Search Results (1,664)

Interzeolite transformation (IZT) has emerged as a versatile strategy for accessing zeolite frameworks through controlled framework reorganization under comparatively simplified synthesis conditions. Unlike traditional synthesis approaches that frequently require organic structure-directing agents (OSDAs), highly alkaline media, and prolonged thermal treatment, IZT converts pre-existing zeolite into a new topology, enabling direct reuse of crystalline matter while reducing synthesis complexity. This review examines how structural drivers, including framework density, structural memory, and building-unit compatibility, govern transformation pathways and phase selectivity across five principal transformation approaches: (i) solution-mediated, (ii) assembly–disassembly–organization–reassembly (ADOR), (iii) mechanically assisted, (iv) steam-assisted, and (v) fully solid-state systems. These approaches promote distinct transformation pathways that govern framework reconstruction, structural inheritance, and phase selectivity. Recent advances in solvent-free, mechanochemical, steam-assisted, and microwave-assisted synthesis demonstrate the potential of IZT to reduce solvent consumption, template usage, and crystallization times. Despite these advances, major challenges remain in predicting transformation outcomes, controlling transient intermediates, and establishing scalable and quantitatively validated sustainability metrics. Collectively, these developments position IZT as a promising platform for the rational and sustainable design of next-generation zeolitic materials. Full article

Diacritization is an essential part of the reading and writing of text in Yorùbá, a widely-spoken tonal language in West Africa and some parts of the American continent. Unfortunately, typical computer-typed texts are not diacritized. Thus, automatic diacritization is a critical issue in Yorùbá natural language processing (NLP), since missing tone marks and underdots affect text comprehension, translation and speech technology. This paper begins by reviewing the state of the art. While there is a paucity of Yorùbá diacritization models, four models found were studied to explore their performances using the standardised Yorùbá Automatic Diacritization Dataset: the 2018 Volta Baseline, the mT5_base_yoruba_adr, GPT-5.2 and Gemini 3.1 Pro. We measured the performance based on a set of metrics: Word Error Rate (WER), Character Error Rate (CER), Diacritization Error Rate (DER), Word Diacritization Error Rate (WDER), BLEU and ChrF, using the complete diacritic removal condition of the YAD test set. To ensure reproducibility, the LLM evaluations were conducted via the respective official APIs and AI Studio with pinned snapshots and deterministic settings, with each model evaluated across three independent full-dataset runs. The findings showed that the specialised mT5_base_yoruba_adr model slightly outperforms the LLMs, achieving the lowest error rates of 34.85% CER, 18.34% WER, 43.37% DER and 18.33% WDER, as well as a BLEU of 0.6872 and ChrF of 0.8436. Gemini 3.1 Pro ranked second across all error rate metrics with 35.68% CER, 18.96% WER, and 44.84% DER but outperformed mT5 by a small margin on ChrF (0.8469), followed by GPT-5.2 with 54.01% CER, 38.05% WER, and 62.64% DER. The Volta Baseline built on the early seq2seq showed the weakest performance with 92.37% CER and 94.42% DER. These results challenge the assumption that large parameter count and massive pre-training guarantee superior performance in low-resource language tasks and show that targeted fine-tuning on Yorùbá-specific data remains important. Our work serves as a reference for researchers seeking an overview of the state of the art, as well as a detailed and reproducible evaluation of existing models. The results highlight methodological progress and gaps in current systems. Addressing these gaps will require domain-adaptive fine-tuning, improved algorithms, and robust datasets to advance the state-of-the-art in African-language automatic diacritization research. Full article

As RFID systems become increasingly widespread, the limitations imposed by tag collisions on system performance are becoming more evident. Parallel decoding has attracted significant attention due to its ability to improve channel utilization and throughput. However, existing schemes often perform poorly when decoding weak signals. Several challenges remain, including the assumption of ideal channel conditions, difficulty in detecting tag state transitions, and the complexity of state cluster formations in the In-phase and Quadrature (IQ) domain. To address the above issues, this paper first experimentally verifies the ability of middle state points to segment tag states, and proposes a time-window-based pre-processing method to improve the density of state clusters in the IQ domain. Second, by leveraging the high vertical resolution of the reader, we propose an ideal magnitude calculation method and a matching strategy for combined state clusters under weak signal conditions. Finally, we propose MagMap, a parallel decoding scheme based on middle state points and magnitude extraction. Experimental results demonstrate that, under weak signal conditions, MagMap reduces the decoding BER (Bit Error Ratio) of received packets by more than 60% compared to the state-of-the-art. Full article

Unmanned Surface Vehicle (USV) clusters operating in maritime environments face dynamic communication conditions, including varying sea states, electromagnetic interference, and satellite denial, that render static communication topologies suboptimal. Existing approaches assess link quality through single indicators, typically the SNR, and lack mechanisms for automatic topology adaptation. This paper presents a multi-layer adaptive communication framework that achieves a mean communication quality score of 0.72 (vs. 0.51–0.66 for baselines), a message delivery rate of 94.1% under benign conditions, and a failure recovery time of 3.2 s (vs. 5.8–8.4 s for baselines) across five communication failure scenarios. The framework integrates three layers: a weighted multi-indicator communication quality metric fusing the SNR, packet loss rate, latency, and link stability into a unified score; a topology utility function that selects among centralized, distributed, and hierarchical topologies by optimizing a quality–threat–overhead objective; and a multi-modal backup communication manager with physics-based underwater acoustic, optical line-of-sight, and multi-hop relay fallback modes. Simulation results demonstrate consistent improvements over single-indicator and static-topology baselines, with particularly strong performance under satellite denial and jamming scenarios where multi-modal backup communication sustains delivery rates above 85% under simulated conditions. In summary, the framework demonstrates consistent improvements across all metrics (communication quality, delivery rate, recovery time) relative to four baselines, with the largest gains observed under the most challenging conditions (satellite denial and jamming). We emphasize that the framework adaptively selects among pre-defined canonical topologies (star, mesh, tree) based on real-time conditions rather than synthesizing optimal topologies de novo—a distinction between topology management and topology optimization. Full article

Rock pillars in deep underground mines are subjected to complex stress environments. The combined effects of in situ stress and cyclic disturbances from mining activities lead to a redistribution of the surrounding rock mass stress field, which readily triggers instability and failure, posing severe threats to mining engineering safety. To investigate the damage mechanism of cyclic loading on rock and its weakening effect on the bearing capacity of mine pillars, this study takes limestone as the research object. A series of uniaxial compression tests were conducted on limestone specimens subjected to triaxial cyclic pre-damage, complemented by numerical simulations to further characterize the energy and deformation evolution of the damaged limestone under cyclic loading conditions. The findings are as follows: (i) Triaxial cyclic tests on limestone show that both the input energy and dissipated energy follow similar trends, decreasing rapidly in the initial stage before stabilizing. The elastic strain energy remains largely constant, with most of the input energy being stored as elastic strain energy. Under constant stress levels and cycle numbers, increases in confining pressure and frequency reduce the rock’s input energy, elastic strain energy, and dissipated energy. (ii) The peak stress of damaged limestone exhibits a positive correlation with the pre-damage confining pressure and cyclic frequency, while it decreases with an increasing number of cycles. Higher confining pressure and frequency raise the input energy, elastic potential energy, and dissipated energy at the peak stress point. (iii) Deformation and failure in damaged limestone originate from the development and propagation of localized deformation zones. Increased lateral displacement within these zones promotes the formation of macroscopic fractures. Due to significant structural heterogeneity inside the localized areas, the evolution of deformation energy is influenced by regional characteristics. (iv) Simulation results indicate that the uniaxial compressive failure of limestone involves the accumulation and propagation of micro-scale tensile cracks, which ultimately coalesce into macro-scale shear fracture surfaces. During uniaxial loading of pre-damaged limestone, newly generated cracks predominantly initiate around pre-existing cracks, with only a limited number distributed randomly. Their peak intensity shows a positive correlation with the pre-damage confining pressure. Full article

Background/objectives: Long COVID is associated with persistent, multi-system symptoms, yet little is known about how it affects individuals with intersecting vulnerabilities, such as a racialized identity and pre-existing mental health conditions. This study aimed to descriptively characterize the symptom burden, functional outcomes and mental health in this population. Methods: A cross-sectional, exploratory study was conducted among 51 adults in Canada who self-identified as racialized and as having a pre-existing mental health condition and reported long COVID symptoms. Participants completed an online survey, including validated measures of symptoms, fatigue, post-exertional malaise, cognitive function, mental health and disability. Descriptive statistics were used to summarize outcomes. Results: Participants reported a slight to moderate overall symptom burden, with the highest scores in respiratory and psychological domains. Functional impairment was moderate across work, social and daily activities (Work and Social Adjustment Scale mean = 17.35; World Health Organization Disability Assessment Schedule 2.0 mean = 16.61; Post COVID-19 Functional Status Scale mean = 2.20). Fatigue and post-exertional malaise were notable (Modified Fatigue Impact Scale mean = 43.39; DePaul Symptom Questionnaire—Post-Exertional Malaise mean = 22.47), and cognitive difficulties were commonly reported (Perceived Deficits Questionnaire mean = 33.43). Anxiety and depression scores were in the mild to moderate range respectively (General Anxiety Disorder-7 mean = 9.27; Patient Health Questionnaire-9 mean = 11.43). Conclusions: Clinically relevant fatigue, post-exertional malaise, and depression were found, alongside moderate functional limitations across life domains. The findings support the conceptualization of long COVID as a syndemic condition and underscore the need for equity-informed research, rehabilitation and public health strategies. Full article

This study aims to develop a decision-making framework for equalizing urban electric vehicle (EV) charging services, which is applied to improve Wuhan’s charging infrastructure. Using grid units as the basic analytical units, the study constructs measurement models for two scenarios—daily commuting and weekend travel—including a spatial demand index based on classified population distribution prediction, a spatial supply index derived from regional charging station statistics, and a supply–demand balance index. Grading systems are established for each scenario’s demand, layout thresholds, and supply, together with an integrated classification combining both scenarios. According to the suitability of grid units for service improvement, three optimization strategies are proposed: adding charging stations, expanding existing stations, and retrofitting parking lots. Evaluation methods are designed to assess spatial equilibrium pre- and post-optimization for residential quarters and commercial POIs. An empirical case study of Wuhan’s main urban area shows that service satisfaction reaches 88.68% for residential quarters and 75.93% for commercial POIs under the current conditions. The proposed scheme recommends the addition of 6 new stations, expansion of 23 stations, and retrofit of 52 parking lots, increasing satisfaction to 99.16% and 89.66%, respectively. The model provides a feasible technical framework for urban EV charging station planning. Full article

Selenium (Se) is an essential micronutrient required for redox regulation and metabolic homeostasis. Altered biomarkers of Se status have been linked with obesity and metabolic syndrome, yet its role in these conditions, particularly in a sex-specific context, is not well defined. This study investigated the impact of suboptimal Se intake on metabolic risk profiles in male and female mice with pre-existing diet-induced obesity. C57BL/6N mice were fed either a standard diet with adequate Se (SD-ASe), a Western diet with adequate Se (WD-ASe), or WD-ASe followed by a Western diet containing suboptimal Se levels (WD-SOSe). Metabolic parameters, adipokine profiles, tissue Se distribution, and gene expression in visceral white adipose tissue (vWAT) were assessed. Both sexes exhibited increased weight gain and adiposity in response to a Western diet; however, only males developed hypertension and elevated non-fasted blood glucose levels. Suboptimal Se intake elicited marked sex-dependent effects. In females, it induced elevated non-fasted blood glucose levels and circulating leptin, and further dysregulated circulating adipokine profiles, accompanied by pronounced alterations in selenoprotein expression and redox-related pathways in vWAT. In contrast, male mice exhibited a partial adaptation, including reduced glucose levels and minimal alterations in gene expression. Tissue Se distribution also appeared to be influenced by biological sex. These findings demonstrate that suboptimal Se intake may exacerbate obesity-related metabolic dysfunction in a sex-specific manner, with females showing greater susceptibility, underscoring the importance of micronutrient status and sex differences in metabolic disorders. Full article

The M_w7.7 Pazarcık–Kahramanmaraş and M_w7.5 Elbistan–Kahramanmaraş earthquakes on 6 February 2023 caused the collapse of 11 buildings in Adana’s city centre—predominantly 15-storey RC structures in a narrow zone—despite peak ground accelerations of only 0.05 g; most collapses occurred during the M_w7.7 event. Two-dimensional seismic site response analyses at the site of interest with bedrock input from station TK0118 yielded topographic amplification factors of 2.37 (EW) and 2.09 (NS) for homogeneous conditions; with stratigraphic heterogeneity, NS increased to 2.66 and EW remained at 2.27, reaching above 3.0 at the slope crest. Spectral amplification factors reached 4.53 (NS, T = 0.90 s) and 3.21 (EW, T = 0.68 s), indicating amplification in the short-to-intermediate period range. These amplified records were applied to idealised 15-storey RC models—from code-compliant to deliberately deficient—with C16 and C8 concrete classes through nonlinear performance analyses. Under unamplified TK0118 records, no model reached collapse-level damage. Under amplified records, only the most deficient model exhibited widespread shear and strain failures in the lower storeys. A detected velocity pulse (T_p = 13.496 s) was excluded as a collapse mechanism, as its period far exceeds structural periods (1.2–1.9 s). The collapses are attributable to the compounding of topographic and stratigraphic amplification with pre-existing structural deficiencies. Full article

Background: Pregnancies tend to progress without any serious complications. Nonetheless, for a subset of women, obstetric complications may develop, ranging in severity. The most critical of these life-threatening events is referred to as Maternal Near Miss (MNM). To identify the epidemiological and obstetric characteristics, as well as clinical outcomes of MNM cases reported over the year 2021 in the Brazilian state of Paraná. This quantitative, population-based study analyzed 888 notifications that occurred in 2021, obtained from the MNM Notification System. Descriptive statistics and a one-sample Chi-square goodness-of-fit test were applied to the data. Among the women reported, 92.6% were pregnant, the mean age was 29 years, 67.1% identified as white, and 45.2% had preexisting health conditions. Regarding obstetric characteristics, 41.6% were classified as high-risk pregnancies, but nearly one-third (32.3%) of MNM cases occurred in women initially classified as usual risk. The clinical worsening event occurred most frequently during the third trimester (71.9%), and emergency cesarean section was indicated in 60.1% of cases with complete information for this variable. Cesarean delivery predominated over vaginal delivery, with an emergency-to-elective cesarean ratio of approximately 4.7:1. Most women (75%) were discharged after recovery. MNM events are not restricted to women initially classified as high-risk, underscoring the need to strengthen early detection strategies and ensure appropriate management at all levels of care. Improved training of healthcare professionals responsible for reporting and the standardization of MNM monitoring systems in Brazil are also essential. Full article

The global regulatory landscape is shifting from voluntary corporate social responsibility (CSR) reporting to mandatory Environmental, Social, and Governance (ESG) disclosure, yet whether this transition drives substantive corporate environmental change or merely symbolic compliance remains empirically contested. This study investigates the causal impact of mandatory ESG disclosure on firm value and operational carbon intensity, drawing on an unbalanced panel of 9682 firm-year observations for 1626 listed firms from the European Union (EU-27) and Japan covering the period 2018 to 2024. The EU serves as the treatment group, where mandatory disclosure requirements escalated substantially from 2021 onward through the Sustainable Finance Disclosure Regulation and the Corporate Sustainability Reporting Directive proposal. Japan serves as the control group, representing a developed economy with sophisticated capital markets and high ESG awareness that maintained a voluntary disclosure environment throughout the study period. A Difference-in-Differences framework with firm- and year-fixed effects is employed, and causal identification is validated through a dynamic event study analysis. Three principal findings emerge. First, mandatory ESG disclosure is not associated with a statistically significant improvement in firm value in the EU–Japan comparative context, a result that is interpreted as descriptive rather than causal given evidence of pre-existing valuation divergence between the two groups. Second, mandatory disclosure is associated with a significant and progressive reduction in Scope 1 and 2 carbon intensity, indicating substantive operational decarbonization rather than symbolic compliance. Third, this emissions-reducing effect is significantly amplified among firms with dedicated CSR sustainability committees, while the board independence policy indicator yields no significant moderating effect, a finding attributed to data limitations. These results carry direct implications for policymakers designing climate-related disclosure frameworks and for scholars examining the boundary conditions under which mandatory transparency translates into genuine environmental performance. Full article

The beneficial utilization of small and medium floods requires a clear flood-control safety boundary before floodwater can be moderately stored and regulated as a water resource. For the Three Gorges Reservoir, a large river-type reservoir with long-distance backwater effects and tributary blocking, this boundary cannot be determined solely from the dam-front water level. This study developed a one-dimensional unsteady hydrodynamic model with dynamic roughness calibration to investigate the risk-constrained flood-season operating water level of the Three Gorges Reservoir. Typical flood events and the 20-year return period design flood were used to examine the responses of the maximum dam-front flood-regulation water level, excess flood volume, longitudinal water levels, and exceedance risk at key reservoir-area sections under different initial regulation water levels and release-discharge conditions. The results show that the Changshou reach is the main control section for high-water-level inundation risk under the study scenarios. When the initial regulation water level is at or below 155 m, the dam-front flood-regulation water level, the peak water level at Changshou, and the exceedance duration generally vary only slightly. When the initial regulation water level exceeds 155 m, these risk indicators increase markedly, indicating a reduced flood-control safety margin. Perturbation analysis further shows that the dam-front flood-regulation indicators are relatively insensitive to small roughness and dam-front boundary perturbations, whereas the Changshou water level and exceedance duration are more sensitive to roughness and flood-volume perturbations. Therefore, 155 m should be interpreted as a conservative operational reference boundary under the current design-flood framework, existing operation rules, and the assumption of no forecast-based pre-release, rather than as an absolute safety threshold. Increasing release discharge can reduce high-water-level risk in the reservoir area under preset release limits, but its practical application must remain conditional on downstream flood-control constraints and real-time flood-conveyance capacity. The results provide a hydrodynamic basis for risk-constrained flood-season operation of large river-type reservoirs. Full article

High-production wells of deep coalbed methane have been widely reported during the last decade. The Qinshui Basin in China is rich in deep coalbed methane resources, but the pore size distribution characteristics of coal under high-temperature and high-stress conditions remain unclear, affecting the formulation of coalbed methane development strategies. In this study, nuclear magnetic resonance simulations were conducted on anthracite samples from the Zhaozhuang and Sihe mines in the Qinshui Basin under varying temperatures and confining pressures, and the difference in stress and temperature sensitivity of pores with varying sizes was determined. The results show that the pores exhibit strong stress sensitivity but weak temperature dependence. Total porosity decreases with increasing confining pressure, with a maximum damage rate of 6.55%. Pore-size heterogeneity governs differential responses: micropores and macropore fractures show reduced porosity, whereas mesopores exhibit minor increases. Temperature-driven porosity changes occur in distinct phases: at lower temperatures (20–35 °C), damage rates escalate with heating, while at elevated temperatures (35–50 °C), sensitivity diverges due to the variations in native fracture structures. Furthermore, stress and temperature responses correlate with the developmental state of pre-existing pores/fractures and mineral infill. These findings provide critical insights for optimizing coalbed methane exploitation in deep anthracite reservoirs. Full article

This study analyses the pharmacological profiles of medications administered to critically ill COVID-19 patients to evaluate their efficacy regarding recovery rates and duration of hospitalization. The results demonstrate a significant difference in clinical outcomes. While the administration of Ceftazidime, Ceftriaxone, and Oseltamivir was associated with negative survival trends, Dexamethasone and Favipiravir were associated with a fourfold higher probability of survival in severe cases. Notably, no pharmacological intervention significantly reduced the length of hospital stay; instead, recovery duration was primarily influenced by comorbidities such as obesity, cardiovascular disease, and diabetes. Furthermore, age and preexisting physiological conditions remained primary predictors of mortality. Observational analysis in our study for drug repurposing identified Amikacin, Remdesivir, and Rivaroxaban as potential therapeutic candidates. However, Dexamethasone was identified as the most effective treatment for recovery, likely due to a molecular structure with high potential binding affinity to the SARS-CoV-2 virus. These findings suggest that while specific repurposed drugs offer measurable benefits, patient history remains a critical determinant of outcomes, highlighting the necessity for further research to refine therapies against emerging viral pathogens. Full article

The introduction of rapid, high-sensitivity cardiac troponin (hs-cTn)-based algorithms has markedly changed the work-up of patients admitted to the emergency department (ED) with suspected acute coronary syndrome (ACS). However, when applied to real-world ED populations, these algorithms perform worse than in clinical studies of derivation and validation. The main reasons for this discrepancy are that patients tested for hs-cTn in real-world settings tend to be older and less clinically preselected. Nevertheless, ACS must often be ruled out in patients with atypical presentations. Routine patients also more frequently have impaired renal function and pre-existing cardiac diseases, such as atrial fibrillation, heart failure, or coronary artery disease. These conditions do not necessarily cause the actual acute ED presentation. Using the standard decision limits of the 0 h, 0/1 h, or 0/2 h algorithms does not hinder the exclusion of ACS in the ED. However, using them in real-world conditions substantially decreases the positive predictive value for acute myocardial infarction (AMI) and classifies a higher percentage of patients into the “observe (gray) zone” than reported in clinical studies. Patients classified with a working diagnosis of “rule-in AMI” often require hospital admission for other reasons, though their discharge diagnosis may differ from AMI. A major challenge in real-world EDs is the high proportion of gray zone hs-cTn concentrations in approximately 50% of tested patients. Therefore, additional hs-cTn sampling at 3 h after admission is often necessary to rule out acute myocardial injury. This review summarizes and critically discusses the evidence for adjusting hs-cTn ED algorithm decision limits according to age, sex, and renal function. It also discusses the critical differential diagnosis of acute and chronic myocardial injury in the ED. Full article