「inclusion」の検索結果

Produce evidence-labelled UX needs, journey, structure, inclusion, and engineering-handoff assets. Use when a practitioner needs a durable UX artifact rather than coaching.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnose and fix .NET HTTPS dev certificate trust issues on Linux. Covers the full certificate lifecycle from generation to system CA bundle inclusion, with distro-specific guidance for Ubuntu, Fedora, Arch, and WSL2.

日本語の概要は準備中です。原文の説明を表示しています。

Handles batch effects in bulk RNA-seq via design-matrix inclusion (the correct path for DE), ComBat/ComBat-seq for visualization, SVA for unknown latent factors, RUVSeq for negative-control-gene-anchored unwanted variation, and limma::removeBatchEffect for plotting only. Encodes the Nygaard 2016 cardinal sin against testing on a batch-corrected matrix, the choice between SVA/RUVg/RUVs/RUVr, the confounding non-identifiability problem, the single-cell boundary (Harmony/MNN are NOT for bulk), and the Goh 2017 harmonization critique. Use when designing a DE analysis with batch structure, troubleshooting batch-dominated PCA, choosing ComBat vs ComBat-seq, handling unknown batch via SVA, integrating across studies, or deciding when (rarely) to subtract batch.

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Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters), VAST-TOOLS (cross-species with microexon support), Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage), or IRFinder-S (intron retention coverage-aware). Distinguishes the five canonical event classes (SE, A5SS, A3SS, MXE, RI), special classes (microexons, exitrons, AFE/ALE), intron retention subtypes (canonical RI vs detained introns), and applies effective-length normalization. Use when measuring splice-site usage or isoform inclusion ratios from short-read RNA-seq.

日本語の概要は準備中です。原文の説明を表示しています。

Query journal indexing/inclusion status on CNKI - check which databases include a journal (北大核心, CSSCI, CSCD, SCI, EI, etc.), get impact factors and evaluation data. Use when user asks about a journal's level, indexing, or ranking.

日本語の概要は準備中です。原文の説明を表示しています。

Redesign a lesson to centre students' cultural backgrounds, community knowledge, and lived experience. Use when making curriculum relevant and inclusive for diverse student populations.

日本語の概要は準備中です。原文の説明を表示しています。

Adapt a classroom task for specific learner needs while preserving the core learning objective intact. Use when differentiating for SEND, EAL, gifted, ADHD, dyslexia, or anxiety.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working on inclusion, i18n/localization, global name/address forms, low-end devices, slow/metered networks, affordability, or first-time/low-confidence users; not WCAG/screen readers (see accessibility).

日本語の概要は準備中です。原文の説明を表示しています。

AutoMCM-Pro industrial-grade math modeling agent (opencode binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.

日本語の概要は準備中です。原文の説明を表示しています。

AutoMCM-Pro industrial-grade math modeling agent (DeepSeek Harness binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.

日本語の概要は準備中です。原文の説明を表示しています。

AutoMCM-Pro industrial-grade math modeling agent (Codex CLI binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.

日本語の概要は準備中です。原文の説明を表示しています。

AutoMCM-Pro industrial-grade math modeling agent. Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.

日本語の概要は準備中です。原文の説明を表示しています。

Conduct a structured literature review on a given topic by defining a search strategy, applying inclusion and exclusion criteria, extracting key findings, and synthesizing results into a coherent academic review. Use when the user requests literature review or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Crystal Growth Specialist. Use when a task calls for Crystal Growth Specialist judgment. Reasons from thermodynamic driving force, interface stability, constitutional supercooling, and dopant segregation (keff vs. k0, G/R) through Cz/Bridgman/FZ/LEC/PVT growth, CGSim and phase-field simulation, XRT topography, etch-pit counting, and FTIR/SIMS mapping while treating striations, inclusions, crucible-reaction contamination, and cool-down slip and cracking as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Solubility-optimized protein sequence design using SolubleMPNN. Use this skill when: (1) Designing for E. coli expression, (2) Optimizing solubility of designed proteins, (3) Reducing aggregation propensity, (4) Need high-yield expression, (5) Avoiding inclusion body formation. For standard design, use proteinmpnn. For ligand-aware design, use ligandmpnn.

日本語の概要は準備中です。原文の説明を表示しています。

Adapt a classroom task for specific learner needs while preserving the core learning objective intact. Use when differentiating for SEND, EAL, gifted, ADHD, dyslexia, or anxiety.

日本語の概要は準備中です。原文の説明を表示しています。

Redesign a lesson to centre students' cultural backgrounds, community knowledge, and lived experience. Use when making curriculum relevant and inclusive for diverse student populations.

日本語の概要は準備中です。原文の説明を表示しています。

Creating and integrating out-of-tree Zephyr modules. Covers module.yml configuration, Kconfig and CMake integration within a module, and West manifest inclusion. Trigger when developing reusable libraries, driver packages, or external software components for Zephyr.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnose and fix .NET HTTPS dev certificate trust issues on Linux. Covers the full certificate lifecycle from generation to system CA bundle inclusion, with distro-specific guidance for Ubuntu, Fedora, Arch, and WSL2.

日本語の概要は準備中です。原文の説明を表示しています。

LLM brand manipulation — build a consensus web so ChatGPT, Claude, Perplexity, and Google AI Overviews mention your brand when people ask about your category. Uses surround sound methodology, entity SEO, and LLM citation science. Use when "get mentioned in AI", "LLM brand presence", "surround sound", "AI search visibility", "Perplexity ranking", "ChatGPT mentions", "AI Overview inclusion", "entity authority", "brand mentions in AI", or any request to influence how AI systems perceive and recommend your brand.

日本語の概要は準備中です。原文の説明を表示しています。

Reference patterns for mathematical and combinatorial problem-solving. Covers modular arithmetic, prime sieves, GCD/LCM, binomial coefficients, fast exponentiation, counting techniques, inclusion-exclusion, and game theory. Load this skill when a problem involves number theory, combinatorics, modular operations, or strategic game analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Plan a sprint by refining backlog items, defining a sprint goal, calculating team capacity, selecting items, and decomposing them into tasks. Produces a SPRINT-PLAN.md with goal, selected items, task breakdown, and capacity allocation. Use when starting a new sprint in a Scrum or agile project, re-planning after significant scope change, transitioning from ad-hoc work to structured sprint cadence, or after backlog grooming when items are ready for inclusion.

日本語の概要は準備中です。原文の説明を表示しています。

Identify gemstones using optical properties, physical tests, and inclusion analysis. Covers refractive index, specific gravity, pleochroism, spectroscopy indicators, and common simulant detection. Use when identifying an unknown gemstone, verifying a seller's claim about species identity, distinguishing natural stones from simulants or synthetics, building gemological literacy through structured observation, or identifying rough material before cutting to ensure safe handling.

日本語の概要は準備中です。原文の説明を表示しています。

Find realistic link prospects with SERP and backlink evidence, discover contact paths via web tools, and draft personalized outreach — with targets saved to .seo/backlink-targets.json for off-page-seo campaigns. Use this skill when the user has a linkable asset (study, tool, guide, template, product page) and wants backlinks, resource-page inclusions, or comparison mentions. Triggers: "link prospecting", "find backlink opportunities", "resource page outreach", "get backlinks for", "link building outreach".

日本語の概要は準備中です。原文の説明を表示しています。