Abstract: Nine activated carbons (ACs) with hierarchical micro- and mesoporous textural structures and varied chemical compositions were evaluated as metal-free electrocatalysts for the Oxygen Reduction Reaction (ORR) under alkaline conditions. The base material was a commercial biomass-based carbon chemically activated with H3PO4, which possesses a hierarchical micro- and mesoporous structure. This material was modified by: oxidative treatment with HNO3 to increase the content of acidic oxygenated functional groups (OFGs); and by heat treatment in an inert atmosphere up to 800 °C to remove most of the acidic OFGs. Furthermore, the original and modified ACs were subjected to ammonization up to 400 or 800 °C to incorporate nitrogen. The results showed that there exists a synergistic effect among at least three critical factors that enhance the ORR performance of the materials: a high specific surface area (SSA); a high electrical conductivity (achieved by means of a well-developed carbon basal plane structure); and the presence of functional groups containing heteroatoms, mainly aromatic nitrogens. Notably, the ACs exhibited high tolerance to methanol crossover. Finally, as a proof-of-concept, a selected AC was tested in a single-cell Direct Methanol Fuel Cell (DMFC), yielding excellent performance. The results demonstrate the high potential of N-doped ACs as electrocatalysts, inexpensive and versatile materials that can replace costly Pt-based electrodes.

Abstract: The oral cavity is the second most diverse microbial ecosystem providing residency to AMP producers which play a significant role in shaping the community structure and preserving the delicate equilibrium between the host and the residential microbial flora. The integration of AMPs in the microbial membranes can disrupt the membrane structure, eventually causing cellular death. On the other hand, the permeabilization of the membrane allows for AMP leakage into the cytoplasm, where it can bind to nucleic acids and cellular components to disrupt the normal functioning of the microbial metabolism. Production of bacteriocins among oral bacteria has been commonly found in of the genera Streptococcus, Lactobacillus, Fusobacterium, and Prevotella. Furthermore, many of these have probiotic potential. Bacteriocins have been explored as alternatives to antibiotics for combating cariogenic species. For instance, the lantibiotic nisin has shown effectiveness in vitro against mono-species biofilms of Streptococcus mutans. Among the late colonizers studied, Porphyromonas gingivalis, Prevotella intermedia, Treponema denticola, and Aggregatibacter actinomycetemcomitans were particularly sensitive to nisin. Furthermore, when cultured in the presence of nisin, multispecies biofilms showed a reduction in biomass and thickness. Through further advancements and collaborations between researchers, healthcare professionals, and industry partners, we can harness the power of these naturally occurring molecules to develop innovative therapies that effectively combat infections and enhance human health.

Abstract: Determining the solution set of a system of linear interval equations is often a difficult task. Establishing such a theory, which should include the theory of classical systems of linear equations in a special case, opens the door to a very comprehensive and arduous work. In this study, we tried to develop information about the solution sets of such equation systems by using the known quasilinear space concept. First of all, we defined the determinant of an interval matrix as an interval and its rank as a pair of natural numbers. Then, we introduced the quasi-inverse concept for interval matrices and obtained some results based on this. With the help of our results, we proved a theorem that we call the Interval-Cramer's rule regarding the solution of some linear interval equation systems. In addition, regarding the existence of solutions to this type of equations, we give a theorem regarding the rank of the interval matrix that models the equation.

Abstract: The 5th Generation New Radio (5G NR) evolution has mainly been focused on three pillars: enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), and massive Machine-Type Communications (mMTC). While eMBB and URLLC focus on high-performance applications and mMTC cater for low-power and low-throughput massive IoT, a considerable void has appeared in price performance ratio for mid-level IoT use cases. Examples of such use cases include industrial sensors, wearables, and video surveillance, all of which call for more than conventional mMTC technologies such as NB-IoT and LTE-M can offer but do not need the full and usually expensive complexity of eMBB/URLLC devices. To bridge this gap, Release 17 introduced Reduced Capability (RedCap) NR, with Release 18 further enhancing it. This survey systematically reviews 5G RedCap technology. It initially gives an account of the cellular IoT landscape, setting the agenda of the unique niche RedCap fills. A thorough technical dive into Release 17 and 18 core specifications then follows, highlighting the key methods of reducing complexity: bandwidth reduction, reduced antenna configurations, half-duplex FDD operation, and power-saving enhancements. This paper further explores the architectural impacts on the 5G network, such as BWP operation, and initial access procedures. Then detailed analyses that relate RedCap features to specific application requirements for industrial IoT, wearables, and smart cities are offered. Performance data from academia and industry reports are consolidated in this survey to give a quantitative comparison of RedCap against other cellular technologies in specific KPIs. Finally, deployment challenges are outlined, a bibliometric analysis of the current research landscape is undertaken, and concrete future directions are proposed to pave the way for further development of this important 5G IoT technology.

Abstract: The increasing demand for permanent post-disaster housing highlights the need for rapid and high-quality construction methods. This study investigates the feasibility of prefabri-cated modular façade systems in accelerating post-disaster permanent housing construc-tion, while maintaining cost efficiency and construction quality. A mixed-methods ap-proach was adopted: semi-structured interviews were conducted with 15 industry stake-holders, and thematic analysis was applied to extract qualitative insights. Subsequently, a quantitative survey involving 366 construction professionals was carried out and statisti-cally analyzed to validate the findings. Additionally, case studies from previous post-disaster reconstruction efforts were reviewed to contextualize the results. The find-ings reveal that prefabricated modular façade systems significantly reduce on-site con-struction time and overall project duration, minimize material waste, and uphold high construction standards. Most participants also noted quality control benefits inherent to factory-based production. However, the study identifies several limitations, including challenges related to cost, logistics, and workforce training. The research contributes to the evolving discourse on disaster-responsive housing policies and provides strategic rec-ommendations to enhance the adoption of modular façade technologies in construction practices.

Abstract: Growing global awareness of climate change and environmental protection has fueled the rapid expansion of the green bond market. Building upon a theoretical framework that links green bond issuance to corporate governance and green innovation effects, this study employs a sample of Chinese A-share listed firms from 2014 to 2022 and applies a staggered difference-in-differences (DID) approach to empirically examine the impact of green bond issuance on corporate risk-taking and the underlying mechanisms. The results indicate that green bond issuance significantly reduces firms’ risk-taking levels. This effect operates primarily through three channels: increasing agency costs, enhancing information transparency, and exacerbating structural imbalances in green innovation. Furthermore, the risk-mitigating effect of green bonds is more pronounced in state-owned enterprises, firms with low audit quality, and firms operating in heavily polluting industries. These findings offer important implications for accelerating the diversification of China’s green financial system, improving firms’ risk management capabilities, and fostering the development of green productivity.

Abstract: Simulations of intermediate-mass black holes (IMBHs) in dwarf galaxies within 10 Mpc that host bright nuclear star clusters (NSCs), prime candidates for IMBH formation, using the High Angular Resolution Monolithic Optical and Near-infrared Integral (HARMONI) field spectrograph on the Extremely Large Telescope probes black hole formation in the early Universe. Our approach combines observed surface brightness profiles from the Hubble Space Telescope (HST), synthetic stellar population spectra, and Jeans Anisotropic Modeling (JAM) for stellar dynamics. Mock HARMONI observations were generated with the HSIM simulator and analyzed in a Bayesian framework to infer IMBH masses down to 0.5% of the NSC mass. In this work, we extend these simulations by constructing improved stellar-mass models using SimCADO to simulate imaging with the Multi-AO Imaging Camera for Deep Observations (MICADO). The MICADO data are jointly analyzed with HARMONI kinematics via JAM to reassess IMBH masses and uncertainties. This combined framework enables us to examine how variations in the NSC inner surface-brightness slope influence IMBH mass estimates, providing tighter constraints on low mass black holes and advancing models for IMBH detection in NSCs.

Abstract: Objective: To address the bottleneck of natural bias in the determination of plant-derived food materials, which relies on experience and lacks quantitative standards in traditional Chinese medicine (TCM) diet therapy and TCM prescription application, this study aimed to construct a standardized application system for the natural bias of plant-derived food materials on the basis of the three-dimensional quantitative evaluation system previously published by our team.Methods: Relying on the three-dimensional quantitative framework of "environmental habits--metabolic characteristics--growth cycle" [11], combined with natural bias data from 417 daily plant-derived food materials and 570 Chinese medicinal materials (a total of 987 species), the practicality and reliability of the system were verified in three core scenarios: daily diet therapy, the quantification of TCM prescriptions, and the directional cultivation of plants.Results: The system could realize multifactor dynamic adaptation of "constitution-season-region" in daily diet therapy, support the quantitative compatibility of "safety-intensity-time-effect" for TCM prescriptions, and directionally regulate the nature bias and core components of plant-derived food materials. These rules are consistent with traditional classic records and clinical application experience, demonstrating the ability to regulate stable nature bias.Limitations: This study has not yet established a dose‒effect relationship between nature bias quantification and clinical efficacy in plant directional cultivation, and the adaptability to extreme scenarios such as deep-sea and genetically modified materials needs further exploration.Conclusions: The three-dimensional quantitative system of "environmental habits--metabolic characteristics--growth cycle" provides an innovative framework for the standardized application of the natural bias of plant-derived food materials. It can support precise diet therapy, optimization of TCM prescriptions, and directional cultivation of food materials, promoting the transformation of plant-derived food material-related applications from experience-driven to scientifically standardized.

Abstract: With the rise of Industry 4.0, Augmented Reality (AR) has become pivotal for human-robot collaboration. However, most industrial AR systems still rely on pre-defined tracked images or markers, limiting adaptability in unmodeled or dynamic environments. This paper proposes a novel Interactive Semantic-Augmented Reality (ISAR) framework that synergizes Edge AI and Cloud Vision-Language Models (VLMs). To ensure real-time performance, we implement a Dual-Thread Asynchronous Architecture on the robotic edge, decoupling video streaming from AI inference. We introduce a Confidence-Based Triggering Mechanism, where a cloud-based VLM is invoked only when edge detection confidence falls below a specific threshold. Instead of traditional image cropping, we employ a Visual Prompting strategy—overlaying bounding boxes on full-frame images—to preserve spatial context for accurate VLM semantic analysis. Finally, the generated insights are anchored to the physical world via Screen-to-World Raycasting without fiducial markers. This framework realizes a semantic-aware 'Intelligent Agent' that enhances Human-in-the-Loop (HITL) decision-making in complex industrial settings.

Abstract: Groundwater resources in semi-arid and industrial regions are increasingly threatened by unsustainable extraction, groundwater contamination, and climate-induced variability. Tiruppur District in Tamil Nadu, India, represents a critical case where rapid industrial growth, intensive agricultural activity, and changing climatic patterns have resulted in severe groundwater stress. This study proposes a hybrid artificial intelligence–based framework for the assessment and forecasting of groundwater levels and quality under climate change conditions. The framework integrates multi-source datasets comprising historical groundwater level records (1994–2024), groundwater quality parameters, and meteorological data. To address the non-stationary nature of hydrological time series, Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and Variational Mode Decomposition (VMD) are employed prior to model training. Deep learning models, including Slime Mould Algorithm–optimized Long Short-Term Memory (SMA–LSTM) networks and CNN–LSTM hybrids, are developed to capture temporal and spatial dependencies. An Adaptive Weighting Model is used to ensemble predictions and improve robustness. Model performance is evaluated using Mean Absolute Error, Root Mean Square Error, Coefficient of Determination, and Nash–Sutcliffe Efficiency. The proposed ensemble framework demonstrates superior predictive accuracy, achieving an R² value of 0.948 and an NSE of 0.938. The results confirm the effectiveness of hybrid deep learning approaches for climate-resilient groundwater management and highlight their scalability to other water-stressed regions.

Abstract: Background. A large proportion of people with obsessive–compulsive disorder (OCD) – roughly 40–60 % even after carefully optimised treatment – do not improve enough with selective serotonin re-uptake inhibitors (SSRIs). Small naturalistic series have suggested that the Cheung Glutamatergic Regimen (CGR), an inexpensive oral combination of dextromethorphan, fluoxetine and piracetam, can ease symptoms quickly. Because CGR acts on synaptic plasticity rather than pure serotonin tone, we asked whether common genetic risk for OCD is concentrated in the same plasticity pathway.Methods. Summary statistics from the 2025 OCD genome-wide association study (23 493 cases and 1 114 613 controls of European ancestry, 23andMe data excluded) were analysed with MAGMA v1.10. Single-nucleotide polymorphisms (SNPs) were mapped, with a 10 kb margin, to 22 genes chosen a priori: NMDA and AMPA receptor subunits, metabolic targets, and six downstream plasticity genes. Two custom sets were evaluated – a "pro-plasticity" group (BDNF, NTRK2, MTOR, AKT1, CREB1, ARC) and an "anti-plasticity" single-gene set (PTEN). The lead SNP was annotated for expression and splicing effects through Open Targets Genetics.Results. Among the 22 candidates, CREB1 stood out (Z = 2.857; p = 0.00214), passing Bonferroni correction for the panel. BDNF (p = 0.058) and PTEN (p = 0.078) showed suggestive but non-significant signals, whereas all NMDA/AMPA receptor genes and metabolic loci (CYP2D6, SIGMAR1) were clearly null (p > 0.10). The top variant, rs7591784 (p = 1.17 × 10⁻⁷), alters CREB1 transcript usage in multiple tissues. Set-based enrichment for the six pro-plasticity genes was not significant (β = 0.167; p = 0.321), reflecting the fact that most of the signal lay in CREB1 alone.Conclusion. Common OCD risk is disproportionately centred on CREB1, a transcription factor that drives long-term synaptic change, rather than on the glutamate receptors that lie upstream. This genetic pattern lends biological weight to the reported clinical benefit of CGR: by delivering a rapid, AMPA-mediated calcium surge, the regimen may compensate for genetically weakened CREB1 activity and sidestep the comparatively weak serotonergic cascade of SSRIs. Prospective trials that stratify patients by CREB1 risk status are warranted, and transcriptional plasticity emerges as an appealing target for new treatments in refractory OCD.

Abstract: In this paper, we presented BlockShare, a blockchain-basedsystem developed to facilitate privacy-preserving data sharing across de-centralized networks. The proposed system enables users to retain controlover their sensitive data while enabling secure, verifiable sharing with au-thorized parties. We implemented an authenticated data structure (ADS)to support decentralized verification and utilized zero-knowledge proofmechanisms to validate conditions without exposing the underlying data.Experimental analysis demonstrated that BlockShare performs efficientlyin constructing data structures, generating proofs, and verifying themwith minimal computational overhead. The platform successfully reducedprivacy risks and enhanced trust in cross-organization data exchanges.

Abstract: The determination of the actual series and sequence impedances, including the reduction factor of a certain HV or EHV distribution cable line, as well as the resulting screening factor of its sheaths and surrounding metal installations, including its inductive influence on any of the surrounding metal installations, is not possible by calculations alone. Considering the inductive influence of surrounding metal installations on the values of these quantities is possible only by the method that includes the test measurements during a simulated ground fault in the supplied substation. However, such measurements presuppose putting at least one HV substation and its feeding line out of service. That is why electricity distribution companies rarely allow such measurements, i.e., only immediately before the commissioning of a newly built HV substation or during a periodical overhaul. In this paper, it is demonstrated that these characteristics of cable lines can also be determined based on the results of synchronous measurements performed permanently in the substations at their ends. In this way, the need to perform a simulated ground fault and corresponding test measurements in HV distribution substations is practically disаpear, and the necessary characteristics can be obtained whenever a need for them appears.

Abstract: Background: Cardiogenic pulmonary edema (CPE) is a severe manifestation of acute heart failure (AHF), typically driven by elevated left ventricular (LV) filling pressures. While LV dysfunction has been the traditional focus, growing evidence highlights the role of right ventricular (RV) impairment and biventricular interaction in the pathophysiology and prognosis of AHF. Objectives: To characterize the clinical and echocardiographic profile of patients presenting with CPE and to assess the comparative prognostic contribution of LV and RV function to in-hospital outcomes. Methods: We retrospectively analyzed 28 patients with CPE from a larger AHF registry, excluding those with incomplete echocardiographic data or missing NT-proBNP measurement. Comprehensive echocardiographic assessment at admission included TAPSE, S RV, RV–RA gradient, LVEF, LVOT VTI, S LV, and E/E′ ratio. Clinical variables, NT-proBNP levels, and in-hospital outcomes (mortality, ventilation, inotropic support, ICU stay) were recorded. Group comparisons, correlation analyses, and ROC curve assessments were performed.Results: The mean S LV was significantly lower than S RV (7.34 ± 2.38 cm/s vs. 11.49 ± 2.70 cm/s; p < 0.001), indicating predominant LV longitudinal systolic impairment. Four patients (14.3%) died during hospitalization. No echocardiographic parameter reached statistical significance for predicting mortality. Patients with higher mitral E velocity and reduced LV systolic velocities tended to have longer ICU hospitalization.Trends toward lower S RV and higher S LV/S RV ratio were noted in patients requiring inotropes.Conclusions: In CPE, LV longitudinal systolic function is more impaired than RV function at presentation. While single echocardiographic indices lacked strong prognostic discrimination in this small cohort, integrated assessment of LV and RV systolic performance alongside diastolic filling pressures may improve early risk stratification. These findings align with the conceptual framework of composite prognostic tools and warrant validation in larger prospective studies.

Abstract:

Medicinal plants have become increasingly important due to the diversity and bactericidal potential of many species. They can work as an alternative to the use of antimicrobials in the treatment of bacterial infections, which may represent impairment to health. Considering the importance of alternative compounds, we aimed to evaluate the antimicrobial activity in vitro of medicinal plants Stryphnodendron adstringens (Mart.) Coville, known as barbatimão, Baccharis crispa Spreng, known as carqueja and Azadiractha indica, known as neem. S. adstringens and B. crispa were used as extract and obtained from plants collected in the municipality of Bambuí, state of Minas Gerais, Brazil. A. indica was evaluated as extract and oil, and the crushed leaves and oil were purchased from a commercial company. Antimicrobial activity was determined by the minimum bactericidal concentration (MBC) test against Staphylococcus aureus, Streptococcus agalactiae, Streptococcus uberis, Escherichia coli, and Salmonella spp, isolated from bovine mastitis. The bacteria were submitted to the MBC test at concentrations of 100, 50, 25, 12.5, 6.25, 3.12, 1.56, 0.78, 0.39, 0.19 and 0.09 mg/mL. The bacteria evaluated were sensitive to most plant extracts for at least one of the concentrations evaluated, except for Gram-negative bacteria, Escherichia coli, and Salmonella spp. There was no activity of B. crispa extract and A. indica against E. coli and neither of A. indica extract against Salmonella spp. even at the highest concentration evaluated. S. adstringens was considered the extract with the highest activity against the bacteria evaluated and S. uberis the most susceptible to antimicrobial action. The results indicate the antimicrobial activity of the compounds and a possible application of these for the development of biotechnological products against the main bacteria causing bovine mastitis, becoming an alternative to the use of antibiotics.

Abstract:

Mealybug Trabutina serpentina has two generations in southeastern Kazakhstan. Second instars of the second generation overwinter. Between 2003 and 2005, for the second time in 50 years, a large reproduction of this pseudococcid was seen in the Ile River valley. This species should be removed from the list of potential biocontrol agents for Tamarix ramosissima that are considered suitable in the USA, due to its potential to harm American populations of T. aphylla. Nonetheless, the species might be used for biological control of tamarisk in South Africa, Australia, and other countries.

Abstract: The deployment of Vision-Language Models (VLMs) in Satellite IoT scenarios is critical for real-time disaster assessment but is often hindered by the substantial memory and compute requirements of state-of-the-art models. While parameter-efficient fine-tuning (PEFT) enables adaptation, with minimal computational overhead, standard supervised methods often fail to ensure robustness and reliability on resource-constrained edge devices. To address this, we propose EdgeV-SE, a self-reflective fine-tuning framework that significantly enhances the performance of VLM without introducing any inference-time overhead. Our framework incorporates an uncertainty-aware self-reflection mechanism with asymmetric dual pathways: a generative linguistic pathway and an auxiliary discriminative visual pathway. By estimating uncertainty from the linguistic pathway using a log-likelihood margin between class verbalizers, EdgeV-SE identifies ambiguous samples and refines its decision boundaries via consistency regularization and cross-pathway mutual learning. Experimental results on hurricane damage assessment demonstrate that our approach improves image classification accuracy, enhances image–text semantic alignment, and achieves superior caption quality. Notably, our work achieves these gains while maintaining practical deployment on a commercial off-the-shelf edge device such as NVIDIA Jetson Orin Nano, preserving the inference latency and memory footprint. Overall, our work contributes a unified self-reflective fine-tuning framework that improves robustness, calibration, and deployability of VLMs on edge devices.

Abstract:

In urban corridors, roundabouts often operate in close proximity to signalized intersections, yet the safety implications of their mutual interaction remain insufficiently explored. This study combines field measurements and VISSIM microsimulation with the Surrogate Safety Assessment Model (SSAM) to analyze roundabout–signalized intersection pair under varying outer radii (12–22 m), spacings (40–160 m), signal red times (17–27 s), and traffic distributions. A multiple linear regression model for predicting the total number of conflicts is developed and partially validated using calibrated real-site models for corridors in Osijek and Poreč, Croatia. Small spacings (40 m) increase the total number of conflicts by 40–60% for small roundabouts (R = 12 m) and 20–40% for larger radii compared with isolated operation. Increasing the outer radius from 12 to 17 m reduces conflicts by up to about 90%, while longer red times further lower conflicts, especially for small roundabouts. The final regression model, based on spacing, red time, and outer radius, explains about 80% of the variance in conflicts and shows good agreement with SSAM estimates within its applicability range, providing a practical tool for safety-oriented design of urban roundabout–signalized intersection corridors thereby contributing to the goals of developing a sustainable transport system in complex urban environment.

Abstract: Sister Mary Joseph Nodules (SMJN) are rare extra intestinal manifestations of metastatic intra-abdominal and pelvic malignancies, often indicating advanced disease and poor prognosis. Their association with cholangiocarcinoma (CCA) is particularly uncommon, with only a limited number of reported cases. We present a case report of a 65-year-old previously healthy male who presented for an elective umbilical hernia repair. His additional cholestatic symptoms and history of fatigue prompted further evaluation with biopsy and imaging, which revealed advanced stage intrahepatic CCA. Following the diagnosis, the patient underwent palliative biliary stenting and chemotherapy. The variable presentation of SMJN, along with their frequent misdiagnoses, often delays recognition and management of the underlying malignancy. This case of SMJN in the setting of CCA highlights the complex interplay between intra-abdominal and pelvic malignancies and their impact on different organ systems. With the rising incidence and mortality rates associated with CCA, early recognition is essential to improving patient outcomes. This underscores the need for increased clinical awareness and further research, thus supporting the development of this case report.

Abstract:

The vitamin D receptor (VDR) acts as both a nuclear transcription factor and a non-genomic mediator that regulates a broad spectrum of physiological processes beyond calcium and phosphate homeostasis. VDR plays an important role in the modulation of ion channels across multiple tissues, including osteoblasts, renal and intestinal epithelial cells, neurons, and vascular smooth muscle. These regulatory mechanisms encompass genomic actions through vitamin D response elements in target genes—such as TRPV5, TRPV6, KCNK3, and KCNH1—as well as rapid, non-genomic actions at the plasma membrane involving protein disulfide isomerase A3 and associated signaling cascades. VDR-mediated transcriptional control of calcium, potassium, and chloride channels contributes to the fine-tuning of cellular excitability, calcium transport, and mitochondrial function. Evidence also implicates VDR–ion channel crosstalk in various pathological contexts, including renal cell carcinoma, breast and cervical cancers, pulmonary arterial hypertension, and osteoporosis. Understanding the molecular interplay between VDR and ion channels provides new perspectives on the pleiotropic effects of vitamin D and offers promising therapeutic opportunities in oncology, cardiovascular disease, and skeletal disorders. This review synthesizes previous and current evidence on the genomic and non-genomic mechanisms underlying VDR–ion channel regulation and highlights novel frontiers in vitamin D signaling relevant to human health and disease.