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Sunbird AI Rain Sensor Dataset: acoustic recordings for rain intensity classification, Kampala, Uganda

Hand-related expressions in Jordanian Arabic

Hand-crafted vibration features from five accelerated-life (run-to-fracture) tests of cracked 40Cr rotor shafts (Ø10 mm, 1000 r/min, fluctuating radial load 170–350 N, 12.8 kHz sampling). Each CSV has no header and 36 feature columns (3 channels × 12 features: vertical displacement, lateral displacement, axial acceleration). One row = one 1-s segment; 15 consecutive rows = one 15-s acquisition window; rows run in time order to fracture. R1/R3/R5 (shafts 10/40/60) are the training records and R2/R4 (shafts 20/50) the test records; R2 and R4 correspond to cracked rotors 4 and 5 in Khan et al., Measurement 239 (2025) 115433. These are the model inputs used in that paper and in the MF-GRU reproduction study. See README.txt for the file format, processing, labels and a note on the training records.

Wildfires worldwide are increasing in severity due to anthropogenic change. Aside from their direct consequences, enormous smoke plumes can influence ecosystems far beyond a wildfire’s original range. Although wildfire smoke has been shown to affect animal physiology and movement, its effects on communication in birds have only been tested in a handful of localized studies at small spatial scales. Thus, its broad impacts on large-scale patterns of avian communication are relatively unknown. Here, we leverage an extensive dataset from BirdWeather, a new distributed network of automated bioacoustic monitors, to examine how large smoke events from the 2023 Canadian wildfires affect bird vocalizations across the northeastern United States. We combined and analyzed more than 579,000 bird vocalizations with measurements of local particle pollution (PM2.5) produced by the Canadian wildfires to the north and northwest during the month of June 2023. Increased smoke pollution significantly altered the dynamics of bird vocalizations across the whole northeastern United States, particularly affecting the dawn chorus. For diurnal species, vocal activity was reduced during early morning hours, and the onset of daily first vocalizations was significantly delayed. During unhealthy air-quality conditions, daily first vocalizations occurred approximately 40 minutes later, on average, compared to low-smoke conditions. Conversely, nocturnal species increased vocal activity during early morning hours under conditions of high smoke pollution, although this did not significantly affect the timing of their final vocalizations. Our results reveal that wildfire smoke can widely restructure community-level patterns of avian communication across broad landscapes. We demonstrate how increasingly severe wildfires can indirectly influence ecologically important behaviors in natural populations and how such phenomena can be studied using emerging advances in citizen science infrastructure and large-scale bioacoustic monitoring.

This dataset is the R replication package for the article "Targeting performance of Bangladesh's social safety net against asset-based and multidimensional poverty: eligibility-adjusted evidence from the 2025 Multiple Indicator Cluster Survey". The study compares receipt of Bangladesh's core social safety-net programmes with the MICS asset (wealth) index and a ten-indicator Alkire-Foster multidimensional poverty index (MPI) for 61,207 households, using design-based inference, headcount-matched comparisons, eligibility-adjusted programme analysis, rank-based metrics (AUC, concentration indices), counterfactual allocations, district-level decomposition and survey-weighted logistic models with average marginal effects. The package contains: (1) a master script (run_all.R) and numbered R scripts (code/) that read the official MICS7 SPSS files, construct all variables, and reproduce every table, figure and number in the manuscript and Supplementary Appendix; (2) the authors' aggregate result tables (CSV) and figures (PNG) in expected_output/, which the code compares against automatically; (3) a README mapping each manuscript and appendix table/figure to its output file. The MICS7 Bangladesh 2025 microdata are NOT included, because the MICS terms of use prohibit redistribution. They are available free of charge to registered users from UNICEF at https://mics.unicef.org/surveys (Bangladesh MICS 2025 SPSS Datasets: hh.sav, hl.sav, wm.sav, ch.sav). Only aggregate statistics are shared here.

This deposit accompanies the manuscript "What do industrial accident databases actually predict? Documentation depth, curation policy, and the limits of barrier-based machine learning in 46,394 process-industry accidents." CONTENTS - data/aria_features.csv - derived analysis table, 64,800 rows x 158 columns (147 predictors + 4 identifiers + 7 outcome/derived fields). UTF-8, comma-separated. - code/ - the complete Python analysis pipeline in execution order (feature engineering, logistic regression with barrier-block ablation, interaction tests, three-way temporal split with Platt calibration and permutation importance, France-only robustness, gradient boosting with SHAP, figures). - results/ - machine-readable JSON outputs of the reported analyses. - README.md - full provenance, column dictionary and reproduction instructions. SOURCE DATA AND ATTRIBUTION The underlying records originate from the ARIA database (Analyse, Recherche et Information sur les Accidents), maintained by BARPI, French Ministry of Ecological Transition, published as open data on data.gouv.fr (full export dated 7 July 2026; 64,800 records). Reuse of the ARIA records is permitted for non-commercial purposes with attribution to BARPI. Any reuse of this derived table must credit BARPI. ANALYSIS POPULATION AND DESIGN 46,394 process-industry (classified-installation, Seveso-type) records with valid dates. Strictly temporal validation: training up to 2015 (n = 32,937), calibration 2016-2018 (n = 3,687), held-out test from 2019 (n = 9,770). Binary outcomes: any human consequence (test base rate 12.43%) and major human consequence (test base rate 1.55%). HEADLINE FINDINGS REPRODUCED (1) Documentation drift: equipment documented in 30.7% of records before 2000 versus 84.7% after 2021, with the equipment-severity association reversing sign across periods. (2) Safety-barrier features add only +0.0060 ROC-AUC (any human consequence) and +0.0030 (major). (3) Major-consequence ROC-AUC falls from 0.8201 on the full sample to 0.5916 on French domestic events alone, indicating a curation artefact. (4) Class weighting inflates predicted probabilities roughly fourfold (Brier 0.2446 uncalibrated versus 0.1081 after Platt scaling). LICENCE Data: CC BY 4.0, subject to the upstream ARIA terms (attribution to BARPI required). Code: MIT.

This repository contains source code relevant of the manuscript: Inter-regional recurrence dynamics of brain reveal the transition toward the preictal state and enable seizure prediction. Azam Ghanaei and Abbas Erfanian Summary: This study introduces a novel approach for seizure prediction in freely moving rats by utilizing nonlinear dynamical analysis of neural signals recorded from the right hippocampus (CA1), left anterior thalamic nuclei (ANT), and motor cortex (M1). The dynamic interactions among these three brain regions during epileptic activity are characterized using Cross-Recurrence Plot (CRP) analysis, a bivariate extension of the Recurrence Plot (RP) method that enables the analysis of dynamic interactions between two systems. The CRPs constructed from artifact-free intracranial electroencephalographic (iEEG) signals are subsequently used as inputs to a three-dimensional convolutional neural network (3D-CNN) for seizure prediction. The performance is compared with that of a 3D-CNN using RP-based features as input. The results indicate that CRP-based features are more effective in detecting the transition from the interictal to the preictal state in a real-time setting and in predicting seizure onset. For more details and code usage, please refer to the code description file.

The first part of Under the Broken Halo set out the SEIR cognitive loop (Sensory experience, Experience encoding, Interpretation, Response) as a single architecture beneath antisocial behavior, from the retaliating child to the genocidal ruler. It defined Loop Lock as the point at which a recursive system can no longer update its model of the world, and it argued that the same structural failure operates at every scale of power, with only the reach of the Response phase changing. That argument was built on a small number of anchoring cases. The second part of the work turns from architecture to evidence. It assembles the documented life histories of forty-four individuals drawn from more than two thousand years of recorded history and cross-references each one against the four stages of the loop, in the manner of a clinical case series. The forty-four cases are organized into seven clinical groups. The first group covers people whose interpretive hardware was physically damaged, through head injury, epilepsy, infection, or psychosis. The second covers developmental accumulation, where repeated childhood wounds loaded the Experience Encoding archive with threat. The third covers grievance loops in which a single perceived injustice was rehearsed until it became the organizing principle of a life. The fourth covers rulers whose personal locks were scaled through the machinery of the state. The fifth covers functionaries and administrators of atrocity whose empathy was dampened through repetition and ideology. The sixth covers assassins and spoilers who experienced peace itself as an existential threat. The seventh and final group covers individuals whose loops visibly unlocked, and whose reversal supplies the strongest form of support for the model: if a locked loop can be opened by corrective Sensory Experience, then the lock was a process and not an essence. Each case is coded on five markers: Sensory load, Encoding evidence, Interpretive distortion, Response escalation, and Lock indicators. Each is also graded for the strength of its documentation, so that the reader can separate cases resting on court records, autopsies, and first-person testimony from cases resting on later biography. The crossreferencing produces a consistent pattern. Across centuries, cultures, and scales of power, the same sequence recurs: an early or acute wound, an interpretive shift toward threat, a retaliatory justification phrased in the grammar of "they hurt me first," an escalating Response that reshapes the environment, and a closing of the system against corrective input. The paper argues that this recurrence is the clinical signature of Loop Lock and that it is visible in the historical record wherever the record is detailed enough to show it.

This paper introduces a grand-unified criminological paradigm by applying the SEIR (Sensory experience, Experience encoding, Interpretation, Response) cognitive loop model to the structural development of antisocial behavior, sociopathy, and macro-scale atrocities. Moving beyond traditional sociological and punitive frameworks, this study redefines criminal behavior as a universal vulnerability rooted in recursive loop deficiencies and error accumulation. Through a progressive spectrum of cognitive distortion, we demonstrate how minor baseline miscalibrations in early childhood—exemplified by the retaliatory defense mechanism "I don't care if he hurts, he hurt me first"—can compound exponentially over time. As these corrupted loops multiply, they fundamentally disrupt the mind’s internal matching mechanism, decoupling current sensory inputs from historical empathy templates. This progressive empathy dampening locks the system into a rigid, self-preserving, and predatory schema. By analyzing this structural lock-in across a continuous scale of power, we argue that an identical algorithmic failure underlies the solitary serial killer and the genocidal dictator, such as Adolf Hitler, whose critical loop corruption was cemented long before attaining leadership. The framework is tested against a broad set of documented cases: Phineas Gage and Charles Whitman at the neurological level; the Adverse Childhood Experiences and Dunedin cohorts at the developmental level; Reserve Police Battalion 101, the Milgram obedience studies, and the trial of Adolf Eichmann at the level of ordinary perpetrators; and Northern Ireland, Rwanda, and post-apartheid South Africa at the level of inherited collective trauma. Challenge cases—including Ted Bundy, Pol Pot, and the neuroscientist James Fallon—are examined to define the model’s boundaries. To resolve this systemic crisis, this paper details a conceptual medical intervention in three phases. Molecular Neuro-Corrective Engram Ablation combines dual-vector chemogenetic tagging with Magnetic Resonance-guided Focused Ultrasound (MRgFUS) to isolate, map, and eliminate the anomalous neural pathways responsible for Loop Lock. A third phase, Symmetry-Location Neural Cartography, extends the protocol beyond criminality: it maps whole-brain patterns across many patients, identifies pathological signatures by their shared location and hemispheric symmetry, and proposes to scan for and eliminate those pathways to maintain an optimal brain free of mental illness. Finally, we balance this hypothesis by examining its profound human rights implications—informed by the history of twentieth-century psychosurgery—and establish the ethical, legal, and systemic guardrails necessary to govern a world where human consciousness and behavioral patterns can be physically restructured.

These supplemental materials accompany the article "Sun Protection Behavior Patterns Among Sun-Exposed U.S. Adults: A Cross-Sectional Analysis of the National Health Interview Survey," accepted for publication in the Journal of the American Academy of Dermatology. The materials provide additional methodological information and supporting analyses for the study of sun-protection behaviors among U.S. adults using National Health Interview Survey data from 2000, 2005, 2010, and 2015.