Search Results (2,812)

Rising volumes of textile waste necessitate the development of more efficient recycling systems, with a primary focus on the optimization of sorting technologies. Near-infrared (NIR) spectroscopy is a state-of-the-art method for fiber identification; however, its accuracy in quantifying textile blends, particularly common polyester/cotton blend textiles, still requires refinement. This study explores the potential and limitations of NIR spectroscopy for quantifying cotton content in post-consumer textiles. A lab-scale NIR sorter and a handheld NIR spectrometer in complementary wavelength ranges were applied to a diverse range of post-consumer textile samples to test model accuracies. Results show that the commonly assumed 10% accuracy threshold in industrial sorting can be exceeded, especially when excluding textiles with <35% cotton content. Identifying and excluding the range of non-linearity significantly improved the model’s performance. The final models achieved an RMSEP of 6.6% and bias of −0.9% for the NIR sorter and an RMSEP of 3.1% and bias of −0.6% for the handheld NIR spectrometer. This study also assessed how textile characteristics—such as color, structure, product type, and alkaline treatment—affect spectral behavior and model accuracy, highlighting their importance for refining quantification when high-purity inputs are needed. By identifying current limitations and potential sources of errors, this study provides a foundation for improving NIR-based models. Full article

In this study, 62 lactic acid bacteria (LAB) strains were isolated from raw camel milk and evaluated for their probiotic potential. The strains exhibited significant variability in their ability to withstand simulated gastrointestinal conditions. Of the isolates, only 26 survived exposure to pH 2, and just 10 were tolerant to 0.3% bile salts. Partial sequencing of the 16S rRNA gene identified all the strains as belonging to the species Enterococcus faecium. Several probiotic traits were assessed, including adhesion to gastric mucin and STC-1 intestinal epithelial cells, as well as auto-aggregation and co-aggregation capacities. Although adhesion to hydrophobic solvents such as chloroform and ethyl acetate was generally low to moderate, all the strains demonstrated strong adhesion to gastric mucin, exceeding 60% at all the growth stages. Notably, two strains—SCC1-33 and SLch6—showed particularly high adhesion to STC-1 cells, with values of 7.8 × 10³ and 4.2 × 10³ CFU/mL, respectively. The strains also exhibited promising aggregation properties, with auto-aggregation and co-aggregation ranging between 33.10% and 63.10%. Furthermore, all the isolates displayed antagonistic activity against Listeria innocua, Micrococcus luteus, and Escherichia coli. Cytotoxicity assays confirmed that none of the tested strains had harmful effects on STC-1 cells, indicating their safety and supporting their potential application as probiotics. Full article

Background/Objectives: Amorphous solid drugs exhibit physical instability and a propensity for crystallization, which leads to reduced solubility and bioavailability. Hence, this study optimized scale manufacturing parameters for producing a physically stable amorphous solid form of nilotinib using neutralization precipitation. Methods: A systematic evaluation of the effects of the solute concentration and filtration rate on amorphous physical stability was conducted using the pair distribution function (PDF), principal component analysis (PCA), and reduced crystallization temperature (R_c) values. Results: It showed concentration-dependent crystallization resistance, with optimal physical stability achieved at a solute concentration of 0.126 mol/L and a 124 mL/min filtration rate. Experiments carried out at a scale of 50 g confirmed the stability of the production process. Conclusions: These findings provide a validated framework for developing lab-scale amorphous drug products with improved shelf-life stability, assessed using indirect indicators (PDF, R_c) and confirmed through accelerated stability tests. Full article

Background: Core laboratory chemistry analyzers typically use plasma and serum samples, while blood gas instruments use whole blood for electrolyte and metabolite tests. Due to high costs to back up the core lab chemistry analyzers, especially in the remote small community hospitals, we have verified the interchangeability of serum/plasma electrolytes and metabolites on blood gas instruments (GEM4000 and Radiometer ABL90) vs. chemistry analyzers. In this study, we sought to extend the investigation to another blood gas device—Radiometer ABL837. Methods: One plasma separator tube and one serum separator tube were drawn from 20 apparently healthy individuals and outpatients and 20 intensive care unit patients. All the samples were run on Roche Cobas8000, and then were run on three Radiometer ABL837 analyzers for sodium (Na⁺), potassium (K⁺), chloride (Cl⁻), glucose, lactate (plasma only), and creatinine parameters. Paired measurements between the ABL837 and Cobas8000 were compared, and their difference were assessed for statistical and clinical significance. Results: ABL837 demonstrated statistical significance (p < 0.05) vs. Cobas8000 on all the plasma and serum parameters. However, no parameter differences were found when comparing the plasma/serum results on ABL837 to those on Cobas8000, indicating that none were clinically significant. ABL837 also demonstrated good–excellent correlations with Cobas8000 on all the parameters. Conclusions: When comparing metabolite and electrolyte values with plasma and serum sample types, the ABL837 blood gas instruments and Cobas 8000 chemistry analyzer are interchangeable. These data proves that ABL837 can be used as a backup for a chemistry analyzer in measuring plasma and serum electrolyte and metabolite concentrations. Full article

Porphyra-derived polysaccharides (PPs) are promising prebiotic candidates due to their capacity to modulate gut microbiota and promote host health. However, their interactions with and utilization by probiotic microorganisms remain unclear. In this study, the fermentability of PPs by murine-derived lactic acid bacteria (LAB) strains was investigated, with particular attention to strain-specific metabolic activity, carbohydrate utilization, and potential exopolysaccharide (EPS) production. All tested strains were capable of utilizing PPs to varying extents, with strain A10 exhibiting the highest level of carbohydrate consumption. Notably, strain A5 showed increased mannose concentrations following fermentation, suggesting the biosynthesis of mannose-rich EPSs. HPLC analysis confirmed the presence of high-molecular-weight polysaccharides ranging from 2.6 to 8.1 × 10⁵ Da, indicative of EPS production. FT-IR spectroscopy further revealed spectral features consistent with EPS structures. The antibacterial activity of postbiotic compounds produced by LAB strains fermenting PPs against Escherichia coli and Staphylococcus aureus was observed. These findings demonstrate distinct metabolic adaptations of LAB strains to PPs and emphasize their potential as prebiotic substrates. Full article

The aim of this study was to isolate and identify lactic acid bacteria (LAB) from a traditional fermented beverage, Boza, and to conduct an in-depth study on their fermentation and probiotic properties. The fermentation (acid production rate, acid tolerance, salt tolerance, amino acid decarboxylase activity) and probiotic properties (gastrointestinal tolerance, bile salt tolerance, hydrophobicity, self-aggregation, drug resistance, bacteriostatic properties) of the 16 isolated LAB were systematically analyzed by morphological, physiological, and biochemical tests and 16S rDNA molecular biology. This analysis utilized principal component analysis (PCA) to comprehensively evaluate the biological properties of the strains. The identified LAB included Limosilactobacillus fermentum (9 strains), Levilactobacillus brevis (2 strains), Lacticaseibacillus paracasei (2 strains), and Lactobacillus helveticus (3 strains). These strains showed strong environmental adaptation at different pH (3.5) and temperature (45 °C), with different gastrointestinal colonization, tolerance, and antioxidant properties. All the strains did not show hemolytic activity and were inhibitory to Staphylococcus aureus, and showed resistance to kanamycin, gentamicin, vancomycin, and streptomycin. Based on the integrated scoring of biological properties by principal component analysis, Limosilactobacillus fermentum S4 and S6 and Levilactobacillus brevis S5 had excellent fermentation properties and tolerance and could be used as potential functional microbial resources. Full article

To meet the European Green Deal targets, the construction sector must improve building thermal performance via advanced insulation systems. Eco-friendly sandwich panels offer a promising solution. Therefore, this work aims to develop and validate a new eco-friendly composite sandwich panel (basalt fibres and recycled extruded polystyrene) with enhanced multifunctionality for lightweight and energy-efficient building façades. Two panels were produced via vacuum infusion—a reference panel and a multifunctional panel incorporating phase change materials (PCMs) and silica aerogels (AGs). Their performance was evaluated through lab-based thermal and acoustic tests, numerical simulations, and on-site monitoring in a living laboratory. The test results from all methods were consistent. The PCM-AG panel showed 16% lower periodic thermal transmittance (0.16 W/(m²K) vs. 0.19 W/(m²K)) and a 92% longer time shift (4.26 h vs. 2.22 h), indicating improved thermal inertia. It also achieved a single-number sound insulation rating of 38 dB. These findings confirm the panel’s potential to reduce operational energy demand and support long-term climate goals. Full article

Background: Pulsed field ablation (PFA) is a novel non-thermal modality for pulmonary vein isolation (PVI) in atrial fibrillation (AF), offering myocardial selectivity through irreversible electroporation while sparing surrounding structures. However, concerns have emerged regarding potential subclinical hemolysis, reflected by alterations in biochemical markers such as lactate dehydrogenase (LDH). Methods: We conducted a retrospective, single-center study involving 249 patients undergoing PVI: 121 treated with PFA (PulseSelect or FARAPULSE) and 128 with radiofrequency (RF) ablation (PVAC catheter). Laboratory parameters were assessed at baseline, post-procedure, and at discharge, including hemoglobin, hematocrit, red blood cell (RBC) count, platelet count, creatinine, and LDH. The primary endpoint was the variation in blood cell indices; the secondary endpoint was the evaluation of LDH and hematocrit changes. Statistical analysis included t-tests and chi-square tests. Results: Baseline characteristics and pre-procedural labs did not differ significantly between groups. No significant changes in hemoglobin, hematocrit, RBC count, platelet count, or creatinine were observed post-ablation or at discharge. However, LDH levels significantly increased in the PFA group both post-procedurally and at discharge (p < 0.001), without concurrent changes in other blood cell parameters. Conclusions: PFA and RF ablation yield comparable hematological profiles after PVI, with no significant impact on key blood cell parameters. Nonetheless, the consistent rise in LDH levels in the PFA group suggests mild, subclinical hemolysis or tissue injury due to more extensive lesions. While supporting the hematologic safety of PFA, these findings underscore the need for further studies to assess the clinical significance of these biochemical alterations, particularly in high-risk patients or extensive ablation settings. Full article

Soil-transmitted helminths (STHs) present a significant global health challenge, particularly in tropical and subtropical regions. The current diagnostic standard involves the microscopic examination of a stool smear but it lacks sensitivity to detect infections of low intensity. Innovative solutions like lab-on-a-disk (LoD) technologies are emerging, showing promise in detecting low-intensity infections. Field tests conducted using our SIMPAQ (single-image parasite quantification) LoD device have demonstrated its potential as a diagnostic tool, especially for such low-intensity infections. Nevertheless, the device’s efficiency has been limited by significant egg loss during sample preparation, low capture efficiency of eggs within the Field of View (FOV), and the presence of larger fecal debris that obstructs effective egg trapping and imaging. In this study, we conducted a set of laboratory experiments using model polystyrene particles and purified STH eggs to improve the sample preparation protocol. These experiments include the entire SIMPAQ procedure starting from sample preparation, infusing it into the LoD device, centrifugation, delivering the (model) eggs to the FOV, capturing an image, and analyzing it. We analyzed egg losses at each step of the procedure following the “standard” protocol, then elaborated and tested alternative, more efficient procedures. The resulting modified protocol significantly minimized particle and egg loss and reduced the amount of debris in the disk, thus enabling effective egg capture and clear images in the FOV, increasing the reliability of the diagnostic results. Full article

Erosion gullies can reduce arable land area and decrease agricultural machinery efficiency; therefore, automatic gully extraction on a regional scale should be one of the preconditions of gully control and land management. The purpose of this study is to compare the effects of the grey level co-occurrence matrix (GLCM) and topographic–hydrologic features on automatic gully extraction and guide future practices in adjacent regions. To accomplish this, GaoFen-2 (GF-2) satellite imagery and high-resolution digital elevation model (DEM) data were first collected. The GLCM and topographic–hydrologic features were generated, and then, a gully label dataset was built via visual interpretation. Second, the study area was divided into training, testing, and validation areas, and four practices using different feature combinations were conducted. The DeepLabV3+ and ResNet50 architectures were applied to train five models in each practice. Thirdly, the trainset gully intersection over union (IOU), test set gully IOU, receiver operating characteristic curve (ROC), area under the curve (AUC), user’s accuracy, producer’s accuracy, Kappa coefficient, and gully IOU in the validation area were used to assess the performance of the models in each practice. The results show that the validated gully IOU was 0.4299 (±0.0082) when only the red (R), green (G), blue (B), and near-infrared (NIR) bands were applied, and solely combining the topographic–hydrologic features with the RGB and NIR bands significantly improved the performance of the models, which boosted the validated gully IOU to 0.4796 (±0.0146). Nevertheless, solely combining GLCM features with RGB and NIR bands decreased the accuracy, which resulted in the lowest validated gully IOU of 0.3755 (±0.0229). Finally, by employing the full set of RGB and NIR bands, the GLCM and topographic–hydrologic features obtained a validated gully IOU of 0.4762 (±0.0163) and tended to show an equivalent improvement with the combination of topographic–hydrologic features and RGB and NIR bands. A preliminary explanation is that the GLCM captures the local textures of gullies and their backgrounds, and thus introduces ambiguity and noise into the convolutional neural network (CNN). Therefore, the GLCM tends to provide no benefit to automatic gully extraction with CNN-type algorithms, while topographic–hydrologic features, which are also original drivers of gullies, help determine the possible presence of water-origin gullies when optical bands fail to tell the difference between a gully and its confusing background. Full article

Epoxy-based nanocomposites have drawn much interest in high-voltage insulation applications due to their improved dielectric properties. The determination of the optimal nanoparticle (NP) concentration required to achieve a significant enhancement in nanocomposite dielectric properties remains a subject of ongoing research. Previous work has employed iterative experimental methodologies, often characterized by the hit-and-trial method, in attempts to find the optimal nanoparticle concentration. However, these efforts have yielded suboptimal or inconsistent results. Moreover, experimental procedures for optimizing the nanoparticle concentration require significant time and cost. This research study proposed the predictive capabilities of machine learning (ML) for the selection of the nanoparticle concentration in epoxy-based nanocomposite insulators. The authors employed a novel systematic approach in this research work, comprising dataset preparation, ML model implementation, and experimental validation. A real-time dataset with varying concentrations of NPs (TiO₂, SiO₂, Al₂O₃) was developed in the High Voltage Lab, KFUEIT, Pakistan. Several advanced machine learning models are trained on this dataset. Support Vector Regression (SVR) exhibits the highest prediction accuracy, with an R² score of 0.97. SVR predicted a breakdown voltage (BDV) of 46.26 kV, with a (w/w %) concentration of 5% TiO₂, 1.17631% SiO₂, and 3.95755% Al₂O₃. To validate the SVR prediction, a hardware prototype with predicted NP concentration is developed and tested. The experimentally measured BDV of the predicted nanocomposite sample, registering 44.72 kV, authenticates the predictive accuracy of machine learning. This work demonstrates the efficacy of machine learning as a viable and efficient alternative to traditional experimental methods for optimizing nanoparticle concentrations using a predictive approach in epoxy-based nanocomposites for high-voltage insulation applications. Full article

To address the limitations of traditional tunnel structural plane modeling—such as low automation, insufficient smoothness, and poor adaptability to real construction environments—this study proposes a novel three-dimensional (3D) modeling framework based on B-spline interpolation combined with deep learning. The method first employs YOLOv5 for rapid detection of structural regions and DeepLabV3+ for precise boundary segmentation, followed by skeleton extraction and coordinate transformation to obtain spatial structural traces. Finally, B-spline interpolation is applied across multiple tunnel sections to construct continuous 3D surfaces. In model training and testing, the segmentation network achieved an F1 score of 94.01%, and the final modeling accuracy demonstrated a mean relative error (MRE) below 2.5%, confirming the reliability of the geometric reconstruction. Additionally, the proposed method was applied to excavation face images from the Paiyashan Tunnel, where multiple structural surfaces were successfully reconstructed in 3D, validating the approach’s applicability and robustness in real geological conditions. Compared to traditional triangulated or linear surface methods, the proposed approach achieves higher smoothness, better geological continuity, and improved automation, making it suitable for real-world geotechnical applications. Full article

Background: The number of women veterans has been rising steadily since the Gulf War and many assume the functions of their male counterparts. Women face unique obstacles in their service, and it is imperative that differences in physiology not be overlooked so as to provide better and appropriate care to our women in uniform. Despite this influx and incorporation of female talent, dedicated reports contrasting female and male veterans are rare, outside of specific psychological studies. We therefore attempt to contrast gut constituents, absorption, innate immune system, and nutritional differences to provide a comprehensive account of similarities and differences between female and male veterans, from our single-center perspective, as this has not been carried out previously. Herein, we obtained a detailed roster of commonly used biomedical tests and some novel entities to detect differences between female and male veterans. The objective of this study was to detect differences in the innate immune system and other ancillary test results to seek differences that may impact the health of female and male veterans differently. Methods: To contrast biochemical and sociomedical parameters in female and male veterans, we studied the data collected on 450 female veterans and contrasted them to a group of approximately 1642 males, sequentially from 1995 to 2022, all selected because of above-average risk for CRC. As part of this colorectal cancer (CRC) screening cross-sectional and longitudinal study, we also collected stool, urine, saliva, and serum specimens. We used ELISA testing to detect stool p87 shedding by the Adnab-9 monoclonal and urinary organ-specific antigen using the BAC18.1 monoclonal. We used the FERAD ratio (blood ferritin/fecal p87), a measure of the innate immune system to gauge the activity of the innate immune system (InImS) by dividing the denominator p87 (10% N-linked glycoprotein detected by ELISA) into the ferritin level (the enumerator, a common lab test to assess anemia). FERAD ratios have not been performed elsewhere despite past Adnab-9 commercial availability so we have had to auto-cite our published data where appropriate. Results: Many differences between female and males were detected. The most impressive differences were those of the InImS where males clearly had the higher numbers (54,957 ± 120,095) in contrast to a much lower level in females (28,621 ± 66,869), which was highly significantly different (p < 0.004). Mortality was higher in males than females (49.4% vs. 24.1%; OR 3.08 [2.40–3.94]; p < 0.0001). Stool p87, which is secreted by Paneth cells and may have a protective function, was lower in males (0.044 ± 0.083) but higher in females (0.063 ± 0.116; p < 0.031). Immunohistochemistry of the Paneth cell-fixed p87 antigen was also higher in females (in the descending colon and rectum). In contrast, male ferritin levels were significantly higher (206.3 ± 255.9 vs. 141.1 ± 211.00 ng/mL; p < 0.0006). Females were less likely to be diabetic (29.4 vs. 37.3%; OR 0.7 [0.55–0.90]; p < 0.006). Females were also more likely to use NSAIDs (14.7 vs. 10.7%, OR 1.08 [1.08–2.00]; p < 0.015). Females also had borderline less GI bleeding by fecal immune tests (FITs), with 13.2% as opposed to 18.2% in males (OR 0.68 [0.46–1.01]; p = 0.057), but were less inclined to have available flexible sigmoidoscopy (OR 0.68 [0.53–0.89]; p < 0.004). Females also had more GI symptomatology, a higher rate of smoking, and were significantly younger than their male counterparts. Conclusions: This study shows significant differences with multiple parameters in female and male veterans. Full article

The increasing complexity of cybersecurity risks highlights the critical need for novel teaching techniques that provide students with the necessary skills and information. Traditional on-premises laboratory setups frequently lack the scalability, flexibility, and accessibility necessary for efficient training in today’s dynamic world. This study compares the efficacy of cloud-based solutions—specifically, Amazon Web Services (AWS) Elastic Compute Cloud (EC2)—against traditional settings like VirtualBox, with the goal of determining their potential to improve cybersecurity education. The study conducts systematic experimentation to compare lab environments based on parameters such as lab completion time, CPU and RAM use, and ease of access. The results show that AWS EC2 outperforms VirtualBox by shortening lab completion times, optimizing resource usage, and providing more remote accessibility. Additionally, the cloud-based strategy provides scalable, cost-effective implementation via a pay-per-use model, serving a wide range of pedagogical needs. These findings show that incorporating cloud technology into cybersecurity curricula can lead to more efficient, adaptable, and inclusive learning experiences, thereby boosting pedagogical methods in the field. Full article

Deployment of nature-based systems for mine water treatment is constrained by system size, and the evidence suggests decreasing hydraulic conductivity (K_sat) of organic substrates over time compromises performance. In lab-scale continuous-flow reactors, we investigated (1) the geochemical and hydraulic performance of organic substrates used in nature-based systems for metals removal (via bacterial sulfate reduction) from mine water, and then (2) the potential to operate systems modestly contaminated with Zn (0.5 mg/L) at reduced hydraulic residence times (HRTs). Bioreactors containing limestone, straw, and wood chips, with and without compost and/or sewage sludge all achieved 88%–90% Zn removal, but those without compost/sludge had higher K_sat (929–1546 m/d). Using a high K_sat substrate, decreasing the HRT from 15 to 9 h had no impact on Zn removal (92.5% to 97.5%). Although the sulfate reduction rate decreased at a shorter HRT, microbial analysis showed high relative abundance (2%–7%) of sulfate reducing bacteria, and geochemical modelling pointed to ZnS(s) precipitation as the main attenuation mechanism (mean ZnS saturation index = 3.91–4.23). High permeability organic substrate treatment systems operated at a short HRT may offer potential for wider deployment of such systems, but pilot-scale testing under ambient environmental conditions is advisable. Full article