Search Results (2,134)

The effects of red seaweed, psyllium husk, and chia seeds on the structural and functional properties of comminuted meat batters were evaluated. Meat batters were formulated with 1% of each ingredient or their combinations totaling 1% and evaluated for pH, cooking loss, microstructure, texture profile analysis, color, rheology, and protein interactions. Formulation did not affect (p ≥ 0.08) pH or cooking loss, indicating that water- and lipid-holding capacity and emulsion stability were preserved across treatments. Hardness increased (p ≤ 0.05) in treatments containing red seaweed, alone or combined with psyllium husk. Fiber addition did not influence (p ≥ 0.17) raw batter color; however, cooked products showed differences (p ≤ 0.05) in lightness (L*) and total color change (ΔE*). Rheological analysis indicated similar viscoelastic behavior among treatments with no significant differences among treatments (p ≥ 0.07) for storage modulus, loss modulus, or tangent delta at the start, peak, or end of the small-amplitude oscillatory shear test. Microstructural observations revealed treatment-dependent networks, and protein solubility analysis showed changes (p ≤ 0.05) in ionic and hydrogen bonding, while disulfide bonds were unaffected (p = 0.60). Incorporation of 1% of these ingredients maintained desirable physicochemical, textural, and functional properties, highlighting their potential as ingredients in meat batters. Full article

Distributed optical fiber acoustic sensing (DAS) has become an important technology for production logging because it can record dense strain or strain-rate responses along an optical fiber under high-temperature, high-pressure, and corrosive downhole conditions. This single-well field case study investigated a hybrid low-frequency DAS processing framework for distributed optical fiber production logging. First, a finite impulse response (FIR)-based preprocessing step was used for low-pass smoothing before an F–K domain analysis. The DAS records were then transformed into the frequency–wavenumber (F–K) domain, where particle swarm optimization (PSO) was used to tune the nu parameter of a one-class support vector machine (OCSVM) for automatic feature extraction. Rule-based feature enhancement and a small-sample support vector classifier (SVC) were then applied to suppress residual F–K domain noise and retain the V-shaped features associated with upgoing and downgoing waves. Finally, linear regression was applied to the enhanced F–K domain branches to estimate the apparent propagation velocities and derive the flow velocity through the field interpretation relationship. The workflow was demonstrated using 15 s field DAS segments from an oil–water two-phase production well, and the six-window validation showed errors below 3.13% relative to the field-reference values. These results demonstrate the feasibility of the proposed workflow for the investigated well, but do not constitute general validation across different wells or acquisition conditions. Full article

Cottonseed hulls (CSH) are by-products of cotton processing, but their use in livestock feed is constrained by lignocellulose and free gossypol. In this study, solid-state fermentation of cottonseed hulls was optimized using Aspergillus niger, Aspergillus oryzae, and Lactobacillus plantarum through an orthogonal experimental design. Fermentation quality, nutrient composition, safety indicators, microstructure, and metabolic profiles were subsequently evaluated under the optimized conditions. The results showed that composite microbial fermentation significantly reduced pH and decreased NH₃-N/TN by 42.35%, while increasing lactic acid content by 20.01 g/kg. Meanwhile, butyric acid was not detected. Compared with the non-inoculated control, neutral detergent fiber and acid detergent fiber were further degraded by 5.78% and 7.37%, respectively. In addition, free gossypol was reduced by 79.79% compared with untreated cottonseed hulls, and aflatoxin B1 content decreased by 60.11% compared with the non-inoculated control. Untargeted metabolomics revealed increased abundances of amino acids and bioactive small peptides, including L-arginine, Ile-Lys, Glu-Met, and L-isoleucyl-L-arginine. Taken together, these findings indicate that composite microbial fermentation may serve as an effective strategy for the detoxification and nutritional improvement of cottonseed hulls, providing a theoretical basis for the application of fermented cottonseed hulls as a feed resource. Full article

This study examines the effect of small ply angle deviations on the structural response of carbon fiber-reinforced polymer laminates representative of structures used in unmanned aerial vehicles (UAVs). A combined experimental and numerical approach was applied, including cantilever bending tests and experimental modal analysis, supported by finite element simulations. Laminates with nominal ply orientations of 0°, 5°, and 10° were manufactured using a manual hand lay-up process to reflect typical production variability. The results show that the numerical model accurately captures the observed trends in both bending deformation and natural frequencies, with discrepancies up to 12.5%. A consistent tendency to slightly overestimate stiffness was observed, leading to lower predicted deflections and higher natural frequencies compared to experimental data. The findings confirm that finite element modeling can reliably detect and predict the structural effects of small fiber misalignment, supporting its use in the assessment and design of lightweight composite structures used in UAV applications. Full article

In the field of shock physics and energetic materials, Fiber Bragg Gratings (FBGs) are used to measure shock velocity, detonation velocity and shock pressure levels. They are also used to measure strain in structures loaded with explosive effects. FBG sensors are known to be light, small, immune electromagnetic environments and have fast response compared to electrical sensors. To use one or more gratings along a fiber, a high-resolution spectrometer with a high sampling rate has been developed. This dynamic spectrometer employs time-multiplexing by wavelength-to-time conversion using dispersion. It provides a complete view of the spectra evolution at a rate of 100 MHz. Thus, complex phenomena can be observed. In this paper, the interrogation technique is presented in more detail, and experimental results are discussed. The experiments presented are a low-pressure shock velocity measurement in epoxy, a deflagration-to-detonation transition in a porous energetic material, a Shock-to-Detonation Transition in a dense energetic material, a tentative-to-measure pressure level in epoxy from an FBG made in a sapphire fiber and multi-point strain measurements up to eight FBGs. The advantages and limits are discussed for each type of experiment. Full article

Introduction: Otorrhagia is an uncommon finding in forensic practice and is classically associated with skull base fractures, temporal bone trauma, or barotraumatic events. However, the literature suggests that ear bleeding may also rarely occur in deaths due to neck compression, including strangulation and hanging. Case Presentation: We report the case of a man died by hanging. External examination revealed an oblique ligature mark on the neck, conjunctival petechiae, and bilateral otorrhagia. At autopsy, no fractures of the skull vault or skull base were identified. Otoscopic examination showed bilateral tympanic membrane laceration. Internal examination of the neck disclosed small hemorrhagic infiltrates in the perithyroid muscles and prevertebral soft tissues, as well as bilateral carotid intimal tears consistent with Amussat’s sign. Moreover, a unilateral lesion involving the petrous portion of the temporal bone was observed. The distinctive feature of this case is the association of bilateral otorrhagia, bilateral tympanic membrane laceration, and unilateral petrous bone erosion in the absence of skull base fracture. Histology showed visceral congestion, pulmonary overdistension with rupture of interalveolar septa, cerebral edema, myocardial fiber fragmentation and trabecular remodeling and areas of necrosis of the bone fragment sampled from the right petrous temporal bone. Death was attributed to mechanical asphyxia due to hanging. Conclusions: This case suggests that bilateral otorrhagia in hanging may result from the combined effects of impaired cervico-cephalic venous drainage and pressure changes transmitted to the middle ear during forceful respiratory efforts. The pre-existing unilateral petrous bone lesion may have acted as a local predisposing factor, although its etiology and actual contribution cannot be established with certainty. Otoscopic examination should therefore be regarded as a potentially useful adjunct in selected cases, particularly for documenting auricular findings and supporting differential diagnosis. Full article

Purpose: To investigate the short-term impact of scleral lens wear on intraocular pressure (IOP) and retinal nerve fiber layer (RNFL) thickness. We hypothesized that scleral lens wear would produce a measurable elevation in IOP accompanied by detectable RNFL thinning compared with soft contact lens wear. Methods: This prospective, randomized, contralateral-eye crossover study included 31 healthy participants (mean age: 26 ± 3 years). Each participant wore a 16.5 mm scleral lens over one eye and a soft contact lens over the fellow eye for 8 h, with assignments reversed between visits. IOP was measured using two tonometers: a transpalpebral Diaton tonometer and a non-contact tonometer (NCT), and RNFL thickness was measured by optical coherence tomography at four time points: pre- and post-lens application, and pre- and post-lens removal. Results: Eyes fitted with scleral lenses exhibited a significant IOP increase immediately after lens application (pre-application: 11 ± 3 mmHg vs. post-application: 16 ± 4 mmHg, p < 0.001), sustained throughout 8 h of wear (pre-removal: 16 ± 4 mmHg), and returned to baseline after removal (11 ± 3 mmHg). No significant IOP changes were observed in soft contact lens-wearing eyes (p > 0.05). Scleral lens wear was also associated with small but statistically significant peripapillary RNFL thinning (pre-application: 110 ± 11 µm vs. post-application: 107 ± 11 µm, p < 0.001), which returned to baseline after lens removal. No significant RNFL changes were observed with soft contact lens wear (p > 0.05). Bland–Altman analysis revealed poor agreement between Diaton and NCT measurements, consistent with the published literature on transpalpebral tonometry. Conclusions: Short-term scleral lens wear was associated with transient IOP elevation and peripapillary RNFL thinning, both reversible upon lens removal, in healthy young adults. These findings highlight the need for further longitudinal investigation in at-risk populations such as those with ocular hypertension, keratoconus, or early glaucoma before clinical monitoring recommendations can be established. Full article

Improvement of the engineering properties of soils by reinforcing them with fibers, at an appropriate percentage of the weight of dry soil, is frequently selected to ensure the safe construction and operation of many structures. However, the published information regarding the investigation of the dynamic properties of fiber-reinforced soils at very small strains is very limited. Toward this end, the dynamic behavior of fiber-reinforced soils is investigated experimentally by conducting Bender Element tests under different confining pressures. The effect of polypropylene fiber reinforcement on the shear wave velocity (V_s), the velocity of the primary wave (V_p), the initial Young’s modulus (E₀) and the initial shear modulus (G₀) of sand and sand–clay mixtures with varying compositions is examined in this study. The soils were reinforced with five different types of polypropylene fibers having lengths from 9 mm to 50 mm, at fiber contents from 0.5% to 2% by weight of dry soil. The results indicate that the dynamic and the small-strain stiffness parameters of fiber-reinforced soils increase with increasing confining pressure, while also being affected by the soil type, the fiber type, and content. Although fiber inclusion resulted generally in a reduction of the dynamic properties of soils, increases ranging from 5% to 55% were observed in certain soil–fiber combinations in comparison with the unreinforced soils. Full article

Distinguishing between human-made interferences and natural background disturbances is of great significance for the safe operation of terrestrial optical cables because human-caused damage can be halted through timely intervention. To address the problem of small-sample disturbance recognition in distributed acoustic sensing (DAS) systems, this paper proposes a fused CNN–SVM classification model based on hybrid features. A convolutional neural network is employed to extract the high-level spatiotemporal features of disturbance signals, which are subsequently fused with statistical features and fed into a support vector machine for classification. Evaluated on open-source data, the proposed model achieves accuracy improvements of 9.1%, 8.7%, and 2.7% over the conventional CNN, the statistical-feature-based SVM, and the conventional CNN-SVM model, respectively. Furthermore, based on field-measured data, a dataset comprising 5664 samples was constructed, covering four typical disturbance-event types: background noise, drilling, knocking, and digging. The field classification results demonstrate that the three-layer convolutional structure of the model achieves a recognition accuracy of 98.5%. Both the ROC curves and multiple evaluation metrics indicate that the proposed three-layer fused CNN–SVM model delivers better classification performance and more balanced category recognition, offering a feasible reference for similar fiber disturbance engineering tasks. Full article

Controlling the parameters of nanoparticles within a polymer matrix is a key challenge in advancing modern materials science, particularly in developing functional cellulose-based materials. This study focused on a comprehensive comparison of in situ and ex situ methods for synthesizing silver nanoparticles (AgNPs) to determine the optimal approach for achieving precise control over nanoparticle size and distribution within Lyocell-type fibers. Cellulose fibers were produced via the NMMO (N-methylmorpholine N-oxide) method, using glucose as an eco-friendly reducing agent for silver nitrate in both approaches. The in situ method involved generating AgNPs directly during spinning dope preparation, whereas the ex situ approach utilized chemical reduction under various conditions (12 h and 24 h, 70 °C) prior to incorporating the pre-synthesized nanoparticles into the fibers. UV-Vis, DLS, and TEM measurements were employed to characterize the nanoparticles, while the resulting fibers were evaluated for their degree of cellulose polymerization, as well as their mechanical and hygroscopic properties. The comparative analysis revealed that the ex situ synthesis (24 h, 70 °C) is the optimal method, enabling superior control over the nanoparticle parameters and successfully introducing a high percentage of small-diameter AgNPs (2–8 nm) into the fiber matrix without degrading the fundamental properties of the cellulose. Full article

Currently, clustering algorithms are mainly used to classify fiber-reinforced composite cylinder damage. However, the number of clustering categories is heavily influenced by the evaluation criteria, and the real damage type categorization cannot be determined. Therefore, we propose a semi-supervised algorithm that obtains higher damage classification information with a small number of labels. Specifically, we first performed a phased fiber-reinforced composite cylinder pressurization experiment and collected damage signals through acoustic emission (AE) hits. We analyzed the damage types of the collected burst-type acoustic emission hits (each hit corresponds to a single waveform captured when the hit’s amplitude exceeds the preset threshold) and marked a small number of these hits. Then, we constructed a mean-teacher semi-supervised network structure based on transfer learning, achieving a classification accuracy of 85.92%. Compared to traditional supervised learning and clustering algorithms, the accuracy improved by nearly 30%. Full article

Residual mud cake on the wellbore significantly compromises the cement–formation interfacial cementation quality. However, the research on the weak cementation mechanism of the cementing interface caused by mud cake properties is insufficient. In this paper, laboratory experiments and theoretical analysis were conducted to investigate the influence of mud cake properties on interfacial cementation strength. The results show that the main mechanism of weak cementation of the cement–formation interface caused by mud cake has three aspects: the thickness of mud cake is large, the structure is loose, the strength is low, the bearing capacity is insufficient, and the deformation–compression behavior is small and easily sheared. Based on this, three interfacial strengthening methods, chemical thinning by anhydrous sodium silicate, density enhancement by wollastonite and deformation–compression regulation using sepiolite fibers, were proposed to improve the cementation strength. The addition of anhydrous sodium silicate reduced mud cake thickness by up to 93.5% and increased interfacial cementation strength by 2.43 times. Wollastonite increased mud cake structural stability from 69 to 284 s·mm⁻¹ and improved interfacial cementation strength by up to 2.27 times. Sepiolite fibers increased the deformation–compression coefficient from 1.26 to 1.83, and the maximum interfacial cementation strength was achieved at R ≈ 1.64. In addition, the proposed additives improve the performance of mud cake and have good compatibility with drilling fluid. This study provides a theoretical basis for improving the cementing quality of the cementing interface. Full article

Background: Childhood obesity is increasingly associated with gut microbiome dysbiosis. This systematic review (PROSPERO CRD420251131354) evaluates evidence from studies published between 2020 and 2026 assessing how nutritional and lifestyle interventions influence gut microbiota in children with obesity. Methods: A systematic search of PubMed, EMBASE and EBSCO identified 21 interventional studies involving children aged 5–18 years with obesity, with the last search conducted in April 2026. Interventions comprised prebiotics, probiotics, synbiotics, postbiotics, high-fiber diets, calorie-restricted dietary approaches, and lifestyle modifications such as physical activity. Microbiome outcomes were analyzed using 16S rRNA sequencing, quantitative real-time polymerase chain reaction (qPCR), or metagenomics. Risk of bias was evaluated using the RoB 2 and ROBINS-I (version 2) tools. Due to substantial heterogeneity in study design, participant characteristics, intervention types, and analytical methods, a meta-analysis was not feasible. Results: Across 21 studies, nutritional interventions included measurable but heterogeneous alterations in gut microbiome composition. Inulin supplementation was associated with a significant increase in alpha diversity and with higher relative abundances of Bifidobacterium, Blautia, Megasphaera, Subdoligranulum, and Eubacterium coprostanoligenes. Synbiotic supplementation increased Prevotella and Dialister and reduced the Firmicutes/Bacteroidetes ratio. High-fiber dietary interventions increased Faecalibacterium, Bifidobacterium, and Clostridium, while reducing Bacteroides, and were associated with shifts in metabolic pathways related to carbohydrate, lipid, and nucleotide metabolism. Calorie-restricted diets and combined diet–exercise interventions increased beneficial taxa such as Akkermansia muciniphila, improved microbial diversity, and correlated with favorable metabolic and anthropometric outcomes. Overall, nutritional and lifestyle interventions in pediatric obesity were associated with taxon-specific and context-dependent microbiome changes, rather than uniform restructuring. Conclusions: Nutritional interventions can modulate gut microbiota diversity, composition, and predicted function in pediatric obesity; however, the observed effects vary substantially across studies. The limited number of trials, small sample sizes, and methodological heterogeneity underscore the need for larger, standardized studies to better define clinical and therapeutic implications. Full article

Although exercise interventions have been shown to alleviate core symptoms of Autism Spectrum Disorder (ASD), the neural mechanisms underlying these improvements, particularly those involving the White Matter Network (WMN), remain poorly understood. This study investigated the effects of a Mini-Basketball Training Program (MBTP) on core symptoms and WMN in children with ASD. This study adopted a two-site cluster-Randomized Controlled Trial (cRCT) design. Participants from two special education centers in China were randomly assigned to either an intervention group (MBTP) or a control group (CON). The participants underwent a 12-week MBTP. Core symptom assessments and a Diffusion Tensor Imaging (DTI) scan were conducted before and after the intervention. The individual WMNs were constructed using Deterministic Fiber Tracking (DFT). Graph theoretical analysis was applied to examine changes in WMN topological properties after MBTP. The MBTP significantly improved core symptoms in children with ASD, alongside the decreased normalized clustering coefficient (Gamma, γ), characteristic path length (Lambda, λ), small-world attributes (Sigma, σ), and increased global efficiency (E_glob). The nodal clustering coefficient (NCC) increased in the left cuneus (CUN.L) and left cerebellum 9 (CRBL9.L). Notably, the increased NCC in CRBL9.L was significantly correlated with improvements in core symptoms following the MBTP. The improvement in core symptoms in children with ASD following exercise intervention is associated with the remodeling of the WMN, highlighting the cerebellum as a key node in this neural mechanism. Full article

The in-plane shear performance of carbon fiber-reinforced polymer (CFRP) composites is critical for structural design but is challenged by significant property scatter. This study aims to achieve individualized prediction of the complete shear stress–strain curve for each composite specimen using only a single early-stage digital image correlation (DIC) strain field. Systematic in-plane shear tests were conducted on 45 laminated carbon fiber/epoxy specimens with synchronized full-field DIC data and macroscopic load–displacement records. A lightweight encoder–decoder convolutional neural network was developed, taking a single DIC strain contour map at 0.2% global strain as input and mapping it directly to the full-range stress–strain curve up to failure for that specific specimen. Data augmentation and Dropout regularization mitigated the small-sample challenge. The proposed model achieved strong predictive performance across the five-fold cross-validation yielded a mean R² of 0.926 ± 0.022 and a mean RMSE of 6.37 ± 1.14 MPa for stress. Individual specimen predictions on the test set yielded an average R² of 0.945, with a minimum of 0.821, confirming robust capability across scattered properties. Residual analysis elucidated error characteristics across deformation stages. This research provides a novel paradigm for non-destructive, early-stage individualized assessment of composite mechanical properties, with applications in structural health monitoring and probabilistic design. Full article