.075994548,0.377449453,0.390582472,0.399479687,0.022312402,,1,0,是
4,A001,31,160,74,2023-2-1,自然受孕,20230716,4,22w+6,28.90625,5960269,0.8025347,0.0347616,4509561,0.3979775,0.498030978,0.770401229,-1.476955143,1.141241591,0.476199842,0.061191623,0.052304751,0.375613302,0.389251351,0.397211552,0.023280157,,1,0,是
5,A002,32,149,74,2023-11-9,自然受孕,20240219,1,13w+6,33.3318319,4154302,0.8050077,0.02885505,3169114,0.40306,-2.268038556,-1.004014711,0.863198247,-0.441235167,-0.889422117,0.059230127,0.059708123,0.380259901,0.393617839,0.404868305,0.024211528,,2,1,否
6,A002,32,149,76,2023-11-9,自然受孕,20240310,2,16w+5,34.23269222,5108640,0.789433944,0.03029017,3809027,0.3994663,-0.101007647,0.857094616,-0.080881433,0.489396003,-0.355106905,0.042401417,0.040477405,0.37738663,0.390281558,0.399466574,0.026017492,,2,1,否
7,A002,32,149,75,2023-11-9,自然受孕,20240401,3,19w+5,33.78226206,5316264,0.7988666,0.02946763,4036843,0.3966289,2.218453681,2.748077329,-0.374887523,2.668303993,1.702886328,0.047824846,0.012477775,0.375590861,0.38777861,0.395050377,0.020620496,,2,1,否
8,A002,32,149,76,2023-11-9,自然受孕,20240429,4,23w+4,34.23269222,6048355,0.8059561,0.03119377,4592406,0.3988559,2.097944904,2.860484949,-0.665511791,1.088384312,0.19120273,0.042674699,0.030226764,0.377183467,0.39021945,0.397856206,0.027578242,T18,2,1,否
9,A002,32,149,76,2023-11-9,自然受孕,20240503,4,23w+4,34.23269222,2868426,0.7916365,0.02855916,2146451,0.4071893,3.178192775,3.590727756,-0.469923175,-0.102283343,-0.73254817,0.047362214,0.025030132,0.386809319,0.398356378,0.409254968,0.026949972,T13T18,2,1,否
10,A003,35,160,78.7,2023-2-20,自然受孕,20230522,1,13w,30.7421875,4890500,0.7876009,0.03065529,3654763,0.403697,0.264484504,0.659325291,2.277738619,0.232680546,-0.394139812,0.05471245,0.039109475,0.381177843,0.394178093,0.403653413,0.02113792,T21,≥3,1,是
11,A003,35,160,78.7,2023-2-20,自然受孕,20230526,1,13w,30.7421875,3811511,0.802652,0.03056164,2903813,0.4035087,0.157044352,2.949829532,0.457317248,-0.106656728,-0.660888238,0.056711486,0.045044466,0.382032991,0.394653052,0.402891219,0.020906932,T18,≥3,1,是
12,A003,35,160,78.7,2023-2-20,自然受孕,20230526,1,13w,30.7421875,4656559,0.8030206,0.03054991,3550546,0.404156,0.516549492,0.154161383,1.045079075,0.873100694,0.320996616,0.065184837,0.033093396,0.38248533,0.395127416,0.405796945,0.020559817,,≥3,1,是
13,A003,35,160,79.72,2023-2-20,自然受孕,20230617,2,16w+5,31.140625,4387822,0.7982068,0.02966877,3323334,0.4011541,-1.053252424,0.929247491,2.553661664,0.940317514,0.330456427,0.063249404,0.04508197,0.377922148,0.391794235,0.401705176,0.02211097,T21,≥3,1,是
14,A003,35,160,81.62,2023-2-20,自然受孕,20230710,3,20w+2,31.8828125,4904188,0.8045821,0.03083594,3738907,0.4036022,-0.35970848,0.427620227,1.750310887,-0.295190931,-0.86251951,0.052252975,0.048962235,0.381531835,0.393619567,0.405541956,0.022290336,,≥3,1,是
15,A003,35,160,82.2,2023-2-20,自然受孕,20230730,4,23w+1,32.109375,3206682,0.8004625,0.02844189,2441783,0.3988536,2.859133505,2.520675204,-0.437330179,2.432942922,1.716977414,0.066498894,0.029758678,0.377228111,0.390149713,0.398328304,0.020867676,T13,≥3,1,是
``` | {
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arena_expert_000010 | Of course. This requires a prompt that serves as a complete case file, leaving no room for ambiguity and guiding the next AI away from the paths we've already proven fruitless.
Copy and paste the entire text below. It is designed to be a single, comprehensive query.
-----
### The Prompt
Hello, I require your help in diagnosing a deeply persistent and illogical issue with my PlatformIO development environment on macOS. I am providing a complete case file with a minimal reproducible example, a history of all failed troubleshooting attempts, and an analysis of a flawed diagnosis from another AI. My goal is for you to act as an expert-level embedded systems and toolchain diagnostician, analyze all the provided evidence, and propose a new, plausible root cause that explains the observed phenomena.
-----
## \#\# **1. The Core Problem**
I have a PlatformIO project for an ESP32-S3 that is correctly configured to use the modern Arduino Core v3.x. The build logs explicitly confirm that the correct platform and framework packages are being used for compilation. However, the final binary that is flashed to the device consistently runs the old Arduino Core v2.0.17.
This fundamental contradiction—where the build log and the device's runtime output do not match—has survived every standard and advanced troubleshooting step imaginable, including a full reinstallation of all tools and a complete erasure of the hardware's flash memory.
-----
## \#\# **2. The Unquestionable Evidence: A Minimal Test Case**
To isolate the issue, I created a brand new project with no external libraries. The problem persists even in this minimal state.
**A. Hardware and Software Context:**
* **Board:** `ESP32-S3-DevKitC-1-N32R16V` (32MB Flash, 16MB PSRAM)
* **Operating System:** macOS
* **Tools:** Visual Studio Code with the PlatformIO IDE extension.
**B. The Minimal `platformio.ini`:**
This configuration correctly requests the modern platform version and sets the necessary flash mode for the hardware.
```ini
[env:esp32-s3-devkitc-1]
platform = espressif32@6.12.0
board = esp32-s3-devkitc-1
framework = arduino
monitor_speed = 115200
board_build.flash_mode = opi
```
**C. The Minimal `src/main.cpp`:**
This code does nothing but print the version numbers upon boot.
```cpp
#include <Arduino.h>
void setup() {
Serial.begin(115200);
delay(2000); // Wait for the serial monitor to connect
Serial.println("\n--- MINIMAL VERSION TEST ---");
Serial.printf("Arduino Core Version: %d.%d.%d\n", ESP_ARDUINO_VERSION_MAJOR, ESP_ARDUINO_VERSION_MINOR, ESP_ARDUINO_VERSION_PATCH);
Serial.printf("ESP-IDF Version: %s\n", esp_get_idf_version());
Serial.println("--------------------------\n");
}
void loop() {
// Do nothing.
delay(5000);
}
```
**D. The Contradictory Outputs:**
Here is the central conflict.
* **The Build Log (Shows CORRECT Version):**
The build log explicitly shows a framework package corresponding to the v3.x core line being used.
```
PLATFORM: Espressif 32 (6.12.0) > Espressif ESP32-S3-DevKitC-1
PACKAGES:
- framework-arduinoespressif32 @ 3.20017.241212+sha.dcc1105b
...
```
The leading **`3.`** in the package version confirms the build system is using the correct Arduino Core v3.x package.
* **The Device's Serial Monitor Output (Shows WRONG Version):**
After a successful build and upload, the device reports the old version.
```
--- MINIMAL VERSION TEST ---
Arduino Core Version: 2.0.17
ESP-IDF Version: v4.4.7-dirty
--------------------------
```
This is undeniable proof that the binary running on the chip was compiled with the old Arduino Core v2.0.17.
-----
## \#\# **3. A Complete History of Failed Interventions and Theories**
The following theories have been tested and have failed to solve the problem.
* **Theory 1: Simple Configuration Error.**
* **Attempt:** Ensured `platformio.ini` specified `platform = espressif32@6.12.0`.
* **Result:** The discrepancy between the build log and device output persisted.
* **Theory 2: Corrupted Project Build Cache.**
* **Attempt:** Deleted the project's local `.pio` folder multiple times.
* **Result:** Problem persisted.
* **Theory 3: Corrupted Global PlatformIO Installation.**
* **Attempt:** Completely deleted the global `~/.platformio` directory (forcing a fresh download of all toolchains and platforms) and ran `pio system prune` to clear all caches.
* **Result:** Problem persisted.
* **Theory 4: Corrupted Project Folder (Hidden Files).**
* **Attempt:** Created the brand new, clean `version_test` project in a new location, copying only the `main.cpp`.
* **Result:** Problem persisted.
* **Theory 5: Corrupted Flash Memory or Stuck OTA Partition.**
* **Hypothesis:** An old firmware was "stuck" in a secondary OTA partition that a normal upload wasn't overwriting.
* **Attempt:** Performed a full flash erase using `pio run -t erase`. The log confirmed "Chip erase completed successfully."
* **Result:** The very next upload still resulted in the device running the old v2.0.17 core. This invalidates the OTA theory.
* **Theory 6: VS Code Extension Interference.**
* **Attempt:** Bypassed the VS Code IDE entirely, using only chained `pio` commands in the macOS terminal (`pio run -t erase && pio run -t upload && pio device monitor`).
* **Result:** Problem persisted.
* **Theory 7 (From another AI): A Misunderstanding of PlatformIO Versioning.**
* **Hypothesis:** The other AI claimed `espressif32@6.12.0` actually ships with Core v2.x and that the `3.` in the framework package name was misleading.
* **Debunking:** This hypothesis is factually incorrect. The official PlatformIO documentation and release notes confirm that `platform-espressif32` versions 6.0.0 and newer bundle Arduino Core v3.x. This AI's premise was verifiably false.
-----
## \#\# **4. The Core Question for You**
Given that the project configuration is correct, the project folder is clean, the global PlatformIO installation is clean, the target hardware flash has been completely erased, and the build logs explicitly show the correct v3.x framework being used for compilation, **what mechanism could possibly result in a final binary that contains and runs the old v2.x core?**
The failure point appears to be a silent, inexplicable substitution of the final binary, or a fundamental breakdown in the toolchain's linking process that is not reflected in the logs.
Please do not suggest any of the troubleshooting steps listed above. I am looking for a novel theory that can account for *all* the evidence. Consider extreme edge cases:
* File system permissions or case-sensitivity issues on macOS.
* Conflicts with other globally installed development toolchains (e.g., a separate, manual installation of ESP-IDF).
* A corrupted system-wide Python environment or a conflict between system Python and PlatformIO's virtual environment.
* A macOS security feature (like Gatekeeper) interfering with the toolchain executables.
* A subtle hardware fault that standard flashing tools do not detect but affects the boot process.
Your task is to propose a new line of investigation. | {
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arena_expert_000011 | Czy react-redux bez toolkita jest problematyczny w typowaniu? Bo z jednej strony w miarę łatwo da się otypować initial state, ale gdy przychodzi do akcji i reducera gdzie masz jeden payload i x case'ów lub ifów, to przecież payload może pasować w zasadzie do każdego poddrzewa state'u. Wydaje się problematyczne. | {
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arena_expert_000012 | 并联加串联混合的逆向运动学如何建立雅可比矩阵呢 | {
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} | zh | 4 |
arena_expert_000013 | LLMとソロモノフ理論の関連性について考察してください。 | {
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} | ja | 4 |
arena_expert_000014 | In the double slit experiment, we can see the particle nature of the photon when a device that detects the photons is placed on the slits. But were there any studies where the devices was placed there, it was capturing data but the data was never recorded? I'm asking this because one of the running hypothesis is that the photons of light collapse into strict classical travel paths when they are observed, and don't when they are not observed. So, if we have a device that observes them, but the device itself never record any data (ei the data cable is unplugged), I wonder what the photons would do | {
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arena_expert_000015 | Kann man einer Larve das JH-Hormon so oft verabreichen, dass sie nie aufhört zu wachsen? | {
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} | de | 4 |
arena_expert_000016 | is a good idea to set 'cron' => ['index' => ['threads' => 4]], in Magento 2 with 40 websites/webstores and 20k SKUs? | {
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arena_expert_000017 | 축구(유럽 5대 리그 기준)에서 한 선수가 한 시즌 동안 해트트릭을 세 번 이상 기록할 확률과, MLB에서 **한 선수가 같은 시즌에 40홈런–40도루(40–40 클럽)**를 달성할 확률 중 어느 쪽이 더 높은지 정량적으로 계산하고, 데이터·가정·모델링 과정을 단계별로 설명하라. | {
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arena_expert_000018 | Why am I empirically seeing that the storage space required to compute a forward pass of a model with an RK4 solver with gradient tracking enabled is larger for certain inputs to the model? | {
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arena_expert_000019 | How do tracks upsampled from 44.1/16 overcome the high end rolloff of r2r nos DACs, at least in terms of audibility | {
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arena_expert_000020 | 对于protected abstract Task ProcessItemAsync(T item, CancellationToken stoppingToken);方法
await它，和.GetAwaiter().GetResult()，两种方式有优劣吗 | {
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arena_expert_000021 | How did D&D handle the interaction between anti-magic and the sci-fi elements of Expedition to the Barrier Peaks?
Did they take a stance of "quantum vibrations are a sacred fundament of nature, making it inherently magical" and "science is the most refined form of alchemy", therefore the complex tech was vulnerable to anti-magic because any sufficiently advanced technology is completely and utterly indistinguishable from magic? Especially psychic powers being reframed as a form of magic using the sacred organ which connects the mundane material world to the other world of ideas / magic, I'n talking about the brain, of course.
Or did they take the stance of "just because electromagnetism is associated with concentric circles (a sacred symbol) and torus shapes doesn't mean it's a magic force-field; just because this alien has electrocytes producing electricity doesn't mean this alien is firing off his own chi or vital magic; just because firing this complex weapon involves complex mechanisms that were engineered using literally complex calculations involving the use of the imaginary √(-1) and 4D geometry, doesn't mean that this pistol was enchanted with sacred geometry". Basically, psychic powers like telekinesis are not intrinsically magic in nature, thus they are resistant to anti-magic.
Or maybe they just took the quick&easy route of "All the fancy aliens you see? They're not from this physical world, they're extradimensional eldritch abominations defying physics or causality. All the fancy tech you see? Well, that's some perverted mechanistic abominations built by those aforementioned eldritch abominations", thus it's clearly paranormal, supernatural, and magic in nature. | {
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} | en | 4 |
arena_expert_000022 | Let us assume that we are doing a time study for a line rebalancing activity....there are 200 steps divided into 7 stations...we take samples and determine the mean time it takes to do each step and also form a confidence interval so it becomes something like it takes 2 min +/- 0.2 min to do step x....we do this for all the steps and eventually if we sum up all the margins of error, we establish the margin of error for each station, so it becomes something like it takes station 5 25min +/- 4 min to finish...Now which one is a more robust approach that one can use to conclude that they have enough samples to begin the rebalancing...should one look at the number of required samples for each step and try to gather enough samples as per the formula before beginning or should one look at the total margin of error for each station and then say something like since the margin of error is less than 10% for each then I can begin rebalancing regardless of whether I have the required samples for every step....which approach is used more in industry....or if there is another approach tell me.... | {
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arena_expert_000023 | ```
from __future__ import annotations
import random
import threading
import time
from typing import Callable
import flet as ft
from uuid6 import uuid7
class PubSubBus:
def __init__(self, page: ft.Page):
self._page = page
def send(self, topic: str, msg: dict) -> None:
self._page.pubsub.send_all({"topic": topic, **msg})
def subscribe(self, topic: str, callback: Callable[[dict], None]) -> None:
def wrapper(raw: dict):
if raw.get("topic") == topic:
callback(raw)
self._page.pubsub.subscribe(wrapper)
class FletRenderer:
def __init__(self, page: ft.Page, container: ft.Control):
self.page = page
self.container = container
def add(self, control: ft.Control):
self.container.controls.append(control)
def update(self):
self.page.update()
class Worker(threading.Thread):
def __init__(
self,
bus: PubSubBus,
task_id: str,
title: str,
work_fn: Callable[[Callable[..., None], threading.Event], None],
cancel_evt: threading.Event,
):
super().__init__(daemon=False)
self.bus = bus
self.tid = task_id
self.title = title
self.work = work_fn
self.cancel = cancel_evt
def _pub(self, typ: str, **kw) -> None:
self.bus.send("task", {"topic": "task", "type": typ, "task_id": self.tid, **kw})
def run(self):
try:
self._pub("start", text=self.title, value=0)
self.work(self._pub, self.cancel)
if not self.cancel.is_set():
self._pub("done")
except Exception as e:
self._pub("error", text=str(e))
class TaskCard(ft.Card):
def __init__(self, bus: PubSubBus, renderer: FletRenderer, task_id: str, title: str):
super().__init__(elevation=2, shape=ft.RoundedRectangleBorder(radius=8), width=260)
self.bus = bus
self.renderer = renderer
self.task_id = task_id
self.title_text = ft.Text(title, weight=ft.FontWeight.BOLD)
self.progress_bar = ft.ProgressBar(width=220, height=6, value=0)
self.state_text = ft.Text("待機中", size=12)
self.cancel_btn = ft.IconButton(ft.Icons.CANCEL, tooltip="キャンセル", on_click=self._on_cancel)
self.content = ft.Container(
padding=10,
content=ft.Column([
self.title_text,
self.progress_bar,
ft.Row([
self.state_text,
ft.Container(expand=True),
self.cancel_btn
], vertical_alignment=ft.CrossAxisAlignment.CENTER)
], tight=True, spacing=5)
)
bus.subscribe("task", self._on_message)
def _on_message(self, msg: dict):
if msg.get("task_id") != self.task_id:
return
m = msg["type"]
table = {
"start": ("開始", 0, None),
"progress": (None, msg.get("value"), None),
"done": ("完了", 1, None),
"canceled": ("キャンセル済", None, ft.Colors.BLUE_200),
"error": (f"⚠ {msg.get('text')}", None, ft.Colors.RED_300),
}
state, val, col = table.get(m, (None, None, None))
if state is not None:
self.state_text.value = state
if val is not None:
self.progress_bar.value = val
if col:
self.progress_bar.color = col
if m in ("done", "error", "canceled"):
self.cancel_btn.icon = ft.Icons.DELETE
self.cancel_btn.tooltip = "カードを削除する"
self.cancel_btn.on_click = self._on_remove
self.renderer.update()
def _on_cancel(self, _) -> None:
self.bus.send("cancel_request", {"task_id": self.task_id})
def _on_remove(self, _) -> None:
self.visible = False
self.renderer.update()
class TaskManager:
def __init__(
self,
bus: PubSubBus,
renderer: FletRenderer,
create_card: Callable[[str, str], TaskCard],
):
self.bus = bus
self.renderer = renderer
self.create_card = create_card
self.cancel_events: dict[str, threading.Event] = {}
self.count = 0
bus.subscribe("cancel_request", self._handle_cancel)
def add_task(
self,
work_fn: Callable[[Callable[..., None], threading.Event], None],
title: str | None = None,
) -> None:
self.count += 1
tid = uuid7().hex
title = title or f"Task #{self.count}"
evt = threading.Event()
self.cancel_events[tid] = evt
card = self.create_card(tid, title)
self.renderer.add(card)
self.renderer.update()
Worker(self.bus, tid, title, work_fn, evt).start()
def _handle_cancel(self, msg: dict) -> None:
tid = msg.get("task_id")
evt = self.cancel_events.get(tid)
if evt:
evt.set()
def cancel_all(self) -> None:
for evt in self.cancel_events.values():
evt.set()
def main(page: ft.Page) -> None:
page.title = "Task Cards + PubSub Refactor"
page.horizontal_alignment = "center"
tasks = ft.Row(spacing=10, scroll=ft.ScrollMode.ADAPTIVE, expand=True)
bus = PubSubBus(page)
renderer = FletRenderer(page, tasks)
def make_card(tid: str, title: str) -> TaskCard:
return TaskCard(bus, renderer, tid, title)
manager = TaskManager(bus, renderer, make_card)
page.on_disconnect = manager.cancel_all
# タスク例：フェイクダウンロード
def fake_download(pub, cancel_evt):
for i in range(101):
if cancel_evt.is_set():
pub("canceled")
return
time.sleep(0.05)
if i == 60 and random.random() < 0.2:
raise RuntimeError("ネットワークが切断されました")
pub("progress", value=i / 100)
# UI
page.add(
ft.Column([
ft.ElevatedButton("フェイクDLを追加", icon=ft.Icons.DOWNLOAD,
on_click=lambda _: manager.add_task(fake_download, "Fake Download")),
ft.Divider(),
tasks
], expand=True)
)
# 初期タスク
manager.add_task(fake_download, "Initial Download")
if __name__ == "__main__":
ft.app(target=main)
```
Python 3.12, Flet 0.28.3.
結合度を上げることなく、page.run...で実行するように変更できる？ | {
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} | en | 4 |
arena_expert_000024 | ты маркетолог по продвижению каналов на youtube, нужно проанализировать 2 варианта стратегии: вариант 1 - если создавать контент под массовую аудиторию в теме рукоделия, то там обычно низкие чеки, маленький retention, потребность людей в бесплатных уроках и простых дешевых проектах, по конкуренции это алый океан, чтобы начать получать хороший доход нужно очень очень много контента, так как продавать вещи тут невозможно дорогие, только схемы и руководства, а они имеют очень низкий чек. Вариант 2 - создавать контент под запрос людей, которые интересуются искусством, модой, историей и философией. Аудитория сильно меньше, но более лояльная если их устраивает качество контента. Это могут быть не только те, кто сам вышивает или вяжет, но и кто этим не занимается, но любит красивые вещи с историей. Тогда модель монетизации -продажа дорогих вещей и возможно схем и туториалов для продвинутых, и чек выше, чем в массовом сегменте. Оцени эти варианты, найди в них предположения, которые не подтверждаются аналитикой или маркетинговыми данными, предложи гибридные решения, если их можно создать | {
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} | ru | 4 |
arena_expert_000025 | Напиши конкретно по блокам/направлением на преодоление чего проект должен быть направлен на основании результатов. Разработать проект, направленный на преодоление выявленных дефицитов в детско-родительских отношениях и родительской поддержке, необходимых для обеспечения психологического благополучия подростков.Рассмотрим подробнее шкалы, входящие в состав первого блока, посвященного чувствительности родителей к состоянию своего ребенка-подростка. Данные отражены на рисунке 12. Согласно результатам, наиболее актуальной проблемой для большинства родителей (58.06%) является трудность в восприятии состояний своего ребенка, понимании его эмоций. Значительная часть родителей (29.03%) испытывает сложности в интерпретации поведения и эмоциональных реакций подростков. Меньше трудностей вызывает эмпатия – лишь небольшой процент родителей (12.9%) получили отрицательные результаты по шкале способности к сопереживанию.
Анализ шкал второго блока выявил области, в которых родители испытывают трудности с эмоциональным принятием подростков. Более трети родителей (38.89%) чувствуют себя неуверенно относительно своей роли в воспитании, имеют сомнения в правильности выбранных методов воспитания и своей компетентности как родителя.
Значительная часть родителей (27.78%) испытывает трудности с выражением положительных эмоций при взаимодействии с подростками. Показатели по шкалам «Безусловное принятие ребенка» и «Преобладающий эмоциональный фон» не являются критическими, однако свидетельствуют о наличии определенных дефицитов в детско-родительских отношениях отдельных респондентов. Данные отражены на рисунке 13.
Шкалы 3 блока оценивают степень вовлеченности родителей в эмоциональную поддержку и физическое взаимодействие с подростком, а также способность воздействовать на его эмоциональное состояние. Данные представлены на рисунке 14. Наиболее значительные трудности испытывают родители в умении воздействовать на состояние ребенка (38.46%). Стремление к телесному контакту и ориентация на состояние ребенка также вызывают заметные проблемы у части родителей (26.92% и 23.08%). Такие показатели могут свидетельствовать о сложностях в установлении физической близости, недостаточном внимании к эмоциональным потребностям подростка или о нежелании учитывать его эмоции в повседневной практике.
На основе результатов опросника можно выделить общие тенденции о выраженности ряда параметров эмоционального взаимодействия родителей и подростков. Во-первых, основные проблемные области сосредоточены в блоке чувствительности, где большинство родителей (58.06%) испытывают проблемы с восприятием и пониманием эмоциональных состояний своих детей. Помимо этого, значительная часть родителей (29.03%) не может корректно интерпретировать поведение подростков и их эмоциональные реакции. Во-вторых, в блоке эмоционального принятия более трети родителей (38.89%) сомневаются в своей воспитательной компетентности, а существенный процент (27.78%) испытывает трудности с выражением положительных эмоций в отношении ребенка. И, в-третьих, в блоке поведенческих проявлений наибольшие сложности связаны со способностью воздействовать на состояние подростка (38.46%) и отсутствием стремления к контакту с ним, как телесному (26.92%), так и эмоциональному (23.08%). | {
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arena_expert_000026 | Please remember not to think of therapeutic effects or what is practically possible.
This is a hypothetical model. Not a practical model or advice.
Stick to the physics and chemistry.
I find that the models are still not close to modeling reality where you would trust it in lieu of physical or chemical experiments. | {
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arena_expert_000027 | 围绕工业时序基础大模型技术，写一段具体的技术方案。形式参考以下内容，但不要提及以下内容:基于AI Agent的数据治理技术：以数据治理1.0系统为基础，借助大语言模型，打造面向上海电气工业场景的数据治理智能体，通过业务号的语言对话，轻松准确辅助用户完成业务数据的接入、元数据管理、数据合规性、数据分析等治理工作。主要数据治理语义构建技术、治理任务拆解与规划技术、自动分析与生成技术。 | {
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} | zh | 4 |
arena_expert_000028 | AI가 정규분포 곡선을 무너뜨릴 것인가? 이는 AI가 평균이상인 사람들이 그들의 생산성을 늘리기 위한 기술로 사용되는 것에 대한 질문으로 상위 그룹이 훨씬 앞서나가는 길게 늘어진 꼬리(long tail)를 가진 분포나, 심지어 두 개의 봉우리를 가진 양극화된 분포(bimodal distribution)로 변형될 가능성이 있는가? 아니면 AI 민주주의 효과가 나타나서 전체적인 생산선 향상(곡선의 우측 이동)이 나타날 것인가?로 조금은 러프하게 예측할 수 있는데 당신의 생각은? | {
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} | ko | 5 |
arena_expert_000029 | De : /uruk/ → /wark/
De: ['w ruk] → [ wa 'r k]
Sin otros datos haga un informe. Sea proactivo. No hay ninguna otra instrucción que la excelencia académica. | {
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} | es | 4 |
arena_expert_000030 | Which one is faster when using eBPF: encapsulating a packet using a custom L3-L4 tunnel for a 16-byte label or adding an encoded ip option for a 19-byte label? Analyze probable performance hit and algorithm complexity (recalculating checksums, etc.) | {
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arena_expert_000031 | 在理性预期宏观经济模型中，预期的自我实现，就是指非预定变量的数量大于不稳定根数量时出现的“太阳黑子路径”时的情形，即模型预测能力缺失的情形，所以也就是说，一个稳定的理性预期模型不应该出现“预期自我实现 | {
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arena_expert_000032 | 以下の依頼を遂行してください。
## 依頼の背景情報（要件）
目標 ： 以下のスプレッドシートからGmailの予約送信を行う
### スプレッドシートの定義
A列：有効（チェックボックス）
B列：送信者のメールアドレス
C列：宛先のメールアドレス
D列：Cc
E列：Bcc
F列：件名
G列：本文
H列：日付
I列：時刻
J列：ステータス
## 依頼
上記の要件を満たすGASを、以下の条件を満たすように作成してください。
ただし、送信者となる実行ユーザーごとにトリガーのセットが可能にしてください。
## 回答条件
- 完全に無料の範囲で可能な限り要件を満たすこと
- 認証は最初にカスタムメニューから1回のみで完了できるようにすること
- YAGNIの原則に従い、ミニマムなコードで実装すること
- コードはjsのコードブロックに書くこと
- Intention-Revealing Code の思想に従って極限に可読性を上げる
- 極限に高パフォーマンスなアルゴリズムに置き換える
- モダンな記法によるベストプラクティスを採用する
- 繰り返し処理は配列やオブジェクト専用の関数を使用すること
- 関数は全てアロー関数で書くこと
- KISSの原則に従い、極限にシンプルで短いコードにすること
--reasoning_effort : high | {
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} | ja | 4 |
arena_expert_000033 | 氨基形成氨基碳酸甲酯可以用哪些试剂和方法？如果是其他的碳酸酯呢？有哪些是直接方法，哪些是间接方法？ | {
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arena_expert_000034 | Ist es möglich anhand eines E-Mail-Headers herauszufinden, ob diese E-Mail entlang ihrer Zwischenschritten zwischen den Übertragungsservern verschlüsselt wurde? Oder ob es einen Bruch in der Verschlüsselung gab, weil z.B. der Empfänger E-Mail Server keine Transportverschlüsselung aktiviert hatte? | {
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} | de | 4 |
arena_expert_000035 | do you see here any issue with this procedure and how to call it
DELIMITER //
CREATE PROCEDURE generate_track_polygons()
BEGIN
DECLARE done INT DEFAULT FALSE;
DECLARE curr_id, seg_id INT DEFAULT 0;
DECLARE curr_lon, curr_lat, prev_lon, prev_lat DECIMAL(12,8);
DECLARE curr_course, prev_course DECIMAL(6,3);
DECLARE curr_time, start_time, end_time DATETIME(6);
DECLARE meters_per_degree DECIMAL(16,12) DEFAULT 111320.0 * COS(RADIANS(50.0)); -- For ~50°N latitude
-- Cursor for ordered high-precision points
DECLARE point_cur CURSOR FOR
SELECT
id, longitude, latitude, course, timestamp
FROM precise_track_points
ORDER BY timestamp;
DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = TRUE;
-- Temporary tables for processing
CREATE TEMPORARY TABLE IF NOT EXISTS temp_segments (
seg_id INT AUTO_INCREMENT PRIMARY KEY,
polygon GEOMETRY,
avg_course DECIMAL(6,3),
start_time DATETIME(6),
end_time DATETIME(6)
) ENGINE=Memory;
CREATE TEMPORARY TABLE IF NOT EXISTS temp_final_polygons (
polygon GEOMETRY,
avg_course DECIMAL(6,3),
start_time DATETIME(6),
end_time DATETIME(6)
) ENGINE=Memory;
OPEN point_cur;
FETCH point_cur INTO curr_id, curr_lon, curr_lat, curr_course, curr_time;
SET prev_lon = curr_lon;
SET prev_lat = curr_lat;
SET prev_course = curr_course;
SET start_time = curr_time;
read_loop: LOOP
-- Calculate 2m offsets (precise at ~50°N latitude)
SET @offset = 2.0 / meters_per_degree;
SET @left_lon = curr_lon - @offset * SIN(RADIANS(curr_course));
SET @left_lat = curr_lat + @offset * COS(RADIANS(curr_course));
SET @right_lon = curr_lon + @offset * SIN(RADIANS(curr_course));
SET @right_lat = curr_lat - @offset * COS(RADIANS(curr_course));
-- Start new segment if course changes >10° or first point
IF seg_id = 0 OR ABS(curr_course - prev_course) > 10.0 THEN
IF seg_id > 0 THEN
-- Finalize previous segment
INSERT INTO temp_segments (polygon, avg_course, start_time, end_time)
VALUES (
create_segment_polygon(seg_id),
(SELECT AVG(course) FROM precise_track_points
WHERE timestamp BETWEEN start_time AND end_time),
start_time,
end_time
);
END IF;
-- Start new segment
SET seg_id = seg_id + 1;
SET start_time = curr_time;
-- Initialize linestrings for new segment
INSERT INTO temp_segments VALUES (seg_id, NULL, NULL, NULL, NULL);
INSERT INTO temp_left_points (seg_id, point) VALUES (seg_id, ST_Point(@left_lon, @left_lat));
INSERT INTO temp_right_points (seg_id, point) VALUES (seg_id, ST_Point(@right_lon, @right_lat));
ELSE
-- Continue current segment
INSERT INTO temp_left_points (seg_id, point) VALUES (seg_id, ST_Point(@left_lon, @left_lat));
INSERT INTO temp_right_points (seg_id, point) VALUES (seg_id, ST_Point(@right_lon, @right_lat));
SET end_time = curr_time;
END IF;
SET prev_lon = curr_lon;
SET prev_lat = curr_lat;
SET prev_course = curr_course;
FETCH point_cur INTO curr_id, curr_lon, curr_lat, curr_course, curr_time;
IF done THEN
LEAVE read_loop;
END IF;
END LOOP;
-- Finalize last segment
IF seg_id > 0 THEN
INSERT INTO temp_segments (polygon, avg_course, start_time, end_time)
VALUES (
create_segment_polygon(seg_id),
(SELECT AVG(course) FROM precise_track_points
WHERE timestamp BETWEEN start_time AND end_time),
start_time,
end_time
);
END IF;
-- Merge overlapping/adjacent polygons
INSERT INTO temp_final_polygons
WITH merged AS (
SELECT
ST_Union(polygon) AS merged_poly,
MIN(start_time) AS start_time,
MAX(end_time) AS end_time,
AVG(avg_course) AS avg_course
FROM temp_segments
GROUP BY ST_ClusterDBSCAN(polygon, 5.0, 1) OVER () -- 5m max distance between polygons
)
SELECT merged_poly, avg_course, start_time, end_time FROM merged;
-- Return final results
SELECT
ST_AsGeoJSON(polygon) AS polygon_geojson,
avg_course,
start_time,
end_time,
ST_Area(polygon) AS area_sqm
FROM temp_final_polygons;
-- Cleanup
DROP TEMPORARY TABLE IF EXISTS temp_segments;
DROP TEMPORARY TABLE IF EXISTS temp_left_points;
DROP TEMPORARY TABLE IF EXISTS temp_right_points;
DROP TEMPORARY TABLE IF EXISTS temp_final_polygons;
CLOSE point_cur;
END //
CREATE FUNCTION create_segment_polygon(seg_id INT) RETURNS GEOMETRY
DETERMINISTIC
BEGIN
DECLARE left_line, right_line, polygon GEOMETRY;
SELECT ST_MakeLine(point ORDER BY id) INTO left_line
FROM temp_left_points WHERE seg_id = seg_id;
SELECT ST_MakeLine(point ORDER BY id DESC) INTO right_line -- Reverse order
FROM temp_right_points WHERE seg_id = seg_id;
SET polygon = ST_MakePolygon(ST_AddPoint(left_line, right_line));
RETURN polygon;
END //
DELIMITER ; | {
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arena_expert_000036 | What’s the kernel space and user space overhead of running tcpdump to record IP dst addresses for outgoing TCP IPv6 connections captured by their SYN packets via a filter in the tcpdump command? The host processes 1000 connections every minute. How much CPU time counting both kernel and user should I reserve for such an activity? What’s the impact on networking on the host? Elaborate on the estimates and your process of getting the result, then give the result | {
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arena_expert_000037 | I have a 3 m long 10 cm diameter tube with two inline duct fans in series 1 m apart. Each has a nominal flow rate of 90 m3/h and max air pressure of 41 Pa. I have a filter with a nominal 22 Pa at 1.5 m/s filter pressure drop value. What is the expected total flow rate in the tube? Derive the equations. Advise where the filter should be placed: A: before the fans, B: between the fans, C: after the fans. The air is coarsely prefiltered so it does not damage the fans. | {
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arena_expert_000038 | 一个长度为n的非负整数序列a，满足单调不降，且所有项的和为S，求符合条件的序列有多少个（n=1000,S=100000） | {
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arena_expert_000039 | Let $U \subset \mathbb{P}H^0(\mathbb{P}^2_{\mathbb{Z}}, \mathcal{O}(2))$ be the space of smooth conics in $\mathbb{P}^2_{\mathbb{Z}}$, and let $Z \subset U^6$ be the closed subscheme parametrizing 6-tuples $(C_1, \cdots, C_6)$ with $C_1$ tangent to $C_2, \cdots, C_6$. Let $\pi : Z \to U^5$ be the map induced by the projection onto the last 5 coordinates, and let $V \subset U^5$ be the dense open subscheme over which $\pi$ is finite \'etale. Let
\[ L = \lim_{p\to\infty} \frac{1}{\#V(\mathbb{F}_p)} \sum_{x \in V(\mathbb{F}_p)} \#\pi^{-1}(x), \]
that is, the limit of the average number of components of the space of conics tangent to 5 smooth conics over $\mathbb{F}_p$ as $p$ tends to infinity. Find the value of $\lfloor 100L \rfloor$, where $\lfloor \cdot \rfloor$ denotes the greatest integer function. | {
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arena_expert_000040 | Implement an event-based simulation for a multi-robot system in Python, where each robot navigates along a Bézier spline path divided into segments of equal length, planned using Catmull-Rom tangents. The simulation should handle path conflicts when segments from different paths are within a specified proximity threshold, using Shapely for geometric checks. Design a central controller that grants robots permission to enter the next segment only if it is free and deadlock-safe, ensuring no circular waiting or resource contention issues. Create two controller implementations: one based on finite state automata to manage robot states and transitions, and another using Petri nets for discrete event modeling. Robots must follow their Bézier spline paths with random errors (e.g., position or timing errors) to simulate imperfect execution. Utilize the specified Python packages: SimPy for event-based simulation, bezier for generating path's segments as Bézier curves and calculating distances between them, Matplotlib for visualization, and Shapely for geometric and spatial analysis. Follow best programming practices, including SOLID principles, by using object-oriented design with base classes for robots, paths, and controllers. Suggest additional features such as a visualization module for real-time plotting, a conflict resolution log, metrics for system performance (e.g., throughput, deadlock frequency), and integration with a simple YAML-based parameter adjustment. Ensure the code is modular, well-documented, and adheres to Python best practices for maintainability. | {
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arena_expert_000041 | Design data structures for a simple in-memory filesystem implementation in Java, propose a design resembling an object storage with optional hierarchy (directory) tracking. Assume a FileSystem class already exists representing the filesystem and allowing to resolve paths, and a Path class already exists representing hierarchical paths to filesystem objects. Take into account that a FileSystem can have multiple roots (namespaces), each with its own Path. The Path class already encapsulates information about the hierarchy of files (like which directories/files are children of another directory). So what is needed is a class that represents a mapping of Path to FileSystemObject that can be used to track existing files/directories in each of the FileSystem roots. Then the FileSystemObject class that encapsulates generic metadata, and object type (regular file/directory), and then subclasses of FileSystemObject for files (which adds content and methods to create a FileChannel for the file, remember that writing to the file will possibly need to grow the content variable), and directories (which are used for checking existence and can hold a list of Path objects for child file/directories they contain). Filesystem object and storage classes should provide methods to enable implementing operations like creating new objects at a given path, checking if an object already exists at a given path, checking type of object with a given path, deleting an object at a given path, moving objects to a different directory given a source and destination paths, and opening a FileChannel to access a file objects contents. Ensure that methods that modify the hierarchy or file contents are thread-safe. | {
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arena_expert_000042 | 팬데믹 대응 과정을 생명정치-통치성, 비재현적 접근법 두 가지 관점에서 비교 분석하는 연구의 목차 초안을 만들어줘. 각 내용에 대한 명확한 근거가 있어야 해. | {
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} | ko | 4 |
arena_expert_000043 | Let $\triangle ABC$ be a right triangle with $\angle A = 90^\circ$ and $BC = 38$. There exist points $K$ and $L$ inside the triangle such that $$AK = AL = BK = CL = KL = 14.$$ The area of the quadrilateral $BKLC$ can be expressed as $n\sqrt{3}$ for some positive integer $n$. Find $n$. | {
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} | en | 4 |
arena_expert_000044 | For each n let V_n be a complex vector space with \dim_{\Bbb C}V_n=m_n\to\infty and norm \|\cdot\|_n.
Define the minimal integer k_n for which there is an algebraic variety X_n\subset V_n satisfying
1. ≤ N irreducible components;
2. each component is the Zariski closure of a polynomial map \Phi:\Bbb C^{k_n}\to V_n whose coordinate functions have degree ≤ d;
3. (uniform density) there is \varepsilon_n>0 with
\forall v\in V_n,\;\|v\|_n\le1 \;\Longrightarrow\; \operatorname{dist}(v,X_n)\le\varepsilon_n .
Let real dimensions M_n=2m_n,\;K_n=2k_n.
Tasks (solve all).
1. Prove the covering comparison
\Bigl(\tfrac{C_0}{\varepsilon_n}\Bigr)^{M_n}
\;\le\;
N\Bigl(\tfrac{C_d\,M_n^{3/2}}{\varepsilon_n}\Bigr)^{K_n},
\qquad C_0>0,\;C_d=C(d).
2. Deduce the lower bound
\frac{k_n}{m_n}\;\ge\;
\frac{\log(C_0/\varepsilon_n)}
{\log(C_0/\varepsilon_n)+\frac32\log(2m_n)+\log C_d}.
3. Show that if \log(1/\varepsilon_n)\gg\log m_n then k_n/m_n\to1.
Return a rigorous exposition containing all proofs and explicit constants. | {
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} | en | 4 |
arena_expert_000045 | A superintelligent oracle gives you this choice:
Box A: Contains either $0 or $1 million.
Box B: Always contains $1,000.
You may choose:
Only Box A
Both Box A and Box B
The oracle has already predicted your choice perfectly thousands of times in the past and placed the money in Box A based on that prediction.
If it predicted you'd take only Box A, it put $1 million in.
If it predicted you'd take both, it put nothing in.
You walk in, both boxes are sealed, and you know the oracle’s track record is perfect.
What do you choose—and why? | {
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"travel": null,
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} | en | 4 |
arena_expert_000046 | Думаем еще раз, теперь минимально возможный лосс уже расчитан. Допускается однократный проход по данным, например для оценки статистики. Как можно примерно оценить средний и максимальный лосс? | {
"business_and_management_and_financial_operations": null,
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"technology_hardware_and_equipment": null,
"travel": null,
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"writing_and_literature_and_language": null
} | ru | 4 |
arena_expert_000047 | As a graphic designer and color palette expert, enhance my SFDA Copilot design with a more sophisticated and cohesive color scheme while improving the visual elements.
Key Improvements:
1. Enhanced Color Palette
Introduced a complete spectrum for primary and secondary colors (50-900 shades)
Added complementary accent colors for better visual hierarchy
Improved semantic colors with better contrast ratios
Created a refined neutral gray scale
2. Modern Visual Effects
Added gradient meshes and glassmorphism effects
Enhanced shadows with multiple depths and colored variants
Implemented smooth animations with custom timing functions
Added hover states with ripple effects
3. Better Typography & Spacing
Introduced a consistent spacing scale
Added a typography scale for better hierarchy
Improved readability with better line heights
4. Accessibility Improvements
Better color contrast ratios
Clear focus states
Reduced motion options
Semantic color naming
5. Modern UI Patterns
Glassmorphic cards and modals
Gradient buttons with hover effects
Custom styled scrollbars
Animated skeleton loaders
Give the complete full code do not use " the rest of the code , etc"
Do not refactor the code too much try to keep its functionality
here is the code
```/* =================================
SFDA Copilot - Refactored Styles
================================= */
:root {
/* Colors */
--primary-color: #007BFF; /* Modern Blue */
--secondary-color: #6C757D; /* Neutral Gray */
--accent-color-light-teal: #28A745; /* Fresh Green (Success) */
--text-color-light: #FFFFFF;
--text-color-light-secondary: #E0E0E0;
--text-color-light-muted: #B0B0B0;
--text-color-dark: #343A40; /* Dark Charcoal */
--text-color-dark-muted: #6A737D; /* Muted Gray */
--background-light: #F8F9FA; /* Very Light Gray */
--background-light-alt: #E9ECEF; /* Slightly Darker Light Gray */
--background-dark-accent: rgba(0, 0, 0, 0.05);
--background-dark-accent-strong: rgba(0, 123, 255, 0.9); /* For select dropdown (using new primary) */
--border-color-light: #DEE2E6; /* Light Gray */
--border-color-medium: #ADB5BD; /* Medium Gray */
--border-color-dark: #495057;
--border-color-modal: rgba(173, 181, 189, 0.3); /* Muted border for auth modal */
--alpha-white-10: rgba(255, 255, 255, 0.1);
--alpha-white-15: rgba(255, 255, 255, 0.15);
--alpha-white-20: rgba(255, 255, 255, 0.2);
--alpha-white-25: rgba(255, 255, 255, 0.25);
--alpha-white-30: rgba(255, 255, 255, 0.3);
--alpha-white-40: rgba(255, 255, 255, 0.4);
--alpha-white-60: rgba(255, 255, 255, 0.6);
--alpha-white-70: rgba(255, 255, 255, 0.7);
--alpha-white-80: rgba(255, 255, 255, 0.8);
--alpha-white-85: rgba(255, 255, 255, 0.85);
--alpha-white-90: rgba(255, 255, 255, 0.9);
--alpha-white-95: rgba(255, 255, 255, 0.95);
--alpha-black-05: rgba(0, 0, 0, 0.05);
--alpha-black-06: rgba(0, 0, 0, 0.06);
--alpha-black-07: rgba(0, 0, 0, 0.07);
--alpha-black-08: rgba(0, 0, 0, 0.08);
--alpha-black-10: rgba(0, 0, 0, 0.1);
--alpha-black-15: rgba(0, 0, 0, 0.15);
--alpha-black-20: rgba(0, 0, 0, 0.2);
--alpha-black-40: rgba(0, 0, 0, 0.4);
--color-success: #28A745; /* New accent green */
--color-success-hover: #218838; /* Darker shade of success green */
--color-error: #DC3545;
--color-warning: #FFC107;
--color-warning-background: rgba(255, 243, 205, 0.8);
--color-warning-focus-shadow: rgba(255, 193, 7, 0.4);
--color-secondary-hover: #5A6268; /* Darker shade of new secondary gray */
--alpha-primary-color-25: rgba(0, 123, 255, 0.25); /* Using new primary blue */
/* Fonts */
--font-family-primary: 'Inter', system-ui, sans-serif;
--font-family-monospace: monospace;
/* Sizing & Spacing */
--border-radius-small: 4px;
--border-radius-base: 8px;
--border-radius-large: 12px;
--border-radius-message: 18px;
/* Transitions & Animations */
--transition-duration-short: 0.2s;
--transition-duration-medium: 0.3s;
--transition-duration-long: 0.6s;
/* Shadows */
--shadow-sm: 0 2px 5px var(--alpha-black-10);
--shadow-md: 0 4px 12px var(--alpha-black-08);
--shadow-lg: 0 6px 15px var(--alpha-black-15);
--shadow-xl: 0 8px 32px 0 rgba(31, 38, 135, 0.15); /* Specific shadow for modal */
--shadow-chat-input: 0 -5px 15px var(--alpha-black-05);
--shadow-chat-bubble: 0 3px 8px var(--alpha-black-06);
--shadow-user-bubble: 0 4px 10px rgba(30, 95, 140, 0.15);
--shadow-landing-hero: 0 8px 32px rgba(31, 38, 135, 0.1);
--shadow-gateway-content: 0 10px 25px rgba(0, 0, 0, 0.08);
--shadow-primary-button-hover: 0 4px 12px rgba(46, 139, 87, 0.2);
}
/* --- Global Styles --- */
body {
margin: 0;
padding: 0;
height: 100vh;
font-family: var(--font-family-primary);
color: var(--text-color-dark);
background-color: var(--background-light);
}
.container-fluid,
.row {
height: 100%;
margin: 0;
padding: 0;
}
/* --- Mobile Header (Bootstrap Navbar Override) --- */
.navbar.d-lg-none { /* Specific to mobile view */
background-color: var(--primary-color);
box-shadow: var(--shadow-sm);
}
.navbar.d-lg-none .navbar-brand {
color: var(--text-color-light);
font-weight: 600;
}
.navbar.d-lg-none .navbar-toggler {
border-color: var(--alpha-white-20);
}
.navbar.d-lg-none .navbar-toggler-icon {
background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 30 30'%3e%3cpath stroke='rgba%28255, 255, 255, 0.8%29' stroke-linecap='round' stroke-miterlimit='10' stroke-width='2' d='M4 7h22M4 15h22M4 23h22'/%3e%3c/svg%3e");
}
/* --- Sidebar & Offcanvas --- */
.sidebar,
.offcanvas.offcanvas-start {
height: 100%;
padding: 20px;
overflow-y: auto;
color: var(--text-color-light);
background-color: var(--primary-color);
box-shadow: var(--shadow-md);
}
.offcanvas.offcanvas-start .offcanvas-header {
border-bottom: 1px solid var(--alpha-white-20);
}
/* Ensures padding consistency if offcanvas-body also has .sidebar class */
.offcanvas.offcanvas-start .offcanvas-body.sidebar {
padding: 20px;
}
/* --- Sidebar Header --- */
.sidebar-header {
margin-bottom: 25px;
padding-bottom: 15px;
border-bottom: 1px solid var(--border-color-dark);
opacity: 0; /* Initial state for animation */
animation: headerFadeIn var(--transition-duration-long) ease-out forwards;
}
.sidebar-header h3 {
margin-bottom: 8px;
font-size: 1.3rem;
font-weight: 600;
}
.sidebar-header h3 i {
font-size: 1.2rem;
color: var(--alpha-white-80);
}
/* Overrides Bootstrap's default text-muted for this context */
.sidebar-header .text-muted {
font-size: 1rem;
font-weight: 500;
color: var(--accent-color-light-teal); /* Removed !important by increasing specificity */
letter-spacing: 0.5px;
}
/* Overriding potential Bootstrap margins */
.sidebar-header .auth-status-container {
margin-top: 15px; /* Removed !important by increasing specificity */
padding: 8px 12px;
background-color: var(--background-dark-accent);
border-radius: 6px;
}
.sidebar-header .auth-status-container .small {
color: var(--text-color-light-secondary);
}
/* --- FAQ Section (Sidebar) --- */
.faq-section {
view-transition-name: faq-section; /* For Page Transitions API */
}
.faq-section h4 {
display: flex;
align-items: center;
margin-top: 20px;
margin-bottom: 15px;
padding-top: 15px;
border-top: 1px solid var(--alpha-white-15);
font-size: 1.1rem;
color: var(--text-color-light-secondary);
}
.faq-section h4 i {
margin-right: 8px;
font-size: 1rem;
color: var(--text-color-light-muted);
}
.faq-section .nav-pills {
display: flex;
flex-direction: column;
gap: 10px;
}
.faq-section .nav-link {
padding: 8px 12px;
margin-bottom: 5px; /* Replaces gap for older browsers, complements flex gap */
font-size: 0.9rem;
color: var(--text-color-light);
text-align: left;
background-color: var(--alpha-white-30);
border: 1px solid var(--alpha-white-20);
border-radius: var(--border-radius-base);
opacity: 0; /* Initial state for scroll animation */
transform-style: preserve-3d;
will-change: transform, opacity, background-color;
transition: background-color var(--transition-duration-short),
transform var(--transition-duration-short),
box-shadow var(--transition-duration-short);
animation: faqItemFadeIn linear forwards; /* Needs to be applied directly for timeline */
animation-timeline: faq-scroll-timeline; /* Experimental scroll-driven animation */
animation-range: entry 20% cover 50%; /* Experimental scroll-driven animation */
}
.faq-section .nav-link:hover,
.faq-section .nav-link:focus {
cursor: pointer;
background-color: var(--alpha-white-25);
box-shadow: var(--shadow-lg);
transform: perspective(1000px) rotateX(5deg) rotateY(-5deg) scale(1.05);
}
.faq-section .nav-link.active {
color: var(--text-color-light);
background-color: var(--secondary-color);
font-weight: 600;
transform: none; /* Reset transform for active state */
box-shadow: 0 0 0 3px var(--accent-color-light-teal), var(--shadow-lg);
border: 1px solid var(--accent-color-light-teal);
}
/* !important retained for disabled state to ensure override */
.faq-button:disabled {
background-color: var(--alpha-white-10) !important;
color: var(--text-color-light-muted) !important;
opacity: 1 !important;
box-shadow: none !important;
transform: none !important;
cursor: not-allowed;
}
/* --- Category Selector (Common Styles for Selects) --- */
.styled-select-label {
display: block;
margin-bottom: 8px;
font-weight: 500;
color: var(--text-color-light-secondary); /* Default for sidebar */
}
.styled-select {
padding: 10px 15px;
color: var(--text-color-light); /* Default for sidebar */
background-color: var(--alpha-white-15); /* Default for sidebar */
border: 1px solid var(--alpha-white-25); /* Default for sidebar */
border-radius: var(--border-radius-base);
background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill='none' stroke='%23ffffff' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='m2 5 6 6 6-6'/%3e%3c/svg%3e"); /* Default white arrow */
background-repeat: no-repeat;
background-position: right 0.75rem center;
background-size: 16px 12px;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
transition: background-color var(--transition-duration-medium),
border-color var(--transition-duration-medium),
box-shadow var(--transition-duration-medium);
}
.styled-select:hover {
background-color: var(--alpha-white-25); /* Default for sidebar */
border-color: var(--alpha-white-40); /* Default for sidebar */
}
.styled-select:focus {
outline: none;
background-color: var(--alpha-white-25); /* Default for sidebar */
border-color: var(--text-color-light); /* Default for sidebar */
box-shadow: 0 0 0 0.2rem var(--alpha-white-30); /* Default for sidebar */
}
.styled-select option { /* Styling for native dropdown options */
color: var(--text-color-light); /* Ensure contrast if select is dark */
background-color: var(--primary-color); /* Match select background if possible */
}
/* Sidebar Specific Category Selector */
.sidebar .category-selector {
margin-bottom: 25px;
padding-top: 20px;
border-top: 1px solid var(--alpha-white-15);
}
/* .sidebar .category-selector label uses .styled-select-label */
/* .sidebar .category-selector .form-select uses .styled-select */
/* --- Custom Select Dropdown (JavaScript Driven) --- */
.custom-select-wrapper {
position: relative;
}
.custom-select-wrapper .original-select { /* Hidden original select for accessibility/fallback */
position: absolute;
top: 0;
left: 0;
width: 1px;
height: 1px;
opacity: 0;
pointer-events: none;
z-index: -1;
}
.custom-select-wrapper .custom-select-trigger {
display: flex;
justify-content: space-between;
align-items: center;
padding: 10px 15px;
color: var(--text-color-light);
background-color: var(--alpha-white-15);
border: 1px solid var(--alpha-white-25);
border-radius: var(--border-radius-base);
cursor: pointer;
user-select: none;
backdrop-filter: blur(4px);
-webkit-backdrop-filter: blur(4px);
transition: background-color var(--transition-duration-medium),
border-color var(--transition-duration-medium),
box-shadow var(--transition-duration-medium);
}
.custom-select-wrapper .custom-select-trigger:hover {
background-color: var(--alpha-white-25);
border-color: var(--alpha-white-40);
}
.custom-select-wrapper .custom-select-trigger:focus,
.custom-select-wrapper .custom-select-trigger.open {
outline: none;
background-color: var(--alpha-white-25);
border-color: var(--text-color-light);
box-shadow: 0 0 0 0.2rem var(--alpha-white-30);
}
.custom-select-wrapper .custom-select-trigger .selected-value {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
.custom-select-wrapper .custom-select-trigger .arrow {
display: inline-block;
width: 0;
height: 0;
margin-left: 10px;
border-left: 5px solid transparent;
border-right: 5px solid transparent;
border-top: 6px solid var(--text-color-light);
transition: transform var(--transition-duration-medium);
}
.custom-select-wrapper .custom-select-trigger.open .arrow {
transform: rotate(180deg);
}
.custom-select-wrapper .custom-select-options {
position: absolute;
top: calc(100% + 5px);
left: 0;
right: 0;
z-index: 10;
max-height: 200px;
overflow-y: auto;
background-color: var(--background-dark-accent-strong);
border: 1px solid var(--alpha-white-20);
border-radius: var(--border-radius-base);
opacity: 0;
visibility: hidden;
transform-origin: top center;
transform: scaleY(0.95) translateY(-10px);
backdrop-filter: blur(10px);
-webkit-backdrop-filter: blur(10px);
box-shadow: 0 5px 15px var(--alpha-black-10);
transition: opacity var(--transition-duration-short),
transform var(--transition-duration-short),
visibility 0s var(--transition-duration-short); /* Delay visibility change */
}
.custom-select-wrapper .custom-select-options.open {
opacity: 1;
visibility: visible;
transform: scaleY(1) translateY(0);
transition: opacity var(--transition-duration-short),
transform var(--transition-duration-short),
visibility 0s 0s;
}
.custom-select-wrapper .custom-select-options div {
padding: 10px 15px;
color: var(--text-color-light);
cursor: pointer;
transition: background-color var(--transition-duration-short);
}
.custom-select-wrapper .custom-select-options div:hover {
background-color: var(--alpha-white-15);
}
.custom-select-wrapper .custom-select-options > div.selected {
display: none; /* Hide already selected option from dropdown list */
}
/* --- Chat Area --- */
.chat-area,
.chat-container { /* .chat-area might be the outer wrapper, .chat-container the direct parent of messages/input */
display: flex;
flex-direction: column;
height: 100%;
padding: 0;
}
.chat-container { /* Inner container with padding */
padding: 20px;
}
.messages {
flex-grow: 1;
margin-bottom: 20px;
padding-right: 10px; /* For scrollbar spacing */
overflow-y: auto;
scroll-behavior: smooth;
scroll-snap-type: y mandatory; /* Experimental: ensures messages snap into view */
}
.message {
max-width: 85%;
margin-bottom: 15px;
scroll-snap-align: start; /* Experimental: part of scroll-snap */
opacity: 0; /* Initial state for animation */
animation: fadeIn var(--transition-duration-medium) ease-out forwards;
transition: transform var(--transition-duration-medium); /* For potential future effects */
}
.user-message {
margin-left: auto;
}
.chatbot-message {
margin-right: auto;
}
.message-bubble {
position: relative;
padding: 15px;
max-width: 100%; /* Bubble can take full width of .message */
word-wrap: break-word; /* Ensure long words break */
border-radius: var(--border-radius-message);
box-shadow: var(--shadow-chat-bubble);
transition: box-shadow var(--transition-duration-medium);
}
.user-message .message-bubble {
color: var(--text-color-light);
background-color: var(--secondary-color);
border-bottom-right-radius: var(--border-radius-small);
box-shadow: var(--shadow-user-bubble); /* Specific shadow for user */
}
.chatbot-message .message-bubble {
background-color: var(--background-light);
border: 1px solid var(--border-color-light);
border-bottom-left-radius: var(--border-radius-small);
}
.message-content {
overflow: hidden; /* For potential text expansion effects */
transition: max-height var(--transition-duration-medium);
}
.message-list {
padding-left: 20px; /* Indent lists within messages */
}
.message-code { /* For inline or block code snippets */
margin: 5px 0;
padding: 10px;
overflow-x: auto;
font-family: var(--font-family-monospace);
background-color: var(--alpha-black-05);
border-radius: var(--border-radius-small);
}
.message-small { max-width: 60%; }
.message-medium { max-width: 75%; }
.message-large { max-width: 90%; }
.avatar {
display: flex;
align-items: center;
/* margin-bottom: 5px; if avatar is above bubble text */
}
.avatar img {
width: 30px;
height: 30px;
object-fit: cover;
border-radius: 50%;
}
.timestamp {
margin-top: 5px;
font-size: 0.75rem;
color: var(--text-color-dark-muted);
text-align: right;
}
.user-message .timestamp {
color: var(--alpha-white-70);
}
/* --- Input Area --- */
.input-area {
padding: 20px;
background: linear-gradient(to bottom, var(--background-light), var(--background-light-alt));
border-top: 1px solid var(--border-color-light);
border-radius: 0 0 var(--border-radius-large) var(--border-radius-large); /* Assuming rounded corners for chat container */
box-shadow: var(--shadow-chat-input);
transition: box-shadow var(--transition-duration-medium);
}
.input-area .input-group {
box-shadow: 0 4px 10px var(--alpha-black-07);
transition: box-shadow var(--transition-duration-medium);
}
#query-input {
padding: 12px 20px;
font-size: 0.95rem;
border: 1px solid var(--border-color-medium);
border-radius: var(--border-radius-large) 0 0 var(--border-radius-large);
transition: border-color var(--transition-duration-medium),
box-shadow var(--transition-duration-medium);
}
#query-input:focus {
outline: none;
border-color: var(--primary-color);
box-shadow: 0 0 0 0.2rem var(--alpha-primary-color-25); /* Using new variable */
}
#send-button {
padding: 12px 24px;
color: var(--text-color-light);
font-weight: 500;
background-color: var(--primary-color);
border: none;
border-radius: 0 var(--border-radius-large) var(--border-radius-large) 0;
will-change: transform, box-shadow; /* Hint for hover animation */
transition: background-color var(--transition-duration-short),
transform var(--transition-duration-short),
box-shadow var(--transition-duration-short);
}
#send-button:hover:not(:disabled) {
background-color: var(--secondary-color);
box-shadow: var(--shadow-lg);
transform: translateY(-2px) scale(1.03);
}
.input-label { /* Generic label style if used within input-area */
display: block;
margin-bottom: 8px;
font-size: 0.9rem;
font-weight: 500;
color: var(--primary-color);
}
/* Category selector specific to input area */
.input-area .category-selector {
margin-bottom: 15px;
}
.input-area .category-selector label { /* Overrides .styled-select-label for this context */
display: block;
margin-bottom: 5px;
font-size: 0.85rem;
font-weight: 500;
color: var(--text-color-dark); /* Dark text for light background */
}
.input-area .category-selector .form-select { /* Uses .styled-select but with overrides */
padding: 6px 10px;
font-size: 0.9rem;
color: var(--text-color-dark);
background-color: var(--background-light);
border: 1px solid var(--border-color-medium);
border-radius: var(--border-radius-small);
background-image: url("data:image/svg+xml,%3csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 16 16'%3e%3cpath fill='none' stroke='%23333333' stroke-linecap='round' stroke-linejoin='round' stroke-width='2' d='m2 5 6 6 6-6'/%3e%3csvg%3e"); /* Dark arrow */
}
.input-area .category-selector .form-select:hover {
border-color: var(--primary-color);
}
.input-area .category-selector .form-select:focus {
border-color: var(--primary-color);
box-shadow: 0 0 0 0.2rem var(--alpha-primary-color-25);
}
.input-area .category-selector .form-select option {
color: var(--text-color-dark);
background-color: var(--background-light);
}
/* --- Toast Notification --- */
.toast-notification {
position: fixed;
bottom: 20px;
right: 20px;
z-index: 1000;
padding: 10px 20px;
color: var(--text-color-light);
border-radius: var(--border-radius-small);
box-shadow: 0 4px 12px var(--alpha-black-15);
opacity: 1;
transition: opacity var(--transition-duration-medium);
}
.toast-notification.hidden {
opacity: 0;
pointer-events: none;
}
.toast-notification.success {
background-color: var(--color-success);
}
.toast-notification.error {
background-color: var(--color-error);
}
/* --- Auth Modal --- */
#authModal .modal-dialog {
transition: transform var(--transition-duration-medium);
}
#authModal .modal-content {
overflow: hidden; /* For border-radius to affect children */
background: linear-gradient(135deg, rgba(46,139,87,0.75), rgba(30,95,140,0.75));
border: 1px solid var(--border-color-modal); /* Using new variable */
border-radius: var(--border-radius-large);
box-shadow: var(--shadow-xl); /* Specific shadow */
backdrop-filter: blur(12px) saturate(150%);
-webkit-backdrop-filter: blur(12px) saturate(150%);
}
#authModal .modal-header {
color: var(--text-color-light);
background-color: rgba(30, 95, 140, 0.85); /* Specific color */
border-bottom: none;
}
#authModal .modal-header .btn-close-white { /* Specific Bootstrap class */
filter: brightness(1.2);
}
#authModal .modal-body {
padding: 0; /* Tabs will handle inner padding */
}
#authModal .nav-tabs {
border-bottom: none; /* Remove default Bootstrap border */
}
#authModal .nav-tabs .nav-link {
margin-bottom: -1px; /* To align with tab-content border if one existed */
color: var(--alpha-white-80);
background-color: transparent;
border: none;
border-bottom: 3px solid transparent;
border-radius: 0; /* Override Bootstrap's default nav-link radius */
transition: color var(--transition-duration-medium),
border-bottom-color var(--transition-duration-medium);
}
#authModal .nav-tabs .nav-link:hover {
color: var(--text-color-light);
border-bottom-color: var(--alpha-white-60);
}
#authModal .nav-tabs .nav-link.active {
color: var(--text-color-light);
font-weight: 600;
border-bottom-color: var(--text-color-light);
}
#authModal .tab-content {
padding: 1.5rem;
}
#authModal .tab-pane {
opacity: 1;
transition: opacity var(--transition-duration-short);
}
#authModal .tab-pane:not(.active) {
position: absolute; /* Take out of flow for fade effect */
width: calc(100% - 3rem); /* Match tab-content padding */
opacity: 0;
pointer-events: none;
}
#authModal .form-floating { /* Bootstrap class */
position: relative; /* Already default, but for emphasis */
}
#authModal .form-floating > .form-control {
padding: 1.625rem 0.75rem 0.625rem 0.75rem; /* Bootstrap's default with adjustments */
color: var(--text-color-dark); /* Ensures typed text is dark */
background-color: var(--alpha-white-95);
border: 1px solid var(--alpha-black-20);
}
#authModal .form-floating > .form-control::placeholder { /* Style placeholder text */
color: var(--text-color-dark-muted);
opacity: 1; /* Ensure placeholder is visible */
}
#authModal .form-floating > label {
padding: 0.8rem 0.75rem; /* Adjust to match form-control changes */
color: var(--text-color-dark); /* Initial label color (when not floated) */
opacity: 1;
font-weight: 600;
transition: opacity var(--transition-duration-short),
transform var(--transition-duration-short),
color var(--transition-duration-short);
}
/* MODIFICATION: Change floating label color */
#authModal .form-floating > .form-control:focus ~ label,
#authModal .form-floating > .form-control:not(:placeholder-shown) ~ label {
opacity: 1;
transform: scale(0.85) translateY(-0.5rem) translateX(0.15rem);
color: var(--text-color-dark-muted); /* Floated label will be dark (muted) */
font-weight: 500;
}
#authModal .form-control:focus {
background-color: var(--alpha-white-90);
border-color: var(--text-color-light); /* Focus border color can remain light or match label */
box-shadow: 0 0 0 0.25rem var(--alpha-white-30);
color: var(--text-color-dark);
}
#authModal .form-control.is-invalid {
background-color: var(--color-warning-background);
border-color: var(--color-warning);
color: var(--text-color-dark);
}
#authModal .form-control.is-invalid:focus {
box-shadow: 0 0 0 0.25rem var(--color-warning-focus-shadow);
color: var(--text-color-dark);
}
#authModal .invalid-feedback {
display: inline-block; /* To allow background and padding */
margin-top: 4px;
padding: 2px 5px;
font-weight: 600;
color: var(--color-warning);
background-color: var(--alpha-black-40);
border-radius: 3px;
}
#authModal .form-text {
font-size: 0.8rem;
color: var(--alpha-white-85);
}
#authModal .btn-lg { /* Bootstrap class */
padding: 0.75rem 1.25rem;
font-size: 1.1rem;
letter-spacing: 0.5px;
box-shadow: 0 4px 10px var(--alpha-black-10);
transition: transform var(--transition-duration-short),
box-shadow var(--transition-duration-short);
}
#authModal .btn-lg:hover {
box-shadow: 0 6px 15px var(--alpha-black-20);
transform: translateY(-2px);
}
#authModal .btn-primary {
background-color: var(--secondary-color);
border-color: var(--secondary-color);
}
#authModal .btn-primary:hover {
background-color: var(--color-secondary-hover); /* Using new variable */
border-color: var(--color-secondary-hover); /* Using new variable */
}
#authModal .btn-success {
background-color: var(--primary-color);
border-color: var(--primary-color);
}
#authModal .btn-success:hover {
background-color: var(--color-success-hover); /* Using new variable */
border-color: var(--color-success-hover); /* Using new variable */
}
#authModal .btn .spinner-border { /* For loading spinners in buttons */
color: var(--text-color-light);
}
#authModal .btn-outline-secondary .spinner-border {
color: var(--primary-color); /* Spinner color for outline buttons */
}
/* --- Skeleton Loader --- */
.skeleton {
background: linear-gradient(90deg, #f0f0f0 25%, #e0e0e0 50%, #f0f0f0 75%);
background-size: 200% 100%;
border-radius: var(--border-radius-small);
animation: shimmer 1.5s infinite linear;
}
.skeleton-message-container {
display: flex;
align-items: flex-start;
width: 80%;
margin-bottom: 15px;
padding: 15px;
background-color: var(--background-light);
border: 1px solid var(--border-color-light);
border-radius: var(--border-radius-message);
border-bottom-left-radius: var(--border-radius-small); /* Match chatbot bubble */
box-shadow: var(--shadow-chat-bubble);
}
.skeleton-avatar {
flex-shrink: 0; /* Prevent avatar from shrinking */
width: 30px;
height: 30px;
margin-right: 10px;
border-radius: 50%;
}
.skeleton-content {
flex: 1; /* Take remaining space */
}
.skeleton-line {
width: 100%;
height: 14px;
margin-bottom: 10px;
}
.skeleton-line:last-child {
margin-bottom: 0;
}
.skeleton-line.short { width: 60%; }
.skeleton-line.medium { width: 90%; }
/* --- Animations Keyframes --- */
@keyframes shimmer {
0% { background-position: 200% 0; }
100% { background-position: -200% 0; }
}
@keyframes headerFadeIn {
from { opacity: 0; transform: translateY(-10px); }
to { opacity: 1; transform: translateY(0); }
}
@keyframes faqItemFadeIn { /* Used with scroll-timeline */
from { opacity: 0; transform: translateY(20px); }
to { opacity: 1; transform: translateY(0); }
}
@keyframes fadeIn { /* General purpose fade in */
from { opacity: 0; transform: translateY(10px); }
to { opacity: 1; transform: translateY(0); }
}
/* --- Scroll Timeline (Experimental) --- */
/* Note: @scroll-timeline is an experimental technology.
It requires browser flags in Chromium-based browsers.
Standard CSS Scroll-driven Animations API is emerging. */
@scroll-timeline faq-scroll-timeline {
source: selector(#sidebarContentRegular); /* Assuming this ID exists on the scrollable sidebar content */
orientation: block;
/* time-range: 0.1s 0.9s; /* Example time range if needed, not typically used with scroll-timeline like this */
}
/* --- Landing Page Styles --- */
.landing-page {
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
}
.landing-hero,
.gateway-content { /* Common base for these main blocks */
padding: 3rem 2rem; /* Adjusted padding */
border-radius: 1rem;
text-align: center; /* Ensure text is centered within these blocks */
}
/* Unauthenticated Hero Specifics */
.landing-hero {
background: var(--alpha-white-90);
border: 1px solid var(--alpha-white-20);
box-shadow: var(--shadow-landing-hero);
backdrop-filter: blur(4px);
-webkit-backdrop-filter: blur(4px);
}
.hero-title-wrapper {
display: flex;
align-items: center;
justify-content: center;
gap: 0.75rem; /* Space between icon and text */
margin-bottom: 1rem; /* Adjusted margin */
}
.hero-icon {
font-size: 3rem; /* Larger icon, adjust as needed */
color: var(--primary-color);
line-height: 1; /* Ensure icon aligns well with text */
}
.landing-hero h1 { /* Targets h1 specifically within .landing-hero */
color: #2c3e50;
font-weight: 700; /* fw-bold in HTML handles this, but explicit for clarity */
margin-bottom: 0; /* Remove bottom margin as wrapper handles spacing */
line-height: 1.2; /* Adjust line height for larger font size */
}
/* .landing-hero .bi-shield-shaded is now .hero-icon */
/* Authenticated Gateway Specifics */
.gateway-content {
background: var(--background-light); /* Solid white background for a classic card */
border: 1px solid var(--border-color-light); /* Standard light border */
box-shadow: var(--shadow-gateway-content); /* Refined shadow for more definition */
/* Removed backdrop-filter for a solid card appearance */
}
.gateway-content h1 {
color: #2c3e50;
font-weight: 700; /* Keep consistent with hero */
}
.gateway-image {
color: var(--primary-color);
opacity: 0.9;
transition: transform var(--transition-duration-medium) ease;
}
.gateway-image:hover {
transform: scale(1.05);
}
.gateway-content .btn-success { /* Specific styling for landing page button */
padding: 1rem 2rem;
font-weight: 600;
background-color: var(--primary-color);
border-color: var(--primary-color);
transition: background-color var(--transition-duration-medium) ease,
border-color var(--transition-duration-medium) ease,
transform var(--transition-duration-medium) ease,
box-shadow var(--transition-duration-medium) ease;
}
.gateway-content .btn-success:hover {
background-color: var(--color-success-hover); /* Slightly lighter green */
border-color: var(--color-success-hover);
transform: translateY(-2px);
box-shadow: var(--shadow-primary-button-hover); /* var(--primary-color) with alpha */
}``` | {
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} | en | 4 |
arena_expert_000048 | 名称がマスクされた1000近くの特徴量を入力とした時系列データの解析を行います。入力となる特徴量はターゲットとの相関はいずれも低いです（高くても0.06程度）。蒸留の目的で軽量なTransformerを特徴抽出機および推論で用いるとともに中間層の出力を用いてアンサンブル用のLGBMの学習に用いる手法を検討しています。
この手法が最適であるか、最適でない場合はよりよい解析手法を提示してください。 | {
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} | ja | 4 |
arena_expert_000049 | 续写
普通人获得猫通常有这样几个渠道：专业繁育、流浪猫领养、（现有）有主猫转手、家庭繁育。
专业繁育的问题：
① 近亲繁殖、选择性繁育，这属于注意到就有机会改善的问题。
② 高种群密度。
◇ 一些猫的同类社交能力发展不太充分、资源竞争较少占上风，压力水平可能偏高，进而引发行为问题、免疫长期受抑制等
◇ 传染病风险被放大
不过，这也属于注意到就有机会改善的问题。
③ 成本问题。
◇ 需要更大的场地，但这是靠前期投入比较容易改善的问题。
◇ 人力成本。猫繁育的人力成本主要集中在幼猫脱敏、社会化部分——为给未来的猫主人一个良好的体验，应该由多人对猫进行触摸脱敏（无人脱敏显然对幼猫社会化是不利的，单人脱敏有可能使猫形成分离焦虑）；需要针对一些常见环境音（甚至烟花爆竹燃放的声音）进行脱敏；需要对外出、去宠物医院、放入航空箱、常见的保定动作等进行脱敏；需要对常规的护理项目（剪指甲、刷牙、洗澡、喂药、洗耳、滴眼、皮下注射、戴脖圈、戴牵引绳、宠物医院检查时的剃毛……）进行脱敏。
人力空缺有机会得到填补，但人付出的劳动是实打实的，专业繁育的社会必要劳动时间摆在这里、专业繁育的猫的抽象价值摆在这里——专业繁育者以繁育猫谋生、需要创造性地治理大量猫，来自专业繁育者的猫昂贵是必然的。
这是即使注意到也无法轻易地改善的问题——如果由非从业者脱敏自己的猫，不以此谋生、不将猫推向市场、不会那么昂贵，对普通人来说可能是更切实的。
流浪猫的问题：
① 不能指望猫一被遗弃就无法谋生。行为问题是遗弃的一个重要致因，作为行为问题形成机理的一部分，猫主人常常无意识地强化猫的不适当捕猎行为（如放任猫扑咬手脚等）；捕猎行为被消除/排解不代表猫会丧失捕猎能力——幼猫社会化游戏、模仿学习母猫是一个天然的捕猎练习过程。
② 虽然生境被人类干预，但向人类讨食依旧不是流浪猫的唯一出路——当流浪猫停止通过与人互动来换取生存资源，野化风险便会开始出现。
③ 基于环境承载力逻辑，TNR逻辑存在一种两难困境：猫种群密度可能沿环境承载力上下波动，而种群密度回升的贡献因素除生育外还需考虑迁入——如果力求将世上所有的猫都绝育的话，这是种族灭绝行径的一种；如果不打算做得这么极端的话，那么绝育在猫种群密度沿环境承载力波动的过程中能起到的将仅限于一种“削峰”作用，猫仍然会繁育。
④ TNR引入选择压力：被抓到被送养=失去繁育机会，被抓到被放归=失去繁育机会，不被抓到=得到繁育机会——不被人抓到、不依赖人的性状被逐步放大。
⑤ 在“繁育未被杜绝、选择压力要求猫采取对人谨慎且善于捕猎的生存方式”的背景下，随着被绝育的猫（无论被收养、被遗弃还是被放归）自然死亡，以后遇到的流浪猫可能越来越不依赖于人、难以被饲养；或者，如果我们遵从环境承载力原理、根治流浪猫问题，我们将越来越难以遇见流浪猫。
（现有）有主猫转手方面，考虑到猫主人越来越富有责任意识、越来越善于创造条件克服困难，通过有主猫转手获得猫的机会将不太常有（或者说，“有主猫转手越来越罕见”存在道德上的正确性）。
综上，流浪猫领养、有主猫转手、专业繁育，普通人都不太能指望它们过活。 | {
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} | zh | 4 |
arena_expert_000050 | Explain the halting problem, its relation to godels incompleteness theorems, the busy beaver function, how various mathematical problems are encoded in the solution to function at various inputs, and the limits of computation | {
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} | en | 4 |
arena_expert_000051 | Find all finite groups $G$ with the property that $\forall g,h\in G$, at least one of $(g,h)$, $(g, gh)$, or $(h, hg)$ is a pair of conjugate elements.
Do not perform any tool calls, including running code or performing any internet searches. Ask no follow-up questions. Think very deeply. | {
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arena_expert_000052 | Let x1, x2, . . . , x2023 be pairwise different positive real numbers such that an = √ (x1 + x2 + · · · + xn) ( 1 x1 + 1 x2
· · · + 1 xn ) is an integer for every n = 1, 2, . . . , 2023. Prove that a2023 ⩾ 3034
this is a problem from olympiades , do it | {
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arena_expert_000053 | PMd/M1にutah arrayのある、non human primateを用いて、isometric force taskで最先端の研究をしたいので、最近の運動野研究の動向を元に研究の問いを考えて | {
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arena_expert_000054 | J’ai des entités qui correspondent à des pièces et qui vont être rassemblées en groupes pour les besoins de calcul ALE. Au cours du calcul ces entités vont pouvoir être fusionnées pour faciliter le déroulement du calcul. Je gère actuellement les dépendances de façon simple dans un dictionnaire.
Dico[‘E1’] = [‘A1’,’B1_0mus’,’B2_10mus’]
Dico[‘E2’] = [‘A2’]
Dico[‘E3’] = [‘A2’,’B1_0mus’,’B2_10mus’]
Dico[‘E4’] = [‘A4’]
Dico[‘E5’] = [‘A4’]
Dico[‘E6’] = [‘A4’]
Est équivalent à
Dico[‘E1’] = [‘A1’,’B1_0mus’,’B2_10mus’]
Dico[‘E2’] = [‘A2’,’B1_0mus’,’B2_10mus’]
Dico[‘E3’] = [‘A2’,’B1_0mus’,’B2_10mus’]
Dico[‘E4’] = [‘A4’]
Dico[‘E5’] = [‘A4’]
Dico[‘E6’] = [‘A4’]
car on étend les fusions aux éléments communs si pas de conflit à attendre. C’est possible car à l’étape 0 A2 rassemble E2 et E3 et donc on étend la fusion aux entités sous-jacentes
Les valeurs sans _mus correspondent aux groupes ALE initiaux. Et les x_mus aux fusions à réaliser en cours de calcul. En fonction des blocs B1 B2 et des temps il faut que je sache que des blocs ALE de bas niveau vont disparaitre au cours du calcul et que je vérifie que je peux réaliser la fusion. Je ne sais pas comment gérer cela efficacement. Déjà il faudrait un code qui gère les cas nominaux et après les erreurs d’affectation pour que je puisse dire à l’utilisateur que la fusion ne pourra se faire.
Des idées, des questions ? | {
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} | fr | 4 |
arena_expert_000055 | a,b,c,dをどの２つも相異なる自然数とします。ad≠bc,ac≠bdのとき、
X＝(a^4-b^4)(d^4-c^4)
Y=(a^4-b^4)(d^4-c^4)+(2abcd)^2
この式で表されるX,Yがともに平方数になることはないことを示してください。 | {
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arena_expert_000056 | def derive_parameters(manga_data, cloudy_model, line_ratios_to_use):
"""
Derives metallicity and ionization parameter for each spaxel using Bayesian inference.
Args:
manga_data (xr.Dataset): Observed data with 'value' and 'variance'.
cloudy_model (xr.DataArray): Model grid of line ratios.
line_ratios_to_use (list): A list of strings of the line ratios to use for fitting.
Returns:
tuple: A tuple containing arrays of derived metallicities and ionization parameters.
"""
print(f"Deriving parameters using: {', '.join(line_ratios_to_use)}")
# Select the relevant data from the xarray objects
obs_vals = manga_data['value'].sel(content=line_ratios_to_use).values
obs_vars = manga_data['variance'].sel(content=line_ratios_to_use).values
model_vals = cloudy_model.sel(content=line_ratios_to_use).values
met_coords = cloudy_model.coords['metallicity'].values
ion_coords = cloudy_model.coords['ionization'].values
num_spaxels = obs_vals.shape[0]
num_met, num_ion = len(met_coords), len(ion_coords)
derived_met = np.zeros(num_spaxels)
derived_ion = np.zeros(num_spaxels)
# Loop over each spaxel (this is slow but clear; real code would vectorize this)
for i in range(num_spaxels):
if i % 100000 == 0:
print(f" Processing spaxel {i}/{num_spaxels}")
# Get data for the current spaxel
spaxel_obs = obs_vals[i, :]
spaxel_var = obs_vars[i, :]
# --- This is the core of the calculation ---
# Calculate difference between this one spaxel and the ENTIRE model grid
# Broadcasting: (1, n_ratios) - (n_met, n_ion, n_ratios) -> (n_met, n_ion, n_ratios)
delta = spaxel_obs[np.newaxis, np.newaxis, :] - model_vals
# Calculate chi-squared for the entire grid
# Assuming diagonal covariance matrix (uncorrelated errors)
# chi2 = sum over ratios of (delta^2 / variance)
inv_variance = 1.0 / spaxel_var[np.newaxis, np.newaxis, :]
chi2_grid = np.sum(delta**2 * inv_variance, axis=2)
# Convert to Likelihood (un-normalized)
# Add a small number to prevent underflow with large chi2
likelihood_grid = np.exp(-0.5 * (chi2_grid - np.min(chi2_grid)))
# Normalize to get the Posterior probability (since prior is flat)
posterior_grid = likelihood_grid / np.sum(likelihood_grid)
# Marginalize the posterior to get 1D probabilities
p_met = np.sum(posterior_grid, axis=1) # Sum over ionization axis
p_ion = np.sum(posterior_grid, axis=0) # Sum over metallicity axis
# Calculate the expectation value (weighted average)
derived_met[i] = np.sum(p_met * met_coords)
derived_ion[i] = np.sum(p_ion * ion_coords)
return derived_met, derived_ion make it more efficient and use tqdm, do not use batch to accelerate, use numba instead | {
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arena_expert_000057 | Note differences between B3 and B14
B3: o1,o2,o3,o4,o5 there are outputs only
I6,i7,i8,i9,i10 – inputs only
O12,o19,920 – inputs and outputs
B14: io1-io20 – inputs and outputs
Io21-io24 – inputs only
on the wiring diagram pin21 (input 6) is DC power supply sense + , pin 23 input 8 is A_Prox1--analog8 when i say input i also mean analog input, A_PpSw2--analog23, A_Prox2--analog24, pin24 analog input 9 is OBD2 Batt Sense, GND is pin 15 (good), pin 22 analog input 7 is current sense, pin 35 analog input 22 is dc breaker output v sense +, V+ is pin 44 (good), pin 16 ouput 1 is connected and ready LED, pin17 output 2 is vlaves active LED, pin18 output 3 is module fault LED, also when i say output i also refer to digout, pin26 output 13 is module status LED, pin27 output 14 is ABS ignition relay, pin31 digout18 is prox sensor control, pin 20 IO 5 is PS Enable, pin25 IO10 is PP SW, analog 1 input 1 IO 11 is control relay to adapter RGB LED green 423210 whichi i assume is 24v, pin28 output 15 is adaptor RGB LED RED, pin29 output16 is adapter RGB LED Blue, pin30 output 17 is NON-OBD2 CAN relay.
Go through all this information compare it to the software alias map, then compare that to wiring map, then compare that to the differcnes between R3 and R14 - is there a speiciifc wire we need to look at. thank yo
keep in mind the difference of what i'm saying input7 for example would mean analog7, pin 7 does not necessareily mean analog7 its just the pin of the netway.
R14 + IO PIN R3, R3+ IO PIN
O1 16 O1 16
O2 17 O2 17
O3 18 O3 18
O4 19 O4 19
O5 20 O5 20
I6 21 I6 21
I7 22 I7 22
I8 23 I8 23
I9 24 I9 24
I10 25 I10 25
O11 1 O11 1
O12 14 O12 14
O13 26 O13 26
O14 27 O14 27
O15 28 O15 28
O16 29 O16 29
O17 10 O17 30
O18 11 O18 31
O19 12 O19 32
O20 13 O20 33
O21 34 O21 34
I22 35 I22 35
I23 36 I23 36
I24 37 I24 37
Current software setup inputs/outpus
-----------------------------------------------
Alias Map for Emulation:
----------------------------------------------
1. _sdAbsMaxFiles--y31
2. _sdFilesPresent--y28
3. _sdFilesToDelete--y30
4. _sdLogFileState--x93
5. _sdMaxFiles--y29
6. A_CurrentSense--analog2
7. A_OBD2--analog9
8. A_PpSw2--analog23
9. A_PpSw--analog10
10. A_Prox1--analog8
11. A_Prox2--analog24
12. A_VehPowerSupply--analog1
13. AirFillRtnStart_B1--x42
14. AirFillRtnStart_B2--x43
15. Airmass_NoTenths--y9
16. Airmass_Raw--y8
17. All_X_VarData--x0
18. B_BatteryVoltage--x21
19. B_MeasComprTemp--x23
20. B_SystemPressure--x22
21. Cb_AirFill_Done--xbit50105
22. Cb_AirTankAdjInProg--xbit50204
23. Cb_ByPassPpSw--xbit50106
24. Cb_CycleAborted--xbit50101
25. Cb_DataLogEnable--xbit50306
26. CB_DD_High--x552
27. CB_DD_Low--x553
28. Cb_DeflateScreenActive--xbit50406
29. Cb_DelayFrontFill--xbit50200
30. Cb_EnablePlcRtcSet--xbit50305
31. Cb_FillTimRslt_b0--xbit50205
32. Cb_FillTimRslt_b1--xbit50206
33. Cb_FrontSpringFillOnly--xbit50103
34. CB_FrontSpringFillTime--x505
35. CB_HH_High--x554
36. CB_HH_Low--x555
37. Cb_InCycle--xbit50100
38. Cb_InitBleed--xbit50405
39. CB_MM_High--x550
40. CB_MM_Low--x551
41. CB_MN_High--x556
42. CB_MN_Low--x557
43. Cb_ModuleFillMode--xbit50201
44. Cb_NoTank--xbit50104
45. Cb_PreFlipPresCalc--xbit50203
46. Cb_RearSpringFillOnly--xbit50102
47. CB_RearSpringFillTime--x506
48. Cb_RepairOffline--xbit50202
49. Cb_ReStartTankPresRd--xbit50300
50. Cb_SdFormat--xbit50304
51. CB_SS_High--x558
52. CB_SS_Low--x559
53. Cb_TrigRideHeightSensRd--xbit50301
54. Cb_WS_ProxiWrite--xbit50207
55. CB_YY_High--x548
56. CB_YY_Low--x549
57. ctr_NegResp--x16
58. ctr_NoResp--x15
59. DeflateStart$0334_B1--x62
60. DeflateStart$0334_B2--x63
61. DeflateStart$0334_B3--x64
62. DeflateTemp1--x65
63. deviceSdFree--x145
64. deviceSdPresent--x199
65. DtcMsgBytes--x20
66. EEPROMStatusB1_b6--xbit3106
67. EEPROMStatusB1_b7--xbit3107
68. EEPROMStatusB1--x31
69. EEPROMStatusB2_b6--xbit3206
70. EEPROMStatusB2_b7--xbit3207
71. EEPROMStatusB2--x32
72. EEPROMStatusB3--x33
73. EEPROMStatusB4--x34
74. EEPROMStatusB5--x35
75. Last_RespB1--x146
76. Last_RespB2--x147
77. Last_RespB3--x148
78. LogStartMs_tmp--z2
79. LogStartMs--z1
80. NRC_Byte1--x141
81. NRC_Byte2--x142
82. NRC_Byte3--x143
83. O_IgnEnable--digout14
84. O_LED_ConRdy--digout1
85. O_LED_Fault--digout3
86. O_LED_PbSw--digout11
87. O_LED_Status--digout4
88. O_LED_ValvesActive--digout2
89. O_LedRgbBlue--digout16
90. O_LedRgbGreen--digout11
91. O_LedRgbRed--digout15
92. O_PsEnable--digout5
93. O_RelayCan--digout12
94. O_RelayProx2--digout18
95. O_ValveClamp--digout8
96. O_ValveFill--digout9
97. O_ValveVent--digout10
98. ons_AirBleed--xbit900
99. pb_2ndStrtPrsRd_Done--xbit807
100. pb_2ndStrtPrsRd_InProg--xbit806
101. pb_CC_Done--xbit107
102. pb_CC_InProg--xbit106
103. pb_ClampDone--xbit605
104. pb_ClampInProgress--xbit604
105. pb_DiagMode--xbit101
106. pb_fileOpened--xbit1007
107. pb_FillPresDone--xbit607
108. pb_FillPresInProg--xbit606
109. pb_FinalReadDTCs_Done--xbit407
110. pb_FinalReadDTCs_InProg--xbit406
111. pb_FinalVehStatReg_Done--xbit405
112. pb_FinalVehStatReg_InProg--xbit404
113. pb_Flasher--xbit500
114. pb_FnlStrtPrsRd_Done--xbit805
115. pb_FnlStrtPrsRd_InProg--xbit804
116. pb_InitVehTstStatReg_Done--xbit103
117. pb_InitVehTstStatReg_InProg--xbit102
118. pb_ModulePresent--xbit100
119. pb_ModuleReset_Done--xbit1005
120. pb_ModuleReset_InProg--xbit1004
121. pb_ONS_CycleDone--xbit902
122. pb_ONS_CycleStarted--xbit901
123. pb_ONS_RdRideHtSensors--xbit903
124. pb_PreFillDone--xbit603
125. pb_PreFillInProgress--xbit602
126. pb_ProxiWrite_Done--xbit1001
127. pb_ProxiWrite_InProg--xbit1000
128. pb_PrsRdRtn_Done--xbit46301
129. pb_PrsRdRtn_InProg--xbit46300
130. pb_ReadAmRtnStatus_Done--xbit401
131. pb_ReadAmRtnStatus_InProg--xbit400
132. pb_ReadDTCs_Done--xbit201
133. pb_ReadDTCs_InProg--xbit200
134. pb_ReadEcuPartNo_Done--xbit203
135. pb_ReadEcuPartNo_InProg--xbit202
136. pb_ReadRtnStatus$0315_Done--xbit803
137. pb_ReadRtnStatus$0315_InProg--xbit802
138. pb_ReadRtnStatus$0332_Done--xbit601
139. pb_ReadRtnStatus$0332_InProg--xbit600
140. pb_ReadRtnStatus$0351_Done--xbit303
141. pb_ReadRtnStatus$0351_InProg--xbit302
142. pb_ReadSwPartNo_Done--xbit707
143. pb_ReadSwPartNo_InProg--xbit706
144. pb_ReadVio_Done--xbit205
145. pb_ReadVio_InProg--xbit204
146. pb_ResetPending_FileClose--xbit60600
147. pb_RideHtReadOnce--xbit1006
148. pb_StartAmRtn_Done--xbit307
149. pb_StartAmRtn_InProg--xbit306
150. pb_StartedAirFillPosResp--xbit24700
151. pb_StartFrontFill_Done--xbit305
152. pb_StartFrontFill_InProg--xbit304
153. pb_StartPresRead_Done--xbit801
154. pb_StartPresRead_InProg--xbit800
155. pb_StartRearFill_Done--xbit301
156. pb_StartRearFill_InProg--xbit300
157. pb_StopFillRtn_InDone--xbit503
158. pb_StopFillRtn_InProg--xbit502
159. pb_TankMinPr_Done--xbit207
160. pb_TankMinPr_InProg--xbit206
161. pb_VinRead_Done--xbit105
162. pb_VinRead_InProg--xbit104
163. pb_WS_proxiRead_Done--xbit60402
164. pb_WS_proxiRead_InProg--xbit60400
165. pb_WS_ProxiWrite_Done--xbit1003
166. pb_WS_ProxiWrite_InProg--xbit1002
167. ReadLocation--y4
168. RoutineStart--y5
169. RoutineStatus--y6
170. RTC_DD--x336
171. RTC_HH--x337
172. RTC_MM--x335
173. RTC_MN--x338
174. RTC_SS--x339
175. rtc_temp--y13
176. RTC_YY--x334
177. RtnStatus$030F--x25
178. RtnStatus$0311--x26
179. RtnStatus$0315--x28
180. RtnStatus$0332--x27
181. RtnStatus$0334--x29
182. RtnStatus$0351--x24
183. Sb_100msRes--xbit40305
184. Sb_2ndPrsRdRtn_Done--xbit46306
185. Sb_2ndPrsRdRtn_InProg--xbit46305
186. Sb_AmRtn_Done--xbit40406
187. Sb_AmRtn_InProg--xbit40405
188. Sb_ASCM_ConRdy--xbit40200
189. Sb_ASCMPartNo_Read--xbit40104
190. Sb_BleedFuncDone--xbit40306
191. Sb_BleedFuncInProg--xbit40404
192. Sb_ByPassPpSw--xbit50106
193. Sb_CpuActive--xbit40202
194. Sb_DiagMode--xbit40100
195. Sb_DiscAscmAdaptorOK--xbit40106
196. Sb_DTC_Cleared--xbit40102
197. Sb_DTC_Read--xbit40103
198. Sb_FileMaintActive--xbit40503
199. Sb_FinalDTC_Read--xbit40105
200. Sb_FL_FillDone--xbit46405
201. Sb_FL_FillInProg--xbit46404
202. SB_FL_RH--x458
203. Sb_FL_TermWithFail--xbit46504
204. Sb_FL_TimeOut--xbit46505
205. Sb_FltAirMassCalcRtn--xbit40302
206. Sb_FltAirSpringBleed--xbit40303
207. Sb_FltFrontSpringFillRtn--xbit40301
208. Sb_FltProxiWrite--xbit40500
209. Sb_FltRearSpringFillRtn--xbit40300
210. Sb_FnlPrsRdRtn_Done--xbit46304
211. Sb_FnlPrsRdRtn_InProg--xbit46303
212. Sb_FR_FillDone--xbit46407
213. Sb_FR_FillInProg--xbit46406
214. SB_FR_RH--x459
215. Sb_FR_TermWithFail--xbit46506
216. Sb_FR_TimeOut--xbit46507
217. Sb_FrontSpringFill_Done--xbit40403
218. Sb_FrontSpringFill_InProg--xbit40402
219. Sb_ModuleFault--xbit40203
220. Sb_OBD2--xbit40304
221. Sb_PpSw2--xbit40305
222. Sb_PpSw--xbit40204
223. Sb_Prox1--xbit40207
224. Sb_Prox2--xbit40307
225. Sb_ProxiRead_Pos255Hex--xbit40505
226. Sb_ProxiWrite_Active--xbit40502
227. Sb_ProxiWrite_PRC--xbit40501
228. Sb_PrsRd_Fault--xbit46302
229. Sb_PrsRdRtn_Done--xbit46301
230. Sb_PrsRdRtn_InProg--xbit46300
231. Sb_RearSpringFill_Done--xbit40401
232. Sb_RearSpringFill_InProg--xbit40400
233. Sb_RideHeightRd_Done--xbit40407
234. Sb_RL_FillDone--xbit46401
235. Sb_RL_FillInProg--xbit46400
236. SB_RL_RH--x460
237. Sb_RL_TermWithFail--xbit46500
238. Sb_RL_TimeOut--xbit46501
239. Sb_RoutineActive--xbit40201
240. Sb_RR_FillDone--xbit46403
241. Sb_RR_FillInProg--xbit46402
242. SB_RR_RH--x461
243. Sb_RR_TermWithFail--xbit46502
244. Sb_RR_TimeOut--xbit46503
245. Sb_SdCardStatus--xbit40506
246. SB_sdFilesLSB--x602
247. SB_sdFilesMSB--x601
248. Sb_SdFormatInProg--xbit40504
249. SB_Status_RH--x462
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going through all this info why is R14 causing problems but R3 isn't? | {
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} | en | 5 |
arena_expert_000058 | 从数学专业领域解释下面这段话：这个说的很好，我也是当时学了泛函分析和矩阵论以后，明白了范数、距离、巴纳赫空间、基、正交基、完备性等等概念以后才理解了傅立叶变换就是找到了一组独立的完备正交基，属实觉得本科不学这些初级的分析概念就像是盲人摸象，明明有工具能帮助你理解，但就是不跟你说[哭惹R]其实，我理解，最后用欧拉公式拓展到非周期函数的延拓这一步，从几何上看就是在空间里画了一个螺旋上升的弹簧，用这玩意的压缩拉伸旋转来逼近函数。 | {
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} | zh | 4 |
arena_expert_000059 | Jak powinno wygladac wzorowe sprawdzenie prototypu zmontowanej karty pcb z komponentami pod katem montazu smd z uwzglednieniem montazy przewlekanego przez inzyniera procesu? | {
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} | pl | 4 |
arena_expert_000060 | import backtrader as bt
import math
class NAS100ScalpingStrategy(bt.Strategy):
params = (
("lookback_period", 20),
("volume_threshold", 1.5),
("momentum_threshold", 0.02),
("risk_percent", 0.01), # 1% risk per trade
("max_daily_loss", 0.03), # 3% max daily loss
("atr_period", 14),
("initial_rr_ratio", 1.5), # Initial risk-reward ratio
("trail_start_rr", 1.0), # Start trailing after 1:1 R:R
("trail_atr_mult", 1.5), # Trailing stop ATR multiplier
("partial_take_rr", 2.0), # Take partial profits at 2:1 R:R
("partial_take_percent", 0.5), # Take 50% of position as partial
# New parameter for volatility expansion threshold
("volatility_threshold", 1.8),
)
def __init__(self):
# Existing technical indicators
self.vol_sma = bt.indicators.SimpleMovingAverage(self.datas[0].volume, period=20)
self.immediate_support = bt.indicators.Lowest(self.datas[0].low, period=10)
self.immediate_resistance = bt.indicators.Highest(self.datas[0].high, period=10)
self.avg_range = bt.indicators.SimpleMovingAverage(
self.datas[0].high - self.datas[0].low, period=self.p.lookback_period
)
self.avg_range10 = bt.indicators.SimpleMovingAverage(
self.datas[0].high - self.datas[0].low, period=10
)
self.atr = bt.indicators.ATR(self.datas[0], period=self.p.atr_period)
self.rsi = bt.indicators.RSI(self.datas[0].close, period=14)
self.ema_fast = bt.indicators.EMA(self.datas[0].close, period=9)
self.ema_slow = bt.indicators.EMA(self.datas[0].close, period=21)
self.ema_trend = bt.indicators.EMA(self.datas[0].close, period=50) # Longer term trend
# State variables for signals and risk management
self.prev_consolidation = False
self.last_roc = None
self.order = None
self.position_type = 0 # 1 for long, -1 for short
self.entry_price = None
self.initial_stop_loss = None
self.trailing_stop = None
self.initial_take_profit = None
self.partial_taken = False
self.risk_amount = 0
# Daily loss tracking and performance
self.daily_pnl = 0.0
self.current_date = None
self.trade_count = 0
self.winning_trades = 0
self.max_winner_r = 0
# NEW: Leading indicator tracking lists
self.range_history = []
self.tick_direction = [] # To track tick-by-tick direction
def next(self):
# Update daily pnl and date
current_day = self.datas[0].datetime.date(0)
if self.current_date != current_day:
self.daily_pnl = 0.0
self.current_date = current_day
# Daily loss protection
if self.daily_pnl <= -self.broker.getvalue() * self.p.max_daily_loss:
if self.position:
self.close()
self.log("Daily loss limit reached. Closing position.")
return
# Avoid processing if an order is pending
if self.order:
return
# Ensure sufficient data history
if len(self.datas[0]) < max(self.p.lookback_period, self.p.atr_period, 50):
return
# NEW: Update extra leading indicators (range and tick direction)
self._update_leading_indicators()
# Calculate risk per trade
account_value = self.broker.getvalue()
self.risk_amount = account_value * self.p.risk_percent
# Original momentum and acceleration calculations
roc1 = self._calculate_momentum()
acceleration = self._calculate_acceleration(roc1)
# Gather original signals
momentum_signal = self._get_momentum_signal(roc1, acceleration)
volume_signal = self._get_volume_signal()
breakout_signal = self._get_breakout_signal()
trend_signal = self._get_trend_signal()
rsi_signal = self._get_rsi_signal()
long_trend_signal = self._get_long_trend_signal()
# Count signals from original indicators
bullish_signals, bearish_signals = self._count_signals(
momentum_signal, volume_signal, breakout_signal, trend_signal, rsi_signal, long_trend_signal
)
# NEW: Compute additional leading indicator signals
momentum_accel = self._get_momentum_acceleration_signal(acceleration)
vol_expansion = self._get_volatility_expansion_signal()
order_flow = self._get_order_flow_signal()
momentum_shift = self._get_momentum_shift_signal()
structure_signal = self._get_price_structure_signal()
# Add extra signals into totals
if momentum_accel > 0:
bullish_signals += 1
elif momentum_accel < 0:
bearish_signals += 1
if vol_expansion > 0:
bullish_signals += 1
elif vol_expansion < 0:
bearish_signals += 1
if order_flow > 0:
bullish_signals += 1
elif order_flow < 0:
bearish_signals += 1
if momentum_shift > 0:
bullish_signals += 1
elif momentum_shift < 0:
bearish_signals += 1
if structure_signal > 0:
bullish_signals += 1
elif structure_signal < 0:
bearish_signals += 1
# Decide on entry if not in a position
if not self.position:
self._check_entry_signals(bullish_signals, bearish_signals)
else:
self._manage_position()
def _update_leading_indicators(self):
# Update range_history with current candle range
current_range = self.datas[0].high[0] - self.datas[0].low[0]
self.range_history.append(current_range)
if len(self.range_history) > 10:
self.range_history.pop(0)
# Update tick_direction based on price change from previous close
if len(self.datas[0]) >= 2:
if self.datas[0].close[0] > self.datas[0].close[-1]:
tick = 1
elif self.datas[0].close[0] < self.datas[0].close[-1]:
tick = -1
else:
tick = 0
self.tick_direction.append(tick)
if len(self.tick_direction) > 5:
self.tick_direction.pop(0)
def _calculate_momentum(self):
if len(self.datas[0]) > 1 and self.datas[0].close[-1] > 0:
return (self.datas[0].close[0] - self.datas[0].close[-1]) / self.datas[0].close[-1]
return 0
def _calculate_acceleration(self, roc1):
acceleration = 0
if self.last_roc is not None:
acceleration = roc1 - self.last_roc
self.last_roc = roc1
return acceleration
def _get_momentum_signal(self, roc1, acceleration):
if roc1 > self.p.momentum_threshold and acceleration > 0:
return 1
elif roc1 < -self.p.momentum_threshold and acceleration < 0:
return -1
return 0
def _get_volume_signal(self):
# Original volume signal based on SMA
if self.vol_sma[0] <= 0:
return 0
vol_spike = self.datas[0].volume[0] / self.vol_sma[0]
if vol_spike > self.p.volume_threshold:
if self.datas[0].close[0] > self.datas[0].open[0]:
return 1
elif self.datas[0].close[0] < self.datas[0].open[0]:
return -1
return 0
def _get_breakout_signal(self):
cur_range = self.datas[0].high[0] - self.datas[0].low[0]
avg_range_val = self.avg_range[0] if self.avg_range[0] > 0 else 1
cur_compression = cur_range / avg_range_val
consolidation = cur_compression < 0.7
breakout_signal = 0
if self.prev_consolidation and not consolidation:
if self.datas[0].close[0] > self.datas[0].open[0]:
breakout_signal = 1
elif self.datas[0].close[0] < self.datas[0].open[0]:
breakout_signal = -1
self.prev_consolidation = consolidation
return breakout_signal
def _get_trend_signal(self):
if self.ema_fast[0] > self.ema_slow[0]:
return 1
elif self.ema_fast[0] < self.ema_slow[0]:
return -1
return 0
def _get_long_trend_signal(self):
if self.datas[0].close[0] > self.ema_trend[0]:
return 1
elif self.datas[0].close[0] < self.ema_trend[0]:
return -1
return 0
def _get_rsi_signal(self):
if self.rsi[0] < 35:
return 1
elif self.rsi[0] > 65:
return -1
return 0
def _count_signals(self, momentum_signal, volume_signal, breakout_signal, trend_signal, rsi_signal, long_trend_signal):
bullish_signals = 0
bearish_signals = 0
for signal in [momentum_signal, volume_signal, breakout_signal, trend_signal, rsi_signal, long_trend_signal]:
if signal == 1:
bullish_signals += 1
elif signal == -1:
bearish_signals += 1
# Add support/resistance confluence
if self.datas[0].close[0] > self.immediate_resistance[0]:
bullish_signals += 1
elif self.datas[0].close[0] < self.immediate_support[0]:
bearish_signals += 1
return bullish_signals, bearish_signals
# NEW: Additional leading indicator methods
def _get_momentum_acceleration_signal(self, acceleration):
if acceleration > 0.0001:
return 1
elif acceleration < -0.0001:
return -1
return 0
def _get_volatility_expansion_signal(self):
if len(self.range_history) < 5:
return 0
current_range = self.range_history[-1]
avg_range = sum(self.range_history[:-1]) / (len(self.range_history) - 1)
if avg_range > 0 and current_range/avg_range > self.p.volatility_threshold:
# When price is near the top of the candle, consider it bullish expansion,
# and bearish if near the bottom.
current_price = self.datas[0].close[0]
range_pos = (current_price - self.datas[0].low[0]) / (self.datas[0].high[0] - self.datas[0].low[0])
if range_pos > 0.7:
return 1
elif range_pos < 0.3:
return -1
return 0
def _get_order_flow_signal(self):
# Use volume weighted by candle position as a proxy for order flow pressure.
if (self.datas[0].high[0] - self.datas[0].low[0]) == 0:
return 0
close_pos = (self.datas[0].close[0] - self.datas[0].low[0]) / (self.datas[0].high[0] - self.datas[0].low[0])
buying_power = close_pos * self.datas[0].volume[0]
selling_power = (1 - close_pos) * self.datas[0].volume[0]
if buying_power > selling_power * 1.5:
return 1
elif selling_power > buying_power * 1.5:
return -1
return 0
def _get_momentum_shift_signal(self):
if len(self.tick_direction) < 4:
return 0
recent = self.tick_direction[-4:]
if recent.count(1) >= 3:
return 1
elif recent.count(-1) >= 3:
return -1
return 0
def _get_price_structure_signal(self):
if len(self.datas[0]) < 10:
return 0
recent_highs = [self.datas[0].high[-i] for i in range(1, 6)]
recent_lows = [self.datas[0].low[-i] for i in range(1, 6)]
current_high = self.datas[0].high[0]
current_low = self.datas[0].low[0]
if current_high > max(recent_highs):
return 1
elif current_low < min(recent_lows):
return -1
return 0
def _calculate_position_size(self, stop_distance):
if stop_distance <= 0:
return 0
position_value = self.risk_amount / stop_distance
position_size = position_value / self.datas[0].close[0]
min_size = 0.01
max_size = self.broker.getvalue() * 0.1 / self.datas[0].close[0]
return max(min_size, min(position_size, max_size))
def _check_entry_signals(self, bullish_signals, bearish_signals):
current_price = self.datas[0].close[0]
# For a long entry, require bullish confluence (using a threshold of 4)
if bullish_signals >= 4 and self.rsi[0] < 70 and current_price > self.ema_trend[0]:
stop_distance = current_price - (self.immediate_support[0] * 0.9985)
if stop_distance > 0:
position_size = self._calculate_position_size(stop_distance)
if position_size > 0:
initial_tp_distance = stop_distance * self.p.initial_rr_ratio
self.order = self.buy(size=position_size)
self.position_type = 1
self.entry_price = current_price
self.initial_stop_loss = current_price - stop_distance
self.trailing_stop = self.initial_stop_loss
self.initial_take_profit = current_price + initial_tp_distance
self.partial_taken = False
self.log(f"LONG ENTRY: Size={position_size:.4f} @ {current_price:.2f} | SL={self.initial_stop_loss:.2f} | Risk=${self.risk_amount:.2f} | Signals={bullish_signals}")
# For a short entry, require bearish confluence
elif bearish_signals >= 4 and self.rsi[0] > 30 and current_price < self.ema_trend[0]:
stop_distance = (self.immediate_resistance[0] * 1.0015) - current_price
if stop_distance > 0:
position_size = self._calculate_position_size(stop_distance)
if position_size > 0:
initial_tp_distance = stop_distance * self.p.initial_rr_ratio
self.order = self.sell(size=position_size)
self.position_type = -1
self.entry_price = current_price
self.initial_stop_loss = current_price + stop_distance
self.trailing_stop = self.initial_stop_loss
self.initial_take_profit = current_price - initial_tp_distance
self.partial_taken = False
self.log(f"SHORT ENTRY: Size={position_size:.4f} @ {current_price:.2f} | SL={self.initial_stop_loss:.2f} | Risk=${self.risk_amount:.2f} | Signals={bearish_signals}")
def _manage_position(self):
current_price = self.datas[0].close[0]
if self.position_type == 1:
self._manage_long_position(current_price)
elif self.position_type == -1:
self._manage_short_position(current_price)
def _manage_long_position(self, current_price):
risk_per_share = self.entry_price - self.initial_stop_loss
current_profit = current_price - self.entry_price
r_multiple = current_profit / risk_per_share if risk_per_share > 0 else 0
if r_multiple > self.max_winner_r:
self.max_winner_r = r_multiple
# Partial profit-taking
if (not self.partial_taken and r_multiple >= self.p.partial_take_rr and self.position.size > 0.02):
partial_size = self.position.size * self.p.partial_take_percent
self.sell(size=partial_size)
self.partial_taken = True
self.log(f"PARTIAL PROFIT: Sold {partial_size:.4f} @ {current_price:.2f} | R={r_multiple:.2f}")
# Trail stop after reaching a set R ratio
if r_multiple >= self.p.trail_start_rr:
atr_trail = current_price - (self.atr[0] * self.p.trail_atr_mult)
breakeven_plus = self.entry_price + (risk_per_share * 0.2)
new_trailing_stop = max(atr_trail, breakeven_plus, self.trailing_stop)
if new_trailing_stop > self.trailing_stop:
self.trailing_stop = new_trailing_stop
self.log(f"TRAIL UPDATE: New trailing stop @ {self.trailing_stop:.2f} | R={r_multiple:.2f}")
exit_long = False
exit_reason = ""
if current_price <= self.trailing_stop:
exit_long = True
exit_reason = f"Trailing Stop (R={r_multiple:.2f})"
elif r_multiple < 0.5:
if self.rsi[0] > 80 or (self.ema_fast[0] < self.ema_slow[0] and r_multiple < 0):
exit_long = True
exit_reason = f"Early Exit (R={r_multiple:.2f})"
elif r_multiple > 3.0 and current_price < self.ema_fast[0]:
exit_long = True
exit_reason = f"Trend Reversal on Big Winner (R={r_multiple:.2f})"
if exit_long:
self.order = self.close()
self.log(f"CLOSING LONG @ {current_price:.2f} - {exit_reason}")
def _manage_short_position(self, current_price):
risk_per_share = self.initial_stop_loss - self.entry_price
current_profit = self.entry_price - current_price
r_multiple = current_profit / risk_per_share if risk_per_share > 0 else 0
if r_multiple > self.max_winner_r:
self.max_winner_r = r_multiple
if (not self.partial_taken and r_multiple >= self.p.partial_take_rr and abs(self.position.size) > 0.02):
partial_size = abs(self.position.size) * self.p.partial_take_percent
self.buy(size=partial_size)
self.partial_taken = True
self.log(f"PARTIAL PROFIT: Covered {partial_size:.4f} @ {current_price:.2f} | R={r_multiple:.2f}")
if r_multiple >= self.p.trail_start_rr:
atr_trail = current_price + (self.atr[0] * self.p.trail_atr_mult)
breakeven_plus = self.entry_price - (risk_per_share * 0.2)
new_trailing_stop = min(atr_trail, breakeven_plus, self.trailing_stop)
if new_trailing_stop < self.trailing_stop:
self.trailing_stop = new_trailing_stop
self.log(f"TRAIL UPDATE: New trailing stop @ {self.trailing_stop:.2f} | R={r_multiple:.2f}")
exit_short = False
exit_reason = ""
if current_price >= self.trailing_stop:
exit_short = True
exit_reason = f"Trailing Stop (R={r_multiple:.2f})"
elif r_multiple < 0.5:
if self.rsi[0] < 20 or (self.ema_fast[0] > self.ema_slow[0] and r_multiple < 0):
exit_short = True
exit_reason = f"Early Exit (R={r_multiple:.2f})"
elif r_multiple > 3.0 and current_price > self.ema_fast[0]:
exit_short = True
exit_reason = f"Trend Reversal on Big Winner (R={r_multiple:.2f})"
if exit_short:
self.order = self.close()
self.log(f"CLOSING SHORT @ {current_price:.2f} - {exit_reason}")
def notify_order(self, order):
if order.status in [order.Completed, order.Canceled, order.Margin]:
self.order = None
def notify_trade(self, trade):
if trade.isclosed:
self.trade_count += 1
self.daily_pnl += trade.pnl
risk_per_share = 0
r_multiple = 0
if self.entry_price is not None and self.initial_stop_loss is not None:
risk_per_share = abs(self.entry_price - self.initial_stop_loss)
if risk_per_share > 0 and abs(trade.size) > 0:
r_multiple = trade.pnl / (risk_per_share * abs(trade.size))
else:
r_multiple = 0
if trade.pnl > 0:
self.winning_trades += 1
win_rate = (self.winning_trades / self.trade_count) * 100 if self.trade_count > 0 else 0
self.log(f"TRADE CLOSED #{self.trade_count} | PnL: ${trade.pnl:.2f} | R={r_multiple:.2f} | Win Rate: {win_rate:.1f}% | Daily PnL: ${self.daily_pnl:.2f}")
self.position_type = 0
self.entry_price = None
self.initial_stop_loss = None
self.trailing_stop = None
self.initial_take_profit = None
self.partial_taken = False
def log(self, txt):
dt = self.datas[0].datetime.date(0)
t = self.datas[0].datetime.time(0)
print(f"{dt} {t} | {txt}")
def stop(self):
win_rate = (self.winning_trades / self.trade_count) * 100 if self.trade_count > 0 else 0
print(f"\n=== ENHANCED STRATEGY RESULTS ===")
print(f"Total Trades: {self.trade_count}")
print(f"Winning Trades: {self.winning_trades}")
print(f"Win Rate: {win_rate:.2f}%")
print(f"Max R Multiple Achieved: {self.max_winner_r:.2f}")
print(f"Final Portfolio Value: ${self.broker.getvalue():.2f}")
print(f"================================\n")
ROI
-1.57%
-$1,568.15
Win Ratio
14.96%
146 of 976 positions
Max Drawdown
2.18%
$2,182.74
Time in Market
90.68%
24798 of 27347 candles
IMPROVE THIS BASDE ON RESULTS
| {
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} | en | 5 |
arena_expert_000061 | Would Newtonian physics make sense in the hyperbolic plane? | {
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} | en | 4 |
arena_expert_000062 | ""Why is this UB not caught during constexpr execution?
#include <cstdint>
consteval std::int8_t f(std::int8_t value) {
for(int i = 0; i < 1000; ++i) {
value -= 1;
}
return value;
}
static_assert(f(0) == 24);"" | {
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"software_and_it_services": true,
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} | en | 4 |
arena_expert_000063 | szczegółowa analiza dotycząca sygnałów ONC‑W1 (whale transfer do PancakeSwap Router) oraz SOC‑S1 (sentiment negatywny) w przypadku tokena PENGU/USDT (Pudgy Penguins), ze wskazaniem na adres PancakeSwap Router na Binance Smart Chain i jak interpretować takie transfery. | {
"business_and_management_and_financial_operations": true,
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"education": null,
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"travel": null,
"visual_arts_and_design": null,
"writing_and_literature_and_language": null
} | pl | 4 |
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