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AI-driven services for comfort, energy efficiency  and grid-ready building operation Smart automation and control services au tomatically generate optimisation strategies adapted to different bui…

AI-driven services for comfort, energy efficiency  and grid-ready building operation Smart automation and control services au tomatically generate optimisation strategies adapted to different buildings and climates. They improve comfort, reducing energy consu mption, make better use of renewable energy and enable buildings to provide flexibility to the grid through an interoperable, service-ba sed architecture

John Wick: Chapter 2 is a 2017 action film; it serves as the sequel to the 2014 film John Wick and the prequel to the 2019 film John Wick: Chapter 3 – Parabellum. The film follows John Wick as h…

John Wick: Chapter 2 is a 2017 action film; it serves as the sequel to the 2014 film John Wick and the prequel to the 2019 film John Wick: Chapter 3 – Parabellum. The film follows John Wick as he carries out an assignment to assassinate a member of the High Table. Several scenes employ parallel editing to link distinct events involving the same protagonist—John Wick—a technique the filmmakers notably utilized in this installment. This study employs a qualitative approach based on the analysis and observation of the film, focusing specifically on spatial shifts and temporal manipulation within the parallel editing sequences. The findings indicate that John Wick: Chapter 2 extensively explores parallel editing throughout the film, demonstrating the technique's capacity to manipulate space and time. The study reveals that a film need not follow a strictly chronological order; parallel editing can be used to interweave three separate events involving the same protagonist without risking audience confusion regarding the narrative, spatial context, or timeline.

 This article examines the role of financial analysis in assessing the business activity of an enterprise and its importance in improving the efficiency of financial and economic management. The …

 This article examines the role of financial analysis in assessing the business activity of an enterprise and its importance in improving the efficiency of financial and economic management. The study considers the theoretical and methodological foundations of financial analysis and identifies the key indicators used to evaluate business activity, including asset turnover, accounts receivable and payable turnover, inventory turnover, capital efficiency, profitability, liquidity, and financial stability. Particular attention is paid to the relationship between financial performance and the level of business activity of an enterprise. The article highlights the importance of financial analysis in identifying internal reserves, detecting negative trends, evaluating the efficiency of resource utilization, and supporting managerial decision-making.

New features emd_fei-format: Add support for reading EELS datasets. (#522) Enhancements TriVista: migrate to rsciio.utils.xml.XmlToDict for XML parsing and dictionary conversion to improve maintain…

New features emd_fei-format: Add support for reading EELS datasets. (#522) Enhancements TriVista: migrate to rsciio.utils.xml.XmlToDict for XML parsing and dictionary conversion to improve maintainability. (#531) Images loaded from Velox EMD files now keep the dtype used to store the data in the file (e.g. uint16) instead of being systematically converted to float64. This reduces memory usage, makes non-lazy loading consistent with lazy loading, and significantly speeds up reading image stacks whose frames are chunked individually in the file. (#476) EDAX TEAM/Genesis: support line scan (.lsd) data (#485) The zspy writer now consolidates metadata by default using zarr.convenience.consolidate_metadata. This bundles all individual .zattrs, .zarray and .zgroup metadata files (~20+ files for a typical signal) into a single .zmetadata entry, reducing the number of HTTP requests needed to open a file from remote storage by an order of magnitude. Set consolidate=False to disable this behaviour (e.g. for interactive workflows where metadata is inspected manually). (#525) Bug Fixes Support ISO 8601 UTC-offset strings in serial-date conversion and make timezone tests platform independent. (#341) Modified empad reader to parse scan sizes from the raw file name following the pattern "scan_xaaa_ybbb.raw", where "aaa" and "bbb" represent the scan sizes in the x and y dimensions, respectively. (#513) Fix lazy loading for NCEM EMD data to avoid eager reads (#526) Fix closing .hspy file when loaded lazily on free-threaded Python. (#533) Fix KeyError: 'XmlClassName' when reading Bruker BCF files with a selected-element region that has no name attribute. (#541) Support the Greek small letter mu (U+03BC) when saving TIFF files. (#549) Maintenance Bump scikit-image requirement to >=0.21.0 and remove vendored code from scikit-image. Dask, numpy, imageio, numba and tifffile mininum-version requirement are also updated to be compatible with scikit-image requirements. (#527) Add a .mailmap file to consolidate duplicate author identities in the git history, fixing contributor attribution for tools that respect mailmap. (#547) Fix test failure related to the change of micro unicode character used by pint in version 0.26.0. (#549) Drop python 3.10 and add python 3.15. Bump mrcz requirement to >=0.6.0, which adds support for numpy 2.0. (#550)

What's Changed Security fixes: same-major dependency bumps for the HIGH/CRITICAL CVEs found in the 2026-09-23 Trivy scan: Jackson 2.21.7 and PostgreSQL JDBC 42.7.12. Also migrated to Kotlin 2.3.20, r…

What's Changed Security fixes: same-major dependency bumps for the HIGH/CRITICAL CVEs found in the 2026-09-23 Trivy scan: Jackson 2.21.7 and PostgreSQL JDBC 42.7.12. Also migrated to Kotlin 2.3.20, radar-commons 1.2.7 and ManagementPortal (radar-auth, managementportal-client) 3.0.1. The CVEs and how each was fixed are listed in the PR. By @pvannierop in https://github.com/RADAR-base/radar-jersey/pull/120 Guidance and examples for coroutine services and request-scope patterns by @this-Aditya in https://github.com/RADAR-base/radar-jersey/pull/105 CI: replace the Snyk scans with Trivy by @pvannierop in https://github.com/RADAR-base/radar-jersey/pull/121 Important Notes radar-jersey is now built with Kotlin 2.3.20. Consumers need a Kotlin 2.x compiler; Jackson 2.21 requires it too. Full Changelog: https://github.com/RADAR-base/radar-jersey/compare/v0.12.8...v0.12.9

1.10.0 (2026-10-06) ✨ Features filaments, instance and panoptic segmentations, annotation tools (#49) (427f127) 🐞 Bug Fixes keep pick ids, scores and orientations on save (#47) (9ada249)

Analysis code accompanying the main paper and online supplement of “Reference Observability and Journal Universe Choice in Open Reconstructions of Recursive Journal Metrics”. The package s…

Analysis code accompanying the main paper and online supplement of “Reference Observability and Journal Universe Choice in Open Reconstructions of Recursive Journal Metrics”. The package starts from precomputed Network Factor (NF) and Article Network Score (ANS) inputs released by Opindx.org. It provides downstream statistical analysis, table and figure code, an independently generated fictional demonstration, full open Leiden/CWTS-universe scores, additional open Norwegian-universe nodes, and input and provenance documentation. No proprietary Clarivate data, commercial journal roster or crosswalk, empirical benchmark outputs, or manuscript files are included. Empirical reproduction requires legitimately held benchmark inputs and the author-specific inputs described in docs/INPUTS.md. Fictional demonstration outputs do not reproduce the paper results.

MEAM-OWL v1.0.0 Release This is the initial release of MEAM-OWL (Motif Enrichment Analysis Modules On the Web (Lite)) MEAM-OWL is a lightweight and browser-based exploratory tool designed to analyze D…

MEAM-OWL v1.0.0 Release This is the initial release of MEAM-OWL (Motif Enrichment Analysis Modules On the Web (Lite)) MEAM-OWL is a lightweight and browser-based exploratory tool designed to analyze DNA motif enrichment (k-mers) and their associations with gene expression data. Key Features Two Analysis Modes: Mode A: Target vs. Background sequence enrichment analysis (HOMER-like hypergeometric test or Mann-Whitney U test). Mode B: Expression-based rank or correlation analysis (DRIMust model or Pearson correlation) paired with transcriptomic data. Sequence Extraction Engine: Directly loads genome FASTA and GFF3 annotation files to extract regions of interest such as gene (exon + intron) regions, mRNA (exon) regions and promoters. Integrated Plant & Universal Motif Databases: Cross-reference discovered k-mers with known motifs from JASPAR, PLACE, and CIS-BP. Zero Installation: Built with pure client-side JavaScript. No servers, no command-line tools, and no coding required. Quick Start Download the attached assets (meam-owl-v1.0.0.zip). Extract the package on your local computer. Open index.html in any modern desktop browser (e.g., Chrome, Firefox, Safari, Edge). Load your sequence / expression data and start exploring! For detailed instructions on parameters, file input formats, and algorithm citations, please refer to the README.md included in the package.

In a market economy, secured parties or secured creditors occupy a central role in ensuring credit safety and fostering capital circulation. However, the effective protection of their rights during ci…

In a market economy, secured parties or secured creditors occupy a central role in ensuring credit safety and fostering capital circulation. However, the effective protection of their rights during civil judgment enforcement for business and commercial judgments in Vietnam remains subject to numerous limitations, particularly given the rapid digital transformation underway in judicial activities. This article analyzes the theoretical foundations of protecting secured parties' rights in civil judgment enforcement, examines existing legal provisions under the 2025 Law on Civil Judgment Enforcement, and identifies inadequacies related to priority of payment, collateral disposal, digital enforcement, and the handling of digital assets, while drawing on relevant international practices. On this basis, the paper offers recommendations to refine the legal framework and develop a digital enforcement model aligned with judicial reform and national digital transformation requirements.