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Rosa canina L. (Rosaceae), широко известная как шиповник собачий, является ценным лекарственным растением, содержащим фенольные соединения, флавоноиды, каротиноиды, органические кислоты, витамины, жир…

Rosa canina L. (Rosaceae), широко известная как шиповник собачий, является ценным лекарственным растением, содержащим фенольные соединения, флавоноиды, каротиноиды, органические кислоты, витамины, жирные кислоты и минеральные элементы. Минеральный состав препаратов растительного происхождения является важным показателем при оценке их химических характеристик, качества и потенциального фармацевтического применения. Целью настоящего исследования являлось изучение макро- и микроэлементного состава сухого экстракта, полученного из семян Rosa canina L., выращенной в условиях Узбекистана.

В статье исследуется правовая природа конфиденциальности двусторонних переговоров по доступу на рынки товаров и услуг в процессе присоединения государств к Всемирной торговой организации (ВТО). Рассма…

В статье исследуется правовая природа конфиденциальности двусторонних переговоров по доступу на рынки товаров и услуг в процессе присоединения государств к Всемирной торговой организации (ВТО). Рассматривается соотношение конфиденциальности переговорного процесса с принципом прозрачности многосторонней торговой системы. Особое внимание уделяется механизму последующей многосторонней консолидации двусторонних договорённостей и влиянию принципа режима наибольшего благоприятствования на переговорную позицию присоединяющегося государства. Обосновывается вывод о том, что конфиденциальность отдельных стадий переговоров не отрицает принцип прозрачности, а выполняет самостоятельную процессуальную функцию, обеспечивая возможность эффективного согласования условий присоединения и защиту переговорного пространства государства-кандидата.    

The Nigerian agricultural ecosystem and its allied critical infrastructure face compounding threats from vandalism, climate-induced disasters, and terrorism. The Nigerian Security and Civil Defence Co…

The Nigerian agricultural ecosystem and its allied critical infrastructure face compounding threats from vandalism, climate-induced disasters, and terrorism. The Nigerian Security and Civil Defence Corps (NSCDC) is statutorily mandated to secure these assets, yet its workforce performance planning remains largely heuristic. This study develops a Constrained Fuzzy Multi-Objective Goal Programming (CFMOGP) model to optimize workforce resource allocation in the NSCDC South-West zone. Utilizing summary statistics from 191 respondents from NSCDC South-west Zone across 60 Likert-scale items, we transform ordinal data into fuzzy membership scores to mitigate cognitive bias. We formalize three competing objectives: Operational & AntiVandalization Efficiency (𝑍1), Disaster-Terrorological Response Readiness (𝑍2), and Workforce Motivation (𝑍3). Through rigorous analytical proofs, we establish the existence of a Pareto-optimal fuzzy solution and its Lipschitz continuity under fiscal perturbations. Applying an Analytic Hierarchy Process (AHP), we simulate baseline, specialized, and balanced policy scenarios, culminating in a 10% fiscal shock sensitivity analysis. Results indicate that a hybrid policy; enforcing a 26% welfare floor and a 45% strategic ring-fence for ICT and disaster training yields optimal agro-infrastructural security outcomes without triggering institutional decay. This manuscript provides a mathematically tractable, TetFund-aligned framework for paramilitary workforce optimization.

First public release of SurfaceCode, an explicit 2.5D ideal-MHD code for the near-surfacelayers of a classical T Tauri star. This is the code version used for the paper*Can accretion-driven waves surv…

First public release of SurfaceCode, an explicit 2.5D ideal-MHD code for the near-surfacelayers of a classical T Tauri star. This is the code version used for the paper*Can accretion-driven waves survive the journey along the surface of T Tauri stars?*(L. Gehrig, submitted to A&A). ## Contents- **Solver** (`src/`): finite-volume ideal MHD with gravity, HLL fluxes, MUSCL/minmod  reconstruction, SSP-RK2 time stepping, GLM divergence cleaning, and a well-balanced  treatment that keeps the stratified background static to machine precision.- **Runs** (`runs/`): validation tests (shock tubes, stratified-wave test, numerical  dissipation floor), pulse calibration, the production single-pulse and continuously  driven runs, the resolution ladder, and a run with a boundary energy ledger and an  unperturbed control.- **Data** (`data/`): the near-surface background stratification of the fiducial star.- **Analysis and figures** (`analysis/`, `Paper/figscripts/`): scripts that produce the  diagnostic plots and the paper figures from the run output.- **Solar benchmark** (`SolarRuns/`): the same solver applied to the 2006 December 6  Moreton wave. ## RequirementsJulia ≥ 1.10 (standard library only) and Python 3 with numpy, matplotlib and scipy. ## NotesThis is research software under active development. It has been validated for thesetups described in the paper, but it may still contain errors or limitations. See theREADME for the layout, parameters and output formats.

Abstract: The transition to renewable energy (RE) is now a global necessity to mitigate climate change and reduce greenhouse gas emissions. Despite declining technology costs, private investment in RE…

Abstract: The transition to renewable energy (RE) is now a global necessity to mitigate climate change and reduce greenhouse gas emissions. Despite declining technology costs, private investment in RE projects remains constrained by multiple barriers. While previous research has identified numerous barriers to renewable energy investment, most studies have focused on individual categories of barriers or specific national contexts. Consequently, there is still limited evidence providing an integrated assessment of the relative importance of different barrier dimensions and comparing their prevalence between developed and developing countries. This study addresses this gap through a systematic synthesis of the existing literature. Using the PRISMA methodology, this study systematically reviews 26 peer-reviewed articles indexed in Scopus and Web of Science to identify and synthesize the barriers limiting private investment in renewable energy projects. The identified barriers were grouped into six dimensions: economic and financial, governance and institutional, market-related, geographical and ecological, technological, and sociocultural. The review shows that governance and institutional barriers are the most frequently reported, appearing in 77% of the selected studies (20/26), followed by economic and financial barriers (69%, 18/26), market-related barriers (62%, 16/26), sociocultural barriers (58%, 15/26), technological barriers (54%, 14/26), and geographical and ecological barriers (46%, 12/26). The comparison also highlights clear differences between economic contexts. Developing countries are primarily constrained by limited access to finance, weak institutional capacity, and restricted investment resources, whereas developed countries more frequently face challenges related to regulatory complexity, market design, and public acceptance of renewable energy projects. These findings suggest that policies aimed at mobilizing private investment should be tailored to national contexts by combining stable regulatory frameworks, targeted financial instruments, and stronger institutional support to accelerate the deployment of renewable energy.

Listening Forward is an interactive web instrument for speculative soundscapes by Anna Troisi. This release archives the version of the instrument described in the 2026 Leonardo manuscript Listening F…

Listening Forward is an interactive web instrument for speculative soundscapes by Anna Troisi. This release archives the version of the instrument described in the 2026 Leonardo manuscript Listening Forward: Tuning Possible Sonic Futures through Artistic Annotation and Machine Learning. The instrument combines environmental recordings, artistic annotation and scenario tagging, machine-learning-based audio analysis, and an interactive tuning interface.

A series of free-to-use models to accompany the text Dynamic Ecology (Flynn, 2026) DOI: 10.5281/zenodo.23081075

Near-Fault Observatories (NFOs) are natural laboratories situated at or near active faults experiencingcomplex geophysical processes, often close to densely populated urban areas. NFOs offer researche…

Near-Fault Observatories (NFOs) are natural laboratories situated at or near active faults experiencingcomplex geophysical processes, often close to densely populated urban areas. NFOs offer researchers from multiple disciplines access to rich, reusable datasets for generating scientificproducts. This facilitates improved understanding of the multi-scale physical and chemical processesdriving earthquake generation—a goal attainable only through continuous, long-term, high-resolutionmultidisciplinary data acquisition and consistent application of state-of-the-art processing techniques. Eight NFOs (and one under evaluation) in Europe have been identified by the European Plate ObservingSystem (EPOS) as long-term Research Infrastructures. NFOs target the enhanced understanding of themechanics of earthquakes to unravel the anatomy of complex seismogenic faults.The TRANSFORM² project has the ambitious goal to improve and transform the existing NFOs, paving theway for the next generation of NFOs across Europe. This will be achieved by: ● Evaluate state-of-the-art sensors.● Accelerate development of promising new sensors.● Develop ML-powered workflows for real-time detection, location, and characterization ofseismicity.● Create next-generation Earthquake Early Warning (EEW) paradigms and validate their societalimpact.● Strengthen stakeholder & decision-maker engagement.● Position existing NFOs as open, high-quality test-beds.● Identify sustainable funding pathways and provide recommendations to national authorities and theEuropean Commission for long-term RI support. Following the half time of the project, the design and testing of cutting-edge sensors, along with thedevelopment of automatic workflows for the detection, characterization of seismic events and sequences,and implementation of EEW systems, are actively being carried out and extended to a growing number ofNFOs. Concurrent deployment of the principal sensors, which are vital for supporting and enabling theadvancements, is already in progress. Finally, a ‘white book’ will be created to document how data, products and services from the nextgeneration Research Infrastructure (RI) can be exploited for the benefit of different target stakeholders.