Showing papers on "Instrumentation (computer programming) published in 2026"
8 Jan 2026
TL;DR: The ASRF-III framework, a stability-oriented framework for adaptive systems, is archived for historical purposes, superseded by Minimal ASRF v1.0, and provides a comprehensive reference for reasoning about adaptive systems under entropy, uncertainty, and oscillation risk.
Abstract: ⚠️ Deprecated / Superseded ReleaseThis record has been superseded by:Minimal ASRF v1.0 (Stan Henry Jr.) — Stable Minimal Reference Implementation. https://doi.org/10.5281/zenodo.18227849 The newer release provides a compressed, operational framework intended for public use and citation. This record remains available for historical traceability only. This release archives the backbone architecture and operational methodology of ASRF-III (Adaptive Systems Resonance Framework), a stability-oriented framework for reasoning about adaptive systems under entropy, uncertainty, and oscillation risk. The archive includes core architectural specifications (dual reservoirs, staged refinement, fail-safe dominance), layered regulatory logic (Reader–Evaluator–Governor, finite-state control, hysteresis and deadbands), observer and instrumentation definitions (measurable variables, time-to-stability, stage timing, pivot metrics), operational tracing methods, live example traces, and a simulation roadmap. The framework emphasizes bounded claims, measurable signals, domain-specific adaptation, and reproducible comparative analysis rather than predictive or optimization guarantees. This release is intended as a frozen reference artifact for research, implementation, and methodological discussion.
13 Jan 2026
TL;DR: A multi-laboratory study reveals significant variability in ion species formation across different ESI-MS instrument vendors, laboratories, and even individual labs, emphasizing the need to consider platform-dependent ESI behavior for improved data reproducibility and comparability.
Abstract: Variation in electrospray (ESI) mass spectrometry (MS) instrument design and local ionization environments influences the formation of ion species, affecting analyte detection and quantitation. Here, we assessed ion species formation variability by analyzing a standardized internal retention time standard (IRTS) mixture across ten laboratories employing high-resolution ESI-MS instrumentation from four different instrument vendors (Agilent Technologies, ThermoFisher Scientific, Shimadzu Corporation, and Waters Corporation). Despite the use of standardized extraction and chromatographic protocols, significant differences in ion species formation were observed across vendors, among laboratories using the same vendor instruments, and even within individual labs. These findings highlight the critical need to consider platform-dependent ESI behavior when interpreting LC-MS small molecule data to improve reproducibility and comparability across studies.