Search Results (3,368)

Background/Objectives: This study aimed to describe how adolescents with attention-deficit/hyperactivity disorder (ADHD) perceive their diagnosis identity and examine its correlation with executive functions (EFs), self-management abilities, and quality of life (QoL). Methods: A total of 66 adolescents with ADHD, aged 12 to 18 years (M = 15.21, SD = 1.84), completed self-report questionnaires, including the Illness Identity Questionnaire, Behavior Rating Inventory of Executive Function, Self-Control and Self-Management Scale, and Pediatric QoL Inventory. We used ANOVA with Bonferroni post hoc tests to assess differences in diagnosis identity domains and Pearson correlations to examine correlations between diagnosis identity, EFs, self-management, and QoL. Results: Adolescents reported significantly higher ADHD Acceptance feelings compared to Rejection, Engulfment, and Enrichment, F (2.38, 149.89) = 32.41, p < 0.001. Total diagnosis identity score was strongly associated with self-management (r = 0.61, p < 0.001). While no significant correlations were found with overall EF or QoL, significant associations did emerge with their sub-scores. Regression analyses indicated that self-monitoring, social QoL, and self-evaluation together explained 45% of the variance in diagnosis identity. The Engulfment dimension of identity was a significant negative predictor of executive functioning (R² = 0.15), self-management (R² = 0.35), and QoL (R² = 0.17). Conclusions: Promoting a positive diagnosis identity may improve functional and emotional outcomes in adolescents with ADHD. In turn, better functional and emotional outcomes may help them embrace a diagnosis identity that is more positive. Full article

The Two-Measure Theory (TMT) has been developing since 1998 and has yielded a number of highly interesting results, including those not realized in traditional field theory models. The most important advantage of TMT as an alternative theory is that, under the conditions under which all classical tests of general relativity are performed, TMT models are able to accurately reproduce Einstein’s general relativity. Despite this, TMT is still often perceived as something too exotic to be relevant to reality. In fact, the fundamental idea underlying TMT seems undeniable: if we truly believe in the effectiveness of mathematics in studying nature, we must agree that there must be a correspondence between the fundamental laws of nature and the structure of the mathematical apparatus necessary to adequately describe them. It then turns out that there is no reason to ignore the volume measure existing on the differentiable manifold on which the theory of gravity and matter fields is built. This idea has far-reaching implications. The goals of this paper are (1) to provide a clear mathematical and conceptual justification for TMT and (2) to collect in a single article some of the main results of TMT obtained over the past 25 years. Full article

Background: Stress urinary incontinence (SUI) is the involuntary loss of urine during increased abdominal pressure, affecting 46% of adult women, particularly those over 40. Pelvic floor muscle (PFM) training is the first-line treatment supported by numerous high-quality studies. However, the effectiveness of biofeedback devices, such as vaginal weight cones, remains controversial. Peflex weights are a new type of vaginal extracorporeal weights developed for PFM training. Aims: To evaluate the effectiveness of PFM training with Peflex weights in reducing SUI symptoms, improving muscle power and endurance, and comparing its efficacy to standard PFM training without weights. Methods: A pilot randomized controlled trial was conducted involving 35 women aged 18 to 50 diagnosed with SUI. Participants were randomly assigned to either the Peflex group (PFM training with Peflex weights) or the control group (PFM training without weights). Both groups engaged in six weeks of home-based training. The primary outcome was assessed using the self-reported International Consultation on Incontinence Questionnaire-Short Form (ICIQ-UI-SF). Secondary outcomes included evaluations based on the PERFECT scheme, perineometer measurements, and levator hiatus diameters obtained via ultrasound. Results: In the intragroup analysis, the Peflex group significantly improved all outcome measurements. Compared to the control group, the Peflex group demonstrated significantly higher improvement in muscle power and repetition of muscle contraction (p = 0.015 and p = 0.007, respectively), as well as in the proportional change in levator hiatus contraction (p = 0.022). There was no significant difference in the improvement in ICIQ-UI-SF and perineometer measurements between the groups (p > 0.05). Additionally, there was a trend of higher satisfaction with the treatment in the Peflex group (p = 0.054). Conclusions: Peflex weights effectively reduce SUI symptoms and improve muscle power and endurance, with high user satisfaction. However, there was no significant difference in the main outcome measure (ICIQ-UI-SF) between the Peflex and control groups. Further research is needed to identify which patients benefit most from this treatment. Full article

This study investigates the volatility of the Israeli corporate bond market, where corporate bonds are traded on a Limit Order Book (LOB) exchange with high retail trading activity. Using data from the Tel-Bond 20 and Tel-Bond 60 indices, we estimate various asymmetric GARCH models to capture the dynamics of bond returns. Our findings highlight a leverage effect, where negative shocks have a more significant impact on volatility than positive shocks, underscoring the importance of investor sentiment. The GJR model with a Student’s t-distribution best captures serial correlation, persistence of conditional volatility, and asymmetric volatility clustering. These results have significant implications for risk management, portfolio allocation, and regulatory policies, emphasizing the need for robust volatility forecasting models in transparent and active corporate bond markets. Full article

Weeding in melon and watermelon fields requires selective and pinpoint operation because the crop plants are sensitive to herbicides and tend to grow on the ground in all directions. Hyperspectral images have high spectral and spatial resolution, enabling an object’s classification according to its spectral properties. Spectral band selection is a common practice with hyperspectral images, as it reduces the number of bands in use with only a minor effect on the results. This study’s innovative contribution is the development and validation of a practical methodology to simplify complex hyperspectral data for real-world robotic weed management. This includes the introduction of the ‘normalized crop sample index’ (NCSI) to guide band selection and the use of machine learning methods, which revealed a set of four spectral bands—480 nm, 550 nm, 686 nm and 750 nm—that hold sufficient discriminating information between weeds and watermelon crop. This minimal set of bands enables the simulation and future development of a low-cost, high-speed multispectral camera system. An XGBoost model showed the lowest misclassification error level of 2–14%. The selected spectral bands were used to extract single-band images from the hyperspectral cube. In these images, vegetation pixels were separated using a normalized difference vegetation index filter, and each pixel was classified into a crop or weed class. The classified pixels were grouped into segmented objects, and weeding points were selected, suitable for robotic pinpoint operation. Full article

Biobutanol can be obtained by fermentation of microorganisms and used as biofuel. The membrane separation is energetically favorable. The incorporation of butanol into syndiotactic polystyrene (sPS) with crystalline nanopores was investigated as a function of the butanol uptake temperature using infrared spectroscopy. The OH stretching modes at 3596 and 3300 cm⁻¹, corresponding to hydrogen-bonded butanol in the crystalline cavity and free butanol in the amorphous region, respectively, were employed for analysis. Upon immersion of the sPS film in butanol, butanol molecules were absorbed in the crystalline nanocavities and amorphous phase. Diffusion increased with the uptake temperature in both regions. This can be associated with the larger molecular mobility of butanol molecules at high temperatures, facilitating contact between the film surface and the butanol molecules. The number of butanol molecules incorporated into the crystalline cavity was estimated using Lambert-Beer’s law. On average 90% of the nanopore cavities were occupied by butanol, while the remaining 10% were empty. Full article

We revisit the constraint proposed by T. Appelquist, A. G. Cohen, and M. Schmaltz (ACS) on asymptotically free field theories, which relates the number of infrared (IR) degrees of freedom to those in the ultraviolet (UV). The original ACS analysis examined several examples—both supersymmetric and non-supersymmetric—and identified only one interacting IR fixed point with a superpotential: Seiberg dual of an $SU\left(N_c\right)$ gauge theory. Here, we extend their analysis to $SO\left(N_c\right)$ and $Sp\left(2N_c\right)$ gauge groups near Banks–Zaks fixed points. We further test the ACS inequality in theories featuring conjectured accidental IR symmetries and nontrivial superpotential deformations. Beginning with ADE-type deformations, we then investigate three chiral theories by estimating decoupled chiral-ring invariants using a-maximization and unitarity bounds. In all cases, we find no violation of the ACS conjecture. Full article

Inverse Synthetic Aperture Radar (ISAR) plays a vital role in the high-resolution imaging of marine targets, particularly under non-cooperative scenarios. However, resolution degradation due to limited observation angles and marine clutter such as wave-induced disturbances remains a major challenge. In this work, we propose a novel deep learning-based framework to enhance ISAR resolution in the presence of marine clutter and additive Gaussian noise, which performs direct restoration in the ISAR image domain after an IFFT2 back projection. Under small aspect sweeps with coarse range alignment, the network implicitly compensates for residual defocus and cross-range blur, while suppressing clutter and noise, to recover high-resolution complex ISAR images. Our approach leverages a residual neural network trained to learn a non-linear mapping between low-resolution and high-resolution ISAR images. The network is designed to preserve both magnitude and phase components, thereby maintaining the physical integrity of radar returns. Extensive simulations on synthetic marine vessel data demonstrate significant improvements in cross-range, outperforming conventional sparsity-driven methods. The proposed method also exhibits robust performance under conditions of low signal-to-noise ratio (SNR) and signal-to-wave ratio (SWR), effectively recovering weak scatterers and suppressing false artifacts. This work establishes a promising direction for data-driven ISAR image enhancement in noisy and cluttered maritime environments with minimal pre-processing. Full article

Beer consumption behaviors within China exhibited significant regional heterogeneity. To elucidate the specific differences in beer consumer behaviors across different regions and their influencing factors, this study systematically analyzed the sensory preference characteristics of consumers in the Chinese beer market based on machine learning methods, and further revealed the core driving mechanisms influencing their consumption behaviors. By integrating consumer data from different regions, a comprehensive dataset was constructed encompassing sensory attribute evaluations (bitterness, malt flavor, hop aroma, smoothness of mouthfeel, foam characteristics, etc.) and other dimensional consumption behavior variables (brand, beer packaging, etc.). Utilizing an ensemble learning framework (LightGBM), Support Vector Machine (SVM), and decision tree models for feature mining, the study identified important factors influencing the consumption behaviors of Chinese beer consumers. Specifically, consumers in mature and upgrading markets placed greater emphasis on the overall drinking experience and drinkability when purchasing beer, whereas consumers in scale-dominant and mainstream competitive markets considered foam persistence, fineness, and light brown color as core quality indicators. Conversely, consumers in potential growth and emerging cultivation markets demonstrated strong brand orientation. This indicated that the factors influencing beer consumption behaviors varied significantly across regions. Through a data-driven paradigm, this study revealed the underlying regional mechanisms behind consumption decisions in different regional beer markets in China, providing a theoretical foundation and empirical support for cross-regional product customization, precision marketing, and resource optimization. Full article

The aim of our study is to investigate the factors that drive craft beer consumption choices in Italy. To this end, we simultaneously analyze purchase intentions and actual craft beer consumption. The theoretical approach took into account the main doctrinal frameworks, particularly those most widely used in marketing studies. Through PLS-SEM analysis (partial least squares structural equation modeling), we examine how consumption habits, liking, appeal, territorial identities, and perceived quality shape intentions and also the actual behavior of Italian consumers towards craft beer. The results highlight how attractiveness and interest in the craft beer phenomenon, lifestyle, and curiosity for new flavors and aromas demonstrate an openness to craft beer and a new cultural identity among consumers. In many cases, respondents stated that they wanted to support local craft breweries and the local economy. Consumer trust in agri-food products is closely linked to their perception of authenticity and compliance with quality and safety standards. A better understanding of these aspects could help everyone involved in the entire supply chain implement more effective and targeted campaigns. Full article

Beer consumption patterns are evolving, with gluten-free beers (GFBs) and low- and no-alcohol beers (NABLABs) exhibiting continuous growth, underpinned by health-conscious consumers, younger generations’ preference for moderate drinking, and a rising awareness of gluten intolerance. This study investigates whether online search behaviour reflects these market changes and anticipates future consumption trends. A combined methodological framework was applied, integrating time-series analysis of Google Trends data—based on a decomposition model with a five-year forecast—with descriptive and semantic insights from Search Engine Optimisation (SEO) techniques using the specialised SEOZoom platform. The statistical decomposition enabled the identification of long-term trends, cyclical variations, and seasonal patterns in user interest. Italy was selected as a case study, representing a market where these niche segments have grown considerably despite a traditionally limited craft beer culture. The results reveal a steady rise in online interest in both GFB and NABLAB; GFB searches are primarily linked to health and dietary concerns, whilst NABLAB queries encompass a broader set of topics, including physiology, legislation, and consumption contexts. The forecasts confirm the persistence of this positive trend over the next five years. The approach demonstrates the potential of integrating digital and statistical tools to monitor emerging consumption dynamics and guide strategic decisions in the beverage sector. Full article

Background/Objectives: This study reports pilot-scale production of gluten-free rice malt extract powder from Thai Chainat 1 rice as a sustainable alternative to barley malt extract. Methods: The process combined controlled malting with sequential enzymatic hydrolysis, optimized through bench-scale validation and scaled up to a 1500 L pilot system. Results: The resulting powder was rich in fermentable sugars (maltose 43.9 g/100 g, glucose 14.3 g/100 g), protein (5.2 g/100 g), γ-aminobutyric acid (GABA, 245.2 mg/100 g), and thiamine (0.64 mg/100 g), while free of detectable gluten, aflatoxins, and heavy metals. Microbiological quality met international safety standards. Shelf-life studies under ambient and accelerated conditions demonstrated chemical stability and bioactive retention for up to three years in laminated and HDPE packaging. Application trials confirmed that the rice malt extract powder supported yeast, bacterial, and mold growth comparably to commercial malt extract in culture media, with optimized yeast–mold agar formulations enabling direct substitution without supplementary glucose. The powder was further applied to a gluten-free malt beverage, yielding a beer-like product with acceptable physicochemical and nutritional quality, though residual alcohol levels exceeded the non-alcoholic threshold and required process optimization. Conclusions: Rice malt extract powder represents a safe, functional ingredient suitable for food, beverage, and industrial microbiology applications, offering opportunities to reduce import dependency and advance gluten-free innovation in emerging markets. Full article

Brewer’s spent grain (BSG), the main lignocellulosic by-product of the beer industry, represents an abundant yet underutilized resource with high potential for valorization. This study presents an integrated biorefinery approach to convert BSG into second-generation (2G) ethanol, bioactive vinasse for plant growth promotion, and fungal biomass as a potential mycoprotein source. The biomass was first subjected to biological delignification using the white-rot fungus Ganoderma lucidum, after which two valorization routes were explored: (i) evaluation of the fungal biomass as a mycoprotein candidate and (ii) alcoholic fermentation for ethanol production. For the latter, three pretreatment strategies were assessed (diluted sulfuric acid and two deep eutectic solvents (DESs) based on choline chloride combined with either glycerol or lactic acid) followed by a one-pot enzymatic saccharification and fermentation using Kluyveromyces marxianus SLP1. The highest ethanol yield on substrate (Y_P/S) was achieved with [Ch]Cl:lactic acid pretreatment (0.46 g/g, 89.32% of theoretical). Vinasse, recovered after distillation, was characterized for organic acid content and tested on Solanum lycopersicum seed germination, showing promising biostimulant activity. Overall, this work highlights the potential of BSG as a sustainable feedstock within circular economy models, enabling the production of multiple bio-based products from a single residue. Full article

Background/Objectives: Seasonal variation in hemoglobin A1c (HbA1c) values has been previously documented, with physical activity (PA) and macronutrient intake (MNI) suggested as potential drivers. This study combines seasonal mean HbA1c values from the Dutch (pre)diabetes population with national survey data on PA and MNI from 2018 to 2021 to identify key associations. Methods: HbA1c data were collected from 24 laboratory organizations in the Netherlands and Dutch Caribbean. MNI and total energy intake data were extracted from the Dutch National Food Consumption Survey, while PA data came from the Dutch National Sports Participation Index Survey. Weighting factors were applied to align PA and MNI data with HbA1c data. Seasonal averages were analyzed for significant differences, and a prediction model compared PA and MNI with actual HbA1c values. Results: Among 5,635,920 HbA1c results, the average HbA1c increased by 0.71 mmol/mol (NGSP 0.06%) over four years, with an overall mean of 52.4 mmol/mol (NGSP 7.0%). Seasonal HbA1c variation showed a dip in summer–autumn and a peak in winter–spring (1.2 mmol/mol; NGSP 0.11%; p < 0.0001). MNI, except for total energy intake (which peaked in summer; p < 0.001), showed no significant trends or association with HbA1c (p = 0.157). PA decreased by 7.2% over the study period, with seasonal peaks in summer–autumn, showing an inverse relationship with HbA1c (p < 0.0001). During the COVID-19 lockdowns, PA significantly decreased, and mean HbA1c values increased more markedly than in previous years. The prediction model confirmed PA as a significant driver of seasonal HbA1c variation (p = 0.004). Conclusions: These findings suggest that PA is the strongest driver of seasonal variation in HbA1c. Public health initiatives and support programs promoting physical activity are essential for improving HbA1c regulation. Full article

Cigarette smoking is known to be an unhealthy activity that can cause a number of human diseases, including chronic obstructive pulmonary disease (COPD) and lung cancer. It was further reported that even being exposed to secondhand cigarette smoke can affect human health. To assess the toxicity of the smoke from different cigarette brands, an artificial smoking device was developed, and three fractions designated, Filter Fraction, Smoke Fraction and Tar Fraction, were prepared from the smoke of each brand. Then, to elucidate possible effects of some of the toxins found in cigarette smoke, we investigated their effects in vitro using a bioluminescent bacterial array that comprises three bacterial strains. Using this array, we compare smoke from three cigarette brands, each with different tar and nicotine contents. GC-MS analysis showed that the cigarette smoke extracts (fractions) from different brands differed in their compositions and chemical concentrations. The results further showed that, in general, cigarette smoke triggered mainly an oxidative stress reaction in our bacterial models. The Smoke Fraction was tested for sequential smoking rounds and found to produce cumulative effects following each subsequent smoking cycle for all three cigarette brands. Finally, it was found that cigarette smoke and its specific components are toxic at various degrees with the Smoke Fraction, acting as oxidative stressors, and that this can be effectively analyzed using bioreporter panel arrays. Full article