Search Results (7,418)

US food regulatory agencies have adopted a preference for researchers and testing labs to use ‘acid adapted challenge cultures’ when performing inoculated validation studies of food processes that involve acidic treatments to accustom the cultures to acidic pH so that they will not be easily affected during processing. We evaluated acid adaptation in regard to the processing of South African style air-dried beef, notably biltong and droëwors, using a mixture of five serovars of Salmonella as well as a unique serovar isolated from dried beef (Salmonella Typhimurium 1,4,[5],12:i:-). Acid adaptation was obtained by growing cultures in tryptic soy (TS) broth containing 1% glucose. Non adapted cultures were obtained by growth in TS broth without glucose or in TS broth with 1% glucose but buffered with 0.2 M phosphate buffer. Processes included biltong (dried solid beef) and droëwors (ground, sausage-style). Each trial was performed twice and triplicate samples were examined at each sampling point (i.e., n = 6). Statistical analysis was applied using analysis of variance (ANOVA) or one-way repeated measures (RM-ANOVA) and the Holm–Sidak test for pairwise multiple comparisons to determine significant differences (p < 0.05). We observed that in all processes examined (eight trials), treatments using acid adapted cultures were more sensitive to the biltong and droëwors processes, giving greater reductions (5.3-log reduction) than when non-adapted cultures were used (3.8-log reduction). Acid adaptation leads to stressed conditions in Salmonella resulting in sensitization to the multiple hurdles found in biltong and droëwors processing (acid/vinegar, salt, desiccation). Based on our data, the use of non adapted Salmonella cultures to achieve desired challenge culture process lethality could result in more robust processing conditions and a greater level of safety in these products as intended by US regulatory guidance. Full article

In response to the inability to quickly assess wind noise performance during the early stages of automotive styling design, this paper proposes a method for predicting interior wind noise by integrating automotive point cloud models with the Gray Wolf Optimization Residual Network model (GWO-ResNet). Based on wind tunnel test data under typical operating conditions, the point cloud model of the test vehicle is compressed using an auto-encoder and used as input features to construct a nonlinear mapping model between the whole vehicle point cloud and the wind noise level at the driver’s left ear. Through adaptive optimization of key hyperparameters of the ResNet model using the gray wolf optimization algorithm, the accuracy and generalization of the prediction model are improved. The prediction results on the test set indicate that the proposed GWO-ResNet model achieves prediction results that are consistent with the actual measured values for the test samples, thereby validating the effectiveness of the proposed method. A comparative analysis with traditional ResNet models, GWO-LSTM models, and LSTM models revealed that the GWO-ResNet model achieved Mean Absolute Percentage Error (MAPE) and mean squared error (MSE) of 9.72% and 20.96, and 9.88% and 19.69, respectively, on the sedan and SUV test sets, significantly outperforming the other comparison models. The prediction results on the independent validation set also demonstrate good generalization ability and stability (MAPE of 10.14% and 10.15%, MSE of 23.97 and 29.15), further proving the reliability of this model in practical applications. The research results provide an efficient and feasible technical approach for the rapid evaluation of wind noise performance in vehicles and provide a reference for wind noise control in the early design stage of vehicles. At the same time, due to the limitations of the current test data, it is impossible to predict the wind noise during the actual driving of the vehicle. Subsequently, the wind noise during actual driving can be predicted by the test data of multiple working conditions. Full article

Spanish “Fino”-style white wines are traditionally aged by a dynamic process under a flor veil of Saccharomyces cerevisiae, requiring ≥15% (v/v) ethanol, which is typically achieved through fortification. Market demand for lower-alcohol wines and the need to reduce production costs have encouraged the development of alternative approaches. Here, static biological aging was evaluated as a method for producing Fino-type wines with reduced ethanol content. Base wines with ~14% and ~15% (v/v) ethanol were aged for nine months, during which chemical, microbiological, and sensory parameters were analyzed, along with flor veil activity. Lower-ethanol wines showed greater flor activity, with approximately 20 more yeast isolates in the wines with 14% (v/v) ethanol. Higher acetaldehyde levels were detected in these wines, reaching about 377 mg L⁻¹ compared to 230 mg L⁻¹ in the control wines (≥15% v/v ethanol). Significant changes were observed in pH (3.13–3.47 vs. 3.04–3.46), volatile acidity (0.20–0.26 g L⁻¹ vs. 0.31–0.66 g L⁻¹), and several volatile compounds, resulting in chemical and sensory profiles consistent with traditional biologically aged wine. Static biological aging can yield lower-alcohol Fino-style white wines with sensory and chemical attributes comparable to the traditional fortified versions, providing a cost-effective alternative that aligns with evolving consumer preferences. Full article

The Mako Belt in the Kédougou-Kéniéba Inlier (eastern Senegal) preserves Paleoproterozoic (2.3–1.9 Ga) mafic and ultramafic rocks that record early crustal growth processes within the southern West African Craton (WAC). Basalt bulk rock compositions preserve primary melt signatures, whereas the associated ultramafic cumulates are variably serpentinized and are better assessed through mineral chemistry. Basalts occur as massive and pillow lavas, with MgO contents of 5.9–9.1 wt.% and flat to slightly LREE-depleted patterns (La/Smₙ = 0.73–0.88). Primitive mantle-normalized diagrams show subduction-related signatures, including enrichment in Ba, Pb, and Rb and depletion in Nb and Ta. Most basalts and all ultramafic rocks display (Nb/La)_PM > 1, consistent with enriched mantle melting in a back-arc setting. Harzburgites and lherzolites have cumulate textures, high Cr and Ni contents, and spinel with chromian cores (Cr# > 0.6) zoned sharply to Cr-rich magnetite rims that overlap basalt spinel compositions. Integration of the petrographic, mineralogical, and whole-rock geochemical data indicates the presence of mafic melts derived from a subduction-modified mantle wedge and likely formed in a back-arc basin above a subducting slab, rather than from a plume or mid-ocean ridge setting. Regional comparisons with other greenstone belts across the WAC suggest that the Mako Belt was part of a broader arc–back-arc system accreted during the Eburnean orogeny (~2.20–2.00 Ga). This study supports the view that modern-style plate tectonics—including subduction and back-arc magmatism—was already active by the Paleoproterozoic, and highlights the Mako Belt as a key archive of early lithospheric evolution in the WAC. Full article

In this paper, we apply an information-theoretic method proposed by Ryabko and Savina (therefore called the RS-method), based on the use of data compression, to recognize the individual author’s style of a writer across four languages from different language groups and families. In this paper, the presented method was used to study fiction texts in Russian (East Slavic group of languages of the Indo-European language family), Amharic (South Ethiosemitic group of the Semitic language family), Chinese (Sinitic group of the Sino-Tibetan language family) and English (West Germanic language group of the Indo-European language family). It was found that the amount of data necessary for recognizing an author’s style is almost the same for all four languages, i.e., the amount of data is invariant across different language groups. The results obtained are of interest to computer science, literary studies, linguistics and, in particular, computational linguistics. Full article

Background/Objectives: National Football League (NFL) American football players are exposed to osteoarthritis risk factors of obesity and high joint loads. We sought to examine the association between total body mass (TBM), lean body mass (LBM), body fat percentage (BF%), and normalized compressive knee joint reaction forces (JRFcomp), peak knee adductor moments (KAM), and vertical ground reaction forces (vGRF) in NFL draft-eligible players during a high-speed run. Methods: A total of 125 participants ran a single trial at 5.5–6.5 m/s for 5 s on an instrumented treadmill. Bilateral vGRF and knee joint kinetics were calculated using inverse dynamics. Body composition was assessed using bioelectrical impedance. Results: LBM demonstrated significant moderate associations with vGRF (left, r(123) = −0.56, p < 0.001; right, r(123) = −0.60, p < 0.001) and low-to-negligible associations with KAM (left, r(123) = −0.20, p = 0.026; right, r(123) = −0.30, p < 0.001) and JRFcomp (left, r(123) = −0.39, p = 0.020; right, r(123) = −0.38, p = 0.015), respectively. TBM showed significant moderate negative associations with vGRF (left, r(123) = −0.56, p < 0.001; right, r(123) = −0.61, p < 0.001) and low-to-negligible associations with KAM (left, r(123) = −0.21, p = 0.021; right, r(123) = −0.28, p = 0.002) and JRFcomp (left, r(123) = −0.39, p < 0.001; right, r(123) = −0.37, p < 0.001), respectively. BF% showed significant low-to-negligible negative associations with JRFcomp (left, r(123) = −0.21, p < 0.001; right, r(123) = −0.22, p < 0.001) and vGRF (left, r(123) = −0.39, p < 0.001; right, r(123) = −0.41, p < 0.001), respectively, and no significant associations with KAM, p > 0.05. The heavier group exhibited significantly lower normalized JRFcomp, and vGRF, p < 0.05. Conclusions: Heavier, but not fatter, players attenuate knee loads. Dampening may be a short-term protective strategy for joints of heavier players. Full article

The glyoxalase pathway intermediate S-d-lactoylglutathione was recently implicated in protein post-translational modifications in animal systems. Here, we examined the spontaneous modification of the Arabidopsis thaliana cytosolic glyceraldehyde-3-phosphate dehydrogenase C1 (GAPC1) by this compound. Incubation of GAPC1 with S-d-lactoylglutathione resulted in the inhibition of enzyme activity. The inhibitory effect was concentration dependent and increased at alkaline pHs. Furthermore, the inhibition of GAPC1 by S-d-lactoylglutathione was favored by oxidative conditions and reversed by reduction with dithiothreitol. Analyses of the S-d-lactoylglutathione-treated protein by nanoLC-MS/MS revealed S-glutathionylation of its two Cys residues and N-lactoylation of six Lys residues. Protein structure predictions showed that the double S-glutathionylation is accommodated by the GAPC1 catalytic pocket, which likely explains enzyme inhibition. N-lactoylated sites overlap partially with previously reported N-acetylated sites at the surface of the GAPC1 tetramer. The efficiency of cytosolic glutaredoxin and thioredoxin isoforms was tested for reversing the S-d-lactoylglutathione-induced modification. In these assays, recovery of GAPC1 activity after inhibition by S-d-lactoylglutathione treatment was used as indicator of efficiency. The results show that both types of redoxins were able to reverse inhibition. We propose a model describing the mechanisms involved in the two types of post-translational modifications found on GAPC1 following exposure to S-d-lactoylglutathione. The possible involvement of these findings for the control over glycolytic metabolism is discussed. Full article

Generating non-standard fonts, such as running script (e.g., XingShu), poses significant challenges due to their high stroke continuity, structural flexibility, and stylistic diversity, which traditional component-based prior knowledge methods struggle to model effectively. While diffusion models excel at capturing continuous feature spaces and stroke variations through iterative denoising, they face critical limitations: (1) style leakage, where large stylistic differences lead to inconsistent outputs due to noise interference; (2) structural distortion, caused by the absence of explicit structural guidance, resulting in broken strokes or deformed glyphs; and (3) style confusion, where similar font styles are inadequately distinguished, producing ambiguous results. To address these issues, we propose a novel skeleton-guided diffusion model with three key innovations: (1) a skeleton-constrained style rendering module that enforces semantic alignment and balanced energy constraints to amplify critical skeletal features, mitigating style leakage and ensuring stylistic consistency; (2) a cross-scale skeleton preservation module that integrates multi-scale glyph skeleton information through cross-dimensional interactions, effectively modeling macro-level layouts and micro-level stroke details to prevent structural distortions; (3) a contrastive style refinement module that leverages skeleton decomposition and recombination strategies, coupled with contrastive learning on positive and negative samples, to establish robust style representations and disambiguate similar styles. Extensive experiments on diverse font datasets demonstrate that our approach significantly improves the generation quality, achieving superior style fidelity, structural integrity, and style differentiation compared to state-of-the-art diffusion-based font generation methods. Full article

Accurate detection and counting of wheat spikes are crucial for yield estimation and variety selection in precision agriculture. However, challenges such as complex field environments, morphological variations, and small target sizes hinder the performance of existing models in real-world applications. This study proposes FEWheat-YOLO, a lightweight and efficient detection framework optimized for deployment on agricultural edge devices. The architecture integrates four key modules: (1) FEMANet, a mixed aggregation feature enhancement network with Efficient Multi-scale Attention (EMA) for improved small-target representation; (2) BiAFA-FPN, a bidirectional asymmetric feature pyramid network for efficient multi-scale feature fusion; (3) ADown, an adaptive downsampling module that preserves structural details during resolution reduction; and (4) GSCDHead, a grouped shared convolution detection head for reduced parameters and computational cost. Evaluated on a hybrid dataset combining GWHD2021 and a self-collected field dataset, FEWheat-YOLO achieved a COCO-style AP of 51.11%, AP@50 of 89.8%, and AP scores of 18.1%, 50.5%, and 61.2% for small, medium, and large targets, respectively, with an average recall (AR) of 58.1%. In wheat spike counting tasks, the model achieved an R² of 0.941, MAE of 3.46, and RMSE of 6.25, demonstrating high counting accuracy and robustness. The proposed model requires only 0.67 M parameters, 5.3 GFLOPs, and 1.6 MB of storage, while achieving an inference speed of 54 FPS. Compared to YOLOv11n, FEWheat-YOLO improved AP@50, AP_s, AP_m, AP_l, and AR by 0.53%, 0.7%, 0.7%, 0.4%, and 0.3%, respectively, while reducing parameters by 74%, computation by 15.9%, and model size by 69.2%. These results indicate that FEWheat-YOLO provides an effective balance between detection accuracy, counting performance, and model efficiency, offering strong potential for real-time agricultural applications on resource-limited platforms. Full article

This study predicts sedimentary architectures and facies distribution within the Pliocene prograding prism of the Roussillon Basin (Gulf of Lion, France), developed along an onshore–offshore continuum. Boreholes and outcrops provide facies-scale observations onshore, while seismic data capture basin-scale structures offshore. Forward seismic modeling bridges spatial and scale gaps between these datasets, yielding characteristic synthetic seismic signatures for the sedimentary facies associations observed onshore, used as analogs for offshore deposits. These signatures are then identified in offshore seismic data, allowing seismic profiles to be populated with sedimentary facies without a well tie. Predicted offshore architectures are consistent with shoreline trajectories and facies successions observed onshore. The Roussillon prism records passive margin reconstruction in the Mediterranean Basin following the Messinian Salinity Crisis, through the following three successive depositional profiles marking the onset of infilling: (1) Gilbert deltas, (2) wave- and storm-reworked fan deltas, and (3) a wave-dominated delta. Offshore, transitions in clinoform type modify sedimentary architectures, influenced by inherited Messinian paleotopography. This autogenic control generates spatial variability in accommodation, driving changes in depositional style. Overall, this multi-scale and integrative approach provides a robust framework for predicting offshore sedimentary architectures and can be applied to other deltaic settings with limited land–sea data continuity. Full article

In this study, I expand on the Black feminist tradition of rethinking Black women’s activism by examining how Black queer women’s fashion shows challenge traditional definitions and sites of activism. I present BlaQueer Style as an interpretive framework that largely draws on the wisdom and theories of Black feminism to undercover how these productions and the politics that shape them are not only sites of activism because they challenge the conventions of mainstream cultural institutions, but because they make space for the social and personal transformation of the communities they center. In this analysis of two public LGBTQ+ fashion shows, I argue that intention aside, the Black queer women founders and fashion workers and their practices and performances of centering marginalized communities, using the body to signal and subvert controlling images, and building coalition among these communities, highlight the liberatory potential of their fashion work. In a time when Black queer and trans people are experiencing misrepresentation and other forms of violence globally, BlaQueer Style is what I name the politics that presents a deep commitment to both the aesthetics and the liberation of these communities in Black queer women’s fashion work. Full article

Urban school environments often face significant thermal discomfort due to extensive paved surfaces, limited vegetation, and outdated building designs. This study examines how green spaces can mitigate temperature extremes and improve thermal comfort at two secondary schools in Coimbra, Portugal: Escola Secundária José Falcão (ESJF) and Escola Secundária D. Dinis (ESDD). Using a mixed-methods approach that combined school community surveys with on-site microclimatic measurements, we integrated user feedback on comfort with data on temperature and humidity variations across different indoor and outdoor spaces. Results revealed that tree-shaded areas consistently maintained lower air temperatures and higher relative humidity than unshaded zones, which experienced intense heat accumulation—up to a 5 °C difference. At ESJF, the older infrastructure and large asphalt surfaces led to severe heat retention, with east-facing classrooms recording the highest indoor temperatures. ESDD’s pavilion-style layout and existing green spaces provided comparatively better thermal conditions, although insufficient vegetation maintenance and limited shade reduced their effectiveness. The findings demonstrate a clear correspondence between the school community’s perceptions of thermal comfort and the measured microclimatic data. Vegetation—particularly deciduous trees—plays a critical role in cooling the school microclimate through shading and evapotranspiration. Strategic interventions such as expanding tree cover in high-exposure areas, installing green roofs and walls, and carefully selecting species can significantly reduce temperature extremes and improve outdoor usability. In addition, fostering environmental education and participatory co-design programs can encourage sustainable behaviors within the school community, underlining the importance of inclusive, nature-based solutions for climate adaptation. This research highlights that integrating green infrastructure in school design and management is a cost-effective strategy for thermal regulation. Green spaces, when co-designed with community involvement, not only enhance climate resilience and student well-being but also contribute to broader sustainable urban development goals. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its progressive form, metabolic dysfunction-associated steatohepatitis (MASH), have become the leading causes of chronic liver disease worldwide, with increasing rates of cirrhosis, hepatocellular carcinoma, and cardiovascular complications. Pathogenesis involves a complex interplay of dietary excess, sedentary lifestyle, insulin resistance, adipose tissue dysfunction, and alterations in the gut microbiome, which collectively lead to hepatocellular stress, inflammation, and fibrogenesis. Despite ongoing advances in pharmacotherapy, lifestyle intervention remains the cornerstone of management. Evidence shows that sustained weight loss of ≥5% reduces hepatic steatosis, ≥7% improves necroinflammation, and ≥10% stabilizes or reverses fibrosis. Dietary strategies, including Mediterranean-style patterns, high-protein approaches, and intermittent fasting, have been shown to be effective in improving insulin sensitivity and reducing intrahepatic triglycerides. Exercise interventions, focusing on both aerobic fitness and resistance training, enhance metabolic flexibility and combat sarcopenia, thereby improving hepatic and systemic outcomes. Equally important are behavioral support, digital health tools, and multidisciplinary approaches that enhance adherence and address barriers such as socioeconomic disparities, limited access, and patient engagement issues. Personalized nutrition plans, integrating physical activity, and ongoing support for behavioral change are essential for long-term disease management. This review synthesizes current evidence on the roles of macronutrients, micronutrients, dietary quality, physical activity, and adjunctive behavioral strategies in managing MASLD. By translating mechanistic insights into practical, evidence-based recommendations, we aim to provide clinicians, dietitians, and exercise professionals with effective frameworks to slow disease progression and improve outcomes across diverse patient populations. Full article

Manual pixel-level annotation remains a major bottleneck in deploying deep learning models for dense prediction and semantic segmentation tasks across domains. This challenge is especially pronounced in applications involving fine-scale structures, such as cracks in infrastructure or lesions in medical imaging, where annotations are time-consuming, expensive, and subject to inter-observer variability. To address these challenges, this work proposes a weakly supervised and annotation-efficient segmentation framework that integrates sparse bounding-box annotations with a limited subset of strong (pixel-level) labels to train robust segmentation models. The fundamental element of the framework is a lightweight Bounding Box Encoder that converts weak annotations into multi-scale attention maps. These maps guide a ConvNeXt-Base encoder, and a lightweight U-Net–style convolutional neural network (CNN) decoder—using nearest-neighbor upsampling and skip connections—reconstructs the final segmentation mask. This design enables the model to focus on semantically relevant regions without relying on full supervision, drastically reducing annotation cost while maintaining high accuracy. We validate our framework on two distinct domains, road crack detection and skin cancer segmentation, demonstrating that it achieves performance comparable to fully supervised segmentation models using only 10–20% of strong annotations. Given the ability of the proposed framework to generalize across varied visual contexts, it has strong potential as a general annotation-efficient segmentation tool for domains where strong labeling is costly or infeasible. Full article

Although laboratory testing to assess aerobic capacity has been a ‘gold standard’ in sports science, its high costs and time-consuming protocols may not be feasible for monitoring and tracking progress in limited conditions. In dancesport athletes, several field-based aerobic tests have been proposed, but the majority of them have been developed for ballet or contemporary dancers at the individual level, while the data among dance couples engaging in standard dance styles is lacking. Therefore, the main purpose of this study was to validate a newly developed Ballroom Aerobic Test (BAT) protocol against objective methods. Twelve standard dancesport couples (age: 20.4 ± 3.9 years; height: 172.1 ± 8.7 cm; weight: 60.1 ± 9.4 kg) with 8.2 ± 3.4 years of training and competing experience participated in this study. Ventilatory and metabolic parameters were generated using the MetaMax^® 3B portable gas analyzer (the BAT), while the KF1 (an increase in speed by 0.5 km * h⁻¹ by every minute) and Bruce protocols were followed in laboratory-based settings on the running ergometer. Large to very large correlations were obtained between the BAT and KF1/Bruce protocols for the absolute maximal oxygen uptake (VO₂max; r = 0.88 and 0.87) and relative VO₂max (r = 0.88 and 0.85), respiratory exchange ratio (RER; r = 0.78 and 0.76), expiratory ventilation (VE; r = 0.86 and 0.79), tidal volume (VT; r = 0.75; 95% CI = 0.57–0.87; p < 0.001), ventilatory equivalent for O₂ (VE/VO₂; r = 0.81 and 0.80) and CO₂ (VE/VCO₂; r = 0.78 and 0.82), and dead space (VD/VT; r = 0.70 and 0.74). The Bland–Altman plots indicated no systematic and proportional biases between the BAT and KF1 protocols (standard error of estimate; SEE = ± 3.36 mL * kg⁻¹ * min⁻¹) and the BAT and Bruce protocols (SEE = ± 3.75 mL * kg⁻¹ * min⁻¹). This study shows that the BAT exhibits satisfactory agreement properties against objective methods and is a valid dance protocol to accurately estimate aerobic capacity in dancesport athletes participating in standard dance styles. Full article