Search Results (41,244)

Giant magnetostrictive Tb-Dy-Fe alloys are extensively applied in transducers, actuators, and smart sensors owing to their exceptional magnetostrictive response. Nevertheless, in addition to the fracture failure caused by the inherent brittleness of the Laves intermetallic compound, Tb-Dy-Fe alloys also suffer from severe eddy current losses due to low electrical resistivity, both of which limit the practical application of Tb-Dy-Fe alloys. To further enhance the overall performance of Tb-Dy-Fe alloys and expand their application scope, it has become essential to develop materials that exhibit high magnetostrictive properties, high electrical resistivity and excellent mechanical properties simultaneously. In this work, the effects of Al and Si co-addition on the microstructure and multifunctional properties of directionally solidified Tb_0.27Dy_0.73(Fe_0.9Al_0.075Si_0.025)_1.95 (hereafter TDF-AlSi) alloy were systematically investigated. Microstructural characterization revealed that Al partially substitutes Fe atoms in the matrix phase while promoting Al(Tb,Dy)Fe₂ nanocluster, whereas Si preferentially segregated to grain boundary regions forming Tb₂Si₃ and TbSi_1.75 phases. The bending strength of TDF-AlSi alloy was improved from 43 MPa to 65 MPa, an increase of 51.2%, which was attributed to solid solution strengthening by Al and grain boundary reinforcement by Si-rich precipitates. Meanwhile TDF-AlSi alloy exhibits a 2.4 times increase in electrical resistivity (1.619 μΩ·m), resulting in a 49% reduction of total loss at 1000 Hz. The enhancement of electrical resistivity mainly originated from the lattice distortion induced electron scattering by Al substitution and electron impedance at grain boundaries via silicide precipitation. Accompanied by enhancement of mechanical property and electrical resistivity, TDF-AlSi alloy maintained a high magnetostriction strain of 1212 ppm (200 kA/m, 10 MPa pre-compressive stress). The findings of the present study offer valuable theoretical and experimental insights with regard to the optimization of the performance of magnetostrictive Tb-Dy-Fe alloys. Full article

Secondary research is a cornerstone of health sciences, with substantial implications for clinical practice and health policy. Within the systematic review process, a key step is assessing study quality and risk of bias. Among the tools available for evaluating observational studies, the Newcastle–Ottawa Scale (NOS) holds a prominent position and is widely applied in medical research. However, ambiguities and excessive subjectivity have been noted in its application. In this commentary, we discuss the Newcastle–Ottawa Scale guidelines, providing illustrative examples and practical recommendations for completing its items. Improving the accuracy of risk-of-bias assessment is crucial for enhancing the reliability of data synthesis and interpretation in the health sciences. Full article

Robotics is increasingly used in higher education laboratories, but most commercial robots are costly and designed for industrial use. This paper presents the design, modeling, and experimental evaluation of a low-cost four-degree-of-freedom (DOF) SCARA robot for educational and research purposes. The robot supports pick-and-place and laser engraving tasks. Direct and inverse kinematics were developed using Denavit–Hartenberg parameters, and the mechanical structure was validated through the dynamic analyses. A new machine learning (ML) framework integrating Support Vector Machine (SVM) and Random Forest (RF) models was implemented to enhance motion precision, predict task success, and compensate positioning errors in real time. Experimental tests over 360 cyles under varying speeds, payloads, and object types show that the SVM predicts grasp success with 94.4% accuracy, while the RF model estimates XY positioning error with an RMSE of 1.84 mm and cycle time error with an RMSE of 0.41 s. Moreover, a novel approach in this work that combines it with a laser engraving machine has been suggested. Repeatability experiments report 0.97 mm ISO-standard repeatability, and laser engraving trials yield mean positional errors of 0.45 mm, with maximum deviation of 0.90 mm. Compared to a baseline PID controller, the ML-enhanced strategy reduces RMS positioning error from 3.30 mm to 1.83 mm and improves repeatability by 36.5%, while slightly decreasing cycle time. These results demonstrate that the proposed SCARA robot achieves high-precision, consistent, and flexible operation suitable for both academic and light-duty practical applications. Full article

Recursion is often presented as a nice and illustrative technique, only to later conclude that it should (almost) never be used due to potential problems with call stack overflow. However, recursion can often be the technique of choice during algorithm development and testing, and even in final solutions. Therefore, a simple but effective technique is needed to overcome call stack limitations. We designed and implemented the Extendable Stack Library (ESL), which provides a simple and effective interface that enables deep recursion in C++. Its flexible usage model allows deep recursion to be used where needed, without requiring major project modifications or customization of development tools. The performance overhead is moderate and localized only to deep recursive functions using ESL. The library is designed to be flexible and cross-platform. It supports Linux on AMD64 and AArch64 processors and Windows on AMD64. It can be adapted to more platforms with relative ease. ESL has been tested through a series of unit tests, experiments, and practical applications. It has proven to be an effective solution for deep recursion. ESL has been successfully used in the implementation of the Wafl programming language interpreter. Full article

This study investigates the tri-objective optimization of underground metro station structures, considering structural reliability, life-cycle economic cost, and annualized carbon emissions simultaneously. Using a representative metro station in Guangzhou as a case study, a multi-objective optimization framework is developed. The model defines structural failure probability, discounted life-cycle cost, and average annual carbon emissions as the primary objectives, with decision variables including concrete strength, cover thickness, the use of epoxy-coated reinforcement, and various maintenance/repair strategies. Material quantities are calculated through Building Information Modeling (BIM), while cost–carbon relationships are derived from industry price data and carbon emission factors. An improved multi-objective particle swarm optimization algorithm (OMOPSO) is used to derive the Pareto-optimal front. Case study results show that increasing cover thickness significantly improves durability and reduces carbon emissions with only moderate cost increases. In contrast, epoxy-coated reinforcement is excluded from the Pareto set due to its high cost under the given conditions. To facilitate practical decision-making, a weight-based solution selection method is introduced, and sensitivity analyses are performed to assess the model’s robustness. The study concludes by emphasizing the framework’s applicability and limitations: the findings are specific to the case context and require recalibration for use in other sites or construction practices. This research contributes by integrating durability, cost, and carbon considerations into an engineering-level optimization workflow, providing valuable decision support for sustainable metro station design. Full article

This study applies the Log-Periodic Power-Law (LPPL) framework to three major equity markets—Mexico (IPC), Brazil (IBOVESPA), and the United States (NYSE Composite)—using daily closes from 8 November 1991–30 January 2025 for IPC and NYSE, and 3 May 1993–30 January 2025 for IBOVESPA. Multi-window calibrations (L$ϵ$ 180, 240, 300, 360, 420) are estimated in raw and log space to evaluate bubble signatures and the stability of the critical time $t_c$. Across all indices, log-space fits consistently outperform raw fits in terms of RMSE and $R^2$, and longer windows reduce parameter variability, yielding coherent clusters of $t_c$. Under full-sample conditions, the LPPL structure points to March–April 2025 for NYSE, mid-October 2025 for IBOVESPA, and October–December 2025 for IPC, while shorter windows pull $t_c$ forward. A rolling early-warning ensemble translates these estimates into lead-based risk bands, with numerical reporting used when median leads fall just outside the 60-trading-day decision horizon. The early-2025 weakening in the U.S. market is consistent with the NYSE cluster, whereas Brazil and Mexico remain within their projected windows as of September 2025. The analysis highlights the strengths of LPPL—behavioral interpretability and hazard-based framing—while noting limitations such as window sensitivity and parameter sloppiness, reinforcing the need for conservative communication and the use of longer-window weighting in practical applications. Full article

The urgent need for sustainable innovation in the construction industry necessitates a reevaluation of how architecture engages with materials and fabrication processes. This paper introduces tailored fiber placement (TFP) as a novel fabrication method with significant potential for advancing sustainable architectural practice. Originally developed for aerospace and automotive applications, TFP enables stress-oriented fiber alignment, offering precision, material efficiency, and lifecycle-conscious design opportunities. To articulate these capabilities, the paper examines four case studies at multiple scales. Ranging from small-scale seating to medium-scale façade components, these examples demonstrate TFP’s ability to enable mold-less forming and integrative fabrication in support of sustainable construction. Through digitally programmed fiber orientations, the cases achieve both structural and geometric requirements while minimizing waste and improving workflow efficiency. This research positions TFP as a material-aware and performance-driven approach to sustainable architectural production. By bridging material, design, and fabrication, TFP contributes to more circular, adaptable, and efficient construction systems. Full article

Alfalfa cultivation is an effective way to achieve soil improvement while utilizing saline soils. Irrigation and drainage, as physical measures to leach salts, can effectively reduce the soil salt content, while application of organic fertilizer fermented with an effective microorganism (EM) may further enhance the improvement effect of saline–alkaline soil by improving soil fertility and microbial community structure. However, there is still a lack of systematic assessment on the effects of applying these three measures on the saline soil–plant system. In this study, we used alfalfa as the plant material and set three water depths of 8 mm (IR1), 16 mm (IR2), and 24 mm (IR3) under the condition of irrigating every 10 days with remote-controlled timed and quantitative irrigation, which is the most acceptable to farmers in the era of smart agriculture. EM organic fertilizer dosage was designed as 0 kg/ha (CK), 1500 kg/ha (OF1), 3000 kg/ha (OF2), 4500 kg/ha (OF3), and 6000 kg/ha (OF4). The multiple-crop alfalfa yield, quality (crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)), and soil electrical conductivity (EC) were observed. The results showed that after the application of EM organic fertilizer, the soil’s EC value of fertilized treatments was higher than that of CK, but this difference became smaller with the prolongation of alfalfa’s growing period, implying that EM organic fertilizer could absorb more soil salts by promoting alfalfa’s growth; the water depth was obviously negatively correlated with the soil’s EC value, demonstrating that the increase in the water depth had a stronger ability to reduce the soil salts. By the end of the experiment, the soil’s EC values were reduced by 21.4–43.7% for the treatments. The alfalfa yield was significantly increased by EM organic fertilizer application, and the three alfalfa yields were increased by 63.3–69.1%, 65.4–83.6%, and 52.6–56.2%, respectively, when fertilizer application was elevated from CK to OF4. The highest alfalfa yields were all found at IR2OF4, reaching 1164.7, 2637.3 and 2519.7 t/ha, corresponding to the first, second, and third alfalfa crops, respectively. The analysis of alfalfa quality indexes revealed that higher CP values were found in the IR2 treatments, and increasing fertilizer application from OF1–OF4 resulted in an increase in CP values by 2.4–9.1%, 1.5–7.4%, and 0.8–6.7% for the three alfalfa crops. Relatively low NDF and ADF values were observed for alfalfa under IR2 conditions; however, the application of EM organic fertilizer reduced the NDF and ADF values within a certain range. According to the results of the entropy weight evaluation model, IR3OF4, IR3OF2, and IR3OF3 were the top three treatments with the best overall benefits, respectively, with relative closeness values of 0.71, 0.70, and 0.68, in that order, which suggests that the appropriate water depth is 24 mm, while the appropriate EM organic fertilizer dosage is in the range of 3000–6000 kg/ha. There was a pattern observed in our study, in which the treatments with better overall benefits were better distributed at high water depths, which emphasizes the critical role of the irrigation volume in ameliorating saline soils. The conclusions of the study are intended to provide a practical basis for the comprehensive utilization and sustainable development of saline soils. Full article

Sjögren’s syndrome (SS) is a chronic systemic autoimmune disease characterized by the main clinical manifestation of oral and ocular dryness, predominantly affecting middle-aged and elderly women. As the most commonly affected target organs in SS, pathological changes in the salivary glands (SGs) and their underlying mechanisms are of great significance for understanding the disease progression. Recent studies have revealed that a dynamic imbalance of the extracellular matrix (ECM) in the SGs plays a crucial role in the pathogenesis of SS. Dysregulation of matrix metalloproteinases (MMPs) and the fibrotic processes they mediate constitute the core pathological changes. These alterations intertwine with local chronic inflammatory responses, cellular senescence, and hyperosmolarity, collectively leading to the destruction of the SG parenchymal structure and progressive loss of secretory function, significantly impairing the patients’ quality of life. However, research on the pathological mechanisms of the SG ECM remains insufficient, and there are currently no specific therapeutic interventions targeting ECM alterations in clinical practice. This review systematically elucidates the characteristics of pathological and physiological changes in the SG ECM in SS and thoroughly explores novel therapeutic strategies based on ECM regulation, as well as their clinical application prospects. Full article

This study presents the development of a smart packaging material utilizing garlic-derived nitrogen-doped carbon dots (CDs) integrated into a whey protein–starch (WP-S) emulsion. The research aimed to create a real-time, non-invasive biosensor capable of detecting microbial spoilage. The synthesized CDs demonstrated strong pH-sensitive photoluminescence, exhibiting distinct changes in CIE coordinates and fluorescence intensity in response to varying pH values. The WP-S-CDs emulsion was tested against E. coli, S. aureus, and C. albicans. The results showed that the composite film provided a clear colorimetric shift and fluorescence quenching, both of which are directly correlated with microbial metabolic activity. The physical and electronic properties of the composite were investigated to understand the sensing mechanism. Scanning electron microscopy (SEM) of the dried film revealed that the WP-S-CDs system formed a more porous structure with larger pore sizes (3.63–8.18 µm) compared to the control WP-S film (1.62–6.52 µm), which facilitated the rapid diffusion of microbial metabolites. Additionally, density functional theory (DFT) calculations demonstrated that the incorporation of CDs significantly enhanced the composite’s electronic properties by reducing its band gap and increasing its dipole moment, thereby heightening its reactivity and sensitivity to spoilage byproducts. In a practical application on apples, the WP-S-CDs coating produced a visible red spot, confirming its function as a dynamic sensor. The material also showed a dual-action antimicrobial effect, synergistically inhibiting C. albicans while exhibiting an antagonistic effect against bacteria. These findings validate the potential of the WP-S-CDs emulsion as a powerful, multi-faceted intelligent packaging system for food quality monitoring. Full article

Photocatalytic water sterilization has emerged as a promising sustainable technology for addressing microbial contamination across diverse sectors including healthcare, food production, and environmental management. This review examines the fundamental mechanisms and recent advances in photocatalytic water sterilization, with a particular emphasis on the differential bactericidal pathways against Gram-negative and Gram-positive bacteria. Gram-negative bacteria undergo a two-step inactivation process involving initial outer membrane lipopolysaccharide (LPS) degradation followed by inner membrane disruption, whereas Gram-positive bacteria exhibit simpler kinetics due to direct oxidative attacks on their thick peptidoglycan layer. Escherichia coli has long been used as the gold standard in photocatalytic sterilization studies owing to its aerobic nature and suitability for the colony-counting method. In contrast, Lactobacillus casei, a facultative anaerobe, can be cultured statically and evaluated rapidly using turbidity-based optical density measurements. Therefore, both organisms serve complementary roles depending on the experimental objectives—E. coli for precise quantification and L. casei for rapid, practical assessments of Gram-positive bacterial inactivation under laboratory conditions. We also describe sterilization using light alone while comparing it to photocatalytic sterilization and then discuss two innovative suspension-based photocatalyst systems: polystyrene bead-supported TiO₂/SiO₂ composites offering balanced reactivity and separability and magnetic TiO₂-SiO₂/Fe₃O₄ nanoparticles enabling rapid magnetic recovery. Future research directions should prioritize enhancing visible-light efficiency using metal-doped TiO₂ such as Cu-doped systems; improving catalyst durability; developing new applications of photocatalysts, such as protecting RO membranes; and validating scalability across diverse industrial and medical water treatment applications. Full article

Droplet microfluidics enables high-throughput, compartmentalized reactions using minimal reagent volumes, but most implementations rely on precision-fabricated chips and external pumping systems that limit portability and accessibility. Here, we present a handheld vibrational droplet generator that repurposes a consumer electric toothbrush and a modified disposable pipette tip to produce nearly monodisperse water-in-oil droplets without microfluidic channels or syringe pumps. The device is powered by the toothbrush’s built-in motor and controlled by a simple 3D-printed adapter and adjustable counterweight that tune the vibration amplitude transmitted to the pipette tip. By varying the aperture of the pipette tip, droplets with diameters from ~100–300 µm were generated at rates of ~100 droplets s⁻¹. Image analysis revealed narrow size distributions with coefficients of variation below 5% in typical operating conditions. We further demonstrate proof-of-concept applications in digital loop-mediated isothermal amplification (LAMP) and microbiological colony-forming unit (CFU) assays. A commercial feline parvovirus (FPV) kit manufactured by Beyotime Biotechnology Co., Ltd. (Shanghai, China), three template concentrations yielded emulsified reaction droplets that remained stable at 65 °C for 45 min and produced distinct fractions of fluorescent-positive droplets, allowing estimation of template concentration via a Poisson model. In a second set of experiments, the device was used as a droplet-based spreader to dispense diluted Escherichia coli suspensions onto LB agar plates, achieving uniform colony distributions across the plate at different dilution factors. The proposed handheld vibrational generator is inexpensive, easy to assemble from off-the-shelf components, and minimizes dead volume and cross-contamination because only the pipette tip contacts the sample. Although the current prototype still exhibits device-to-device variability and moving droplets in open containers complicate real-time imaging, these results indicate that toothbrush-based vibrational actuation can provide a practical and scalable route toward “lab-in-hand” droplet assays in resource-limited or educational settings. Full article

Amniotic membrane (AM) has gained wide application in regenerative medicine due to its biocompatibility and extracellular matrix (ECM) composition. Effective decellularization is essential to minimize immunogenicity while preserving tissue architecture. This study standardized AM procurement and compared a simplified alkaline-based decellularization protocol with a conventional detergent–alkaline method, emphasizing practicality, histological integrity, and collagen preservation. Methods: Human AM was aseptically obtained from placental tissue and processed using either method. Histological analysis with hematoxylin eosin and Masson’s trichrome staining quantified nuclear content and collagen integrity. Results: The alkaline method achieved the greatest nuclear clearance but retained epithelial outlines, indicating partial persistence of cellular structures. In contrast, the detergent method achieved complete morphological decellularization but showed slightly higher residual nuclear signal. Masson’s trichrome staining revealed that the detergent-based method preserved collagen intensity most closely to native tissue (mean gray values: 128.3 ± 28.2 vs. 140.2 ± 23.4), while the alkaline group exhibited significantly reduced staining (177.8 ± 17.2; p < 0.001). Conclusions: the simplified alkaline method provided efficient decellularization with reduced cost, time, and cytotoxic risk, making it a practical approach for AM processing. However, partial ECM alteration suggests that detergent-based methods remain preferable when optimal structural preservation is required. Full article

Near-infrared spectroscopy (NIRS) is widely used in food, pharmaceutical, and agricultural analyses but is highly susceptible to noise. To address this, we propose BiLSTM-FuseNet, a denoising framework that combines temporal modeling and explicit noise estimation. It uses stacked Bidirectional Long Short-Term Memory (BiLSTM) layers for global–local spectral learning and an MLP branch to predict and subtract noise. Evaluated on the Tablet and AnHui soil datasets with various synthetic noise types, the model outperformed the conventional methods, achieving an RMSE of 0.024 and R² of 0.68 under mixed noise. The downstream regression improved the tablet weight prediction R² from 0.079 to 0.218. These findings demonstrate the robustness of BiLSTM-FuseNet and its clear advantages for practical downstream NIR applications. Full article

Low clouds significantly impact weather, climate, and multiple environmental and economic sectors such as agriculture, fire risk management, aviation, and renewable energy. Accurate knowledge of cloud base height (CBH) is critical for optimizing crop yields, improving fire danger forecasts, enhancing flight safety, and increasing solar energy efficiency. This study evaluates a shadow-based CBH retrieval method using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite visible imagery and compares the results against collocated lidar measurements from the Micro-Pulse Lidar Network (MPLNET) ground stations. The shadow method leverages sun–sensor geometry to estimate CBH from the displacement of cloud shadows on the surface, offering a practical and high-resolution passive remote sensing technique, especially useful where active sensors are unavailable. The validation results show strong agreement, with a correlation coefficient (R) = 0.96 between shadow-based and lidar-derived CBH estimates, confirming the robustness of the approach for shallow, isolated cumulus clouds. The method’s advantages include direct physical height estimation without reliance on cloud top heights or stereo imaging, applicability across archived datasets, and suitability for diurnal studies. This work highlights the potential of shadow-based retrievals as a reliable, cost-effective tool for global low cloud monitoring, with important implications for atmospheric research and operational forecasting. Full article