Search Results (4,142)

This study reports the sustainable synthesis and thermal, morphological, and structural characterization of multifunctional silver/hydroxyapatite nanocomposite prepared from recycled caprine bone. The organic extract from caprine bone was characterized using Fourier Transform Infrared (FTIR) and Ultraviolet–Visible Spectroscopy (UV-Vis). The biogenic hydroxyapatite (CHAP) and its silver composite (Ag@CHAP) were characterized using thermal gravimetric analysis (TGA), Raman spectra, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), and transmission electron microscope (TEM). The photocatalytic activity of Ag@CHAP was quantitatively confirmed through the degradation of Crystal Violet (5 ppm) under sunlight, achieving a high removal efficiency of 99.8% under optimum conditions, demonstrating significant potential for wastewater remediation. Ag@CHAP also demonstrated enhanced antimicrobial activity compared with CHAP and showed broad-spectrum efficacy against clinical human isolates P. aeruginosa ATCC 10145, E. coli ATCC 35218, S. aureus ATCC 25923, and C. albicans (human isolate). The in vitro hemolytic-activity assays revealed that both CHAP and Ag@CHAP had no hemolytic activity after 24 h of red blood cells incubation and effectively reduced lead-induced hemolysis from 86.73% to 39.35% and 49.13%, respectively. These findings confirm CHAP and Ag@CHAP as stable, biocompatible, and high-performance materials with promising applications in the sustainable water-treatment and biomedical fields. Full article

The rise of multidrug-resistant enteric pathogens and increased demand for antibiotic alternatives have intensified efforts to find reliable, safe, and effective probiotics. This study reports the isolation, characterization, and assessment of the probiotic potential of five Enterococcus strains isolated from the feces of healthy goats aged 7–9 months raised under conventional management. Following an initial screening of 57 lactic acid bacteria, 5 isolates (Enterococcus faecium, E. hirae, E. faecalis, Enterococcus sp., and Streptococcus lutetiensis) were chosen based on their catalase-negative, non-motile, and non-hemolytic characteristics, in addition to their high tolerance to gastric (pH 2.0) and intestinal (pH 8.0, 0.3–1.5% bile salt) stress. In simulated gastric juice, survival rates reached 89.05% (E5) and 85.03% (E3), while in intestinal juice, survival peaked at 78.01% (E4). All strains thrived in 4% NaCl and maintained at least 8 Log₁₀ CFU/mL after 12 h of exposure to 1.5% porcine bile salt. Cell surface hydrophobicity (0.78–93.85%) and auto-aggregation (23–91%) properties were strain-dependent, but exceeded the thresholds required for efficient gut colonization. Co-aggregation assays demonstrated over 45% binding with E. coli and S. typhimurium, suggesting a strong potential to displace pathogens. Cell-free supernatants created inhibition zones measuring 15.02 mm against E. coli and 11.04 mm against S. flexneri, while maintaining activity against methicillin-resistant S. aureus (MRSA). Antibiotic testing indicated that all strains were sensitive to ciprofloxacin and florfenicol. No β-hemolysis or mobile resistance genes were found, supporting the initial safety findings. This study reveals that Enterococcus isolates from goats display a unique combination of gastrointestinal survivability and broad-spectrum antipathogenic activity and, therefore, are promising candidates for the development of next-generation probiotic strains for use in livestock (and, potentially, humans). Further in vivo validation and genome-based safety assessments are warranted. Full article

Polymeric microfiltration membranes are among the most utilized pressure-driven membranes due to their excellent permeation flux, moderate removal efficiency, low operating pressure, low cost, as well as their potential for reusability and cleanability. Therefore, these membranes are used in different crucial sectors, including the water and wastewater, dairy, beverage, and pharmaceutical industries. However, well-known polymeric microfiltration membranes suffer from their poor hydrophilic properties, causing fouling phenomenon. A reduction in permeate flux, a shortened operational lifespan, and increased energy consumption are the primary negative consequences of membrane fouling. Over the years, a broad spectrum of studies has been performed to modify polymeric microfiltration membranes to improve their hydrophilic, transport, and antifouling characteristics. Despite extensive research, this issue remains a subject of ongoing discussion and scrutiny within the scientific community. This review article provides promising information about different physical and chemical modification methods—such as polymer blending, the incorporation of nanomaterials, surface coating, chemical crosslinking, in situ nanoparticle immobilization, and chemical surface functionalization—for polymeric microfiltration membranes. The physical and chemical modification methods are comparatively evaluated, highlighting their positive and negative aspects, supported by findings from recent investigations. Moreover, promising ideas and future-oriented techniques were proposed to obtain polymeric microfiltration membranes containing superior efficiency, extended service life, and mechanical strength. Full article

Lignin is a complex aromatic polymer that constitutes a major fraction of plant biomass and represents a valuable renewable carbon resource. Naturally decaying wood serves as an environmental reservoir of microorganisms capable of degrading lignin. In this study, we isolated and characterized sixteen bacterial strains from decaying Tilia cordata wood using an enrichment culture technique with lignin as the sole carbon source. Taxonomic identification via 16S rRNA gene sequencing revealed microbial diversity spanning the genera Bacillus, Pseudomonas, Stenotrophomonas, and several members of the Enterobacteriaceae family, including Raoultella terrigena isolates. Metagenomic sequencing of the wood substrate revealed an exceptionally rich and balanced bacterial community (Shannon index H′ = 5.07), dominated by Streptomyces, Bradyrhizobium, Bacillus, and Pseudomonas, likely reflecting a specialized consortium adapted to lignin rich late-stage decay. Functional phenotyping demonstrated that all isolates possess ligninolytic potential, evidenced by peroxidase/laccase-type activity through methylene blue decolorization. Dynamic Light Scattering (DLS) and HPLC analyses showed that some isolates, such as Raoultella terrigena MGMM806, effectively depolymerized lignosulfonate into low molecular weight fragments (1.23 nm), while others accumulated intermediate metabolites or completely mineralized the substrate. Growth profiling on monolignol substrates revealed a broad spectrum of catabolic specialization in lignin monomer degradation. The results demonstrate a complex system of metabolic partitioning within a natural bacterial consortium. This collection represents a foundational genetic resource for developing engineered biocatalysts and synthetic microbial communities aimed at the efficient conversion of lignin into valuable aromatic compounds. Full article

In the context of fifth-generation (5G) communications and the dawn of sixth-generation (6G) networks, a surged societal demand on bandwidth and data rate and more stringent commercial requirements on transmission efficiency, cost, and reliability are increasingly evident and, hence, driving the maturity of reconfigurable millimeter-wave (mmW) and terahertz (THz) devices and systems, in particular, liquid crystal (LC)-based tunable solutions for delay line phase shifters (DLPSs). However, the field of LC-combined electronics has witnessed only incremental developments in the past decade. First, the tuning principle has largely been unchanged (leveraging the shape anisotropy of LC molecules in microscale and continuum mechanics in macroscale for variable polarizability). Second, LC-enabled devices’ performance has yet to be standardized (suboptimal case by case at different frequency domains). In this context, this work points out three underestimated knowledge gaps as drawn from our theoretical designs, computational simulations, and experimental prototypes, respectively. The first gap reports previously overlooked physical constraints from the analytical model of an LC-embedded coaxial DLPS. A new geometry-dielectric bound is identified. The second gap deals with the lack of consideration in the suboptimal dispersion behavior in differential delay time (DDT) and differential delay length (DDL) for LC phase-shifting devices. A new figure of merit (FoM) is proposed and defined at the V-band (60 GHz) to comprehensively evaluate the ratios of the DDT and DDL over their standard deviations across the 54 to 66 GHz spectrum. The third identified gap deals with the in-depth explanation of our recent experimental results and outlook for partial leakage attack analysis of LC phase shifters in modern eavesdropping. Full article

We propose a strain-optimized design strategy for lattice-matched InAs_1−xSb_x/Al_1−yIn_ySb Type-I quantum wells (QWs) that emit across the near-to mid-infrared spectrum (2–5 µm). By combining elastic strain energy minimization with band offset calculations, we identify Type-I alignment for Sb contents (x ≤ 0.40) and In contents (0.10 < y ≤ 1). At the same time, Type-II dominates at higher Sb compositions (x ≥ 0.50). Using the transfer matrix method under the effective mass approximation, we demonstrate precise emission tuning via QW thickness (L_W) and compositional control, achieving a wavelength coverage of 2–5 µm with <5% strain-induced energy deviation. Our results provide a roadmap for high-efficiency infrared optoelectronic devices, addressing applications in sensing and communications technologies. Full article

Unmanned aerial vehicle (UAV)-assisted satellite downlink transmission is a promising solution for improving coverage and throughput under challenging propagation conditions. However, the achievable performance gains are fundamentally constrained by the coupling between access transmission and the satellite–UAV backhaul, especially when decode-and-forward (DF) relaying and hybrid multiple access are employed. In this paper, we investigate the problem of end-to-end downlink sum-rate maximization in a UAV-assisted satellite network with hybrid non-orthogonal multiple access (NOMA)/orthogonal multiple access (OMA) transmission. We propose a performance-driven end-to-end optimization framework, in which UAV placement is optimized as an outer-layer control variable through an iterative procedure. For each candidate UAV position, a greedy transmission mode selection mechanism and a KKT-based satellite-to-UAV backhaul bandwidth allocation scheme are jointly executed in the inner layer to evaluate the resulting end-to-end downlink performance, whose feedback is then used to update the UAV position until convergence. Simulation results show that the proposed framework consistently outperforms benchmark schemes without requiring additional spectrum or transmit power. Under low satellite elevation angles, the proposed design improves system sum rate and spectral efficiency by approximately 25–35% compared with satellite-only NOMA transmission. In addition, the average user rate is increased by up to 37% under moderate network sizes, while maintaining stable relative gains as the number of users increases, confirming the effectiveness and scalability of the proposed approach. Full article

This study aimed to classify Escherichia coli phages using bioinformatics analysis systematically and to establish corresponding PCR and qPCR detection methods for rapid molecular typing and identification. Based on 419 complete E. coli phage genomes available in NCBI, phylogenetic and pan-genomic analyses were conducted to classify the phages at the family, subfamily, and genus levels and to identify highly conserved core genes. Specific primers targeting these core genes were designed, and their specificity, sensitivity, and reproducibility were verified using conventional PCR and dye-based qPCR. A total of 357 phages were successfully classified, encompassing 10 families, 20 subfamilies, and 67 genera. Pan-genomic analysis identified type-specific core genes within 16 taxa, including Ackermannviridae and Demerecviridae, for which 16 pairs of primers were designed. Validation using bacteriophages isolated from Xinjiang cattle farms showed distinct single PCR bands with high specificity, and the qPCR assay achieved a sensitivity of up to 10⁻⁵ µg/µL. This study established an efficient and broad-spectrum molecular typing and detection method for E. coli phages, providing a powerful preliminary screening tool for phage selection. Full article

Point-of-care ultrasound (POCUS) is an essential component of emergency medicine, enabling rapid bedside assessment across a wide spectrum of acute conditions. Its effectiveness, however, remains constrained by operator dependency, variable image quality, and time-critical decision-making. Recent advances in artificial intelligence (AI) offer opportunities to augment POCUS by supporting image acquisition, interpretation, and quantitative analysis. This narrative review synthesizes current evidence on AI-enhanced POCUS applications in emergency care, encompassing trauma, non-traumatic emergencies, integrated workflows, resource-limited settings, and education and training. Across trauma settings, AI-assisted POCUS has demonstrated promising performance for automated detection of pneumothorax, hemothorax, and free intraperitoneal fluid, supporting standardized eFAST examinations and rapid triage. In non-traumatic emergencies, AI-enabled cardiovascular, pulmonary, and abdominal applications provide automated measurements and pattern recognition that can approach expert-level performance when image quality is adequate. Integrated AI–POCUS systems and educational tools further highlight the potential to expand ultrasound access, support non-expert users, and standardize training. Nevertheless, important limitations persist, including limited generalizability, dataset bias, device heterogeneity, and uncertain impact on clinical decision-making and patient outcomes. In conclusion, AI-enhanced POCUS is transitioning from proof-of-concept toward early clinical integration in emergency medicine. While current evidence supports its role as a decision-support tool that may enhance consistency and efficiency, widespread adoption will require prospective multicentre validation, development of representative POCUS-specific datasets, vendor-agnostic solutions, and alignment with clinical, ethical, and regulatory frameworks. Full article

The anticipated transition from 5G to 6G is driven not by incremental performance demands but by a widening mismatch between emerging application requirements and the capabilities of existing cellular systems. Despite rapid progress across 3GPP Releases 15–20, the current literature lacks a unified analysis that connects these standardization milestones to the concrete technical gaps that 6G must resolve. This study addresses this omission through a cross-release, application-driven review that traces how the evolution from enhanced mobile broadband to intelligent, sensing integrated networks lays the foundation for three core 6G service pillars: immersive communication (IC), everything connected (EC), and high-precision positioning. By examining use cases such as holographic telepresence, cooperative drone swarms, and large-scale Extended Reality (XR) ecosystems, this study exposes the limitations of today’s spectrum strategies, network architectures, and device capabilities and identifies the performance thresholds of Tbps-level throughput, sub-10 cm localization, sub-ms latency, and 10 M/km² device density that next-generation systems must achieve. The novelty of this review lies in its synthesis of 3GPP advancements in XR, the non-terrestrial network (NTN), RedCap, ambient Internet of Things (IoT), and consideration of sustainability into a cohesive key performance indicator (KPI) framework that links future services to the required architectural and protocol innovations, including AI-native design and sub-THz operation. Positioned against global initiatives such as Hexa-X and the Next G Alliance, this paper argues that 6G represents a fundamental redesign of wireless communication advancement in 5G, driven by intelligence, adaptability, and long-term energy efficiency to satisfy diverse uses cases and requirements. Full article

The calculation of the limiting efficiency and structural optimization of solar cells based on the detailed balance principle is systematically investigated in this study. Through modeling and numerical simulations of various cell architectures, the theoretical efficiency limits of these structures under AM1.5G (Air Mass 1.5 Global) spectrum were quantitatively evaluated. Through a comprehensive consideration of the effects of bandgap and composition, the Al_0.03Ga_0.97As/Ge (1.46 eV/0.67 eV) cell configuration was determined to achieve a high theoretical efficiency of 43.0% for two-junction cells while maintaining satisfactory lattice matching. Furthermore, the study proposes that incorporating a Ga_0.96In_0.04As (8.3 nm)/GaAs_0.77P_0.23 (3.3 nm) strain-balanced multiple quantum wells (MQWs) structure enables precise bandgap engineering, modulating the effective bandgap to the optimal middle-cell value of 1.37 eV, as determined by graphical analysis for triple junctions. This approach effectively surpasses the efficiency constraints inherent in conventional bulk-material III–V semiconductor solar cells. The results demonstrate that an optimized triple-junction solar cell with MQWs can theoretically achieve a conversion efficiency of 51.5%. This study provides a reliable theoretical foundation and a feasible technical pathway for the design of high-efficiency solar cells, especially for the emerging MQW-integrated III–V semiconductor tandem cells. Full article

This critical review explores the transformative impact of artificial intelligence (AI), particularly machine learning (ML) and computer vision (CV), on scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) for metallic microstructure analysis, spanning research from 2010 to 2025. It critically evaluates how AI techniques balance automation, accuracy, and scalability, analysing why certain methods (e.g., Vision Transformers for complex microstructures) excel in specific contexts and how trade-offs in data availability, computational resources, and interpretability shape their adoption. The review examines AI-driven techniques, including semantic segmentation, object detection, and instance segmentation, which automate the identification and characterisation of microstructural features, defects, and inclusions, achieving enhanced accuracy, efficiency, and reproducibility compared to traditional manual methods. It introduces the Microstructure Analysis Spectrum, a novel framework categorising techniques by task complexity and scalability, providing a new lens to understand AI’s role in materials science. The paper also evaluates AI’s role in chemical composition analysis and predictive modelling, facilitating rapid forecasts of mechanical properties such as hardness and fracture strain. Practical applications in steelmaking (e.g., automated inclusion characterisation) and case studies on high-entropy alloys and additively manufactured metals underscore AI’s benefits, including reduced analysis time and improved quality control. Extending prior reviews, this work incorporates recent advancements like Vision Transformers, 3D Convolutional Neural Networks (CNNs), and Generative Adversarial Networks (GANs). Key challenges—data scarcity, model interpretability, and computational demands—are critically analysed, with representative trade-offs from the literature highlighted (e.g., GANs can substantially augment effective dataset size through synthetic data generation, typically at the cost of significantly increased training time). 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

The increasing demand for efficient parking lots in urban environments has intensified research into puzzle-based storage parking systems. However, this high-density approach introduces challenges related to optimizing retrieval time and determining efficient vehicle access paths. Research shows that standardized testing platforms are needed to enable fair comparisons of algorithmic approaches in the puzzle-based storage (PBS) field. This study introduces a comprehensive, modular, and free environment for the systematic evaluation of shortest-path algorithms within PBS problems. The paper provides a practical example of the environment’s application and outlines future development perspectives. Moreover, the article provides a comparative analysis of vehicle retrieval performance across a spectrum of scenarios, including variations in parking lot dimensions, occupancy densities, movement strategies (orthogonal versus octilinear), and input/output point configurations. Experiments reveal that grid size, storage density, and depot placement significantly influence retrieval efficiency, computational complexity, and solution optimality, which is consistent with the literature. This study demonstrates that the environment encompasses all essential elements for conducting research and allows reliable comparisons of results across various algorithm implementations. Full article

With the aid of non-orthogonal multiple access (NOMA), this paper investigates simultaneous two-way communications for cooperative cognitive radio networks, where a group of secondary access points (APs) scattered over a primary cell not only serve their own users but also help the primary cell-edge users′ transmissions cooperatively. As a reward for the cooperation, these APs are granted full access to the primary frequency spectrum. To coordinate the two-way transmissions of the primary and secondary networks, we propose a spectrum-efficient cooperative scheme that only involves two transmission phases, and particularly, the two variable-length transmission phases endow the system with the capability of adapting to possible DL and UL traffic asymmetry. For the system design, we formulate a power minimization problem subject to the bidirectional transmission rate constraints of both networks. The formulated problem is shown to be nonlinear and nonconvex, and for the numerically efficient solution, we propose an iterative algorithm facilitated by the successive convex approximation technique. Simulation results show that the proposed design algorithm has fast convergence speed and is superior to the hybrid orthogonal multiple access and NOMA schemes. Full article