Search Results (4,683)

Background/Objectives: Global estimates suggest that approximately 43% of individuals living with diabetes remain undiagnosed, underscoring the need for early identification of adults at high risk of type 2 diabetes mellitus (T2DM) to support timely preventive interventions. This scoping review aimed to map and summarize existing non-invasive screening tools for identifying adults at high risk of T2DM. Methods: PubMed (MEDLINE), Web of Science, ScienceDirect, and Scopus were searched in accordance with the PRISMA extension for Scoping Reviews (PRISMA-ScR). Studies published between 1995 and 2026 that described screening tools for adult populations were included. Results: A total of 58 studies describing screening tools were identified. The tools were developed and applied across diverse populations and ethnic groups. Most were questionnaire-based, easy to administer, and low cost. Commonly included variables comprised demographic characteristics, anthropometric measures, lifestyle factors, and clinical indicators associated with increased T2DM risk. Substantial heterogeneity was observed in tool structure and reported predictive components. Conclusions: This scoping review provides an overview of available screening tools for the early identification of adults at high risk of T2DM. The mapped evidence may inform future validation studies and support context-specific implementation in public health and clinical practice settings, including integration into digital platforms. Full article

This paper introduces D³O-GT, a distributed optimization framework designed to operate under partial, heterogeneous, and delayed information—conditions commonly encountered in large-scale logistics and networked decision support systems. The proposed approach integrates gradient tracking with delay-aware updates to address the steady-state bias and instability that often affect classical distributed gradient methods. We formulate a consensus optimization model that captures decentralized decision variables while preserving global optimality, and we develop an algorithmic structure that balances convergence accuracy, communication efficiency, and robustness to asynchronous updates. Extensive numerical experiments demonstrate that D³O-GT achieves machine precision convergence in synchronous settings and remains stable under bounded communication delays, converging to a small neighborhood of the optimum. In contrast, conventional distributed gradient descent exhibits significant residual error under the same conditions. Scalability analyses further indicate that the proposed method maintains favorable iteration complexity as the number of agents increases. These results position D³O-GT as a practical and scalable solution for distributed decision-making environments, with direct relevance to logistics-oriented applications such as resource allocation, coordination of networked services, and real-time operational planning. Full article

With the increasing importance of securing quantum communication networks, practical and robust entity authentication is a critical requirement. Accordingly, we propose and experimentally validate a quantum entity authentication (QEA) protocol specifically designed for integration with BB84-type quantum key distribution (QKD) workflows and existing terminal architectures. We analyze the protocol’s security against intercept–resend man-in-the-middle (MitM) impersonation, showing that an unauthenticated adversary induces a characteristic 25% correlation error and that the rejection probability approaches unity as the number of detected authentication events increases. For practical realization, the protocol is deployed using weak coherent pulses (WCPs) with decoy-state estimation to bound single-photon contributions and mitigate photon-number-splitting (PNS)-enabled leakage. The system is demonstrated over a field-deployed fiber link of approximately 20 km with ~8 dB optical loss using signal/decoy intensities of ~0.5/~0.15 and sending probabilities 0.88/0.10/0.02 (signal/decoy/vacuum). Across both verification directions, stable operation is observed with quantum bit error rate (QBER) typically fluctuating between 1% and 4% while the sifted key rate remains constant over time. These results provide an experimental basis for integrating physical-layer entity authentication into deployed quantum communication networks. Full article

Global citrus exports rely heavily on temperature-controlled logistics to safeguard fruit quality and minimise postharvest losses. Temperature management remains a critical factor governing citrus quality throughout export logistics. Yet the extent to which historical shipment temperature data can meaningfully predict fruit condition at arrival has never been systematically assessed. This study presents a comprehensive review of how historical temperature records have been used to assess citrus quality within export supply chains, highlighting the lack of longitudinal temperature–quality correlations in existing research. Using PRISMA 2020 guidelines and Kitchenham’s three-phase review framework, 35 relevant peer-reviewed articles published between 2013 and 2025 were analysed. Bibliometric mapping identified dominant research concentrations in experimental cold chain studies and simulation-based approaches, with emerging themes around digital twins and virtual cold chain technologies. The review shows that current research predominantly employs controlled experimental designs and computational simulations to quantify temperature-driven deterioration, including chilling injury, decay rate, and weight loss. Although real-time temperature monitoring in commercial shipments is emerging, temperature deviations are rarely assessed alongside direct quality metrics. Although several studies have examined shipment temperatures alongside arrival-quality outcomes, these analyses are generally limited in duration, scope, or sensor resolution. Consequently, rigorous, multi-year, longitudinal datasets that pair detailed shipment temperature histories with standardised fruit-quality assessments remain largely unavailable, constraining the empirical validation of temperature–quality relationships in real export conditions. This gap significantly limits predictive capability in real-world export contexts. The review highlights the urgent need for a coordinated, long-term data infrastructure that integrates temperature and quality measurements across global citrus supply chains. Establishing such datasets, particularly in major exporting regions such as South Africa, would enable more robust modelling of temperature impacts, support the optimisation of cold chain practices, and contribute to international food loss-reduction goals. Full article

The ability to autonomously navigate and explore complex 3D environments in a purposeful manner, while integrating visual perception with natural language interaction in a human-like way, represents a longstanding research objective in Artificial Intelligence (AI) and embodied cognition. Vision-Language Navigation (VLN) has evolved from geometry-driven to semantics-driven and, more recently, knowledge-driven approaches. With the introduction of Large Language Models (LLMs) and Vision-Language Models (VLMs), recent methods have achieved substantial improvements in instruction interpretation, cross-modal alignment, and reasoning-based planning. However, existing surveys primarily focus on traditional VLN settings and offer limited coverage of LLM-based VLN, particularly in relation to Sim2Real transfer and edge-oriented deployment. This paper presents a structured review of LLM-enabled VLN, covering four core components: instruction understanding, environment perception, high-level planning, and low-level control. Edge deployment and implementation requirements, datasets, and evaluation protocols are summarized, along with an analysis of task evolution from path-following to goal-oriented and demand-driven navigation. Key challenges, including reasoning complexity, spatial cognition, real-time efficiency, robustness, and Sim2Real adaptation, are examined. Future research directions, such as knowledge-enhanced navigation, multimodal integration, and world-model-based frameworks, are discussed. Overall, LLM-driven VLN is progressing toward deeper cognitive integration, supporting the development of more explainable, generalizable, and deployable embodied navigation systems. Full article

Minimal residual disease (MRD) refers to the persistence of low-level malignant cells or tumor-derived nucleic acids that remain after curative-intent therapy and are undetectable by conventional diagnostic methods. In oncology, MRD has emerged as a powerful biomarker with well-established prognostic value in hematologic malignancies and rapidly expanding relevance in solid tumors. Advances in sensitive detection technologies, including multiparameter flow cytometry, quantitative real-time polymerase chain reaction, next-generation sequencing, and digital polymerase chain reaction, have enabled the identification of residual disease at the molecular level, often preceding clinical or radiological relapse. Beyond its conventional role as a binary indicator of treatment response or cure, MRD is increasingly recognized as a dynamic longitudinal biomarker that supports personalized disease management. Within this evolving paradigm, patient-informed MRD strategies that incorporate tumor-specific molecular profiling and serial monitoring, particularly through circulating tumor DNA, offer the potential to guide treatment adaptation, including escalation, de-escalation, maintenance optimization, and surveillance strategies across both hematologic and solid malignancies. In this review, we summarize the biological basis of MRD, current and emerging detection methodologies, and clinical applications across cancer types, with a focus on patient-informed approaches. We also discuss key limitations, including assay standardization, biological variability in solid tumors, and the lack of clearly defined actionability thresholds. Finally, we highlight future directions for integrating MRD with multi-omics and AI-driven analytical frameworks to enable adaptive, risk-informed cancer management and advanced precision oncology. Full article

The Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) is the vector of the devastating citrus disease Huanglongbing, posing a significant threat to the global citrus industry and necessitating environmentally sound management strategies. This study aimed to evaluate Australian tea tree oil (TTO) and its primary constituents as potential botanical insecticides. Gas chromatography-mass spectrometry (GC-MS) was performed to analyze the chemical profile of commercial TTO, and behavioral effects on D. citri adults were assessed using a Y-tube olfactometer. Direct spray bioassays were conducted to determine contact toxicity. A total of 12 compounds were identified, with TTO being a Terpinen-4-ol chemotype, dominated by Terpinen-4-ol (40.62%), γ-Terpinene (21.46%), and α-Terpinene (10.45%). TTO demonstrated potent, concentration-dependent repellency, achieving 100% repellency at 10 g/L. In contrast, Terpinen-4-ol alone was attractive to psyllids at low concentrations, suggesting synergistic or masking effects within the complex oil blend. TTO and its major constituents also exhibited significant dose- and time-dependent contact toxicity. Although the 72 h LC₅₀ of TTO (19.18 g/L) indicates lower potency compared to conventional insecticides (0.59–1.23 g/L), its combined repellent and toxic properties make it a promising candidate for integrated pest management (IPM) programs aimed at controlling D. citri and mitigating insecticide resistance. Full article

Background/Objectives: Hemodynamic monitoring is essential for guiding appropriate treatment by assessing cardiac output and volume status, as well as for preventing complications associated with excessive fluid administration. The EdgeFlow CW10 Plus is a device that extends conventional hemodynamic monitoring by incorporating pulmonary abnormality surveillance through B-line detection. This study aimed to evaluate whether the hemodynamic monitoring and pulmonary monitoring functions are well integrated, and verify the usability and efficiency of the system. Methods: A usability test was conducted with a panel of 15 medical professionals from diverse specialties and varying levels of clinical experience. Data from satisfaction surveys, heat maps, the System Usability Scale (SUS), and the NASA-TLX were analyzed to determine whether usability differences existed based on the duration of clinical experience. Results: The device demonstrated a high overall task success rate, averaging 93.2%. Regarding eye-tracking analysis based on clinical experience, it was observed that participants with more years of experience either failed to direct their gaze toward task-relevant user interface (UI) elements as effectively as those with fewer years of experience or showed similar patterns. Conclusions: The usability evaluation confirmed that the hemodynamic and pulmonary monitoring functions of the EdgeFlow CW 10 PLUS are well integrated, with the device demonstrating high usability and satisfaction. This integration is expected to support medical professionals in monitoring cardiac output and fluid status, facilitating timely therapeutic interventions while preventing complications related to fluid overload. Full article

Climate-related economic losses across Europe have evolved from isolated environmental shocks to persistent, structurally embedded fiscal risks, posing a direct challenge to the long-term fiscal sustainability of European states. This study presents an empirical framework for diagnosing and quantifying this transformation across 38 European countries between 1980 and 2023. Combining regime-switching time-series models with a two-part panel design, we identify temporal shifts and spatial asymmetries in loss exposure. Our findings reveal the emergence of a high-loss regime from the early 2000s, alongside a widening inequality in national vulnerability, with countries such as France, Germany, Italy, and Spain bearing a disproportionate burden. This concentration raises critical questions about the sustainability and equity of current EU risk-sharing frameworks. The two-part model further disaggregates the probability of experiencing losses from their conditional magnitude, enabling country-level estimates of expected annual losses. These results highlight the limitations of current fiscal instruments, which remain reactive and fail to align with the spatial and temporal dynamics of climate risk. We argue for a shift from climate loss management to climate loss governance, underpinned by predictive analytics, differentiated policy tools, and a reorientation of EU fiscal solidarity mechanisms. By quantifying, measuring, and spatially disaggregating climate-related fiscal exposure, this study contributes directly to the sustainability agenda: it demonstrates that climate losses are no longer exogenous disruptions but endogenous features of the European economic landscape that must be integrated into sustainable development planning, fiscal governance, and EU-level adaptation policy. Full article

Chronic crop diseases caused by uncultured, obligate, or host-dependent pathogens challenge traditional pathogen-centric paradigms that often interpret symptoms as direct outcomes of pathogen toxins, effectors, or tissue colonization. Here, we advance a host-centric immune framework that reframes disease as an emergent consequence of dysregulated host immune network activity, including prolonged activation, signaling miscoordination, and systemic physiological disruption. Using citrus huanglongbing (HLB) as a primary exemplar and canola clubroot as a parallel system, we synthesize evidence that persistent immune stimulation can drive self-damaging outputs, including sustained reactive oxygen species accumulation, chronic vascular and transport dysfunction, hormone imbalance, and growth–defense trade-offs. While many observations derive from transcriptomic, physiological, and genetic studies conducted under controlled experimental conditions, the available evidence collectively suggests that persistent immune activation may contribute substantially to disease-associated decline in these systems. We argue that pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) operate as an integrated immune network whose feedback structure can become destabilized under chronic infection, generating immune states that are simultaneously harmful and often ineffective at pathogen clearance. We further discuss how panomic profiling, spatially resolved analyses, and network inference can diagnose host immune states at tissue and cell-type resolution, and how genome editing enables causal tests and rational immune tuning strategies that optimize defense amplitude, timing, and localization rather than indiscriminately amplifying resistance. By centering the host immune system as both a source of protection and pathology, this framework provides a conceptual and practical roadmap for understanding and engineering resilience in HLB, clubroot, and other chronic crop diseases in which pathogen biology remains experimentally opaque. Full article

In this paper, we construct a probabilistic model of a sliding mode. This model is based on the moment a random walk with positive jumps crosses a certain critical level. It is assumed that the jump magnitude has a geometric distribution. If the initial state is negative and the critical level is zero, then after crossing this level, a random walk begins in the opposite direction until it crosses zero again. As a result, motion orthogonal to the slip line is defined as a regenerative process, in which the moments of regeneration are the moments of zero crossings from right to left. An estimate of the Qi Fan metric of the maximum deviation of this random walk over a certain time interval is constructed under the assumption that the time and magnitude of the jumps are reduced by a factor of m. This estimate is found to be of the order of $lnm/m$ as $m\to \infty$ and characterizes the deviation of a random trajectory orthogonal to the slip line. In the model of motion along a slip line, its velocity is assumed to have fixed values when the trajectory of motion orthogonal to the slip line is above or below zero. Using the central limit theorem for the integral of a regenerative process, an estimate of the non-uniformity of motion of a random trajectory along the slip line is constructed. It is found that the characteristic magnitude of this non-uniformity is of the order of $1/m$ as $m\to \infty$. This indicates that the accumulation of random errors during motion along the slip line is significantly faster than during motion orthogonal to the slip line. Full article

The Jiaodong gold concentration area, one of the most important gold metallogenic belts in China, has long been the focus of contentious debates regarding the genetic mechanisms and timing of gold mineralization. This study presents the new monazite U-Pb and pyrite Rb-Sr isotopic chronology data for the No. I ore zone of the Xidouya gold deposit, integrated with H-O-S isotopic geochemical analyses, to systematically investigate the mineralization age, ore-forming fluid sources and material provenance of the deposit. The main mineralization age of the deposit is constrained to 117 Ma, which is highly consistent with the regional mineralization peak of 120 ± 5 Ma in the Jiaodong gold concentration area. The δD values of the fluids range from −88.0‰ to −75.0‰ (mean = −82.6‰), while the δ¹⁸O_H2O values are calculated to be between 4.6‰ and 6.1‰. H-O isotopic data indicate that the ore-forming fluids of the Xidouya gold deposit originated from a mixed magmatic and meteoric source. As mineralization progressed from Stage I through Stage III, there was a detectable trend of increasing meteoric water involvement and a general decrease in δD and δ¹⁸O_H2O values. This signature indicates that the initial mineralizing system was dominated by primary magmatic water which subsequently underwent significant water–rock interaction with Early Cretaceous granitic bodies and progressive dilution by meteoric fluids in an open tectonic environment. Furthermore, sulfur isotopes (average δ³⁴S = +7.43‰) and the initial strontium isotope ratio (⁸⁷Sr/⁸⁶Sr = 0.71012) support a mixed-source model for the ore-forming materials, likely dominated by the anatexis of ancient crust with potential minor mantle-derived contributions. During the Early Cretaceous, lithospheric thinning and extension in the North China Craton (NCC) triggered large-scale magmatism and mineralization. The Xidouya gold deposit is a direct product of these regional tectono-magmatic-mineralizing events. This study provides new high-precision isotopic dating data for the Xidouya gold deposit, clarifies the evolutionary history of ore-forming fluids and the supply mechanism of ore-forming materials, and provides important theoretical insights and practical references for gold prospecting and exploration in the eastern part of the Jiaodong gold concentration area. Full article

The Tianshan–Pamir mountain region, serving as the core “water tower” for countries in Central Asia east of the Aral Sea, is a critical bulwark for sustaining downstream socioeconomic systems. However, constrained by complex topography and harsh climatic conditions, this region suffers from a severe scarcity of long-term, continuous hydrological observation data. This study focuses on a typical data-scarce mountainous area, coupling UAV and satellite imagery-based (e.g., Landsat/Sentinel) flow inversion with a hybrid spatial regionalization method—integrating spatial proximity, basin similarity, and regression-based hydrograph reconstruction—to quantitatively estimate long-term discharge time series. The results indicate that, for the validation of instantaneous discharge inversion, the Nash–Sutcliffe efficiency coefficient (NSE) at 29 river cross-sections was consistently greater than 0.80, with the coefficient of determination (R²) reached 0.94 (p < 0.01). Subsequently, for the long-term discharge series reconstructed using the regionalization method, the NSE values at three representative verification sites—each corresponding to a distinct basin type—were 0.88, 0.84, and 0.86, respectively. These findings exhibit higher precision compared to direct temporal upscaling, confirming the reliability of the regionalization method across varying temporal scales. An analysis of monthly discharge trends from 1989 to 2020 revealed a decreasing trend in the discharge of glacier-dominated rivers, with an average rate of change of −2.89 ± 2.54% (p < 0.05); the Pamir Plateau experienced the largest decline (−4.89 ± 6.58%), which is closely linked to large-scale glacial retreat within the basins. Conversely, the discharge of non-glacier-dominated rivers showed an increasing trend, with a multi-year average rate of change of +0.32 ± 8.43% (n.s.), primarily driven by shifts in precipitation and vegetation cover. This research introduces a new approach for hydrological monitoring in data-scarce regions and provides essential data and methodological support for water resource management decisions in arid zones. Full article

It is of great significance in real time to accurately monitor the internal state parameters of lithium-ion batteries toy ensure the safety, reliability and lasting efficiency of battery energy storage systems. The battery management system can monitor the working state, prevent overcharge or overdischarge, and make the working process more safe and reliable. The state of charge (SOC) is one of the most important indicators to monitor a working battery, and its accurate estimation is the most important work at present. SOC cannot be measured directly, so the state estimation problem of batteries is transformed into a state estimation problem of time-varying nonlinear systems, the core of which is how to obtain a more accurate and reasonable state estimation value in real time. This paper introduces the definition of battery charge state, summarizes common estimation methods and disadvantages of the ampere-hour integration method and open-circuit voltage method, and finally points out the future development direction of battery charge state estimation methods. Full article

Proton exchange membrane fuel cells (PEMFCs) play a key role in hydrogen-based energy systems; however, accurate and practical modelling remains challenging due to system nonlinearities, parameter variability, and degradation effects. This paper presents a low-complexity parameter estimation methodology for a simplified PEMFC equivalent circuit model using current-switching techniques. The approach enables direct extraction of key parameters, including internal resistance and capacitance, from transient voltage responses without requiring complex optimization or large datasets. Experimental validation was conducted using 100 W and 1 kW PEMFC systems under current loading and interruption conditions. The results demonstrate good agreement between measured and simulated voltage responses, with a maximum error below 10% and typical error levels in the range of ~1.4–3%. Compared to conventional mechanistic and data-driven models, the proposed method significantly reduces computational complexity and measurement requirements while maintaining high predictive accuracy. Moreover, the combination of the simplified equivalent circuit model with current-switching-based parameter estimation offers an effective and practical tool for electrical engineers, enabling real-time monitoring, control-oriented modelling, and seamless integration with power electronic systems. The proposed approach is particularly suitable for applications in DC microgrids and digital twin-based monitoring of hydrogen energy systems. Full article