Search Results (1,395)

This paper investigates backscatter-aided relaying for interactive dual-HAP wireless-powered sensor networks (WPSNs), in which two cooperative sensor groups transmit sensed data to opposite hybrid access points (HAPs) using harvested radio-frequency energy. Each group consists of multiple source sensor nodes (SNs) and one relay SN selected according to its proximity to the target HAP. To reduce local cooperation overhead, source SNs reuse the wireless power transfer (WPT) signal as a controllable carrier and convey their information to the relay SN through passive backscatter communication. The collected information is then delivered to the target HAPs through direct source transmission and relay forwarding. A source common-throughput maximization problem is formulated by jointly optimizing time allocation, transmit energy allocation, and dual-HAP energy beamforming, subject to energy-causality and relay minimum-rate constraints. To address the resulting non-convexity, an alternating optimization algorithm is developed, where the time-and-energy allocation subproblem is transformed into a convex form and the energy beamforming matrices are updated through energy-feasibility margin maximization. Numerical results show that the proposed scheme outperforms active cooperation without backscatter and direct transmission, demonstrating the effectiveness of integrating passive local information collection, relay-assisted uplink transmission, and optimized dual-HAP WPT. Full article

Drawing on signaling theory, this study investigates the role of lead founders’ human capital signals in the success outcomes of equity crowdfunding (ECF) campaigns. While prior research emphasizes entrepreneurial teams or broadly defined founder characteristics, the role of dominant entrepreneurial actors remains underexplored. We focus on the lead founder, defined as the individual combining founder status, CEO authority, and ownership concentration, as the primary signal carrier in ECF contexts. Using a multi-platform dataset of 1067 campaigns from Republic Europe, Crowdcube, Mamacrowd, and Invesdor (2012–2024), we examine how lead founders’ education and experience shape investor decisions. Our results indicate that industry-related education is the strongest predictor of the number of investors. Furthermore, while industry experience alone can positively predict investor engagement, its role disappears once education is accounted for, suggesting that education in industry-related fields can outweigh industry experience in shaping investor perceptions. Additionally, our findings suggest that entrepreneurial experience and attendance at a top-ranked university do not contribute meaningfully to explaining investor participation. Accordingly, the study contributes to the human capital signaling literature by showing that investors evaluate the incremental informational value of human capital signals rather than assessing each signal independently, and highlights the centrality of the lead founder in decision-making under highly uncertain crowdfunding environments. Full article

Ammonia is a promising zero-carbon energy carrier for maritime decarbonisation, but its deployment is limited by safety risks that are not adequately addressed by conventional marine fuel safety frameworks. This study critically reviews safety assessment, risk management and control strategies for ammonia storage and handling in maritime applications using a PRISMA-informed literature synthesis. Evidence is analysed across hazard characterisation, storage configurations, transfer operations, risk assessment methods, mitigation barriers and regulatory frameworks. The review shows that ammonia safety is governed by coupled release–exposure–barrier interactions shaped by storage condition, tank configuration, pressure–temperature behaviour, material compatibility, transfer mode, ventilation, ship geometry and human intervention. Existing methods, including HAZID, HAZOP, risk matrices and QRA, support hazard screening and prioritisation, but remain limited in representing flashing two-phase releases, dense gas dispersion, confined-space accumulation, exposure duration, ventilation effectiveness and safeguard timing under maritime conditions. CFD, FTA, Bayesian approaches and Monte Carlo analysis offer higher analytical resolution, but their reliability is constrained by limited validation data, uncertain leak-frequency inputs and simplified assumptions for human exposure and emergency response. Effective risk control therefore requires a toxicity-centred barrier strategy linking containment integrity, ammonia-compatible materials, gas and process monitoring, emergency shutdown, ventilation, water-based mitigation, PPE, competency-based training and emergency planning. Current regulatory and classification guidance provides an essential foundation but remains fragmented and insufficiently aligned with ammonia-specific requirements for exposure modelling, safety-zone definition and approval pathways. This review contributes a maritime-specific synthesis of ammonia storage and handling safety by connecting hazard behaviour, storage design, transfer operations, risk assessment limitations, control-barrier logic and regulatory approval needs. The findings highlight the need for validated source-term models, full-scale release and dispersion data, exposure-based safety criteria and harmonised regulatory pathways to support the safe and scalable use of ammonia in maritime decarbonisation. Full article

Mobile RFID inventory in libraries must be planned and evaluated under noisy observations, configuration-dependent read regimes, and incomplete supervision. This paper presents an uncertainty-aware analytics framework for robot-assisted RFID inventory using the public RFID Location dataset. The framework has three phases. Phase 1 converts irregular list-encoded logs into atomic RFID events and quantifies how operating configuration changes read density and signal variability. Phase 2 performs map-constrained Bayesian shelf inference by synchronizing RFID reads with robot trajectory and antenna geometry and by fusing RSSI and carrier phase over feasible shelf candidates. Phase 3 translates posterior spread and non-convergence into proxy review workload and cost, enabling configuration comparison and certainty–throughput trade-off analysis when strict EPC-to-item linkage is unavailable. Across 688,073 aligned RFID observations, the pipeline produces 18,190 posterior tag estimates from five inventory runs. The empirical results show strong run dependence: the best run achieves a mean posterior spread of 0.906 m with a convergence rate of 0.553, whereas a degraded run reaches only 0.004 convergence with a mean spread above 2.1 m. Because EPC-to-item linkage is unavailable, these values are posterior concentration and workload indicators rather than ground-truthed localization-accuracy metrics. A saved phase-weight ablation further shows that adding phase information substantially sharpens posterior concentration relative to an RSSI-only baseline. Under the proxy workload model, autonomous-S1-P30 provides the most favorable balance among posterior certainty, scan effort, and implied review burden. Full article

Background/Objectives: Krebs von den Lungen-6 (KL-6) is a mucin-like glycoprotein that is elevated in a variety of lung diseases and used as a diagnostic and prognostic biomarker in people with cystic fibrosis (pwCF). Single nucleotide polymorphisms (SNPs) in mucin-1 (MUC1) influence KL-6 serum concentration. This study investigated the relationship between serum KL-6 concentrations in pwCF and a MUC1 SNP and its longitudinal dynamics. Methods: The study included pwCF (n = 174) and healthy controls (n = 30). In pwCF, 365 samples were collected for longitudinal analyses; KL-6 levels were measured and the MUC1 SNP rs4072037 was genotyped in pwCF and controls. Cross-sectional and longitudinal associations between KL-6, genotype, and clinical parameters, such as infectious exacerbation, body mass index, inflammatory values and lung function, were analyzed using linear mixed-effects models. Results: Serum KL-6 was significantly elevated in pwCF compared with controls (458 ± 357 vs. 283 ± 103 U/mL; p < 0.001). Homozygous G/G carriers exhibited higher baseline KL-6 than A/A carriers (627 ± 673 vs. 397 ± 148 U/mL; p < 0.001), while heterozygous individuals showed intermediate levels. Longitudinally, the MUC1 SNP and interindividual differences in vital capacity (ppFVC) primarily determined baseline KL-6 levels, explaining 52.5% of variance. Short-term intraindividual fluctuations were largely driven by infectious exacerbations independent of genotype, accounting for ~10% of within-subject variance. Conclusions: PwCF generally showed elevated serum KL-6 levels and reflected both stable interindividual differences, mainly driven by the MUC1 SNP and ppFVC. Dynamic intraindividualchanges were associated with infectious exacerbations. Given the influence of MUC1 polymorphisms (e.g., rs4072037) on KL-6 concentration, personalized interpretation based on the genotype status may be informative in pwCF. Full article

Empty-vehicle repositioning is a persistent challenge in long-haul road freight because carriers must reduce empty mileage without sacrificing service reliability under lead times, appointment windows, and uncertain load realization. This paper formulates empty-vehicle repositioning on freight corridors as a stochastic control problem with explicit space–time feasibility and a stated within-epoch event order. Lead times couple current dispatch decisions to future capacity, pickup windows impose reachability constraints, and stochastic match feasibility captures information and market frictions. We develop dynamic lower bounds from time-expanded relaxations, showing that dual prices of inventory-balance constraints can be interpreted as space–time scarcity values. We further introduce an order-dependent nested friction decomposition that separates excess empty movement into spatial imbalance, temporal mismatch induced by lead times and time windows, and information frictions. Guided by this structure, we propose price-guided rolling-horizon and generalized-cost policies and evaluate them on synthetic corridor experiments organized around the three friction families. The results reveal service–empty-mileage trade-offs, a pronounced knee in the Pareto frontier, lower service loss under widened tight pickup windows, and strong sensitivity to match feasibility. The PG-RH policy reduces empty-distance exposure and total cost relative to static balancing in the main scenarios while maintaining comparable, but not uniformly dominant, service performance. The framework provides a diagnostic basis for identifying the sources of deadhead and for designing operational interventions that reduce empty mileage without undermining reliability. Full article

Regulated cell death is essential for tissue homeostasis, immune defense, and disease progression, yet the lipid-based regulatory mechanisms that coordinate cell death signaling remain incompletely understood. Protein palmitoylation is a dynamic and reversible lipid post-translational modification that controls protein membrane association, trafficking, stability, and signaling complex assembly. This review summarizes the regulatory roles of palmitoylation and depalmitoylation in major forms of regulated cell death, including apoptosis, necroptosis, pyroptosis, ferroptosis, and autophagy-related cell death. Particular attention is given to representative palmitoylated substrates, including Fas cell surface death receptor (Fas), receptor-interacting protein kinase 1 (RIPK1), NLR family pyrin domain containing 3 (NLRP3), gasdermin D (GSDMD), glutathione peroxidase 4 (GPX4), solute carrier family 7 member 11 (SLC7A11), autophagy-related 16 like 1 (ATG16L1), and Beclin1. These substrates illustrate how palmitoylation links membrane organization, metabolic status, inflammatory signaling, and cell fate decisions. Disease-oriented evidence further indicates that dysregulated palmitoylation contributes to cancer, neurodegenerative diseases, and inflammatory or immune-related disorders by modulating cell death resistance, inflammatory amplification, immune evasion, or impaired proteostasis. Current challenges include limited quantitative information on palmitoylation dynamics, incomplete evidence for some enzyme–substrate relationships, and insufficient distinction between disease-driving and secondary palmitoylation events. Targeting zinc finger Asp-His-His-Cys (zDHHC) palmitoyl acyltransferases, depalmitoylating enzymes, or specific palmitoylated substrates may provide new therapeutic opportunities. Overall, this review positions protein palmitoylation as a dynamic molecular switch linking lipid metabolism, membrane signaling, regulated cell death, and disease remodeling. Full article

Hepatocellular carcinoma (HCC) remains a major global health burden, characterized by late diagnosis, limited therapeutic options, and high mortality rates. Conventional diagnostic tools such as serum α-fetoprotein testing and imaging lack sufficient sensitivity for early detection. In recent years, liquid biopsy has emerged as a minimally invasive approach that enables real-time molecular profiling of tumors through the analysis of circulating biomarkers such as nucleic acids, proteins, and extracellular vesicles. Recent advances have underscored exosomes—nano-sized extracellular vesicles (EVs) secreted by nearly all cell types—as pivotal mediators of intercellular communication and dynamic carriers of tumor-derived molecular information, offering exciting prospects for early cancer detection and personalized therapy. In HCC, EV microRNAs (miRNAs) participate in multiple oncogenic processes, including proliferation, angiogenesis, epithelial–mesenchymal transition, and immune modulation. Specific EV-associated miRNAs, such as miR-21, miR-122, miR-224, and miR-221, show distinctive expression profiles in HCC and correlate with tumor stage, metastasis, and patient prognosis. Moreover, panels of circulating EV-associated miRNAs demonstrate superior diagnostic accuracy compared with traditional biomarkers, underscoring their potential as non-invasive tools for early detection and disease monitoring. Their inherent stability in biofluids and resistance to enzymatic degradation further support their application in liquid biopsy approaches. Despite promising results, continued research is essential to validate EV-associated miRNA signatures and to integrate these “silent messengers” into routine clinical practice for precision management of hepatocellular carcinoma. Full article

The sortie generation rate (SGR), a key metric of carrier-based aircraft operations, is severely degraded by multi-source coupled faults across the human–equipment–environment triad. Existing models oversimplify these dynamics by employing static failure probabilities and treating contributing factors in isolation, thereby underestimating systemic risk. To address this, we propose a mechanism-driven, hybrid simulation framework that dynamically captures fault coupling and cascading effects within the phased-mission system (PMS) of flight deck operations. First, 22 basic fault events are identified via fuzzy fault tree analysis (FFTA) and translated into a Bayesian network (BN) to establish a probabilistic baseline. A multi-source coupled fault model is then constructed, integrating human reliability, time-varying equipment degradation, and fault stress propagation to describe spatiotemporal coupling. A protocol is designed to robustly simulate heterogeneous fault dynamics within a discrete-continuous hybrid engine. Simulation experiments demonstrate that: (1) the baseline replicates real-world exercise data, validating framework credibility; (2) the model reveals a nonlinear SGR degradation with a sharp decline beyond a critical maintenance-pressure threshold, a behavior missed by static models; and (3) a comprehensive maintenance strategy improves long-term SGR by 73.13% over a reactive baseline. This framework provides a scalable testbed for evaluating operational resilience and informing maintenance strategies for next-generation aircraft carriers. Full article

East Coast Fever (ECF) causes approximately one million livestock deaths annually in sub-Saharan Africa, posing a significant threat to livestock. The wildlife–livestock interface complicates disease management, as wildlife serve as reservoirs. This study developed a Continuous Time Markov Chain (CTMC) model incorporating the wildlife–livestock interface to analyze ECF dynamics. Using the Galton–Watson approximation, we assessed the probability of disease extinction following the introduction of infected hosts or vectors. The probability of disease extinction calculated from the branching process is shown to be in good agreement with the probability approximated from numerical simulations. The disease dynamics of the deterministic model and the CTMC model are compared to ascertain the effect of demographic stochasticity on ECF dynamics. Differences in model predictions and asymptotic dynamics between stochastic and deterministic models were evident. The deterministic and stochastic formulations should therefore be viewed as complementary modeling frameworks, with the deterministic model characterizing average epidemic dynamics and the CTMC model capturing the probabilistic variability and extinction behavior inherent in real transmission processes. These differences are crucial for intervention strategies earmarked to prevent outbreaks. Our analysis revealed a high probability of ECF extinction if the disease emerges from recovered carrier cattle. Finite time to ECF disease extinction is estimated using 10,000 sample paths, and it is shown that the epidemic duration is shortest if the disease is introduced by infectious cattle. The epidemic duration is longest when the disease is introduced by infectious ticks. Additionally, we observed that host interactions at the wildlife–livestock interface play a critical role in shaping ECF transmission and informing control strategies. Full article

Identifying village functional differentiation within rural territorial systems is essential for differentiated rural revitalization and place-based governance. However, existing approaches still lack effective analytical pathways for translating complex rural territorial relations and sparse planning labels into fine-grained measures of rural functional intensity. To address these gaps, this study develops a Few-Shot Hierarchical Graph Representation Learning (FH-GRL) framework. By integrating a Hierarchical Graph Infomax (HGI) model to capture cross-scale village–township–city relational dependencies and an Evidential Deep Learning (EDL) mechanism to map high-dimensional representations into class-specific evidence and Global Percentile Ranks (GPR), the framework supports fine-grained classification and continuous grading of rural functions. Empirical analysis in Pingdingshan City yields three main findings. First, within the present case study, FH-GRL shows more stable performance than traditional flat clustering and local graph models in identifying complex rural functions under limited labeled samples. Second, hierarchical context serves as a spatial calibration mechanism, reducing locally generated noise and improving the identification of village functional differentiation under spatial heterogeneity. Third, rural functional differentiation reflects the combined effects of place-based conditions and potential flow-related interaction conditions. In particular, Center villages show differentiated trajectories between endogenous production or service centers in agricultural plains and exogenous service centers along urban development axes. Overall, this study provides a planning-oriented quantitative framework for diagnosing rural functional differentiation under label scarcity and spatial heterogeneity. The GPR-based outputs can support the identification of high-intensity functional carriers, transitional villages, and general reserve areas, thereby providing diagnostic evidence for differentiated governance and tiered resource allocation. Rather than replacing formal planning judgment, the framework offers geospatially informed support for classified rural governance and more evidence-informed territorial planning. Full article

Multidrug-resistant organisms, particularly carbapenem-resistant Enterobacterales (CRE), represent a major global health threat. In settings with endemic circulation of carbapenem-resistant organisms, early identification of colonised patients before hospital admission may play a critical role in limiting in-hospital spread and guiding infection prevention strategies. We conducted a retrospective monocentric observational study including all patients evaluated for hospital admission in 2025. Patients presenting predefined epidemiological or clinical risk factors underwent risk-based pre-admission screening for CRE. Patient-level deduplication was applied to microbiologically positive records. Among 2694 patients evaluated for hospital admission, 1084 met predefined screening criteria and underwent rectal swab testing. Overall, 191 unique patients were confirmed as carriers of carbapenemase-producing Enterobacterales, corresponding to 17.6% of screened patients and 7.1% of the overall cohort evaluated for admission. KPC was the most prevalent carbapenemase gene (102/191, 53.4%), followed by NDM (57/191, 29.8%) and KPC/NDM co-production (14/191, 7.3%). Less frequent gene profiles included VIM, OXA-48, and combined carbapenemase patterns. In high-endemic healthcare settings, risk-based pre-admission screening may represent a pragmatic component of infection prevention pathways by supporting early identification of patients with probable CRE/CPE carriage. When analysed at the patient level, such programmes can provide useful operational and epidemiological information for admission management and infection control planning. Full article

Background/Objectives: Recessive titinopathies caused by biallelic TTN truncating variants (TTNtvs) present a clinically heterogeneous spectrum from fetal demise to late-onset slowly progressive distal muscular dystrophy. Prognostic counseling is challenging due to the vast size of the TTN gene, complex splicing patterns, and differential expression throughout developmental stages and tissues. This paper aims to delineate the regional genotype patterns and clinical characteristics of recessive titinopathies described from the prenatal period onwards to inform genotype–phenotype associations and genetic counseling. Methods: We analyzed clinical and genetic data from a prenatal-onset cohort with biallelic TTNtvs from both previously reported cases and novel cases from our center. To characterize the regional distribution of biallelic variants within this specific cohort, a two-dimensional scatter plot was utilized to map variants onto 10 biological regions (R1–R10) and 55 analytical units (U1–U55). We also performed Fisher’s exact tests on the subset of 50 cases with confirmed survival records to evaluate statistically significant associations between biallelic regional or percent spliced-in (PSI) thresholds combinations and severe clinical endpoints (intrauterine demise or death before 5 years). Results: A total of 96 prenatal cases from 76 unrelated families were analyzed. Decreased fetal movement was the most commonly reported symptom, observed in 81.3% (78/96) of cases, which was followed by arthrogryposis in 45.8% (44/96) and amniotic fluid volume abnormalities in 35.4% (34/96). Additionally, of the 95 cases with known pregnancy outcomes, 25.3% (24/95) resulted in termination and 11.6% (11/95) resulted in intrauterine demise (IUD), while 63.2% (60/95) reached birth with over 16.7% (10/60) being preterm. Among 60 live-born infants, severe postnatal morbidity was high: 45.0% (27/60) experienced respiratory failure, and 33.3% (20/60) died before the age of five. In this cohort, 84.4% (81/96) of cases possessed at least one TTNtv in either the metatranscript-only or A-band regions. The most common biallelic changes involved TTNtvs in both the A-band and metatranscript-only regions, accounting for 35.4% (34/96) of cases, followed by metatranscript-only combined with I-band variants at 16.7% (16/96), regardless of the PSI score of exons. Overall, 83.3% (80/96) had ≥1 variant on low-PSI (<50%) exons, and 19.8% (19/96) had both alleles on these low-PSI exons. In the 50 patients with confirmed survival records, biallelic changes (excluding splice-site variants) affecting both high-PSI (>90%) exons were significantly associated with severe outcomes (intrauterine demise or death before 5 years; exact p = 0.015), whereas the metatranscript-only plus I-band combination conferred a significantly lower risk of lethality before 5 years of age (exact p = 0.001). Conclusions: Our findings add to the accumulating evidence that TTNtvs on low PSl exons or metatranscript-only regions are frequently observed among reported prenatal-onset recessive titinopathy. Health surveillance for heterozygous carriers among family members is warranted due to the substantial risk for adult-onset dilated cardiomyopathy and peripartum cardiomyopathy. Full article

Driven by China’s “dual carbon” (carbon peak and carbon neutrality) goals and the national strategy of new-type urbanization, prefabricated construction has emerged as a pivotal pathway toward industrialized and sustainable development in the construction sector—leveraging its distinctive advantages in construction efficiency, cost optimization, environmental performance, and design adaptability. Nevertheless, the inherently sequential and interdependent nature of the full construction process—encompassing off-site component manufacturing, logistics transportation, and on-site assembly—introduces pronounced cross-stage risk transmission mechanisms, with prefabricated components serving as critical risk carriers. Such transmission dynamics significantly impede the scalable and safe deployment of prefabricated construction. To date, scholarly efforts on construction safety in prefabricated buildings have predominantly addressed isolated, stage-specific risks, falling short in quantitatively modeling the coupled propagation of risks across stages, accommodating epistemic uncertainties and latent (i.e., unknown or unobserved) risks, and informing targeted, evidence-based mitigation strategies. To bridge this gap, this study develops a rigorous quantitative framework for assessing cross-stage risk transmission in prefabricated construction safety. Specifically, it aims to (i) uncover the structural patterns and driving mechanisms underlying inter-stage risk propagation; (ii) reduce the likelihood of safety incidents throughout the construction life cycle; and (iii) deliver actionable theoretical insights and methodological guidance for practitioners and policymakers. Methodologically, we first conduct a systematic identification of safety-critical risk factors and establish a hierarchical risk indicator system comprising three first-level dimensions and twenty second-level indicators. Second, using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, causal relationships among risk factors are clarified, while incorporating the Leaky Noisy-or Gate (LNOG) extended model to account for unknown risks. Risk data are processed using triangular fuzzy functions, and a Bayesian network (BN) topology diagram is constructed via the GeNIe 5.0 platform, forming a DEMATEL-LNOG-BN-based model for assessing cross-phase risk transmission. Finally, applying the model to an actual project—”a prefabricated construction project in Shanghai”—the study conducts a cross-phase risk transmission analysis. Through forward probability inference, backward causality tracing, sensitivity analysis, and pathway decomposition, sensitivity comparisons are performed under different LNOG unknown risk parameters. Results are compared with those from the traditional DEMATEL-BN model to validate the stability and consistency of high-sensitivity risk factor identification, comprehensively verifying the applicability and predictive reliability of the proposed DEMATEL-LNOG-BN model. The study quantitatively reveals the progressive diffusion and amplification mechanisms of risks across the production–transportation–assembly process, providing scientific support and practical reference for precise safety risk prevention, critical node control, and the optimization of management systems in prefabricated construction sites. Full article

Liquid biopsy has evolved beyond its original role as a minimally invasive approach for mutation detection and is now being developed as a broader analytical framework for cancer detection, stratification, and longitudinal monitoring. Improvements in next-generation sequencing, assay chemistry, and computational analysis have increased analytical sensitivity, including in settings with low tumor fraction and very low variant allele abundance. These advances have expanded the utility of cfDNA analysis in measurable residual disease assessment and in the detection of low-abundance tumor-derived signals across multiple clinical contexts. At the same time, the field has shifted toward interpreting cfDNA as a carrier of higher-order biological information rather than solely a substrate for mutation calling. Fragmentation profiles, nucleosome positioning, and chromatin accessibility patterns derived from plasma DNA have been used to infer transcriptional and regulatory states, raising the possibility that cfDNA may capture functional tumor states not readily accessible through genotype-focused assays alone. These developments have prompted growing interest in chromatin-informed cfDNA analysis as a means of identifying pathway activity, enhancer usage, transcription factor occupancy, and potentially actionable biological dependencies. However, the translational relevance of many such inferences remains incompletely established, and preanalytical variability, limited cross-cohort generalizability, and the gap between analytical performance and clinical utility continue to constrain clinical translation. This review examines the role of cfDNA in adaptive oncology, highlighting recent analytical advances, assessing the current evidence supporting their biological and clinical utility, and considering the extent to which cfDNA-derived regulatory inference may contribute to adaptive oncology and therapeutic decision-making. Full article