Software and derived tables for partitioning every record of the BOLD public data package into three provenance states: imported from INSDC, native to BOLD but deposited into INSDC, and exclusive to BOLD. For the median taxonomic class, 79% of BOLD records are also held by INSDC. Includes the audit that adjudicates the provenance criterion, and a null simulation for testing associations between ratios that share a denominator.
F. Patti· Zenodo (CERN European Organi...· 0 citations
This second section of the study addresses the design and fabrication of the equipment developed for the preparation and shaping of rocket propellant. Two primary pieces of equipment were developed within the scope of the study: a Temperature-Controlled Fryer and a Propellant Shaping Stand. The Temperature-Controlled Fryer was designed to maintain the temperature of the container in which the rocket propellant is prepared at the desired value through a microcontroller (MCU – PIC). The Propellant Shaping Stand is used to shape the prepared propellant into the desired form. These pieces of equipment were developed as a result of extensive testing and design studies and also allow different design approaches to be implemented. The study additionally addresses the importance of indirect and controlled heating and explains the fundamental operating principles of the equipment employed. By presenting the design drawings, fabrication stages, electronic circuits, and software as an integrated part of the study, the design and manufacturing processes of the developed systems are examined.
ercan koçlar· Zenodo (CERN European Organi...· 0 citations
This second section of the study addresses the design and fabrication of the equipment developed for the preparation and shaping of rocket propellant. Two primary pieces of equipment were developed within the scope of the study: a Temperature-Controlled Fryer and a Propellant Shaping Stand. The Temperature-Controlled Fryer was designed to maintain the temperature of the container in which the rocket propellant is prepared at the desired value through a microcontroller (MCU – PIC). The Propellant Shaping Stand is used to shape the prepared propellant into the desired form. These pieces of equipment were developed as a result of extensive testing and design studies and also allow different design approaches to be implemented. The study additionally addresses the importance of indirect and controlled heating and explains the fundamental operating principles of the equipment employed. By presenting the design drawings, fabrication stages, electronic circuits, and software as an integrated part of the study, the design and manufacturing processes of the developed systems are examined.
ercan koçlar· Zenodo (CERN European Organi...· 0 citations
This reproducibility-focused software archive provides the Residual-on-Inertia Curve–Event Transformer (RICE-Former) materials used in the manuscript RICE-Former: A Residual-on-Inertia Curve–Event Transformer for Event-Aware 1–4 h Glucose Trajectory and Glycemic Event Forecasting. The repository supports independent audit of the study's four connected designs: (1) typed event marks that retain each meal, bolus, correction, and basal record; (2) wall-clock lag encoding relative to the prediction origin; (3) a residual-on-inertia connection that generates a 48-point 1–4 h trajectory over a persistence reference; and (4) a curve–event dual-branch decoder that produces the trajectory and 16 event–horizon scores from shared memory. Included materials RICE-Former method code: marked-event adapters, shared encoder, residual-on-inertia curve generation, and dual-branch event queries (CEQT is the retained engineering codename) Locked protocol and splits: prediction horizons, event thresholds, leakage checks, and the frozen AZT1D participant allocation Evaluation and baseline code for the staged experiment pipeline Privacy-preserving aggregate result tables for AZT1D, OhioT1DM, and DiaTrend curve, event, ablation, slice, and mechanism summaries Aggregate analysis tables for subject-level metrics and paired statistical tests Manuscript figures used in the paper, including the illustrative trajectory panels Documentation for data access, reproducibility, and GitHub–Zenodo release steps Repository layout src/ceqt/: model, data adapters, training, evaluation, baselines, and staged experiment code results/tables/: locked protocol, split identifiers, aggregate performance tables, and leakage-test report results/analysis/: aggregate subject-level metrics and paired tests results/figures/: manuscript figures scripts/: subject-level aggregate analysis exports docs/: data access, reproducibility, and release instructions Install and verify conda env create -f environment.yml conda activate rice-former export PYTHONPATH="$PWD/src" Obtain AZT1D, OhioT1DM, and DiaTrend from their original providers, arrange them as described in docs/data-access.md, and run selected stages with python -m ceqt.phases.run --from P0 --to P9. Data and privacy boundary The datasets analyzed in the study are available from their original sources: AZT1D (Mendeley Data, 10.17632/gk9m674wcx.1), OhioT1DM (Marling and Bunescu, 2020), and DiaTrend (Synapse, 10.7303/syn38187184). This deposit archives method and evaluation code, locked protocol files, aggregate result tables, analysis tables, and manuscript figures. Raw CGM records, participant event logs, the numeric extract behind the illustrative trajectory figure, credentials, trained weights, and caches are not redistributed. Details are provided in docs/data-access.md. Citation Please cite this software archive as: Liu Q, Yang M, Wang Z, Wang S, An X, Lu S, Yang Q, Liu M, Wu Z, Huang D. RICE-Former: a curve–event Transformer. Zenodo. https://doi.org/10.5281/zenodo.22171786 Citation metadata are also provided in CITATION.cff. Please cite the accompanying manuscript when referring to the scientific findings. Software repository: https://github.com/modalfuse/rice-former
Qiang Liu, Ming Yang, Zijiaqi Wang et al.· Zenodo (CERN European Organi...· 0 citations
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This dataset contains the 6-month Standardized Precipitation Index (SPI-6) monthly time series for all 331 Divisional Secretariat (DS) divisions of Sri Lanka, spanning 1981 to 2024. SPI-6 values were computed using the SPI_SL_6.exe software, developed in line with World Meteorological Organization (WMO) recommendations, from monthly precipitation data interpolated across the 331 DS-divisions via Kriging from 62 meteorological stations operated by the Department of Meteorology, Sri Lanka. The dataset supports the manuscript "SPI-Based Spatiotemporal Drought Frequency and Trends across the Divisional Secretariat Divisions in Sri Lanka" (Pramudi et al., submitted to Natural Hazards and Earth System Sciences, manuscript ID egusphere-2026-5234), which uses these SPI-6 values to derive drought frequency across five severity categories and to assess long-term monotonic trends at the DS-division scale using the Mann–Kendall test and Sen's slope estimator.
D.G.L. Pramudi, U. T. G. Perera, F. Ruzaik et al.· Zenodo (CERN European Organi...· 0 citations
This release contains the versioned software, frozen experiment records, automated tests, publication figures, and bilingual manuscript sources associated with an identifiability-aware method for selecting shared finite-memory models from sparse grouped observations. The method fits candidate positive-rate realizations with rates shared across independent specimens or material groups and unit-specific amplitudes and offsets. A candidate order is retained only when information gain, held-unit early-to-late prediction, foldwise log-rate stability, and adjacent-rate resolution support the same interpretation. When these criteria disagree, the model order is reported as unresolved. The archive corresponds to GitHub commit 13001874f788f9de9b49632961166d3713561f7b. It includes source code, 151 automated tests, frozen machine-readable results, experiment drivers, vector figures, and English and Chinese AMM manuscript sources. Third-party public datasets are not redistributed. Persistent source identifiers, frozen SHA-256 digests, and a verified downloader are included so that the public inputs can be retrieved from their authoritative repositories. The software is released under the MIT License. Dataset licenses and attribution requirements remain those of the original data providers.
Haitao Duan, Ning Hu, Shuqun Li et al.· Zenodo (CERN European Organi...· 0 citations
The Machine with Two Levers is a standalone WidiVision exploration of Expanded Halving and Doubling (EHD). A museum-story Vignette introduces a machine with two principal motions—MEDIATE and DUPLICATE—and a small REMEMBER tray. The following Illumination reorganizes addition, subtraction, multiplication, and division as different journeys through a common architecture of descent, ascent, parity memory, comparison, selection, and reconstruction. The purpose is conceptual rather than computational speed. The publication does not claim novelty for the classical halving-and-doubling methods used in multiplication and division. Its contribution is a unified WidiVision reading that makes relationships among the four basic operations visible to a general reader. Multiplication and division are closed within the system by reusing EHD addition and subtraction as nested journeys rather than silently importing the ordinary operations. The deposit includes Computational Exploration EHD.1 — The Two-Lever Laboratory, a self-contained offline browser instrument. Readers may enter their own numbers, advance through structural events one step at a time, inspect the memory record, and reconstruct results for a single number, addition, subtraction, multiplication, and division. Bill Widi conceived EHD and directed its development as a WidiVision exploration. ChatGPT (OpenAI) assisted with formalization, drafting, software implementation and testing, and editorial refinement. Bill Widi reviewed the work and takes responsibility for its final form.
Bill Widi· Zenodo (CERN European Organi...· 0 citations
The aim of this study is to determine the levels of organizational deviance behaviors among employees in the banking sector, to identify the sub-dimensions of organizational deviance, and to examine whether these behaviors differ according to employees’ demographic characteristics. The population of the study consists of employees working in public and private banks operating in the city center and districts of Konya. Within the scope of the sample determined based on a 95% confidence level and a 5% margin of error, data were collected from 470 bank employees using a survey method. To measure organizational deviance behaviors, the “Workplace Deviance Scale” developed by Bennett and Robinson (2000) and adapted into Turkish was utilized. The collected data were analyzed using the SPSS 22 statistical software package; descriptive statistics, factor analysis, reliability analysis, t-test, ANOVA, Kruskal–Wallis, and correlation analyses were employed. The findings indicate that organizational deviance behaviors are more strongly associated with organizational processes and work environment–related factors rather than individual demographic characteristics. By examining organizational deviance behaviors within the context of the banking sector, this study contributes to the literature and provides important implications for managers regarding the evaluation of employee behaviors within the framework of preventive and developmental human resource policies.
Fatih İbrahim Kurşunmaden· Selcuk Universitesi Sosyal B...· 0 citations
This record contains the corrected deterministic implementation freeze for HLV-R-MECH-001. The controlling scientific protocol is: Krūger, M. (2026). HLV-R-MECH-001: Prospective Triangle-Matched Mechanism Test of the Surviving Degree-Preserving Rewire Spectral Residual — Pre-Execution Protocol Freeze v0.1.0. Zenodo. DOI: 10.5281/zenodo.22166283 The public predecessor implementation is: Krūger, M. (2026). HLV-R-MECH-001: Deterministic One-Click Engine for Triangle-Matched Rewire Mechanism Testing — Implementation Freeze v0.1.0 [Computer software]. Zenodo. DOI: 10.5281/zenodo.22166434 Version v0.1.1 corrects only the numerical-runtime bootstrap of the One-Click Colab launcher. The first locked execution under v0.1.0 terminated before any scientific evaluation because the assigned Google Colab runtime exposed: NumPy 2.1.3 SciPy 1.16.3 while the frozen scientific implementation requires: NumPy 2.3.5 SciPy 1.17.0. The resulting machine state was: RMECH001_INCONCLUSIVE_NUMERICAL with spectral_computation_started = false. Therefore the stopped execution did not evaluate the confirmatory R_DEG or R_TRI spectra, did not compute target QSPEC or RRESP scores, and did not produce a scientific HLV-R-MECH-001 mechanism verdict. The scientific engine itself has not been changed. The v0.1.1 launcher contains the exact byte-identical scientific engine used in public implementation freeze v0.1.0. Frozen scientific engine SHA-256: 317df650991120f686768ffc07d12f044f58e38ce8f2c47c083901bf1d7a8a14 The corrected launcher now performs the following runtime bootstrap before starting the unchanged scientific engine: 1. inspect the assigned host numerical environment; 2. if the host already provides exactly NumPy 2.3.5 and SciPy 1.17.0, use that environment directly; 3. otherwise create an isolated Python virtual environment; 4. install exact binary versions: NumPy 2.3.5 SciPy 1.17.0; 5. verify the installed versions explicitly; 6. verify the embedded scientific-engine SHA-256; 7. only after these checks execute the unchanged frozen HLV-R-MECH-001 scientific engine. The correction occurs entirely outside the scientific engine. No scientific rule has been modified. In particular, v0.1.1 does not change: - the DG-001 target; - the target graph identity; - the R_DEG control family; - the R_TRI control family; - confirmatory seed streams; - candidate ordering; - accepted-swap counts; - proposal caps; - structural admission rules; - the 40–45% edge-replacement-depth requirement; - the 31-control family size; - exact degree-sequence preservation; - exact global triangle preservation T = 6960 in R_TRI; - the between-family rewiring-depth gate; - QSPEC; - RRESP; - spectral bands; - leave-one-out scoring; - the robust-margin threshold; - numerical scientific hard gates; - or scientific machine-verdict logic. The frozen mechanism design therefore remains identical to the controlling protocol DOI 10.5281/zenodo.22166283. The two confirmatory control families remain: R_DEG: fresh degree-preserving structural rewires of the fixed DG-001 target graph. R_TRI: fresh rewires preserving both the exact labelled target degree sequence and the exact global triangle count T = 6960. Each family requires 31 accepted controls. The structural firewall remains unchanged: the complete R_DEG and R_TRI control banks must be generated, structurally validated, written to disk, and hash-fixed before any confirmatory spectral calculation is permitted. No control may be admitted or rejected using eigenvalues, QSPEC, RRESP, spectral-band distances, target-control scores, or scientific verdict information. The corrected implementation was validated only with burned development seeds and synthetic numerical checks. Correction validation confirmed: - exact protocol verification: PASS; - NumPy 2.3.5 / SciPy 1.17.0 environment validation: PASS; - burned R_DEG generation: PASS; - exact labelled degree-sequence preservation: PASS; - burned R_TRI generation with 10,000 accepted swaps: PASS; - exact triangle preservation T = 6960: PASS; - connectivity: PASS; - approximately 40–45% edge replacement: PASS; - deterministic replay: PASS; - synthetic QSPEC/RRESP implementation checks: PASS. No confirmatory HLV-R-MECH-001 seed stream was used during correction validation. No confirmatory target spectrum was computed. No confirmatory target QSPEC or RRESP score was computed. No scientific HLV-R-MECH-001 verdict was generated. The corrected One-Click notebook SHA-256 is: e8d1f516bc7a600039b44a7f2de8bdf5ecdc51a739d39aaf1e839d97d7e4bc95 The corrected implementation-freeze PDF SHA-256 is: e75aee3a4c790fefafda41aee93c6c267c814b66739bd1070355b519eb98452c The corrected implementation package SHA-256 is: d6e2d6ef3bf0b315bcbf7270c3be591bca28b7c13ef5730af30cb9bbead70b0f The unchanged scientific engine SHA-256 is: 317df650991120f686768ffc07d12f044f58e38ce8f2c47c083901bf1d7a8a14 This record supersedes implementation freeze v0.1.0 only with respect to numerical-environment bootstrapping. It does not supersede or alter the scientific protocol. HLV-R-MECH-001 remains a finite graph-mechanism test. Neither this corrected implementation nor any later HLV-R-MECH-001 result can by itself establish unique HLV geometry, physical selection of the golden ratio, extra dimensions, spacetime, particle physics, an absolute energy scale, gravity, dark matter, dark energy, cosmology, or experimental validation. The purpose of this corrected implementation freeze is solely to ensure that the prospectively frozen scientific engine can execute in a numerically reproducible environment despite changes in the externally assigned Colab runtime.
Marcel Krüger· Zenodo (CERN European Organi...· 0 citations
Overview: The dataset provides a fully synthetic, computer-generated cohort of 10,000 virtual patients with colorectal cancer (CRC). No actual patient data was accessed, collected, or utilized at any stage of this research.Variables: The dataset includes 39 variables organized across six clinical domains. These domains cover demographics, presenting symptoms, laboratory values, tumor pathology, TNM staging, treatment, and short-term postoperative outcomes.Methodology: The dataset was built using a causal-chain design programmed in Python. It also incorporates realistic missing-at-random patterns for three specific laboratory values: CA19-9, CRP, and albumin.Validation: The synthetic data's aggregate statistics (such as microsatellite instability prevalence, postoperative complications, and 30-day mortality) closely align with published real-world benchmarks. It successfully preserves expected directional clinical relationships.Intended Use: The data is designed to be an open resource for machine learning benchmarking, clinical informatics software testing, and educational purposes. It allows researchers to bypass patient privacy barriers for pipeline development.Restrictions: The dataset is explicitly not meant for direct clinical decision-making or to validate real-world predictive performance.
The rapid expansion of internet-facing web applications has widened the attack surface available to automated scanners, botnets and malicious actors, while common weaknesses such as misconfigured servers, unpatched software, obsolete transport-layer encryption and missing HTTP security headers continue to be exploited at scale. Commercial vulnerability scanners are costly and largely opaque, whereas open-source command-line utilities operate independently of one another and demand specialised expertise, offering little contextual or remediation guidance. This paper presents the design of SecureXon , a modular, full-stack security reconnaissance and threat-intelligence platform built around a Python/Flask backend that consolidates fifteen asynchronous reconnaissance modules with a large-language-model-driven Security Operations Center (SOC) assistant for false-positive vulnerability filtering and remediation guidance. A dedicated Zero-Trust defensive subsystem, the SSRF Guard, validates every outbound network request against loopback, private, link-local, multicast and encoded IP representations before it is dispatched. A companion log-analysis engine maps detected attack signatures in Nginx/Apache traffic to the MITRE ATT&CK knowledge base. Beyond the system design, this paper contributes a normalised risk-scoring formulation, an architecture and workflow specification, a structured SSRF bypass test-vector suite, and a precision/recall/F1-based evaluation protocol for the AI-assisted CVE triage stage. As the platform is currently at the design-and-development stage, the paper specifies evaluation protocols for quantitative validation rather than reporting unmeasured performance results.
Sahil Bagde, Swapnil Meshram, Harish Dange et al.· Zenodo (CERN European Organi...· 0 citations
This record contains the locked confirmatory scientific results of HLV-R-MECH-001, a prospectively frozen mechanism test of the previously observed degree-preserving rewire spectral residual within the Helix–Light–Vortex Framework (HLV), positioned as a Cut-and-Project and Incidence-Spectral Research Programme. The controlling scientific protocol is: Krūger, M. (2026). HLV-R-MECH-001: Prospective Triangle-Matched Mechanism Test of the Surviving Degree-Preserving Rewire Spectral Residual — Pre-Execution Protocol Freeze v0.1.0. Zenodo. DOI: 10.5281/zenodo.22166283 The authoritative corrected implementation freeze is: Krūger, M. (2026). HLV-R-MECH-001: Deterministic One-Click Engine for Triangle-Matched Rewire Mechanism Testing — Corrected Implementation Freeze v0.1.2 [Computer software]. Zenodo. DOI: 10.5281/zenodo.22170307 The v0.1.2 implementation changed only the numerical-runtime bootstrap. The scientific engine remained byte-identical to the prospectively frozen implementation. Frozen scientific engine SHA-256: 317df650991120f686768ffc07d12f044f58e38ce8f2c47c083901bf1d7a8a14 The successful locked scientific execution returned the machine verdict: RMECH001_PASS_TRIANGLE_MATCH_COLLAPSE_PATTERN The experiment contained two fresh prospectively frozen control families. R_DEG: fresh simple connected degree-preserving rewires matched to the target in labelled degree sequence and perturbation depth, with global triangle count unconstrained. R_TRI: fresh simple connected rewires preserving both the exact labelled target degree sequence and the exact global target triangle count T = 6960. Each family contained 31 accepted controls. The frozen family outcomes were: R_DEG: QSPEC PASS RRESP PASS Family PASS R_TRI: QSPEC FAIL RRESP FAIL Family FAIL For the fresh R_DEG family, the previously observed degree-preserving rewire spectral residual reproduced strongly. QSPEC: D_target = 0.008715193283827952 max D_LOO = 0.005181032910966849 median D_LOO = 0.0015059971709314455 robust margin = 5.786991803203511 2 of 3 frozen spectral bands pass. RRESP: D_target = 0.008334776747240381 max D_LOO = 0.0019187166287396942 median D_LOO = 0.0010793384522247884 robust margin = 7.722116014731345 2 of 3 frozen spectral bands pass. Thus the fresh degree-only baseline independently reproduces the earlier R-family spectral separation under the frozen mechanism-test design. For the exact-triangle-matched R_TRI family: QSPEC: D_target = 0.002191501382099135 max D_LOO = 0.0017606104448781759 robust margin = 1.7780654702146463 1 of 3 frozen spectral bands passes. RRESP: D_target = 0.0025511096413481766 max D_LOO = 0.0021234752495009907 robust margin = 2.2593200944928404 1 of 3 frozen spectral bands passes. Both R_TRI signatures therefore fail the complete frozen signature gate because the prospectively required minimum of 2 of 3 passing spectral bands is not reached. The rewiring-depth matching gate passed. Median edge-replacement fraction: R_DEG = 0.42768942937324606 R_TRI = 0.42076707202993446 absolute difference = 0.0069223573433115915 which is below the frozen maximum allowed difference of 0.02. The result therefore cannot be attributed to a substantially weaker perturbation depth in the triangle-matched family. The numerical environment and hard numerical audits also passed. The successful locked execution used: NumPy 2.3.5 SciPy 1.17.0 and completed the prospectively frozen target and selected control eigensolver/identity checks. The central scientific result is: exact preservation of the target's global triangle count collapses the previously robust two-signature, multi-band degree-preserving rewire spectral separation under the frozen HLV-R-MECH-001 gate. This provides prospective evidence that triangle/face organization is a major mechanism contributing to the previously observed R-family spectral residual. The result has a direct analytic basis. For a simple graph Laplacian L = D - A, Tr(L) = sum_i d_i, Tr(L^2) = sum_i d_i^2 + sum_i d_i, and Tr(L^3) = sum_i d_i^3 + 3 sum_i d_i^2 - 6T. Because R_TRI preserves both the complete degree sequence and the exact target triangle count T = 6960, it matches the target exactly in the first three raw Laplacian spectral moments. The observed collapse is therefore consistent with the hypothesis that the earlier degree-preserving R residual was strongly driven by face-triangle and associated short-cycle organization that was destroyed by the original degree-only rewires. However, the result does not prove that global triangle count is the sole causal invariant. Residual differences remain inside the R_TRI family. In particular, although the complete frozen QSPEC and RRESP gates fail, the R_TRI target distances still exceed the corresponding maximum leave-one-out distances and retain robust margins above 1.5. The failure occurs because only one of the three frozen spectral bands passes in each signature. Predeclared secondary diagnostics also show that exact global triangle matching does not reproduce the complete local target organization. For example, R_TRI controls still differ from the target in quantities including: - local per-vertex triangle distribution; - average clustering; - four-cycle count; - degree assortativity; - algebraic connectivity; - and other local or higher-order structural observables. Accordingly, the scientifically admissible conclusion is: The previously robust degree-preserving rewire spectral residual is strongly reduced and loses its frozen two-signature multi-band PASS once the exact global triangle count is preserved, supporting triangle/face organization as a major mechanism behind the original R-family effect. Remaining local and higher-order structural differences prevent the conclusion that global triangle count alone fully explains the residual. The locked result ZIP SHA-256 is: 69f927faba83b203d7dffbf028de680e6a6a3e36818002bc0e1ab27d5c01797d This result does not establish: - unique HLV geometry; - physical selection of the golden ratio; - a unique 6D-to-3D microscopic substrate; - spacetime; - extra dimensions; - particle physics; - an absolute energy scale; - gravity; - dark matter; - dark energy; - cosmology; - or experimental validation. The result instead narrows the active research programme toward the structural origin of the surviving local incidence-spectral residual. A natural successor is a separately prospectively frozen mechanism test using stronger controls that preserve local triangle profiles and selected short-cycle or motif structure before evaluating the inherited spectral signatures. The negative full-carrier-specificity results of the earlier HLV programme remain unchanged.
Marcel Krüger· Zenodo (CERN European Organi...· 0 citations
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.
