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
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ABSTRACT This study aims to examine and provide empirical evidence regarding the effect of utilizing Artificial Intelligence (AI) as a learning medium in accounting education on students’ financial management behavior, both directly and through financial literacy as a mediating variable. This study is important given the rapid development of AI technology in education, while students’ ability to understand and manage their finances wisely needs to be continuously strengthened. Therefore, empirical research is needed to determine whether the use of AI in accounting education can contribute to improving students’ financial literacy and financial management behavior. This study employs a quantitative approach using a survey method. The research sample consisted of 35 eleventh-grade accounting students at SMK Negeri 6 Medan, selected through purposive sampling based on the criterion that participants were active users of AI technology. Data were collected using a closed-ended questionnaire with a Likert scale, while data analysis was conducted using simple and multiple linear regression and the Sobel test, processed using SPSS software. The results show that AI utilization has a positive and significant effect on financial literacy, with a contribution of 61.6%, and has a direct effect on financial management behavior of 65.5%. Financial literacy also has a significant partial effect on financial management behavior, with a contribution of 80.4%. Simultaneously, AI utilization and financial literacy influence financial management behavior by 83.3%. The Sobel test further demonstrates that financial literacy significantly serves as a partial mediator in the relationship between AI utilization and students’ financial management behavior. In conclusion, the utilization of AI as a learning medium in accounting education is an effective strategy for developing students’ financial literacy and financial management behavior in an integrated manner. ABSTRAK Penelitian ini bertujuan untuk menguji dan memberikan bukti empiris mengenai pengaruh pemanfaatan Artificial Intelligence (AI) sebagai media pembelajaran akuntansi terhadap perilaku pengelolaan keuangan siswa, baik secara langsung maupun melalui literasi keuangan sebagai variabel mediasi. Penelitian ini penting dilakukan mengingat perkembangan teknologi AI dalam pembelajaran semakin pesat, sementara kemampuan siswa dalam memahami dan mengelola keuangan secara bijak perlu terus diperkuat. Oleh karena itu, diperlukan kajian empiris untuk mengetahui apakah pemanfaatan AI dalam pembelajaran akuntansi dapat berkontribusi terhadap peningkatan literasi keuangan dan perilaku pengelolaan keuangan siswa. Penelitian ini menggunakan pendekatan kuantitatif dengan metode survei. Sampel penelitian berjumlah 35 siswa kelas XI jurusan Akuntansi di SMK Negeri 6 Medan yang dipilih melalui teknik purposive sampling dengan kriteria merupakan pengguna aktif teknologi AI. Pengumpulan data dilakukan menggunakan instrumen kuesioner tertutup berskala Likert, sedangkan analisis data menggunakan regresi linier (sederhana dan berganda) serta Uji Sobel yang diolah menggunakan perangkat lunak SPSS. Hasil penelitian menunjukkan bahwa pemanfaatan AI berpengaruh positif dan signifikan terhadap literasi keuangan dengan kontribusi sebesar 61,6%, serta berpengaruh langsung terhadap perilaku pengelolaan keuangan sebesar 65,5%. Literasi keuangan secara parsial juga berpengaruh signifikan terhadap perilaku pengelolaan keuangan sebesar 80,4%. Secara simultan, pemanfaatan AI dan literasi keuangan memengaruhi perilaku pengelolaan keuangan sebesar 83,3%. Melalui pengujian Uji Sobel, literasi keuangan terbukti secara signifikan berperan sebagai mediator parsial (partial mediation) dalam hubungan antara pemanfaatan AI dan perilaku pengelolaan keuangan siswa. Kesimpulannya, pemanfaatan AI sebagai media pembelajaran akuntansi terbukti menjadi strategi efektif yang mampu membentuk literasi keuangan dan perilaku pengelolaan keuangan siswa secara terintegrasi.
Muhammad Ariel, Natasya Ramadhani Citra, Delima Sianipar et al.· SECONDARY Jurnal Inovasi Pen...· 0 citations
Introduction: The nose has long been known to hold an important place in the medical sphere, owing to its important functions in olfaction and respiration. Its normal morphology and morphometry are also crucial for determining facial aesthetics. Different types of nasal deformities are also seen to be associated with various congenital anomalies. Anthropometry of the nose varies with age, gender and ethnicity. Aim: To explore region-, ethnic-, and gender-specific nasal angulations of the adult population of Garhwal, Himalayas, Uttarakhand, India. Materials and Methods: This community-based crosssectional observational study was conducted at the Department of Anatomy, Veer Chandra Singh Garhwali Government Institute of Medical Science and Research, Srinagar Garhwal, Uttarakhand, India, from July 2024 to June 2025. Multistage sampling was applied to measure 141 males and 105 females residing in the Garhwal Himalayas, using the photogrammetric method. Nasofrontal, nasofacial, nasolabial, nasal-tip and interalar angles were measured employing the Magnus Analytics MagVision application. Descriptive (Mean and Standard deviation) and inferential (Independent t-test and Welch’s t-test) statistics were done by Statistical Package for Social Sciences (SPSS) software, with p<0.05 as significant. Results: Means of nasofrontal angle was 123.79°±13.28° in males and 133.59°±6.72° in females, nasofacial angle was 33.94°±4.74° in males and 32.08°±3.47° in females, nasolabial angle was 93.49°±13.61° in males and 96.07°±12.20° in females, nasal-tip angle was 82.03°±5.05° in males and 82.69°±6.09° in females, inter-alar angle was 77.73°±10.58° in males and 79.14°±10.16° in females. Nasofrontal angle was found to be significantly higher in females, whereas nasofacial angle was higher in males. All angles also showed significant differences with those found by other authors in various ethnicities. Conclusion: Normal values of nasal angular parameters of the Garhwal Himalayan population have been established in this study. This will prove its worth during plastic surgeries of the face, diagnosing genetic diseases, manufacturing facial accessories and criminal investigation procedures.
Niyati Airan, A. K. Dwivedi, Ananya Sharma et al.· JOURNAL OF CLINICAL AND DIAG...· 0 citations
PooledScreenID is an installable, research-use Python package that separately reports material cold-start gain, outcome-blind control association, representation separability and external calibration before generating a claim resolution. Version 0.1.2 includes a minimal Python API, command-line interface, machine-readable four-axis claim ledger, tests, continuous-integration configuration, frozen configurations and reproducible EGFR and MET examples. The software does not prove a molecular mechanism and does not make patient-level treatment recommendations.
niu niu, Wei Fang, wenjuan li et al.· Zenodo (CERN European Organi...· 0 citations
This study aimed to investigate the effect of using educational software on developing mathematical problem-solving skills among Grade Six primary school pupils. The study adopted a descriptive-analytical approach to examine pupils’ performance before and after the educational intervention. The study sample consisted of 140 pupils from five basic education schools. A 25-item mathematics problem-solving test was administered as a pre-test and post-test, with a maximum score of 25 points. The results revealed a clear improvement in pupils’ performance following the educational intervention. The overall mean score increased from 14.70 in the pre-test to 21.72 in the post-test, with an overall mean gain of 7.02 points. In terms of percentage, the overall performance increased from 58.80% to 86.88%. Among the five schools, Manarat Al-Ilm Basic Education School achieved the highest mean gain, reaching 7.53 points, equivalent to 30.12 percentage points. These findings indicate that the use of educational software had a positive effect on improving pupils’ mathematical problem-solving skills. The study recommends expanding the use of educational software in mathematics teaching, providing appropriate training for teachers, improving the technological infrastructure of schools, and conducting future studies using larger samples and longer intervention periods.
Abeer Hussein Saleh Al-Hajjahi· Comprehensive Journal of Sci...· 0 citations
This record contains Rigorous Consolidated Core v2.1.5 of the Helix–Light–Vortex Framework (HLV). HLV is positioned in this revision as: Helix–Light–Vortex Framework (HLV) A Cut-and-Project and Incidence-Spectral Research Programme. The term “Framework” denotes the existing mathematical architecture and provenance of the programme. The active scientific direction is the HLV Cut-and-Project / Incidence-Spectral Research Programme. The present work is not presented as a validated fundamental physical theory. The consolidated core separates: - native 6D-to-3D cut-and-project carrier construction; - abstract incidence structure; - finite carrier fingerprints; - spectral and Hodge diagnostics; - explicitly postulated free dynamics; - continuum obligations; - gauge-sector mathematics; - theorem-level no-go boundaries; - and physical interpretation. Version 2.1.5 preserves the previous locked negative and bounded results while integrating the completed HLV-R-MECH-001 mechanism chain. The principal established structural constraints remain: 1. Native projected geometry HLV-LAYER-ORIGIN-007F / 007F-CERT establishes that the tested native projected tetrahedral assembly is not a strict global face-to-face simplicial realization. The local projected rank-three cell geometry remains mathematically valid, but the tested assembly cannot be promoted to a global native piecewise-flat or Regge manifold without a new validated global metric-complex construction. 2. Abstract incidence complex HLV-DG-001 independently certifies the retained parent-labelled structure as an exact finite oriented 0–3 chain complex with (N0, N1, N2, N3) = (1110, 5345, 6960, 2826), boundary ranks (1109, 4137, 2823), Betti vector (1, 99, 0, 3), and exact chain identities B1 B2 = 0, B2 B3 = 0. 3. Static and dynamic specificity HLV-DG-002 rejects HLV-specificity of the frozen cross-grade Hodge signature under the complete R/Q/W null ensemble. HLV-FA-DYN-001 rejects overall HLV-specific dynamic transport under its frozen R/Q/W ensemble. Its degree-preserving rewire family separates strongly, but the broader geometric controls defeat the complete specificity claim. HLV-DS-SPEC-001R separately rejects full native-carrier graph-spectral specificity under the frozen R/Q/W/IRR ensemble. Its locked machine verdict is: DSSPEC001R_FAIL_PARTIAL_SIGNATURE_OR_FAMILY_ONLY The degree-preserving R family passes both QSPEC and RRESP, while Q, W, and IRR fail the complete frozen criteria. This result established only a bounded graph-spectral structural residual and did not identify its mechanism. 4. HLV-R-MECH-001 mechanism localization Version 2.1.5 integrates the first prospectively frozen mechanism localization of that surviving graph-spectral R residual. Controlling protocol: 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 Authoritative corrected implementation: 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 Locked confirmatory results: Krūger, M. (2026). HLV-R-MECH-001: Locked Confirmatory Results for Triangle-Matched Mechanism Testing of the Degree-Preserving Rewire Spectral Residual v0.1.0 [Computer software]. Zenodo. DOI: 10.5281/zenodo.22170620 Locked result ZIP SHA-256: 69f927faba83b203d7dffbf028de680e6a6a3e36818002bc0e1ab27d5c01797d The successful locked machine verdict is: RMECH001_PASS_TRIANGLE_MATCH_COLLAPSE_PATTERN The experiment used two fresh prospectively frozen control families. R_DEG preserves the exact labelled target degree sequence while allowing the global triangle count to vary. R_TRI preserves both the complete labelled degree sequence and the exact global target triangle count T = 6960. Both families were matched in rewiring depth. The fresh R_DEG baseline reproduces the earlier graph-spectral residual: QSPEC: PASS RRESP: PASS with robust margins approximately 5.7870 and 7.7221. Under exact triangle matching, R_TRI returns: QSPEC: FAIL RRESP: FAIL under the complete prospectively frozen multi-band gate. The target-control distance relative to R_DEG is reduced by approximately: 74.85% for QSPEC, and 69.39% for RRESP. This prospectively localizes triangle/face organization as a major contributor to the previously observed degree-preserving rewire spectral residual. The result has an exact low-order spectral basis. For a simple graph Laplacian L = D - A, the identities 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 hold. Consequently, preserving the complete degree sequence and exact triangle count fixes the target values of the first three raw Laplacian spectral moments exactly. This mechanism result does not prove that global triangle count is the sole cause of the residual. In R_TRI, the target distances remain above the corresponding maximum leave-one-out distances and retain robust margins above 1.5, but only one of three frozen spectral bands passes in each signature. Predeclared secondary diagnostics also retain structural differences in: - local per-vertex triangle distribution; - clustering; - four-cycle counts; - assortativity; - algebraic connectivity; - and other higher-order local structure. The natural successor is therefore a separately prospectively frozen local-triangle-profile and short-cycle mechanism test. 5. Carrier fingerprint status The finite orientation-sensitive carrier fingerprint remains a bounded C2 result. Stage 6B and Stages 12–16 support an internally replicated orientation-sensitive finite carrier fingerprint under the stated frozen nulls. Stage 17 blocks the stronger fixed-window R = 2,3,4 scaling claim. Stage 18 remains diagnostic and does not overwrite that result. No injectivity theorem currently maps the finite fingerprint uniquely back to a microscopic carrier or physical spacetime. 6. Minimal free dynamics HLV-FA-0 remains explicitly axiomatic rather than derived. It postulates the cochain Hilbert space H_FA = direct sum from p=0 to 3 of C^p(K_abs; C), the minimal incidence-linear self-adjoint Hodge–Dirac generator D_K = d + delta, and one symbolic positive energy scale E_H. The numerical value of E_H is not predicted. The DG-001 Betti vector implies 103 exact Hodge–Dirac zero modes on the finite target. No particle masses, gauge interactions, gravity, dark-sector portal, or absolute physical energy scale follows from FA-0 alone. 7. Scalar-mode and gauge boundaries The core retains theorem-level no-go and covariance results showing, among other things, that: - a positive carrier Laplacian cannot generate a homogeneous negative quadratic direction from a nonnegative local mass; - a centered deformation F(L_G) with F(0)=0 leaves the constant-mode quadratic coefficient unchanged; - a bare tensor Laplacian L_G tensor I_r is not locally U(r)-frame covariant without independently supplied link transporters; - a fixed wrong-sign coefficient on a genuine refinement generator with diverging ultraviolet edge produces an unbounded negative spectral minimum. The finite compact-group gauge Hamiltonian remains mathematically well-defined with a positive finite-complex spectral gap, but this does not establish a continuum Yang–Mills mass gap. 8. Continuum boundary A single fixed bounded-degree, bounded-weight carrier has bounded Laplacian spectrum and therefore no intrinsic ultraviolet limit. A genuine continuum programme requires a changing refinement family, explicit scaling, identification maps, and an appropriate convergence theorem such as Mosco or generalized strong-resolvent convergence. No such native HLV continuum theorem is established in the present core. Scientific status after v2.1.5 The HLV Framework contains a reproducible mathematical cut-and-project construction, a certified finite abstract incidence complex, several rigorous operator sectors, theorem-level no-go results, finite carrier diagnostics, preserved negative specificity results, and a prospectively confirmed graph-spectral mechanism localization. The new HLV-R-MECH-001 result substantially clarifies the origin of the earlier degree-preserving R residual: triangle/face organization is a major contributor. It does not rescue the previously failed full carrier-specificity claims and does not establish that the native golden 6D-to-3D carrier is a fundamental physical substrate. The present evidence does not establish: - physical selection of the golden ratio; - a unique microscopic 6D-to-3D geometry; - Lorentzian spacetime; - a native Regge manifold; - Standard-Model recovery; - a Higgs mechanism; - particle masses; - an absolute HLV energy scale; - continuum Yang–Mills; - gravity; - dark matter; - dark energy; - cosmology; - or experimental validation. The active programme is therefore intentionally narrower: to determine which structural, incidence, spectral, and refinement properties of cut-and-project and related discrete systems survive increasingly strong matched alternatives, and to distinguish general mathematical mechanisms from genuinely carrier-specific effects before any physical interpretation is attempted. This revision strengthens mechanism identification and falsification discipline while leaving the fundamental physical claim level unchanged.
Marcel Krüger· Zenodo (CERN European Organi...· 0 citations
A guaranteed-coverage confidence interval for the two-sample standardized effect William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.22114522. Published v1.0.0:10.5281/zenodo.22114523 (2026-08-26, the earlier two-tier construction). The three-tier update described below is staged as a pending new version (v1.1.0) on the same concept DOI. What this is The reproducibility deposit for the m01te methods paper: a guaranteed-coverage confidence interval for the two-sample standardized effect (Cohen's d) at the skewed, unequal-variance, small-n corner where the textbook interval silently under-covers. The noncentral-t inversion assumes normal data and equal variances; at a lognormal, four-to-one variance-ratio, n = 10 design its realized coverage falls to 0.81 against a nominal 0.95, and a naive percentile bootstrap of dfalls further, to 0.78 — a joint failure of the mean-difference reference and the variance estimate that standardizes it, which resampling does not repair. The paper gives a three-tier recommendation, mirroring the companion two-sample test and the one-way effect-size paper: Classical — the noncentral-t / normal-approximation interval, the everyday default, liberal at the corner. Calibrated middle tier — the guaranteed two-sample test T_BB inverted for the mean difference at the full level, divided by the plug-in pooled scale. Closed-form and deterministic (no resampling), with near-nominal worst-case coverage 0.93 at about 1.6× the classical width. It keeps the mean-difference deflation that repairs the actual under-coverage while treating the scale at its point estimate; the over-covering numerator and the under-covering plugged-in scale roughly cancel to near nominal. Guaranteed floor — a Bonferroni combination of the T_BB-inverted mean-difference interval with a distribution-free bootstrap scale interval, carrying a proved finite-sample coverage floor (worst-case 0.97) at about 4× the classical width. What the deposit contains Manuscript (author + anonymized markdown; built .docx/.pdf, including a cross-reference–hyperlinked variant) and the derivations (D1–D6): the estimand and its d_av scale; the T_BB-inverted mean-difference interval; the exact Bonferroni coverage floor of the ratio interval; why the classical standard error under-covers off its normal/equal-variance premise; the deterministic-simulation confirmation; and the calibrated middle tier with its compensation argument. Reproducibility runner — rerun/rc_m01te_coverage.py computes, for each design cell across the parent-distribution × sample-size × variance-ratio × effect grid, the realized coverage and mean width of all four intervals (classical, percentile-bootstrap, calibrated middle, guaranteed floor). Every number regenerates from this deterministically-seeded script (seed 20260826); its locked output CSV is deposited. Figure — figures/m01te_coverage.png (built by make_m01te_figure.py): the four coverage curves cell by cell across the grid, the classical and bootstrap curves sliding below nominal at the corner, the calibrated curve tracking near it, and the guaranteed curve holding above it. All evaluation is simulation-based. Code is released under the MIT License; text and figures under CC BY 4.0. How to cite Please cite this deposit if you use the package or the method. Citing the concept DOI references the work in general and always resolves to the latest version; cite a specific version DOI to point at an exact snapshot. Dwyer, W. J. (2026). A guaranteed-coverage confidence interval for the two-sample standardized effect: reproducibility deposit (Version 1.0.0) [Software]. Zenodo. https://doi.org/10.5281/zenodo.22114522
William Dwyer· Zenodo (CERN European Organi...· 0 citations
Modern software systems rely on observability infrastructure (metrics, logs, and traces) to detect failures and maintain reliability. In practice, key observability decisions are made through untested defaults: static alerting thresholds, keyword-based log-level selection, and monitoring feature sets chosen by convention rather than evaluation. Despite growing interest in AIOps, no prior study has directly measured the gap between these default rule-based practices and machine learning across both anomaly detection and logging decisions. We present a two-part empirical study quantifying this gap. In Part A, we evaluate static-threshold baselines (𝜇 ± 3𝜎) against per-KPI machine learning models on the AIOps 2018 benchmark, which comprises 2.67 million labelled data points. ML models outperformed the static threshold on 91% of evaluable KPIs, though absolute performance varied widely (mean F1 = 0.41, median = 0.116), and an ablation study showed that 53% of monitoring features could be removed without degrading detection. SHAP analysis confirmed that no universal feature ranking exists across KPIs. In Part B, we mine 15,702 log statements from 15 open-source Node.js/TypeScript repositories and train classifiers to predict developer-chosen log levels from code context. The model achieves cross-project macro F1 of 0.92 when surrounding code (including existing log statements) is available, compared to 0.38 for a keyword heuristic. However, a level-name-stripped ablation reveals this drops to 0.52 without neighbouring log-level tokens, showing the dominant signal is inter-statement level clustering rather than deeper code-structural patterns. This clustering generalises across 15 independent codebases and 3 unseen test repositories. Our results demonstrate that default observability practices leave substantial performance on the table, while identifying boundary conditions where simple rules remain competitive.
Ivy Murage· Zenodo (CERN European Organi...· 0 citations
The real part 1/2 occurs in the theory of the Riemann zeta function as the symmetry axis of its non-trivial zeros. This monograph asks a narrower question than the Riemann Hypothesis itself: can the distinguished role of the half-axis be explained by a common structural mechanism joining binary complementarity, information balance, two-channel interference, spinorial phase, and the anti-linear symmetry of the completed zeta function? The exact part of the programme is developed first. Binary Shannon entropy has its unique maximum at σ = 1/2, with value ln 2. A normalized equal-gain two-channel amplitude A(σ, ϕ) = √ σ + e iϕ√ 1 − σ vanishes if and only if σ = 1/2 and ϕ ≡ π (mod 2π). The involution J (s) = 1 − s has fixed set ℜs = 1/2. If the spinorial sign is parameterized by e 2πiσ, then the sign −1 also selects σ = 1/2 in the open unit interval. These statements combine into an exact “triple coincidence” theorem inside the explicitly defined binary-spinor model. A non-metaphorical bridge to zeta theory is provided by the Dirichlet eta function, η(s) = X n≥1 (−1)n−1n −s = (1 − 2 1−s )ζ(s), with η(1) = ln 2. Within the open critical strip, the eta and zeta zero sets coincide because the binary prefactor has no zeros there. This establishes a genuine relation among alternating binary sign, ln 2, and the non-trivial zeta zeros. It does not determine the horizontal location of those zeros. The central conditional theorem is then stated. If there exists a canonical, involution- covariant Hilbert-space state map whose fixed readout vanishes exactly with ξ(s) and whose normalized channel weights are ℜs and 1 − ℜs, then every non-trivial zero lies on ℜs = 1/2. The theorem is short; the construction of such a map is the entire unresolved burden. Several tempting shortcuts are shown to fail: symmetry alone produces zero quartets rather than fixed points, eta alternation adds a separate line of prefactor zeros, unequal channel metrics move the balance point away from one half, and a pointwise normalized factorization can be engineered non-canonically. The monograph closes by formulating operator, positivity-kernel, de Branges, Li-coefficient, and theta-kernel routes as concrete research programmes. Numerical calculations are used only as regression tests for identities and software, never as substitutes for proof.
Adrian Lipa· 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.
