Search Results (222)

This paper investigates the problem of computation offloading and resource allocation in an integrated space–air–sea network based on unmanned aerial vehicle (UAV) and low Earth orbit (LEO) satellites supporting Maritime Internet of Things (M-IoT) devices. Considering the complex, dynamic environment comprising M-IoT devices, UAVs and LEO satellites, traditional optimization methods encounter significant limitations due to non-convexity and the combinatorial explosion in possible solutions. A multi-agent deep deterministic policy gradient (MADDPG)-based optimization algorithm is proposed to address these challenges. This algorithm is designed to minimize the total system costs, balancing energy consumption and latency through partial task offloading within a cloud–edge-device collaborative mobile edge computing (MEC) system. A comprehensive system model is proposed, with the problem formulated as a partially observable Markov decision process (POMDP) that integrates association control, power control, computing resource allocation, and task distribution. Each M-IoT device and UAV acts as an intelligent agent, collaboratively learning the optimal offloading strategies through a centralized training and decentralized execution framework inherent in the MADDPG. The numerical simulations validate the effectiveness of the proposed MADDPG-based approach, which demonstrates rapid convergence and significantly outperforms baseline methods, and indicate that the proposed MADDPG-based algorithm reduces the total system cost by 15–60% specifically. Full article

This work addresses for the first time the effect of anode serpentine channel depth on Methanol Electrolysis Cells (MECs) and Direct Methanol Fuel Cells (DMFCs) for improving performance of both devices. Anode plates with serpentine flow fields of 0.5 mm, 1.0 mm and 1.5 mm depths are designed and tested in single-cells to compare their behaviour. Performance was evaluated through methanol crossover, polarization and power density curves. Results suggest shallower channels enhance mass transfer efficiency reducing MEC energy consumption for hydrogen production at 40 mA∙cm⁻² by 4.2%, but increasing methanol crossover by 30.3%. The findings of this study indicate 1.0 mm is the best depth among those studied for a MEC with 16 cm² of active area, while 0.5 mm is the best for a DMFC with the same area with an increase in peak power density of 14.2%. The difference in results for both devices is attributed to higher CO₂ production in the MEC due to its higher current density operation. This increased CO₂ production alters anode two-phase flow, partially hindering the methanol oxidation reaction with shallower channels. These findings underscore the critical role of channel depth in the efficiency of both MEC and DMFC single-cells. Full article

Background/Objectives: European hedgehogs (Erinaceus europaeus) are present in areas where there is human activity; therefore, they can be a source of pathogens for other animals and humans. Methods: Eighteen hedgehog carcasses were collected and analyzed for Staphylococcus spp. Isolated strains were typed and analyzed for exfoliative toxins genes and the phenotypic and genotypic characteristics of antimicrobial resistance. Results: A total of 54 strains were isolated and typed as S. aureus, S. xylosus, S. sciuri, S. pseudintermedius, S. simulans, S. chromogenes, S. epidermidis, S. hyicus, and S. lentus. No strains had the eta and etb genes coding for exfoliative toxins. Overall, 39/54 (72.20%) isolates showed phenotypic resistance to at least one antimicrobial and 21/54 (38.80%) showed more than one resistance. The lowest efficacy was observed for erythromycin, with 40/54 (74.08%) strains classified as intermediate and 6/54 (11.11%) classified as resistant. Among the 29 isolates shown to be penicillin-resistant, 11 (37.93%) were oxacillin-resistant, with a minimum inhibitory concentration (MIC). Among the 54 staphylococcal strains, 2 (3.70%) were resistant to vancomycin, both with an MIC value equal to the maximum concentration of the antibiotic tested (256 μg/mL) and 2 (3.70%) had an intermediate resistance profile with an 8 μg/mL MIC value. No strains had the genes vanA and vanB. Two of the 29 (6.90%) penicillin-resistant strains had the blaZ gene; 8 (27.13%) strains had the mecA gene. Overall, 2/54 (3.70%) isolates were classified as extensively drug-resistant (XDR) and 9/54 (16.66%) were classified as multidrug-resistant (MDR). Conclusions: Hedgehogs can harbor antimicrobial-resistant staphylococci and can be sources of these bacteria for other animals and humans. They can also serve as bioindicators of the pathogens and antimicrobial-resistant bacteria circulating in a given habitat. Full article

Infections caused by oxacillin-resistant Staphylococcus pseudintermedius are increasingly common in veterinary medicine. The indiscriminate use of antibiotics by pet owners worsens this problem, reducing treatment efficacy and creating the need for alternative therapies. This study aimed to evaluate the inhibitory effect of clove essential oil (Syzygium aromaticum) on both oxacillin-resistant and susceptible S. pseudintermedius. Thirty-five isolates from dogs with otitis externa were analyzed. The bacteria were identified by phenotypic tests and tested for susceptibility to 22 antibiotics using disk diffusion. Resistance genes (mecA and blaZ) were detected using conventional PCR. Among the isolates, 34.28% (12/35) were positive for mecA, and 97.14% (34/35) for blaZ. The essential oil’s efficacy was assessed using broth microdilution to determine its minimum inhibitory concentration (MIC). Clove oil showed an average MIC and minimum bactericidal concentration (MBC) of 6.4 mg/mL, inhibiting both resistant and susceptible isolates. In conclusion, clove essential oil demonstrated in vitro antimicrobial activity against S. pseudintermedius. Full article

Staphylococcus saprophyticus (S. saprophyticus) is an opportunistic coagulase-negative staphylococcus (CoNS) known to cause urinary tract infections in humans and is increasingly recognized in veterinary medicine. The aim of this study was to provide an epidemiological characterization of S. saprophyticus strains and to identify potential virulence factors that may contribute to interspecies transmission. This research is particularly important, as companion animals represent an understudied reservoir of this microorganism, and their role in the spread of resistant pathogens remains insufficiently understood. A total of 61 S. saprophyticus strains isolated from humans, dogs, and cats were analyzed. Identification was performed using MALDI-TOF MS and confirmed by PCR targeting the hrcA gene. Antimicrobial susceptibility was assessed using the disk diffusion and broth microdilution methods, while resistance genes were detected by PCR. The blaZ and mecA genes were present in all strains; additionally, the majority harbored the resistance genes ermA, ermB, tetM, and tetK. Multidrug resistance (MDR) was identified in 21/61 strains (34.4%). Biofilm-forming capacity was temperature-dependent, with the strongest biofilm production observed at 37 °C (70.5%). At 38 °C and 39 °C, the proportion of strong biofilm producers decreased to 50.8% and 52.5%, respectively. All tested strains demonstrated pathogenic potential in the Galleria mellonella larvae infection model, with the highest mortality recorded for selected feline and canine strains. These findings indicate that S. saprophyticus strains from both humans and companion animals possess notable virulence and multidrug resistance. The detection of genotypically and phenotypically resistant strains in animals highlights their potential role as reservoir for zoonotic transmission. Full article

The increasing emergence of antifungal resistance poses potential clinical challenges, particularly among immunocompromised patients with cancer at risk of invasive mold infections, but data on antifungal susceptibility trends specific to this population are few. We evaluated distributions of minimal inhibitory concentrations (MIC), including minimal effective concentrations (MEC) for echinocandins, of 11 antifungal agents for 523 mold isolates (395 Aspergillus spp.) from cancer patients. Based on published Clinical and Laboratory Standards Institute guidelines, isavuconazole had notably high rates of non-wild-type MICs for A. fumigatus (19.6%), A. flavus/oryzae (34.8%), A. niger complex (26.1%), and A. terreus complex (8.33%). Persistent low baseline resistance of A. fumigatus to voriconazole was observed across multiple years (2.4–11.5% per year, average 8.41%) without significant trends in MIC change over time. Itraconazole and posaconazole demonstrated the lowest MIC distributions (MIC₅₀ ≤ 0.06–0.5 µg/mL) of the azoles against Aspergillus spp. Amongst the A. niger complex, 29.4% (27/92) demonstrated non-wild-type MICs to itraconazole. While the A. nidulans group was less frequent (n = 24), bimodal peaks in MIC/MEC were noted for caspofungin (≤0.06 and 1 µg/mL). Non-Aspergillus molds of significance (Zygomycetes, Fusarium spp., Scedosporium spp., and Lomentospora prolificans) demonstrated variable but increased MICs to antifungal agents as previously described. Our results highlight increased rates of non-wild type MICs for Aspergillus spp. to isavuconazole and voriconazole, which are commonly used antifungal agents in cancer patients. Such AST trends should be closely monitored in populations with frequent antifungal use and encourage increased antifungal stewardship efforts. Full article

Background: Pyoderma is a superficial bacterial infection that is considered the formation of pus-containing lesions on the skin occurring in animals. Staphylococci, including Staphylococcus aureus and Staphylococcus pseudintermedius, that cause pyoderma in pet animals is a global health concern. The objectives of this study were to investigate antibiotic-resistant staphylococci isolated from pyoderma in dogs and cats and to analyse whole genome sequences of multidrug-resistant (MDR) staphylococci. Methods: A total of 56 pyoderma swabbing samples from 42 dogs and 14 cats located in Southern Thailand was collected to isolate staphylococci. Antibiotic susceptibility and antibiotic-resistant genes of staphylococcal isolates were investigated. Furthermore, the representative MDR isolates were investigated using whole genome sequence analysis. Results: 61 isolates were identified as staphylococci, which can be classified into 12 different species, mostly including 13 S. intermedius (13.26%), 13 S. saprophyticus (13.26%), 8 S. sciuri (8.16%), and Staphylococcus cohnii (8.16%). Remarkably, the main pyoderma-causing species that were isolated in this study were S. aureus (5.10%) and S. pseudintermedius (3.06%). Most staphylococci were resistant to penicillin G (30%), and the blaZ gene was found to be the highest prevalence of the resistance genes. Both MDR-S. aureus WU1-1 and MDR-S. pseudintermedius WU48-1 carried capsule-related genes as main virulence factor genes. Interestingly, MDR-S. pseudintermedius WU48-1 was resistant to seven antibiotic classes, which simultaneously carried blaZ, mecA, aac, dfrK, aph3, and tetM. Genes related to antibiotic efflux were the highest proportion of the mechanism found in both representatives. Remarkably, SCCmec cassette genes were found in both isolates; however, the mecA gene was found only in MDR-S. pseudintermedius WU48-1. In addition, these were mostly carried by macrolide- and tetracycline-resistance genes. Mobile gene transfer and horizontal gene transfer events frequently contain genes involved in the antibiotic target alteration mechanism. Conclusions: This study found that MDR staphylococci, especially S. aureus and S. pseudintermedius, are important in animals and owners in terms of One Health concern. The information on whole genome sequences of these MDR staphylococci, particularly antimicrobial resistance genes, mobile genetic elements, and horizontal gene transfer events, can help to understand gene transmission and be applied for antibiotic resistance surveillance in veterinary medicine. Full article

This study explores the feasibility of producing biohydrogen from winery wastewater using a dual-chamber microbial electrolysis cell (MEC). A mixed microbial consortium pre-adapted to heavy-metal environments and enriched with Geobacter sulfurreducens was anaerobically cultivated from diverse waste streams. Over 5000 h of development, the MEC system was progressively adapted to winery wastewater, enabling long-term electrochemical stability and high organic matter degradation. Upon winery wastewater addition (5% v/v), the system achieved a sustained hydrogen production rate of (0.7 ± 0.3) L H₂ L⁻¹ d⁻¹, with an average current density of (60 ± 4) A m⁻³, and COD removal efficiency exceeding 55%, highlighting the system’s resilience despite the presence of inhibitory compounds. Coulombic efficiency and cathodic hydrogen recovery reached (75 ± 4)% and (87 ± 5)%, respectively. Electrochemical impedance spectroscopy provided mechanistic insight into charge transfer and biofilm development, correlating resistive parameters with biological adaptation. These findings demonstrate the potential of MECs to simultaneously treat agro-industrial wastewaters and recover energy in the form of hydrogen, supporting circular resource management strategies. Full article

A pilot-scale (4000 L) continuous flow electromethanogenic reactor (EMR), also known as a microbial electrochemical cell coupled with an anaerobic digester (MEC-AD), treating brewery wastewater was designed and installed at Hepworth’s Brewery, UK. This investigation presents a 4-fold increase in size compared to the next largest pilot-scale MEC-AD system presented in the literature, providing findings to inform the operation of a 52,000 L MEC-AD system (currently under construction). Housed in a 20 ft shipping container, the pilot system features four 1000 L reaction vessels arranged in series, each with a working volume of 900 L. Each reaction vessel contained 8 electrode modules. The system was tested over varying organic loading rates (OLRs), achieved through systematic reductions in hydraulic retention time (HRT). HRTs between 24 and 1.8 days were investigated to align with commercial viability targets. OLRs were observed from 0.4 to 7.5 kgCOD/m³/d. A maximum stable OLR of 6.75 kgCOD/m³/d at a HRT of 2.3 days was observed while maintaining COD removal of 65 and 88% over the first two vessels. This pilot demonstrated commercially viable performance of an EMR at a brewery, resulting in the purchase of the technology at commercial scale (52,000 L) to form part of a wastewater treatment system. Full article

As the performance requirements for printed circuit boards (PCBs) in electronic devices continue to increase, reliable defect detection during PCB manufacturing is vital. However, due to the small size, complex categories, and subtle differences in defect features, traditional detection methods are limited in accuracy and robustness. To overcome these challenges, this paper proposes MAS-YOLO, a lightweight detection algorithm for PCB defect detection based on improved YOLOv12 architecture. In the Backbone, a Median-enhanced Channel and Spatial Attention Block (MECS) expands the receptive field through median enhancement and depthwise convolution to generate attention maps that effectively capture subtle defect features. In the Neck, an Adaptive Hierarchical Feature Integration Network (AHFIN) adaptively fuses multi-scale features through weighted integration, enhancing feature utilization and focus on defect regions. Moreover, the original YOLOv12 loss function is replaced with the Slide Alignment Loss (SAL) to improve bounding box localization and detect complex defect types. Experimental results demonstrate that MAS-YOLO significantly improves mean average precision (mAP) and frames per second (FPS) compared to the original YOLOv12, fulfilling real-time industrial detection requirements. Full article

The conserved and essential Cdc13/CTC1-Stn1-Ten1 telomeric complex (CST) ensures chromosome stability by protecting telomere ends and regulating telomerase accessibility. In a recent study, we uncovered mutants of the S. cerevisiae CST, in which damage was sensed by the two major G2/M spindle checkpoints (one is Bub2-dependent and the other one Mad2-dependent), as well as the major G2/M DNA damage checkpoint (Mec1-dependent). In this study, we found, by fluorescence microscopy, that the stability of the mitotic tubulin spindle was profoundly affected in the best-studied of these mutants, stn1-sz2. Additional data from genetic analyses suggested the potential involvement of Stu1 and Stu2, as well as Slk19, in these defects. Throughout this study, we compared the phenotypes of stn1-sz2 with those of cdc13-1, the best-studied CST mutant, which also serves as a prototype of telomere-damage-characterized CST mutants. We propose that stn1-sz2 represents the prototype of cst mutants characterized by tubulin spindle damage. These newly described phenotypes potentially represent the basis for identifying new functions of the CST telomeric complex. These functions might consist of ensuring correct chromosome segregation through the stabilization of the mitotic spindle. Full article

In complex indoor and outdoor scenarios, traditional GPS-based ranging technology faces limitations in availability due to signal occlusion and user privacy issues. Wireless signal ranging technology based on 5G base stations has emerged as a potential alternative. However, existing methods are limited by low efficiency in constructing static signal databases, poor environmental adaptability, and high resource overhead, restricting their practical application. This paper proposes a 5G wireless signal ranging framework that integrates mobile edge computing (MEC) and crowdsourced intelligence to systematically address the aforementioned issues. This study designs a progressive solution by (1) building a crowdsourced data collection network, using mobile terminals equipped with GPS technology to automatically collect device signal features, replacing inefficient manual drive tests; (2) developing a progressive signal update algorithm that integrates real-time crowdsourced data and historical signals to optimize the signal fingerprint database in dynamic environments; (3) establishing an edge service architecture to offload signal matching and trajectory estimation tasks to MEC nodes, using lightweight computing engines to reduce the load on the core network. Experimental results demonstrate a mean positioning error of 5 m, with 95% of devices achieving errors within 10 m, as well as building and floor prediction error rates of 0.5% and 1%, respectively. The proposed framework outperforms traditional static methods by 3× in ranging accuracy while maintaining computational efficiency, achieving significant improvements in environmental adaptability and service scalability. Full article

Introduction/Objectives: Antibiotic resistance makes the treatment of pneumonia challenging. Effective management depends on accurate diagnostic techniques to identify resistance genes and customize drugs. This study primarily aimed to identify antibiotic resistance genes in respiratory samples from patients with pneumonia using polymerase chain reaction (PCR) to determine the prevalence of specific resistance genes and analyze clinical factors contributing to antibiotic resistance, as well as to provide actionable insights into resistance patterns in Jordan and support efforts to improve pneumonia management. Methods: This retrospective observational study included 114 patients who were diagnosed with pneumonia. Clinical data, including prior antibiotic exposure and treatment history, were collected. PCR diagnostics were used to detect resistance genes in respiratory samples. In this study, we evaluated 14 antibiotic resistance genes in pneumonia pathogens, highlighting their diverse resistance mechanisms. Results: Mec A was the most frequently detected gene, appearing in 87 samples (77.3%). Additionally, Tem in 80 samples (70.2%), Oxa-48-like in 15 samples (13.2%), and Ctx-M-1 in 38 samples (33.3%) were among the most commonly detected genes. In contrast, Oxa-40-like (7.0%), Vim (8.8%), and Imp (4.4%) genes exhibited a lower prevalence. The Oxa-51-like gene showed the only significant association with ertapenem resistance (p-value = 0.046). Further analysis revealed statistically significant associations between Mec A and methicillin resistance (p < 0.001), underscoring its critical role. However, other genes, such as Oxa-40-like and Oxa-48-like, showed no significant correlation with the antibiotic resistance patterns of imipenem and meropenem (p > 0.05). Conclusions: This study demonstrates the utility of PCR-based diagnostics for detecting resistance genes and highlights the critical clinical factors associated with antibiotic resistance in patients with pneumonia. These findings underscore the importance of integrating molecular diagnostics into routine care to improve treatment outcomes and combat the growing threat of antibiotic resistance in Jordan. This highlights PCR’s value in guiding effective treatment strategies and addressing multidrug-resistant pneumonia. Full article

Background: The Pearl River Delta (PRD) region in Guangdong, China, is urbanized and economically significant. Rapid development has shaped diverse dietary habits. In this densely populated area, there is an urgent need to assess vitamin status and its impact on age-related diseases. Methods: A total of 2646 participants (age: 50.92 ± 9.30 years; male: 64.06%) were recruited from the Pearl River Delta (PRD) region. Participants were included from 1 December 2020 to 30 November 2021. Three restricted cubic spline logistic models, interaction terms, and mediated effects analyses were used to assess the association between vitamin A, B, E, B₁, B₂, B₃, B₅, B₆, and B₉ between five age-related diseases: cerebrovascular disease (CVD), coronary heart disease (CHD), hypertension (HTN), dyslipidemia (DYS), and type 2 diabetes mellitus (T2DM). Results: Blood concentrations of nine vitamins showed a right-skewed distribution. Significant correlations were found between vitamin levels and age-related diseases across nine groups (p < 0.05). A J-shaped relationship was observed between vitamin levels and the risk of age-related diseases, except for the Vitamin A-HTN/T2DM, which showed Maximum Effective Concentration (MEC). Specific thresholds included: Vitamin A: 1080 ng/mL (DYS); Vitamin B₁: 77 ng/mL (CVD), 75.5 ng/mL (HTN); Vitamin B₅: 900 ng/mL (CVD), 600 ng/mL (HTN), 690 ng/mL (DYS); Vitamin B₆: 82 ng/mL (CVD). The protective effect of vitamins against age-related diseases decreased with age, and higher levels of vitamins A and B₁ correlated with increased hypertension risk in older adults (P_interaction < 0.01). Low Body Resilience Index (BRI) and physical activity mediated the protective effects of vitamins A and B₅ on HTN and DYS, while no mediating effects were found for smoking and alcohol consumption. Conclusions: The effectiveness of multivitamin supplementation in preventing cardiovascular, cerebrovascular, and metabolic diseases may be limited in healthy aging populations. Health professionals should consider patients’ physiological conditions and blood vitamin levels to avoid overdose. More interventional studies are needed to establish causal relationships. Full article

The rapid development of Multi-access Edge Computing (MEC) technology is transforming traditional platform services and enabling realization of the mMTC vision of 5G networks. MEC allows computational tasks to be offloaded to devices at the network edge, enabling real-time crowd sensing. However, due to the limited resources in MEC environments, it is essential to propose efficient service deployment and traffic management strategies that balance Quality of Service (QoS) with costs. This paper addresses the challenge by modeling the QoS-effective joint service deployment and traffic management problem (QST) as a nonlinear integer optimization problem. We propose a customized genetic algorithm called GA4QST, which aims to minimize cost-performance ratios. In the experimental section, GA4QST is compared with baseline algorithms in terms of efficiency and effectiveness. Although GA4QST exhibits slightly increased complexity compared to the original genetic algorithm, it performs exceptionally well in balancing benefits and average time costs. GA4QST demonstrates strong capabilities in finding optimal solutions, consistently outperforming baseline algorithms. This further confirms the effectiveness and potential applicability of GA4QST in real-world scenarios. Finally, we also explore the impact on optimization outcomes of system configurations such as service diversity, data volume, processing power, and network characteristics. The results indicate that GA4QST has broad applicability and represents a feasible solution for practical MEC applications. Full article