Search Results (11,397)

Background/Objectives: Accurate quantification of alveolar cleft defects for bone grafting remains difficult due to inconsistent anatomical boundaries. This study established an expert consensus on boundary landmarks for alveolar bone graft (ABG) planning and validated the accuracy and reliability of digital volumetric measurement methods. Methods: Three cleft specialists performed repeated simulated graft procedures in seven patient-specific 3D-printed models, first according to the operator’s clinical judgment, and subsequently according to panel-derived consensus boundaries. Two radiologists independently conducted digital volumetric assessments in 3D X-ray imaging using four measurement approaches (axial tracing, interpolated axial tracing, landmark-based mirroring, and mesh-based mirroring), generating 56 independent digital segmentations to be evaluated against the consensus-based physical reference standard. Volumes of the defects were recorded, intra- and inter-rater reliabilities were calculated using the intraclass correlation coefficient (ICC), and differences among methods were analyzed. Results: Operator-defined plans showed significant inter-operator differences (p < 0.001) with poor-to-excellent reliability (intra-rater ICC 0.060–0.967; inter-rater ICC 0.300–0.635). Consensus established standardized boundaries: tilted plane from base of anterior nasal spine to hard palate, cemento-enamel junctions, incisive canal, and alveolar contour. Consensus-based filling showed non-significant inter-rater differences (p = 0.139) and substantially improved reliability (intra-rater ICC 0.904–0.988; inter-rater ICC 0.622–0.861). Among the four digital methods evaluated, axial tracing demonstrated excellent reliability (intra-rater ICC 0.971–0.99; inter-rater ICC 0.965) and high accuracy (mean difference 0.001–0.026 cm³), with no significant difference (p = 0.999) from the physical reference standard. Conclusions: These proposed consensus-based boundary definitions and validated volumetric measurement methods improved the accuracy and reproducibility of personalized alveolar bone graft planning. Full article

The aim of this work is to explore a load frequency control (LFC) strategy in micro hydro power plants (MHPPs). Using MATLAB/Simulink, we examined several variants of genetic algorithms (GAs), including Roulette, Tournament, and Uniform, which are utilized to optimize tuning proportional integral derivative (PID) parameters by addressing the problem of instability caused by load variations. The performances are compared with conventional PID methods and other advanced techniques like particle swarm optimization (PSO), adaptive neuro-fuzzy inference system (ANFIS), and artificial neural networks (ANN) algorithms for both single and dual-area MHPP systems. The results show that the GA-optimized PID controller with the roulette wheel achieves the fastest settling time of 0.3 s and the smallest undershoot of 0.015 pu in the single area. Also, optimizing GA demonstrates superior performance in the dual area, with the fastest settling times of 2.5 s for both Roulette and Uniform. In contrast, PSO is slower than GA, and conventional PID requires a much longer settling time of 19.8 s, a similar result occurring in the dual area. These findings confirm the effectiveness of the GA-optimized PID controller, especially the Roulette variant, as a reliable and fast solution for maintaining frequency stability in MHPPs. Full article

Constructed wetlands (CWs) are a low-energy alternative for treating dye-containing wastewater; however, the mechanisms enabling azo dye removal without external carbon supplementation remain unclear. This study demonstrates that azo dye reduction can proceed under oxic bulk conditions in CWs through vegetation-induced microscale redox heterogeneity. Lab-scale CWs planted with cattail and papyrus were evaluated for the removal of Reactive Orange 16 (RO16, monoazo) and Reactive Black 5 (RB5, diazo) at influent concentrations of 10–50 mg/L under varying ambient temperature (2–36 °C) and hydraulic retention time (1–15 days). Vegetated CWs consistently outperformed the unplanted system, achieving 60–95% removal for RO16 and up to 98% removal for RB5, whereas the unplanted CW showed substantially inferior performance, with removal efficiencies below 54% for RO16 and below 37% for RB5. Dye-decolorizing bacteria, including Priestia megaterium and Clostridium spp., were isolated exclusively under anaerobic conditions from vegetated CWs despite oxic bulk dissolved oxygen levels. The isolates did not decolorize dyes under aerobic conditions or when dyes were provided as sole carbon sources, indicating that azo dyes functioned as electron acceptors and required additional electron donors. These results suggest that vegetation promotes localized reductive microenvironments and supplies endogenous organic carbon, enabling anaerobic azo bond reduction within otherwise oxic systems. The findings indicate a mechanistic basis for plant–microbe interactions in CWs and support the design of sustainable treatment systems for dye-containing wastewater without external carbon input, particularly in warm regions. This study resolves a long-standing question of how azo dye reduction proceeds in CWs without external carbon input. Full article

Objective: To study the prevalence and associated factors of digital eye strain among university students. Methodology: A cross-sectional survey and analytical study was conducted on 387 university students, ranging from 1st to 4th year, aged 18–23 years. The participants were digital device users who had not been medically diagnosed with any eye diseases affecting their use of digital devices. Statistical analyses were performed using the Descriptive Statistics, Chi-square test, and Fisher’s exact test. Results: The prevalence of digital eye strain among university students was found to be 80.40%. The most common symptoms were headache (80.62%), burning sensation in the eyes (75.19%), and eye pain (71.06%). The study found that 30.49% were male and 69.51% were female, with an average age of 20.07 ± 0.07 years. It was found that gender (p < 0.05, Phi = 0.14), vision problems (p < 0.05, Phi = 0.20), wearing light-filtering glasses (p < 0.05, Phi = 0.12), average daily smartphone screen time (p < 0.05, Phi = 0.19), avoiding digital devices before sleep (p < 0.05, Phi = 0.22), glare (p < 0.05, Phi = 0.19), wind exposure to the eyes (p < 0.05, Phi = 0.20), and ambient air conditions (p < 0.05, Phi = 0.15) were significantly associated with digital eye strain (p < 0.05); however, the strength of these associations was small (Phi = 0.12–0.22), indicating limited practical impact. Conclusions: Digital eye strain is highly prevalent among university students. Although several factors were statistically associated with digital eye strain, the small effect sizes suggest that each factor contributes only modestly. These findings highlight the multifactorial nature of digital eye strain and the importance of considering combined behavioral, environmental, and ergonomic influences. Full article

Background: Meningioma is the most common primary intracranial tumor in adults, and survival outcomes are influenced by histopathological grade, tumor characteristics, and treatment strategies. This study aimed to evaluate overall survival (OS) and identify prognostic factors in patients with meningioma treated at a national referral cancer center in Indonesia. Methods: A retrospective cohort study was conducted at Dharmais National Cancer Center Hospital, including adult patients with histopathologically confirmed intracranial meningioma who underwent surgical resection between January 2019 and 17 August 2025. Overall survival was calculated from the date of histopathological diagnosis to death or last follow-up and analyzed using Kaplan–Meier methods and Cox proportional hazards regression. Results: A total of 114 patients were included (mean age 48.1 ± 10.5 years; 86.8% female), with most tumors classified as WHO Grade I (64.0%) and located at the skull base (57.0%). Subtotal resection was more common (67.5%), and 71.9% did not receive adjuvant radiotherapy. During follow-up, 14.0% of patients died, with cumulative overall survival rates of 95.6% at 6 months and 86.0% at 96 months. On multivariate analysis, only WHO tumor grade remained an independent prognostic factor (HR 2.199; 95% CI 1.161–4.167; p = 0.016), with higher grades associated with worse survival. Extent of resection and adjuvant radiotherapy were not significantly associated with overall survival after adjustment. Conclusions: In this Indonesian tertiary referral cohort, WHO tumor grade emerged as the only independent predictor of overall survival, underscoring its important prognostic role in meningioma; however, these findings should be interpreted with caution due to incomplete clinical data and relatively short follow-up duration. The high proportion of complex cases, including skull base tumors, reflects referral patterns and may also influence treatment outcomes. Full article

Background/Objectives: Melioidosis, caused by Burkholderia pseudomallei, is a severe tropical infectious disease associated with high mortality in endemic regions. Early diagnosis remains challenging because conventional diagnostic methods, including culture, serological assays, and molecular techniques, have limitations in sensitivity, specificity, processing time, and accessibility in resource-limited settings. This review evaluates current diagnostic approaches and highlights the potential of short peptide biomarkers for improving melioidosis detection. Methods: A narrative literature review was conducted using four electronic databases (PubMed, Scopus, Web of Science, and Google Scholar) covering publications from 2000 to 2024. Relevant studies were identified using predefined keywords related to melioidosis diagnostics, biomarkers, and peptide-based approaches, and were screened based on relevance to diagnostic methods and peptide biomarker development in Burkholderia pseudomallei. Results: Several biomarkers have been investigated for melioidosis diagnostics, including capsular polysaccharide (CPS), type III secretion system 1 (TTS1), and other virulence-associated proteins such as Hcp1 and BPSS1187. Among these, CPS and TTS1 are highly conserved and specific targets widely used in molecular and antigen-based detection methods. Short peptide epitopes derived from these antigens demonstrate promising advantages over whole proteins, including improved stability, high specificity, easier synthesis, and reduced production costs. Advances in epitope prediction technologies and peptide-based biosensors have further expanded the potential applications of short peptides in rapid diagnostic platforms, including ELISA, lateral flow immunoassays, and biosensor-based detection systems. Conclusions: Short peptide–based biomarkers represent a promising strategy for developing rapid, sensitive, and cost-effective diagnostic tools for melioidosis, particularly in endemic and resource-limited settings. Full article

This study examines the determinants and impacts of household biogas adoption among dairy-based mixed crop–livestock systems in West Java, Indonesia. Using primary survey data from 201 households, we estimate adoption drivers through logistic regression and assess post-adoption outcomes using propensity score matching combined with doubly robust estimation. The results show that adoption is primarily driven by structural feasibility and institutional exposure, particularly livestock ownership, participation in technical training, perceived time-saving benefits, and fuel-cost pressure, while general socioeconomic variables such as income and education are not statistically significant. Treatment-effect estimates indicate that adoption leads to significant reductions in LPG and firewood consumption, as well as decreased use of chemical fertilizers, reflecting partial substitution of external inputs with locally available resources. However, these benefits are unevenly distributed, with stronger effects observed among households with larger livestock holdings, while training plays a more critical role for smaller-scale farmers. The findings are interpreted through a sustainability–resilience framework, which is used as an analytical lens rather than a causal measurement model. The results highlight the importance of institutional support, service provision, and policy alignment in determining the durability and scalability of biogas adoption. The study contributes to the literature by integrating determinants of adoption with causal impact estimation and situating household-level outcomes within broader socio-technical systems. Full article

Ship collision accidents remain a critical concern in maritime safety because of their potential to cause operational disruption as well as environmental and economic damage in areas with dense shipping activity. Complex traffic interactions, differences in vessel characteristics, and dynamic environmental conditions make collision risk increasingly difficult to manage using traditional navigation measures alone. This paper presents a structured review of ship collision research, focusing on collision impacts, collision avoidance strategies, risk assessment methodologies, and safety index development. The review synthesizes reported collision cases and their environmental consequences, examines commonly used analytical frameworks including probabilistic, data-driven, and multicriteria approaches, and discusses recent developments in AIS-based analysis, sensor-based monitoring, and intelligent prediction techniques. The analysis identifies several methodological gaps in existing studies. Collision avoidance methods and risk assessment models are often developed independently, while their integration with safety index frameworks remains limited. In addition, safety index formulations differ considerably in terms of indicator selection and modeling approaches, which reduces comparability between studies conducted in different waterways. The findings highlight how different analytical approaches contribute to maritime safety evaluation at strategic, operational, and real-time levels and provide insights for developing more integrated safety assessment frameworks to support navigation risk monitoring in high-traffic maritime environments. Full article

Accurate prediction of food consumption is essential for strengthening regional food security planning, particularly in areas experiencing increasing food demand and environmental uncertainty. This study aims to predict food consumption patterns in Sukabumi Regency, West Java, Indonesia, using an integrated artificial intelligence approach. The research combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) for forecasting food consumption trends with three machine learning classification algorithms—Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression (LR)—to classify food consumption levels. Historical rice consumption data from 2014 to 2024 were used to train the forecasting model and generate projections up to 2030. The ANFIS training process was conducted with 100 epochs and an error tolerance of 0, resulting in a training error value of 0.182, indicating strong model learning capability. The comparison between predicted and actual consumption values showed a prediction accuracy of 95.2%, demonstrating the reliability of the model in capturing consumption patterns. Furthermore, food consumption levels were classified into three categories: low, medium, and high. The classification results revealed that Random Forest achieved the most consistent performance across cross-validation folds, while SVM and Logistic Regression experienced misclassification in the medium consumption category. In several evaluation scenarios, machine learning models achieved accuracy levels up to 99.75%, precision 99.76%, recall 99.75%, and F1-score 99.75%. The integration of ANFIS forecasting and machine learning classification provides a robust analytical framework for understanding food consumption dynamics and supports data-driven policy formulation aimed at strengthening regional food security in Sukabumi Regency. Full article

Availability of phosphorus (P) is thought to limit bole growth in wet tropical forests, raising concern that removing P through repeated logging in P-limited stands may be unsustainable. Motivated by a study in Indonesia, we analyzed Olsen extractable and total soil P in the upper 10 cm in paired samples we collected under vs. near decaying boles of two contrasting species in a wet tropical forest in Puerto Rico. Guarea guidonia had higher wood and leaf P concentrations than Dacryodes excelsa. G. guidonia colonized valleys with higher soil P concentrations than ridge sites dominated by D. excelsa. We used two age cohorts of trees > 30 cm diameter, felled by hurricanes Hugo in 1989 (11 years old) and Georges in 1998 (1.5 years old), but soil P did not differ with age. Soil Olsen P concentrations were significantly higher under versus away from boles of both species. Paradoxically, augmentation of soil P was greater under boles of D. excelsa than G. guidonia despite having lower wood P. Soil % C and Olsen P were strongly positively correlated in D. excelsa but not in G. guidonia, suggesting that regulation of soil P-availability differs between ridges and valleys. Both soil C and P may be critical for maintaining soil fertility on ridges in a wet tropical forest. Our results are discussed in the context of prior experiments at our site, including two where bole growth increased with wood addition and/or decreased after removal of woody debris. These studies in Puerto Rico, together with others elsewhere, suggest that reduced forest productivity could potentially result from repeated logging of forest stands on ridges with low P-availability in humid tropical areas since decaying wood could directly and indirectly maintain P-availability in sites with low soil P-availability. We suggest several hypotheses on P-cycling in montane humid tropical forests that need further research to elucidate mechanisms controlling soil P-availability and identify sites where repeated logging is likely to be unsustainable. Full article

Gabapentin is widely used for epilepsy and neuropathic pain. Beyond neurological indications, preclinical evidence suggests that gabapentin may exert anti-inflammatory effects that have not been systematically reviewed. A systematic review (2015–2025) was performed, resulting in thirteen in vitro and in vivo studies evaluating gabapentin’s impact on inflammatory signaling pathways, cytokine production, immune cell activity, and tissue inflammation. Outcomes included molecular pathways, inflammatory mediators, histopathological changes, and functional inflammatory measures. Risk of bias and study quality were assessed using the SYRCLE RoB tool for in vivo studies and the SciRAP approach for in vitro studies. Gabapentin demonstrated potential modulation of inflammatory responses in neuropathic pain, neuroinflammation, uveitis, and sepsis models through inhibition of MAPK and NF-κB signaling, reduction in pro-inflammatory cytokines, modulation of PPAR signaling pathways, and activation of Nrf2/HO-1 pathway. Gabapentin’s pharmacological actions extend beyond neuronal excitability to include modulation of inflammatory pathways, supporting a broader biological role for gabapentin. Although preclinical data support gabapentin’s potential anti-inflammatory properties, further targeted experimental and clinical studies are warranted to confirm these findings. Full article

Background: Polycystic ovary syndrome (PCOS) is a complex endocrine–metabolic disorder characterized by interconnected dysregulation of steroidogenesis and insulin signaling. Multi-target therapeutic strategies are increasingly needed to address its heterogeneous pathophysiology. Methods: An integrative approach combining transcriptomic analysis of GSE137684, including stratification of normoandrogenic and hyperandrogenic PCOS subtypes to capture androgen-related heterogeneity, network pharmacology, molecular docking, and in vitro validation was employed. Principal component analysis (PCA), differential expression analysis, and enrichment analyses were used to identify candidate genes and pathways. Molecular docking evaluated interactions between phytochemicals from Cinnamomum burmannii and Myristica fragrans and key PCOS targets. Functional validation was performed in insulin-resistant 3T3-L1 adipocytes and DHEA-induced KGN cells, assessing cell viability, lipid accumulation, glucose uptake, gene expression, and hormone levels. Results: PCA revealed partial separation between PCOS and the control samples, with PC1 and PC2 explaining 44.8% and 12.5% of variance, respectively. No genes remained significant after multiple testing correction; however, nominally significant candidates (p < 0.01) highlighted pathways related to steroidogenesis and metabolic regulation. Network analysis identified key hub genes including CYP17A1, CYP19A1, AKT1, ESR1, and MAPK1. Molecular docking demonstrated strong binding affinities, with top compounds showing binding energies up to −11.4 kcal/mol (CYP17A1) and −10.9 kcal/mol (AKT1). In vitro, cell viability remained above 80% across all tested concentrations, indicating low cytotoxicity. Treatment significantly reduced lipid accumulation and enhanced glucose uptake in insulin-resistant 3T3-L1 cells (p < 0.05). Additionally, expression of AKT1 and MAPK1 was significantly restored (p < 0.05). In KGN cells, testosterone levels were significantly decreased while the estradiol levels increased (p < 0.05), accompanied by the downregulation of CYP17A1 and upregulation of CYP19A1 (p < 0.05). The combination treatment exhibited more consistent effects across metabolic and hormonal endpoints. Conclusions:Cinnamomum burmannii and Myristica fragrans exert multi-target effects on metabolic and steroidogenic pathways relevant to PCOS. This integrative study demonstrates that transcriptomics-guided network pharmacology combined with experimental validation can identify synergistic phytotherapeutic strategies for complex endocrine disorders. Full article

In various parts of Indonesia, particularly in coastal areas, wind energy can be used as a source of electricity, using wind turbines, whose energy depends on wind speed. Basically, the number of blades in a wind turbine affects the overall turbine performance. This research analyzes the influence of the blade number on the performance of a small-scale horizontal-axis wind turbine using experimental measurements and Computational Fluid Dynamics (CFD) simulations. The CFD simulations were conducted using ANSYS 2022 R2 software on a small-scale horizontal-axis wind turbine with variations in the number of blades, specifically three, four, and five blades, conducted at various wind speeds. It should be noted that due to the setup limitation in the experiment, only the RPM of the three-bladed turbine was measured. Other variables such as torque and power were derived from CFD simulations. The results of this research indicate that an increase in the number of turbine blades tends to result in higher power output, where the highest output obtained was 46.25 Watts. Furthermore, as the number of turbine blades increases, the turbine efficiency also tends to increase, but as wind speed increases, the efficiency decreases. This is demonstrated by the research results, where a wind turbine with five blades achieved the highest efficiency at a speed of 3 m/s, at 38.00%, while at a speed of 6 m/s, the efficiency was 34.80%. Overall, through experiments and cross-validation of CFD and QBlade version 0.963.1, the present study could confirm the significant effect of the number of blades on the power produced by a small-scale horizontal-axis wind turbine under low-speed conditions. Full article

This study presents a comparative evaluation of the sinking performance of traditional small-scale purse-seine gears used in Aceh and Papua, Indonesia, using a three-dimensional mass–spring framework validated by sea-trial data from the Java Sea. Simulations compared sinking behavior under changes in the netting material, knot type, mesh size, and total sinking force across region-specific gear configurations. Compared with existing gear configurations, both modified gear scenarios demonstrated improved sinking performance in Aceh and Papua. In Aceh, the average sinking speed increased from 0.07 to 0.15 m/s in Improved Gear I and to 0.18 m/s in Improved Gear II, while the maximum depth increased from 37.3 to 54.8 m and 56.2 m, respectively. In Papua, the average sinking speed increased from 0.08 to 0.18 m/s and 0.20 m/s, while the maximum depth increased from 37.2 to 56.8 m and 60.6 m, respectively. In both regions, Improved Gear II exhibited the highest sinking performance. Enhanced sinking performance was accompanied by higher purse-line tension during pursing, with maximum values of 1666 kgf in Aceh and 1589 kgf in Papua. These results suggest that design tendencies identified in previous Indonesian studies, particularly a comparative reference sinking force (1.24 kgf/m), larger mesh size, and knotless polyester netting, appear consistent across the two regional cases examined. However, because the modified scenarios represent coupled multivariable scenarios and direct local field validation was not available for Aceh and Papua, the findings should be interpreted as comparative simulation-based evidence for assessing gear-modification options rather than as absolute in situ predictions. Full article

This study reports a mechanistic analysis of Pb²⁺ and Cu²⁺ adsorption on activated carbon (AC) obtained from durian skin. Pb²⁺ and Cu²⁺ adsorption tests were carried out at 303–323 K and pH 5.5 to interpret the heavy metal—durian skin AC systems. A monolayer model was applied to simulate experimental isotherms and calculate steric and energy parameters. The results indicated that the removal of these target pollutants was a multi-ionic process. The saturation adsorption capacities of this AC improved with increasing aqueous solution temperature, ranging from 81 to 139 mg/g for Pb²⁺ and from 95 to 180 mg/g for Cu²⁺ under the tested operating conditions. The calculated interaction energies indicated a physisorption mechanism where oxygenated functional groups played a relevant role. Durian skin AC can be used as an alternative adsorbent for purifying wastewater and industrial streams polluted by heavy metals. Full article