Comparative Analysis of Sinkhole Susceptibility Models Using Ensemble Machine Learning and Local Interpretable Model‐Agnostic Explanations ( LIME )

ABSTRACT The accelerating rate of cover‐collapse sinkhole formation in the Konya Closed Basin (KCB) poses a critical threat to infrastructure and agriculture. However, standard machine learning susceptibility models often yield unreliable results by failing to account for the strong spatial clustering inherent in such geohazards. This study addresses this methodological gap by developing spatially robust and explainable Sinkhole susceptibility maps (SSMs). A comprehensive inventory of 495 sinkholes (2008–2025) was analyzed using a temporally consistent dataset. Unlike traditional studies relying on random partitioning, this study implemented a rigorous Spatial Block Cross‐Validation (SBCV) strategy to mitigate spatial leakage. Five ensemble algorithms were evaluated; results indicated that XGBoost and CatBoost demonstrated superior spatial discrimination with mean AUC scores of 0.88 and 0.85, respectively, confirming their robustness against spatial heterogeneity. To transcend “black‐box” opacity, the LIME technique was employed, revealing novel causal mechanisms. Crucially, the analysis empirically validated the “hypogenic karstification” theory, identifying a 20 km influence zone around volcanic forms. Furthermore, the strong predictive power of well density and groundwater depletion exposed the direct link between unsustainable irrigation and sinkhole formation. This study provides a statistically robust baseline for land‐use planning and advocates for a paradigm shift from reactive response to proactive aquifer management.

Efficacy of Digital Mental Health Interventions for Depression and Anxiety in Older Adults: A Systematic Review and Meta‐Analysis

ABSTRACT Background Older adults face growing risks of depression and anxiety, yet stigma, comorbidities, cost, and limited access impede receipt of conventional care. Digital mental health interventions (DMHIs), including immersive virtual reality (VR), exergaming, and mobile apps, may reduce these barriers. Aim To evaluate the efficacy of DMHIs in reducing depressive and anxiety symptoms among adults aged ≥ 50 years. Methods We conducted a PRISMA adherent systematic review and meta‐analysis of randomized controlled trials. Interventions included immersive VR, exergaming/physical digital platforms, mobile applications, and digital cognitive training. Standardized mean differences (SMDs) were pooled with random effects models; heterogeneity was assessed with I 2 . Results Nineteen RCTs ( n  = 718; mean ages 50.9–84.7 years) met inclusion criteria. Across studies, DMHIs significantly reduced depressive symptoms (SMD = −0.656, 95% CI = −0.932 to −0.380; p  < 0.001) and anxiety symptoms (SMD = −0.559, 95% CI = −0.740 to −0.380; p  < 0.0001). Immersive and physically engaging modalities (e.g., VR, exergaming) outperformed app‐based approaches. Heterogeneity ranged from moderate to high ( I 2  ≈ 69.6%–97%). Linking Evidence to Action Offer DMHIs : especially VR or exergaming when access to in‐person therapy is limited or as an adjunct to usual care. Provide brief onboarding and, when feasible, caregiver support to boost adherence and confidence with technology. Select or configure age‐friendly interfaces (e.g., large fonts, simple navigation) to address common usability barriers. Integrate DMHIs into stepped‐care or rehabilitation pathways and monitor outcomes with validated tools (e.g., GDS, STAI). Address equity by supplying devices/connectivity solutions and consider cost‐effectiveness and long‐term engagement in implementation plans. Trial Registration: PROSPERO ID: CRD420250655153

LLM-guided multimodal attention network for robust multiclass Parkinson’s disease diagnosis

Preparation, optimization, and characterization of ivermectin microemulsion as a potential glioblastoma treatment

The prognosis for glioblastoma multiforme (GBM), a very aggressive brain tumor, is poor, and there are few available treatments. Various oils, cosurfactants, and surfactants were tested for solubility. A pseudo-ternary phase diagram was made using the water-titration method. Box-behenken design (BBD) was used to optimize the microemulsion, which was prepared in batches by varying the ratio of surfactant to co-surfactant. The optimised batch was evaluated for particle size (PS), polydispersity index (PDI), zeta potential (ZP), %Transmittance, chemical interaction, pH, conductivity, specific gravity, drug content, in-vitro drug release, and in-silico docking. The microemulsion formulation having Transcutol HP, Tween 80, and Capmul MCM C8, showed satisfactory PS (74.9 ± 0.35 nm), PDI (0.223 ± 0.021) and ZP (−0.35 ± 0.15 mV) respectively. The in vitro cell line study in U87 cells of optimized IVM formulation shown better treatment for brain diseases. Additionally, IVM has a good binding affinity towards mTOR kinase for GBM as shown by an in-silico study. In summary, IVM-loaded MEs offer a promising approach for GBM treatment, warranting further pre-clinical evaluation.

Multipoint Stress Mixed Finite Element Methods for Elasticity on Distorted Quadrilateral Grids

We develop multipoint stress mixed finite element methods for linear elasticity with weakly enforced stress symmetry on distorted quadrilateral grids, which can be reduced to positive definite cell-centered systems. The methods utilize the lowest-order Brezzi–Douglas–Marini finite element spaces for the stress and employ vertex quadrature rules to localize the interaction of degrees of freedom. This approach allows for local stress elimination around each vertex. We introduce two methods. The first method uses a piecewise constant rotation, resulting in a cell-centered system for the displacement and the rotation. The second method employs a continuous piecewise bilinear rotation, enabling further elimination of the rotation and resulting in a cell-centered system for the displacement only. The methods utilize a non-symmetric vertex quadrature rule for the stress bilinear form and both non-symmetric and symmetric vertex quadrature rules for the asymmetry bilinear forms. Stability and error analysis are performed for both methods. First-order convergence is established for all variables in theL2{L^{2}}-norm. Numerical results are presented that verify the theoretical results.

Marriage Obstacles for Individuals with Intellectual Disabilities from Their Perspectives

Marriage is contentious social issue for persons with intellectual impairments, that their families and the individuals with disabilities themselves are divided on it. Some people look at marriage from a positive perspective that it helps them integrate into society and live a normal and independent life. But others believe marriage in such cases has many problems and it is not easy to succeed. This study aims to identify the main challenges faced by individuals with intellectual disabilities regarding marriage from their own perspective. The researchers created a questionnaire with 30 questions, divided into four main aspects: the nature of the disability itself, and the psychological, social, and economic challenges. The questionnaire was distributed it to a sample of 294 people with intellectual disabilities to understand their opinions on the matter. The results showed that the participants perceived the challenges as significant, with the most affecting aspect being the economic side, followed by the social, then the psychological, and lastly the nature of the disability itself. There were also no clear differences between the responses of males and females or between the specialisations or academic levels. the study revealed that many people with intellectual disabilities suffer from society’s perception of them and the discrimination they face. The study provided solutions such as government and private sector assistance to enable their marriage, exemptions and facilities, and promoting public knowledge about their nature, talents, and achievements. Furthermore, their inherent right to marriage should be protected by enacting rules and regulations that take into account their interests and desires for a normal married life.

Efficiency enhancement and cost analysis of a low-frequency induction motor using Metglas stator core: a comparative study with traditional designs

The efficiency of conventional induction motors is constrained by the substantial core losses associated with silicon steel, prompting the investigation of alternative magnetic materials for their fabrication. This study aims to enhance the performance of a low-frequency (50 Hz) induction motor by substituting the traditional M19 stator core with Metglas 2605SA1, an amorphous alloy known for its minimal hysteresis and eddy current losses. The study was conducted using ANSYS Motor-CAD simulations under identical geometric and electrical conditions to ensure fair comparison. The key performance indicators, namely efficiency, losses, and thermal stability, were analysed alongside the lifecycle cost and environmental impact. The results indicate that the Metglas-based motor achieved a system efficiency of 85.46 %, compared to 80.71 % for M19, with a total loss reduction of 21.15 % and a core-loss reduction of 62 % (110.3 W → 41.89 W). The peak stator temperature decreased by 17 °C, which enhanced the insulation life and reduced the cooling requirements. Despite the higher initial material cost, the Metglas motor offers long-term economic and environmental benefits, including lower operating costs and reduced CO 2 emissions. These findings underscore the industrial significance of amorphous alloys in realising next-generation, high-efficiency, and sustainable motors.

Chromatographic analysis of Crataegus azarolus and possible psychiatric implications

A photovoltaic-based VLC system for simultaneous data transmission and energy harvesting

The growing demand for batteryless indoor Internet of Things (IoT) devices has stimulated interest in visible light communication (VLC) systems capable of simultaneously delivering information and harvesting energy from ambient illumination. This paper presents a photovoltaic (PV)-based VLC system employing asymmetrically clipped optical orthogonal frequency-division multiplexing (ACO-OFDM) to enable simultaneous lightwave information and power transfer (SLIPT) using a single PV receiver. A bias-tee front-end separates the harvested direct-current (DC) component from the data-bearing alternating-current (AC) signal, while an adaptive normalized least mean squares (NLMS) equalizer is applied to mitigate illumination-dependent gain drift, PV nonlinearity, and maximum power point tracking (MPPT)-induced ripple. Comprehensive simulations evaluate bit error rate (BER), spectral efficiency (SE), and harvested power under practical indoor conditions. Results show that reliable communication with BER below 10 −3 is achieved at approximately 18 dB SNR for 16-QAM and 25 dB for 64-QAM. The system attains spectral efficiency approaching 1 bit/s/Hz and 1.5 bit/s/Hz for 64-QAM at moderate-to-high SNRs while maintaining energy-neutral operation at illumination levels above approximately 800 lux. These findings confirm the feasibility of PV-based VLC as an effective solution for low-power, batteryless indoor IoT applications.

A rare case of severe short stature diagnosed after late-onset hypocalcemia: Kenny–Caffey syndrome type 2