Search Results (240)

This study aimed to analyse the spatiotemporal evolution of phytoplankton community dynamics and its underlying mechanisms in the Liaoning section of the Liao River Basin in 2010, 2015, and 2020. Phytoplankton species diversity increased significantly, with an increase from three phyla and 31 species in 2010 to six phyla and 74 species in 2020. Concurrent increases in α-diversity indicated continuous improvements in habitat heterogeneity. The community structure shifted from a diatom-dominated assemblage to a green algae–diatom co-dominated configuration, contributing to an enhanced water purification capacity. The upstream agricultural zone (Tieling section) had elevated biomass and low diversity, indicating persistent non-point-source pollution stress. The midstream urban–industrial zone (Shenyang–Anshan section) emerged as a phytoplankton diversity hotspot, likely due to expanding niche availability in response to point-source pollution control. The downstream wetland zone (Panjin section) exhibited significant biomass decline and delayed diversity recovery, shaped by the dual pressures of resource competition and habitat filtering. The driving mechanism of community succession shifted from nutrient-dominated factors (NH₃-N, TN) to redox-sensitive factors (DO, pH). These findings support a ‘zoned–graded–staged’ ecological restoration strategy for the Liao River Basin and inform the use of phytoplankton as bioindicators in watershed monitoring networks. Full article

Wormholes are non-trivial topological structures that arise as exact solutions to Einstein’s field equations, theoretically connecting distinct regions of spacetime via a throat-like geometry. While static traversable wormholes necessarily require exotic matter that violates the classical energy conditions, subsequent studies have sought to minimize such violations by introducing time-dependent geometries embedded within cosmological backgrounds. This review provides a comprehensive survey of evolving wormhole solutions, emphasizing their formulation within both general relativity and alternative theories of gravity. We explore key developments in the construction of non-static wormhole spacetimes, including those conformally related to static solutions, as well as dynamically evolving geometries influenced by scalar fields. Particular attention is given to the wormholes embedded into Friedmann–Lemaître–Robertson–Walker (FLRW) universes and de Sitter backgrounds, where the interplay between the cosmic expansion and wormhole dynamics is analyzed. We also examine the role of modified gravity theories, especially in hybrid metric–Palatini gravity, which enable the realization of traversable wormholes supported by effective stress–energy tensors that do not violate the null or weak energy conditions. By systematically analyzing a wide range of time-dependent wormhole solutions, this review identifies the specific geometric and physical conditions under which wormholes can evolve consistently with null and weak energy conditions. These findings clarify how such configurations can be naturally integrated into cosmological models governed by general relativity or modified gravity, thereby contributing to a deeper theoretical understanding of localized spacetime structures in an expanding universe. Full article

This study explores the use of embedded piezo sensor (EPS) employing the Electro-Mechanical Impedance (EMI) technique for real-time corrosion monitoring in reinforced E-waste concrete exposed to chloride-laden environments. With the growing environmental concerns over electronic waste (E-waste) and the demand for sustainable construction practices, printed circuit board (PCB) materials were incorporated as partial replacements for coarse aggregates in concrete. The experiment utilized M30-grade concrete mixes, substituting 15% of natural coarse aggregates with E-waste, aiming to assess both sustainability and structural performance without compromising durability. EPS configured with Lead Zirconate Titanate (PZT) patches were embedded into both conventional and E-waste concrete specimens. The EPS monitored the changes in the form of conductance and susceptance signatures across a 100–400 kHz frequency range during accelerated corrosion exposure over a 60-day period in a 3.5% NaCl solution. The corrosion progression was evaluated qualitatively through electrical impedance signatures, visually via rust formation and cracking, and quantitatively using the Root Mean Square Deviation (RMSD) of EMI signatures. The results showed that the EMI technique effectively captured the initiation and propagation stages of corrosion. E-waste concrete exhibited earlier and more severe signs of corrosion compared to conventional concrete, indicated by faster increases and subsequent declines in conductance and susceptance and higher RMSD values during the initiation phase. The EMI-based system demonstrated its capability to detect microstructural changes at early stages, making it a promising method for Structural Health Monitoring (SHM) of sustainable concretes. The study concludes that while the use of E-waste in concrete contributes positively to sustainability, it may compromise long-term durability in aggressive environments. However, the integration of EPS and EMI offers a reliable, non-destructive, and sensitive technique for real-time corrosion monitoring, supporting preventive maintenance and improved infrastructure longevity. Full article

Steel lazy wave risers (SLWRs) are critical in offshore hydrocarbon transport for linking subsea wells to floating production facilities in deep-water environments. The incorporation of buoyancy modules reduces curvature-induced stress concentrations in the touchdown zone (TDZ); however, extended operational exposure under cyclic environmental and operational loads results in repeated seabed contact. This repeated interaction modifies the seabed soil over time, gradually forming a trench and altering the riser configuration, which significantly impacts stress patterns and contributes to fatigue degradation. Accurately reconstructing the riser’s evolving profile in the TDZ is essential for reliable fatigue life estimation and structural integrity evaluation. This study proposes a simulation-based framework for the autonomous tracking of SLWRs using a fin-actuated autonomous underwater vehicle (AUV) equipped with a monocular camera and multibeam echosounder. By fusing visual and acoustic data, the system continuously estimates the AUV’s relative position concerning the riser. A dedicated image processing pipeline, comprising bilateral filtering, edge detection, Hough transform, and K-means clustering, facilitates the extraction of the riser’s centerline and measures its displacement from nearby objects and seabed variations. The framework was developed and validated in the underwater unmanned vehicle (UUV) Simulator, a high-fidelity underwater robotics and pipeline inspection environment. Simulated scenarios included the riser’s dynamic lateral and vertical oscillations, in which the system demonstrated robust performance in capturing complex three-dimensional trajectories. The resulting riser profiles can be integrated into numerical models incorporating riser–soil interaction and non-linear hysteretic behavior, ultimately enhancing fatigue prediction accuracy and informing long-term infrastructure maintenance strategies. Full article

With the growing demand for labeled textual data in Natural Language Processing (NLP), traditional data collection and annotation methods face significant challenges, such as high cost, limited scalability, and privacy constraints. This study presents a novel web-based platform that automates text data generation and labeling by integrating Llama 3.3, an open-source large language model (LLM), with advanced prompt engineering techniques. A core contribution of this work is the Attributed Prompt Engineering Framework, which enables modular and configurable prompt templates for both data generation and labeling tasks. This framework combines zero-shot, few-shot, role-based, and chain-of-thought prompting strategies within a unified architecture to optimize output quality and control. Users can interactively configure prompt parameters and generate synthetic datasets or annotate raw data with minimal human intervention. We evaluated the platform using both benchmark datasets (AG News, Yelp, Amazon Reviews) and two fully synthetic datasets we generated (restaurant reviews and news articles). The system achieved 99% accuracy and F1-score on generated news article data, 98% accuracy and F1-score on generated restaurant review data, and 92%, 90%, and 89% accuracy and F1-scores on the benchmark labeling tasks for AG News, Yelp Reviews, and Amazon Reviews, respectively, demonstrating high effectiveness and generalizability. A usability study also confirmed the platform’s practicality for non-expert users. This work advances scalable NLP data pipeline design and provides a cost-effective alternative to manual annotation for supervised learning applications. Full article

In this work, we undertake a comprehensive study of the functional measure of gravitational path integrals within a general framework involving non-trivial configuration spaces. As in Riemannian geometry, the integration over non-trival configuration spaces requires a metric. We examine the interplay between the functional measure and the dynamics of spacetime for general configuration-space metrics. The functional measure gives an exact contribution to the effective action at the one-loop level. We discuss the implications and phenomenological consequences of this correction, shedding light on the role of the functional measure in quantum gravity theories. In particular, we describe a mechanism in which the graviton acquires a mass from the functional measure without violating the diffeomorphism symmetry nor including Stückelberg fields. Since gauge invariance is not violated, the number of degrees of freedom goes as in general relativity. For the same reason, Boulware–Deser ghosts and the vDVZ discontinuity do not show up. The graviton thus becomes massive at the quantum level while avoiding the usual issues of massive gravity. Full article

This study numerically examines laminar natural convection within a square cavity that has a horizontally attached adiabatic fin on its heated vertical wall. The analysis employed the finite element method to investigate how fin position, length, thickness, and thermal conductivity affect heat transfer behavior over a broad spectrum of Rayleigh numbers (Ra = 10 to 10⁶) and Prandtl numbers (Pr = 0.1 to 10). The findings indicate that the geometric configuration and the properties of the fluid largely influence the thermal disturbances caused by the fin. At lower Ra values, conduction is the primary mechanism, resulting in minimal impact from the fin. However, as Ra rises, convection becomes increasingly significant, with the fin positioned at mid-height (Y_fin = 0.5), significantly improving thermal mixing and flow symmetry, especially for high-Pr fluids. Extending the fin complicates vortex dynamics, whereas thickening the fin improves conductive heat transfer, thereby enhancing convection to the fluid. A new fluid-focused metric, the normalized Nusselt ratio (NNR), is introduced to evaluate the true thermal contribution of fin geometry beyond area-based scaling. It exhibits a non-monotonic response to geometric changes, with peak enhancement observed at high Ra and Pr. The findings provide practical guidance for designing passive thermal management systems in sealed enclosures, such as electronics housings, battery modules, and solar thermal collectors, where active cooling is infeasible. This study offers a scalable reference for optimizing natural convection performance in laminar regimes by characterizing the interplay between buoyancy, fluid properties, and fin geometry. Full article

This study presents a unique and comprehensive application of ANSYS Mechanical R19.2’s SMART crack growth feature, leveraging its capabilities to conduct an unprecedented parametric investigation into fatigue crack propagation behavior under a wide range of positive and negative stress ratios, and to provide detailed insights into the influence of hole positioning on crack trajectory. By uniquely employing an unstructured mesh method that significantly reduces computational overhead and automates mesh updates, this research overcomes traditional fracture simulation limitations. The investigation breaks new ground by comprehensively examining an unprecedented range of both positive (R = 0.1 to 0.5) and negative (R = −0.1 to −0.5) stress ratios, revealing previously unexplored relationships in fracture mechanics. Through rigorous and extensive numerical simulations on two distinct specimen configurations, i.e., a notched plate with a strategically positioned hole under fatigue loading and a cracked rectangular plate with dual holes under static loading, this work establishes groundbreaking correlations between stress parameters and fatigue behavior. The research reveals a novel inverse relationship between the equivalent stress intensity factor and stress ratio, alongside a previously uncharacterized inverse correlation between stress ratio and von Mises stress. Notably, a direct, accelerating relationship between stress ratio and fatigue life is demonstrated, where higher R-values non-linearly increase fatigue resistance by mitigating stress concentration, challenging conventional linear approximations. This investigation makes a substantial contribution to fracture mechanics by elucidating the fundamental role of hole positioning in controlling crack propagation paths. The research uniquely demonstrates that depending on precise hole location, cracks will either deviate toward the hole or maintain their original trajectory, a phenomenon attributed to the asymmetric stress distribution at the crack tip induced by the hole’s presence. These novel findings, validated against existing literature, represent a significant advancement in predictive modeling for fatigue life assessment, offering critical new insights for engineering design and maintenance strategies in high-stakes industries. Full article

The increase in temperature in the built environment impedes the utilization of outdoor amenities and non-motorized transportation by residents of Arabian Gulf cities throughout the prolonged hot season. The urban heat island (UHI) phenomenon, denoted by the substantial temperature difference between the city and its periphery, is associated with multiple parameters. Building heights, setbacks, and configurations influence the temperature within street canyons. Nowadays, it is vital for urban designers to understand the role of these parameters in UHI effect, and translate those insights into design guidelines and urban forms they propose. This study delves into the relationship between building geometry and urban heat island effects in the context of Doha City, using residential building areas as the basis for comparison. Using dual-pronged methodology, the study entails simulating the dry bulb temperature and the sky view factor, alongside field measurements for land surface temperature (LST), across two residential zones within the city. This analytical approach integrates both prescribed building regulations and the physical characteristics of the extant urban fabric and configuration. Climate data were collected from the weather station in the format of EnergyPlus weather data, and LST historical data were collected from satellite imagery datasets. The results show a correlation between building geometry and UHI-related metrics, particularly evident during nocturnal periods. Notably, a negative correlation was found between the sky view factor and temperature increments. The study concludes with a strong correlation between building geometry and UHI, underscoring the imperative of integrating the building geometry and configuration considerations within the broader context of urban environmental assessments. While similar studies have been undertaken in different regions, there is a research gap in UHI within the GCC region. This study aims to contribute valuable insights to understanding urban heat island dynamics in Gulf cities. Full article

The digitalization of rural areas has emerged as a crucial strategy for promoting economic development, yet the phenomenon of “digital suspension” poses a challenge, where the lack of digital integration in certain sectors may hinder economic progress. This study delves into this issue by identifying multiple configurations that drive county-level economic growth. More specifically, this study aims to explore how rural digitalization contributes to county-level economic growth through different combinations of environmental and subject-level factors. To address this issue, this study applies the fuzzy-set qualitative comparative analysis method, guided by systems thinking and ecological systems theory. The analysis is based on 89 case samples selected from China’s digital village pilot counties, using data from the China County-level Digital Rural Index Research Report jointly released by Peking University and Ali Research Institute, published in 2022, and other county-level statistical data. The study explores the complex causal mechanisms and configuration paths through which rural digitalization empowers county-level economic growth. This study found that (1) the conditions necessary to generate high county-level economic growth do not exist in the process of rural digitalization (at least not within the digital village pilot); (2) four configurations facilitate high county-level economic growth: digital governance-led configuration, dual promotion of digital governance and digital infrastructure, dual promotion of digital life and digital infrastructure, and dual promotion of digital life and digital economy; and (3) two configurations yield non-high county-level economic growth and exhibit asymmetrical relationships with those configurations conducive to high growth. These research findings not only broaden the application of systems thinking and ecological systems theory in the realm of rural digitalization but also offer practical insights into strategies for enhancing county-level economic growth. Full article

Polyomaviruses have the potential to cause significant morbidity not only in transplant medicine, but also in other forms of disease or variants of immunosuppression. In kidney transplant recipients or recipients of human stem cell transplants, the BK-Virus is the major proponent of manifestations such as BKPyV-associated nephropathy or hemorrhagic cystitis. As no polyomavirus-specific drug with proven in vivo effects has been developed so far, methods to screen for such drugs are important. This work describes the establishment of a virus-secreting cell line. By infecting a pre-established monkey kidney cell line (COS-1) with a non-rearranged human BK polyomavirus isolated from a kidney transplant patient suffering from BKPyV-associated nephropathy, a continuously replicating cell type with consistent virus secretion could be established and was termed COSSA. Measurements of BKPyV replication, virion production, and secretion were performed both intracellularly and in the cell supernatant. Viral proteins such as VP1 and LTAg were accurately tracked by confocal microscopy, as well as by immunoblot and qPCR. An intracellular flow cytometry (FACS) assay detecting VP1 protein was established and revealed an expanded range of positive intracellular signals. The viruses produced proved to be infectious in human tubular epithelial cell lines. Long-range sequencing of the COSSA genome using Oxford Nanopore Technology revealed a total of five distinct BKPyV integration events. One integration of a partial BKPyV genome was located upstream of the epidermal growth factor receptor gene. The second and third, both truncated forms of integration, were close to histocompatibility gene locuses, while the fourth was characterized by a ninefold and the fifth by a fourfold tandem repeat of the BKPyV genome. From both of the repeat forms, virus replicates were derived showing deletions/duplications on early and late genes and inversions within the non-coding control region (NCCR). This pattern of repetitive viral genome integration is a potential key driver of enhanced viral replication and increased virion assembly, ultimately supporting efficient virus egress. Quantitative PCR analysis confirmed the release of approximately 10⁸/mL viral units per 48 h from 2 × 10⁵ COSSA cells into the culture supernatant. Notably, the NCCR region of the most frequent copies of circular virus and the integrated tetrameric tandem repeat exhibited a rearranged configuration, which may contribute to the observed high replication dynamics. The establishment of a consistent methodology to generate and secrete BKPyV from a cell line is expected to significantly facilitate antiviral drug development. Full article

Constraint satisfaction problems (CSPs) are widely used in domains such as product configuration, scheduling, and resource allocation. However, formulating constraint models remains a significant challenge that often requires specialized expertise in constraint programming (CP). This study introduces the Automatic Constraint Model Generator (ACMG), a novel framework that leverages fine-tuned large language models (LLMs) to automate the translation of natural language problem descriptions into formal CSP models. The ACMG employs a multi-step process involving semantic entity extraction, constraint model generation, and iterative validation using the MiniZinc solver. Our approach achieves state-of-the-art (SOTA) or near-SOTA results, demonstrating the viability of LLMs in simplifying the adoption of CP. Its key contributions include a high-quality dataset for fine-tuning, a modular architecture with specialized LLM components, and empirical validation which shows its promising results for complex configuration tasks. By bridging the gap between natural language and formal constraint models, the ACMG significantly lowers the barrier to CP, making it more accessible to non-experts while maintaining a high level of robustness for industrial applications. Full article

The advent of digital mining has become a tangible reality in recent years. This digital evolution requires a predictive understanding of key elements, particularly considering the reliable communication infrastructures needed for autonomous machines. The LoRa technology and its underground propagation behavior can make an important contribution to this digitalization. Since LoRa operates with a high signal budget and long ranges in sub-GHz frequencies, its behavior is very promising for underground sensor networks. The aim of the development and series of measurements was to observe LoRa’s applicability and propagation behavior in active salt mines and to detect and identify effects arising from the special environment. The propagation of LoRa was measured via packet loss and signal strength in line-of-sight and non-line-of-sight configurations over entire mining sections. The aim was to analyze the performance of LoRa at the macroscopic level. LoRa operated at 868 MHz in the free band, and units were equipped with omni-directional antennas. The K+S Group’s active salt and potash mine Werra, Germany, was kindly opened as a distinctive experimental setting. The LoRa exhibited characteristics that were highly distinctive in this environment. The presence of the massive salt allowed the signal to bounce along drift edges with near-perfect reflection, which enabled travel over kilometers due to a waveguide-like effect. A packet loss of below $15\%$ showed that LoRa communication was possible over distances exceeding 1000 m with no line-of-sight in room-and-pillar structures. Measured differences of $\Delta 50\mathrm{dBm}$ values confirmed consistent path loss across different materials and tunnel geometries. This effect occurs due to the physical structure of the mining drifts, facilitating the containment and direction of signals, minimizing losses during propagation. Further modeling and measurements are of great interest, as they indicate that LoRa can achieve even better outcomes underground than in urban or indoor environments, as this waveguide effect has been consistently observed. Full article

The prognosis for Hormonal Receptor positive-HER2-negative (HR+ HER2-negative) metastatic breast cancer (mBC) has significantly improved by advances in hormone therapies, targeted drugs, and antibody–drug conjugates (ADCs). Nevertheless, maintaining quality of life (QoL), managing symptoms, and reducing treatment-related toxicity remain essential. Background: eHealth solutions offer new opportunities to enhance patient engagement and well-being through digital tools. This paper aims to delineate the fundamental functionalities and objectives of TreC_Metha, a technologically advanced instrument to provide effective support during all care process of patients diagnosed with HR+HER2-negative mBC able to proactively change its configuration depending on the treatment line or on the intra-line treatment phase the patient undergoes, as set by the healthcare team. Methods: The TreC_Metha platform was developed through a structured, evidence-based four-phase process aimed at scalability, usability, and clinical relevance. The development began with a formal analysis of the metastatic breast cancer (mBC) care pathway using BPMN modeling to map phases, activities, and stakeholders, highlighting differences from early-stage breast cancer. This analysis informed the identification of key points where digital support could enhance care. Patient needs were assessed through a web-based questionnaire (N = 20) and two focus groups (N = 11), enabling a participatory design approach. Based on these insights, the platform’s functional and non-functional requirements were defined, leading to the design and implementation of a patient-facing mobile app and a clinical dashboard tailored to mBC-specific needs. Results: Preliminary findings from the web survey focus groups revealed significant gaps in communication and information delivery during the mBC care journey, contributing to patient anxiety and reduced confidence. Participants expressed a preference for digital and printed resources to improve understanding and facilitate interactions with healthcare providers. These insights informed the development of the TreC_Metha platform. The clinical dashboard enables real-time monitoring and decision-making, while the mobile app supports bidirectional communication, therapy adherence, and patient-reported data collection. A system prototype is currently under refinement and will undergo usability testing with a small cohort of users. Following this phase, the pilot study will evaluate the platform’s impact on QoL, aiming for a ≥10% improvement in outcome measures and contributing to a more patient-centered care model in the mBC setting. Conclusions: TreC_Metha represents an innovative tool that may enable involvement and active participation in the mBC care process for both a multidisciplinary care team of professionals and the patient, and that can be easily adapted to other cancer types and chronic diseases. Full article

Increasing reported works identify that drones could and should be sufficiently utilized to work as aerial base stations in the upcoming 6G aerial vehicular networks, for providing emergency communication and flexible coverage. Objectively, light-emitting diode (LED) based lighting devices are ubiquitously integrated into these commercially available drone platforms for the general purposes of illumination and indication. Impresively, for further enhancing and diversifying the wireless air interface capability of the above 6G aerial vehicular networks, the solid-state light emitter, especially LED-based visible light communication (VLC) technologies, is increasingly introduced and explored in the rapidly developing drone communications. However, the emerging investigation dimension of spatial light beam is still waiting for essential research attention for the LED-based drone VLC. Up to now, to the best of our knowledge, almost all LED-based drone VLC schemes are still limited to conventional Lambertian LED beam configuration and objectively reject these technical possibilities and potential value of drone VLC schemes with distinct non-Lambertian LED beam configurations. The core contribution of the study is overcoming the existing limitation of the current rigid Lambertian beam use, and comparatively investigating the performance of drone VLC with non-Lambertian LED beam configurations for future 6G aerial vehicular networks. Objectively, this work opens a novel research dimension and provides a series of valuable research opportunities for the community of drone VLC. Numerical results demonstrate that, for a typical drone VLC scenario, compared with about 6.40 Bits/J/Hz energy efficiency of drone VLC based on the baseline Lambertian LED beam configuration with the same emitted power, up to about 15.64 Bits/J/Hz energy efficiency could be provided by the studied drone VLC with a distinct non-Lambertian LED beam configuration. These results show that the spatial LED beam dimension should be further elaborately explored and utilized to derive more performance improvement of the 6G aerial vehicular networks oriented drone VLC. Full article