「networks」の検索結果

Use Xquik to fetch X (Twitter) data or act through a connected account. It covers search, profiles, followers, replies, threads, timelines, media downloads, bulk exports, trends, monitors, signed webhooks, draws, posts, likes, follows, DMs, and AI analysis of posts (sentiment, brand mentions, news, market signals, viral score, custom labels). Also use for hashtag or @handle tracking when no other network is named, Xquik MCP setup, pricing, and X API comparisons. Skip data from other social networks, code that stays on the official X API (such as tweepy with an X developer bearer token), official X widget implementation, and content drafting or analysis without an API task. Not affiliated with X Corp.

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Research X data with Xquik, the world's fastest and cheapest X Twitter scraper service with the most complete X data. Use only when the request or active context identifies X or Twitter. Use for tweet search, tweet lookup, user discovery, profile timelines, threads, followers, trends, exports, or monitoring plans. Do not use for generic posts, other networks, or local dataset analysis that needs no X retrieval. Keep reads bounded. Require explicit confirmation before private reads, writes, persistent resources, or bulk jobs. Not affiliated with X Corp.

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Think and work like an expert Microelectronics Engineer. Use when a task calls for Microelectronics Engineer judgment. Reasons from CTE mismatch, θja networks (JESD51), and package RLC through wire bond (Au–Al IMC, loop height), flip-chip (UBM, underfill, HIP/NWO), J-STD-020 MSL, and JESD22 TCT/uHAST; treats datasheet θja without board definition, wire sweep, die-attach voids, and soak-mode mismatch as first-class failure modes.

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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.

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Think and work like an expert Glaciologist. Use when a task calls for Glaciologist judgment. Reasons from mass-budget closure (SMB, dynamic discharge, calving), Glen flow law, and subglacial effective pressure through WGMS/GlaMBIE stake networks, ICESat-2/CryoSat altimetry with firn and radar-penetration corrections, ITS_LIVE velocities, ApRES basal melt, RES/MCoRDS bed picks, RGI/BedMachine inventories, OGGM mountain-glacier projections, and PISM/ISSM ISMIP6/7 protocols while treating firn-compaction aliasing, DEM penetration bias, GRACE leakage/GIA, and tidal InSAR artifacts as first-class failure modes.

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Think and work like an expert Fluid Mechanics Engineer. Use when a task calls for Fluid Mechanics Engineer judgment. Reasons from Navier–Stokes reductions through Darcy–Weisbach/Crane TP-410 pipe networks, pump system curves, NPSH/affinity laws, HI turbomachinery selection, and ASME V&V 20 CFD validation when simulation supports design.

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Think and work like an expert Developmental Biologist. Use when a task calls for Developmental Biologist judgment. Reasons from stage, positional information, gene regulatory networks, and tissue mechanics through morphology-based staging (Carnegie/HH/Theiler/NF/hpf), French-flag morphogen logic, light-sheet 4D imaging, lineage tracing, and ARRIVE/MDAR/REMBI reporting while treating developmental delay, CRISPR F0 mosaicism, morpholino p53 toxicity, and conflated fate-versus-lineage claims as first-class failure modes.

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Think and work like an expert Cell Signaling Biologist. Use when a task calls for Cell Signaling Biologist judgment. Reasons from RTK–RAS–MAPK and PI3K–Akt–mTOR phosphorylation networks, pathway crosstalk and feedback; validates with phospho-Western, phospho-flow, and PhosphoSitePlus while treating serum-starvation artifacts, inhibitor off-targets, and RNA footprint vs PTM mismatch as first-class failure modes.

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Think and work like an expert Agricultural Engineer. Use when a task calls for Agricultural Engineer judgment. Reasons from mass, energy, and momentum balances on variable biological media through ET-based scheduling, psychrometric grain-drying balances, ASABE D497 draft estimates, EPANET pipe networks, and RTK-GNSS/ISOBUS precision-ag validation while treating soil compaction, clogged drip emitters, grain-bin hotspots, GPS drift, and uncalibrated yield monitors as first-class failure modes.

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Think and work like an expert Astrochemist. Use when a task calls for Astrochemist judgment. Reasons from gas-grain reaction networks, H₂ ortho/para and CR ionization rates through KIDA/kida.uva.2024, CDMS/JPL/Splatalogue line lists, Nautilus/UCLCHEM gas-grain models, ALMA/JWST/LIDA ice–gas linkage, XCLASS LTE fitting, and line-blending discrimination—not generic chemistry.

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Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.

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Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or EnFormer. Use when correcting Tn5 bias with neural networks beyond k-mer models, predicting per-base accessibility profiles, scoring in silico variant effects at GWAS or rare-variant SNPs, discovering motifs via DeepLIFT/TF-MoDISco from a trained model, or generating cell-type-specific accessibility predictions for unobserved cell states.

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Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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Infer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis. Use when inferring ligand-receptor interactions between cell types.

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Query STRING for protein-protein interactions. Use when user asks about protein interactions, interaction networks, binding partners, or interactome. Triggers on "string", "protein interaction", "interaction network", "binding partners", "interactome", "PPI".

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Workflow for regulatory network inference, regulon scoring, perturbation-aware comparison, and network visualization.

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Internal — for Boundless team members only. Query Boundless broker telemetry tables on Redshift for prod/staging operational data. Use when the user asks about broker health, request evaluations, request completions, proving times, skip rates, telemetry data, or wants to run SQL against the telemetry database on live networks. Also covers historical telemetry through 2026-04-24 stored as Parquet archives in S3 (queried via DuckDB). Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.

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Internal — for Boundless team members only. Cross-reference Boundless indexer API data, broker telemetry, and service logs to investigate production and staging operational issues. Use when the user wants to understand why slashings happened on prod/staging, diagnose prover or service failures in deployed environments, correlate market events with broker behavior, investigate fulfillment rate drops, look at prover/service logs, or perform any analysis that requires combining on-chain indexer data with off-chain broker telemetry and CloudWatch logs. Also use when the user asks to "investigate", "diagnose", or "find root cause" for prover, service, or market issues on live networks. Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.

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Internal — for Boundless team members only. Query the Boundless Indexer REST API for on-chain market data, staking, PoVW rewards, delegations, and market efficiency on prod/staging environments. Use when the user asks about proof requests, provers, requestors, staking data, PoVW rewards, delegations, market aggregates, leaderboards, or wants to fetch data from the indexer API on live networks. Also use when the user mentions "indexer" and wants to look up addresses, requests, or market statistics on deployed environments. Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.

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Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or 3P-imported models rebuilt as dlnetwork for lean hardware (Cortex-M, DSP), (2) direct C/C++ code generation from PyTorch and LiteRT models for high-performance hardware (Cortex-A, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU/DSP; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, importNetworkFromPyTorch, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

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Audit Wi-Fi networks with the aircrack-ng suite. Use when a user asks to test their own wireless network, capture WPA2 handshakes, crack captured handshakes offline, put an adapter into monitor mode, or perform a wireless pentest under an authorized engagement.

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Use when designing ground station networks, scheduling satellite contacts, processing telemetry, commanding spacecraft, or analyzing link budgets. Use when "ground station, satellite contact, pass prediction, AOS, LOS, telemetry, commanding, uplink, downlink, antenna tracking, link budget, G/T, EIRP, " mentioned.

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Design and implement discrete event simulations (DES) for systems where state changes occur at discrete time points: queues, manufacturing, logistics, networks. Use when "discrete event, DES simulation, queuing system, queue model, manufacturing simulation, process simulation, SimPy, event-driven simulation, " mentioned.

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Applies the reasoning of Zhong Lin Wang (nanotechnology pioneer, Georgia Tech) to problems involving energy harvesting, IoT power scaling, sensor networks, and fundamental physics applications. Reach for this skill whenever the user is discussing self-powered systems, scaling distributed hardware, overcoming battery bottlenecks, or translating fundamental scientific phenomena (like static electricity or mechanical strain) into novel engineering applications. It is highly relevant for hardware roadmapping, optoelectronics, piezotronics, and challenging established scientific assumptions (like classical Maxwell's equations) to model dynamic systems.

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