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At present, medicinal products derived from medicinal plants represent an important area of pharmaceutical research and development. The development of such products requires several stages, including…

At present, medicinal products derived from medicinal plants represent an important area of pharmaceutical research and development. The development of such products requires several stages, including the detailed study of the medicinal plant, investigation of its chemical composition, evaluation of biologically active compounds, and assessment of its pharmacological properties. The comprehensive study of medicinal plants provides a scientific basis for the development of new herbal preparations and their subsequent application in pharmaceutical practice. The first step in this study was to analyze the selected medicinal plant, Rosa canina L., in accordance with the research objectives. Numerous researchers have investigated the chemical composition, biological activity, and medicinal properties of Rosa canina L. In this article, we summarize and compare the available scientific data concerning the pharmacological properties of Rosa canina L., with particular attention to studies relevant to medicinal plant research and its potential pharmaceutical applications in Uzbekistan.

Reference implementation of the AB-constrained Gaussian Switching System (GSS) framework: a fast constant-gain exact optimal filter under the AB structural assumption, with support for a known exogeno…

Reference implementation of the AB-constrained Gaussian Switching System (GSS) framework: a fast constant-gain exact optimal filter under the AB structural assumption, with support for a known exogenous input (deterministic command), supervised and semi-supervised parameter estimation (Baum-Welch EM), and Monte-Carlo benchmarks including real-data studies (vehicle dynamics and NOAA ENSO indices).The repository also contains the reference implementations (exact K^N mixture filter, order-1 IMM, GPB2) and the experiment script backing the numerical section of the companion paper on the exactness domains of the IMM and GPB2 filters.

Concrete is a mixture of cement, sand, aggregate, and water. High-strength concrete is that concrete which is a mixture of normal concrete with some chemical and mineral admixtures with the lowest wat…

Concrete is a mixture of cement, sand, aggregate, and water. High-strength concrete is that concrete which is a mixture of normal concrete with some chemical and mineral admixtures with the lowest water-cement ratio. High-strength concrete demands a lower water-cement ratio for long-term performance and durability. This paper presents the experimental study of fourteen mix designs targeting the M60 and M70 grade trial mixes proportioned as per IS 10262:2019, by binary and ternary blends at a water-cement ratio between 0.25 and 0.32. The only compressive strength was performed on cubes for 7, 14, and 28 days. Binder content shows the strongest positive results with 28-day strength. The ternary blends of 15% GGBS, 10% metakaolin, and 10% silica fume produced the highest 28-day strength. These results provide a quantitative basis for selecting additional cementing material combinations.

This record contains custom Fiji/ImageJ macros and workflow documentation for quantifying nuclear SMAD2/3 fluorescence in A549 cells, developed for the study “CRMP2 restrains TGFβ signaling…

This record contains custom Fiji/ImageJ macros and workflow documentation for quantifying nuclear SMAD2/3 fluorescence in A549 cells, developed for the study “CRMP2 restrains TGFβ signaling by limiting SMAD2/3 nuclear accumulation.” The workflow supports batch image analysis, identification of nuclear regions of interest (ROIs), quality-control review, manual ROI correction, and export of approved fluorescence measurements. Nuclear ROIs are identified using the DAPI channel and used to measure SMAD2/3 fluorescence in the corresponding fluorescence channel. The macros were used to analyze CRMP2 wild-type and CRMP2-knockout A549 cells with and without TGFβ1 treatment. The accompanying README_WORKFLOW.txt describes the workflow and execution order. This record contains analysis code and documentation; microscopy images are not included.

This is the raw data used in the figures of the manuscript titled EVALUATION OF CANDIDATE HIGH-TEMPERATURE PHOSPHORS FORINDUSTRIAL TEMPERATURE MEASUREMENTS ABOVE 1000 °C

Data and code for the article 'Lexical-postlexical interaction: The reorganisation of pitch prominence in Persian calling intonation'. 

What's Changed fix: read big OpenSlide regions in OpenSlide's own 4096 px chunks by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/72 fix: fastslide reader reads after detach and pads region…

What's Changed fix: read big OpenSlide regions in OpenSlide's own 4096 px chunks by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/72 fix: fastslide reader reads after detach and pads regions past the edge by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/73 fix: pickle readers and tile datasets for spawned DataLoader workers by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/74 feat: deprecate color_norm and ColorNormalizer, to be removed in 0.13.0 by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/75 fix: keep the CPU torch index out of git installs of wsidata by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/76 docs: image_size resizes tiles, and is ignored with a TileSpec by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/77 refactor: remove the zarr v2 reader store, unreachable with spatialdata's zarr>=3 by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/78 fix: open_wsi passes extra keyword arguments to the reader by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/79 fix: keep set_mpp and set_bounds values when a store is reopened by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/80 fix: align features to tiles by tile_id; graph_data takes sparse arrays by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/81 fix: agg_wsi and concat_feature_anndata find scene stores and name slides by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/82 fix: store set_bounds in the slide properties attrs, not a table by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/84 fix: pass sdata_formats, not the deprecated format, to SpatialData.write by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/83 fix: to_datatree reads exact level pixels and survives pickling by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/87 fix: require spatialdata>=0.7.3 to write images with ome-zarr>=0.14 by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/86 fix: refuse to overwrite a store that lazily loaded elements read from by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/85 fix: open_wsi keeps slides out of each other's stores by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/88 fix: write() falls back to the path when the WSIData has no store by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/89 fix: safer overwrites of a store, and support for anndata 0.13 and pandas 3 by @Mr-Milk in https://github.com/rendeirolab/wsidata/pull/90 Full Changelog: https://github.com/rendeirolab/wsidata/compare/v0.11.1...v0.12.0

This dataset contains derived trade and freight-emissions data and computational tools for examining supplier reallocation under fixed commodity import quantities. The regional data cover imports into…

This dataset contains derived trade and freight-emissions data and computational tools for examining supplier reallocation under fixed commodity import quantities. The regional data cover imports into Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan, with transport-project calculations for 2018 and 2019.The package includes country and commodity scenario tables, supplier contributions, sensitivity calculations, saved regression coefficients and covariance matrices, and a standalone procurement calculator. The calculator uses baseline supplier quantities, delivered-price changes, transport emissions intensities and substitution parameters to calculate direct route savings, procurement-related emissions changes and net savings. It includes seven synthetic worked examples, a complete 144-combination parameter grid, and derived inputs for twelve regional scenario replays comprising 125,760 supplier records. A separate calculation reproduces forty Caspian-segment emission-factor scenarios.Technical documentation describes the variables, units, input construction, computational scope and external sources. Verification scripts and checksums support reproducible use. The package starts from derived inputs; original raw trade databases, full network reconstruction and observation-level regression re-estimation are outside its scope. The regional inputs and synthetic examples are identified separately.

Python library for pairwise Kalman filtering and smoothing on Gaussian pairwise Markov models: linear pairwise Kalman filter (PKF), nonlinear extensions (EPKF, UPKF, pairwise particle filter), linear …

Python library for pairwise Kalman filtering and smoothing on Gaussian pairwise Markov models: linear pairwise Kalman filter (PKF), nonlinear extensions (EPKF, UPKF, pairwise particle filter), linear smoothers, EM learning and back-action tests.

Plant phenotyping is the quantitative analysis of plant structures, functions, and performance, measuring traits like growth, yield, and stress acclimation. It combines sensing technologies with AI to…

Plant phenotyping is the quantitative analysis of plant structures, functions, and performance, measuring traits like growth, yield, and stress acclimation. It combines sensing technologies with AI to evaluate how genotypes respond to environmental conditions—a crucial process for plant breeding and enhancing crop resilience. The protocol described here is suitable for the PlantEye F500 laser scanning system located within the PHENOPLANT phenotyping platform at the University of Turin. The system enables non-destructive measurement of plant morphological traits using 3D laser scanning and multispectral imaging.