Search Results (499)

Background/Objectives: Vitamin D supplementation has shown promise in managing type 2 diabetes mellitus (T2DM), while the simultaneous impact on glycemic control and inflammation in T2DM remains poorly understood. This study aimed to investigate the potential role of vitamin D supplementation in managing T2DM using fasting plasma glucose (FPG), insulin levels, HOMA-IR, HOMA-B, HbA1c, and Hs-CRP as the biomarkers. Methods: Original articles from Scopus, Pubmed, Cochrane Library, Epistemonikos, and ScienceDirect published between 2014 and 2024 were the sources. Inclusion criteria included studies conducted as clinical trials or randomized controlled trials involving adult patients diagnosed with T2DM undergoing treatment with vitamin D. The risk of bias was evaluated using the ROB-2 tool and meta-analysis was conducted to quantitatively synthesize the results across the studies using pooled effect sizes and confidence intervals. Results: Nine studies were included in the meta-analysis. Significant differences were found at 12-week follow-up in insulin level (MD(−3.59) [95% CI: −6.93, −0.25]), HOMA-B (MD(−50.35) [95% CI: −92.29, −8.41]), hs-CRP (−2.51 [95% CI: −3.45, −1.57]), and HbA1c level (MD(−0.30) [95% CI: −0.54, −0.06]) and at 24-week follow-up in HOMA-IR (MD(−0.38) [CI: −0.53, −0.24]). The quality of the included studies was generally moderate, with three showing a potential risk of bias. Conclusions: The observed trends in FPG, insulin levels, HOMA-IR, HOMA-B, HbA1c, and hs-CRP indicate that vitamin D may influence glycemic control, insulin sensitivity, and inflammation, but these effects are often modest and may diminish over time. Future studies should explore longer duration randomized trials with standardized dosing and baseline vitamin D status stratification. Full article

The increasing demand for high-performance energy storage devices has stimulated interest in advanced electrolyte materials. Among them, ionic liquids ($\mathrm{I}\mathrm{L}\mathrm{s}$) stand out for their thermal stability, wide electrochemical windows, and good ionic conductivity. When doped into polymeric matrices, these ionic liquids form hybrid polymeric electrolytes that synergize the benefits of both liquid and solid electrolytes. This study explores a polymeric electrolyte based on polyethylene oxide ($\mathrm{P}\mathrm{E}\mathrm{O}$) doped with tributylmethylphosphonium iodide $\left(\mathrm{T}\mathrm{M}\mathrm{P}\mathrm{I}\right)$ and ammonium iodide ($\mathrm{N}{\mathrm{H}}_4\mathrm{I}$), focusing on its synthesis, structural and electrical properties, and performance in energy storage devices such as dye-sensitized solar cells and supercapacitors. Strategies to improve its ionic conductivity, mechanical and chemical stability, and electrode compatibility are also discussed, along with future directions in this field. Full article

Indonesia’s commitment to digital transformation is exemplified by the Gerakan 100 Smart City program, aiming to enhance public sector performance through technology integration. This study examines how information technology capability and 21st century digital skills influence public sector performance, mediated by managerial digital readiness and moderated by digital leadership. Grounded in Dynamic Capability Theory and Upper Echelon Theory, data from 1380 civil servants were analyzed using PLS-SEM via SmartPLS 4.1.0.9. Results show that both IT capability and digital skills significantly improve managerial digital readiness, which in turn positively impacts public sector performance. Managerial readiness mediates the effect of both predictors on performance, while digital leadership strengthens these relationships. Theoretically, this study frames managerial digital readiness as a dynamic capability shaped by leadership cognition. Practically, it highlights the importance of aligning infrastructure, skills, and leadership development to advance digital governance. Future research should consider longitudinal, multilevel, and qualitative designs to deepen insights. Full article

Land subsidence significantly threatens vulnerable coastal environments. This study aims to explore how Semarang’s government, local communities, and researchers address land subsidence and its role in exacerbating flood risk, against the backdrop of ongoing efforts within flood risk governance. Employing an integrated mixed-methods approach, the research combined quantitative geospatial analysis (InSAR and land cover change detection) with qualitative socio-political and governance analysis (interviews, FGDs, field observations). Findings show high subsidence rates in Semarang. Line of sight displacement measurements revealed a continuous downward trend from late 2014 to mid-2023, with rates varying from −8.8 to −10.1 cm/year in Karangroto and Sembungharjo. Built-up areas concurrently expanded from 21,512 hectares in 2017 to 23,755 hectares in 2023, largely displacing cropland and tree cover. Groundwater extraction was identified as the dominant driver, alongside urbanization and geological factors. A critical disconnect emerged: community views focused on flooding, often overlooking subsidence’s fundamental role as an exacerbating factor. The study concluded that multi-level collaboration, improved risk communication, and sustainable land management are critical for enhancing urban coastal resilience against dual threats of subsidence and flooding. These insights offer guidance for similar rapidly developing coastal cities. Full article

Determining the optimal portfolio is important in the investment process because it includes the selection of appropriate fund allocation to manage financial risk effectively. Although risk cannot be entirely eliminated, it is managed through strategic allocation based on investor preferences. Therefore, this research aimed to use mathematical models, including the power utility function, the natural logarithm utility function, and a combination of both, to capture varying degrees of risk aversion. The optimal allocation was obtained by analytically maximizing the expected end-of-period wealth utility under each specification, where the investor level of risk aversion was derived by determining the constant. The utility function that failed to produce closed-form solutions was solved through the use of a numerical method to approximate the optimal portfolio weight. Furthermore, numerical simulations were performed using data from two stocks in the e-commerce sector to prove the impact of parameter changes on investment decisions. The result showed explicit analytical values for each utility function, providing investors with a structured framework for determining optimal portfolio weights consistent with their risk profile. Full article

The major challenge facing big cities in developing nations is allocating residential land to the urban poor, given the constraints on land availability. This article investigates how and why the management of Waqf land, a particular type of land tenure in urban informal settlements, transforms. The analysis draws on principles of responsible land management and focuses on the specific case of Waqf land owned by the Kauman Grand Mosque in Semarang City, Indonesia. With a questionnaire distributed among tenants of the Waqf land, it was possible to retrieve data on experiences with the management of the Waqf land. The questionnaire and subsequent analysis used a scoring sheet based on the 8R framework of responsible land management. The findings indicate that the management of Waqf land in the study area changed and improved over time, evolving from an informal to a more formal structure. The responses additionally demonstrate a gradual transformation whereby, gradually, nearly all aspects of the 8R framework of responsible land management are considered positively. Nevertheless, the aspects of reflexivity and retraceability still score low, as access to documentation is still limited, and evaluations of how effective the management of land is are infrequent. The study concludes that despite being an unconventional form of land management, the Waqf land tenure regime appears to secure informal types of urban tenure, especially in areas with limited land availability. Moreover, the Waqf land institution supports strong and cooperative relationships within the community. Full article

This study evaluates the impacts of Solar Radiation Management (SRM) on precipitation-related climate extremes in Southeast Asia. Using simulations from the Geoengineering Large Ensemble (GLENS), we assess spatial anomalies and differences in extreme precipitation indices—number of wet days (RR1), very heavy precipitation days (R20mm), maximum 5-day precipitation (Rx5day), consecutive dry days (CDD), and consecutive wet days (CWD)—relative to historical (1980–2009) and Representative Concentration Pathway 8.5 (RCP8.5) baselines. The results reveal that SRM induces highly heterogeneous precipitation responses across the region. While SRM increases rainfall frequency in parts of Indonesia, it reduces the number of wet days and lengthens dry spells over Vietnam, Thailand, and the Philippines. Spatial variations are also observed in changes to heavy precipitation days and multi-day rainfall events, with potential implications for flood and drought risks. These findings highlight the complex trade-offs in hydrological responses under SRM deployment, with important considerations for agriculture, water resource management, and climate adaptation strategies in Southeast Asia. Full article

Anion exchange membrane fuel cells (AEMFCs) have garnered significant attention for their potential to advance fuel cell technology. In this study, we developed and characterized anion exchange membranes (AEMs) composed of quaternized poly(vinyl alcohol) (QPVA) electrospun nanofiber mats with poly(acrylamide-co-diallyldimethylammonium chloride) (PAADDA) as a matrix filler for interfiber voids. The objective was to investigate the effect of varying PAADDA concentrations as a matrix filler for interfiber voids on the structural, mechanical, and electrochemical properties of QPVA-based electrospun AEMs. Membranes with various concentrations of PAADDA were fabricated and extensively characterized using FTIR, SEM, tensile strength, water uptake, swelling degree, ion exchange capacity (IEC), and hydroxide ion conductivity (σ). FTIR confirmed the successful incorporation of PAADDA into the membrane structure, while SEM images showed that PAADDA effectively filled the voids between the QPVA fibers, resulting in denser membranes. The results indicated that the eQPAD5.0 membrane, with the highest PAADDA content, exhibited the best overall performance. The incorporation of PAADDA into QPVA-based electrospun AEMs significantly enhanced their mechanical strength, achieving a tensile strength of 23.9 MPa, an IEC of 1.25 mmol g⁻¹, and hydroxide conductivity of 19.49 mS cm⁻¹ at 30 °C and 29.29 mS cm⁻¹ at 80 °C, making them promising candidates for fuel cell applications. Full article

Our knowledge of the molecular data on viruses infecting potato (Solanum tuberosum) and its weeds in Indonesia still needs to be expanded. Thirteen potato leaves, together with one carrot (Daucus carota subsp. sativus) and one Oxalis latifolia leaves grew adjacent to potato fields were sampled in West, Central, and East Java Provinces of Indonesia to be tested using RT-PCR with universal primers to monitor the presence of potyviruses, carlaviruses, and begomoviruses in the surveyed regions. According to the test results and BLAST nucleotide analysis, four potato samples were found to be infected by potato virus Y (PVY, Potyvirus). All samples tested negative for carlaviruses and begomoviruses. Both phylogenetic trees constructed by MEGA11 software based on partial coat protein and partial coat protein + 3′-UTR sequences demonstrated that the four new PVY isolates belong to strain N. Nucleotide and amino acid homology analysis determined that all four new and 12 other strain N isolates registered in NBCI GenBank were identical at the observed genome region, suggested the same origin of Indonesian isolates. This study improved our understanding of the variation in PVY isolates in Indonesia and highlighted the need for tight surveillance since the country imports most of its tubers used as planting material. Full article

Medical image segmentation, especially in chest X-ray (CXR) analysis, encounters substantial problems such as class imbalance, annotation inconsistencies, and the necessity for accurate pathological region identification. This research aims to improve the precision and clinical reliability of pulmonary abnormality segmentation by developing NCT-CXR, a framework that combines anatomically constrained data augmentation with expert-guided annotation refinement. NCT-CXR applies carefully calibrated discrete-angle rotations (±5°, ±10°) and intensity-based augmentations to enrich training data while preserving spatial and anatomical integrity. To address label noise in the NIH Chest X-ray dataset, we further introduce a clinically validated annotation refinement pipeline using the OncoDocAI platform, resulting in multi-label pixel-level segmentation masks for nine thoracic conditions. YOLOv8 was selected as the segmentation backbone due to its architectural efficiency, speed, and high spatial accuracy. Experimental results show that NCT-CXR significantly improves segmentation precision, especially for pneumothorax (0.829 and 0.804 for ±5° and ±10°, respectively). Non-parametric statistical testing (Kruskal–Wallis, H = 14.874, p = 0.0019) and post hoc Nemenyi analysis (p = 0.0138 and p = 0.0056) confirm the superiority of discrete-angle augmentation over mixed strategies. These findings underscore the importance of clinically constrained augmentation and high-quality annotation in building robust segmentation models. NCT-CXR offers a practical, high-performance solution for integrating deep learning into radiological workflows. Full article

Background/Objectives: Cariprazine, a D3/D2 partial agonist, is one of the few recommended treatment options for bipolar 1 disorder (BP1D) in Southeast Asia. This study aims to generate insights from leading experts on the safe and effective use of cariprazine for BP1D, specifically by formulating practical recommendations not thoroughly covered in the existing literature. Methods: A formal consensus methodology using the modified RAND/UCLA Appropriateness Method was employed to develop consensus recommendations. The methodology included a targeted literature search, creation of clinical scenarios, two rounds of rating of the appropriateness of each scenario on a nine-point Likert scale by an expert panel of psychiatrists from Southeast Asia (n = 13), and a face-to-face discussion among the expert panel between the two rounds of rating. In the absence of disagreement, scenarios were classified as appropriate (7–9), equivocal (4–6), or inappropriate (1–3) based on median scores. Clinical scenarios were subsequently converted to consensus recommendations upon approval by the expert panel. Results: Most experts recommended a 4–8-week trial of cariprazine for bipolar depression (85%) and 3–4 weeks for acute mania/mixed (71%). For longer treatment, 61.5% and 69% recommended >1 year for acute mania/mixed and bipolar depression, respectively. Cariprazine was also considered suitable as first-line therapy, including for first-episode bipolar depression (Mdn: 8, IQR: 7–9) and first-episode mania (Mdn: 8; IQR: 8–9). Conclusions: The consensus recommendations may serve as practical guidance for clinicians to make informed decisions regarding the management of adult patients with BP1D, while considering the preferences and circumstances of individual patients. Full article

Accurate segmentation of brain tumors in magnetic resonance imaging (MRI) remains a challenging task due to heterogeneous tumor structures, varying intensities across modalities, and limited annotated data. Deep learning has significantly advanced segmentation accuracy; however, it often suffers from sensitivity to hyperparameter settings and limited generalization. To overcome these challenges, bio-inspired metaheuristic algorithms have been increasingly employed to optimize various stages of the deep learning pipeline—including hyperparameter tuning, preprocessing, architectural design, and attention modulation. This review systematically examines developments from 2015 to 2025, focusing on the integration of nature-inspired optimization methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and novel hybrids including CJHBA and BioSwarmNet into deep learning-based brain tumor segmentation frameworks. A structured multi-query search strategy was executed using Publish or Perish across Google Scholar and Scopus databases. Following PRISMA guidelines, 3895 records were screened through automated filtering and manual eligibility checks, yielding a curated set of 106 primary studies. Through bibliometric mapping, methodological synthesis, and performance analysis, we highlight trends in algorithm usage, application domains (e.g., preprocessing, architecture search), and segmentation outcomes measured by metrics such as Dice Similarity Coefficient (DSC), Jaccard Index (JI), Hausdorff Distance (HD), and ASSD. Our findings demonstrate that bio-inspired optimization significantly enhances segmentation accuracy and robustness, particularly in multimodal settings involving FLAIR and T1CE modalities. The review concludes by identifying emerging research directions in hybrid optimization, real-time clinical applicability, and explainable AI, providing a roadmap for future exploration in this interdisciplinary domain. Full article

This study evaluates the performance of a statistical-based automatic contrast-to-noise ratio (CNR) measurement method on images of the ACR CT phantom under varying imaging parameters. A statistical automatic method for segmenting low-contrast objects and for measuring CNR was recently introduced. The method employs a 25 mm region of interest (ROI), rotated in 2° clockwise steps, to identify the low-contrast object by locating the maximum CT value. The CNR was measured on images acquired with different parameters: tube voltage (80–140 kVp), tube current (80–200 mA), slice thickness (1.25–10 mm), field of view (190–230 mm), and convolution kernel (edge, ultra, lung, bone, chest, standard). The automatic results were compared to manual measurements. The automatic method accurately identified the largest low-contrast object. The CNR values from the automatic and manual methods showed no significant difference (p > 0.05). The CNR increased with higher tube voltage and current, and with thinner slice thickness. Chest and standard kernels yielded higher CNRs, while edge, ultra, lung, and bone kernels yielded lower ones. The CNR remained stable with minor FOV changes. The statistical-based automatic method provided accurate and consistent CNR measurements across a range of imaging settings for the ACR CT phantom. Full article

Macular hole (MH) surgery generally has a high success rate, but finding anatomical plug for refractory cases remains challenging. The human amniotic membrane (hAM), with its anti-inflammatory and regenerative properties, has emerged as a potential option. This study aims to report the anatomical and functional outcomes of human amniotic membrane (hAM) graft as an intervention to repair refractory macular hole cases where wide internal limiting membrane (ILM) peeling was unsuccessful. A retrospective chart review was conducted at a single center, with the main outcomes being closure rate and postoperative BCVA at 6 months. Eleven eyes of 11 patients with refractory macular holes were identified and included in the study. Participants were predominantly males (72.73%) with a mean age of 49.27 years. Nine eyes achieved successful MH closure with a single intervention and showed no recurrence during the 6-month follow-up. Mean BCVA at 3 and 6 months improved significantly (p = 0.0207) from 1.747 ± 0.74 logMAR to 1.210 ± 0.51 logMAR and 0.939 ± 0.47 logMAR (range 2.079–0.301 logMAR). The use of human amniotic membrane (hAM) graft seems to be a viable and effective alternative for the treatment of refractory macular holes. However, further larger prospective controlled studies are necessary to confirm our results. Full article

Background/Objectives: The evaluation of metabolic and physiological health indicators in people with Down syndrome (DS) is crucial, since these people are more prone to metabolic problems. However, there is limited scientific evidence regarding the health status and health literacy (HL) of adults with DS and their legal guardians. This study aimed to assess the health status of adults with DS and determine the HL levels of their legal guardians. Methods: Eighteen adults (11 females, 7 males) with DS aged 28.64 ± 9.01 years were tested for health status, and their legal guardians completed the HL survey. Gender differences in all study variables were checked by t-tests for independent samples and Cohen’s D effect sizes (ESs). Differences in all study variables between parents with low and adequate HL were calculated via receiver operating characteristic curves. Results: Males were overweight, whereas females were obese (mean BMI = 26.51 and 30.10 for males and females, respectively). Females had higher high-density lipoprotein concentrations (large ES), whereas males had higher hematocrit and hemoglobin concentrations (large ES). Hematological parameters were the most significant variables that differed between parents with limited and adequate HL status (AUC = 0.79–0.87). Conclusions: These findings suggest that in the absence of severe comorbidities, adults with DS may achieve stable health profiles, particularly when supported by structured physical activity and informed caregiving. The influence of parental HL on health parameters points to the potential for parent-targeted health education to improve health outcomes and promote autonomy in individuals with DS through supported decision-making. Thus, our findings highlight the need for greater investment in caregiver and parental health education and systemic support to optimize health outcomes in adults with DS. Future research should explore interventions aimed at improving parental HL and examine the extent to which these efforts translate into improved health outcomes for people with DS. Full article