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Objectives: To present one case report of a patient who presented with facial erythema post dermal filler injections. Methodology: This is an observatory descriptive case report study. Results: A 23 …

Objectives: To present one case report of a patient who presented with facial erythema post dermal filler injections. Methodology: This is an observatory descriptive case report study. Results: A 23 year old female presented with bilateral cheek redness post dermal filler injection. She was managed with topical steroids, oral antihistamine and ice pack compression. Conclusion: Dermal fillers are commonly done cosmetic procedures in today’s time mainly because the results post procedure are immediate. But one must also be aware of the side effects it may have including allergic or inflammatory reactions. This report highlights one of the adverse effects of dermal fillers and how it can be possibly managed.

Reviewer-oriented reproducibility repository for a locus-resolved, quantitative integrative analysis of the Gli3 regulatory landscape in mouse limb development. The repository is organized into figure…

Reviewer-oriented reproducibility repository for a locus-resolved, quantitative integrative analysis of the Gli3 regulatory landscape in mouse limb development. The repository is organized into figure- and supplement-specific modules and includes processed/derived data tables, scripts, provenance notes, and manuscript-ready figure/table submission bundles. This archived release corresponds to version v1.0-BMCGenomics-submission and GitHub commit 8b7d9e3.

Abstract Mango (Mangifera indica) is one of the most important fruit crops, but its productivity is often affected by insect pests, particularly mango hoppers (Amritodus atkinsoni), which are highly …

Abstract Mango (Mangifera indica) is one of the most important fruit crops, but its productivity is often affected by insect pests, particularly mango hoppers (Amritodus atkinsoni), which are highly active during the flowering stage. These pests feed on plant sap, leading to flower drop, reduced fruit set, and ultimately lower yield. Farmers commonly rely on chemical insecticides for quick control; however, their excessive use raises concerns related to environmental safety, pest resistance, and export quality.The present study evaluates the effectiveness of Azadirachtin, a neem-based biopesticide derived from (Azadirachta indica), in managing mango hopper populations. Different concentrations of Azadirachtin were assessed and compared with other management approaches, including biological control agents and conventional chemical practices, under field conditions. Observations were recorded at regular intervals to determine changes in hopper population and crop response.The findings indicated that chemical insecticides showed the highest immediate reduction in hopper population. However, Azadirachtin also demonstrated a significant decrease in pest numbers compared to untreated plants, especially at higher concentrations. Although its action was relatively slower, it effectively reduced feeding activity and interfered with the growth and development of the insects. In addition, Azadirachtin contributed to maintaining crop health and yield while minimizing harmful environmental effects.In conclusion, Azadirachtin can be considered a reliable and eco-friendly alternative for the management of mango hopper. While it may not completely replace chemical pesticides, it plays an important role in integrated pest management and supports sustainable mango cultivation practices.

The data provided is part of the publication Impact of Hydrogen Blending Constraints on Electrolyser Operation and Hydrogen Production Costs: A Case Study of a Regional Gas Grid Section in Austri…

The data provided is part of the publication Impact of Hydrogen Blending Constraints on Electrolyser Operation and Hydrogen Production Costs: A Case Study of a Regional Gas Grid Section in AustriaThe data contains simulation inputs and results for dynamic gas grid simulations with DynANA as well as results of the dispatch optimisation with IESopt DynANA simulation inputs and outputs Model topology (pipes, nodes) Nodal timeseries of gas demand Timeseries of H2 injection profile for upstream electrolyser Nodal timeserie of pressure and hydrogen concentration IESopt optimization results Data for upstream electrolyser and downstream electrolyser (three electricty price years and three injection constraint cases) Timeseries of electrolyser operation, grid feed-in and trailer filling

Ushbu matnda global axborot maydoni va uning asosiy tarkibiy qismlari, shuningdek, axborot iqtisodiyoti, raqamli iqtisodiyot, kreativ iqtisodiyot, internet va tarmoq iqtisodiyoti tushunchala…

Ushbu matnda global axborot maydoni va uning asosiy tarkibiy qismlari, shuningdek, axborot iqtisodiyoti, raqamli iqtisodiyot, kreativ iqtisodiyot, internet va tarmoq iqtisodiyoti tushunchalari batafsil bayon qilinadi. Axborotkommunikatsion texnologiyalarning iqtisodiyotdagi roli, yangi raqamli texnologiyalar va innovatsiyalar natijasida yuzaga kelayotgan iqtisodiy va ijtimoiy jarayonlar tahlil qilinadi. Matnda shuningdek, bilim iqtisodiyoti va ijodiy iqtisodiyotning ahamiyati va o‘zaro bog‘liqligi ham ko‘rsatib o‘tilgan. 

Based on data from eight leading commercial banks in Uzbekistan, this article provides anempirical assessment of the state of internal audit during 2020–2024. It examines organisational capacity…

Based on data from eight leading commercial banks in Uzbekistan, this article provides anempirical assessment of the state of internal audit during 2020–2024. It examines organisational capacity, auditcoverage, the implementation of recommendations, the dynamics of identified deficiencies, and the level ofcompliance with the relevant domains of international standards. Alongside the progress observed, the findingsidentify several systemic challenges, including resource constraints, partial implementation of the risk-basedapproach, limited digitalisation, and insufficient development of quality assurance programmes. Based on theresults, recommendations are proposed for commercial banks and the supervisory authority to support thealignment of internal audit practices with international standards.

Dataset accompanying the work "Characterising AlphaFold 3's ability to predict T cell antigen specificity". The provided data is one tarball split into multiple parts. To recreate the original file, r…

Dataset accompanying the work "Characterising AlphaFold 3's ability to predict T cell antigen specificity". The provided data is one tarball split into multiple parts. To recreate the original file, run the command "cat tcr-pmhc-predicted-structures.tar.gz.part.* > tcr-pmhc-predicted-structures.tar.gz". This tarball can then be uncompressed and extracted using "tar -vxzf tcr-pmhc-predicted-structures.tar.gz".    

Coronary artery disease is one of the leading causes of morbidity and mortality worldwide, with X-ray coronary angiography serving as the clinical gold standard for diagnosis and intervention planning…

Coronary artery disease is one of the leading causes of morbidity and mortality worldwide, with X-ray coronary angiography serving as the clinical gold standard for diagnosis and intervention planning. Accurate segmentation of coronary arteries is essential for quantitative analysis, assessment of stenosis severity, and reliable clinical decision-making. In current clinical practice, coronary artery evaluation largely depends on manual or visual interpretation by cardiologists. This process is time-consuming, subjective, and affected by inter-observer variability, particularly in angiograms characterized by low contrast, image noise, and complex vascular structures. To overcome these challenges, automated segmentation methods based on deep learning have emerged as a promising solution. In this study, an automated pipeline for coronary artery segmentation in X-ray angiograms is proposed and evaluated using four deep learning architectures: U-Net, U-Net++, U-Net3+, and nnU-Net. A unified experimental framework incorporating standardized data organization, image preprocessing, and k-fold cross-validation is employed. Model performance is assessed using Dice coefficient, Intersection over Union, precision, and recall. The results show that U-Net++ achieved the highest segmentation accuracy with a Dice score of 0.724, compared to 0.671 for U-Net, 0.716 for U-Net3+, and 0.712 for nnU-Net. These findings confirm that modern U-Net-based architectures can provide reliable and reproducible coronary artery segmentation under consistent evaluation conditions.

Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und die Betreiber der AKTIN-Infrastruktur und des Notaufnahmeregisters bereitgestellt. Der Datensatz beinhaltet ag…

Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und die Betreiber der AKTIN-Infrastruktur und des Notaufnahmeregisters bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI), sowie hitzeassoziierte Notaunfahmevorstellungen (HEAT). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.