778 件 ・ 関連度順
概要と使いどころ
Render a deterministic text-only video ad from approved copy, font, colors, timing and CTA. Use when a brand needs an animated message without product photography or a creator.
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。
Assemble the FREE steps of the product-hypermotion + kinetic-typography video format — dice ONE Seedance 2.0 hypermotion clip into 5-6 segments and intercut them with PIL kinetic-typography spec/CTA cards (italic skew, 1.08x outline echo, 3D extrusion, slam-with-shake, inversion flash) plus a real-logo PIL end card (base64-decoded from the brand SVG), center-crop 1:1 to 9:16, and explicit-map mux a music bed. Deterministic, FREE (PIL + FFmpeg), no paid calls, the real logo and spec typography stay pixel-crisp. The paid steps (the ONE Seedance i2v, the music) are separate capabilities; the recipe orchestrates them. Use for the product-hypermotion format.
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。
Render a 'photo-grid promo card' video from a config — a real-DOM card with a FIXED header/footer and a CONTINUOUSLY SCROLLING 2-row grid of MIXED tiles (video clips, product/lifestyle stills, big-serif %-OFF, dark promo-code or CTA) + feature chips, frame-stepped via Playwright with real-time <video> playback and encoded with FFmpeg — deterministic assembly, FREE (the clips + music come from create-video-fal + create-music-elevenlabs), text stays pixel-crisp. Use for the photo-grid-promo-card format.
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。
Assemble an Apple Notes list video ad from a note + end-card JSON — a frame-accurate fake iPhone screen recording of a short list being typed into Apple Notes (character by character, key pops, blinking caret, the note scrolling up as it fills) crossfaded into a checklist end card (the note's picks as ticked rows, real product photos, logo, CTA, in the brand's colours and fonts), with an optional music bed. FREE assembly (Playwright + ffmpeg); the recipe supplies the per-brand note + end card and gates the paid music call to its own capability. The Apple Notes sibling of render-imessage-chat and render-chatgpt-chat. Use for the apple-notes format.
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。
Assemble a wordless macro-tabletop food-product sizzle ad from a config — normalize fps and SAR across ~4 photorealistic macro clips (hands tearing, flat lay, bite, box hero), concat them, apply a global anti-AI grain pass (eq plus hqdn3d plus noise), composite the audio (a non-diegetic instrumental music bed plus a couple of short diegetic SFX like a snap and a tear placed at measured cue points, loudnorm), composite a STATIC end card entirely in PIL (real logo PNG plus real product PNG plus a serif heritage headline plus a CTA — never AI-rendered text), and burn optional serif stat-callout pills at beats. This is the FREE deterministic assembly stage (normalized concat plus grain plus music and SFX mix plus PIL end card plus callouts); the macro keyframes, i2v clips, and music bed come from create-image-fal, create-video-fal, and create-music-elevenlabs. Use for the food-product-sizzle format.
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。
Decides how to preprocess plasma cfDNA sequencing data so the recoverable signal survives - library-prep-aware fragment expectations (dsDNA vs ssDNA/adaptase prep), UMI/duplex consensus with fgbio (ExtractUmisFromBam, GroupReadsByUmi --strategy paired for duplex, CallMolecularConsensusReads vs CallDuplexConsensusReads, FilterConsensusReads min-reads "total s1 s2"), the align->group->consensus->RE-align ordering, and the cfDNA dedup trap where naive coordinate dedup collapses nucleosome-coincident independent molecules. Covers when single-strand consensus suffices vs when duplex is mandatory, the singleton/sensitivity tax at low input, and reading the insert-size histogram as a pre-analytical QC instrument. Use when processing plasma cfDNA reads before fragmentomics, ctDNA mutation calling, or tumor-fraction estimation.
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。
Tracks ctDNA across serial liquid-biopsy timepoints for molecular residual disease (MRD) and treatment-response monitoring, treating MRD as a binary integrated detection call across the patient's full variant set (with a defined LoD95 and per-sample specificity) rather than a per-timepoint VAF threshold, and handling undetectable samples as left-censored at the per-sample limit of detection rather than true zeros. Covers tumor-informed bespoke vs tumor-naive design, landmark vs surveillance sampling, molecular-response definitions and their non-standardization, censoring-aware clearance kinetics, and the multiple-testing structure of repeated surveillance. Use when monitoring ctDNA during therapy, calling molecular relapse before imaging, or estimating clearance half-life from serial samples.
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。
Profiles a genome from raw reads BEFORE assembly with a k-mer spectrum (KMC or Jellyfish histogram), then models it with GenomeScope2 to estimate genome size, heterozygosity, repeat content, and ploidy, and Smudgeplot to infer ploidy from heterozygous k-mer pairs (diploid AB vs triploid AAB vs tetraploid AABB). Covers choosing k via Merqury best_k.sh, the k-mer-coverage vs sequencing-coverage confusion, reading het/repeat/contamination/organelle peaks, why noisy ONT must not be used for counting, and how the estimate becomes the NG50 denominator, the Flye -g value, the hifiasm --hom-cov/purge setting, and the 1.5-2x-too-big haplotig sanity check. Use when starting any de novo assembly, deciding whether short reads can work, estimating genome size for an unknown organism, diagnosing ploidy, or sanity-checking an assembly's size against expectation.
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。
Defines cell populations in flow and spectral cytometry through manual gates (rectangle, polygon, quadrant, boolean) and reproducible automated gating (openCyto gating templates, flowDensity data-driven thresholds, flowClust model-based gates), organized as a hierarchical GatingSet (flowWorkspace) and round-tripped with FlowJo via CytoML. Covers the canonical gate order (time -> debris -> singlets -> live -> lineage), FMO-vs-isotype boundary setting, gate-order dependence and recompute semantics, rare-event/MRD gating, and per-population statistics. Use when building a gating strategy, automating a manual FlowJo scheme across samples, choosing manual vs data-driven gates, or extracting population frequencies.
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。
Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.
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。
Estimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the baseline-LD model, Finucane 2018 cell-type prioritization, LDAK SumHer, HDL, HESS local heritability, BOLT-REML, GCTA-GREML, graphREML, and Popcorn cross-population genetic correlation. Use when computing total h2_SNP from summary stats, partitioning heritability across functional categories, prioritizing trait-relevant tissues or cell types from ENCODE/Roadmap chromatin marks, reconciling LDSC vs LDAK enrichment estimates, computing local heritability with HESS, estimating genetic correlation between traits, or producing publication-grade enrichment with calibrated sensitivity to model assumptions.
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。
Test-driven development for behaviour a unit test cannot reach, by writing the expectation against the running app before writing the code. Declare the consequence first, watch it fail, implement, watch it pass. Use when building a user-facing feature, when the user asks for TDD on UI or full-stack work, when a unit test cannot express the outcome that matters, or when you want a red-green loop that runs against the real app instead of mocks.
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。
Transcribe speech to text using Apple's Speech framework. Use when implementing live microphone transcription with AVAudioEngine, recognizing recorded audio files, handling speech and microphone authorization, choosing on-device vs server-backed SFSpeechRecognizer behavior, or adopting SpeechAnalyzer, SpeechTranscriber, DictationTranscriber, AssetInventory, and async result streams on iOS 26+.
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。
Analyze signal spectra in MATLAB using nonparametric and parametric estimators. Use when computing frequency content, PSD, power spectrum, spectral peaks, bandwidth, or streaming spectral analysis. Covers pspectrum, pwelch, periodogram, pmtm, pburg, pmusic, rootmusic, plomb, poctave, spectrumAnalyzer, dsp.SpectrumEstimator. TRIGGER: FFT, PSD, power spectrum, spectral analysis, frequency content, bandwidth measurement, spectral leakage, window selection, streaming spectrum, periodicity, resolve close frequencies, multitaper. DO NOT TRIGGER: filter design, spectrogram/time-frequency, audio features.
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。
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.
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。
TikTok Shop shipping setup — carrier selection, shipping templates, delivery expectations
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。
Audit and optimize e-commerce landing pages for conversion. CTA placement, trust signals, page structure, copy optimization, and A/B testing strategy for product pages, collection pages, and campaign landing pages.
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。
Generate a complete, deployable landing page from a brief. Produces a single self-contained HTML file with Tailwind CSS (via CDN), responsive design, dark mode, semantic HTML, and OG meta tags. Sections: hero with CTA, features, social proof, pricing (optional), FAQ, footer. Use when building a marketing page, product launch page, coming soon page, or any standalone landing page. Triggers: 'landing page', 'create a page', 'marketing page', 'launch page', 'coming soon page', 'one-page site'.
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。
When the user wants to set up, audit, or optimize analytics tracking (GA4, events, conversions). Also use when the user mentions "Google Analytics," "GA4," "event tracking," "conversions," "attribution model," "gtag," "data layer," "GA4 setup," "conversion tracking," "event setup," "User ID tracking," or "CTA attribution." For traffic insights, use traffic-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。
Deprecated compatibility entry for Call to Action construction. This component is now maintained in Bricks; install and use component-builder to build a new Call to Action.
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。
Reviews and migrates deprecated wildcard (*) values in Power Pages Web API fields site settings to least-privilege explicit Dataverse columns. Use whenever a user mentions Web API wildcard or select-all remediation, fields settings containing *, data-exposure review, wildcard deprecation readiness, or Web API failures after wildcard retirement. Applies to both traditional sites using HTML, CSS, JavaScript, Liquid, and downloaded YAML, and SPA sites using React, Vue, Angular, Astro, or TypeScript. The agent must inspect every source Web API call and consumer, report exact fixes for every wildcard, report every already-explicit configuration, apply approved edits, and verify no wildcard remains.
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 making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants. Also for revising one variant or resuming a partially completed batch. Not for a new commercial from a still image, ordinary single-clip grading, or automatic Cartesian combinations.
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 producing a video ad with Scenario from a product shot or brand assets: a mobile 9:16 or landscape 16:9 commercial, a TikTok, Reels, Shorts, YouTube, or CTV spot, or campaign creative needing a creative brief, storyboard, cinematic camera work, brand-faithful product footage, music and voiceover, captions, ad variants, budget planning, or platform delivery specs. Keywords: video ad, commercial, product video, advert, hook, CTA, end card, campaign, ad creative.
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。
为 Seedance 2.0（Higgsfield）生成三维CGI和渲染视频提示词。在用户想要三维渲染、CGI、皮克斯风格、Unreal Engine、逼真3D、计算机生成或数字渲染视频内容时使用。触发词：3D动画、CGI、渲染、Blender、Unreal Engine、octane render、光线追踪、体积、次表面散射、基于物理的渲染或任何3D/CG视频请求。即使用户只说"使其看起来像3D"或描述了渲染美学，也要使用。
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。