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Psychometric properties of International HIV Dementia Scale as screening tool for neurocognitive disorder among people living with HIV/AIDS

The IUCN Red List and newspaper coverage of threatened freshwater eel species in Japan: A variable but limited influence

The IUCN Red List is a vital tool for identifying threatened species and raising public awareness. This study examined how the listing of freshwater eels ( Anguilla spp.) influenced newspaper coverage in Japan, a major consumer of eels. We analysed 8387 eel-related articles from four major newspapers between 1992 and 2021 using text-mining and statistical methods, along with manual review of a part of the articles. Peaks in article numbers coincided with major events, such as the IUCN listing of the Japanese eel as Endangered in 2014. However, the influence of the Red List was short-lived and limited in strength, with minimal media attention given to non-native eel species such as European eel. Category-specific analysis revealed that issues related to food and trade dominated media coverage, while conservation-focused reporting was less prominent. Our findings suggest that while the Red List can momentarily increase media attention, its impact on long-term public awareness is limited. Strengthening expert engagement, international cooperation, and consumer education could be essential to enhance the conservation impact of the Red List.

Cryptographic protection of RGB images using SPN over Eisenstein integer ring modulo Eisenstein prime

Clay minerals evidences for cold-warm fluctuations in the Early Silurian

The Late Ordovician and Early Silurian transition is an important period of geological evolution, attracting increasing attentions. However, the cause for the biotic recovery from the end-Ordovician mass extinction has remained controversial. A set of black shales deposited in the Longmaxi Formation of the Early Silurian recorded the characteristics of the climate evolution after this extinction event, which played a crucial role in the biological recovery. In this paper, the shale of the Longmaxi Formation(LMX Fm.) in Well Yucan-6, Sichuan Basin is selected to analyze total organic carbon (TOC) and clay mineral composition, so as to address the climate evolution and its implications for the biotic recovery. The results show that the TOC content in the shale is higher at the bottom of the Longmaxi Formation in Well Yucan-6, and gradually decreases upward; the clay minerals are dominated by chlorite, illite, illite/smectite and chlorite/smectite mixed layer minerals, with no kaolinite and montmorillonite minerals being found. The clay minerals are mainly composed of illite/smectite mixed layer mineral with subordinate minerals of illite and chlorite, and a mall amount of chlorite/smectite mixed layer. Based on the characteristics of the illite and chlorite contents, and the ratios of illite/chlorite (I/C) and (smectite illit/smectite mixed layer mineral)/(illite+chlorite), i.e., (S + I/S)/(I + C), the paleoclimate evolution process of the Longmaxi Age is divided into three stages. Stage 1 is a climate evolution period of dry-wet, cold-hot rhythms; Stage 2 is a warm and humid climate evolution period, without obvious change in TOC content; and Stage 3 is a dry and cold climate evolution period, without obvious change in TOC. When combining these study results with the characteristics of the inorganic carbon isotope change trend in Silurian Epoch in the Tibet area and the whole world, the following conclusion has been drawn: The Early Silurian Longmaxi Age in Sichuan Basin was generally in a dry and cold environment, consistent with the characteristics of global paleoclimate evolution. These further indicates that the biotic recovery was delayed by the dry and cold climatic conditions in the earliest Silurian following the Hirnantian glaciation. Until the relative warm and cold climatic conditions in the early Silurian, biotic recovery started with the ameliorative environments.

Uniaxial creep characteristics and constitutive model of arkose sandstone with different moisture contents under repeated freeze thaw cycles

Ultrasounic-radiomics models for predicting the response to Atezolizumab plus Bevacizumab in patients with unresectable hepatocellular carcinoma

Background Atezolizumab plus Bevacizumab is an effective treatment for unresectable hepatocellular carcinoma, but the assessment methods are limited. Objective To establish an early predictive model using Ultrasounic-radiomics (UR) for predicting the therapeutic efficacy of Atezolizumab plus Bevacizumab in unresectable hepatocellular carcinoma. Methods We retrospectively analyzed 170 patients with unresectable hepatocellular carcinoma, extracting 1560 imaging features pre- and one-week post-treatment. Separate UR models were established to predict treatment efficacy. Model performance was evaluated using calibration curves and the area under the receiver operating characteristic curve (AUC). Results Two UR models were ultimately established. The pre-treatment UR model achieved an AUC of 0.790 in the train group and 0.706 in the validation group. The post-treatment UR model achieved an AUC of 0.855 in the train group and 0.704 in the validation group. Using a cutoff value of 0.528 to divide patients into high-risk and low-risk groups, the Kaplan-Meier survival curves showed statistically significant differences between the two groups. The hazardous and moderate-risk groups’ Kaplan-Meier survival curves revealed statistically significant distinctions. Conclusion The UR models show promise in predicting the efficacy and prognosis of combined targeted therapy and immunotherapy in unresectable hepatocellular carcinoma, particularly highlighting the importance of ultrasound assessments three months post-treatment.

Integrated use of finite element analysis and gaussian process regression in the structural analysis of AISI 316 stainless steel chimney systems

Abstract This study aimed to conduct a comprehensive structural analysis and machine learning-assisted predictive modelling of a chimney system manufactured from 2 mm thick AISI 316 stainless steel with a diameter of Ø500 mm. The primary motivation of this work was to examine, in detail, the structural behavior of chimney modules under various force and pressure conditions using conventional methods, and to develop a reliable model capable of performing parametric predictions for new scenarios based on the acquired data. The scope of the study encompassed finite element analyses of both the entire chimney system and 3-meter-long intermediate modules, field tests, and the application of the Gaussian Process Regression (GPR) machine learning model. In the analysis of the entire chimney system under an applied force of 22,000 N, a maximum stress of 28 MPa and a safety factor of 8.39 were observed in the chimney clamps. The total deformation was found to be 0.58 mm, which is within acceptable limits. In the structural analysis of the intermediate chimney modules under a force of 1000 N and an internal pressure of 5 MPa, a maximum stress of 11,984 MPa, a safety factor of 1.71, and a total deformation of 0.46 mm were determined, all of which are consistent with the literature. The accuracy of these analyses was validated through pressure and leakage tests conducted in accordance with the EN 1859 standard. The developed GPR machine learning model demonstrated exceptionally high accuracy (R² > 0.999) in predicting Von Mises stress values, providing reliable forecasts with an error rate of less than 3% when compared to ANSYS simulation outputs. However, in predicting total deformation values, error rates exceeded 70%, indicating that the model was less sensitive in low-amplitude deformation cases. These findings suggest that the GPR model can generate reliable predictions for Von Mises stress a more critical parameter than total deformation in chimney design. By integrating conventional structural analysis methods with advanced machine learning techniques, this study demonstrates the potential of predictive modeling as an efficient and reliable tool in engineering design processes, making a significant contribution to the field’s body of knowledge.

Reliability and validity of the PORTRAIT-10 tool for assessing complex health care needs in French-speaking people living with chronic pain

Chronic pain (CP) presents multidimensional components, leading individuals to experience complex biopsychosocial needs. However, efficient tools to assess these needs remain scarce. PORTRAIT-10 is a tool designed to measure the complexity of patients’ needs. The present study was aimed at documenting the psychometric properties of this tool in a sample of individuals with CP who completed the INTERMED-Self Assessment (IMSA), PORTRAIT-10, Pain Catastrophizing Scale (PCS), and Pain Self-Efficacy Questionnaire (PSEQ). PORTRAIT-10 was re-administered 3 weeks later. The sample comprised 295 participants. Mean age of the respondents was 53.3 ± 9.3 years; 88.3% were females. The median pain duration was 15 years. Results of an exploratory factor analysis showed that a 4-factor solution best fit the PORTRAIT-10 data, with at least 2 of these factors (psychological and social) being consistent with the conceptual framework of the tool. PORTRAIT-10 also showed acceptable internal consistency (Cronbach α = 0.67, 0.73) and very good reliability over time (ρ = 0.85). Correlation with IMSA was high (ρ = 0.74) and as expected, was low with PCS (ρ = 0.34) suggesting a very good construct validity. A ROC analysis demonstrated that a PORTRAIT-10 cut-off score of 10 displayed good sensitivity (0.86) and specificity (0.71) in detecting complex care needs in this population. This study provides initial validity and reliability of PORTRAIT-10 and suggests that this tool may be helpful in identifying individuals with CP who have complex needs. Further research is needed to explore the psychometric properties of PORTRAIT-10 in large and more diverse chronic pain populations and to evaluate its impact on clinical outcomes.

MUC1 promoter methylation pattern diversity and its association with TET3 expression and prognosis in cholangiocarcinoma

AgNPs treatment reduces time recovery and increases bacterial sensitivity to antibiotics in cow´s purulent catarrhal endometritis. A translational study

Cow purulent catarrhal endometritis (PCE) is a common reproductive disorder in dairy cattle caused by bacterial infections. PCE impacts fertility, milk production, and animal health. Therapeutic approaches include systemic or intrauterine antibiotics. Unfortunately, the overuse of antibiotics in treating PCE drives the emergence of antibiotic-resistant bacteria, making infections difficult to treat and increasing food safety concerns due to antibiotic residues remaining in milk and meat products, posing health risks to consumers. Antimicrobial nanomaterials, particularly silver nanoparticles (AgNPs), provide an efficient alternative to combat multi-resistant bacteria, and the synergistic activity of AgNPs and antibiotics has been well documented, making the treatments of bacterial infections more efficient. Here, a comparative study is shown applying Argovit-C (AgNPs) and Enrocide as therapeutics for treating PCE in cattle. Intrauterine application of Argovit-C reduces the recovery time of cattle in comparison with Enrocide treatment as well as increases the sensitivity to antibiotics of Escherichia coli isolates from cervical canal secretion samples of diseased cattle. The increased sensitivity was found to 24 antibiotics, including aminoglycosides, fluoroquinolones, tetracyclines, penicillins, cephalosporins, macrolides, polymyxin, rifampicin, and chloramphenicol. The increased sensitivity was much higher for those bacteria that did not show an active efflux effect. Furthermore, Argovit-C reduced the acquisition of blaDHA and blaGES resistance genes in E. coli , as well as the number of bacterial isolates without efflux effect. Overall, this translational study performed in 300 cows demonstrates the ability of Argovit-C AgNPs to combat bacterial infections, favoring an increase in bacterial susceptibility to antibiotics and reducing their ability to acquire antibiotic multi-resistant genes.

Antibacterial properties of Aloe adigratana and Aloe elegans extracts and their potential applications in shampoo and soap development

Research on the optimization of delivery routes for vehicles with drones under no-fly zone restrictions

With the rapid development of e-commerce, logistics and distribution systems face the dual pressures of efficiency improvement and cost control. Unmanned Aerial Vehicle (UAV) delivery, featuring flexibility, high efficiency, and low carbon emissions, has become an effective means to solve the “last-mile” problem. However, the widespread no-fly zones in urban environments (e.g., airports, government agencies, and high-voltage power lines) severely limit the application scope of UAVs and increase the complexity of path planning. Against this backdrop, the vehicle-assisted UAV collaborative delivery model has emerged: through the division of labor and collaboration between ground vehicles and UAVs, it not only expands the service radius of UAVs but also overcomes the constraints of no-fly zones, achieving dual improvements in delivery efficiency and service quality.This study focuses on the optimization of vehicle-assisted UAV delivery paths under no-fly zone constraints, aiming to construct a multi-objective optimization model that balances delivery costs, carbon emissions, and customer satisfaction, and to design an efficient solution algorithm for providing scientific decision support to logistics enterprises. First, the paper systematically sorts out the classification and definition of no-fly zones as well as their impact mechanisms on UAV path planning, and elaborates on the theoretical basis of vehicle-UAV collaborative delivery, including the constituent elements of the problem, methods for quantifying customer satisfaction, and the application framework of heuristic algorithms. On this basis, a mixed-integer programming model is built with the objectives of minimizing total cost, minimizing carbon emissions, and maximizing customer satisfaction. Given that this model falls into the category of NP-hard problems, we have designed a four-stage heuristic solution. First, an improved K-means algorithm (IKM) is used to cluster customer points under the constraint of the UAV’s maximum flight radius, so as to determine vehicle parking points. Second, a multi-objective genetic algorithm is applied to plan UAV delivery routes for customers in open areas. Next, the multi-objective genetic algorithm is continued to design initial routes for vehicles between parking points. Finally, the multi-objective genetic algorithm is utilized again to plan delivery routes for customers in no-fly zones, ultimately forming a complete collaborative “vehicle-UAV” delivery scheme.To verify the effectiveness of the model and algorithm, simulation experiments are conducted using two sets of cases: 30 customer points in a local area of Harbin and the large-scale R201 case from the Solomon dataset. The results show that compared with traditional vehicle-only or UAV-only delivery models, the vehicle-UAV collaborative delivery model exhibits significant advantages in total cost, carbon emissions, and customer satisfaction; the model maintains good robustness in stability tests under different no-fly zone settings; and parameter sensitivity analysis further reveals the impact of key parameters (e.g., UAV load capacity, endurance, and vehicle load capacity) on delivery performance, providing practical references for logistics enterprises in equipment selection and operation strategy formulation.

Integrated bulk and single-cell transcriptomics identify RELB, S100A9, and SOCS1 as key autophagy-endoplasmic reticulum stress genes linking T2DM with MAFLD

How is vocabulary involved in second language reading comprehension? A study in Chinese-English bilingual children

It remains unclear as to how vocabulary contributes to reading comprehension in a second language (L2). This study aims to explore the specific roles of vocabulary in reading comprehension in children learning English as an L2 based on three theoretical perspectives. Namely, whether vocabulary should be considered as a subcomponent of language comprehension, an independent predictor of reading comprehension, or an indirect predictor of reading comprehension through decoding and listening comprehension? A total of 167 Grade 4 and 5 Chinese primary school English learners with a mean age of 9.96 years old in Hong Kong participated in this study, and they completed a series of English language tasks. The measurement models indicated that vocabulary was strongly associated with both decoding and listening comprehension, explaining above 65% of their variance. The results of structural equation modeling indicate that vocabulary substantially and indirectly contributed to reading comprehension (accounting for around 44% of its variance) through decoding and language comprehension. Theoretical and practical implications are discussed.

Sketch to photo recognition using IF and Fuzzy minimal structure oscillation in the sift domain

Correction: Differences in rehabilitation for high-risk newborns: The impact of neonatal intensive care unit hospitalization

Holographically sensing of volatile organic compounds using cellulose acetate-based photopolymer film

Association of perchlorate, nitrate, and thiocyanate with age-related macular degeneration in the United States

Perchlorate, nitrate, and thiocyanate are endocrine-disrupting chemicals, but their associations with AMD is unclear. This study aims to investigate this relationship. We included 4727 participants aged 40 years and older from the National Health and Nutrition Examination Survey (NHANES) 2005–2008. Logistic regression analysis, restricted cubic spline (RCS), and weighted quantile sum (WQS) were applied to investigate the single, non-linear, and combined effects on AMD risk. Nitrate exposure was positively associated with any AMD risk (OR Any AMD , 1.19; 95% CI, 1.05–1.35; P = 0.010) and early AMD risk (OR Early AMD , 1.19; 95% CI, 1.05–1.36; P = 0.010); compared to the first quartile, the highest quartile of nitrate (OR, 1.94; 95% CI, 1.18–3.19; P = 0.012) and thiocyanate (OR, 1.70; 95% CI, 1.19–2.42; P = 0.006) levels were positively associated with AMD risk. The results of RCS showed a nonlinear relationship between nitrate exposure (P for nonlinearity = 0.020), thiocyanate (P for nonlinearity = 0.041), and AMD risk. WQS analysis indicated a positive relationship between mixed exposure and AMD risk (OR, 1.24; 95% CI, 1.01 to 1.51; P = 0.037). This study indicated that high urinary nitrate and thiocyanate levels were associated with an increased AMD risk among US adults. However, the cross-sectional design precludes causal inference.

The selective serotonin reuptake inhibitor escitalopram oxalate negatively impacts the fracture healing in healthy adults and in osteoporotic rats

Study on static properties and mechanism of basalt fibre reinforced cement cured red sandstone soil

To enhance the suitability of red sandstone as a railway roadbed fill, basalt fiber (BF) was utilized to modify cement cured red sandstone soil. The study commenced with the determination of the optimal cement admixture in improved red sandstone soil through disintegration testing. Following this, unconfined compressive strength (UCS) tests, undrained and unconsolidated shear (UU) tests were conducted to assess the impact of BF on the strength and deformation characteristics of the cement cured red sandstone soil. Finally, the intrinsic and damage mechanisms through which BF improves the mechanical properties of cement cured red sandstone soil were elucidated in conjunction with scanning electron microscopy (SEM) testing. The results of the study indicate that cement significantly enhances the water stability of red sandstone soil. The disintegration of the specimens effectively ceased once the cement dosage exceeded 4%. The addition of BF significantly enhances the strength of cement cured red sandstone soil. As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. The incorporation of BF also enhanced the deformation and stability properties of the cement cured red sandstone soil, resulting in increased elastic modulus and failure strain. However, the soil brittleness index exhibited varying degrees of reduction, while ductility was improved. The SEM test results indicate that cement primarily provides cohesion between soil particle. BF effectively inhibits the generation and propagation of cracks through the adhesive properties of cement and its interfacial friction with soil particle, as well as by forming a three-dimensional reinforcing network. The research result demonstrates that the use of BF to enhance cement-cured red sandstone soil significantly improves its mechanical properties, offering a sustainable method for strengthening railway foundations and contributing to advancements in civil engineering applications.