Search Results (801)

Introduction: Drug resistance testing may improve the management of people living with HIV (PLWH) in several scenarios in low- and middle-income countries (LMICs). To guide assay development, the WHO published a target product profile (TPP) outlining two priority use cases (scenarios) for genotypic resistance testing: (1) PLWH with confirmed virological failure (VF) on an integrase strand transfer inhibitor (INSTI)-based regimen, such as tenofovir (TFV) disoproxil fumarate, lamivudine (3TC), and dolutegravir (DTG) and (2) heavily treated PLWH, including infants and young children, with confirmed VF after receiving multiple regimens including a boosted protease inhibitor (PI). An additional potential scenario includes PLWH testing positive for HIV-1 while on pre-exposure prophylaxis (PrEP). Methods: To identify drug-resistance mutations (DRMs) most likely to influence clinical management of PLWH in each WHO TPP scenarios and to inform development of assays that detect individual DRMs and the interpretation of sequence-based assays, we reviewed prevalence and in vitro susceptibility data on HIV-1 DRMs in the Stanford HIV Drug Resistance Database associated with the nucleoside RT inhibitor (NRTI), nonnucleoside RT inhibitor (NNRTI), PI, and INSTI classes and the capsid inhibitor lenacapavir. Results: In the first scenario, the most informative NRTI DRMs were K65R and M184V/I; and the most informative INSTI DRMs were G118R, N155H, Q148H/K/R, and R263K. In the second scenario, a broader spectrum of DRMs is likely to be clinically relevant, including additional NRTI DRMs, the PI DRMs associated with reduced susceptibility to darunavir, and the NNRTI DRMs associated with reduced susceptibility to etravirine and doravirine. In PLWH testing positive for HIV-1 despite PrEP, the most informative NRTI and INSTI DRMs overlap with those in the first scenario, together with the capsid DRMs reported in persons experiencing VF while receiving lenacapavir. Conclusions: As global ART programs increasingly rely on INSTI-based regimens, and as the number of heavily treated individuals and difficult-to-treat pediatric cases grows, many LMICs have begun introducing HIV drug resistance testing for patient management. Although sequence-based assays provide the most comprehensive information for managing individual PLWH, assays that detect individual DRMs are also likely to be highly useful in the three WHO TPP scenarios. Full article

Adequate spray deposition and penetration of pesticides into the lower part of the soybean canopy can increase the chances of successfully protecting plants from diseases and insects. Only a small number of comprehensive studies have examined how spray application parameters (nozzle types, travel speed, droplet size, application rate, application equipment) affect droplet penetration into the inner and lower parts of the soybean canopy. However, the data obtained from replicated plots in these field experiments showed significant variability due to uneven soybean canopy characteristics and unpredictable wind speed and direction. To minimize variability in field studies, this study used a new methodology: conducting the experiment under controlled conditions in a wind tunnel. This research was conducted to evaluate the effect of increasing the distance between soybean rows on the spray coverage and deposition of different droplet size classes from various nozzles, delivering spray to the lower canopy in a wind tunnel. Four commercially available spray nozzles with droplet size classification from medium to extremely coarse were mounted on a spray boom with a spray controller to spray an application rate of 150 L ha⁻¹ under laminar wind speeds of 0, 2.4, and 5.1 m s⁻¹. Rectangular pots containing fully grown soybeans were placed in the test section of the tunnel at center-to-center distances of 0.38 and 0.76 m to replicate narrow and wide row spacings, respectively, commonly used by soybean growers. Eight points in each soybean row were selected to collect spray deposition and coverage with water-sensitive papers (WSPs) and acrylic plates (APs), respectively, at the top, middle, and lower layers of the canopy. Results showed that the top of the soybean canopy consistently received the highest amount of spray, regardless of application conditions, as expected, while the middle and lower layers of the canopy did not receive much spray. Nozzle types and wind speeds were not significant factors in increasing spray penetration into the middle to lower layers of soybean plants. Although wider row spacing improved the spray deposition in the lower part of the canopy, this improvement was not statistically significant. The main conclusions derived from this study indicate that even using wider row spacing configurations, spray penetration into the lower parts of the soybean canopy was limited due to denser canopy conditions and the effects of high wind speeds. Therefore, other advanced spray techniques, such as air-assisted spraying or using other mechanisms to expose lower parts of the canopy to the nozzles, may be needed to effectively overcome these limitations. Full article

To address the problems of subtle style differences, high inter-class similarity, and complex structural and texture features in woodblock New Year paintings, this paper proposes a style classification method for woodblock New Year paintings based on an improved ResNeXt-50. The method introduces SA-CBAM at the middle- and high-level feature stages. Through the synergistic effect of channel attention and edge-enhanced spatial attention, the model is guided to focus on key structural regions such as human contours. Furthermore, single-stage 2D-DWT is introduced to separate deep features into low-frequency global structural components and high-frequency local detail components, thereby enabling effective representation of overall composition information and fine-grained carving textures. The Gram matrix is introduced to conduct statistical modeling of the fusion features, so as to characterize the overall style distribution from the perspective of channel correlation. The model is trained and tested on a dataset of 4043 independent images across six categories, achieving an overall classification accuracy of 97.68%, which is significantly superior to mainstream models such as Vision Transformer. Ablation experiments further verify the complementary effects of each module in structural perception, frequency-domain feature representation, and style statistical modeling, demonstrating the effectiveness and application potential of the proposed method for digital preservation and fine-grained style recognition of woodblock New Year paintings. Full article

Background: Neglected diseases caused by protozoan parasites remain a major public health burden, particularly in low- and middle-income countries. Among the chemical motifs explored in antiparasitic drug discovery, guanidine-containing compounds have attracted considerable attention due to their strong cationic character, high capacity for hydrogen bonding, and versatility in interacting with biological targets. Methodology: This review summarizes advances reported in the last decade regarding guanidine derivatives with activity against pathogens associated with Chagas disease, human African trypanosomiasis, Leishmaniasis, tuberculosis, toxoplasmosis, dengue and schistosomiasis. Results: Evidence gathered from synthetic, natural, and drug-repurposing studies indicates that the guanidine, guanidine-containing and guanidine-related compounds contribute to modulating biological activity by changing electrostatic interactions, hydrogen-bonding networks, and physicochemical properties, with enzymes, nucleic acids, and membrane-associated targets essential for parasite survival. Across the analyzed studies, several emerging structure–activity relationship trends were identified, including the contribution of polycationic or dicationic architectures, the influence of halogenated or lipophilic substituents, and the dependence of biological activity on the complete molecular framework, including heterocyclic systems, macrocycles, peptide conjugates, hybrid scaffolds, and repurposed drugs. In addition to direct antiparasitic effects, certain guanidine-containing and guanidine-related compounds demonstrate immunomodulatory or host-protective properties, expanding the therapeutic relevance of this class. Despite promising in vitro results, protonation trapping, efflux pump susceptibility, and pharmacokinetic limitations such as poor oral absorption, high polarity, plasma protein binding and limited membrane permeability remain significant challenges for clinical translation. Nonetheless, the integration of medicinal chemistry, computational modeling, and biological screening continues to accelerate the identification of optimized scaffolds. Conclusions: Overall, guanidine-based compounds constitute a promising scaffold for the development of new therapeutic strategies targeting neglected parasitic diseases, and further structural optimization may enable the emergence of candidates with improved efficacy, selectivity, and drug-like properties. Full article

This study tackles the middle atmosphere phenomenon known as Mesospheric Inversion Layers (MILs). Reinterpreting Envisat’s GOMOS instrument limb-sounding temperature profiles which we compared to the MSIS-2.0 climatological model, we studied 340,000 resolute temperature profiles, detecting 44,000 (13%) MILs in this dataset. We have shown that MILs are a worldwide phenomenon, concentrated around the tropics and in the Winter Hemisphere’s mid-latitude region (between $30\%$ and $50\%$ of profiles are MILs in those areas). MILs follow a correlation law ($R^2=0.5$ on pure data, $R^2=0.97$ on binned-mean data) between the log-amplitude of its peak and its altitude. Median altitudes are about 70 km worldwide, but the median amplitude reached by equatorial MILs is typically higher (14.5 K compared to the others at 12.5 K). Lastly, equatorial MILs (but not mid-latitude MILs) are correlated with high-difference estimated tide temperature gradient contributions. Results suggest that the MIL is a common phenomenon with statistically consistent characteristics. Seasonal occurrence hinted that there is probably a class of MILs favoured by planetary waves at the edge of the polar vortex, while the equatorial type of inversions seems to occur when the atmospheric tide model flattens the temperature gradient around 70 km. Full article

This study examined a moderated mediation model linking parental rejection and overprotection to smartphone addiction, with sense of security as a mediator and forgiveness as a moderator. A total of 730 students (mean age = 12.15 ± 1.13 years; 50.7% female) were recruited from two primary and two secondary schools in Hunan, China, using cluster sampling by class, and all participants completed a set of self-report questionnaires. Results showed that, after controlling for gender and age, both parental rejection and overprotection were positively associated with smartphone addiction and negatively associated with sense of security and forgiveness. Sense of security partially mediated the links between negative parenting and smartphone addiction. Interpersonal forgiveness moderates the direct associations between parental rejection, overprotection and adolescent smartphone addiction, and self-forgiveness moderates the relationships between sense of security and smartphone addiction. The present study clarifies the associations between negative parenting behaviors (i.e., parental rejection and overprotection) and problematic smartphone use in early and middle adolescence, highlights the vital protective roles of security and forgiveness, and provides empirical evidence to inform the prevention and intervention strategies for adolescent smartphone addiction. Full article

Rapid population growth is increasing housing demand and accelerating the expansion of the built environment in Egypt. However, practical and sustainable residential building decarbonization remains constrained by limited supplies of supplementary cementitious materials, limited structural timber resources, code restrictions on cement reduction, and cost sensitivity. This study evaluates two Egyptian multi-unit residential case studies—one affordable housing project and one middle-class housing project—to assess whether wall-system substitution can reduce both embodied and operational carbon under local material, code, and cost constraints. An integrated BIM-based digital twin workflow was used to link quantity takeoff, finite-element structural assessment, and whole-building energy simulation. An architectural BIM model was used for material quantification, wall-system definition, and energy-model inputs. A structural model was used to assess the effects of reducing wall density on reinforcement and concrete demand under gravity and seismic load combinations. Operational performance was assessed through cooling-focused energy simulations under hot-arid climatic conditions representative of Egypt’s new desert cities. Alternative wall systems were then evaluated through scenario- based material substitution and revised structural and energy assessments. The results show that reinforcement, concrete, and wall- core materials account for about 80% of total embodied carbon, while cooling accounts for about 72% of operational emissions. Non-structural cement uses, mainly mortars and finishes, account for 36% of total cement demand, ranging from 161 to 229 tons per building across the two case studies. Replacing conventional partition walls with lightweight, energy-efficient alternatives reduced embodied carbon by up to 35.2%, operational carbon by about 15.7% to 16.5%, and total life-cycle carbon by about 17.4% to 17.5% over a 60- year service life. The average savings per building corresponded to avoiding about 30 tons of steel, 165 m³ of ready-mix concrete, and 191 m³ of mortar, with net cost savings of about 3.15 million EGP per building. These results identify a practical pathway toward more sustainable, lower-carbon Egyptian residential buildings without increasing project cost. Full article

This study examines behavioral predictors of academic success among seventh graders enrolled in the Russian School of Mathematics, a rigorous extracurricular mathematics program. Using a comprehensive set of engagement and homework indicators available for the online portion of our classes, multiple regression models were applied to explore how persistence, time management, and participation predicted performance across three curriculum levels, namely Accelerated, Advanced, and Honors. Accelerated and Honors students exhibited similarly strong work habits but required different types of instructional support. Advanced-level students were further distinguished into “progressing” and “plateaued” groups, each with unique behavioral profiles. Across levels, several habits such as starting homework promptly, revisiting unsolved problems, and providing detailed work were consistently associated with higher achievement. These findings highlight the value of differentiated instruction and targeted feedback, particularly in mixed-ability classrooms. By identifying the behaviors most closely linked to success, this work offers actionable insights for fostering self-regulated learning in middle school mathematics. Full article

Ononis spinosa L. (Fabaceae), commonly known as spiny restharrow, is a widely distributed medicinal plant traditionally used in European and Middle Eastern phytotherapy, particularly for the management of urological and inflammatory conditions. Despite its long-standing ethnomedicinal relevance, comprehensive syntheses of its phytochemical profile and biological activities remain limited. This review aimed to summarize current evidence regarding the chemical constituents and pharmacological effects of O. spinosa. Four electronic databases (PubMed, Scopus, Web of Science, and SpringerLink) were searched for studies published between 1997 and 2024. The search yielded 308 records; after duplicate removal and eligibility screening, 34 studies met the inclusion criteria. The phytochemical profile of O. spinosa is characterized predominantly by isoflavonoids (e.g., ononin and other formononetin derivatives), triterpenes, phenolic acids, and additional polyphenolic compounds. Although the phytochemical profile of O. spinosa includes multiple classes of secondary metabolites, this review places particular emphasis on phenolic compounds, given their prevalence and well-documented biological activities. Experimental evidence indicates a broad spectrum of biological activities, including anti-inflammatory effects (associated with cPLA2α inhibition and cytokine modulation), antibacterial and antifungal activity, antioxidant capacity, wound-healing and dermatological benefits, as well as diuretic and anti-adhesive effects in urinary models. Additional reported properties include antiproliferative, anti-adipogenic, analgesic, and neurotrophic activities. Proposed mechanisms of action involve enzyme inhibition (e.g., Hyal-1 and COX-2), modulation of transient receptor potential (TRP) channels, redox regulation, and interference with microbial adhesion and inflammatory signaling pathways. Overall, O. spinosa contains bioactive compounds exhibiting a wide range of pharmacological activities supported by in vitro and in vivo studies. Among the investigated effects, anti-inflammatory, urological, and wound-healing activities appear to be the most promising targets for future research. These findings highlight its therapeutic potential while emphasizing the need for well-designed clinical studies to further validate its medicinal applications. Full article

The concepts of “circular economy” and “sustainable chemistry” cover a range of related topics, including resource efficiency, the transition to renewable resources, as well as the choice of recycling, reusing, or recovering materials. At the middle school level, the “green message” of chemistry and the circular economy can be conveyed during regular classes or optional subjects. This paper presents an experimental study conducted with middle school students, aiming to develop ecological competencies by comparing traditional educational methods of teaching–learning–assessment with modern methods. The study was conducted on a sample of 58 lower secondary students (N = 30 in class 8A—traditional methods; N = 28 in class 8B—modern/STEM-based methods), using a quasi-experimental pre-test/post-test design using a questionnaire. The results indicated a significant improvement in students’ performance, with correct response rates increasing from 17–33% in the pre-test to over 80–100% in the post-test across most items. While both traditional and modern teaching methods improved students’ theoretical understanding of green chemistry and circular economy concepts, the modern STEM-based approach facilitated higher performance in application-oriented items, critical thinking, and real-life problem-solving tasks. The study emphasizes the importance of fostering an environmentally friendly attitude among students, encouraging a commitment to sustainability, as well as their active involvement in pollution prevention. Thus, the effectiveness of the applied educational strategies in increasing ecological awareness is underlined. Full article

Urinary Tract Infections (UTIs) represent one of the most prevalent bacterial infections globally, posing significant health burdens, especially in low- and middle-income countries (LMICs), due to delayed diagnoses, limited access to laboratory services, and rising antimicrobial resistance. This study presents a machine learning (ML)-based diagnostic support framework for early UTI detection, leveraging structured clinical data and explainable artificial intelligence (XAI) techniques to enhance interpretability and trust among healthcare providers. A patient dataset containing 4865 records was used in the study to train and test Extreme Gradient Boosting (XGBoost), Decision Tree (DT) and Random Forest (RF) classifiers, while class imbalance was addressed using Synthetic Minority Over-sampling Technique (SMOTE). The performance of the models was evaluated through accuracy, precision, recall, F1-score, Log Loss, and AUC-ROC, and random forest showed the best results (accuracy: 86.43%, F1-score: 86.71%, AUC-ROC: 0.8695). To ensure that such models can be adopted by stakeholders in the health sector, Local Interpret-able Model-agnostic Explanations (LIME) were integrated, which identified painful urination, urinary frequency, and suprapubic pain as primary predictors in the model. This study shows that interpretable ML models can be helpful in resource-limited regions in predicting UTIs, thereby rendering a solution to improve the management of infections in these regions. Full article

Equity in gifted education remains a persistent international challenge, particularly regarding the “excellence gap” in advanced achievement and long-term attainment. This study investigates the supports and barriers shaping the talent development of socio-economically disadvantaged gifted students in Taiwan. Using a retrospective narrative inquiry, we analyzed the life stories of 25 alumni from the “Bright Minds Award Program,” a long-term initiative providing financial aid, mentorship, and enrichment opportunities for high-ability learners from low-income households. Findings indicate that participants often displayed early academic promise, yet their developmental trajectories were continuously negotiated under structural constraints (limited material and cultural resources, restricted access to domain-specific cultivation, and opportunity gaps across educational transitions) and the psychosocial burden of poverty (shame, stigma management, and identity strain). Drawing on the Actiotope Model of Giftedness, we identify how exogenous educational capital (e.g., scholarships, information brokerage, mentoring networks) and endogenous learning capital (e.g., resilience, self-regulation, goal persistence) interact to stabilize—or destabilize—developmental pathways. A novel contribution is the emergence of “Acting Middle Class” as a coping mechanism through which participants navigated social stigma and the hidden curriculum of elite educational settings. We argue that effective intervention requires not only resource provision but sustained “educational scaffolding” that is psychologically safe and institutionally stigma-sensitive. Implications are discussed for talent development research, school practice, and equity-oriented policy designs aimed at preventing talent attrition and promoting developmental justice. Full article

Background/Objectives: Schools may represent an ideal setting for increasing vaccine literacy and uptake. This quasi-experimental study took place between February and June 2025 with the aim of assessing the feasibility and effectiveness of a school-based educational intervention about vaccination among Italian adolescents. Methods: The European Commission’s e-Bug methodology was used to enhance vaccine knowledge in a sample of students attending four randomly chosen middle schools from Southern Italy. Pre and post-intervention vaccination knowledge was assessed through a questionnaire and compared through the Wilcoxon signed-rank test. Regression models were used to identify predictors of intervention-related outcomes. Results: A total of 262 students (mean age 12.3 ± 0.7 years, 52.3% female) participated in the study. A significant increase in vaccination knowledge score was registered from pre (5.6 ± 1.43) to post-intervention (6.79 ± 1.77). A significant improvement was found to be related to a lower number of cohabitants (OR = 0.61; 95% CI = 0.45–0.82), a lower score in the pre-test (OR = 0.60; 95% CI = 0.47–0.77), having considered the information provided completely clear (OR = 1.98; 95% CI = 1.05–3.74), and being willing to participate in similar future interventions (OR = 2.23; 95% CI = 1.12–4.42). Conclusions: These results show the effectiveness of school-based education strategies in increasing vaccine literacy within the targeted adolescent population. Similar interventions can be useful to increase compliance with vaccination in this age class. Randomized controlled studies are needed to confirm these findings. Full article

Context: In numerous low- and middle-income nations, malaria remains a significant issue due to the challenges associated with diagnosing it through thin blood smears. The appearance of images can vary significantly depending on the microscope type, magnification, lighting conditions, slide preparation methods, and staining techniques. Due to the delicate morphology of parasites, false negatives might adversely affect patient care. Objective: To achieve optimal outcomes from validation, it is essential to construct a robust and easily replicable process. This pipeline should integrate the optimal elements of classical machine learning and end-to-end deep learning, enhance reliability by pairwise ensembling, and select ensemble weights in a logical, data-driven manner. Method: To achieve our objective, we propose two tracks. The initial track encompasses real-time augmentation, convolution-based feature extraction, and the training of calibrated classical classifiers. The second module focuses on training many convolutional networks from inception to completion. Subsequently, we construct paired ensembles and employ a hybrid methodology to select convex weights for combining the findings. This method initially evaluates a set of candidate weights and then refines them to maximise validation accuracy. Results: The precision of the two-track architecture consistently improves, transitioning from conventional baselines to end-to-end models. Optimal and consistent enhancements are achieved through weighted ensembling. Utilising optimised fusion reduces the incidence of false negatives for subtle parasites and false positives caused by staining artefacts. This yields an accuracy of 96.35% on the reserved data and reduced variance across folds. Conclusions: The integration of augmentation, multiple modelling tracks, and optimal pairwise ensembling yields the highest accuracy in categorising malaria smears. It facilitates further enhancements by incorporating supplementary models, multi-class extensions, and operating-point calibration. Full article

This paper considers the problem of controlling the motion of an autonomous underwater vehicle (AUV) following a leader in a leader–follower scheme based on visual information about the leader’s position. It is assumed that the leader is equipped with a system of light markers with known geometry, and the follower determines its relative position based on data from an onboard camera without using a hydroacoustic communication channel or direct exchange of navigation information. To synthesize the control law, a reinforcement learning method based on the Proximal Policy Optimization algorithm is used. Policy learning is performed in a simulation environment, taking into account the dynamic model of the agent in the horizontal plane and observation noise. A structure of state space, actions, and reward function is proposed, aimed at minimizing the error in relative position and orientation. Additionally, Bayesian optimization of the weight coefficients of the reward function is performed. Bayesian optimization of the reward function weights reduces the RMS tracking error from 0.24 m to 0.09 m and demonstrates that heading regulation has a significantly stronger impact on stability than position penalties. The results of modeling, testing in the Webots environment, and experiments on MiddleAUV class devices confirm the feasibility and scalability of the approach. It is shown that a single trained policy ensures stable formation maintenance when the number of follower agents and initial conditions change without additional retraining. Full article