JAS Technologies (Poland)

BACKGROUND: The chromatin-remodeling enzyme BRG1 (brahma-related gene 1) regulates gene expression in a variety of rapidly differentiating cells during embryonic development. However, the critical genes that BRG1 regulates during lymphatic vascular development are unknown. METHODS: We used genetic and imaging techniques to define the role of BRG1 in murine embryonic lymphatic development, although this approach inadvertently expanded our study to multiple interacting cell types. RESULTS: We found that omental macrophages fine-tune an unexpected developmental process by which erythrocytes escaping from naturally discontinuous omental blood vessels are collected by nearby lymphatic vessels. Our data indicate that circulating fibrin(ogen) leaking from gaps in omental blood vessels can trigger inflammasome-mediated IL-1β (interleukin-1β) production and secretion from nearby macrophages. IL-1β destabilizes adherens junctions in omental blood and lymphatic vessels, contributing to both extravasation of erythrocytes and their uptake by lymphatics. BRG1 regulates IL-1β production in omental macrophages by transcriptionally suppressing the inflammasome trigger RIPK3 (receptor interacting protein kinase 3). CONCLUSIONS: in embryonic macrophages leads to excessive IL-1β production, erythrocyte leakage from blood vessels, and blood-filled lymphatics in the developing omentum. Altogether, these results highlight a novel context for epigenetically regulated crosstalk between macrophages, blood vessels, and lymphatics.

The paper presents the application of the RFID technology in the international system of the European Union (EU) border control. The proposed architecture consists of computerized portable units (equipped with specialized devices for data acquisition) carried by border officers and the server cloud infrastructure. Among other details of the proposed system (such as QR codes or images of people trying to enter EU), RFID information is critical for the border control procedure. It must be read from passports and confronted against local and remote data, stored in the central database The paper presents the general architecture of the proposed border control system. The structure of the application, responsible for connecting the RFID reader with the portable computer and communicating with the Internet database via the Web Services technology is presented. Introduced use cases show functionality of the system, focusing on the acquisition and analysis of the RFID information.

This paper presents the interdisciplinary project aimed at detecting the undesired or dangerous behavior of persons in the confined institutions such as prisons or wards, based on the video streams provided by the CCTV cameras. Currently, there are IT systems working in such areas, but their efficiency is limited, forcing the operator to focus his/her attention on every image separately. Design of a system for autonomous detection of anomalous behaviors - such as fights or passing illegal material - based on the input from multiple surveillance cameras would allow for providing the decision support module. With the acceptable detection accuracy, the solution would help in minimizing the accidents and unwanted behavior of monitored inmates. The system should also provide the catalogue of predefined dangerous situations, prepared by the experts in criminal sciences, including the features useful for predicting the specific events.

The paper presents the approach to identify fake signatures based on the image analysis. The problem is related with the forensics operations in order to distinguish handwritten signatures made by the human from the machine-originated counterfeits. The identification system is based on the selected artificial intelligence-based classifiers and processes features extracted from the signature images. The source material comes from either human or the 5-dimensional printer, being able to mimic a hand with the pen writing on the sheet of paper. Each image is then processed by the profilometer to extract important information allowing for distinguishing the original signature from the false one. Features include attributes related with the pen's position and inclination, obtained through the Fourier and wavelet transformations. The identification is then made by the intelligent classifier. For the project multiple algorithms were selected and tested regarding their accuracy, such as multilayered perceptron, decision tree or k Nearest Neighbors classifier. Presented experimental results show the ability of the system to support human during the task of the signature authenticity verification.

The paper describes the implementation of an automatic speech recognition (ASR) model as a component of a system generating automatic notes for doctor-patient interviews in Polish (done in harsh acoustic conditions). It works as part of a web application for recording the conversation, generating notes and automatically completing the medical record. The goal of the research was to evaluate Open-Source ASR models available for Polish language, on the authors’ dataset. The second aspect involved verifying the influence of the transfer learning of the models on the word detection accuracy. The paper presents stages of this process and its successful implementation. A description of the original dataset used in the study was also included.

The aim of the paper is to present the distributed system for the unwanted event detection regarding inmates in the closed penitentiary facilities. The system processes large number of data streams from IP cameras (up to 180) and performs the event detection using Deep Learning neural networks. Both audio and video streams are processed to produce the classification outcome. The application-specific data set has been prepared for training the neural models. For the particular event types 3DCNN and YOLO architectures have been used. The system was thoroughly tested both in the laboratory conditions and in the actual facility. Accuracy of the particular event detection is on the satisfactory level, though problems with the particular events have been reported and will be dealt with in the future.

<p align="center"><strong> ABSTRAK </strong></p><p><strong><em>Latar Belakang:</em></strong><strong><em> </em></strong><em>DM Tipe</em><em> 2 merupakan gangguan metabolik yang ditandai hiperglikemia akibat penurunan sekresi insulin oleh sel β-pankreas. Upaya pengendaliannya dilakukan melalui pengaturan pola makan. Biskuit berbahan bekatul beras merah, tepung mocaf, dan biji labu kuning yang diperkaya inulin berpotensi sebagai camilan alternatif bagi penderita DM Tipe 2.</em></p><p><strong><em>Tujuan</em></strong><em>: Penelitian ini bertujuan menganalisis karakteristik organoleptik serta kandungan gizi biskuit berbasis bekatul beras merah, mocaf, dan biji labu kuning dengan penambahan inulin, meliputi kadar air, abu, protein, lemak, karbohidrat, antioksidan, gula reduksi, serat pangan, pati total, amilosa, amilopektin, pati resisten, indeks glikemik, dan beban glikemik.</em></p><p><strong><em>Metode</em></strong><em>: Penelitian menggunakan rancangan acak lengkap dengan tiga ulangan dan empat formulasi perbandingan bekatul beras merah dan mocaf, yaitu F1(30%:70%), F2(40%:60%), F3(50%:50%), dan F4(60%:40%). Uji organoleptik dianalisis menggunakan Kruskal-Wallis dan Mann-Whitney, sedangkan kandungan gizi menggunakan ANOVA dan Duncan.</em></p><p><strong><em>Hasil</em></strong><em>: Hasil penelitian menunjukkan bahwa terdapat perbedaan nyata pada mutu hedonik (warna, tekstur, rasa pahit) dan kandungan gizi, kecuali gula reduksi. Kadar air 11,48–13,58%, abu 3,30–4,78%, lemak 18,69–21,19%, protein 12,49–15,27%, karbohidrat 47,14–53,92%, antioksidan 16,4–41,89%, gula reduksi 2,76–3,14%, serat pangan total 1,19–3,56%, pati total 35,03–40,42%, amilosa 8,76–9,76%, amilopektin 26,26–30,66%, pati resisten 0,81–2,60%, indeks glikemik 27,46–84,14. Formulasi terbaik adalah F3 (50% bekatul beras merah:50% mocaf) dengan beban glikemik 1,64–9,81 per takaran saji (10–60 g) dengan kategori rendah.</em></p><p><strong><em>Kesimpulan</em></strong><em>: Biskuit berbahan bekatul beras merah, mocaf, dan biji labu dengan inulin memiliki indeks dan beban glikemik rendah, sehingga berpotensi diaplikasikan sebagai camilan sehat bagi penderita DMT2.</em></p><p><em> </em></p><p><strong>KATA KUNCI<em>: </em></strong><em>bekatul beras merah</em><em>; </em><em>biji labu kuning</em><em>; biskuit;</em><em> diabetes mellitus tipe 2; tepung mocaf</em><em></em></p><p align="center"><strong> </strong></p><p align="center"><strong>ABSTRACT</strong></p><p><strong><em>Background: </em></strong><em>Type 2 DM is a metabolic disorder marked by hyperglycemia due to reduced insulin secretion from pancreatic β-cells. Dietary management is essential to control blood glucose levels. Biscuits made from red rice bran, mocaf, and pumpkin seeds enriched with inulin are proposed as an alternative snack for individuals with T2DM.</em></p><p><strong><em>Objectives: </em></strong><em>This study aimed to analyze organoleptic and nutrient content of biscuits formulated with red rice bran, mocaf, and pumpkin seeds enriched with inulin, including moisture, ash, protein, fat, carbohydrates, antioxidants, reducing sugars, dietary fiber, resistant starch, glycemic index, and glycemic load.</em></p><p><strong><em>Methods: </em></strong><em>Completely randomized design (CRD) with three replications was applied. Four formulations of red rice bran and mocaf were tested: F1(30%:70%), F2(40%:60%), F3(50%:50%), and F4(60%:40%). Organoleptic were assessed using Kruskal-Wallis and Mann-Whitney tests, while nutrient content was analyzed by ANOVA and Duncan’s test.</em><strong><em></em></strong></p><p><strong><em>Results: </em></strong><em>The study revealed significant differences in hedonic quality tests for color, texture, bitter taste, and nutritional content, except for reducing sugars. Nutrient values ranged as follows: moisture 11.48–13.58%, ash 3.30–4.78%, fat 18.69–21.19%, protein 12.49–15.27%, carbohydrates 47.14–53.92%, antioxidants 16.4–41.89%, reducing sugars 2.76–3.14%, total dietary fiber 1.19–3.56%, starch 35.03–40.42%, amylose 8.76–9.76%, amylopectin 26.26–30.66%, resistant starch 0.81–2.60%, and GI 27.46–84.14. The selected formulation F3(50%:50%), with GL values of 1.64–9.81 per 10–60 g serving, classified as low.</em></p><p><strong><em>Conclusions: </em></strong><em>Biscuits formulated with red rice bran, mocaf flour, and pumpkin seeds enriched with inulin may be a potential snack for patient with T2DM.</em></p><p><em> </em></p><p><strong>KEYWORD</strong><strong><em>: </em></strong><em>biscuits; mocaf flour; pumpkin seeds; red rice bran; type 2 diabetes mellitus</em><em></em><br /><br /><br /><br /></p><p>Article submitted on December 29, 2024; Articles revised on March 05, 2025; Articles received on August 19, 2025; Articles available online on November 28, 2025</p>