Search Results (524)

Background: Acinetobacter baumannii (A. baumannii) has emerged as a critical human pathogen, causing high mortality rates among hospitalized patients and frequently triggering nosocomial outbreaks. The increasing prevalence of multidrug-resistant (MDR) A. baumannii poses a pressing threat to public health. To date, no commercially available vaccine against A. baumannii has been developed for clinical use. messenger RNA (mRNA)–lipid nanoparticle (LNP) vaccines have emerged as a promising vaccination strategy. Methods: In this work, we developed two mRNA vaccines targeting SmpA-PLD and the fusion protein of outer membrane proteins OmpK and Omp22. The mRNA was encapsulated in LNP and administered to BALB/c mice. We evaluated humoral and cellular immune responses, bacterial burden, inflammation, and protective efficacy against A. baumannii infection in a sepsis model. Results: These mRNA vaccines triggered robust humoral and cellular immune responses in BALB/c mice, reduced bacterial burden and inflammation in sepsis models, and provided significant protection against A. baumannii infection. Notably, the OmpK-Omp22 vaccine exhibited superior protective efficacy, reducing bacterial loads in various organs and improving survival rates in the sepsis model compared to the SmpA-PLD vaccine. Conclusions: Our findings demonstrate mRNA-LNP vaccine technology as a versatile and promising platform for the development of innovative therapeutics against A. baumannii, with the potential to mitigate acute disease and promote bacterial decolonization. These findings pave the way for the development of urgently needed and effective antibacterial vaccines. Full article

Recent advancements in polymer science have catalyzed a transformative shift in biomedical engineering, particularly through the development of biodegradable and smart polymers. This review explores the evolution, functionality, and application of these materials in areas such as tissue scaffolding, cardiovascular occluders, and controlled drug delivery systems. Emphasis is placed on shape-memory polymers (SMPs), conductive polymers, and polymer-based composites that combine tunable degradation, mechanical strength, and bioactivity. The synergy between natural and synthetic polymers—augmented by nanotechnology and additive manufacturing—enables the creation of intelligent scaffolds and implantable devices tailored for specific clinical needs. Key fabrication methods, including electrospinning, freeze-drying, and emulsion-based techniques, are discussed in relation to pore structure and functionalization strategies. Finally, the review highlights emerging trends, including ionic doping, 3D printing, and multifunctional nanocarriers, outlining their roles in the future of regenerative medicine and personalized therapeutics. Full article

Addressing the urgent need for lightweight and reusable energy-absorbing materials in aviation impact resistance, this study introduces an innovative multi-directional braided metamaterial design enabled by 4D printing technology. This approach overcomes the dual challenges of intricate manufacturing processes and the limited functionality inherent to traditional textile preforms. Six distinct braided structural units (types 1–6) were devised based on periodic trigonometric functions (Y = A sin(12πX)), and integrated with shape memory polylactic acid (SMP-PLA), thereby achieving a synergistic combination of topological architecture and adaptive response characteristics. Compression tests reveal that reducing strip density to 50–25% (as in types 1–3) markedly enhances energy absorption performance, achieving a maximum specific energy absorption of 3.3 J/g. Three-point bending tests further demonstrate that the yarn amplitude parameter A is inversely correlated with load-bearing capacity; for instance, the type 1 structure (A = 3) withstands a maximum load stress of 8 MPa, representing a 100% increase compared to the type 2 structure (A = 4.5). A multi-branch viscoelastic constitutive model elucidates the temperature-dependent stress relaxation behavior during the glass–rubber phase transition and clarifies the relaxation time conversion mechanism governed by the Williams–Landel–Ferry (WLF) and Arrhenius equations. Experimental results further confirm the shape memory effect, with the type 3 structure fully recovering its original shape within 3 s under thermal stimulation at 80 °C, thus addressing the non-reusability issue of conventional energy-absorbing structures. This work establishes a new paradigm for the design of impact-resistant aviation components, particularly in the context of anti-collision structures and reusable energy absorption systems for eVTOL aircraft. Future research should further investigate the regulation of multi-stimulus response behaviors and microstructural optimization to advance the engineering application of smart textile metamaterials in aviation protection systems. Full article

Badminton is an intermittent sport with a diverse exercise profile that stresses both aerobic and anaerobic energy systems. The aim of this study was to compare the internal and external load profiles of multi-feeding (MF) drills and simulated match play (SMP) in elite junior badminton players, and to explore potential sex-based differences. Forty-two players (24 males (age 17.4 ± 2.6 years, training experience 9.9 ± 1.8 years) and 18 females (age 16.9 ± 2.9 years, training experience 9.4 ± 2.1 years)) completed MF and SM sessions while external load (e.g., relative distance, explosive distance, relative jumps) and internal load (heart rate [HR], session rating of perceived exertion [sRPE]) variables were recorded using inertial measurement units and HR monitors. Two-way ANOVA revealed that MF induced significantly greater external (p < 0.05) and internal (p < 0.001) loads compared to SM, with large effect sizes. Male players showed markedly higher jump frequency (1.60 n/min vs. 0.80 n/min) and maximum speed (19.80 km/h vs. 15.80 km/h), although HR and sRPE values were similar between sexes (p > 0.05), suggesting that female athletes may experience greater relative physiological load. These findings highlight the importance of using MF drills to target specific conditioning goals and reinforce the need for individualized training strategies considering sex differences. Full article

Electricity theft remains a pressing challenge in modern smart grid systems, leading to significant economic losses and compromised grid stability. This paper presents a sensor-driven framework for electricity theft detection that leverages data collected from smart meter sensors, key components in smart grid monitoring infrastructure. The proposed approach combines prototype learning and meta-level ensemble learning to develop a scalable and accurate detection model, capable of identifying zero-day attacks that are not present in the training data. Smart meter data is compressed using Principal Component Analysis (PCA) and K-means clustering to extract representative consumption patterns, i.e., prototypes, achieving a 92% reduction in dataset size while preserving critical anomaly-relevant features. These prototypes are then used to train base-level one-class classifiers, specifically the One-Class Support Vector Machine (OCSVM) and the Gaussian Mixture Model (GMM). The outputs of these classifiers are normalized and fused in a meta-OCSVM layer, which learns decision boundaries in the transformed score space. Experimental results using the Irish CER Smart Metering Project (SMP) dataset show that the proposed sensor-based detection framework achieves superior performance, with an accuracy of 88.45% and a false alarm rate of just 13.85%, while reducing training time by over 75%. By efficiently processing high-frequency smart meter sensor data, this model contributes to developing real-time and energy-efficient anomaly detection systems in smart grid environments. Full article

A lightweight YOLOv8 variant, CIMB-YOLOv8, is proposed to address challenges in remote sensing object detection, such as complex backgrounds and multi-scale targets. The method enhances detection accuracy while reducing computational costs through two key innovations: Contextual Multi-branch Fusion: Integrates a space-to-depth multi-branch pyramid (SMP) to capture rich contextual features, improving small target detection by 1.2% on DIOR; Lightweight Architecture: Employs Lightweight GroupNorm Detail-enhance Detection (LGDD) with shared convolution, reducing parameters by 14% compared to YOLOv8n. Extensive experiments on DIOR, DOTA, and NWPU VHR-10 datasets demonstrate the model’s superiority, achieving 68.1% mAP on DOTA (+0.7% over YOLOv8n) and 82.9% mAP on NWPU VHR-10 (+1.7%). The model runs at 118.7 FPS on NVIDIA 3090, making it well-suited for real-time applications on resource-constrained devices. Results highlight its practical value for remote sensing scenarios requiring high-precision and lightweight detection. Full article

Pulse-width modulation (PWM) and pulse-density modulation (PDM) are widely used in applications where electrical energy is delivered in a pulsed manner. Typical examples include LED (light-emitting diode) control, DC motor control, switched-mode power supplies (SMPS), and electric heating control. However, the pulsed operation of power switches is often associated with significant electromagnetic interference (EMI). As an alternative, stochastic pulse-density modulation (SPDM), also referred to as stochastic signal density modulation (SSDM), can be considered. This technique distributes the energy of generated harmonics over a broader frequency spectrum, thereby reducing the amplitude of individual frequency components. As a result, unwanted frequencies become easier to filter out, mitigating EMI more effectively. Full article

The design of high-performance drilling fluid systems is of vital importance for the safe and efficient exploitation of natural gas hydrates. Incorporating appropriate nanoparticles into drilling fluids can significantly enhance drilling fluid loss control, wellbore stability, and hydrate inhibition. However, the combined effects of nanoparticles and conventional additives on hydrate inhibition in drilling fluid systems remain poorly understood. In this study, the influence of nanoparticles on hydrate formation was first evaluated in a base mud, followed by an investigation of their combined effects with common drilling fluid additives. The results demonstrate that hydrophilic nano-CaCO₃ particles exhibit hydrate inhibitory effects, with the strongest inhibition observed at 3.0%. Composite system tests (incorporating nanoparticles with sepiolite, filtrate reducers, and flow modifiers) revealed diverse effects on hydrate formation. Specifically, the combination of nanoparticles and sepiolite promoted hydrate formation; the combination of nanoparticles and filtrate reducers showed divergent effects. Mixtures of nanoparticles with 0.2% low-viscosity anionic cellulose (LV-PAC), carboxymethyl starch (CMS), and low-viscosity carboxymethyl cellulose (LV-CMC) inhibited hydrate formation, while mixtures with 0.2% sulfonated phenolic resin (SMP-2) and hydrolyzed ammonium polyacrylonitrile (NH₄-HPAN) accelerated hydrate formation. Notably, the incorporation of nanoparticles with 0.3% guar gum, sesbania gum, high-viscosity carboxymethyl cellulose (HV-CMC), or high-viscosity polyanionic cellulose (HV-PAC) resulted in the complete inhibition of hydrate formation. By contrast, the synergistic inhibition effect of the nanoparticle/xanthan gum (XC) composite system was relatively weak, with the optimal compounding concentration determined to be 0.3%. These findings provide critical insights for the development of drilling fluid systems in natural gas hydrate reservoirs, facilitating the optimization of drilling performance and enhancing operational safety in hydrate-bearing formations. Full article

Precision seeding plays a critical role in optimizing crop yield and resource efficiency. This study evaluates the application of a Seed Miss Prevention System (SMPS) integrated with a spoon-wheel precision metering device to mitigate seed misses and enhance its performance. A combination of Discrete Element Method (DEM) simulations, electrical hardware design, mechanical retrofitting, software development and laboratory experiments was employed to assess the effectiveness of the system across multiple seed cultivars and operating speeds. Experimental results demonstrated that the SMPS significantly reduced seed misses at lower operational speeds (3–10 rpm), with the implementation of a dual-sensor configuration further improving detection accuracy by filtering out false positives. At higher speeds (≥15 rpm), however, seed miss rates increased, particularly for irregularly shaped seeds like white beans ‘Great Northern’, due to the mechanical limitations of the metering device. Statistical analyses, including Tukey’s HSD test, confirmed the effectiveness of the SMPS in reducing miss rates across different seed types. Despite these improvements, complete elimination of seed misses was not achieved, highlighting the need for further optimization in seed miss detection. Future research should explore adaptations for higher-speed metering devices and field-scale validations. The findings underscore the potential of SMPS technology in advancing precision agriculture by improving seeding accuracy and operational efficiency. Full article

The aim of this study was to investigate the influence of genotype (GT) and seasonality (NP) on the quality parameters of sow colostrum and evaluate the efficiency of the radial immunodiffusion (RID) analysis and the Brix refractometer in determining the IgG concentration. This study was conducted on 240 sows that originated from two genotypes, namely GT1 (TOPIGS, n = 120) and GT2 (Pig Improvement Company, n = 120), during the three farrowing periods: the winter farrowing period (WNP, n = 80), the summer farrowing period (SMP, n = 80) and the spring farrowing period (SSP, n = 80). The significant interaction effect was observed for protein (p < 0.0001), lactose (p < 0.05) and non-fat solids (SNT) (p < 0.001). At the same time, the interaction effect influenced the IgG concentration measured with the Brix refractometer (p < 0.0001) and RID (p < 0.0001). Pearson’s correlation coefficient showed that Brix percentage was positively correlated with RID results (r = 0.52, p < 0.0001), while the Bland–Altman plots indicated a mean bias of −1.93. Partial eta-squared analysis (η²) showed that the genotype explained the largest proportion of variance in fat content (η² = 0.136) and IgG concentration (η² = 0.164), while interaction effects were largest for protein (η² = 0.072). The results of this study show that genotype and seasonality influence sow colostrum quality, which indicates the importance of genotype−seasonality interactions in breeding programs for optimizing the colostrum quality and piglet survival. Full article

With the worldwide spread of clear aligner treatment (CAT), a plethora of new thermoplastics is currently commercially available on the market, claiming to have superior properties and greater comfort. This review aims to summarise the properties of the materials and their effects on treatment effectiveness and comfort to ease material selection and also incorporate new emerging trends such as shape memory polymers (SMPs) and direct 3D printer aligners. First, a concise historical overview of orthodontics will be presented, along with the basic properties of thermoplastics and their importance in treatment. Following the individual properties, we present an analysis of optical, biocompatibility, and toxicity aspects, passing through others such as thermal, mechanical, and special methods to simulate in vivo measurements. We end with the impact of this technique on the environment and the advances and perspectives of CAT. Full article

Precision agriculture facilitates improved management by studying the spatial and temporal variability of soil attributes. Soybean (Glycine max (L.) Merrill) seeds may exhibit distinct quality when produced in different management zones. This study aimed to validate management zones during seed production and identify the variability and spatial distribution of soybean seed physiological quality using geostatistical tools. Management zones were defined based on interpolated maps of soil and vegetation attributes using the Smart Map Plugin (SMP) within the QGIS environment. Post-harvest, the variability of physiological seed quality across different management zones was assessed. Germination, accelerated aging, dry weight, emergence, electrical conductivity, and tetrazolium tests were conducted in a completely randomized design. Soil attributes, initial plant stand, and soybean seed productivity validated the management zones. Physiological seed quality varies across the production field, particularly in terms of vigor, thereby enhancing diagnostics through map interpolation. Geostatistics enable determination of the spatial distribution of soybean seed physiological quality in seed production areas, facilitating decision-making regarding harvest zones. Full article

Particulate matter is a mixture of fine dust and tiny droplets of liquid suspended in the air. PM₁₀ is a pollutant composed of particles smaller than 10 µm. These particles are harmful to the respiratory system. The air quality in the region and capital Lima in the Republic of Peru has been investigated in recent years. In this context, statistical analyses of PM₁₀ data with forecast models can contribute to planning actions that can improve air quality. The objective of this work is to perform a statistical analysis of the available PM₁₀ data and evaluate the quality of time series classical models and neural networks for short-term forecasting. This study demonstrates that classical time series models, particularly ARIMA and SSA, achieve lower average forecast errors than LSTM across stations SMP, CRB, and ATE. This finding suggests that for data with seasonal patterns and relatively short time series, traditional models may be more efficient and robust. Although neural networks have the potential to capture more complex relationships and long-term dependencies, their performance may be limited by hyperparameter settings and intrinsic data characteristics. Full article

Shape memory polymers (SMPs), due to the programmable deformation and recovery ability, exhibit widespread potential in fields of biomedical devices, smart actuators, and engineering structures. Thermoplastic SMPs, which possess the intrinsic linear molecular chain structures, are able to be processed through diverse methods, in addition to being re-processed after process-forming, compared with thermoset SMPs. The environmental recycling characteristics for thermoplastic SMPs describe their wide use potential and prospect. In this paper, a comprehensive description of mechanism, matrix polymers, actuations, and applications for thermoplastic SMPs and composites was reviewed. Furthermore, two promising potential developing directions, 4D printing metamaterial and dynamic covalent networks, were proposed. The multifunctionality and enhanced performances of thermoplastic SMPs and composites exhibited excellent application value, which is significant for future advancements. Full article

The improved multi-stage drip irrigation scheduling, combined with agronomic engineering, was successfully applied for spring re-vegetation in coastal saline soils. To date, few studies have addressed summer vegetation planting using this method. The aim of this study is to reveal the desalinization mechanism associated with summer afforestation and multi-stage drip irrigation. A three-year field experiment was conducted in the coastal saline land of southern China. The trial consisted of four irrigation stages, with the soil moisture potential (SMP) monitored directly beneath the drip emitter at a depth of 0.2 m, correspondingly controlled to be higher than −10 kPa (Stage I), −25 kPa (Stage II), and −45 kPa (Stage III), respectively. Results indicated that soil bulk density decreased by 14%, while soil moisture increased by 30% compared to initial conditions. The average electrical conductivity (EC) value across the entire soil layer decreased by 65.64% to 97.79%. Soil pH gradually increased during the first three irrigation stages, with the rate of increase accelerating during the rainfed stage, reaching values between 9.22 and 9.87. The concentrations of soil ions, including Ca²⁺, K⁺, Mg²⁺, Na⁺, and SO₄²⁻, decreased by 95.18%, 79.67%, 87.74%, 89.68%, and 57.19%, respectively, in the final irrigation stage. Throughout the entire soil profile, the average sodium adsorption ratio (SAR) decreased by 49.37%, while the average exchangeable sodium percentage (ESP) increased by 9.98%. This study demonstrated that multi-stage drip irrigation scheduling significantly influenced the soil physicochemical properties, soil salt ions, and vegetation growth, and thereby explained the efficient desalinization mechanism associated with this irrigation strategy. It is recommended to increase the amount of irrigation water and apply acidic regulators during the rainfed stage to reduce soil pH for vegetation establishment in coastal saline areas. Full article