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A theoretical study on the corrosion inhibition of Cu surfaces using 4-amino-3-thioxo-6-methyl-1,2,4-triazine-5-one and its derivatives

Synergistic optical, dielectric and visible-light photocatalytic enhancement in Mo-modified BaTiO3 nanostructures

Abstract Molybdenum-doped barium titanate (BaTiO 3 ) nanostructures were fabricated by a solid-state reaction and evaluated for simultaneous enhancement of dielectric and optical performance. X-ray diffraction confirmed that progressively higher Mo content drives a tetragonal to cubic phase transformation, evidencing effective lattice tuning. Complementary SEM and EDX analyses showed well-defined grain morphology and uniform elemental distribution, verifying successful Mo incorporation. XPS detected Mo in mixed valence states (Mo 3+ /Mo 4+ /Mo 6+ ) together with Ti 3+ species, implicating abundant oxygen vacancies that promote charge transport and surface reactivity. Dielectric measurements revealed a marked rise in room-temperature permittivity accompanied by lower loss, indicating improved polarization dynamics. UV–vis diffuse-reflectance spectra displayed a red-shifted absorption edge and a band-gap narrowing from 3.24 eV (pristine BaTiO 3 ) to 2.92 eV (MBT4), thereby extending visible-light harvesting. All Mo-doped BaTiO 3 samples exhibited notable visible-light photocatalytic performance, with the 3% Mo-doped sample (MBT3) achieving significantly enhanced degradation of Congo red dye under direct sunlight. Notably, MBT3 demonstrated about 90% degradation efficiency within 60 min, compared to the slower response of undoped BaTiO 3 , and the corresponding photocatalytic rate constant increased from 0.01754 min −1 (pure BTO) to 0.03673 min −1 , underscoring the superior reactivity and light-harvesting capability imparted by Mo incorporation. These results demonstrate that Mo incorporation simultaneously tailors BaTiO 3 crystal structure, electronic structure, and dielectric response, positioning the material as a promising multifunctional candidate for sustainable energy and environmental applications.

Rapid 3D phenotyping of chick embryo liver development at HH22-HH41 embryonic stages using X-ray microcomputed tomography with PTA staining

Animal models, particularly the chicken embryo (CE), remain crucial for advancing developmental biology and medicine. Liver embryogenesis, a complex and tightly regulated process, is particularly susceptible to developmental abnormalities. This study presents a comprehensive 2D and 3D µCT analysis of CE liver development (HH22–HH41) using a refined 1% phosphotungstic acid (PTA) staining protocol. Our methodology yielded high-resolution visualization of liver microstructures, including intricate vascular networks, with image quality and contrast comparable to histological analysis. Quantitative assessment revealed a critical period of rapid liver growth between incubation days 6 and 9 (HH29–HH35), followed by the stabilization of hepatic vascular volume by day 10 (HH36). The ease of structural orientation in µCT datasets, enhanced by 3D renderings, further underscores the technique’s utility. By establishing µCT as an effective tool for liver imaging, this study provides essential normative data on the liver’s spatial organization, morphology, and vascular architecture during embryogenesis, thereby opening new avenues for research in embryology, teratology, pharmacology, and toxicology.

Assessment of meridic larval and adult diets for mass rearing of Bactrocera dorsalis (Diptera: Tephritidae)

The oriental fruit fly, Bactrocera dorsalis (Diptera: Tephritidae), is a widespread pest in Bangladesh. Sterile Insect Technique (SIT) offers a solution for effectively suppressing this fruit fly species. However, SIT involves mass rearing of fruit fly species in a laboratory where a standardized artificial rearing diet is crucial for ensuring uniform growth, development, and reproduction. In this study, we assessed efficacy of a new formulated gel-based meridic larval diet as well as protein and carbohydrate rich adult diets for the rearing of B. dorsalis in laboratory conditions. Proximate analysis was conducted for our formulated rearing diets to determine the content of moisture, protein, fat, carbohydrate, and ash. For our formulated diets, several key biological parameters, including egg hatching rate, pupation rate, pupal weight, adult emergence, adult growth, sex ratio, and flight capacity, were assessed. Statistical analysis using Tukey box plots revealed a significant improvement for the laboratory reared body parameters of adults while maintained in meridic diets, as compared to their wild counterparts. Adults fruit flies reared on our formulated meridic adult diets exhibited sufficient longevity, especially when compared to those provided with only water. In addition, our study presents survival analysis using non-parametric Kaplan–Meier estimator and Weibull parametric model. Our findings indicate that the formulated diets presented in this study can be effectively incorporated into B. dorsalis laboratory mass-rearing, meeting the required standard quality parameters outlined in the FAO/IAEA/USDA mass-rearing guideline of tephritid fruit flies.

Research on emission reduction investment strategies for low carbon technology enterprises

This study investigates optimal capital allocation strategies for corporate decarbonization initiatives under technological transition constraints. A decision analysis framework grounded in real options theory is developed, incorporating fuzzy-set parameters to address implementation uncertainties in emission mitigation systems. Analytical results demonstrate inverse correlations between critical intervention factors (technological decarbonization efficiency, environmental taxation levels, eco-product market premiums, and fiscal incentive mechanisms) and capital deployment thresholds. Improved technical specifications, reinforced regulatory constraints, positive consumer responses, and targeted subsidy mechanisms synergistically facilitate sustainable infrastructure investments. Comparative evaluations confirm the proposed fuzzy option model’s superiority over conventional NPV methods in valuing managerial flexibility and mitigating valuation biases. Sequential option analysis reveals that modular implementation approaches can generate incremental value through adaptive capacity in operational execution. Empirical validation through ‘’industrial case studies illustrate the framework’s practical efficacy in assessing sustainable technology portfolios, offering actionable insights for strategic planning in carbon-intensive industries. This research contributes methodological advancements for timing optimization and risk assessment in environmental technology adoption scenarios.

Auditory sensory processing induces cortical and thalamic event-related desynchronization in the mouse

Studies of human perception have shown early cortical signals for primary information encoding, and later signals for higher order processing. An important late signal is the cortical event-related desynchronization (ERD) in the alpha (8–12 Hz) and beta (12–30 Hz) frequency band, which has been linked to human perceptual awareness. Detailed mechanistic investigation of the ERD would be greatly facilitated by availability of a suitable animal model. We conducted local field potential recordings in the mouse frontal association cortex (FrA), thalamic intralaminar centrolateral nucleus (CL), primary auditory cortex (A1), and primary visual cortex (V1) during two auditory tasks. Fully audible brief 50 ms stimuli with both tasks produced early broadband gamma (30–100 Hz) frequency activity at 0–250ms, followed by a late cortical alpha/beta ERD 250–750 ms after stimulus onset. The ERD was statistically significant in FrA and A1, but not in V1. Interestingly, a significant ERD was also observed in thalamic CL. The magnitude of the ERD at full stimulus intensity, and the slope of the relationship between stimulus intensity versus ERD magnitude, were both largest in FrA, and smaller in CL and A1. Conversely, for early broadband gamma activity the magnitude at full intensity and slopes were largest in A1, smaller in CL and smaller still in FrA. These findings strongly support mice as a promising platform for further investigation of the ERD to better understand the origin and function of this robust yet understudied electrophysiological phenomenon.

Online exposure to marriage information and marriage expectations of Generation Z in China: The roles of marriage value and relative information exposure

Purpose The marriage expectations of Generation Z youth in China, the main force of marriage currently and over the next decade, are declining. In this study, several moderated mediation models were constructed to explain the effects of online exposure to marriage information on the marriage expectations of Gen Z from an information processing perspective. Participants and methods A total of 1,390 questionnaires, based on the Online Exposure to Marriage Information Scale, Relative Information Exposure Scale, Marriage Values Scale, and Marriage Expectation Scale, were collected from Gen Z youth across 31 provincial administrative regions in China. Preliminary data analysis was conducted using SPSS 24.0, and the mediation effect test and moderated mediation effect test were conducted using Process 3.5. Results The results indicated that (1) online exposure to marriage utility information was positively related to marriage intention, and online exposure to marriage cost information was negatively related to marriage intention; (2) marriage values mediated the relationship between online exposure to marriage information and marriage intention and that between online exposure to marriage information and expected marriage age; and (3) relative utility and cost information exposure played opposite moderating roles in the relationship between online exposure to marriage information and marriage intention, ultimately inhibiting the marriage intention of Chinese Generation Z. Conclusion Different types of online exposure to marriage information and the relative information exposure of Chinese Generation Z individuals have varying impacts on their marriage values and marriage expectations. Policy-makers and online platforms should enhance supervision and guidance on online marriage information. Additionally, Generation Z youth should adjust their relative exposure to cultivate healthy marriage values.

Identification of novel therapeutic inhibitors against E6 and E7 oncogenes of HPV-16 associated with cervical cancer

Human Papilloma Virus type 16 (HPV-16) is highly oncogenic with the E6 and E7 oncogenes playing crucial roles in the pathogenesis of HPV-related cervical carcinogenesis. Targeting these oncoproteins with specific inhibitors offers a promising approach for therapeutic intervention. This study aimed to identify potential inhibitors of the HPV-16 E6 and E7 oncoproteins through an in silico approach, providing a foundation for the development of targeted therapies against HPV associated malignancies. We performed virtual screening on a library of 1000 compounds to identify promising candidates. Subsequent molecular docking studies were conducted to assess the binding affinities of the promising candidates. The top-scoring compounds for oncoproteins were then subjected to molecular dynamics simulations to evaluate their stability and interaction profiles. The virtual screening identified 14 promising candidates followed by docking studies. Among these Galangin was identified as a promising inhibitor for the E6 oncogene, while Neoechinulin showed potential as an inhibitor of the E7 oncogene. Our findings suggest Galangin and Neoechinulin with high potential as therapeutic inhibitors of HPV-16 E6 and E7 oncogenes respectively. These inhibitors could contribute significantly to the development of targeted therapies against HPV associated malignancies. However, further in vitro and in vivo investigations are required to use these phytochemicals as antiviral agents against HPV-16.

Development and characterisation of fast dispersible dimenhydrinate tablets: Compactional study and in-silico PBPK modeling

The aim of this study was to optimize and evaluate dimenhydrinate fast dispersible tablets (50 mg) by utilizing cost effective direct compression method. A total of nine formulations (F1-F9) were designed and developed by central composite rotatable design using design expert ® software (version 11.0, Stat-Ease Inc.,) to study the impact of avicel PH102 (15–55%) and sodium starch glycolate (2–8%) on responses, i.e., hardness (R 1 ), disintegration time (R 2 ) and % drug release (R 3 ). Powder blends of all formulations showed good flow behavior. Post compressional studies were conducted to assess the quality attributes of the compressed formulations. Formulation F2 was found to be optimized with good mechanical strength, i.e., hardness 4.2 kg, friability 0.77%, disintegration time 19 secs and % drug release 100.01% at 15 minutes. Compressional behavior of optimized formulation was determined with the help of Heckle plot. The PY (yield value) and the tensile strength of the optimized formulation (F2) were found to be 66.66 MN/m 2 and 1.093 ± 1.66 to 1.642 ± 1.76 MN/m 2 respectively. Differential scanning calorimetric and scanning electron microscopy analysis were performed to explore compatibility between ingredients and morphological features. All formulations followed weibull model in four different dissolution media. All the formulations were found to be stable at accelerated conditions. The in-silico GastroPlus™ PBPK modeling was also carried out to determine the pharmacokinetic parameters of the optimized formulation (F2) as an alternative to in vivo dimenhydrinate studies. Simulated PK values of F2 were found to be 143.16 ng/ml (C max ), 2 h (T max ), 2533.8 ng-h/ml (AUC 0-inf ) and 1477.9 ng-h/ml (AUC 0-t ). Results indicated that the fold error value was > 2 which indicated that experimental values are comparable with the predicted values. This type of study will be helpful for pharmaceutical manufacturers to produce patient compliance, low-cost tablet dosage form.

Retrieval-augmented Chinese text-to-SQL generation for conversational bibliographic search

To overcome the limitations of current bibliographic search systems, such as low semantic precision and inadequate handling of complex queries, this study introduces a novel conversational search framework for the Chinese bibliographic domain. Our approach makes several contributions. We first developed BibSQL, the first Chinese Text-to-SQL dataset for bibliographic metadata. Using this dataset, we built a two-stage conversational system that combines semantic retrieval of relevant question-SQL pairs with in-context SQL generation by large language models (LLMs). To enhance retrieval, we designed SoftSimMatch, a supervised similarity learning model that improves semantic alignment. We further refined SQL generation using a Program-of-Thoughts (PoT) prompting strategy, which guides the LLM to produce more accurate output by first creating Python pseudocode. Experimental results demonstrate the framework’s effectiveness. Retrieval-augmented generation (RAG) significantly boosts performance, achieving up to 96.6% execution accuracy. Our SoftSimMatch-enhanced RAG approach surpasses zero-shot prompting and random example selection in both semantic alignment and SQL accuracy. Ablation studies confirm that the PoT strategy and self-correction mechanism are particularly beneficial under low-resource conditions, increasing one model’s exact matching accuracy from 74.8% to 82.9%. While acknowledging limitations such as potential logic errors in complex queries and reliance on domain-specific knowledge, the proposed framework shows strong generalizability and practical applicability. By uniquely integrating semantic similarity learning, RAG, and PoT prompting, this work establishes a scalable foundation for future intelligent bibliographic retrieval systems and domain-specific Text-to-SQL applications.

Intersecting challenges and ways forward: The impact of the COVID-19 pandemic on an urban First Nations community in Southern Ontario, Canada

The COVID-19 pandemic has had wide-ranging impacts on communities worldwide, with Indigenous communities in southern Ontario, Canada, being no exception. Partnering with Aamjiwnaang First Nation, we explored the multifaceted impacts of the pandemic and learnings for the future. This study utilized semi-structured interviews with the community’s pandemic committee and other front line essential services (N = 12) to explore the nuanced dimensions of the pandemic’s effects. Data were analysed using a template approach to codebook thematic analysis to examine various aspects of the pandemic response. Five main themes were identified, including: (i) Wellbeing and mental health, (ii) Work-life balance, (iii) Community and social factors, (iv) Organizational dynamics, and (v) Lessons learned and future planning. Our findings unveiled a multifaceted spectrum of challenges, encompassing socioeconomic, psychological, and organizational aspects, which the First Nations community encountered amidst the pandemic. Despite these challenges, the commitment to community adaptation and collaboration highlighted the resilience cultivated through strong Indigenous leadership, trusting partnerships, and transparent communication, contributing to an effective response. This research stresses the need for future pandemic preparedness efforts to prioritize Indigenous leadership and address the social and cultural determinants of Indigenous health. Additionally, to effectively address future environmental and health emergencies, there is a pressing need to adopt an all-hazards approach and develop comprehensive, yet adaptable plans tailored to meet the diverse needs of communities.

Normative value of upper extremity Y balance test in healthy subjects aged between 18 and 36 years from South India: A cross-sectional study

Introduction The Upper Quarter Y Balance Test (UQYBT) is a validated tool used to assess unilateral upper extremity function in a closed kinetic chain. It evaluates parameters such as mobility, stability, and injury risk, and can inform rehabilitation planning. Normative data have been well established for adolescent and active adult populations in the United States. This study aims to establish normative UQYBT values for healthy adults aged 18–36 years in the Indian subcontinent. Methods A total of 190 healthy young adults (95 males and 95 females) aged 18–36 years who met the eligibility criteria were included. Baseline demographic data—age, height, weight, body mass index (BMI), and limb length—were collected. Participants performed the UQ-YBT by reaching in the inferolateral, medial, and superolateral directions using the three-reach box. Average reach distances were calculated for each limb, and composite scores (CS) were normalized using arm length. Results Age- and sex-specific reference values were established for both upper extremities and for average bilateral performance. Males demonstrated significantly greater reach distances than females; however, the difference decreased after normalization for limb length. Age-related variations were observed, with participants aged 26–30 years achieving the highest normalized reach scores (p < 0.05). Conclusion The age- and sex-specific normative values obtained from this study can serve as benchmarks for assessing shoulder mobility and stability among healthy Indian adults aged 18–36 years.

“I just thought I was lucky to be protected from HIV:” Qualitative evaluation of barriers and facilitators of pre-exposure prophylaxis use for adolescent girls and young women at higher risk of HIV acquisition in Lilongwe, Malawi

Adolescent girls and young women (AGYW) are at higher risk of HIV acquisition than their male counterparts, especially in sub-Saharan African countries such as Malawi. Therefore, HIV prevention programming is a key component to reducing this risk. We conducted a formative qualitative assessment with AGYW and their health providers to understand AGYW’s perceptions of their own HIV risk, self-efficacy to protect themselves, and the implications of these factors on pre-exposure prophylaxis (PrEP) use. Our study found that AGYW are aware and interested in using PrEP, which can allow choices that protect their sexual health and well-being. Innovative service delivery models that minimize stigma and offer other reproductive health services such as contraception are needed to provide comprehensive care. Additionally, AGYW and their health providers would benefit from education about HIV risk perception and PrEP effectiveness to improve use of PrEP. Robust AGYW PrEP service delivery, including new biomedical prevention strategies, may facilitate efforts to achieve epidemic control.

Dual-resonance optical fiber lossy mode resonance refractive index sensor

In this paper, we propose a dual-channel surface refractive index sensor based on optical fiber lossy mode resonance (LMR). A multilayer transmission matrix model is constructed to simulate and analyze the optical fiber LMR effect based on two semiconductor oxides, SnO 2 and TiO 2 . Through the rational design of structural parameters, we successfully realize the coexistence of mutually independent LMRs on a single fiber, thereby enabling dual-channel sensing. The dual-channel optical fiber LMR sensor was prepared by electrostatically assembling TiO 2 nanofilms and SnO 2 nanofilms on the sidewall of the optical fiber. The refractive index sensitivity of the dual-channel optical fiber LMR was evaluated via wavelength interrogation, achieving dual-channel refractive index sensing. The refractive index sensitivities are 538.422 nm/RIU and 615.647 nm/RIU in the range of 1.3350 ~ 1.3742. The dual-channel optical fiber LMR refractometer designed in this investigation is a promising platform for the simultaneous detection of multiple protein species and heavy metal ions in biochemical applications.

Impacts of agricultural machine renting on cereal crop productivity and commercialization in West Gojjam Zone, Ethiopia

Agricultural mechanization plays an essential role to increase production, productivity and commercialization of cereal crops. Despite the Ethiopian’s government has made substantial efforts to increase production, productivity and commercialization of cereal crops by the introduction of selective and adaptable agricultural machines to smallholder farmers has remained low. This study, therefore, investigated the impacts of agricultural machine renting on cereal crop productivity and commercialization. The study used cross-sectional data collected from 192 agricultural machine users and 208 non-users from West Gojjam zone, Ethiopia. The data were analyzed using descriptive statistics and econometric models. The econometric model includes Trans log production function, Endogenous switch regression and propensity score matching. The result of descriptive statistics showed that the total factor productivity index of the cereal crop was 2.89, and the mean commercialization index for the sample households was 0.506. The estimation of results of Trans log production function model showed an average level of Technical Efficiency of 80.6%. The result of first stage Endogenous switch regression model showed that age, education level, ownership of oxen, total cultivated land, extension visit, access to information, family size, the position a farmer, and distance to the nearest market significantly affected adoption of agricultural machine renting. The result of endogenous switching regression and propensity score matching models showed that agricultural machine renting had a positive and significant impact on the selected outcome variables, total factor productivity, technical efficiency and output commercialization index. Based on the findings, the study suggests that the government and stakeholders should focus on strengthening the provision of education, development of infrastructures, extension service, to promote agricultural machine renting service, and enhance cereal crops productivity and commercialization.

Predicting microscopic vehicle collision risks at toll plaza diverging area using bayesian dynamic logistic regressions

The absence of lane markings at toll plaza diverging areas results in frequent vehicle weaving motions, making these areas typical high-risk bottlenecks on highways. Existing conflict prediction methods often rely on historical data and static models, which lack adaptability to dynamic changing traffic conditions. This study proposes a Bayesian dynamic logistic regression approach capable of self-adaptive prediction of vehicle collision risks at toll plaza diverging areas. First, the aggregated traffic characteristics were extracted from the high-precision vehicle trajectory data and the indicator Extended Time-to-Collision (ETTC) was employed to measure multi-directional vehicle collision risks. Then, Bayesian dynamic logistic regression models were developed based on aggregated traffic characteristics from different sampling strategies. Results show that as the data volume increases, the Area Under the Curve (AUC) values of these models all gradually exceeds 0.9, demonstrating strong self-adaptive correction capabilities. Compared with standard logistic regression models, the Bayesian dynamic logistic regression models identified more influencing factors and required only 20% of the data for initialization, while continuously updating estimates with incoming data, significantly reducing computational resource demands for collision risk prediction. Furthermore, sensitivity analysis of the forgetting parameter indicates that incorporating richer prior information enhances predictive accuracy. These findings provide valuable insights for developing tailored management strategies to reduce potential traffic conflicts at toll plaza diverging areas.

Biological control of citrus rust mite Phyllocoptruta oleivora by three bacterial species

Association between no-shows to scheduled clinic appointments and 30-day risk of overdose in patients prescribed methadone for opioid use disorder

Background The introduction of synthetic opiates and non-opiate sedatives into the illicit drug market has increased overdose risk for individuals who use opiates and other drugs. The ongoing risk of overdose for patients receiving methadone as a medication for opioid use disorder in the context of this more potent and less predictable drug supply is not well characterized. Additionally, little research has explored whether commonly available clinical data (including data available even in low resource settings) can predict near-term acute overdose in patients prescribed methadone for opioid use disorder. Objective To determine whether the number of recent no-shows to scheduled clinic appointments in the past 30 days is associated with 30-day overdose risk among patients enrolled in one Opioid Treatment Program who are prescribed methadone for opioid use disorder. Methods We analyzed clinical records from 1,049 patients in an opioid treatment program (May 2020–April 2024), and for each patient-day, counted the number of no-shows to scheduled clinic appointments (not methadone administrations) in the previous 30 days. Associations between the number of standardized no-shows in the past 30 days and overdose in the subsequent 30 days were analyzed with logistic regression via generalized linear model controlling for temporal and patient-specific variables. Goodness of fit was assessed with marginal R 2 and a simulation-based approach designed for multilevel models. Results The sample included 56 overdoses with an average of 0.919 no-shows in the last 30 days (std. dev 1.37). The z-standardized number of no-shows to scheduled appointments in the past 30 days was both statistically and clinically significantly associated with risk of overdose in the next 30 days adjusting for study month and season (odds ratio 1.18 [95% CI 1.13–1.23] P < 0.001), as well as adjusting for demographics and overdoses during study period (odds ratio 1.28 [95% CI 1.22–1.34] P < 0.001), and a marginal R 2 of 0.04. Model diagnostics revealed adequate fit using a generalized additive model, with results virtually unchanged from the generalized linear model. Conclusion No-shows to scheduled clinic appointments in the past 30 days are significantly associated with overdose risk in the next 30 days with a linear relationship among patients receiving methadone in a single opioid treatment program. Population-specific acute risk prediction tools could help clinicians prioritize resources for timely intervention.

Research on the law of multiple mining in close coal seams and the roadway support of lower coal seam

Comparison of serum lactate and lactate-derived ratios as prognostic biomarkers in pediatric dengue shock syndrome using supervised machine learning models

Background Dengue shock syndrome (DSS), with critical complications encompassing mechanical ventilation (MV), dengue-associated acute liver failure (PALF), and encephalitis, is associated with high mortality in children. Although serum lactate is a recognized prognostic biomarker, it may not fully reflect the complex metabolic disturbances in DSS. Recent evidence suggests that lactate-derived indices, including lactate-to-albumin ratio (LAR) and lactate-to-bicarbonate ratio (LB), may enhance prognostic accuracy. This study aimed to evaluate and compare the predictive performance of the LAR, LB ratio, and serum lactate levels in pediatric DSS using machine learning approaches. Methods and findings We conducted a secondary analysis of a retrospective cohort study involving children with DSS at a tertiary pediatric center in Vietnam (2013–2022). The primary composite endpoint included in-hospital mortality, MV, dengue-associated PALF and encephalitis. Predictors were selected based on clinical expertise, literature review, Akaike Information Criterion and Least Absolute Shrinkage and Selection Operator. Multiple supervised machine-learning algorithms – logistic regression, random forest (RF), support vector machine (SVM), k-nearest neighbor, naïve Bayes, AdaBoost, and XGBoost - were applied. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and feature importance was assessed using Shapley Additive Explanations (SHAP). Results Of the 524 eligible patients (median age: 8.7 years), 17% met the composite endpoint. At admission, LAR demonstrated superior discriminatory ability (AUC: 0.82; 95% CI: 0.76–0.87) compared to serum lactate (AUC: 0.72; 95% CI: 0.65–0.78) and LB ratio (AUC: 0.68; 95% CI: 0.62–0.74) (all p < 0.001). The Youden-index based optimal LAR cutoff was 1.25, whereas that for the LB ratio was 0.20. The RF, XGBoost and SVM models achieved the highest performance. SHAP analysis revealed that LAR was the most influential predictor among the lactate-based variables. Conclusions LAR exceeded serum lactate and the LB ratio in predicting critical outcomes in pediatric DSS. These findings support its utility as a practical and accessible tool for early risk stratification in DSS patients. These results support the use of LAR as a practical and accessible tool for risk stratification in pediatric dengue care.