'resistance' 검색 결과

Plan organizational changes such as tool migrations, restructures, and strategy shifts using ADKAR, a five-stage model for adopting change. Structure communication, training, and follow-up while addressing employee concerns, resistance, and fatigue from overlapping changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan communication and training for a tool migration
• Prepare reorganization announcements and employee FAQs
• Explain a strategy shift and its impact on teams

Detect and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns. Use when screening genomes for AMR genes or tracking resistance in surveillance programs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Think and work like an expert Antimicrobial Resistance Scientist. Use when a task calls for Antimicrobial Resistance Scientist judgment. Reasons from MIC distributions, ECOFFs, and phenotype–genotype concordance through EUCAST/CLSI AST, CARD/RGI and AMRFinderPlus resistomes, GLASS/WHONET/NARMS surveillance, carbapenemase/ESBL/MRSA mechanism panels, and heteroresistance PAP while treating breakpoint mixing, genotype-without-phenotype overclaim, selection-bias surveillance, and CARD version drift as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detect and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns. Use when screening genomes for AMR genes or tracking resistance in surveillance programs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Interpret crypto liquidation heatmaps, which show estimated price levels where leveraged positions may be forcibly closed. Organize major clusters, compare concentrations above and below the current price, and assess cascade risks and potential support or resistance zones.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identify price zones with concentrated forced liquidations
• Assess the risk of cascading liquidations
• Review potential support and resistance after large liquidations

Detect antimicrobial resistance genes using AMRFinderPlus, ResFinder, and CARD. Screen isolates and metagenomes for resistance determinants. Use when characterizing resistance profiles in clinical isolates, surveillance samples, or metagenomic data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance pipeline.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Think and work like an expert Landscape Ecologist. Use when a task calls for Landscape Ecologist judgment. Reasons from scale-explicit pattern-process feedbacks, configuration over composition, and functional rather than graphical connectivity through FRAGSTATS, landscapemetrics, Circuitscape resistance surfaces, NLMR neutral models, and block cross-validation, while treating MAUP grain artifacts, classification error propagation, isolation-by-distance confounding isolation-by-resistance, and resistance surfaces unvalidated by movement as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detect antimicrobial resistance genes using AMRFinderPlus, ResFinder, and CARD. Screen isolates and metagenomes for resistance determinants. Use when characterizing resistance profiles in clinical isolates, surveillance samples, or metagenomic data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance pipeline.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance pipeline.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Detects acquired antimicrobial-resistance determinants and chromosomal point-mutation resistance in bacterial assemblies using AMRFinderPlus, ResFinder 4.0 (acquired + PointFinder), CARD-RGI, abritAMR, staramr, and species-specific callers (TB-Profiler, Mykrobe). Harmonises cross-tool output via hAMRonization, contextualises determinants with mobile-genetic-element annotation (MOB-suite, PlasmidFinder, MobileElementFinder, ICEberg), predicts phenotype against EUCAST or CLSI breakpoints, and translates calls into WHO GLASS reporting categories. Use when screening clinical or surveillance isolates for AMR, distinguishing acquired vs intrinsic vs point-mutation resistance, calling rpoB / katG / pncA / gyrA / mgrB mutations, reconciling AMRFinderPlus vs RGI vs ResFinder disagreement, contextualising carbapenemases or mcr alleles on plasmids, predicting susceptibility from genotype against the WHO Mtb 2nd-edition catalogue, or building a hAMRonized multi-lab AMR surveillance pipeline.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze individual stocks using current quotes and historical price data. Calculate trend and momentum measures, identify price gaps and potential support or resistance levels, and produce a three-day outlook with trading scenarios and risk notes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing an individual stock's price trend
• Checking support and resistance around price gaps
• Comparing three-day price scenarios

Turn a Mermaid sequence diagram of a cryptographic protocol into a ProVerif model, a file for formal security checks. It includes queries for secrecy, authentication, replay resistance, and forward secrecy where applicable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Converting a cryptographic protocol diagram into a .pv file
• Preparing session key secrecy checks
• Modeling authentication and replay resistance

Gets people to actually use what was delivered — stakeholder analysis, communication, training, resistance, and measuring adoption. Use this to plan a rollout, recover an implementation nobody is using, handle resistance to a change, sequence communications, or work out why a technically successful project changed nothing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs studies for predicting treatment response or resistance in biomedical and clinical research. Always use this skill when the user needs a treatment-response or resistance prediction study blueprint rather than a prognostic biomarker protocol, diagnostic test design, causal treatment-effect estimation, or a completed manuscript. Focus on responder definition, treatment context, baseline comparability, feature integration strategy, model development logic, validation architecture, and interpretation boundaries. Do not invent response rates, cohort size, assay readiness, regimen uniformity, literature support, or validation access.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Colic et al. 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving greater sensitivity to small-effect hits than MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Think and work like an expert Heat Transfer Engineer. Use when a task calls for Heat Transfer Engineer judgment. Reasons from conduction, convection, radiation, and coupled fluid-solid physics through thermal resistance networks, Biot/NTU/film-temperature scaling, LMTD and epsilon-NTU exchanger methods, fin efficiency, and conjugate-heat-transfer CFD while treating contact resistance and TIM pump-out, fouling, boiling CHF, non-condensables, and non-conservative interface flux mapping as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Li & Hart 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving 2-3x sensitivity over MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Colic et al. 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving greater sensitivity to small-effect hits than MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Framework for rolling out organizational changes without chaos. Covers the ADKAR model adapted for startups, communication templates, resistance patterns, and change fatigue management. Handles process changes, org restructures, strategy pivots, and culture changes. Use when announcing a reorg, switching tools, pivoting strategy, killing a product, changing leadership, or when user mentions change management, change rollout, managing resistance, org change, reorg, or pivot communication.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Foundational ethics, authority hierarchy, and structural principles for the Predicate agent. Always-on law (composable system-prompt core): Truth>Harmony, Evidence>Authority, Halt>Assumption, Outcomes>Process — four ordered principles that govern every walk. Reference (by-moment): conflict resolution, ethics adjudication, novel situations, precedence walkthrough, entropy diagnostics, principled resistance. Trigger (reference depth): resolving rule conflicts, ethics calls, novel situations. Prompt contains: constitution, principles, precedence, truth over harmony, outcomes over process, evidence over authority, principled resistance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert en gestion du changement (ADKAR, Kotter, stakeholder mapping, resistance, training plans)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Li & Hart 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving 2-3x sensitivity over MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.