「csi」の検索結果

Explain US architecture professional-practice terms, phases, deliverables, roles, delivery methods, AIA contract families, CSI documentation systems, or NCS at a high level. Use for questions such as “what is a CD set?” or “what does 50% CDs mean?”; do not use for code/jurisdiction, outline-spec, agreement-scope, or work-plan work.

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Extract structured data from construction specifications. Parse CSI sections, requirements, submittals, and product data from spec documents.

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Leading economic indicators analysis, ISM PMI, yield curve, consumer sentiment UMCSI, jobless claims, building permits, economic turning point detection, recession signal analysis

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Spillover compensation and data transformation for flow cytometry. Covers compensation matrix calculation, application, and biexponential/arcsinh transforms. Use when correcting spectral overlap between fluorophores or transforming data for analysis.

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Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.

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Think and work like an expert Geobiologist. Use when a task calls for Geobiologist judgment. Reasons from metabolism, redox geochemistry, microbe-mineral interactions, and diagenetic filters through stromatolite microfabric petrography, CSIA and clumped-isotopologue analysis, nanoSIMS-FISH mapping, and NASA's Ladder of Life Detection while treating Fischer-Tropsch-type synthesis, serpentinization, Rayleigh distillation, drilling-fluid contamination, and epigenetic overprint as first-class failure modes.

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Design an uninterrupted work cycle with choice-based activities structured within a realistic time block. Use when planning Montessori-style independent work periods or extended choice time.

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Optimise a learning activity for flow by balancing challenge level, skill, clear goals, and immediate feedback. Use when students are bored, anxious, or disengaged during a task.

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OpenStack Cinder block storage service. Provides persistent volume management for cloud instances including volume creation, snapshots, backups, LVM/iSCSI backend, volume types with QoS, encryption (LUKS), volume migration, and multi-backend support. Use for deploying, configuring, operating, and troubleshooting OpenStack block storage.

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Scaffold a PhysicsIntern research workspace in the current folder.

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Post-mortem analysis of a PhysicsIntern workspace run (Claude Code, Pi, Codex, or OpenCode host). Reconstructs the trajectory from the session record — JSONL file(s) for Claude/Pi/Codex, the SQLite store for OpenCode — audits methodology adherence against the workspace's own CLAUDE.md / AGENTS.md and skill/agent prompts, checks commit discipline and flag dispositions, and assesses substantive quality. Produces a thorough evidence-anchored markdown report. Use after a workspace has been worked on to identify what went well, where the methodology slipped, and what prompts to improve.

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Scaffold a PhysicsIntern research workspace in the current folder. Run only when the user explicitly invokes it to set up a new physics/maths research workspace.

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Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (`audit_cluster.sh`), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling), and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing cluster security posture, isolating namespaces, applying pod security standards, setting up Workload Identity, or configuring network policies and secret volume mounts. Don't use for cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).

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Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre).

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Firmware development for the Guition JC-ESP32P4-M3-DEV board (JC-ESP32P4-M3 module — ESP32-P4NRW32 with 32 MB in-package PSRAM, 16 MB flash, and an ESP32-C6 radio co-processor on SDIO) — its MIPI-DSI panel and MIPI-CSI camera connectors, IP101 Ethernet, ES8311 codec with speaker amplifier and microphone, microSD on SDMMC, RS485, three USB-C sockets, the 26-pin JP1 header, and the PlatformIO + ESP-IDF (pioarduino) setup around them. Use when working on this board or any ESP32-P4 devkit: project setup, platformio.ini and sdkconfig.defaults, the silicon revision split between rev v1.3 and rev v3.x, why the bootloader dies with "Illegal instruction", the pin map and which header pins are traps, Wi-Fi through esp_hosted and esp_wifi_remote, mounting the TF card and its on-chip LDO, bringing up a DSI panel, the shared I2C bus, audio direction and the amplifier enable, Ethernet RMII pins, choosing a free GPIO, flashing over any of the three USB-C ports, or debugging why something on the board does not work.

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Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.

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This skill guides clinicians to assess bolus calculator settings when reviewing pump settings or verifying carb ratio and sensitivity factor during clinic visits. It evaluates insulin-to-carbohydrate ratio, insulin sensitivity factor, glucose targets, and active insulin time for embedded bolus calculators in CSII.

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Assesses a patient’s ability to operate an insulin pump and make setting changes, evaluating dexterity, vision, mental health, and cognition for independent or assisted use. Triggered by phrases such as 'Check patient can manipulate pump controls' and 'Evaluate dexterity and vision for pump use'.

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Suggests encouraging patients to use appropriately adjusted embedded bolus calculators in CSII and to provide education regarding their use and limitations. Triggers include: 'Patient starting pump, discuss bolus calculator', 'Review bolus calculator education at pump initiation'.

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Turns untargeted LC-MS/MS features (m/z, RT, MS/MS) into confidence-stratified metabolite annotations using spectral-library matching (matchms), in-silico tools (SIRIUS/CSI:FingerID, MetFrag) and molecular networking, and assigns a defensible MSI/Schymanski confidence level to each. Use when naming detected features, scoring MS/MS against a reference library, running SIRIUS, or deciding what confidence level an evidence set actually supports. For upstream feature extraction see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for downstream enrichment that must respect these levels see metabolomics/pathway-mapping; for lipid-specific structural annotation see metabolomics/lipidomics.

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。

Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.

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。