Our Work

Adds the results of notebooks 08 (four-class comparison with Mohiuddin and Almogren) and 09 (tag-direction projection under HGS), regenerates all figures to match the paper, and updates the documentat…

Adds the results of notebooks 08 (four-class comparison with Mohiuddin and Almogren) and 09 (tag-direction projection under HGS), regenerates all figures to match the paper, and updates the documentation. The dataset is not included; scripts/download_data.py fetches and verifies it.

This updated version contains 7 new zipped files related to the manuscript entitled "Stretch versus shortening contractions subsequently decrease versus increase neural drive to the human tibialis ant…

This updated version contains 7 new zipped files related to the manuscript entitled "Stretch versus shortening contractions subsequently decrease versus increase neural drive to the human tibialis anterior". The zipped files contain .mat data files of the analysed torque and EMG signals (stored as pid_analysed), the raw files used for decomposition (stored as pid_intensity_raw - formatted for MUedit) and the raw (stored as pid_intensity_decompraw) and edited (stored as pid_intensity_decomp) decomposition results from DEMUSE and MUedit separately (formatted for DEMUSE* - motor unit firing timestamps = MUPulses; EMG signals = SIG; *the raw output from MUeditraw is formatted for MUedit). Important abbreviations are indicated below: pid = unique ID assigned to each participant – note: P07 does not exist decomp = decomposition method, DEMUSE or MUedit intensity = contraction intensity, 20% or 40% of maximal voluntary torque condition = contraction condition, column 1=fixed-end reference, column 2=stretch-hold, column 3=shortening-hold

International Environmental Law stands at a crossroad, where its basic ideas and principles are massively coming at odds with the depth and demand of universal environmental catastrophe. Greatly based…

International Environmental Law stands at a crossroad, where its basic ideas and principles are massively coming at odds with the depth and demand of universal environmental catastrophe. Greatly based upon notions of state control, assent, and fragmented international agreement, the discipline has failed to respond to massive environmental degradation and biodiversity failure. The formation of the scientific notion of the ecological boundaries and limits has elevated the constraint by introducing a bunch of environmental thresholds and limits within which the humankind can remain secure. Developed by the Stockholm Resilience Centre, this framework uncovers crucial biodiversity dynamics like the massive ecological destruction, ecological threshold, poor land usage and change, and bio-geochemical cycles and hence introduces a novice standard beyond which the irreparable environmental damage sharply increases and spikes. While this model has gained impeccable speed and admiration among scientific and policy stakeholders, its ethical interpretation and application for international law remains questionable. This paper argues that adopting environmental limits within the scope and ambit of international environmental law calls for a thorough transformation from fragmented governance towards an obligatory structure of earth system governance.

ClassicalOrthogonalPolynomials v0.15.22 Diff since v0.15.21 Merged pull requests: Port Chebyshev-based roots algorithm for orthogonal polynomial expansions (#286) (@Copilot) Uplus (#289) (@dlfivefift…

ClassicalOrthogonalPolynomials v0.15.22 Diff since v0.15.21 Merged pull requests: Port Chebyshev-based roots algorithm for orthogonal polynomial expansions (#286) (@Copilot) Uplus (#289) (@dlfivefifty) Vector/matrix expand (#290) (@dlfivefifty) Support vector/matrix-valued expansions on a UnionDomain (#291) (@dlfivefifty) Closed issues: port over roots from ApproxFunOrthogonalPolynomials.jl (#285)

STATA .do file with instructions for accessing data from the Census Bureau and IPUMS websites and conducting analysis reported in manuscript titled "Community Composition and Naturalization Among U.S.…

STATA .do file with instructions for accessing data from the Census Bureau and IPUMS websites and conducting analysis reported in manuscript titled "Community Composition and Naturalization Among U.S. Immigrants from China, India, the Philippines, Korea, and Vietnam." STATA .dta file with binary indicator for whether each U.S. state provides public benefits to immigrants, based on 2014 Pew report (https://www.pew.org/en/research-and-analysis/issue-briefs/2014/09/mapping-public-benefits-for-immigrants-in-the-states).

O agronegócio é vetor central do desenvolvimento brasileiro: a safra de grãos 2025/26 é estimada em 360,11 milhões de toneladas, das quais 180,57 milhões…

O agronegócio é vetor central do desenvolvimento brasileiro: a safra de grãos 2025/26 é estimada em 360,11 milhões de toneladas, das quais 180,57 milhões de toneladas de soja, consolidando o país como maior produtor e exportador mundial da oleaginosa (CONAB, 2026). Goiás figura entre os quatro maiores produtores nacionais de grãos e Rio Verde (GO) ocupa a segunda posição entre os municípios brasileiros produtores de soja (IBGE, 2023), o que torna a região Sudoeste goiana um laboratório privilegiado para investigar a relação entre expansão agrícola, conservação do Cerrado e inserção competitiva em mercados internacionais. Simultaneamente, consolida-se uma nova arquitetura regulatória internacional que condiciona o acesso a mercados ao desempenho socioambiental das cadeias produtivas. O Regulamento (UE) 2023/1115 – conhecido como EUDR – proíbe a colocação no mercado europeu de soja, carne bovina, café, cacau, dendê, madeira, borracha e derivados oriundos de áreas desmatadas após 31 de dezembro de 2020, exigindo devida diligência com geolocalização das parcelas produtivas (UNIÃO EUROPEIA, 2023). Após sucessivas prorrogações e medidas de simplificação, o Regulamento (UE) 2025/2650 fixou a aplicação das obrigações para grandes e médios operadores em 30 de dezembro de 2026 e, para micro e pequenas empresas, em 30 de junho de 2027 (UNIÃO EUROPEIA, 2025).

The ETSI OpenOP initiative represents a significant step toward open, federated, and multi-domain 6G experimen tation. However, as these testbeds grow in complexity and scale, researchers face signifi…

The ETSI OpenOP initiative represents a significant step toward open, federated, and multi-domain 6G experimen tation. However, as these testbeds grow in complexity and scale, researchers face significant hurdles in experiment discovery, resource selection, and—most critically—reproducibility. Existing orchestration frameworks focus primarily on low-level resource management and deployment automation, leaving a ”semantic gap” in how experimentation knowledge is captured and reused. In this paper, we propose OpenOP-KG, a novel framework that introduces a semantic intelligence layer top of ETSI OpenOP. By modeling testbed resources, network capabilities, experimen tation workflows, and historical Key Performance Indicators (KPIs) within a unified Knowledge Graph (KG), OpenOP-KG enables intelligent experiment recommendation and automated reproducibility support. We define a semantic similarity model that allows researchers to discover reusable experiment templates and compatible infrastructure across federated domains. Further more, we introduce an AI-assisted ”Experiment Digital Memory” that captures systemic dependencies to ensure experiments re main reproducible even as underlying infrastructures evolve. Our evaluation, conducted using representative 6G experimentation scenarios, demonstrates that OpenOP-KG reduces experiment preparation effort by up to 45% and significantly enhances the reliability of cross-site experiment replication.

Satellite, in-situ hydrographical, and zooplankton abundance data collected in the Pacific Arctic Ocean during late summers from 2008 to 2021. Satellite data includes open-water duration, melt day, op…

Satellite, in-situ hydrographical, and zooplankton abundance data collected in the Pacific Arctic Ocean during late summers from 2008 to 2021. Satellite data includes open-water duration, melt day, open-water-period median surface temperature, open-water-period median surface chl a, and open-water-period cumulative primary production. The data is a second production analyzed by Dr. Amane Fujiwara. In-situ hydrographical data are water-column integrated mean temperature, water-column integrated mean salinity, and water-column integrated fluorescence at all sampling stations. Zooplankton abundance data is quantitative abundance for copepod species or other taxa collected by 330-µm mesh plankton nets. More detailed methodology is explained in the paper. Kim, J-H., E.J. Yang, Y.S. Kwon, S.-H Kang, A. Fujiwara, K. Matsuno (2026): Projected Future Distributions of Key Copepods in the Pacific Arctic Ocean to 2100. submitted to Limnol. Oceanogr.

Analysis code for a pooled NHANES study (1999-2018, 10 cycles) of blood lead, cadmium and mercury (plus selenium and manganese) and all-cause / cardiovascular mortality, including weighted Cox models,…

Analysis code for a pooled NHANES study (1999-2018, 10 cycles) of blood lead, cadmium and mercury (plus selenium and manganese) and all-cause / cardiovascular mortality, including weighted Cox models, quantile g-computation, Bayesian kernel machine regression, restricted cubic splines and sensitivity analyses.

Conventional black-box predictive models consistently exhaust the limited memory boundaries of industrial edge microcontrollers. Massive parameter footprints and opaque decision pathways render standa…

Conventional black-box predictive models consistently exhaust the limited memory boundaries of industrial edge microcontrollers. Massive parameter footprints and opaque decision pathways render standard neural networks highly vulnerable to out-of-distribution catastrophic failures. The proposed physics-informed symbolic artificial intelligence architecture formulates transparent degradation equations tailored directly to individual hardware characteristics. An autonomous generator fuses fundamental electrical constraints with a localized polynomial expansion to produce extreme low-dimensional operational logic. Empirical evaluations utilizing the NASA Ames repository demonstrate the absolute elimination of cross-run extrapolation errors. The customized equations require a strict maximum footprint of 140 Bytes and execute at a constant O(1) inference complexity. The explicit physical formulation reduces total execution energy consumption by a factor of 2.8 compared to baseline multi-layer perceptrons, while maintaining a 0.9994 accuracy score under severe data scarcity. Synthetic noise injection tests confirm supreme operational resilience against severe sensor distortions. Absolute white-box interpretability provides field engineers with the direct capability to audit the precise prognostic logic prior to chip deployment. The decentralized deployment of deterministic diagnostic intelligence establishes a highly robust foundation for sustainable smart manufacturing ecosystems.