Search Results (2,990)

Wireless Body Area Networks (WBANs) enable real-time data collection for medical monitoring, sports tracking, and environmental sensing, driven by Internet of Things advancements. Their layered architecture supports efficient sensing, aggregation, and analysis, but energy constraints from transmission (over 60% of consumption), idle listening, and dynamic conditions like body motion hinder adoption. Challenges include minimizing energy waste while ensuring data reliability, Quality of Service (QoS), and adaptation to channel variations, alongside algorithm complexity and privacy concerns. This paper reviews recent power control mechanisms in WBANs, encompassing feedback control, dynamic and convex optimization, graph theory-based path optimization, game theory, reinforcement learning, deep reinforcement learning, hybrid frameworks, and emerging architectures such as federated learning and cell-free massive MIMO, adopting a systematic review approach with a focus on healthcare and IoT application scenarios. Achieving energy savings ranging from 6% (simple feedback control) to 50% (hybrid frameworks with emerging architectures), depending on method complexity and application scenario, with prolonged network lifetime and improved reliability while preserving QoS requirements in healthcare and IoT applications. Full article

Maritime emergency communication facilities are essential for establishing land-sea connectivity and supporting disaster rescue operations. However, current systems often struggle with slow deployment, link instability, and insufficient coverage. To overcome these limitations, this paper proposes a method utilizing aircraft equipped with communication payloads for rapid network construction in target sea areas, aiming to satisfy the dual demands of quick response and stable transmission. A critical component of this framework is the optimal selection of aircraft bases. Addressing the distinct coverage capabilities of different platforms, we construct a multi-objective optimization model for base location. This model integrates a hierarchical coverage mechanism involving multiple aircraft types and is solved using the proposed Hybrid Adaptive Multi-objective Optimization (HAMO) algorithm. Experimental validation in the Bohai Sea region demonstrates the feasibility and effectiveness of the proposed model. Full article

Accurate electricity carbon emission factors are crucial for assessing overall social carbon emissions and achieving China’s “dual carbon” goals. This paper proposes a dynamic correction model that integrates lifecycle extension, power exchange networks, and multi-time-scale decomposition to address the limitations of static carbon emission factors. The model considers factors such as power generation structure, cross-regional transmission, clean energy proportion, line losses, and non-CO₂ greenhouse gas emissions, and achieves dynamic correction at quarterly and monthly scales, enhancing timeliness and regional adaptability. Results show that transmission losses, energy structure, and inter-provincial electricity exchange significantly impact carbon emission factors. For instance, in 2022, line losses in Xinjiang and Gansu raised the electricity carbon emission factor by over 0.06 kgCO₂/kWh. Monthly factors exhibit significant seasonal fluctuations, with some regions showing variations of up to 105% of the annual average. Areas rich in hydropower, such as Yunnan, Sichuan, and Qinghai, experience pronounced fluctuations, highly sensitive to changes in water volume, offering more accurate reflections of carbon emission changes during electricity consumption. This study presents a refined dynamic correction method for electricity carbon emission accounting, providing theoretical support for carbon emission policy development and performance evaluation. Full article

Semitransparent perovskite photovoltaic (sPV) covers offer an attractive route for agrivoltaics, but their spectrally selective transmittance must be validated on plants cultivated under panel or in simulated conditions. Here, an AVA–MAPI perovskite module transmission profile was replicated using a programmable multi-channel LED platform and compared with a Reference McCree-adapted LED spectrum at identical photon flux density. Two lettuce cultivars (Lactuca sativa L.; ‘Canasta’ and ‘Trocadero’) were grown hydroponically in a light-sealed phytotron for 30 days (300 μmol m⁻² s⁻¹; 16/8 h photoperiod) under uniform temperature and humidity. Leaf gas exchange was quantified by fitting photosynthetic light-response curves, and plant performance was concurrently evaluated through growth metrics, biomass partitioning, and pigment-related traits (chlorophyll a/b, total carotenoids). The perovskite-emulated spectrum measurably reshaped net CO₂ assimilation across the PAR domain—yielding higher A_N at selected irradiances in post hoc contrasts—yet these physiological shifts did not translate into differences in leaf area, shoot or root biomass, or pigment concentrations—demonstrating spectral plasticity and agricultural compatibility of field-characterized perovskite transmission spectra. Overall, perovskite-emulated light sustained agronomically equivalent lettuce performance under moderate irradiance, supporting the feasibility of semitransparent perovskite PV covers, while underscoring the need for validation under natural sunlight. Full article

Exudative epidermitis (EE), caused by Staphylococcus hyicus, represents an issue for swine production, particularly due to antimicrobial resistance. In this project, we isolated bacteriophages using S. hyicus as host and studied them as a potential alternative to antibiotic treatment in Quebec, Canada. Three phages, STAE-4, STAF-3, and STAM-1, were isolated from swine farm samples using a single S. hyicus strain (SC366) as the host. Transmission electron microscopy revealed that all three phages exhibited a siphovirus-like morphology, and RAPD-PCR profiling indicated that the phages were genetically distinct. Whole genome sequencing confirmed these differences and showed that the three phages were closely related to each other, and, more importantly, highly similar to phages previously described as infecting Staphylococcus chromogenes, a species closely related to S. hyicus. Host range analysis confirmed that the three phages preferentially infected the S. chromogenes strains included in the study, exhibiting minimal to no lytic activity against other strains of S. hyicus or Staphylococcus agnetis, another closely related species. The only exception was the host S. hyicus strain SC366, which was effectively infected by all three phages, albeit less efficiently than the most sensitive S. chromogenes strain (SC385). Adsorption tests further supported these observations, showing that phages bound to strain SC366 much more quickly than to SC385, despite the lower lytic activity observed. Taken together, these results highlight that while the phages retain some capacity to infect S. hyicus, their biological properties point to a stronger adaptation to S. chromogenes, indicating that they are not suitable candidates for controlling EE. Full article

This article examines an integrated approach to data acquisition and transmission within an intelligent thermal conditioning system for engines and vehicles that operates using thermal energy storage and the digital twin concept. The system is characterized by its use of multiple primary energy sources to power internal subsystems and maintain optimal engine and vehicle temperature conditions. Building on a formalized conceptual model of the intelligent thermal conditioning system, the study identifies key technological features required for implementing complex operational processes, as well as the stages necessary for applying the proposed approach during the design and modernization phases throughout the system’s life cycle. A core block diagram of the system’s digital twin is presented, developed using mathematical models that describe support and monitoring processes under real operating conditions. Additionally, an architectural framework for organizing data collection and transmission is proposed, highlighting the integration of digital twin technologies into the thermal conditioning workflow. The article also introduces methods for adaptive data formation, transfer, and processing, supported by a specialized onboard software-diagnostic complex that enables structured information management. The practical implementation of the proposed solutions has the potential to enhance the energy efficiency of thermal conditioning processes and improve the reliability of vehicles employing thermal energy storage technologies. Full article

Against the backdrop of global warming and an increase in extreme weather events, the freshwater aquaculture industry, which is highly dependent on environmental conditions, faces severe challenges. As the world’s largest producer of freshwater aquaculture, the stability of China’s production is crucial for ensuring national food security and rural livelihoods. This study utilizes provincial panel data from China (2007–2023) and employs the HP filter separately for each province to construct a “climate-induced output” indicator. A panel data model is then established to examine the impact and transmission mechanisms of extreme climate risks on freshwater aquaculture output. The findings reveal the following: (1) Climate risks exert a significant negative impact on freshwater aquaculture production, with extreme low temperatures, droughts, and extreme rainfall having particularly pronounced effects. (2) Natural disasters play a partial mediating role between extreme climate and output, accounting for approximately 26.35% of the total effect. (3) From an overall perspective, both increased labor productivity and greater operational scale can significantly mitigate the negative impacts of climate risks. This study provides empirical evidence to inform policies on optimizing regional aquaculture layouts, enhancing climate resilience, and formulating adaptive strategies. Full article

This paper presents a waveguide energy-selective device operating in the Ku band. By utilizing the nonlinear characteristics of PIN diodes, the device can autonomously switch its operating state according to the power level of incident signals inside the waveguide, achieving an adaptive transmission response. Concurrently, through a dual-layer structural design and optimized inter-layer coupling, it enables the device to deliver broadband-protective performance within the Ku band. To validate its feasibility, the device was designed and implemented based on the waveguide WR62. The results indicate that during the transmission of a −10 dBm signal, the device exhibits insertion loss fluctuating around 1 dB within the 13–17 GHz band, whereas under 45 dBm signal incidence, the shielding effectiveness exceeds 10 dB across this frequency range. The device can be integrated into waveguides to provide adaptive high-power protection, thus demonstrating significant application potential in the field of electromagnetic protection for sensitive electronic equipment. Full article

Sarcocystis is a genus of heteroxenous, globally distributed apicomplexan parasites found in reptiles, birds, and mammals. Typically, sarcocysts develop in muscles of intermediate hosts, and oocysts sporulate in intestines of definitive hosts. The parasite’s life cycle is based on prey–predator relationships and usually involves two distinct host species. However, some Sarcocystis spp. can complete their full development within a single host species. Brown rats (Rattus norvegicus) are invasive, synanthropic, highly adaptable rodents that are true omnivores and opportunistic feeders. Therefore, it is possible that they can act as definitive hosts of Sarcocystis parasites. This study provides the first comprehensive assessment of Sarcocystis protists in brown rat intestinal samples under natural conditions, combining microscopy and molecular analyses. Of 27 brown rats investigated, 25.9% (7/27) of animals harbored oocysts/sporocysts of Sarcocystis spp. Based on nested PCR and sequencing of four genetic loci (18S rRNA, 28S rRNA, ITS1, and cox1), 59.3% of samples were positive for Sarcocystis spp. Parasites identified were genetically similar to Sarcocystis spp. using bird–bird, bird–Carnivora, rodent–Carnivora, or ungulate–Carnivora as their intermediate–definitive hosts. The present study suggests that synanthropic rodents may facilitate cross-ecosystem transmission of these parasites, increasing infection pressure on livestock, companion animals, and wildlife in human-dominated environments. Future molecular and dietary ecological studies are needed to assess the role of synanthropic and opportunistic hosts, such as the brown rat, in the transmission of Sarcocystis spp. Full article

Against the backdrop of accelerating urbanisation in China, the urban-rural divide continues to widen, while cave dwellings along the Yellow River have been largely abandoned, facing the challenge of cultural erosion. This study breaks from conventional conservation approaches by empirically exploring the viability of living heritage in promoting sustainable rural revitalisation and integrated urban-rural development. Employing participatory action research, it engaged multiple stakeholders—including villagers, returning migrants, and urban designers—across 60 villages in the middle reaches of the Yellow River. This collaboration catalysed a “collective-centred” adaptive reuse model, generating multifaceted solutions. The case of Fangshan County’s transformation into a cultural ecosystem demonstrates how this model simultaneously fosters endogenous social cohesion, attracts tourism resources and investment, while disseminating traditional culture. Quantitative analysis using the Yao Dong Living Heritage Sensitivity Index (Y-LHSI) and Living Heritage Transmission Index (Y-LHI) indicates that the efficacy of collective action is a decisive factor, revealing an inverted U-shaped relationship between economic development and cultural preservation. The findings further propose that living heritage regeneration should be reconceptualised from a purely technical restoration task into a viable social design pathway fostering mutually beneficial urban-rural symbiosis. It presents a replicable “Yao Dong Solution” integrating cultural sustainability, community resilience, and inclusive economic development, offering insights for achieving sustainable development goals in similar contexts across China and globally. Full article

This paper presents the design and optimisation of a low-power embedded sensor-node architecture for real-time environmental monitoring with on-board machine-learning inference. The proposed system integrates heterogeneous sensing elements for air quality and ambient parameters (temperature, humidity, gas concentration, and particulate matter) into a modular embedded platform based on a low-power microcontroller coupled with an energy-efficient neural inference accelerator. The design emphasises end-to-end energy optimisation through adaptive duty-cycling, hierarchical power domains, and edge-level data reduction. The embedded machine-learning layer performs lightweight event/anomaly detection via on-device multi-class classification (normal/anomalous/critical) using quantised neural models in fixed-point arithmetic. A comprehensive system-level analysis, performed via MATLAB Simulink simulations, evaluates inference accuracy, latency, and energy consumption under realistic environmental conditions. Results indicate that the proposed node achieves 94% inference accuracy, 0.87 ms latency, and an average power consumption of approximately 2.9 mWh, enabling energy-autonomous operation with hybrid solar–battery harvesting. The adaptive LoRaWAN communication strategy further reduces data transmissions by ≈88% relative to periodic reporting. The results indicate that on-device inference can reduce network traffic while maintaining reliable event detection under the evaluated operating conditions. The proposed architecture is intended to support energy-efficient environmental sensing deployments in smart-city and climate-monitoring contexts. Full article

Linear array detector-based infrared push-broom imaging systems are widely employed in remote sensing and security surveillance due to their high spatial resolution, wide swath coverage, and low cost. However, the massive data volume generated during continuous scanning presents substantial storage and transmission challenges. To mitigate this issue, we propose a lossless compression algorithm based on pixel-adaptive prediction and hierarchical decomposition of residuals. The algorithm first performs pixel-wise adaptive noise compensation according to local image characteristics and achieves efficient prediction by exploiting the strong inter-pixel correlation along the scanning direction. Subsequently, hierarchical decomposition is applied to high-energy residual blocks to further eliminate spatial redundancy. Finally, the Golomb–Rice coding parameters are adaptively adjusted based on the neighborhood residual energy, optimizing the overall code length distribution. The experimental results demonstrate that our method significantly outperforms most state-of-the-art approaches in terms of both the compression ratio (CR) and bits per pixel (BPP). Moreover, while maintaining a CR comparable to H.265-Intra, our method achieves a 21-fold reduction in time complexity, confirming its superiority for large-format image compression. Full article

Falls are a leading cause of bone fractures among the elderly, particularly hip fractures resulting from side falls. This research deals with the feasibility of application of shear-thickening fluids (STFs) to design self-protective wearable devices to rapidly respond to sudden impact due to falls. The device consists of a lightweight, flexible foam structure embedded with STF-filled compartments, which remain soft during normal movements but stiffen upon sudden impact, effectively dissipating energy and reducing force trans-mission to the bones. First, a foam-based sandwich panel filled with STF is fabricated and subjected to several falling scenarios through a ball drop test. The induced strain of the device with and without STF is measured using Fiber Bragg Grating (FBG) sensors. Then, the effect of localized STF is explored by fabricating a soft 3D-printed (TPU) sandwich panel filled with STF at selected cavities. It was observed that the application of STF reduces the induced strain by approximately 50% for the TPU skin device and 30% for the foam-based device. This adaptive response mechanism offers a balance between comfort and protection, ensuring wearability for daily use while significantly lowering fracture risks. The proposed solution aims to enhance fall-related injury prevention for the elderly, improving their quality of life and reducing healthcare burdens associated with fall-related fractures. Full article

Background/Objectives: Staphylococcus aureus is a multifaceted pathogen responsible for diseases in humans and in several animal species, including dairy cows. This study aimed to characterize and compare the genetic diversity, lineage distribution, and antimicrobial resistance profiles of S. aureus isolates from bovine milk with human-derived reference genomes to investigate host adaptation and inter-species transmission. Methods: Genomic analyses were performed on S. aureus isolates from quarter milk samples of dairy cows together with human-derived sequences from public databases. Whole-genome sequencing and multi-locus sequence typing (MLST) were used to determine sequence type (ST) distribution, and the presence of key antibiotic resistance genes and mobile genetic elements (MGEs) was assessed. Comparative genomics was applied to evaluate gene content, phylogenetic relationships, and lineage–host associations. Results: The dataset encompassed bovine-adapted lineages (CC97, CC133, CC151) and human-associated lineages (CC1, CC5, CC8, CC30, CC45), as well as livestock-associated ST398 in bovine samples and human-adapted ST5 and ST6 in animals. ST8 was the only ST shared between animal and human isolates and showed differing resistance profiles, with animal ST8 carrying resistance determinants absent from human ST8. Bovine-adapted strains were characterized by recurrent loss of human-associated virulence genes and acquisition of bovine-associated mobile genetic elements, and blaZ and mecA were rarely detected in bovine-adapted CC97 but were frequently present in human CC5 and CC8. Overall, animal isolates carried fewer resistance genes than human isolates. Conclusions: S. aureus from dairy cows and humans displayed substantial genetic diversity, with evidence of host-associated lineages and dynamic changes in gene and mobile element content. These findings support the need for integrated One Health surveillance to track shared and host-adapted lineages and their antibiotic resistance determinants. Full article

Symbiotic radio (SR) has recently emerged as a promising paradigm for enabling spectrum- and energy-efficient massive connectivity in low-power Internet-of-Things (IoT) networks. By allowing passive backscatter devices (BDs) to coexist with active primary link transmissions, SR significantly improves spectrum utilization without requiring dedicated spectrum resources. However, most existing studies on multi-tag multiple-input multiple-output (MIMO) SR systems assume homogeneous traffic demands among BDs and primarily focus on rate-based performance metrics, while neglecting system-level task completion time (TCT) optimization under heterogeneous data requirements. In this paper, we investigate a joint performance optimization framework for a multi-tag MIMO symbiotic radio network. We first formulate a weighted sum-rate (WSR) maximization problem for the secondary backscatter links. The original non-convex WSR maximization problem is transformed into an equivalent weighted minimum mean square error (WMMSE) problem, and then solved by a block coordinate descent (BCD) approach, where the transmit precoding matrix, decoding filters, backscatter reflection coefficients are alternatively optimized. Second, to address the transmission delay imbalance caused by heterogeneous data sizes among BDs, we further propose a rate weight adaptive task TCT minimization scheme, which dynamically updates the rate weight of each BD to minimize the overall TCT. Simulation results demonstrate that the proposed framework significantly improves the WSR of the secondary system without degrading the primary link performance, and achieves substantial TCT reduction in multi-tag heterogeneous traffic scenarios, validating its effectiveness and robustness for MIMO symbiotic radio networks. Full article