Kim, Ah Young · Kim, Jin Su · Ko, Jung Yun · et al.

3 files · 307 KB · pdf, xlsxdeclared

This dataset contains the source data associated with the manuscript entitled "Overexpression of SlMPBQMT (VTE3) enhances α-tocopherol accumulation and reduces oxidative stress in tomato." The uploaded files include the original experimental data used to generate the figures and analyses presented in the manuscript, including: HPLC quantification of α-tocopherol. Plant phenotype measurements. qRT-PCR expression data. DAB and NBT staining quantification data. These data are provided to ensure transparency, reproducibility, and compliance with the data availability policy of BMC Plant Biology .

Bell, Peter

2 files · 14 MB · pdf, zipdeclared

This working paper asks how Canada should assess strategic resource infrastructure that may not earn a commercial return on its own. A road, port, power system, pipeline, smelter, or processing plant can appear uneconomic when evaluated as an individual asset while still enabling new production, preserving difficult-to-replace processing capacity, supporting several users, or improving security of supply. The paper develops a framework for deciding when public support for such an asset may be justified. Its central rule is that an asset-level loss is defensible only when it produces wider benefits that are specific, measurable, and subject to effective public oversight. The analysis draws on Canadian wartime industrial mobilization, concentration in critical-mineral supply chains, proposed support for processing capacity at Trail, current infrastructure and northern development programs, and cautionary cases involving mining subsidies, managed decline, remote transport, and major-project governance. The paper converts the argument into a twelve-question approval test and a measurement framework for tracking public cost, avoided closure, new production, secure supply, shared infrastructure use, and signs of failure. It does not recommend a particular project and does not argue that all loss-making assets deserve public support. Its purpose is to distinguish infrastructure that creates durable public value from subsidy, bailout, or white-elephant risk.

Chen, Hang

1 files · 151 MB · zipdeclared

What's Changed Add GPT API-based multi-agent system for automated ERT workflows by @geohang with @Copilot in https://github.com/geohang/PyHydroGeophysX/pull/3 Add multi-LLM provider support and position agent system for cross-modal geophysics by @geohang with @Copilot in https://github.com/geohang/PyHydroGeophysX/pull/4 Add ClimateDataAgent for PyDaymet integration with ERT workflows by @geohang with @Copilot in https://github.com/geohang/PyHydroGeophysX/pull/5 Add ClimateDataAgent integration for cross-modal climate-ERT reasoning by @geohang with @Copilot in https://github.com/geohang/PyHydroGeophysX/pull/6 New Contributors @geohang with @Copilot made their first contribution in https://github.com/geohang/PyHydroGeophysX/pull/3 Full Changelog : https://github.com/geohang/PyHydroGeophysX/compare/1.0...v0.3.0

Tabiri, Josephine Konamah

1 files · 11 MB · zipdeclared

This repository contains photographic images from six stores used in my thesis reserach. The files document the visual material analyzed in the study.

Lafleur, Trevor · Rawoof, Shaik · Bowden, George · et al.

13 files · 762 KB · xlsxdeclared

Datasets correspond to data used/presented in the open-access paper: T. Lafleur, R. Shaik, G. Bowden, D. Petty, and C. Corr, "Frequency-Agile Matching of Inductively Coupled Plasmas", Plasma Sources Science and Technology, accepted (2026) Specific files correspond to the data presented in the relevant figures of the above paper: Sweep_Prf_56ugs.xlsx: Data for the thruster at a fixed mass flow rate of 56 ug/s and different powers. The columns indicate different system properties. Used in Figures 3 and 4. Sweep_mdot_7W.xlsx: Data for the thruster at a fixed power of 7 W and different mass flow rates. The columns indicate different system properties. Used in Figures 3 and 4. Sweep_freq_56ugs_7W.xlsx: Data for the thruster at a fixed power and mass flow rate of 7 W and 56 ug/s respectively, and different frequencies. The columns indicate different system properties. Used in Figure 5. Agile_Sweep_Prf_56ugs.xlsx: Data for the thruster at a fixed mass flow rate of 56 ug/s and different powers, and with frequency-agile matching used. The columns indicate different system properties. Used in Figure 6. Agile_Sweep_Prf_56ugs_Fixed.xlsx: Data for the thruster at a fixed mass flow rate of 56 ug/s and different powers, and with the frequency fixed. The columns indicate different system properties. Used in Figure 6. Sweep_2D.xlsx: Data for the thruster at difference powers and mass flow rates, and with frequency-agile matching used. Each sheet indicates 2D data for the relevant property in that sheet. Used in Figure 7. Sweep_2D_Fixed.xlsx: Data for the thruster at difference powers and mass flow rates, and with the frequency fixed. Each sheet indicates 2D data for the relevant property in that sheet. Used in Figure 7. Torch_Sweep_mdot_800W.xlsx: Data for the torch at a fixed power of 800 W and different mass flow rates. The columns indicate different system properties. Used in Figure 8. Torch_Sweep_freq_100mgs_800W.xlsx: Data for the torch at a fixed power and mass flow rate of 800 W and 100 mg/s respectively, and different frequencies. The columns indicate different system properties. Used in Figure 9. Agile_Torch_Sweep_mdot_800W.xlsx: Data for the torch at a fixed power of 800 W and different mass flow rates, and with frequency-agile matching used. The columns indicate different system properties. Used in Figure 10. Agile_Torch_Sweep_mdot_800W_Fixed.xlsx: Data for the torch at a fixed power of 800 W and different mass flow rates, and with the frequency fixed. The columns indicate different system properties. Used in Figure 10. Torch_Sweep_2D.xlsx: Data for the torch at difference powers and mass flow rates, and with frequency-agile matching used. Each sheet indicates 2D data for the relevant property in that sheet. Used in Figure 11. Torch_Sweep_2D_Fixed.xlsx: Data for the torch at difference powers and mass flow rates, and with the frequency fixed. Each sheet indicates 2D data for the relevant property in that sheet. Used in Figure 11.

Levine, Jonathan · MacEachern, Leonard

1 files · 510 KB · zipdeclared

Supplementary artifact for the IEEE Embedded Systems Letters manuscript "Threshold-Based Batch Normalization for Integer-Only Binarized Neural Network Inference" by Jonathan Levine and Leonard MacEachern. The package contains FPGA HLS sources, exported trained-network parameters, ECDF/statistics data, TCL reproduction scripts, selected logs and reports, and helper scripts for the MNIST, CERN jet-substructure tagging, and UNSW-NB15 workloads. It supports the paper's threshold-export formulation for integer-only dense BNN inference and the Alveo U250 HLS results reported in the manuscript. Repository: https://github.com/maceacla/tbbn-bnn-hls

Anonymous

6 files · 4.5 MB · xlsxdeclared

Replication package for the paper submitted to SE4FP 2026

Anonymus

1 files · 424 KB · zipdeclared

Analysis code for the manuscript "Bayesian sensory integration explains ball-count bias in Major League Baseball umpires" (submitted to Communications Psychology; author information withheld for double-anonymised peer review). This archive contains the complete analysis pipeline for quantifying the ball-count-dependent strike/ball decision bias of MLB home-plate umpires and explaining it with a Bayesian sensory integration model, together with the derived result files and figures reported in the manuscript. Data: MLB 2015-2024 regular and post-season games, 451,172 called pitches (four-seam fastballs thrown by right-handed pitchers to right-handed batters). Pipeline (numbered folders 00-05): - Data acquisition (Statcast pitch-tracking data and home-plate umpire assignments) - Merging and inclusion-criteria filtering - Count-wise psychometric (probit) function fits (point of subjective equality and perceptual uncertainty) - Two-component Gaussian Mixture Model of called-pitch locations (count-specific priors) - Trial-level Bayesian sensory integration model fit (count-specific vs. universal prior) - Umpire-wise individual-differences analysis (n = 89) Environment: Python 3.13 (pybaseball 2.2.7, pandas, pyarrow) and MATLAB R2022b (Statistics and Machine Learning Toolbox). Raw and intermediate pitch-tracking data are not included, owing to file size and to avoid redistributing Baseball Savant data; they can be regenerated with the scripts in steps 00-01. See the included README.md for the full folder structure, reproduction instructions, and the correspondence between output files and the values reported in the manuscript.

Chen, Jianyong

6 files · 1.5 GB · gzipdeclared

A first sequence of the Ae. speltoides B chromosome has been available since 2020 (RUBAN et al. 2020b), but this assembly represents ~16% of the B only and thus cannot be used to uncover B-encoded genes. Now, high-molecular-weight DNA from +B leaf tissue of the clonally propagated +B plant was used to generate a chromosome-scale genome assembly. A total of 154 Gb of PacBio HiFi reads and 36.4 Gb of Nanopore reads (>25 kb) were generated for primary assembly using hifiasm (Cheng et al. 2026). The resulting 5.47 Gb assembly achieved 93.7% BUSCO completeness (contig N50 = 17.1 Mb). Approximately 104 Gb of Hi-C sequencing data derived from leaf tissue of the same +B plant were employed to scaffold the primary contigs. The assembly yielded eight large scaffolds (398-835 Mb), each displaying a characteristic Rabl configuration. Alignment of these scaffolds to the reference genome of Ae. speltoides accession AEG-9674-1 without B chromosome (Avni et al. 2022) revealed that seven of the eight scaffolds showed strong synteny with the standard A chromosomes 1S-7S. To determine whether the remaining large scaffold corresponded to the B chromosome, we generated ~60 Gb of whole-genome sequencing (WGS) data from 0B AR-derived lateral root tissue of the same plant, as well as approximately 36 Gb of WGS data from +B leaf tissue. Comparative read-mapping analyses showed that the eighth scaffold exhibited normal sequencing coverage in +B leaf-derived data but substantially reduced coverage in 0B AR-derived data. Thus, the 398 Mb scaffold represents the B chromosome, accounting for 69% of its size as estimated by flow cytometry. Additionally, 4.81 Gb of contigs were assigned to the seven pairs of A chromosomes, representing 91% of their estimated size (1C=5.27 Gb). Consequently, we produced a high-quality chromosome-scale assembly of Ae. speltoides carrying B chromosomes. To identify genes associated with the B chromosome elimination process, RNA-seq was performed across developmental stages and different tissues in which B chromosome behavior differs. Using all +B RNA-seq datasets, we annotated the Ae. speltoides genome assembly containing the B chromosome. This annotation identified 59,981 transcripts and 47792 protein-coding genes on the seven A chromosomes and 5,940 transcripts and 4,196 protein-coding genes on the B chromosome.

Bradley, Alex

1 files · 244 KB · zipdeclared

Companion code for fitting hierarchical Bayesian spatial models that calibrate sedimentary leaf-wax n-C29 alkane hydrogen isotope ratios against precipitation isotope composition and environmental covariates. Implements 14 model variants in Stan with a Matern 3/2 Gaussian process predictive-process approximation on 125 globally distributed knots. Compares spatial and non-spatial calibrations across n = 1,128 surface sediment and soil sites from 73 publications.

Krajnc, Matej · Comi, Troy · Miao, Siqi · et al.

10 files · 25 GB · csv, zipdeclared

This dataset accompanies the manuscript "A Controlled in Silico Benchmark for GNN Prediction of Tissue Dynamics." It contains model prediction outputs, trained checkpoints, train/validation/test splits, spring-embedding outputs, generated analysis figures, analysis tables, and manuscript-specific diagnostic outputs used to reproduce the post-prediction analyses and figures. The dataset is distributed as logical ZIP archives with file-level and archive-level SHA-256 checksums. For questions, contact Tomer Stern at tomers@umich.edu.

Garrett, Patrick T. · Yates III, John R.

1 files · 83 MB · zipdeclared

Added Precursor-space MS1 gates ( tdfpy.noise.gates ). Two acquisition-aware NoiseFilter s that drop MS1 signal the instrument never fragments — signal that cannot become an identification. Both convert their (m/z, 1/K0) region once to per-scan integer TOF-index intervals (via the run calibration) and test membership with a vectorised binary search; both no-op (keep everything) when the run carries no region. Ported from the dnoise Rust tool. Compose like any filter, e.g. noise=[SelectionPolygonGate(), MadThreshold(k=3)] . SelectionPolygonGate (ddaPASEF) — keeps only MS1 points inside the run's PASEF selection polygon (the "IMS PolygonFilter" read from analysis.tdf 's GroupProperties ). A generalisation of ChargeStateRegion from a single line to the real acquisition polygon. Skipped on diaPASEF (where the same property stores window quads). Padded in physical units ( mz_pad default 5 Da, im_pad default 0.05 1/K0) so an edge precursor keeps its isotopic envelope / mobility spread rather than being clipped at a hard polygon boundary; pass mz_pad=0.0, im_pad=0.0 for a hard cutoff. DiaMs1WindowGate (diaPASEF) — keeps only MS1 points inside the union of the isolation windows ( DiaFrameMsMsWindows ); everything outside is a precursor the method never isolates. Windows are padded in physical units ( mz_pad default 5 Da, im_pad default 0.05 1/K0). No-op on ddaPASEF. Both gates now no-op (keep everything) on non-MS1 frames rather than testing fragment peaks against the MS1 precursor region (which would empty an MS2 spectrum), so they are safe to leave in a noise=[...] list applied across frame types. build_window_intervals clamps a negative scan_lo to 0 and skips boxes lying wholly outside the scan range instead of letting a negative bound wrap around via Python indexing.

Fabbri, Renato

1 files · 3.5 MB · zipdeclared

BSC Lab is an open-source sensory stimulation platform with two integrated layers: a precision multi-engine audiovisual stimulation application, and a knowledge layer built on the SSTIM ontology (OWL class hierarchy, multilingual SKOS vocabulary, SHACL validation shapes, exposure module, and external alignments) published at https://w3id.org/sstim under CC BY 4.0. Each tagged release is archived here for citation.

MENEGUZZO, FRANCESCO · Zabini, Federica

4 files · 146 KB · csvdeclared

This record contains the de-identified, analysis-ready dataset and Python analysis code associated with a school-based quasi-experimental pilot study on therapist-guided forest therapy and persistent anxiety symptoms in adolescents. The study involved two fourth-year high-school classrooms in Cecina, Tuscany, Italy: one intervention classroom that attended four therapist-guided forest therapy sessions in a coastal pine forest, and one control classroom that followed usual school activities. The dataset includes anonymized student codes, classroom allocation, SCAS total raw scores and derived reduction scores across repeated assessments, POMS-A acute mood-state variables for the intervention classroom, exploratory post-intervention nature-exposure and connectedness variables, and exploratory school-performance variables. The repository includes four files: 1. forest_therapy_adolescent_anxiety_dataset.csv: de-identified analysis-ready dataset. 2. README_forest_therapy_adolescent_anxiety_dataset.txt: dataset metadata and variable descriptions. 3. analyze_forest_therapy_adolescent_anxiety.py: Python script used to reproduce the main analyses and generate analysis outputs. 4. README_analyze_forest_therapy_adolescent_anxiety.txt: operational guide for running the analysis script and interpreting the output files. The dataset uses semicolon-separated values. Missing values are encoded as NaN and must not be interpreted as zero. Because the study involved minors, item-level questionnaire responses and more granular school records are not shared; only de-identified and analysis-ready variables compatible with privacy, ethical approval, and consent constraints are provided.

Bradley, Alex

1 files · 12 MB · zipdeclared

R package for reconstructing precipitation hydrogen isotope ratios from sedimentary leaf-wax n-C29 alkane measurements using the spatially-aware hierarchical Bayesian calibration of Bradley (2026). Inverts the forward calibration with full uncertainty propagation, combining analytical error, residual variance, slope posterior, and the spatial Gaussian process intercept. Supports per-record change detection with autocorrelation-adjusted thresholds and a four-level claim taxonomy from measurement-level changes through uniquely- attributable precipitation-isotope claims.

Juniper L. Simonis

1 files · 86 MB · zipdeclared

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Padilla-Villanueva, Johel

1 files · 457 KB · zipdeclared

Academy Learning Tau is an open educational and research software platform that operationalizes the Systemic Tau framework and the Discrete Extramental Clock (RECD) for complex time-series analysis. It provides ordinal metrics (τ_s, nested RECD levels), classical early-warning signals for dual reading, surrogate null models, multilingual pedagogy (Spanish, English, French), and a reproducible Streamlit laboratory for teaching and exploratory research.

Li, Mei-Ling · Hsieh, Cheng-Hong · Huang, Shang-Ming · et al.

1 files · 394 KB · xlsxdeclared

Supporting dataset for the manuscript "Quantum Mechanical Insights into the Inhibition of Xanthine Oxidase by Dietary Flavonoids: Ligand-to-Metal Charge Transfer at the Molybdenum Cofactor Governs Inhibitory Potency" (submitted to Inorganic Chemistry). Contains 10 worksheets: - README: Version history and sheet descriptions - Per_Flavonoid_Summary: Mean ± SD per compound (Ki, IC50, CT_lig, ΔE_Coul) - Table_S1_Mulliken_All: Mulliken atomic charges for all 50 QM/MM snapshots - Table_S1_Mo_Charges: Molybdenum Mulliken charges (gas-phase vs bound) - Table_S2_QM_Energies: QM/MM total energies and interaction energies - Gas_Phase_References: Gas-phase MoCo reference calculations - Correlation_Analysis: Pearson/Spearman correlations (10 metrics) - Table_S4_Hirshfeld_CT: Hirshfeld CT_lig and ΔE_Coulomb for all 50 snapshots - Table_S5_IGMH: IGMH δg_inter analysis (5 representative snapshots) - Hirshfeld_Summary: Cross-method validation (Mulliken vs Hirshfeld) QM/MM level: B3LYP-D3BJ/def2-SVP with RIJCOSX and electrostatic embedding (ORCA 6.1.0). Five flavonoids: apigenin, kaempferol, quercetin, morin, naringenin. 10 MD snapshots per compound (10-100 ns), 50 calculations total.

Aouladali, Amal · Alaoui, Souad · Hnini, Abdelhalim

4 files · 491 KB · zipdeclared

Replication code and measured artifacts for KeystrokeAuthChain: a keystroke-dynamics continuous-authentication Transformer evaluated on the public CMU Killourhy-Maxion dataset (EER 7.47%), coupled to an on-chain audit layer that anchors each authentication decision on the Ethereum Sepolia testnet for non-repudiation and third-party-verifiable auditing. Includes the recognition pipeline, paired baselines, significance tests, the audit smart contracts and gas measurements, and the real end-to-end anchoring run (10 genuine decisions, on-chain decisionHash verified 10/10). The CMU dataset is not redistributed here (see data/README.md inside the archive).