Search Results (1,024)

Background/Objectives: Amorphous solid drugs exhibit physical instability and a propensity for crystallization, which leads to reduced solubility and bioavailability. Hence, this study optimized scale manufacturing parameters for producing a physically stable amorphous solid form of nilotinib using neutralization precipitation. Methods: A systematic evaluation of the effects of the solute concentration and filtration rate on amorphous physical stability was conducted using the pair distribution function (PDF), principal component analysis (PCA), and reduced crystallization temperature (R_c) values. Results: It showed concentration-dependent crystallization resistance, with optimal physical stability achieved at a solute concentration of 0.126 mol/L and a 124 mL/min filtration rate. Experiments carried out at a scale of 50 g confirmed the stability of the production process. Conclusions: These findings provide a validated framework for developing lab-scale amorphous drug products with improved shelf-life stability, assessed using indirect indicators (PDF, R_c) and confirmed through accelerated stability tests. Full article

In an era where online interactions increasingly shape social dynamics, the pervasive issue of cyberbullying poses a significant threat to the well-being of individuals, particularly among vulnerable groups. Despite extensive research on text-based cyberbullying detection, the rise of visual content on social media platforms necessitates new approaches to address cyberbullying using images. This domain has been largely overlooked. In this paper, we present a novel dataset specifically designed for the detection of visual cyberbullying, encompassing four distinct classes: abuse, curse, discourage, and threat. The initial prepared dataset (cyberbullying visual indicators dataset (CVID)) comprised 664 samples for training and validation, expanded through data augmentation techniques to ensure balanced and accurate results across all classes. We analyzed this dataset using several advanced deep learning models, including VGG16, VGG19, MobileNetV2, and Vision Transformer. The proposed model, based on DenseNet201, achieved the highest test accuracy of 99%, demonstrating its efficacy in identifying the visual cues associated with cyberbullying. To prove the proposed model’s generalizability, the 5-fold stratified K-fold was also considered, and the model achieved an average test accuracy of 99%. This work introduces a dataset and highlights the potential of leveraging deep learning models to address the multifaceted challenges of detecting cyberbullying in visual content. Full article

COVID-19 vaccine hesitancy in Pakistan is a barrier to optimal vaccine uptake and has been situated within a context of hesitancy towards other vaccines. A mixed-methods study was conducted during the initial COVID-19 vaccine roll-out in 2021 in four union councils in Peshawar, consisting of a cross-sectional survey, eight focus group discussions (FGDs) with community members and eight in-depth interviews with healthcare workers (HCWs) to assess perceptions toward vaccines. Multivariable logistic regression was used to assess factors associated with COVID-19 vaccine hesitancy. Of 400 survey participants, 57.3% were vaccine acceptant and 42.8% vaccine hesitant. Just over half (56.8%) perceived COVID-19 vaccines to be safe. Most (88%) reported trust in HCWs to provide accurate vaccine information. FGDs revealed that women received less information about the vaccine compared to men and cultural restrictions were barriers even for those willing to be vaccinated. Correlates of vaccine acceptance included male sex (aOR 2.25; 95% CI 1.29–3.91), age 50 years or greater (aOR 1.74; 95% CI 1.19–6.31), social network support (e.g., vaccine acceptance among an individual’s social network) in receiving COVID-19 vaccines (aOR 2.38; 95% CI 1.45–3.89), community concern about COVID-19 spread (aOR 2.84; 95% CI 1.73–4.66), and trust in HCWs to provide vaccine information (aOR 3.47; 95% CI 1.62–7.42). Future vaccine promotion should prioritize engaging community leaders, sharing transparent information, combatting misinformation and rumors, and implementing household-based interventions especially targeting the importance of vaccination among women and young people to increase uptake. Full article

Organic polymer introduction effectively enhances the toughness, bond strength, and durability of ordinary cement-based materials, and is often used for concrete repair and reinforcement. However, the entrained air effect simultaneously induced by polymer and the inhibitory action on cement hydration kinetics often lead to degradation in mechanical performances of polymer-modified cement-based composite (PMC). Nanomaterials provide unique advantages in enhancing the properties of PMC due to their characteristic ultrahigh specific surface area, quantum effects, and interface modulation capabilities. This review systematically examines recent advances in nano-reinforced PMC (NPMC), elucidating their synergistic optimization mechanisms. The synergistic effects of nanomaterials—nano-nucleation, pore-filling, and templating mechanisms—refine the microstructure, significantly enhancing the mechanical strength, impermeability, and erosion resistance of NPMC. Furthermore, nanomaterials establish interpenetrating network structures (A composite structure composed of polymer networks and other materials interwoven with each other) with polymer cured film (The film formed after the polymer loses water), enhancing load-transfer efficiency through physical and chemical action while optimizing dispersion and compatibility of nanomaterials and polymers. By systematically analyzing the synergy among nanomaterials, polymer, and cement matrix, this work provides valuable insights for advancing high-performance repair materials. Full article

The Ganges–Brahmaputra–Meghna (GBM) delta, characterized by complex topography and hydrological conditions, is highly susceptible to recurrent flooding, particularly in its coastal regions where tidal dynamics hinder floodwater discharge. This study integrates Synthetic Aperture Radar (SAR) imagery with machine learning (ML) techniques to assess near real-time flood inundation patterns associated with extreme weather events, including recent cyclones between 2017 to 2024 (namely, Mora, Titli, Fani, Amphan, Yaas, Sitrang, Midhili, and Remal) as well as intense monsoonal rainfall during the same period, across a large spatial scale, to support disaster risk management efforts. Three machine learning algorithms, namely, random forest (RF), support vector machine (SVM), and K-nearest neighbors (KNN), were applied to flood extent data derived from SAR imagery to enhance flood detection accuracy. Among these, the SVM algorithm demonstrated the highest classification accuracy (75%) and exhibited superior robustness in delineating flood-affected areas. The analysis reveals that both cyclone intensity and rainfall magnitude significantly influence flood extent, with the western coastal zone (e.g., Morrelganj and Kaliganj) being most consistently affected. The peak inundation extent was observed during the 2023 monsoon (10,333 sq. km), while interannual variability in rainfall intensity directly influenced the spatial extent of flood-affected zones. In parallel, eight major cyclones, including Amphan (2020) and Remal (2024), triggered substantial flooding, with the most severe inundation recorded during Cyclone Remal with an area of 9243 sq. km. Morrelganj and Chakaria were consistently identified as flood hotspots during both monsoonal and cyclonic events. Comparative analysis indicates that cyclones result in larger areas with low-level inundation (19,085 sq. km) compared to monsoons (13,829 sq. km). However, monsoon events result in a larger area impacted by frequent inundation, underscoring the critical role of rainfall intensity. These findings underscore the utility of SAR-ML integration in operational flood monitoring and highlight the urgent need for localized, event-specific flood risk management strategies to enhance flood resilience in the GBM delta. Full article

The Chagai porphyry copper belt is a major component of the Tethyan metallogenic domain, which spans approximately 300 km and hosts several giant porphyry copper deposits. The tectonic setting, whether subduction-related or post-collisional, and the deep dynamic processes governing the formation of these giant deposits remain poorly understood. Mafic microgranular enclaves (MMEs), mafic dikes, and multiple porphyries have been documented in the Saindak mining area. This work examines both the ore-rich and non-ore intrusions in the Saindak porphyry Cu-Au deposit, using methods like molybdenite Re-Os dating, U-Pb zircon ages, Hf isotopes, and bulk-rock geochemical data. Geochronological results indicate that ore-fertile and barren porphyries yield ages of 22.15 ± 0.22 Ma and 22.21 ± 0.33 Ma, respectively. Both MMEs and mafic dikes have zircons with nearly identical ²⁰⁶Pb/²³⁸U weighted mean ages (21.21 ± 0.18 Ma and 21.21 ± 0.16 Ma, respectively), corresponding to the age of the host rock. Geochemical and Sr–Nd–Hf isotopic evidence indicates that the Saindak adakites were generated by the subduction of the Arabian oceanic lithosphere under the Eurasian plate, rather than through continental collision. The adakites were mainly formed by the partial melting of a metasomatized mantle wedge, induced by fluids from the dehydrating subducting slab, with minor input from subducted sediments and later crust–mantle interactions during magma ascent. We conclude that shallow subduction of the Arabian plate during the Oligocene–Miocene may have increased the flow of subducted fluids into the sub-arc mantle source of the Chagai arc. This process may have facilitated the widespread deposition of porphyry copper and copper–gold mineralization in the region. Full article

This study investigates the interplay between adaptive online learning, students’ digital intelligence, sustainable learning, and digital mental well-being among female university students in Saudi Arabia. In response to the growing reliance on digital platforms in higher education, a structured questionnaire was distributed via social media to capture student perceptions of their online learning experiences. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the analysis revealed that while adaptive online learning is a critical enabler, its influence is most effective when mediated by students’ digital intelligence. The findings highlighted that students with higher digital intelligence are more likely to engage in sustainable learning practices and maintain better mental well-being in digital environments. Furthermore, innovative teaching practices were shown to strengthen these relationships, underscoring the importance of interactive and adaptive pedagogies. This research contributes to the growing discourse on digital education by emphasizing the importance of indirect pathways and learner-centred dynamics in shaping positive educational and psychological outcomes. This study offers practical and theoretical implications for educators, institutions, and policymakers aiming to create inclusive, resilient, and psychologically supportive digital learning environments. Future research is encouraged to examine these relationships across different cultural and institutional contexts and explore the longitudinal impacts of digital learning strategies. Full article

This research evaluates the mechanical properties, environmental impacts, and cost-effectiveness of Hub Coal fly ash (FA)-based geopolymer concrete (FAGPC) as a sustainable alternative to ordinary Portland cement (OPC) concrete. This local FA has not been investigated previously. A total of 24 FAGPC mixes were tested under both ambient and heat curing conditions, varying the molarities of sodium hydroxide (NaOH) solution (10-M, 12-M 14-M and 16-M), sodium silicate to sodium hydroxide (Na₂SiO₃/NaOH) ratios (1.5, 2.0, and 2.5), and alkaline activator solution to fly ash (AAS/FA) ratios (0.5 and 0.6). The test results demonstrated that increasing NaOH molarity enhances the compressive strength (CS.) by 145% under ambient curing, with a peak CS. of 32.8 MPa at 16-M NaOH, and similarly, flexural strength (FS.) increases by 90% with a maximum FS. of 6.5 MPa at 14-M NaOH. Conversely, increasing the Na₂SiO₃/NaOH ratio to 2.5 reduced the CS. and FS. of ambient-cured specimens by 12.5% and 10.5%, respectively. Microstructural analysis revealed that higher NaOH molarity produced a denser, more homogeneous matrix, supported by increased Si–O–Al bond formation observed through energy-dispersive X-ray spectrometry. Environmentally, FAGPC demonstrated a 35–40% reduction in embodied CO₂ emissions compared to OPC, although the production costs of FAGPC were 30–35% higher, largely due to the expense of alkaline activators. These findings highlight the potential of FAGPC as a low-carbon alternative to OPC concrete, balancing enhanced mechanical performance with sustainability. New, green, and cheap activation solutions are sought for a new generation of more sustainable and affordable FAGPC. Full article

Incremental energy demand, environmental constraints, restrictions in the availability of energy resources, economic conditions, and political impact prompt the power sector toward deregulation. In addition to these impediments, electric power competition for power quality, reliability, availability, and cost forces utilities to maximize utilization of the existing infrastructure by flowing power on transmission lines near to their thermal limits. All these factors introduce problems related to power network stability, reliability, quality, congestion management, and security in restructured power systems. To overcome these problems, power-electronics-based FACTS devices are one of the beneficial solutions at present. In this review paper, the significant role of FACTS devices in restructured power networks and their technical benefits against various power system problems such as load frequency control, voltage stability, and congestion management will be presented. In addition, an extensive discussion about the comparison between different FACTS devices (series, shunt, and their combination) and comparison between various optimization techniques (classical, analytical, hybrid, and meta-heuristics) that support FACTS devices to achieve their respective benefits is presented in this paper. Generally, it is concluded that third-generation FACTS controllers are more popular to mitigate various power system problems (i.e., load frequency control, voltage stability, and congestion management). Moreover, a combination of multiple FACTS devices, with or without energy storage devices, is more beneficial compared to their individual usage. However, this is not commonly adopted in small power systems due to high installation or maintenance costs. Therefore, there is a trade-off between the selection and cost of FACTS devices to minimize the power system problems. Likewise, meta-heuristics and hybrid optimization techniques are commonly adopted to optimize FACTS devices due to their fast convergence, robustness, higher accuracy, and flexibility. Full article

Biomimetic design for engineering applications may suggest the optimal performance of engineering devices. In this work the passive/pure pitching characteristics of a hydrofoil are investigated experimentally with and without a pair of biomimetic fin strips placed symmetrically on the two sides of the foil leading edge. The work is performed in a recirculating water channel at low Reynolds numbers (Re) with a range of 1300 ≤ Re ≤ 3200. Using high-speed videography and Particle Image Velocimetry (PIV), the pitching characteristics and wakes are visualized. Passive pitching characteristics, i.e., the pitching amplitude and pitching frequency of the hydrofoils, are investigated based on their trailing edge movement. Significant improvement in both pitching frequency and amplitudes are observed for the foil with fin strips compared to the baseline simple foil. Comparing the pitching characteristics of the two foils, it is observed that the hydrofoil with biomimetic fin strips exhibits 25% and 21% higher pitching amplitude and pitching frequency, respectively, compared to that of the baseline at comparable Reynolds numbers. The initiation of pitching for the finned foil is also observed at comparatively low Reynolds numbers. The wake is also studied using time mean and fluctuating velocity profiles obtained using PIV. Full article

The determination of the live body weight of camels (required for their successful breeding) is a rather difficult task due to the problems with handling and restraining these animals. Therefore, the main aim of this study was to predict the ABW of eight indigenous camel (Camelus dromedarius) breeds of Pakistan (Bravhi, Kachi, Kharani, Kohi, Lassi, Makrani, Pishin, and Rodbari). Selected productive (hair production, milk yield per lactation, and lactation length) and reproductive (age of puberty, age at first breeding, gestation period, dry period, and calving interval) traits served as the predictors. Six data mining methods [classification and regression trees (CARTs), chi-square automatic interaction detector (CHAID), exhaustive CHAID (EXCHAID), multivariate adaptive regression splines (MARSs), MLP, and RBF] were applied for ABW prediction. Additionally, hierarchical cluster analysis with Euclidean distance was performed for the phenotypic characterization of the camel breeds. The highest Pearson correlation coefficient between the observed and predicted values (0.84, p < 0.05) was obtained for MLP, which was also characterized by the lowest root-mean-square error (RMSE) (20.86 kg), standard deviation ratio (SD_ratio) (0.54), mean absolute percentage error (MAPE) (2.44%), and mean absolute deviation (MAD) (16.45 kg). The most influential predictor for all the models was the camel breed. The applied methods allowed for the moderately accurate prediction of ABW (average R² equal to 65.0%) and the identification of the most important productive and reproductive traits affecting its value. However, one important limitation of the present study is its relatively small dataset, especially for training the ANN (MLP and RBF). Hence, the obtained preliminary results should be validated on larger datasets in the future. Full article

This paper presents a novel, four-port, rectangular microstrip, inset-feed multiple-input and multiple-output (MIMO) antenna array, enhanced with metamaterials for improved gain and isolation, specifically designed for multi-operator 5G open radio access network (ORAN)-based indoor software-defined radio (SDR) applications. ORAN is an open-source interoperable framework for radio access networks (RANs), while SDR refers to a radio communication system where functions are implemented via software on a programmable platform. A 3 × 3 metamaterial (MTM) superstrate is placed above the MIMO antenna array to improve gain and reduce the mutual coupling of MIMO. The proposed MIMO antenna operates over a 300 MHz bandwidth (3.5–3.8 GHz), enabling shared infrastructure for multiple operators. The antenna’s dimensions are 75 × 75 × 18.2 mm³. The antenna possesses a reduced mutual coupling less than −30 dB and a 3.5 dB enhancement in gain with the help of a novel 3 × 3 MTM superstrate 15 mm above the radiating MIMO elements. A performance evaluation based on simulated results and lab measurements demonstrates the promising value of key MIMO metrics such as a low envelope correlation coefficient (ECC) < 0.002, diversity gain (DG) ~10 dB, total active reflection coefficient (TARC) < −10 dB, and channel capacity loss (CCL) < 0.2 bits/sec/Hz. Real-world testing of the proposed antenna for ORAN-based sub-6 GHz indoor wireless systems demonstrates a downlink throughput of approximately 200 Mbps, uplink throughput of 80 Mbps, and transmission delays below 80 ms. Additionally, a walk test in an indoor environment with a corresponding floor plan and reference signal received power (RSRP) measurements indicates that most of the coverage area achieves RSRP values exceeding −75 dBm, confirming its suitability for indoor applications. Full article

Gastric cancer (GC) remains a major global health burden, with high morbidity and mortality rates, particularly in regions with prevalent Helicobacter pylori (H. pylori) infection. While H. pylori has long been recognized as a primary carcinogenic agent, recent research has underscored the broader contribution of the gastric microbiota to gastric carcinogenesis. Alterations in the microbial community, or dysbiosis, contribute to chronic inflammation, immune modulation, and epithelial transformation through a range of mechanisms, including disruption of mucosal integrity, activation of oncogenic signaling pathways (e.g., PI3K/Akt, NF-κB, STAT3), and epigenetic alterations. Furthermore, microbial metabolites, such as short-chain fatty acids, secondary bile acids, and lactate, play dual roles in either promoting or suppressing tumorigenesis. Oral and gut-derived microbes, translocated to the gastric niche, have been implicated in reshaping the gastric microenvironment and exacerbating disease progression. The composition of the microbiota also influences responses to cancer immunotherapy, suggesting that microbial profiles can serve as both prognostic biomarkers and therapeutic targets. Emerging strategies, such as probiotics, dietary interventions, and fecal microbiota transplantation (FMT), offer new avenues for restoring microbial balance and enhancing therapy response. This review synthesizes current knowledge on the complex interplay between microbiota and gastric cancer development and emphasizes the potential of microbiome modulation in both preventive and therapeutic frameworks. Full article

Background/Objectives: Non-melanoma skin cancer (NMSC) is among the most common cancers in the United States, with solar ultraviolet (UV) radiation being a primary etiological factor. T-LAK cell-originated protein kinase (TOPK), a serine/threonine kinase activated by solar UV, has been implicated in skin carcinogenesis. This study aimed to investigate the mechanistic role of TOPK in solar UV-induced skin damage and tumor development. Methods: RNA sequencing (RNA-seq) was performed on skin tissues from wild-type (WT) and TOPK knockout (KO) mice, with or without solar UV exposure, to identify TOPK-regulated genes and pathways. Follow-up experiments using Western blotting, immunofluorescence, and luciferase assays were conducted in vitro and in vivo. Functional assays included 3D spheroid and Transwell co-culture systems involving cutaneous squamous cell carcinoma (cSCC) and fibroblast cells. Results: TOPK deletion altered gene expression profiles and inhibited solar UV-induced activation of multiple signaling pathways, including cytokine–cytokine receptor interaction, PI3K/AKT, MAPKs, PKG, cAMP, and calcium signaling. RNA-seq and protein analyses identified interleukin-19 (IL19) as a key downstream effector suppressed by TOPK deletion. In cSCC and fibroblast cells, TOPK knockdown reduced IL19 expression and secretion. IL19 promoted cSCC growth and activated PI3K/AKT, ERK, and TOPK pathways. Additionally, chronic TGFβ exposure increased IL19 expression and activated fibroblasts, as indicated by elevated αSMA and FAPα levels. Conclusions: These findings establish TOPK as a central regulator of solar UV-induced skin carcinogenesis, partially via modulation of IL19 signaling and fibroblast activation. Targeting TOPK may offer a novel strategy for the prevention and treatment of NMSC. Full article

Recurrent catastrophic inverter failures significantly undermine the reliability and economic viability of utility-scale photovoltaic (PV) power plants. This paper presents a comprehensive investigation of severe inverter destruction incidents at the Kopli Solar Power Plant, Estonia, by integrating controlled laboratory simulations with extensive field monitoring. Initially, detailed laboratory experiments were conducted to replicate critical DC-side short-circuit scenarios, particularly focusing on negative DC input terminal faults. The results consistently showed these faults rapidly escalating into multi-phase short-circuits and sustained ground-fault arcs due to inadequate internal protection mechanisms, semiconductor breakdown, and delayed relay response. Subsequently, extensive field-based waveform analyses of multiple inverter failure events captured identical fault signatures, thereby conclusively validating laboratory-identified failure mechanisms. Critical vulnerabilities were explicitly identified, including insufficient isolation relay responsiveness, inadequate semiconductor transient ratings, and ineffective internal insulation leading to prolonged arc conditions. Based on the validated findings, the paper proposes targeted inverter design enhancements—particularly advanced DC-side protective schemes, rapid fault-isolation mechanisms, and improved internal insulation practices. Additionally, robust operational and monitoring guidelines are recommended for industry-wide adoption to proactively mitigate future inverter failures. The presented integrated methodological framework and actionable recommendations significantly contribute toward enhancing inverter reliability standards and operational stability within grid-connected photovoltaic installations. Full article