Journal of Current Science and Technology

Waste Heat Recovery from Biomass Charcoal Cookstoves via Elliptical-Tube Helical Coils: Application in a Medium Sized Thai Restaurant

Suriya Sukarin, Manusak Janthong, Sathaporn Thongwik — Thu, 25 Jun 2026 00:00:00 +0700

This study proposes a compact and high-performance waste-heat recovery system designed for small food-service establishments using biomass cookstoves (BCS). The system incorporates elliptical-tube helical coil heat exchangers (HHEs) to intensify secondary flows and enhance convective heat transfer compared with that of conventional circular-tube designs. Four geometric configurations (H01–H04), differing in coil diameters, pitch lengths, and tube ovalities, were evaluated through an integrated framework consisting of: (i) CFD-based thermal assessment under wall-temperature conditions of 160°C, 180°C, and 200°C; (ii) techno-economic analysis, including annual energy cost savings, net present value (NPV), and payback period; and (iii) environmental impact assessment focusing on CO₂ emission reduction. Heat-transfer oil was used as the working fluid at a constant inlet temperature of 30°C. The CFD results confirm the strong influence of coil geometry on heat-transfer enhancement. H01 consistently demonstrates the highest thermal performance, outperforming H02, H03, and H04 by 2.78%, 4.10%, and 12.83%, respectively. Deploying H01 as both the exhaust-gas ( ) and hot-water ( ) recovery units under optimal conditions (200°C and ṁ = 2.5 L/min) yields 17,144.34 kWh/year of recoverable thermal energy, equivalent to 71,422.27 THB in electricity savings. Techno-economic indicators further reveal strong feasibility, with an NPV of 263,887.97 THB and a payback period of only 1.36 years. CO₂ emission reduction reaches 3,948.17 kg/year, highlighting the system’s environmental significance. Overall, the elliptical-tube HHE configuration (H01) offers superior energy, economic, and environmental benefits for BCS-based food enterprises, aligning effectively with renewable-energy goals and contributing to more sustainable thermal practices in the food-service sector.

A Reinforcement Learning–Guided Hybrid NSGA-II + ALNS Framework for Large-Scale Capacitated Transportation Optimization in Thai Sugarcane Logistics

Putis Wittayasin, Nuchsara Kriengkorakot, Preecha Kriengkorakot — Thu, 25 Jun 2026 00:00:00 +0700

Efficient planning of large-scale agricultural transportation requires balancing travel distance, fleet utilization, and factory capacity constraints. While mixed-integer linear programming (MILP) becomes computationally intractable for large-scale instances and conventional metaheuristics rely on static operator-selection mechanisms, adaptive learning-guided approaches for multi-objective capacitated transportation remain limited. This study proposes a reinforcement learning–guided hybrid NSGA-II + ALNS framework to minimize total transportation distance and truck trips in sugarcane logistics. A real-world case involving 199 subdistricts and four processing plants (796 origin–destination pairs) in northeastern Thailand is examined. Compared with a greedy nearest-assignment baseline, the proposed method reduces total transportation distance from 123,313.52 km to 109,245.22 km (by 11.41%), fuel consumption from 28,131.83 L to 25,108.96 L (by 10.75%), and CO₂ emissions from 75,955.94 kg to 67,794.20 kg (by 10.75%), resulting in an estimated fuel cost saving of approximately 96,550 Thai Baht per cycle. Statistical validation using ANOVA and Tukey’s HSD confirms that performance differences are significant at the 95% confidence level. The results demonstrate that reinforcement learning–guided operator adaptation improves convergence stability, Pareto-front quality, and environmental performance in large-scale bi-objective agricultural transportation systems.

Applying Bias-Correction Methods to Parameter Estimation for the Zeghdoudi Distribution in Medical Data

Chanakan Sungboonchoo — Thu, 25 Jun 2026 00:00:00 +0700

The Zeghdoudi distribution (ZD) is a valuable model for analyzing lifetime data. It has been further developed for modeling various data types and for constructing related lifetime models. In statistical inference, the maximum likelihood method is well known for estimating the parameters of different distributions using large samples. However, when applied to small or moderate samples, the bias of the maximum likelihood estimator (MLE) can become problematic. This study proposes point estimators for the Zeghdoudi distribution using two bias-correction methods: the Cox-Snell method and the parametric bootstrap. The performance of these estimators is evaluated using average bias and root mean square error (RMSE) in simulation studies. The results demonstrate that the point estimators derived from the bias-correction methods improve finite-sample accuracy by reducing the bias of the maximum likelihood estimator to second order. In addition, the findings indicate that the parametric bootstrap technique outperformed the others under various conditions, whereas the MLE can be biased for small or moderate sample sizes. Furthermore, analyses of two medical datasets were conducted to validate the performance of the proposed estimators.

Roles of CCL2 Gene Expression in Peripheral Blood of Patients with Kidney Disease

Mohammed Hudhaifa A. Karem, Amjed Qays Ibrahim Alqaisi — Thu, 25 Jun 2026 00:00:00 +0700

Chronic kidney disease (CKD), acute kidney injury (AKI), and IgA nephropathy (IgAN) are kidney disorders that lead to progressive impairment of filtration. Standard diagnostic markers (creatinine, urea, and eGFR) remain the cornerstone of clinical detection, but they are still insufficient for early diagnosis. Recent studies highlight the potential role of genetic indicators such as CCL2, which are involved in inflammatory signaling and renal tissue injury by attracting monocytes and macrophages into the damaged kidney. This study was designed as a cross-sectional case-control investigation aimed at assessing fold-change expression of CCL2 in the peripheral blood of patients with CKD (n = 30), AKI (n = 10) and IgAN (n = 14), compared with healthy controls (n = 30) after clinical diagnosis of patients with physiological markers. Creatinine, urea and eGFR exhibited highly significant differences between patients and controls, demonstrating strong diagnostic ability (AUC > 0.90 for all markers). Conversely, CCL2 expression showed no significant difference between patient groups and controls, and no significant correlation with physiological markers. Mean CCL2 fold-change were 1.707 in AKI, 1.795 in CKD, and 1.378 in IgAN, indicating only mild elevation without statistical significance. These findings contribute to the evaluation of inflammatory molecular biomarkers in renal diseases by indicating that circulating CCL2 mRNA expression in peripheral blood does not offer additional diagnostic value beyond established physiological markers within this cohort. The results indicate that physiological markers such as creatinine, urea, and eGFR are still good indicators and highlight the limitations of blood-based transcriptional assessment of CCL2 for reflecting renal inflammatory activity, suggesting that tissue-specific or urinary biomarkers may better represent the underlying renal pathological processes. Therefore, blood-based CCL2 in this cohort lacks diagnostic utility, whereas tissue-based or urinary biomarkers could provide enhanced distinction.

Phytoextraction Potential of Colocasia esculenta for Cadmium- and Zinc-contaminated Soils under Moderate Drought Stress: A Short-Term Pot Study

Thu, 25 Jun 2026 00:00:00 +0700

This study investigates the effects of moderate drought on growth, physiology, and heavy metal accumulation in Colocasia esculenta cultivated in cadmium (Cd) and zinc (Zn) contaminated soils. Plants were grown for 30 days under moisture levels of 100% (well-watered), 60%, and 40% field capacity (FC), representing moderate drought, in soils containing 100 mg/kg Cd and Zn. Drought had no impact on the relative growth rate (RGR), whereas metal exposure significantly reduced dry weight and stem height (p < 0.05) of the plants. The photochemical efficiency of PSII (Fv/Fm) and chlorophyll content remained stable (p > 0.05), but the water content (WC) of the leaves decreased under drought stress (p < 0.05). Translocation factors (TF) for both metals were above 1 in all treatments, indicating that heavy metal predominantly accumulated in shoots, with Cd exhibiting greater bioaccumulation factors (BAF) (2.40–3.03) than Zn (1.39–2.98). Overall, moderate drought limited biomass production but enhanced the accumulation of Cd and Zn and translocation to the shoots. These findings suggest that C. esculenta is suitable for the phytoextraction of Cd- and Zn-contaminated soils under drought-stress conditions after short-term exposure of 30 days. However, reduced biomass under drought may decrease overall phytoextraction despite higher tissue concentrations. Therefore, field-scale investigations under variable rainfall conditions are still required.

Prevalence of Myopia and Its Association with Indoor and Outdoor Sport Participation among University Student Athletes in Thailand

Thu, 25 Jun 2026 00:00:00 +0700

Myopia is a growing public health problem in East and Southeast Asia, but evidence among university athletes remains limited. This cross-sectional study determined the prevalence of myopia among amateur university athletes at Rangsit University, Thailand, and examined associations with sport environment and selected risk factors. A total of 157 athletes (115 males, 42 females; mean age 19.79 ± 1.88 years) completed a demographic questionnaire and underwent axial length measurement, slit-lamp biomicroscopy, non-mydriatic fundus photography, autorefraction, and manifest refraction. Myopia was defined as a spherical equivalent ≤ −0.50 D using the more myopic eye. Sports were classified as indoor or outdoor according to the primary training and competition environment. Multivariable logistic regression was used to assess associations with family history of myopia, sport environment, sleep duration, years of athletic practice, daily training duration, and gender. Overall myopia prevalence was 51.60% (81/157). A positive family history was associated with higher odds of myopia (AOR = 2.53; 95% CI: 1.25–5.12; p = 0.010). After adjustment, indoor sport participation was associated with higher odds compared with outdoor sport participation (AOR = 2.44; 95% CI: 1.14–5.23; p = 0.021). Sleeping >6 hours per day was protective (AOR = 0.37; 95% CI: 0.18–0.79; p = 0.010). Gender, years of practice, and daily training duration were not significant predictors. These findings suggest that regular sports participation alone may not offset myopia risk when training occurs mainly indoors. Vision screening for student-athletes should consider family history, sport environment, and sleep habits.

Oral Health-promoting Potential of Standardized Cyanthillium cinereum (Ya Dok Kao) Extract: Anti-inflammatory and Cytoprotective Activities

Thu, 25 Jun 2026 00:00:00 +0700

Cigarette smoking causes oral inflammation, dental caries, and gingival hyperpigmentation, thereby impairing oral health and self-confidence. This study evaluated the potential of standardized Cyanthillium cinereum extract (SCCE) in oral health promotion, focusing on its anti-inflammatory, cytoprotective, antibacterial, and anti-tyrosinase activities. SCCE was prepared using microwave-assisted extraction and standardized to contain high levels of apigenin and luteolin contents. Anti-inflammatory effects were assessed in murine macrophages by measuring nitric oxide scavenging activity and the expression of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and tumor necrosis factor-α (TNF-α). Cytoprotective activity was evaluated in human gingival fibroblasts exposed to H₂O₂. Antibacterial activity against Streptococcus mutans was tested using disc diffusion method, while tyrosinase inhibitory activity was examined using enzymatic assays. SCCE effectively scavenged nitric oxide (IC₅₀ of 189.20 mg/mL) and significantly suppressed iNOS, COX-2, and TNF-α expression in macrophages. Its activity was comparable to apigenin and luteolin, and in some assays superior to indomethacin. SCCE also protected gingival fibroblasts from H₂O₂-induced cell death, with cell viability up to 57.29 - 73.66%, though its cytotoxicity profile varied by cell type. However, SCCE demonstrated no antibacterial activity against S. mutans at 1 mg/disc and showed no significant tyrosinase inhibition. SCCE exhibits strong anti-inflammatory and cytoprotective effects, supporting its potential as a natural oral healthcare product for smokers. Despite its limited antibacterial and tyrosinase inhibitory activities, its anti-inflammatory and antioxidative properties highlight its promise in mitigating smoking-related oral health problems. Further clinical studies and prototype formulation development are warranted to advance its application.

Impact of Modeling Simplifications on the Dynamics and Control of the Furuta Pendulum

Paul Alvarez, Alexander Rodríguez Gamboa — Thu, 25 Jun 2026 00:00:00 +0700

This study analyzes the impact of modeling simplifications on the dynamics and control performance of the Furuta pendulum. A complete multibond graph model is developed, incorporating full system dynamics, and providing an energetically consistent and modular framework. The model is validated against a Simulink-Simscape reference, achieving a maximum normalized root mean squared error (NRMSE) of 0.2035 × 10^–3. The commonly used simplified model, which neglects secondary inertias, is compared with full-dynamics models under open- and closed-loop conditions. Open-loop results show appreciable discrepancies, with NRMSE values increasing notably for both θ₁ and θ₂ as the inertias are progressively increased. A nonlinear control scheme based on energy shaping, collocated partial feedback linearization, and linear quadratic regulation (LQR) is designed using the simplified model. In closed loop, the controller achieves swing-up and stabilization in all cases within 10 seconds. For nominal and moderately increased inertias, performance degradation is minimal, with settling times around 7.4 s and control effort between 0.453 and 0.475 N²m²s. However, for large inertias, the settling time increases to 8.91 s, control effort rises to 0.655 N²m²s, and an additional oscillation is required. These results show that simplified models are suitable for control design under typical conditions, while full-dynamics models are essential for validation and robustness assessment.

Relationship between Family Violence and Psychological Stress Among Thai Young People: A Mixed-Methods Study in Pathum Thani Province

Phitchasuda Dechboon, Apichet Jumneansuk, Rattanaporn Arsa — Thu, 25 Jun 2026 00:00:00 +0700

Family violence among young people remains a significant public health concern, yet primary care screening remains inconsistent in Thailand. To understand which specific types of violence most strongly predict adolescent stress and why these problems remain hidden during healthcare visits, we enrolled 350 young people aged 13 – 24 years from Pathum Thani Province between February and April 2025. Participants completed surveys measuring six types of violence, psychological stress using the ST-5 instrument, and family relationship quality. The 138 participants scoring ST-5 ≥ 8 subsequently completed in-depth interviews. Associations were analyzed using Pearson correlations and stepwise regression, and interview transcripts were then coded thematically.

Of the 365 young people approached, 350 participated, yielding a response rate of 95.9%. Violence exposure affected 46% of participants, while 39.5% demonstrated high-to-severe stress levels. Stepwise regression revealed that witnessing parental arguments was the only violence-related predictor independently associated with stress, accounting for 23.6% of the variance (β = .486, p < .001). Shared family activities provided modest protection (β = -.127, p = .007), increasing the total explained variance to 25.2%. Paradoxically, 57.1% of violence-exposed participants described their family relationships positively overall, reflecting the coexistence of violence and support within Thai family systems. Based on these findings, brief ST-5 screening combined with culturally adapted indirect inquiry about parental conflict may represent a promising direction for improving the detection in primary care settings, although prospective evaluation is required. Clinicians must recognize that violence and support can coexist within Thai families, requiring interventions that validate young people’s distress while preserving essential family bonds.

Green Conversion of Macroalgae Ulva lactuca to 5-Hydroxymethylfurfural in Deep Eutectic Solvent Catalyzed by ChCl and HCl

Thu, 25 Jun 2026 00:00:00 +0700

In this research, sustainable production of 5-hydroxymethylfurfural (5-HMF) from macroalgae Ulva lactuca (MUL) was methodically studied in a closed system in the presence of a deep eutectic solvent (DES). Herein, the DES consisted of choline chloride (ChCl) and hydrochloric acid (HCl) in acetonitrile solvent, which could be practically applied in relevant reactions such as hydrolysis, isomerization, and dehydration. The roles and benefits of the DES and the types of organic solvents utilized in the reactions were described in preliminary detail. Polymeric humins, as undesirable by-products, were favorably formed via further condensation and/or polymerization of 5-HMF when excessive amounts of HCl or ChCl were utilized under harsh conditions in the catalytic system. Important parameters, such as HCl amount, ChCl amount, reaction time, and temperature, were scrupulously investigated to determine the optimum conditions for 5-HMF production. As anticipated, a maximum yield of 5-HMF (93.9%) was achieved at 120°C for 90 min using 2.4 mmol of HCl and 28 mmol of ChCl. The long-term reusability of ChCl in the catalytic system was also tested under optimum conditions, and the results showed that spent ChCl could be successfully recrystallized and reused four times with only slight reductions in 5-HMF yield. These studies pave the way for future advancements in green catalytic processes for the specific production of high value-added chemicals. This research offers an alternative route for sustainable production of 5-HMF from MUL feedstock, and is also potentially applicable to practical bio-refinery processes.

An Ontology-Driven Ambient Assisted Living Framework for Personalized Elderly Care with Health-Risk Inference

Suksawat Saelim, Udsanee Pakdeetrakulwong, Naruapon Suwanwijit — Thu, 25 Jun 2026 00:00:00 +0700

As the global elderly population increases, there is a growing need for structured long-term care systems that support independent living and explainable health monitoring. This study presents AALHealthIoT, a Web Ontology Language (OWL) 2 DL–based ontology framework for Ambient Assisted Living (AAL) that integrates physiological measurements, environmental conditions, and personal profile attributes within a unified semantic architecture. Unlike existing Internet of Things (IoT) ontologies such as SSN/SOSA, SAREF, SAREF4EHAW, and OntoDomus, which primarily emphasize interoperability, AALHealthIoT operationalizes cross-domain health-risk inference using Semantic Web Rule Language (SWRL) rules grounded in publicly available clinical guidelines. The ontology comprises 188 classes, 159 object properties, 30 data properties, and 2,077 axioms and was developed using the NeOn methodology. Validation included structural verification, pitfall detection, logical consistency checking, competency-question testing, and quantitative performance evaluation. Under controlled synthetic scenarios ranging from 50 to 1,000 seniors (up to 8,000 ontology individuals), SWRL reasoning remained under 2 seconds, while SPARQL Protocol and RDF Query Language (SPARQL) query latency remained below 1 second, even for the most complex cross-domain queries. These results demonstrate that ontology-driven semantic reasoning can provide an explainable and computationally feasible foundation for decision support in community-based AAL environments.

Development of Electro-Fenton Process for Methylene Blue Degradation using NiFeCo Foam Alloy Cathode and Porous Graphite Anode

Thu, 25 Jun 2026 00:00:00 +0700

The low efficiency of electro-Fenton (EF) technology in generating hydrogen peroxide (H₂O₂) is one of the most frequently encountered obstacles. Thus, the search for high-performance electrodes and reactors is necessary to increase system efficiency. In this study, porous graphite served as the control group to increase oxygen mass transfer in the reactor, while foam alloy was used as the cathode for producing in situ H₂O₂. X-Ray diffraction analyzer (XRD) and scanning electron microscope (SEM) were utilized to investigate the microstructure of the electrodes. Response surface methodology (RSM) was used to examine the various operational parameters affecting the reduction of methylene blue (MB) dye. A FeSO₄.7H₂O concentration of 0.5 mM, a current density of 8 mA/cm², and a reaction time of 30 min were the optimal conditions for the electro-Fenton technique. Under these conditions, the MB removal efficiency (RE%) was 97.73%, and the energy consumption was 11.76 kWh/kg MB. The two most important factors controlling dye reduction in the electro-Fenton process are the FeSO₄.7H₂O concentration and the current density, which contributed 68.33% and 15.44%, respectively, in this model. The coefficient of multiple correlation (R²) was 99.59%, which demonstrated the statistical significance of the regression analysis. Therefore, the foam alloy electrode represents a new and viable strategy for contaminant degradation in the electro-Fenton process.

Safety and Dose-Related Glycemic Signals of a Gymnema inodorum-Based Beverage in Type 2 Diabetes: An Open-Label Randomized Pilot Study

Thu, 25 Jun 2026 00:00:00 +0700

Gymnema inodorum is a popular traditional remedy for diabetes, yet clinical safety data for multi-herb beverages combined with metformin remain limited. This 12-week, open-label, randomized pilot study compared two daily doses of a G. inodorum–mulberry–chamomile beverage in adults with recently diagnosed type 2 diabetes mellitus (≤6 months since diagnosis) receiving stable metformin monotherapy. Thirty-two T2DM patients receiving metformin were assigned to consume the beverage at 150 mL/day (Group A) or 300 mL/day (Group B). The primary outcomes assessed safety markers, including hematology and hepatic and renal function. Secondary outcomes included fasting blood glucose (FBG), HbA1C, and oral glucose tolerance test (OGTT) indices. The beverage was generally well tolerated over 12 weeks; liver enzymes and serum creatinine remained stable in both groups. BUN changed differently between groups (p = 0.007), decreasing slightly in Group A but increasing in Group B. FBG changed by −6.21 mg/dL in Group A and +22.25 mg/dL in Group B (between-group p = 0.014), whereas HbA1C changed by +0.23% in Group A and +0.42% in Group B, with no significant between-group difference (p = 0.230). OGTT glucose exposure increased within both groups (Group A: tAUC +12,821 and iAUC +12,209; Group B: tAUC +15,504 and iAUC +12,651), with no significant between-group difference. These findings indicate short-term tolerability but do not demonstrate improved dynamic glucose tolerance; the lower dose showed a more favorable glycemic trend than the higher dose in this small non-placebo pilot. However, this observation is hypothesis-generating and should not be interpreted as a clinical recommendation.

DDoS Detection Framework Using Machine Learning Optimized by Bayesian and PSO Techniques

Thu, 25 Jun 2026 00:00:00 +0700

This paper presents a distributed denial of service (DDoS) detection framework using machine learning techniques enhanced with hyperparameter optimization for network traffic classification and evaluated on the BCCC-cPacket-Cloud-DDoS-2024 dataset. The framework includes data preprocessing with normalization and class imbalance handling via the synthetic minority over-sampling technique. A critical contribution of this study is the rigorous analysis of the trade-off between detection accuracy and model complexity. Unlike arbitrary feature selection methods, we empirically determined the optimal feature set using information gain, identifying that the top 100 features represent the saturation point that balances high accuracy with minimal overhead. Model performance was further improved through hyperparameter optimization using particle swarm optimization and Bayesian algorithms. The extreme gradient boosting (XGBoost) model optimized using Bayesian optimization and the top 100 features achieved the highest performance, with an accuracy of 99.29% and an F1-score of 98.91%. As a result, the proposed framework improves detection performance while reducing model complexity by selecting an optimal feature set to improve model stability and efficiency.

Energy-Efficient Scheduling and Control of Aluminum Melting Processes Using Genetic Algorithms and Reinforcement Learning

Kraiwitch Pawadee, Narongdech Keeratipranon — Thu, 25 Jun 2026 00:00:00 +0700

Manufacturing is a primary driver of global energy consumption, necessitating advanced production strategies to maintain industrial competitiveness. This study explores opportunities for thermal optimization within an industrial aluminum melting process in Thailand. While traditional manual furnace regulation and heuristic scheduling provide operational stability, the inherent complexity of multi-stage processes presents opportunities to further minimize holding and reheat losses through automated synchronization. However, existing studies typically address batch-level thermal control and system-level scheduling separately, and few explicitly target the holding and reheat losses caused by unsynchronized transfer between induction and melt-and-hold stages. To address this gap, we propose an integrated framework that combines deep reinforcement learning (RL) for batch-level power control with a genetic algorithm (GA) for system-level energy-aware scheduling. The RL component uses a deep Q-network (DQN) to learn an expert-guided power-control policy, while the GA incorporates a just-in-time (JIT) Gate, a synchronization mechanism that delays or releases melting batches to align induction-furnace output with downstream melt-and-hold (M&H) demand. Under repeated mixed-start evaluation, the revised RL controller achieved 597.96 ± 18.23 kWh per batch, slightly improving upon the original DQN result (600.79 ± 19.96 kWh) and the fixed expert-profile baseline (601.73 kWh), while preserving 100% target attainment and zero executed safety violations. At the system level, the GA-based scheduler eliminated reheat energy from 2,833.3 kWh to 0 kWh and reduced peak demand by 23.9%. These results indicate that RL provides robust, near-expert batch-level control, while GA-based JIT synchronization delivers the major energy-saving benefit at the production-system level.

Expanding Polyurethane Foam Injection for Ground Improvement: Mechanisms of Soil–Resin Interaction, Field Verification Methods, and Practical Design Considerations

Nares Pantaratorn, Banjie Sarmiento — Thu, 25 Jun 2026 00:00:00 +0700

Expanding polyurethane (PU) foam injection has emerged as a technically versatile alternative to cementitious grouting for geotechnical rehabilitation, offering rapid cure, low unit weight, and suitability for both dry and actively seeping ground conditions. Despite growing field adoption, systematic guidance on material selection, injection design, and performance verification remains absent, with knowledge distributed across disparate testing protocols and performance metrics. This review synthesizes laboratory experiments, field case studies, and monitoring data to address three deficiencies: an incomplete mechanistic understanding of soil–resin interactions across injection regimes; the absence of an integrated verification protocol; and the lack of standardized design codes. PU systems span hydrophobic and hydrophilic types across a density range of 35–1,000 kg/m³, achieving cured compressive strengths of 0.3–10 MPa and hydraulic conductivities of 10⁻⁵ to 10⁻⁸ m/s. Three injection configurations, which are slab jacking, tunnel void grouting, and deep foundation underpinning, are distinguished by borehole geometry, pressure limits, and staging sequence. Field evidence confirms pavement faulting reductions of 2 to 5 mm, a 160% foundation stiffness increase at Noi Bai International Airport, and a 98% seepage reduction in tunnel waterproofing applications. Comparative analysis demonstrates that PU foam outperforms cementitious grouting in cure speed, fine-void penetrability, and faulting correction, while cement retains advantages in bulk compressive strength and unit material cost. Key limitations include buoyancy risk in saturated ground, chemical sensitivity above pH 9, exothermic damage risk in confined spaces, and insufficient long-term durability data to support design codification. The review consolidates the evidence into a structured framework linking PU material class, injection parameters, and verification method to specific geotechnical objectives, providing a unified resource for researchers and practitioners.

Efficacy of Collagen Biostimulator Injections for Facial Aesthetics: A Systematic Review and Meta-analysis Based on Global Aesthetic Improvement Scale (GAIS) Outcomes

Thu, 25 Jun 2026 00:00:00 +0700

This systematic review and meta-analysis evaluated the efficacy of injectable collagen biostimulators for facial aesthetic enhancement. The primary outcome was the Global Aesthetic Improvement Scale (GAIS), with adverse events assessed as a secondary outcome. A comprehensive literature search was conducted across five databases (PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL) following the PRISMA 2020 guidelines. Eligible studies included healthy adults receiving facial injections of poly-L-lactic acid (PLLA), polydioxanone (PDO), calcium hydroxylapatite (CaHA), polycaprolactone (PCL), or poly-D,L-lactic acid (PDLLA); however, no eligible PDLLA studies were identified. The included studies consisted of randomized controlled trials and observational studies. Data were synthesized using a random-effects meta-analysis model, and the risk of bias was evaluated using the RoB 2 and ROBINS-I tools. Twenty-four studies were included in the quantitative synthesis. The pooled mean GAIS score was 3.88 (95% CI: 3.63–4.14), indicating moderate to marked aesthetic improvement. Subgroup analysis revealed the highest GAIS scores with PDO (4.20), followed by PLLA (4.13, single study), PCL (4.00), and CaHA (3.33). Reported adverse events were mostly mild and transient, including erythema, swelling, and tenderness. Based on the GRADE assessment, the overall certainty of evidence was low for efficacy and very low for adverse events. Collagen biostimulators demonstrated favorable efficacy profiles for facial rejuvenation. Although all four agents were effective, outcomes varied by product type, suggesting the importance of personalized treatment selection. These findings provide evidence-based support for clinical application and highlight the need for future comparative studies with standardized outcome reporting.

Suspension Control Strategies for High-Speed Trains: A Comprehensive Review and Future Perspectives

Tien-Dat Tran, Cong-Son Doan, Thanh-Dat Le, Viet-Dung Do, Xuan Kien Dang — Thu, 25 Jun 2026 00:00:00 +0700

The suspension system plays a crucial role in ensuring the smoothness, stability, and safety of high-speed trains. This paper provides a comprehensive overview of the development of passive, semi-active, and active suspension systems. Advanced intelligent control architectures, such as Proportional Integral Derivative (PID), Linear Quadratic Regulator/Gaussian (LQR/LQG), and Sliding Mode Control (SMC), are compared with modern approaches, specifically fuzzy logic control frameworks based on Particle Swarm Optimization (PSO), Adaptive Neural Networks (ANN), and Adaptive Nonlinear Control (ANC). The paper evaluates the advantages and disadvantages of each strategy by considering five core criteria: passenger comfort, vibration suppression capability, disturbance rejection, adaptability, and implementation complexity. The synthesis of results indicates that intelligent and adaptive controllers provide significant quantitative enhancements; for instance, a PSO-optimized hybrid Fuzzy-PID controller achieves a 42.8% reduction in root-mean-square (RMS) acceleration. Most notably, the ANC strategy attains the highest improvement, enhancing ride comfort by up to 68.2% compared with passive systems. Finally, future research directions are outlined, emphasizing the necessity of high-fidelity multi-physics modeling and the development of computationally optimized, data-efficient reinforcement learning frameworks directly integrated into fault-tolerant control loops.