Search Results (2,034)

This paper proposes a control method that combines a fractional-order sliding mode observer and a cooperative control strategy to address the problem of path-following for underactuated autonomous underwater vehicles (AUVs) in complex marine environments. First, a fractional-order sliding mode observer is designed, combining fractional calculus and double-power convergence laws to enhance the estimation accuracy of high-frequency disturbances. An adaptive gain mechanism is introduced to avoid dependence on the upper bound of disturbances. Second, a formation cooperative control strategy based on path parameter coordination is proposed. By setting independent reference points for each AUV and exchanging path parameters, formation consistency is achieved with low communication overhead. For the followers’ speed control problem, an error-based expected speed adjustment mechanism is introduced, and a hyperbolic tangent function is used to replace the traditional arctangent function to improve the response speed of the system. Numerical simulation results show that this control method performs well in terms of path-following accuracy, formation maintenance capability, and disturbance suppression, verifying its effectiveness and robustness in complex marine environments. Full article

In the context of efforts to reduce greenhouse gas emissions in the building sector, the reintegration of traditional earthen construction into modern architectural and renovation practices offers a sustainable alternative. To address the mechanical and water-resistance limitations of adobe bricks, the use of agricultural waste—such as rice husk—is increasingly being explored. This experimental study evaluates the effects of rice husk addition on the mechanical, hygrothermal, and acoustic properties of adobe bricks. Two soil types—one siliceous and one calcareous—were combined with 1, 2, and 3 wt% rice husk to produce bio-based earthen bricks. The influence of rice husk was found to depend strongly on the soils’ mineralogical and granulometric characteristics. The most significant improvements were in hygrothermal performance: at 3 wt%, thermal conductivity was reduced by up to 35% for calcareous soil and 20% for siliceous soil, indicating enhanced insulation. Specific heat capacity also increased with husk content, suggesting better thermal inertia. The moisture buffering capacity, already high in raw soils, is further improved due to increased surface porosity. Mechanically, rice husk incorporation had mixed effects: a modest increase in compressive strength was observed in siliceous soil at 1 wt%, while calcareous soil showed slight improvement at 3 wt%. Acoustic performance remained low across all samples, with minimal gains attributed to limited macro-porosity. These findings highlight the importance of soil composition in optimizing rice husk dosage and suggest promising potential for rice husk-stabilized adobe bricks, especially in thermally demanding environments. Full article

The consumption and farming of insects are gaining global attention as sustainable alternatives to conventional protein sources. Industrial processing of insects into powders or pastes complicates species identification, raising concerns about product authenticity, food safety, and potential fraud. In Western countries, particularly in Europe, the sector is expanding under a stringent regulatory framework, especially regarding rearing substrates, which hinders economic development. This study aimed to assess the species authenticity of commercial insect-based food and feed products and detect the presence of animal-derived DNA from unauthorized substrates. A total of 119 samples (pure insect meals and processed products) were collected from various origins. Species-specific real-time PCR assays targeted Tenebrio molitor, Hermetia illucens, Alphitobius diaperinus, Acheta domesticus, Bombyx mori, and Gryllodes sigillatus, alongside assays for ruminant, porcine, and poultry DNA. High-throughput sequencing (HTS) using metabarcoding confirmed and broadened species detection. Most samples contained the declared species; however, cases of mislabeling, substitution, and cross-contamination were observed. A few insect meals contained animal DNA which could suggest potential use of prohibited substrates. These findings highlight the urgent need for standardized authentication methods and improved transparency to ensure regulatory compliance, consumer trust, and sustainable development of the insect-based sector. Full article

Soccer, as a high-intensity sport, places significant physical demands on athletes and is associated with a high risk of injury. Electrical muscle stimulation (EMS), a training and rehabilitation technology, has gained attention for its potential benefits in sports settings. This systematic review, conducted under the PRISMA guidelines, rigorously assessed the effectiveness of EMS in improving muscle strength, promoting post-exercise recovery, and facilitating injury rehabilitation among soccer players. A comprehensive search of the PubMed, Scopus, and Web of Science databases identified 10 studies meeting the inclusion criteria. Among these, six studies demonstrated a significant improvement in athletic performance following local or whole-body EMS application. Four studies provided evidence supporting EMS’s efficacy in enhancing post-exercise recovery and reducing recovery time after injuries, with observed reductions in recovery time. However, the majority of the included studies were not double-blind, which limits the strength of the evidence. None of the included studies reported EMS-related adverse effects. Overall, the current results suggest that EMS may be a useful adjunct to improve athletic performance and facilitate recovery in soccer players. This review offers actionable insights for coaches and athletes regarding the safe and effective application of EMS in soccer training and rehabilitation programs. Full article

Background and objectives: Duloxetine is widely used for the treatment of major depressive disorder (MDD), generalized anxiety disorder (GAD), and various types of neuropathic pain. While its efficacy is well documented in clinical trials, less is known about how it is perceived and utilized in routine psychiatric practice. To address this knowledge gap, we conducted a cross-sectional observational study involving 80 psychiatrists from Spain to assess real-world clinical attitudes toward duloxetine. Methods: Participants completed a 20-item multiple-choice questionnaire that examined familiarity, perceived efficacy in multiple conditions (MDD, GAD, neuropathic pain, somatization, and quality of life), and perspectives on tolerability, safety, adherence, and overall satisfaction. Results: Survey results indicated that a large majority of psychiatrists frequently prescribe duloxetine, particularly for patients with MDD and comorbid chronic pain. Notably, 94% rated it as either “more effective” or “much more effective” for diabetic peripheral neuropathic pain. Psychiatrists reported a high perceived efficacy of duloxetine: 94% rated it as “more effective” or “much more effective” for diabetic peripheral neuropathy, and 93% gave similarly positive ratings for general neuropathic pain. For somatization, 70% found it “effective” or “very effective”, and 83% observed improvements in quality of life for many of their patients. Psychiatrists generally reported favorable perceptions of duloxetine’s tolerability profile: 97.5% rated it as the antidepressant associated with the least weight gain, and 82.5% perceived fewer sexual side effects compared to other options. Sedation and gastrointestinal side effects were generally considered mild or less severe. In terms of treatment adherence, 69% rated it as “better” or “much better” than other antidepressants, and 80% found its combination with other antidepressants to be “favorable” or “very favorable”. Overall satisfaction was high, with 99% of psychiatrists reporting being either “satisfied” or “very satisfied” with its use. The side effect profile was generally viewed as manageable, with low perceived rates of weight gain, sedation, and sexual dysfunction. Furthermore, 96% of respondents expressed a willingness to recommend duloxetine to their colleagues. Conclusions: Psychiatrists reported highly favorable attitudes toward duloxetine, viewing it as a flexible treatment option in routine care. However, these findings reflect clinicians’ subjective perceptions rather than objective clinical outcomes and should be interpreted accordingly. Full article

Maximizing the power output of wind farms is critical for improving the economic viability and grid integration of renewable energy. Active wake control (AWC) strategies, such as yaw-based wake steering, offer significant potential for power generation increase but require predictive models that are both accurate and computationally efficient for real-time implementation. This paper proposes a data-driven observer to rapidly estimate the potential power gain achievable through AWC as a function of the ambient wind direction. The approach is rooted in Koopman operator theory, which allows a linear representation of nonlinear dynamics. Specifically, a model is developed using an Input–Output Extended Dynamic Mode Decomposition framework combined with Sparse Identification (IOEDMDSINDy). This method lifts the low-dimensional wind direction input into a high-dimensional space of observable functions and then employs iterative sparse regression to identify a minimal, interpretable linear model in this lifted space. By training on offline simulation data, the resulting observer serves as an ultra-fast surrogate model, capable of providing instantaneous predictions to inform online control decisions. The methodology is demonstrated and its performance is validated using two case studies: a 9-turbine and a 20-turbine wind farm. The results show that the observer accurately captures the complex, nonlinear relationship between wind direction and power gain, significantly outperforming simpler models. This work provides a key enabling technology for advanced, real-time wind farm control systems. Full article

Quinoa (Chenopodium quinoa Willd) is a tetraploid crop that has provided vital subsistence, nutrition, and medicine for Andean indigenous cultures. In recent years, quinoa has gained global importance all over the world. However, variations in fertility have been frequently observed during the flower development of quinoa, severely affecting quinoa production. To comprehend the fundamental causes of fertility variation in quinoa, this research examined hormonal metabolism and gene expression across three ecotypes: normal fertility (F), absent stamens (S1), and abnormal stamens (S3). S1 and S3 presented absent and abnormal stamens, respectively, compared with F. Phytohormone profiling yielded 60 metabolites and revealed the clear separation between different ecotypes at different developmental stages according to principal component analysis (PCA). The results of transcriptomics showed more DEGs (differentially expressed genes) identified between F and S1 ecotypes (8002 and 10,716 for earlier and later stages, respectively) than F vs. S3 (4500 and 9882 for earlier and later stages, respectively) and S1 vs. S3 (4203 and 5052 for earlier and later stages, respectively). Zeatin biosynthesis and hormone signal transduction pathways were enriched among 19 KEGG (Kyoto Encyclopedia of Genes and Genomes) terms, indicating their potential roles in quinoa flower fertility regulation. The correlation-based network presented the associations between selected hormones and genes, possibly regulating fertile ecotypes. Furthermore, we explored the expression of flower development-related genes in three ecotypes using RT-PCR, showing the higher expressions of AP1, AP3, and FLS in sterile ecotypes than fertile ecotypes at both stages. These findings reveal new insights into the hormonal and genetic regulations of floral fertility in quinoa, which may have consequences for developing high-yielding cultivars. Full article

High-resolution ISAR (Inverse Synthetic Aperture Radar) imaging plays a crucial role in dynamic target monitoring for aerospace, maritime, and ground surveillance. Among various remote sensing techniques, ISAR is distinguished by its ability to produce high-resolution images of non-cooperative maneuvering targets. To meet the increasing demands for resolution and robustness, modern ISAR systems are evolving toward wideband and multi-channel architectures. In particular, multi-channel configurations based on large-scale receiving arrays have gained significant attention. In such systems, each receiving element functions as an independent spatial channel, acquiring observations from distinct perspectives. These multi-angle measurements enrich the available echo information and enhance the robustness of target imaging. However, this setup also brings significant challenges, including inter-channel coupling, high-dimensional joint signal modeling, and non-Gaussian, mixed-mode interference, which often degrade image quality and hinder reconstruction performance. To address these issues, this paper proposes a Hybrid Variational Bayesian Multi-Interference (HVB-MI) imaging algorithm based on a hierarchical Bayesian framework. The method jointly models temporal correlations and inter-channel structure, introducing a coupled processing strategy to reduce dimensionality and computational complexity. To handle complex noise environments, a Gaussian mixture model (GMM) is used to represent nonstationary mixed noise. A variational Bayesian inference (VBI) approach is developed for efficient parameter estimation and robust image recovery. Experimental results on both simulated and real-measured data demonstrate that the proposed method achieves significantly improved image resolution and noise robustness compared with existing approaches, particularly under conditions of sparse sampling or strong interference. Quantitative evaluation further shows that under the continuous sparse mode with a 75% sampling rate, the proposed method achieves a significantly higher Laplacian Variance (LV), outperforming PCSBL and CPESBL by 61.7% and 28.9%, respectively and thereby demonstrating its superior ability to preserve fine image details. Full article

This work presents the design of a control algorithm based on an augmented incremental state-space model, emphasizing its compatibility with Takagi–Sugeno (T–S) fuzzy models for nonlinear systems. The methodology integrates key components such as incremental modeling, fuzzy system identification, discrete Linear Quadratic Regulator (LQR) design, and state observer implementation. To optimize controller performance, the Extremum Seeking Control (ESC) technique is employed for the automatic tuning of LQR gains, minimizing a predefined cost function. The control strategy is formulated within a generalized framework that evolves from conventional discrete fuzzy models to a higher-order incremental-N state-space representation. The simulation results on a nonlinear multivariable thermal mixing tank system validate the effectiveness of the proposed approach under reference tracking and various disturbance scenarios, including ramp, parabolic, and higher-order polynomial signals. The main contribution of this work is that the proposed scheme achieves zero steady-state error for reference inputs and disturbances up to order N−1 by employing the incremental-N formulation. Furthermore, the system exhibits robustness against input and load disturbances, as well as measurement noise. Remarkably, the ESC algorithm maintains its effectiveness even when noise is present in the system output. Additionally, the proposed incremental-N model is applicable to fast dynamic systems, provided that the system dynamics are accurately identified and the model is discretized using a suitable sampling rate. This makes the approach particularly relevant for control applications in electrical systems, where handling high-order reference signals and disturbances is critical. The incremental formulation, thus, offers a practical and effective framework for achieving high-performance control in both slow and fast nonlinear multivariable processes. Full article

In recent times, fiber reinforced polymer composite materials have become more popular due to their remarkable features such as high specific strength, high stiffness and durability. Particularly, Carbon Fiber Reinforced Polymer (CFRP) composites are one of the most prominent materials used in the field of transportation and building engineering, replacing conventional materials due to their attractive properties as mentioned. In this work, a CFRP laminate is fabricated with carbon fiber mats and epoxy by a hand layup technique. Alumina (Al₂O₃) micro particles are used as a filler material, mixed with epoxy at different weight fractions of 0% to 4% during the fabrication of CFRP laminates. The important objective of the study is to investigate the influence of alumina micro particles on the mechanical performance of the laminates through characterization for various physical and mechanical properties. It is revealed from the results of study that the mass density of the laminates steadily increased with the quantity of alumina micro particles added and subsequently, the porosity of the laminates is reduced significantly. The SEM micrograph confirmed the constituents of the laminate and uniform distribution of Al₂O₃ micro particles with no significant agglomeration. The hardness of the CFRP laminates increased significantly for about 60% with an increase in weight % of Al₂O₃ from 0% to 4%, whereas the water gain % gradually drops from 0 to 2%, after which a substantial rise is observed for 3 to 4%. The improved interlocking due to the addition of filler material reduced the voids in the interfaces and thereby resist the absorption of water and in turn reduced the plasticity of the resin too. Tensile, flexural and inter-laminar shear strengths of the CFRP laminate were improved appreciably with the addition of alumina particles through extended grain boundary and enhanced interfacial bonding between the fibers, epoxy and alumina particles, except at 1 and 3 wt.% of Al₂O₃, which may be due to the pooling of alumina particles within the matrix. Inclusion of hard alumina particles resulted in a significant drop in impact strength due to appreciable reduction in softness of the core region of the laminates. Full article

This study evaluates the effects of dietary lipid levels on growth performance, hematological health, and muscle composition of juvenile Arapaima gigas. We tested five isonitrogenous diets (451.7 g kg⁻¹ of crude protein) with increasing lipid levels (6%, 10%, 14%, 18%, and 22%). A total of 600 juvenile A. gigas (80.0 ± 10.5 g; 21.8 ± 1.0 cm) were distributed into 20 tanks (500 L; n = 4; 30 fish per tank) in an indoor open system. The fish were fed to apparent satiety four times daily for 60 days. As dietary lipid levels increased, all growth parameters and lipid content in both the whole body and muscle declined. The diet containing 6% lipids resulted in the maximum final weight, weight gain, feed intake, and the lowest feed conversion rate. However, a maximum lipid level of up to 10.26%, with a gross energy-to-protein ratio of 10.15 kcal g⁻¹ in the diet, as determined through polynomial regression analysis, can be used for juvenile A. gigas without significantly affecting weight gain. Diets with high lipid content (18% and 22% lipids) resulted in the lowest survival rates, highest feed conversion rates, lowest condition factor, visible skeletal protrusions, scale depigmentation, and impaired blood biochemistry. The content of eicosapentaenoic acid, docosahexaenoic acid, n-3, and the n-3:n-6 ratio increased in the muscle lipid fraction (mg g⁻¹ of total lipids) in response to higher dietary lipid levels; however, this does not represent an overall improvement in the meat quality, since the total lipid content in the muscle (g of lipid per 100 g of muscle) was reduced due to impaired growth in fish fed high-lipid diets. Notably, the experimental diets also differed in fatty acid composition, which may have influenced some of the physiological and compositional responses observed. Diets with 6% lipids are recommended to provide optimal growth performance, and a maximum dietary lipid level of up to 10.26% is advised to ensure successful A. gigas farming without impairing weight gain. Full article

This paper presents a compact, high-performance metasurface-based leaky-wave MIMO antenna with dimensions of 40 × 30 mm², achieving a gain of 12.5 dBi and a radiation efficiency of 85%. The antenna enables precise control of electromagnetic waves, featuring a flower-like metasurface (MTS) with coffee bean-shaped arrays on substrates of varying permittivity, separated by a cavity layer to enhance coupling. Its dual-port MIMO design boosts data throughput operating in three bands (3.75–5.25 GHz, 6.4–15.4 GHz, and 22.5–30 GHz), while the leaky-wave mechanism supports frequency- or phase-dependent beamsteering without mechanical parts. Ideal for CubeSat communications, its compact size meets CubeSat constraints, and its high gain and efficiency ensure reliable long-distance communication with low power consumption, which is crucial for low Earth orbit operations. Circular polarization (CP) maintains signal integrity despite orientation changes, and MIMO capability supports high data rates for applications such as Earth observations or inter-satellite links. The beamsteering feature allows for dynamic tracking of ground stations or satellites, enhancing mission flexibility and reducing interference. This lightweight, efficient antenna addresses modern CubeSat challenges, providing a robust solution for advanced space communication systems with significant potential to enhance satellite connectivity and data transmission in complex space environments. Full article

Beamforming plays a key role in improving the spectrum utilization efficiency of multi-antenna systems. However, we observe that (i) conventional beam prediction solutions suffer from high model training overhead and computational latency and thus cannot adapt quickly to changing wireless environments, and (ii) deep-learning-based beamforming may face the risk of catastrophic oblivion in dynamically changing environments, which can significantly degrade system performance. Inspired by the above challenges, we propose a continuous-learning-inspired beam prediction model for fast beamforming adaptation in dynamic downlink millimeter-wave (mmWave) communications. More specifically, we develop a meta-empirical replay (MER)-based beam prediction model. It combines empirical replay and optimization-based meta-learning. This approach optimizes the trade-offs between transmission and interference in dynamic environments, enabling effective fast beamforming adaptation. Finally, the high-performance gains brought by the proposed model in dynamic communication environments are verified through simulations. The simulation results show that our proposed model not only maintains a high-performance memory for old tasks but also adapts quickly to new tasks. Full article

In this study, we delve into the intricate microstructural features of Ti-6Al-4V alloy additively manufactured and heat-treated at 800 °C for 4 h. Our in-depth analysis will enable us to gain a better understanding of the β-Ti precipitation process, its dependence on temperature, and its ultimate effect on the overall mechanical properties. As well as α-Ti martensite grains and β-Ti particles interspersed in the α-Ti grain boundaries, there is a third microstructural feature, overlooked by many researchers. This feature is observed as nano-sized particles homogeneously embedded inside the α-Ti laths. Using high-resolution transmission electron microscopy, we reveal that these nano-sized features do not constitute a different phase. Instead, they define isolated regions of α-Ti in its relaxed form, surrounded by the heavily strained form of the α-Ti phase. This phenomenon is a result of the “incomplete” precipitation of the β-Ti phase following the heat treatment stage. The straining of the α-Ti phase appears as a shift in the equilibrium atomic position. Full article

Sedentary behavior among young women is increasingly associated with adverse metabolic and cardiovascular outcomes. The aim of this randomized controlled trial was to evaluate and compare the effects of three structured group fitness programs on anthropometric parameters, body composition, and lipid profile in overweight young women (N = 111, age 18–25, BMI ≥ 25). Participants were assigned to mix aerobics (E1, n = 27), kickbox aerobics (E2, n = 28), step aerobics (E3, n = 27), or a control group (C, n = 29). Each intervention lasted 12 weeks, with sessions conducted three times per week, each lasting 60 min. The results were analyzed using repeated measures ANOVA. Significant reductions were observed in body weight (−4.8 kg in E1, p < 0.01), waist circumference (−5.3 cm in E1, p < 0.001), and body fat percentage (−3.6% in E1, p < 0.01). High-density lipoprotein (HDL) increased by 7.4 mg/dL (p < 0.01), while low-density lipoprotein (LDL), total cholesterol, and triglycerides decreased by 12.1 mg/dL, 18.6 mg/dL, and 19.4 mg/dL, respectively (all p < 0.01). The most pronounced overall improvements were found in the mix aerobics group. In contrast, the control group showed significant deterioration in most variables, including a 2.1 kg weight gain and a 6.3 mg/dL increase in total cholesterol (p < 0.05). These findings confirm the superior effectiveness of mix aerobics as a non-pharmacological intervention to improve body composition (notably through reductions in body weight, fat percentage, and waist circumference) and cardiovascular biomarkers (such as increased HDL and decreased LDL, total cholesterol, and triglycerides) in young overweight women. Compared to kickboxing and step aerobics, mix aerobics consistently achieved the greatest improvements across all measured parameters, making it the most comprehensive and effective option among the three programs tested. Full article