Browse Articles

Wind dynamic environment, sand material transport law and prevention strategies of Sichuan Tibet Railway

Determinants of leprosy among patients visiting Sheshamane comprehensive specialized hospital, West Arsi zone, oromia region, ethiopia: a case-control study

From performance to prediction: extracting aging data from the effects of base load aging on washing machines for a machine learning model

Characterization of Enterococcus species in surface drinking water from Akoko Edo Nigeria reveals contamination levels and risks to public health

Precipitation modeling in Northeastern Bangladesh–India transboundary flood regions using bi-metaheuristic-optimized NMF-neural network

Abstract Two fundamental questions in rainfall modeling using Artificial Neural Networks (ANN) are: (1) how to best handle highly nonlinear, noisy, short-duration rainfall data, and (2) how to locate a solution to the optimization issue of ANN, particularly in formulating the optimum weights and biases. Most of the single-step rainfall forecasting models that rely on single-step optimization and conventional ANN feature selection techniques are not capable of adequately addressing these critical challenges. In this study, Non-Negative Matrix Factorization (NMF) is applied to model complex short-term rainfall patterns, and an optimal differential approach is used to compute NMF components. For the optimization of the ANN model, in this paper, three recently proposed metaheuristic algorithms namely Harris Hawks Optimization (HHO), Egret Swarm Optimization Algorithm (ESOA), and Hippopotamus Optimization (HO) are explored along with traditional well-known methods like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Furthermore, a two-step hybrid optimization approach is introduced to enhance ANN performance in rainfall forecasting. This significantly improves model precision, with reductions in mean squared error (MSE) ranging from 1.00% to 97.46% in Sylhet, 8.33% to 97.10% in Chittagong, 6.96% to 89.57% in Meghalaya, and 17.74% to 76.09% in Assam compared to single-step optimization models. The results indicate that the two-step optimization approach not only outperforms single optimization techniques but also outperforms recently introduced metaheuristic algorithms such as HHO, ESOA, and HO, demonstrating its superior potential for improving the accuracy of rainfall modeling. On the other hand, the sensitivity analysis of the hidden neuron indicates that the impact of hidden neuron quantity is highly sensitive to the optimizer and the characteristics of the data.

Effect of Pb3O4 nanocomposite on the structural, optical, and radiation shielding properties of PVA Films

Abstract This study investigated the effect of lead tetroxide nanoparticles (Pb 3 O 4 NPs) on the properties of polyvinyl alcohol (PVA). PVA films were prepared by a conventional casting method, with varying concentrations of Pb 3 O 4 NPs (0, 2, 4, 6, 7, and 9 wt %). A significant increase in the crystallinity of the PVA film with increasing Pb 3 O 4 NPs concentrations and the uniform distribution of Pb 3 O 4 NPs on the surface of the films were demonstrated using X-ray diffraction (XRD) analysis and scanning electron microscopy (SEM), respectively. Optical characterizations revealed increased light absorption and decreased light transmittance with increasing Pb 3 O 4 concentration. Among the significant optical results, the band gap energy of the samples decreased from 4.95 to 3.77 eV for pure PVA and PVA/9% Pb 3 O 4 . The radiation blocking capabilities of the PVA films were investigated experimentally using a NaI (Tl) detector and theoretically using Phy-X/PSD software in the gamma-ray energy range (0.511–1.332) MeV. The experimental and theoretical results were consistent, highlighting that higher concentrations of Pb 3 O 4 improve the effectiveness of PVA films in reducing gamma ray penetration. Thus, the control of the filler concentrations to enhance the shielding properties will open up a new strategy to synthesize novel materials for radiation applications.

Whole-genome nanopore sequencing and automatic downstream analysis of respiratory syncytial virus using RSVTyper

Abstract Respiratory syncytial virus (RSV) is a globally circulating virus, causing severe respiratory infections in infants and the elderly. Two RSV vaccines were recently approved, and passive immunization is now recommended in several countries for all newborns, therefore careful surveillance of RSV variants will be important in the future. We therefore develop an integrated whole genome RSV amplification, sequencing and bioinformatics analysis method („RSVTyper“; https://anaconda.org/bioconda/rsv-typer ) that is suitable for patient samples as well as wastewater. 243 RSV isolates from 2008 to 2025 and wastewater samples from 2023/2024 were amplified in a multiplex tiling PCR with specific primers, generating 39 amplicons ~ 550 bp in length, and sequenced with Oxford Nanopore Technologies. Sequencing reads of patient isolates were analyzed with the RSVTyper pipeline, a tailored analysis pipeline including automatic reference selection, consensus sequence generation and clade assignment via Nextclade. Amplification and sequencing were successful for 213/243 samples. Whole genomes (> 90% coverage) were obtained from 98% of samples with > 10,000 copies/mL, from 3/14 samples with 1,000–10,000 copies/mL, and from none with < 1,000 copies/mL. Average genome-wide mean depth for successfully sequenced samples was 31,800x with an average mean depth of 41,400x in the F gene. Phylogenetic analysis showed seasonal clade and subtype shifting, with a good representation of clade frequencies from patients in wastewater sequences. No variants with known escape mutations from prophylactic monoclonal antibodies were detected. In conclusion, we developed RSVTyper, a cost-effective and scalable RSV sequencing pipeline by integrating sequencing and bioinformatic analysis. It is suitable for both resource-limited settings and high-throughput applications. It will facilitate enhanced RSV surveillance, allowing for further characterization of the RSV genome and rapid detection of potential escape mutations.

Optimum incision geometry in side-to-side anastomosis

Assessment of knowledge, attitudes and behaviors related to self-medication practices among the adult population during the COVID-19 pandemic in Italy

Ameliorative effect of folic acid and vitamin B12 against Ivermectin-induced hepatotoxicity, renal toxicity, oxidative stress and immunohistochemical changes in male albino rats

Abstract Since its remarkable discovery 35 years ago, Ivermectin (IVM) has remained one of the most crucial medications for treating parasitic infections in both human and animal medicine. Ivermectin was recommended in high doses for treatment of SARS-CoV-2, severe acute respiratory syndrome coronavirus 2 and as a part of feed in fish farms that exposed the treated animal or human for risk of its toxicity. It can cause hepatotoxicity, renal toxicity and other side effects, which may require prompt intervention for removal. Therefore the current study aimed to investigate the potential protective effects of folic acid (FA) and vitamin B12 (Vit.B12) against IVM-induced hepatotoxicity and renal toxicity in rats after prolonged high-dose exposure. 28 male Albino rats were divided into four groups of seven rats for each group. The first group is the control group (Ctrl group) received distilled water, the second group was subcutaneously injected with IVM (IVM group), the third group was subcutaneously injected with IVM and orally administered FA (IVM + FA group), and the fourth group was subcutaneously injected with IVM and intramuscular injection of Vit.B12 (IVM + Vit.B12 group). After 30 days of the experiment, blood samples were collected for biochemical analysis while liver and kidney tissue specimens were collected for oxidative analysis and histological investigation. In addition, immunohistochemistry assays of caspase3, BAX protein, Bcl2 protein and PCNA were checked. Results revealed that IVM group displayed significant increase in the liver enzymes (AST and ALT) associated with decreased albumin, total protein and alkaline phosphatase in the serum. All kidney parameters were found significantly increased. In addition, significant increase was observed in malondialdehyde combined with significant decrease of catalase, total antioxidant capacity and superoxide dismutase in the IVM group. IVM group showed histological and immunohistochemical changes in the liver and the kidney compared to the control group. Immunoexpression of caspase3 and BAX were enhanced after administration of IVM while Bcl2 protein and PCNA were negatively expressed. All of these above mentioned parameters were almost returned to normal levels after administration of FA and Vit.B12 associated with improvement in liver and kidney function. These findings highlight the ameliorative effects of FA and Vit.B12, emphasizing the necessity of their co-administration with IVM to maximize its therapeutic benefits-including promoting food security-while minimizing its harmful effects on the liver and kidneys during treatment protocols.

Of the article: Microbiological assessment of a herbal mouth rinse for treating chronic generalized periodontitis

Abstract Periodontal diseases remain highly prevalent across age groups, often aggravated by poor oral hygiene, occlusal anomalies, and defective restorations. This study evaluated the effectiveness of Art-Dentale Expert mouthwash against major periodontopathogens in patients with mild chronic generalized periodontitis (CGP) using PCR diagnostics. Thirty-nine patients with CGP were randomized into a main group (Art-Dentale Expert) and a control group (Chlorhexidine). Gingival pocket samples were collected before treatment and at 7 days, 1 month, and 6 months. Four periodontopathogens (P. gingivalis, T. forsythia, T. denticola, and P. intermedia) were analyzed. The results obtained were processed statistically. Both rinses significantly reduced P. gingivalis and T. forsythia at 7 days, with Chlorhexidine showing a sharper initial decline in P. gingivalis. At 6 months, P. intermedia was completely absent in the Art-Dentale Expert group ( p  = 0.0209), whereas it persisted in 10% of controls. Art-Dentale Expert demonstrated sustained efficacy, particularly against T. denticola and P. intermedia. These findings support its role as an effective adjunct in periodontal therapy.

Multi-scale influence mechanism of fine coal gangue on the mechanical properties of concrete

Lightweight pavement crack detection model for edge computing devices

Optimal distributed PV system assessment for renewable energy based microgrid application in Makkah, Saudi Arabia

Multi-feature deep learning framework for predicting CO adsorption mechanisms at metal oxide interfaces: a transformer-based approach

Resistance patterns and virulence factors of Pseudomonas aeruginosa in hospitalized patients: A Saudi Arabian study

Comprehensive rheological characterization of polynucleotide/BDDE-crosslinked hyaluronic acid blend for intra-articular viscosupplementation

Abstract Viscosupplementation is a widely used treatment for osteoarthritis, aiming to restore the viscoelastic properties of synovial fluid and improve joint function. While hyaluronic acid (HA), BDDE-crosslinked hyaluronic acid (BDDE-HA), and polynucleotide (PN) have been studied individually, the rheological properties of their mixtures remain insufficiently explored. This study investigates the viscoelastic characteristics of PN/HA and PN/BDDE-HA blends through rheological evaluations, including simple shear tests, oscillatory shear tests, and 3-interval thixotropy tests. Results indicate that BDDE-HA maintains high viscosity over a range of shear rates, whereas PN exhibits viscosity loss at high shear rates. PN/HA exhibits synergistic structural recovery properties, consistent with clinical findings suggesting improved efficacy compared to individual components. PN/BDDE-HA exhibits improved viscoelastic behavior but prolonged structural recovery. These findings highlight the importance of comprehensive rheological analysis in understanding viscosupplement formulations and their potential clinical implications. This study provides fundamental data to support future clinical research on PN/BDDE-HA as a novel viscosupplement.

Independent validation of lung adenocarcinoma prognostic risk scores incorporating cholesterol and estrogen metabolism related transcriptional biomarkers

Abstract We investigated the prognostic significance of cholesterol metabolism-related genes (CMRGs) and estrogen metabolism-related genes (EMRGs) in lung adenocarcinoma (LUAD). Transcriptomic and clinical data from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases were analyzed. Iterative sure independence screening and least absolute shrinkage and selection operator (ISIS-LASSO) Cox regression identified prognostic CMRGs and EMRGs. Two risk scores—Cholescore and Estrogenscore—were constructed and validated. High Cholescore was associated with poor overall survival (OS), reduced immune infiltration, low immune checkpoint expression, and high tumor purity, suggesting an immunosuppressive tumor microenvironment. Estrogenscore also independently predicted LUAD prognosis. Mediation analysis revealed that estrogen-related pathways partially mediated the impact of cholesterol metabolism on prognosis. A significant interaction between Cholescore and Estrogenscore was identified, and patients with both high scores had the worst OS and lowest predicted immunotherapy benefit. Combining the two scores significantly improved the area under the curve (AUC) for 1–5 years OS prediction. These findings suggest that integrating cholesterol and estrogen metabolism signatures can improve LUAD prognostic stratification and provide molecular insights into tumor–immune interactions and immunotherapy response prediction.

Metal-organic framework (Pd-DTPA-MOF)-based materials as heterogeneous catalysts for C–S cross-coupling reactions

Spectral efficiency enhancement in multiuser NOMA over Nakagami-m fading channels through power allocation and pairing strategies under hardware and SIC imperfections

Abstract Non-orthogonal multiple access (NOMA) is a key enabler for future sixth-generation (6G) and massive machine-type communication networks, offering superior sum spectral efficiency (SSE) and user fairness compared to traditional orthogonal multiple access (OMA) schemes. However, practical deployments face challenges due to hardware impairments (HI) and imperfect successive interference cancellation ( i SIC), which cause signal distortion and residual interference, degrading system reliability. Most existing works overlook these impairments or assume ideal fading scenarios, thereby limiting their real-world applicability. This work addresses these issues by developing a comprehensive outage probability analysis for both downlink (DL) and uplink (UL)-NOMA over Nakagami- m fading channels, a versatile model for realistic fading conditions. Closed-form expressions are derived using Gamma-function-based modeling, and a low-complexity optimization of power allocation (PA) and user pairing is proposed to enhance system performance under impairments. The results demonstrate that employing a strong–weak (SW) user pairing strategy, along with optimally tuned PA factors, yields a notable improvement in SSE $$\approx 15.58\%$$ in DL and $$\approx 25.55\%$$ in UL. The accuracy of the proposed analytical models are substantiated through a strong agreement with simulation outcomes. The integration of user pairing with optimized PA not only enhances spectral efficiency (SE) but also facilitates efficient resource utilization while maintaining low computational complexity. This comprehensive approach positions the proposed system as a viable solution for meeting the performance and scalability requirements of next-generation wireless networks.