Results for “physiological-signals”

Process and analyze physiological signals including ECG, EEG, EDA, RSP, PPG, EMG, and EOG using Python.

Explains biomedical concepts, vital signs, biological signals, medical device classifications, and healthcare data standards for technical teams.

Implement signal-based reactive state management in Angular v20+. Use for creating reactive state with signal(), derived state with computed(), dependent state with linkedSignal(), and side effects with effect(). Triggers on state management questions, converting from BehaviorSubject/Observable patterns to signals, or implementing reactive data flows.

Angular forms: Signal Forms (experimental) and Reactive Forms. Trigger: When working with forms, validation, or form state in Angular.

Calculates a per-ticker panic index (0-100) from six weighted signals including VIX, IV Rank, RSI-14, volume anomaly, put/call ratio, and consecutive down days, triggering Bull Put Spread entry signals at scores ≥60.

Applies physical principles to model biological systems, including protein folding, membrane transport, molecular forces, and neural signaling.

Build clinical deep-learning pipelines with PyHealth: load EHR, signal, and imaging datasets, define prediction tasks, instantiate models, train with the PyHealth Trainer, and compute clinical metrics.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Detects whether current market conditions match David Tepper's historic panic-buy signal by combining VIX, FearScore, and a quality filter.

Design feedback patterns for user actions, including confirmations, status updates, and notifications.

Teleological physiology analysis framework for understanding biological systems through multi-constraint optimization. Use when analyzing physiological mechanisms, explaining apparent biological "inefficiencies", preparing for medical examinations (CICM/ANZCA Primary), understanding why biological systems are designed the way they are, or when seeking deeper mechanistic understanding beyond descriptive knowledge. Triggers on questions like "why is X designed this way", "what purpose does Y serve", "how is Z optimized", analysis of physiological trade-offs, or exploration of evolutionary/design constraints.

Use to measure customer effort from behavioural signals instead of CES surveys, and to audit whether a composite effort score is honest. Trigger for "customer effort score", "behavioural CES", effort without survey, repeat contacts and channel switches, transfers and reopens, or "our CES doesn't match operational data".

Synthesize interviews into themes, contradictions, opportunities, and product implications.

Use to identify signals of customer vulnerability in support conversations and audit whether they were recognised and acted on. Trigger for "identify vulnerable customers", "did we spot the vulnerability signals", "customers in financial difficulty", bereavement or health disclosures in support, vulnerable customer handling audits, or designing vulnerability recognition for a support team.

Use to surface fraud, scam and financial-crime signals that customers describe to support before detection systems see them, and to check whether agents recognised and routed them. Trigger for "are customers reporting scams", "new scam pattern targeting our customers", "did we spot the fraud signals", authorised push payment scams, "customer was coached by someone on the phone", or fraud reports arriving through support.

Recommends confirmatory testing with corticotropin stimulation test in patients presenting with clinical symptoms or signs suggesting PAI (e.g., fatigue, hypotension, hyponatremia, hyperpigmentation) when the patient's condition permits safe testing. Use when a clinician identifies suggestive features and circumstances allow outpatient stimulation testing without imminent need for emergency glucocorticoids.

Configures autonomous heartbeat and cron-based proactive routines (e.g., morning briefing setup, unanswered-message scan cadence). Invoke when user is SETTING UP or MODIFYING a proactive routine, not when the routine itself fires. Cron crons execute their own logic — they do NOT load this skill. Triggers: "set up proactive check", "configure heartbeat", "add morning briefing", "tune cron cadence".

Record and analyze post-trade outcomes for trading signals, tracking false positives, missed opportunities, and regime mismatches to generate feedback for signal aggregation and skill improvement.

Optimize prompts via process goals (controllable behavioral instructions) rather than outcome goals (sparse end-result demands). Grounded in sports psychology meta-analysis showing process goals (d=1.36) vastly outperform outcome goals (d=0.09). Use when designing prompts, optimizing LLM steering, implementing CoT/decomposition patterns, or building automatic prompt optimization pipelines. Instantiates surrogate loss paradigm for discrete prompt space.

Acoustics Based Analysis Skill

当需要进入并维持高效、专注的心流状态，以提升学习、工作或技能获取效率时

Score a clinical ASR manifest against a chosen NIM, produce a five-section KER leaderboard, and route the user via a post-eval decision tree.

Design, select, and analyze waveforms for radar, sonar, and active sensing using the Phased Array System Toolbox. Covers LFM, NLFM, FMCW, phase-coded, CW, stepped FM, custom IQ, ambiguity functions, sidelobe reduction, and Doppler tolerance. Key objects: phased.LinearFMWaveform, phased.NonlinearFMWaveform, phased.CustomFMWaveform, phased.PhaseCodedWaveform, phased.FMCWWaveform, phased.SteppedFMWaveform, phased.MFSKWaveform, phased.RectangularWaveform, nlfmspec2freq, shapespectrum, ambgfun, pambgfun, sidelobelevel, legendreseq, mlseq, radarWaveformGenerator.

Use to find upgrade, seat-growth and new-use-case signals that customers give support and nobody routes anywhere. Trigger for "find upsell opportunities in support", "customers hitting plan limits", "which accounts are asking about enterprise features", expansion signals from tickets, or support-sourced pipeline.

Apply behavioral science and persuasion principles to make marketing more convincing.

Use when the user wants more human-like AI responses — less robotic, less listy, more authentic. Triggers: 'behuman', 'be real', 'like a human', 'more human', 'less AI', 'talk like a person', 'mirror mode', 'stop being so AI', or when conversations are emotionally charged (grief, job loss, relationship advice, fear). NOT for technical questions, code generation, or factual lookups.

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

Applies behavioral science and persuasion frameworks to marketing. Use when the user requests 'cognitive bias', 'loss aversion', 'social proof', 'scarcity', 'Cialdini', or 'persuasion framework'.

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

Batch signal isolation for Phenocycler spleen channels using matched blank pairs and kintsugi.signal

Flamingo: A Visual Language Model for Few-Shot Learning

Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"

Use to design or audit the support contribution to a customer health score, so the score predicts something instead of averaging weakly-related signals into a colour. Trigger for "build a customer health score", "add support signal to health scoring", "our health scores don't predict churn", red/amber/green account scoring, or a health score nobody trusts.