Search Results (3,113)

Wet cracks caused by leakage often exhibit visual and structural distortions due to surface contamination, salt crystallization, and corrosion byproducts. These factors significantly degrade the performance of sensor- and vision-based crack detection systems. In moist environments, the initiation and propagation of cracks tend to be highly nonlinear and irregular, making it challenging to distinguish crack regions from the background—especially under visual noise such as reflections, stains, and low contrast. To address these challenges, this study proposes a segmentation framework that integrates a dedicated preprocessing pipeline aimed at suppressing noise and enhancing feature clarity, all without altering the underlying segmentation architecture. The pipeline begins with adaptive thresholding to perform initial binarization under varying lighting conditions. This is followed by morphological operations and connected component analysis to eliminate micro-level noise and restore structural continuity of crack patterns. Subsequently, both local and global contrast are enhanced using histogram stretching and contrast limited adaptive histogram equalization. Finally, a background fusion step is applied to emphasize crack features while preserving the original surface texture. Experimental results demonstrate that the proposed method significantly improves segmentation performance under adverse conditions. Notably, it achieves a precision of 97.5% and exhibits strong robustness against noise introduced by moisture, reflections, and surface irregularities. These findings confirm that targeted preprocessing can substantially enhance the accuracy and reliability of crack detection systems deployed in real-world infrastructure inspection scenarios. Full article

Vitiligo is an acquired depigmentation disorder characterized by the selective destruction of melanocytes, resulting in the progressive loss of pigment in the skin and hair. This condition frequently leads to significant psychological distress. Its pathogenesis is complex and multifactorial, involving a combination of genetic susceptibility, metabolic derangement related to oxidative stress, defective melanocyte adhesion to the basal epidermis, and dysregulated innate and adaptive immune responses, ultimately converging in the targeted elimination of melanocytes. Despite the availability of several therapeutic modalities, current corrective options are often limited in efficacy and are associated with high relapse rates. There remains a pressing need for novel, safe, and more effective therapeutic strategies to improve patients’ quality of life. Growing evidence indicates that the immune system plays a pivotal role in vitiligo onset and progression, as most triggers converge on inflammatory and autoimmune pathways targeting melanocytes. However, immunosuppressive therapies alone have shown limited effectiveness in halting disease progression and achieving lasting repigmentation. Targeting only immunological processes without addressing the underlying triggers of their activation likely represents a significant limitation in restoring pigmentation. In contrast, interventions aimed at upstream events may help prevent the initiation of the immune response. Consequently, combinatorial therapeutic approaches that target multiple pathogenic pathways and incorporate diverse pharmacological agents are being explored to improve clinical outcomes. This review aims to re-evaluate the intrinsic cellular abnormalities and associated dysregulated signaling pathways in vitiligo, with the goal of identifying novel, effective, nonimmunological treatment strategies. Full article

The safe and effective operation of labs is essential for the sustainable development of universities and academies. However, due to the need for more experience in lab management to eliminate safety risks, it is primarily necessary to solve the problem of inadaptability caused by the simple application of other industry management models. According to the comprehensive survey research on the current management status of chemical labs, this paper explores a new sustainable safety management system based on the trajectory intersecting model. This work established a hierarchical model that includes the layers of base, analysis, control, and goal to systematically analyze the safe operation of chemical labs and identify hazards and related evolving potential accidents. Then, multiple targeted suggestions for practical system applications are formulated and continuously acted upon until the development of the hazard has halted. The results of this study could establish a sustainable safety-protecting shell for chemical labs through step-by-step promotion and optimization feedback between layers. Thus, the chemical lab management will achieve its safety target more effectively. Finally, these findings have implications for improving the existing chemical lab management model and quality. Full article

As a high-frequency and essential type of special electromechanical equipment, a vertical elevator has a significant societal implication for their safe operation. The load-weighing module, serving as the core component for overload warning, is susceptible to precision degradation due to the nonlinear deformation of rubber buffers installed at the base of the elevator car. This deformation arises from the coupled effects of environmental factors such as temperature, humidity, and material aging, leading to potential safety risks including missed overload alarms and false empty status detections. To address the issue of accuracy deterioration in elevator load-weighing systems, this study proposes an online self-calibration method based on multimodal information fusion. A reference detection model is first constructed to map the relationship between applied load and the corresponding relative compression of the rubber buffers. Subsequently, displacement data from a draw-wire sensor are integrated with target detection model outputs, enabling real-time extraction of dynamic rubber buffers’ deformation characteristics under empty conditions. Based on the above, a displacement-based compensation term is derived to enhance the accuracy of load estimation. This is further supported by a dynamic error compensation mechanism and an online computation framework, allowing the system to self-calibrate without manual intervention. The proposed approach eliminates the dependency on manual tuning inherent in traditional methods and forms a highly robust solution for load monitoring. Field experiments demonstrate the effectiveness of the proposed method and the stability of the prototype system. The results confirm that the synergistic integration of multimodal perception and adaptive calibration technologies effectively resolves the challenge of load-weighing precision degradation under complex operating conditions, offering a novel technical paradigm for elevator safety monitoring. Full article

Macrophages are essential for immune homeostasis, playing crucial roles in immune responses from initiation to resolution. They trigger acute inflammation to promote elimination of pathogens and regulate excessive immune reactions to prevent chronic inflammation and autoimmune diseases. Consequently, macrophage dysfunction contributes to the progression of many disorders that involve inflammation. Cannabinoid Receptor 2 (CB2) has emerged as a promising therapeutic target due to its role in regulating macrophage-mediated immune functions, including via modulation of cytokine secretion, migration, phagocytosis, and polarisation. CB2 activation can produce beneficial outcomes via suppressing macrophage-mediated inflammatory pathways in animal models for various diseases that involve acute or chronic central or peripheral inflammation, whereas blocking CB2 may have utility when macrophage polarisation to a “resolving” phenotype is deleterious, such as in tumour-associated macrophages. However, despite abundant promising preclinical results, the relatively few CB2-selective agonists tested in clinical trials to date have exhibited limited efficacy. Here, we provide an overview of the roles of macrophages in health and disease, thoroughly review in vitro and in vivo preclinical findings on CB2-mediated modulation of macrophage function, summarise current progress in clinical trials for CB2-targeted compounds, and discuss approaches for addressing current challenges in ongoing efforts toward developing safe and effective CB2-targeted therapeutics. Full article

To address the challenges of dynamic coupling interference and time-frequency feature degradation in current approaches to Ultra-High-Frequency Radio-Frequency Identification (UHF RFID) behavior recognition, this study proposes a novel behavior recognition method integrating multi-feature analysis with a dual-path residual network. The proposed method mitigates interference by using phase difference methods to eliminate signal errors and cross-correlation, as well as adaptive equalization algorithms to decouple interfering signals. To identify the target tags participating in behavioral interactions, we construct a three-dimensional feature space and apply an improved weighted isolated forest algorithm to detect active tags during interactions. Subsequently, Doppler shift analysis extracts behavioral features, and multiscale wavelet-packet decomposition generates time-frequency representations. The dual-path residual network then fuses global and local features from these time-frequency representations for behavioral classification, thereby identifying interaction behaviors such as ‘taking away’, ‘putting back’, and ‘hesitation’ (characterized by picking up, then putting back). Experimental results demonstrate that the proposed scheme achieves behavioral recognition accuracy of 94% in complex scenarios, significantly enhancing the overall robustness of interaction behavior recognition. Full article

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) encompasses a spectrum of liver conditions and involves gut–liver axis crosstalk. We aimed to evaluate whether oral vancomycin modifies liver injury and the cecal microbiota in a methionine–choline-deficient (MCD) diet model of NASH. Male C57BL/6J mice (n = 28) were block-randomized to four groups (n = 7 each) for 10 weeks: standard diet (STD); MCD diet; STD + vancomycin (VANC); and MCD + VANC (2 mg/mouse ≈ 50 mg/kg, every 72 h). After 10 weeks, liver tissues were analyzed for histological changes, cytokine levels [interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor beta 1 (TGF-β1)], and immunohistochemical markers [ubiquitin and cytokeratin 18 (CK18)]. Cecal microbiota composition was evaluated with 16S ribosomal RNA (rRNA) sequencing. The MCD reproduced key NASH features (macrovesicular steatosis, lobular inflammation). Vancomycin shifted steatosis toward a microvesicular pattern and reduced hepatocyte injury: CK18 and ubiquitin immunoreactivity were decreased in MCD + VANC vs. MCD, and hepatic IL-8 and TGF-β1 levels were lower in MCD + VANC vs. STD. Taxonomically, STD mice had Lactobacillus-rich microbiota. The MCD diet alone reduced alpha diversity (α-diversity), modestly lowered Firmicutes and increased Desulfobacterota/Fusobacteriota. Vancomycin alone caused a much larger collapse in richness, depleting Gram-positive commensals and promoting blooms of Escherichia–Shigella, Klebsiella, Parabacteroides, and Akkermansia. In the MCD + VANC group, vancomycin profoundly remodeled the microbiota, eliminating key commensals (e.g., Lactobacillus) and enriching Desulfobacterota, Fusobacteriota, and Campylobacterota. Oral vancomycin in the MCD model of NASH improved liver injury markers and altered steatosis morphology, but concurrently reprogrammed the gut into a low-diversity, pathobiont-enriched ecosystem with near-loss of Lactobacillus. These findings highlight a therapeutic trade-off—hepatic benefit accompanied by microbiome cost—that should guide microbiota-targeted strategies for NAFLD/NASH. Full article

Small targets in drone imagery are often difficult to accurately locate and identify due to scale imbalance and limitations, such as pixel representation and dynamic environmental interference, and the balance between detection accuracy and resource consumption of the model also poses challenges. Therefore, we propose an interpretable computer vision framework based on YOLOv12m, called LCW-YOLO. First, we adopt multi-scale heterogeneous convolutional kernels to improve the lightweight channel-level and spatial attention combined context (LA2C2f) structure, enhancing spatial perception capabilities while reducing model computational load. Second, to enhance feature fusion capabilities, we propose the Convolutional Attention Integration Module (CAIM), enabling the fusion of original features across channels, spatial dimensions, and layers, thereby strengthening contextual attention. Finally, the model incorporates Wise-IoU (WIoU) v3, which dynamically allocates loss weights for detected objects. This allows the model to adjust its focus on samples of average quality during training based on object difficulty, thereby improving the model’s generalization capabilities. According to experimental results, LCW-YOLO eliminates 0.4 M parameters and improves mAP@0.5 by 3.3% on the VisDrone2019 dataset when compared to YOLOv12m. And the model improves mAP@0.5 by 1.9% on the UAVVaste dataset. In the task of identifying small objects with drones, LCW-YOLO, as an explainable AI (XAI) model, provides visual detection results and effectively balances accuracy, lightweight design, and generalization capabilities. Full article

Congenital ichthyoses, now grouped under the acronym EDD (Epidermal Differentiation Disorders), include nonsyndromic forms (nEDD) that may be caused by loss-of-function mutations in the CDSN gene encoding corneodesmosin (CDSN-nEDD, formerly Peeling skin syndrome type 1). It is characterized by skin peeling, inflammation, itching and food allergies, while no specific therapy is currently available. High levels of KLK5, the serine protease that initiates the desquamation cascade, are found in the epidermis of CDSN-nEDD patients. Thus, we hypothesized that KLK5 inhibition would alleviate the symptoms of CDSN-nEDD and could serve as a new pharmacological target. A human epidermal equivalent (HEE) model for CDSN-nEDD was developed using shRNA-mediated CDSN knockdown. This model was characterized and used to assess the role of KLK5 knockdown on CDSN-nEDD. Also, Klk5^−/− mice were crossed with Cdsn^epi−/− mice, the murine model of CDSN-nEDD, to examine in vivo the effect(s) of Klk5 deletion in CDSN-nEDD. Both models recapitulated the CDSN-nEDD desquamating phenotype. Elimination of KLK5 aggravated the CDSN-nEDD phenotype. Epidermal proteolysis was surprisingly elevated, while severe ultrastructural (corneo)desmosomal alterations increased epidermal barrier permeability and stratum corneum detachment was manifested. Based on these results, we concluded that targeting epidermal proteolysis with KLK5 ablation cannot compensate for the loss of corneodesmosin and rescue over-desquamation of the CDSN-nEDD. Possibly, in the absence of KLK5, other proteases take over which increases the severity of over-desquamation in CDSN-nEDD. The translational outcome is that over-desquamation may not always be rescued by eliminating epidermal proteolysis, but fine protease modulation is more likely required. Full article

This paper presents the design of a permanent-magnet-assisted synchronous reluctance motor (PMa-SynRM) for compressor applications using Sm-series injection-molded magnets that eliminate heavy rare-earth elements. The high shape flexibility of the injection-molded magnets enables the formation of a curved multi-layer flux-barrier rotor geometry based on the Joukowski airfoil potential, optimizing magnetic flux flow under typical compressor operating conditions. Furthermore, electromagnetic performance, irreversible demagnetization behavior, and rotor stress sensitivity were analyzed with respect to key design variables to derive a model that satisfies the target performance requirements. The validity of the proposed design was confirmed through finite element method (FEM) comparisons with a conventional IPMSM using sintered NdFeB magnets, demonstrating the feasibility of HRE-free PMa-SynRM for high-performance compressor drives. Full article

Alkaline pectate lyases hold significant promise for various industrial applications, including the degumming processes in papermaking and textiles. In this study, a novel pectinase, PelA, derived from a strain of Paenibacillus borealis, was characterized both at the molecular level and through enzymatic analysis. This enzyme represents a distinct cluster diverging from the well-characterized Bacillus pectinases and exhibits molecular activity under alkaline conditions, with an optimal pH of 9.5. It can be classified as an endo-(1,4)-pectate lyase, capable of cleaving the α-1,4 glycosidic bonds of polygalacturonic acid via a trans-elimination mechanism. Notably, the addition of the metal ion Ca²⁺ did not enhance enzyme activity. To achieve high-level secretory expression and improve its economic viability for bioapplications, the gene copy number of pelA in the host genome was increased by constructing tandem pelA gene expression cassettes. Following optimization of cultivation conditions and monitoring of cell growth, the recombinant strain harboring the multi-copy pelA gene attained an expression level of 7520 U/mL in a bioreactor. This study successfully achieved high-level secretory expression of an alkaline pectinase, thereby enhancing its potential for industrial bioapplications and providing a reference for future research on the heterologous expression of target genes. Full article

In equipment health management, inefficient key feature selection and model overfitting caused by data scarcity in small-sample scenarios severely restrict the practical applications of predictive maintenance technologies. To address this challenge, this study proposes an improved key feature selection method integrating dynamic particle swarm optimization (PSO) and cross-domain transfer learning. First, principal component analysis (PCA) is employed for the dimensionality reduction of high-dimensional health-related features. An improved PSO algorithm is then used to dynamically optimize XGBoost hyperparameters, coupled with a recursive feature elimination (RFE) framework to screen for key features. A hierarchical transfer strategy is then introduced to address small-sample data limitations in the target domain via source domain knowledge transfer, achieving cross-domain feature space alignment and model parameter fine-tuning. Experiments on the UCI bearing dataset demonstrated that the proposed model achieved a 9% improvement in the classification F1-score, a 60% reduction in overfitting and a 24% increase in the feature selection overlap rate compared to traditional methods in small-sample scenarios. Full article

Indonesia’s power sector is heavily reliant on coal, making it a major contributor to greenhouse gas (GHG) emissions. This study evaluates the role of carbon capture (CC) as a transitional mitigation strategy using the Low Emissions Analysis Platform (LEAP) for least-cost optimization. Five scenarios up to 2060 are assessed: Business as Usual (BAU), a renewables-only pathway (NRE), two carbon-capture strategies (CALL and CNEW), and a hybrid scenario (COMB). Results show that NRE eliminates fossil power plants but increases system costs by 3.2% and raises reliability challenges due to the variability of solar generation. CALL achieves the lowest abatement cost (USD 0.93/tCO₂e) but leaves 105 Mt CO₂e residual emissions by 2060. COMB provides the most balanced outcome, cutting emissions by 96% (40 Mt CO₂e), increasing costs by only 1.9%, and ensuring energy security by combining CC with renewable expansion. These findings highlight that a hybrid strategy offers a pragmatic, least-cost pathway for Indonesia to align its power sector with net-zero targets while maintaining grid adequacy. Full article

Background/Objectives: Interleukin-33 (IL-33) is crucial in immune-mediated diseases like asthma. Targeting the IL-33/ST2 pathway holds therapeutic promise. This study characterized the pharmacokinetics (PK) and metabolism of KB-1517 and KB-1518, new oxazolo[4,5-c]quinoline IL-33 inhibitors. Methods: PK studies were conducted in male ICR mice following intravenous (IV) and oral (PO) administration. In vitro metabolic stability and metabolite identification were assessed using human and mouse liver S9 fractions supplemented with cofactors (NADPH, UDPGA, PAPS, GSH). Plasma and incubation samples were analyzed using validated LC-MS/MS methods. Results: KB-1517 exhibited slow absorption/elimination and high apparent oral bioavailability (>100%) post-PO, with an unusually late increase in plasma concentration after IV dosing, hindering terminal parameter calculation. KB-1518 showed low clearance post-IV but suffered from low oral bioavailability (~14%). Both compounds demonstrated high in vitro metabolic stability (t_½ > 60 min) in both human and mouse liver S9 fractions. Primary metabolism involved phase I oxidation (N-oxidation and N-demethylation), yielding several metabolites identified in vitro and confirmed in vivo. Some species differences in metabolite profiles were observed. Conclusions: KB-1517 and KB-1518 are promising, metabolically stable IL-33 inhibitor lead compounds with distinct PK profiles. KB-1517’s complex kinetics suggest potential sustained exposure but require further elucidation. KB-1518’s low oral bioavailability necessitates further optimization. These ADME findings provide a critical foundation for their continued optimization and development. Full article

Introduction: Eliminating mother-to-child transmission (EMTCT) of HIV is a global health priority to ensure that no child is born with HIV. When EMTCT services are underutilized, mothers and babies face greater risks, including the vertical transmission of HIV and higher rates of maternal and neonatal mortality. Despite ongoing efforts, many women worldwide still struggle to access and use these vital services. Objective: This study sought to explore barriers and facilitators to the elimination of mother-to-child transmission services among pregnant and breastfeeding women (PBFW) in Gauteng province, South Africa. Methods: A qualitative, explorative, and descriptive research design was used. Convenience and purposive sampling were used to select participants. The study population consisted of PBFW aged 18 years or above who were utilizing EMTCT services. Data was collected through in-depth face-to-face individual interviews with participants. A semi-structured interview guide was used to collect data until data saturation was reached after interviewing 25 participants. Data were analyzed using thematic analysis (Tesch’s open coding method). Trustworthiness and ethical principles were ensured. Results: Four main themes emerged from the data analyzed, namely, barriers associated with EMTCT service utilization, facility-based strategies to improve EMTCT service uptake, community support for enhancing EMTCT engagement, and the role of partner support in service utilization, each with linked sub-themes. This study found that health education about EMTCT, along with community awareness and involvement, encourages the target group to utilize these services. Conclusions: Increasing women’s use of EMTCT services is an important step toward eliminating MTCT and increasing the health and well-being of mothers and their children. Addressing numerous barriers to receiving these services, as well as implementing targeted measures, can help ensure that all women gain access to the care and support that they require to safeguard their families from HIV. Full article