Ministry of Health of the Republic of Uzbekistan

s of mazut gives rise to an enormous primary plume, its 512-fold dilution along a 90 km radius appreciably alleviates the immediate direct toxicological impact [9].Together with the 30% penetration factor, however, the residual PM 2.5 concentration may still contribute a readily measurable #/m3 value to the city's general background air quality and be in excess of WHO daily guidelines during conditions of low wind dispersion [10].The outcome verifies that the distance of 80-90 km is insufficient to provide 'complete immunity' against the emissions of industries, thereby prompting the use of 'clean coal' technology/WESP in the power stations [11].In conclusion, it can be asserted that the simplified exponential wind model is an essential 'tool' in the hands of regional planners to estimate the 'risks to the environment' in the absence of complex 'dispersement software tools' in the initial stage [12].Lastly, the outcome strongly supports the formulation of a tough 'legislative policy regarding the use of mazut in thermal power stations to protect the health of distant urban areas ' [13].

In this study, a novel GO/Fe@TANG composite catalyst was designed by functionalizing graphene oxide (GO) with iron (Fe) and incorporating a hydrogen (H 2 ) trapping TANG COF.

Background . A promising research avenue in recent years has been implementing research findings on biological markers of inflammation into clinical practice. One such marker is fecal calprotectin. The literature contains only isolated reports on fecal calprotectin concentrations in patients with celiac disease, and the available data vary significantly. Objective . To determine the clinical significance of fecal calprotectin in pediatric celiac disease and to find its relationship with small bowel permeability. Materials and methods. From January 2018 to June 2019, 42 pediatric patients were examined: 28 with newly diagnosed celiac disease, 14 previously diagnosed children adhering to a gluten-free diet, and 20 apparently healthy, age-matched control subjects. All participants were tested for IgA tissue transglutaminase antibodies and for total IgA (ELISA). Fecal calprotectin levels were also measured using ELISA. Intestinal permeability was assessed using a non-invasive method (after Petrov V.I. et al., 2003). Results . Fecal calprotectin levels were elevated in newly diagnosed celiac patients (36.6 ± 10.2 мcg/g) compared with the control group (20.9 ± 8.7 мcg/g). In children with refractory celiac disease, fecal calprotectin levels were significantly higher than in both the newly diagnosed group and controls (77.9 ± 24 мcg/g). Assessment of the intestinal barrier showed increased intestinal permeability in celiac patients compared with healthy controls (0.3 ± 0.02 optical units, p < 0.05), with the most pronounced changes observed in newly diagnosed patients (–0.1 ± 0.05 optical units). Correlation analysis revealed a strong positive relationship between fecal calprotectin levels and small bowel permeability in refractory celiac disease (r = 0.96). Conclusion . In children with refractory celiac disease, fecal calprotectin levels exceed those of both healthy controls and newly diagnosed patients. A strong correlation was identified between elevated fecal calprotectin values and increased intestinal per- meability in children with refractory celiac disease.

ARDS is a critical condition commonly encountered in intensive care units with a high death rate more than 40 %, and early diagnosis is very essential in patient outcome management. Current diagnostic approaches rely heavily on clinical judgment and static measurements, often resulting in delayed recognition and suboptimal treatment timing.The proposed work will design and construct an AI-based real-time monitoring system, which will predict the onset of ARDS 6-12 hours earlier than the patients may have shown their first clinical symptoms in the ICUs. We developed a deep learning ensemble model, consisting of convolutional neural networks and long short-term memory networks, that was trained using multimodal data such as continuous vital signs, laboratory data, and ventilator settings in addition to various types of imaging data of the chest over 2,847 ICU patients in three clinical centers. The model was validated using time-series cross-validation and external validation datasets. The AI system achieved 94.2% sensitivity and 89.7% specificity in ARDS prediction, with an average early detection time of 8.4 hours before clinical diagnosis, significantly outperforming traditional scoring systems. The implementation of this real-time monitoring system has the potential to revolutionize critical care by enabling proactive interventions, reducing mortality rates, and optimizing resource allocation in intensive care settings.

Abstract The Pamir Plateau is situated at the northwestern edge of the India–Eurasia Plate collision zone, making it a key region for studying continental collision and plateau uplift. The deep structure and dynamic processes of this region have long been of great scientific interest. This paper synthesizes recent advancements in the application of geophysical techniques to investigate the deep structure of the Pamir Plateau. The study focuses on the heterogeneity of the crust and lithosphere, the morphology of the Moho and the double Moho structure, the depth variations of the lithosphere‐asthenosphere boundary (LAB), and the complex features of the mantle transition zone (MTZ). The results indicate that the deep tectonic structure of the Pamir region is closely associated with subduction of the Indian Plate, the southward compression of the Asian lithosphere, and lateral tectonic interactions from the Tarim Basin, which jointly drive the region's uplift and deformation. The paper further examines the deep interactions between the Pamir Plateau and adjacent regions. Additionally, the study discuss key controversies in current research, such as the spatial relationship between the Moho and deep seismic zones, the mechanisms of lithosphere delamination, and its effects on shallow structural deformation, etc.

Background. Primary open-angle glaucoma (POAG) is a chronic, progressive eye condition causing optic nerve damage and irreversible vision loss by increasing intraocular pressure (IOP). Therapy primarily aimed at reducing IOP to prevent disease progression. Pharmacoeconomic evaluation of fixed-dose combinations (FDCs) has attracted growing interest in recent years as a strategy to enhance both treatment efficacy and accessibility.Objective: To review the cost and clinical effectiveness for FDCs of travoprost/timolol (TT) and latanoprost/timolol (LT) for POAG treatment.Material and methods. A systematic literature review was conducted using PubMed/MEDLINE, Web of Science, ScienceDirect, and Google Scholar databases. The sampling included studies evaluating FDCs of TT and LT in terms of its cost and clinical effectiveness, as well as cost-effectiveness and cost-utility ratios.Results. TT-FCD proved to be more cost-effective than LT-FDC in several European countries and the Philippines, resulting in lower long-term costs and slowing the progression of vision loss. Conversely, in China identified LT-FDC was more cost-effective due to lower daily costs. Both FDC options improved patient adherence to treatment due to their simplified administration.Conclusion. TT-FCD may be a more favorable treatment option for POAG in certain regions, considering its pharmacoeconomic and clinical advantages. However, treatment selection should be individualized based on regional healthcare dynamics, medicine pricing, and patient access to medicines.

The shrubland ecosystems in arid areas are highly sensitive to global climate change and human activities. Accurate extraction of shrubs using computer vision techniques plays an essential role in monitoring ecological balance and desertification. However, shrub extraction from high-resolution GF-2 satellite images remains challenging due to their dense distribution and small size, along with complex background. Therefore, this study introduces a Feature Enhancement and Transformer Network (FETNet) by integrating the Feature Enhancement Module (FEM) and Transformer module (EdgeViT). Correspondently, they can strengthen both global and local features and enable accurate segmentation of small shrubs in complex backgrounds. The ablation experiments demonstrated that incorporation of FEM and EdgeViT can improve the overall segmentation accuracy, with 1.19% improvement of the Mean Intersection Over Union (MIOU). Comparison experiments show that FETNet outperforms the two leading models of FCN8s and SegNet, with the MIOU improvements of 7.2% and 0.96%, respectively. The spatial details of the extracted results indicated that FETNet is able to accurately extract dense, small shrubs while effectively suppressing interference from roads and building shadows in spatial details. The proposed FETNet enables precise shrub extraction in arid areas and can support ecological assessment and land management.

The increasing sophistication of cyber threats necessitates a strategic approach to network security, ensuring resilience and safeguarding sensitive data. This paper explores contemporary methods of network security, focusing on preventive measures, detection strategies, and response mechanisms. Key areas of discussion include firewalls, intrusion detection systems, encryption techniques, and access control methodologies. Firewalls act as the first line of defense, filtering network traffic to prevent unauthorized access. Intrusion detection systems complement firewalls by monitoring and identifying potential threats in real time, leveraging machine learning for enhanced detection accuracy. Encryption techniques play a crucial role in data protection, employing symmetric, asymmetric, and hybrid encryption methods to maintain confidentiality and integrity. Additionally, authentication protocols such as multi-factor authentication and role-based access control ensure secure access management. The adoption of Zero Trust Architecture further enhances network security by requiring continuous verification of users and devices. Emerging trends, including artificial intelligence-driven threat detection and blockchain technology, offer promising advancements in cybersecurity frameworks. As organizations increasingly rely on cloud computing and the Internet of Things, the complexity of network security continues to evolve. Proactive measures, continuous monitoring, and adaptive security policies are essential in mitigating risks. By integrating innovative security strategies, businesses and individuals can establish a robust defense against cyber threats, ensuring a secure digital environment. This paper underscores the necessity of a comprehensive, multi-layered security approach to address the dynamic nature of cyber risks in today's interconnected world.