Search Results (393)

Two-dimensional GaS_xTe_1−x alloy nanosheets with different compositions were synthesized by chemical vapor deposition using GaS and GaTe powders as precursors. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) analyses confirmed their sheet-like morphology and the uniform distribution of S and Te, while Raman and photoluminescence measurements revealed composition-dependent vibrational and emission characteristics. Te-rich samples exhibited position-dependent emission ranging from the red to the near-infrared region, whereas increasing the S content gradually shifted the emission toward the blue-green region. Among the synthesized samples, GaS_0.9Te_0.1 showed a relatively stable photoluminescence peak near 520 nm and was therefore selected as a fluorescent powder for latent fingermark development. Its performance was evaluated on glass, stainless steel, plastic, and ceramic surfaces and compared with that of silver powder, gold powder, and commercial red fluorescent powder. GaS_0.9Te_0.1 produced clear fluorescent ridge patterns and strong background contrast, particularly on glass, plastic, and white ceramic. The mean contrast across the four substrates reached 25.83, exceeding that of the reference powders. These results demonstrate that GaS_xTe_1−x nanosheets possess tunable optical properties and that GaS_0.9Te_0.1 is a promising fluorescent material for latent fingermark development on non-porous surfaces. Full article

Though a number of Eimeria species have been described in geese, the host responses to these parasites at the molecular level have yet to be explored. In the present study, fresh fecal samples were collected for single-oocyst isolation. The recovered oocysts were identified based on molecular analysis using PCR and sequencing. Subsequently, we examined the transcriptional response of the Landes goose cecum following infection with the isolated Eimeria strain. Molecular analysis showed that the isolated Eimeria strain was Eimeria stigmosa, which was named the E. stigmosa SX-01 strain. Transcriptomic profiling identified 3806 differentially expressed genes (DEGs), including 2238 genes with increased expression and 1568 genes with decreased expression. The results obtained from the quantitative reverse transcription PCR (qRT-PCR) analysis confirmed that the RNA sequencing (RNA-seq) data were reliable. According to pathway enrichment analysis for the obtained DEGs, 24 pathways were significantly affected following infection with the E. stigmosa SX-01 strain, such as cytokine–cytokine receptor interaction, intestinal immune network for IgA production, cell adhesion molecules, gap junction, arachidonic acid metabolism, alpha-Linolenic acid metabolism, retinol metabolism, and PPAR signaling pathway. These transcriptional alterations were observed in E. stigmosa-infected geese without obvious clinical signs, indicating that E. stigmosa infection may trigger a strong subclinical host response related to metabolism, immune and inflammatory responses, and intercellular junctional complex-associated processes. Collectively, these findings have implications for better understanding the E. stigmosa–goose interactions at the molecular level and provide a foundation for future functional and comparative studies to dissect the pathogenic mechanisms and molecular markers associated with disease resistance, which are expected to inform the design of effective control strategies. Full article

It is imperative that freshwater fish biodiversity research incorporates diverse components, encompassing taxonomy, phylogeny and function, alongside multifaceted facets, including richness, divergence and regularity. This comprehensive approach is essential to facilitate a more profound comprehension of freshwater ecosystem functions, to elucidate the mechanisms underpinning fish community assembly, and to accurately assess the impacts of anthropogenic disturbance. Consequently, this scientific understanding can inform the development of effective fish conservation and ecosystem management strategies. This study utilized environmental DNA metabarcoding to assess the diversity of fish across the entire Yangtze River, encompassing the upper reach (Upper), the Three Gorges Reservoir area (RES_SX), and the downstream reach (Down). The results indicated that 150 distinct fish species were detected, with the RES_SX area exhibiting a significantly lower taxonomic diversity and fish detection rate in comparison to the other two regions. Conversely, phylogenetic and functional diversity exhibited stability post-normalization by taxonomic richness. Furthermore, investigation of the divergence facet of alpha-diversity demonstrated a reduction in clustering and an improvement of overdispersion on the phylogenetic and functional diversity, respectively, in the RES_SX and Down regions. Beta-diversity analysis further revealed lower taxonomic beta-diversity but higher phylogenetic and functional beta-diversity in the RES_SX area. A substantial degree of geographic distance-dependent similarity was identified for all three components of beta-diversity in the Upper Reach. Conversely, these components were found to be disrupted in the Down Reach. Finally, an analysis of the assembly mechanism revealed stochastic processes, dispersal limitation and drift as the dominant factors shaping the fish communities, with reduced dispersal limitation in the RES_SX area. This study provides novel insights into the multidimensional diversity of fish populations in response to dam construction, emphasizing the necessity of integrating multiple facets of diversity for accurate impact assessment and supporting evidence-based conservation of fish species in the Yangtze River. Full article

The rapid proliferation of Internet of Things (IoT) technologies and smart grids has substantially intensified the cybersecurity challenges associated with smart energy meters (SEMs). The data collected by the plugs are transmitted via a wireless communication protocol to a smart electricity meter that acts as a local gateway. This meter centralizes the information from the various sensors, may perform data pre-processing, aggregation, or validation operations, and then forwards the information to a central server. The main contributions of this system can be categorized into two key aspects. First, the implementation of a centralized wireless local energy consumption network using the Wi-Fi protocol to coordinate smart plugs over distances of up to 20 m. Second, the real-time acquisition of power characteristics and the remote control (ON/OFF switching) of household appliances for direct appliance-level submetering purposes. Data collected by the smart meter are transmitted to a processing unit through a Semtech SX1276 LoRa transceiver communication link. The central server constitutes the processing and storage layer of the system: it receives the collected data, archives it in a dedicated database, and makes it available through analysis, visualization, and decision-support tools. This architecture enables real-time monitoring of energy consumption, anomaly detection, optimization of electrical resource use, and the development of effective energy management strategies for smart electrical grids. Although current smart meter architectures incorporate multi-layer protection mechanisms at the hardware, communication, and data levels, additional security measures are required to counter advanced cyber threats aimed at data interception and manipulation. This paper improves the security framework of smart energy meters by integrating a chaos-based encryption layer to ensure secure data transmission. Chaotic systems exhibit intrinsic properties such as sensitivity to initial conditions, pseudo-randomness, and ergodicity, which render them particularly suitable for cryptographic applications. The proposed framework employs a Lorenz-based chaotic encryption module to secure SEM-utility data exchanges. Full article

Objective, noninvasive biomarkers of joint inflammation or pain are needed for dogs with osteoarthritis (OA). This prospective, observational study investigated whether body surface temperature quantified by infrared thermography was associated with joint pain and/or radiographic osteoarthritis (rOA) in dogs. Using thermal images, 14 regions of interest (ROI) were created for bilateral limb joints and the vertebral column for each dog and the mean temperature was calculated for each ROI. Orthopedic examination and radiographs classified each joint/region as affected or unaffected by rOA, pain, or both, called symptomatic OA (sxOA). Mean temperatures were compared between affected and unaffected joints. Eighteen dogs were enrolled, encompassing analysis of 250 ROI (rOA = 83/250, 33%; pain = 83/250, 33%; sxOA = 61/250, 24%). No temperature differences were detected between affected and unaffected joints for rOA (0.405 °C, 95% CI [−0.204, 1.025 °C]), pain (0.208 °C, 95% CI [−0.390, 0.806 °C]), or sxOA (0.276 °C, 95% CI [−0.344, 0.915 °C]). Elbow and stifle regions were warmer, and the lumbosacral region was cooler than the carpus. Long-haired dogs were cooler than short-coated dogs. Regional temperature variability and haircoat type might hinder detection of OA-related thermal signals. In dogs with OA, findings do not support infrared thermography as a standalone tool to identify affected joints. Full article

Introduction: Osteoporosis is a debilitating bone disease that affects a large segment of the population. Currently, pharmacological treatment options for osteoporosis, including antiresorptive drugs and those that prevent bone loss, are limited. Multiple studies have shown that the endocannabinoid system and cannabis may play a significant role in bone remodeling. As both the use of cannabis and high-quality research on its effects continue to grow, novel medicinal uses of selected components, such as tetrahydrocannabinol (THC), are being investigated. The present study examined the potential effect of chronic THC inhalation during early adulthood on an ovariectomized rodent model of post-menopausal osteoporosis. Materials and Methods: Young (26-week-old) adult female rats received daily either THC or air inhalation for 8 weeks. The rats then underwent an ovariectomy (OVX) or sham surgery (Sx) when they were 34 weeks old. They were then euthanized 4 weeks post-OVX, and skeletal tissues were collected for analysis. Results: MicroCT analysis of femora showed that THC + OVX rats showed a significant decrease (45%) in trabecular bone volume compared to Air + Sham Sx rats. As expected, the Air + OVX rats also showed a 17% reduction in trabecular bone volume. Discussion: Overall, early adulthood THC exposure increased susceptibility to osteoporosis following ovariectomy-induced menopause. This suggests that THC exerts long-lasting effects on bone health, which may exacerbate post-menopausal bone loss. Full article

Wireless sensor networks have become essential tools for environmental monitoring, enabling distributed data acquisition in remote and dynamic environments. However, challenges related to communication reliability, energy efficiency, synchronization, and real-time data availability remain critical for long-term deployments. This work presents the design, implementation, and validation of a synchronous wireless sensor network tailored for environmental monitoring in the challenging conditions of an estuarine setting. The proposed architecture is based on Digi XBee SX 868 RF modules operating in DigiMesh mode with synchronized cyclic sleep, enabling coordinated measurements and low-power operation. The network comprises monitoring, repeater, and coordinator/gateway nodes, integrated with a web-based platform for real-time data visualization and management. A custom message exchange format was developed to support seamless transmission of monitoring information from sensors to the web server through the wireless mesh infrastructure. Field experiments were conducted to evaluate network coverage, synchronization performance, communication reliability, and energy consumption. The results demonstrated successful multi-hop communication over the estuarine area, stable synchronization among distributed nodes over extended periods, and energy savings through synchronized sleep operation. The developed web platform enabled reliable real-time data access and network management. The proposed system demonstrates the feasibility of deploying scalable, energy-efficient, and synchronized wireless sensor networks for long-term environmental monitoring in estuarine environments. Full article

Platinum group metals (PGMs) play a key role in many industries. However, the growing demand for PGMs, the systematic decline in their natural resources, and the generation of large amounts of waste, constituting a secondary source, are closely related to the search for effective and environmentally safe methods for their separation. Although solvent extraction (SX) processes, long used to extract PGMs from various ores/waste leachates, typically allow for effective separation of these valuable metals, they rely primarily on the use of organic solvents, many of which are environmentally hazardous. Therefore, recent research efforts have focused, among others, on the utilization of potentially “greener” chemicals, such as ionic liquids (ILs) and deep eutectic solvents (DESs). Due to their tunable properties to specific applications, these chemicals usually enable not only efficient (often >90%) but also selective and more eco-safe separation of PGMs from various matrices. This review concerns the latest developments in the SX of PGM ions from aqueous solutions and suspensions using ILs and DESs (e.g., as extractants, solvents, and leaching agents), taking into account their most important advantages, limitations, and potential impact on the environment. IL- and DES-based SX methods fit into the green chemistry trend and are consistent with sustainable development goals. Full article

Cobalt has emerged as a strategic critical metal due to its essential role in rechargeable batteries, high-performance alloys, catalysts, and clean energy technologies. However, its supply chain remains heavily dependent on cobalt produced as a by-product of copper and nickel mining and is geographically concentrated, particularly in the Democratic Republic of Congo. This review provides a comprehensive assessment of cobalt geology, mineralogy, global reserves, market trends, primary extraction routes, and emerging secondary recovery strategies. Unlike previous reviews that address these topics separately, this work integrates geological occurrence, mineralogical characteristics, extraction technologies, and resource circularity within a unified framework aimed at evaluating future cobalt supply resilience. The main cobalt-bearing deposit types of sediment-hosted Cu–Co deposits, Ni–Co laterites, and magmatic Ni–Cu–Co sulphide deposits are compared in terms of their mineralogical characteristics and processing requirements. Hydrometallurgy is identified as the dominant industrial route, typically combining high-pressure acid leaching (HPAL) with downstream purification and recovery processes such as solvent extraction and electrowinning (SX–EW). Emphasis is placed on the relationship between ore mineralogy and process selection, as well as on the growing integration of secondary resources, including tailings, slags, and spent batteries, into existing cobalt production chains. Despite promising recovery rates at laboratory scale, challenges remain in impurity control, economic scalability, and integration into established refining infrastructure. This review demonstrates that secondary resources are evolving from supplementary feedstocks to strategically important contributors to cobalt supply. Future supply security will depend on feedstock diversification, more flexible refining systems, improved impurity management, and the implementation of sustainable circular-economy strategies. Full article

This study investigated whether neuro-exergaming with an interactive physical and cognitive exercise system (iPACES), might alleviate symptoms in college students with symptoms of Attention Deficit Hyperactivity Disorder (sxADHD). It was hypothesized that challenges with attention and executive function, often experienced by those with sxADHD, would improve after an acute bout of pedal-n-play exercise. College students (n = 33; 18 with sxADHD) participated in a 20 min single bout of exercise, pedaling along a virtual pathway (tour), while steering the tablet. Mental exercise included a working memory (focus) task to steer toward assigned locations along the path. An exploratory experimental condition was also embedded in the basic pre/post design, wherein half of the students were randomly assigned collectibles (coins) in the pathway. Cognition was assessed (e.g., paper and digital Stroop, Trails, Digit Span) before and after the acute bout of exercise. Paired t-tests revealed significant improvements in executive function on both paper and electronic Stroop tasks for those with sxADHD, while significant change was also seen on Trails and Digit Span for normative students. Surprisingly, those with sxADHD, assigned to the experimental “multi-tasking” collectible (coin) challenge, performed significantly better on tests of executive functioning than normative peers, who improved more without coins. It is hypothesized that the collectible challenge provided additional mental stimulation or reward needed to increase attentional focus for those with sxADHD, leading to improved performance, post-exercise. While the findings of this study are preliminary, additional research can further explore possible designs for combined, interactive mental and physical exercise challenges, as well as further possible synergistic or differential neural activation, in order to maximize outcomes from the same amount of time exercising. Additionally, future research could examine longer-term use of neuro-exergaming, through a clinical trial, as an alternative to, or in conjunction with, medication for sxADHD treatment and symptom relief. Full article

Alkaline nickel zinc batteries feature high safety, low cost and eco-friendly characteristics, making them highly promising for large-scale energy storage deployment. However, their practical application is severely constrained by the cathode’s electrical conductivity, available active sites, and cycling stability. Herein, vertical 2D hierarchical flake-like NiCoS_x arrays were in situ grown on nickel foam (NF) via a facile alkali-free solvothermal and in situ sulfidation approach. This highly interconnected and open porous flaky structure significantly shortens the ion diffusion pathways, exposes abundant redox-active sites, and accelerates electron transport, imparting excellent rate performance and superior long-cycle stability to the material. The optimized NiCoS_x/NF electrode achieves a high specific capacity of 323 mAh g⁻¹ at 0.5 A g⁻¹, along with excellent capacity retention capability. Assembled with a commercial Zn anode, the NiCoS_x/NF//Zn full battery delivers 124 mAh g⁻¹ at 3 A g⁻¹, and maintains 112.5% of the initial capacity after 500 cyclic tests. Moreover, the assembled NiCoS_x/NF//Zn full cell possesses a high energy density of 615.2 Wh kg⁻¹ along with a power density of 38.6 kW kg⁻¹ (based on the mass of positive electrode active materials). This unique vertical 2D open hierarchical structure plays a crucial role in enhancing the electrochemical performance of cobalt sulfide cathodes and provides valuable insights for the design of high-performance alkaline zinc-based battery electrodes. Full article

To meet the increasing demands of aircraft engines for high thrust-to-weight ratios and elevated turbine inlet temperatures, turbine blades have been progressively designed with thin-walled structures. It has been demonstrated that the mechanical properties of Ni₃Al-based single-crystal alloys (SXs) are highly sensitive to specimen thickness. In this study, the high-cycle fatigue behavior of [111]-oriented Ni₃Al-based SXs with wall thicknesses of 0.3, 0.5, and 0.8 mm was systematically investigated under tensile–tensile loading conditions at 1000 °C. The results revealed that, as the wall thickness decreased, the fatigue life of the alloy significantly deteriorated, while the crack initiation site gradually shifted from the specimen interior toward the surface and near-surface regions. Furthermore, the fatigue failure mode transitioned from being dominated by internal defects to being controlled primarily by near-surface damage. Near-surface damage induced by high-temperature oxidation and geometric constraints was identified as the primary factor responsible for the degradation of the high-cycle fatigue performance of the SXs. In addition, the cyclic deformation behavior at 1000 °C was governed by the synergistic effects of dislocation climb, cross-slip, and γ′-phase shearing. This study provides both theoretical guidance and experimental evidence for the structural optimization of next-generation single-crystal turbine blades for advanced aircraft engines. Full article

Accurate performance prediction for large offshore wind turbines requires a principled treatment of uncertainty in both the wind resource and the rotor design parameters. In the present work, we develop a surrogate-based, multi-level uncertainty quantification (UQ) framework coupling a physics-based Blade Element Momentum (BEM) solver with a spectral Polynomial Chaos Expansion (PCE) surrogate that replaces the expensive Monte Carlo loop and apply it to the IEA 15 MW offshore reference wind turbine. The framework is completed by Sobol variance-based global sensitivity analysis. The contribution is methodological rather than algorithmic: although each individual ingredient (PCE, Sobol, BEM, and Jensen) is well established, their joint deployment in a single, internally consistent, end-to-end probabilistic workflow that simultaneously delivers (i) aerodynamic–structural UQ with analytical Sobol ranking, (ii) a like-for-like cross-comparison of three reference turbines, (iii) a quantitative leading-edge icing degradation study, and (iv) a farm-level wake-steering optimization on the same IEA 15 MW reference rotor yields a unified probabilistic envelope from which manufacturing tolerances, cold-climate investment thresholds, and farm-layout/control trade-offs can be read off consistently. Five input parameters are treated as random variables: hub-height wind speed (Weibull, k = 2.2, c = 9.8 m/s), air density, blade chord length, twist angle, and rotor speed. A degree-4 sparse PCE is built by non-intrusive spectral projection using N = 5000 Sobol quasi-random realizations, which allows the Sobol indices to be recovered analytically from the expansion coefficients at essentially no extra cost. Three parallel engineering studies complement the core UQ analysis: (A) a head-to-head comparison of the NREL 5 MW, DTU 10 MW, and IEA 15 MW reference turbines; (B) a quantitative assessment of leading-edge ice accretion at four severity levels; and (C) a Jensen-based wake optimization for a 25-turbine offshore array with static wake steering. The main results are as follows: the turbine reaches C_p,max = 0.480 at λ_opt = 8.51, and an annual energy production (AEP) of 71,261 MWh/year (PCE: 70,840 ± 2,140 MWh/year, 95% CI). Wind speed emerges as the dominant driver of C_p variance (S₁ = 0.412), followed by blade twist (0.198) and chord (0.143). Severe icing (30 kg/m) reduces C_p by 18.2% and increases the blade-root Damage Equivalent Load (DEL) by 18.5%. For the array, the optimal spacing (s_x = 8D, s_y = 6D) gives a farm efficiency of 89.6% and 1296 GWh/year, and a 15° wake-steering offset adds a further +3.2% to farm AEP. Compared with plain Monte Carlo, the sparse PCE delivers the same statistics with about 36% fewer model evaluations and a relative error below 0.8%. Full article

Accurate path-loss models are essential for planning reliable wireless networks in underground mines, yet existing characterization studies rely on specialized channel sounders and vector network analyzers costing tens of thousands of dollars, placing them beyond the reach of most mine operators. This paper demonstrates that LoRa transceivers costing approximately US $15 per node can serve as a self-contained path-loss measurement instrument, logging the received signal strength indicator (RSSI) and signal-to-noise ratio (SNR) directly to a CSV file over a standard USB serial connection. A measurement campaign conducted at the Missouri S&T Experimental Mine on 31 March 2026 collected 4801 packets across four distinct underground canonical primitives: straight tunnel, T-junction, vertical shaft, and post-bend NLoS gallery at distances of 5 to 60 m using Waveshare Pico-LoRa-SX1262 boards operating at 915 MHz. The results reveal a pronounced two-zone propagation structure, including a line-of-sight (LoS) zone with a negative path-loss exponent of −0.34, confirming tunnel waveguide gain up to 25 m, followed by a steep NLoS zone with an exponent of 13.0 after a 24.0 dB bend diffraction loss. Environment-specific measurements quantify a 5.5 dB junction excess loss and a 29.5 dB shaft excess loss relative to a straight-tunnel reference. Spreading factor sensitivity tests across SF7, SF9, and SF12 confirm that RSSI measurements are consistent to within 2 dB across all SFs, validating the measurement methodology. The resulting four-zone path-loss model provides mine network planners with parameters sufficient for LoRa link budget design and relay node placement without any specialized RF instrumentation. Full article

Background: Long-term diabetes mellitus may precipitate severe complications, including cognitive dysfunction. Existing research has shown that diabetic cognitive impairment (DCI) in rats is characterized by memory deterioration and a disordered arrangement of hippocampal cells. The Shichangpu–Xiyangshen herb pair (SX) effectively improved the pathological changes induced by DCI. However, the role of SX in regulating the physiological and behavioral responses to DCI remains unclear. Methods: We sought to determine the small-molecule metabolites of cerebrospinal fluid (CSF) and delineate the pathways to elucidate the potential mechanism of the effect of SX in the treatment of DCI by metabolomics strategies, focusing on key mechanisms. Behavioral assessments were conducted on DCI rats and the rats treated with SX, as well as an evaluation of neuronal morphology in the hippocampal region. Metabolomics was used to analyze biomarkers in cerebrospinal fluid at different time points during the development of DCI, to uncover the underlying core mechanisms of DCI, and to investigate the regulatory effects of SX on these core mechanisms. The mechanisms of SX on DCI were investigated using quantitative reverse transcription polymerase chain reaction, immunohistochemistry, Western blot, and ELISA. Results: The Morris water maze (MWM) and social interaction test results revealed that SX administration effectively counteracted cognitive impairments in rats with DCI while simultaneously diminishing pathological damage in the CA1, CA3, and DG hippocampal regions. Further analysis showed that SX restored the significantly reduced levels of IL-8, ROX, and TNF-α, and reduced Aβ plaque formation (as indicated by APP and BACE1 protein expression). Simultaneously, SX markedly ameliorated arachidonic acid metabolic disorders in DCI, including significant reductions in arachidonic acid (AA), PGE2, and LTB4 and reduced expression of COX-2 (PTGS2) and 5-LOX (ALOX-5). Conclusions: Our findings indicate that SX effectively counteracted cognitive impairment in rats with DCI by inhibiting AA metabolism through both cyclooxygenase and lipoxygenase pathways, thereby minimizing neuronal damage. Full article