Search Results (794)

We develop a four-dimensional nonlinear model of a reflexive financial system by extending the Xin–Zhang system with a self-reinforcing sentiment channel. The model comprises four interacting variables—interest rate, investment demand, price index, and market confidence—and incorporates reflexivity to capture feedback between economic fundamentals and investor sentiment. A Lyapunov function shows that the system is well-posed and dissipative, ensuring bounded trajectories. We then analyse the dynamics using standard nonlinear-dynamics tools. Reflexive confidence sustains chaotic motion, inhibits convergence to equilibria, and produces irregular, aperiodic bifurcation patterns; sentiment-driven feedback destabilises a dissipative macroeconomic model and sustains volatility, as evidenced by a positive largest Lyapunov exponent and Kolmogorov–Sinai entropy greater than zero. Using U.S. monthly consumer sentiment and the S&P 500, we observe co-movement, a medium-horizon lead of sentiment, and a nonlinear persistence map $w_{t+1}=f\left(w_t\right)$—stylised facts consistent with the model’s self-reinforcing confidence channel. Full article

Achieving a decarbonized built environment in Canada requires proven, resilient, and scalable building envelope assemblies. In 2022, building operations accounted for 18% of Canada’s greenhouse gas (GHG) emissions, with space heating responsible for nearly two-thirds of this total. Alongside operational carbon reductions, embodied carbon emissions—stemming from the production and transport of building materials—must be prioritized during the design phase. Without intervention, construction materials could consume up to half of the remaining global 1.5 °C carbon budget by 2050. This paper highlights NRCan’s prototype, low-carbon, prefabricated panels filled with chopped straw and cellulose insulation under the Prefabricated Exterior Energy Retrofit (PEER) research project. The research advances confidence in performance and durability of biogenic materials by conducting controlled experiments, guarded hot box testing, and hygrothermal modelling. These panels present a promising pathway to drastically lower embodied carbon in the built environment. The validated hygrothermal model, accurate to between 3% and 7, enables assessment of hygrothermal performance across Canadian climates, retrofit scenarios and future climate conditions. This work supports the evidence for low-carbon or bio-based materials as a solution for Canada’s built environment. Full article

Introduction: Alcohol-induced headaches are one of the most prevalent types of headaches. The International Classification of Headache Disorders defined them as throbbing and bilateral, and their phenotype combines characteristics of migraines and headaches secondary to low cerebrospinal fluid pressure. We aimed to evaluate the factors associated with the presence of a headache as a hangover symptom. Methods: This was a prospective cohort study, including 32 healthy individuals who voluntarily consumed alcohol and completed self-administered questionnaires during three separate alcohol consumption and hangover episodes. Results: A headache was a hangover symptom in 55/96 (57.3%) episodes. The phenotype was predominantly holocranial (94.5%), frontal (98.2%), and pressing (67.2%), with a median intensity of 6 (IQR 4–8). Headaches worsened with physical activity (100%) and had orthostatic changes (89.1%). A prior history of headaches was associated with headache occurrence (odds ratio: 3.480; 95% confidence interval (CI): 1.084 to 11.177), and headache precipitation by standing up was associated with a shorter duration (hazard ratio: 0.257; 95% CI: 0.073 to 0.901). Conclusions: Delayed alcohol-induced headaches had a migraine-like phenotype. An orthostatic pattern suggestive of a low cerebrospinal fluid pressure was associated with a shorter duration of the headache. Full article

Objectives: Gestational diabetes mellitus (GDM), particularly when combined with overweight or obesity, is associated with adverse neonatal outcomes such as high birth weight and increased adiposity. We determined the effect of a preconception lifestyle intervention initiated before and continued throughout pregnancy on neonatal, birth-related, and body composition outcomes at birth and 6–8 weeks of age in children of participants in the BEFORE THE BEGINNING randomized controlled trial. Methods: People (N = 167) at increased risk of GDM and planning pregnancy were randomly allocated 1:1 to intervention or control. The intervention included time-restricted eating and exercise training. Time-restricted eating involved consuming all energy within ≤10 h/day, ≥5 days per week, and the amount of exercise was set using a heart rate-based physical activity metric (Personal Activity Intelligence, PAI), with the goal of ≥100 weekly PAI points. The main outcome of interest in this report was the proportion of infants with birth weight > 4.0 kg. Results: Among 106 live births, 21% (11/53) of infants in the intervention group and 28% (15/53) in the control group had birth weight > 4 kg (p = 0.367). Mean birth weight did not differ significantly between groups (mean difference −159.3 g, 95% confidence interval −375.7 to 57.2, p = 0.148). No significant between-group differences were found for additional neonatal, birth-related, or early postnatal body composition outcomes. Conclusions: In this secondary analysis, we found no evidence of effects of a preconception lifestyle intervention on the risk of macrosomia or neonatal body composition. Full article

The rapid rise of fashion resale platforms has created new pathways for sustainable consumption, yet little research has compared how different governance models, company-controlled versus seller-controlled, shape consumer trust and purchasing behavior. This study addresses that gap by applying the Stimulus–Organism–Response (SOR) framework to examine how information precision, authenticity, and risk aversion influence consumer trust and purchase intention within circular fashion markets. Drawing on an experimental design with 524 U.S. consumers randomly assigned to each platform type, multi-group structural equation modeling reveals that the three stimuli significantly enhance trust, which in turn drives purchase intention. Risk aversion exerted stronger effects in company-controlled contexts, whereas trust translated more directly into purchase intention on seller-controlled platforms. Theoretically, the research extends SOR applications to sustainability by identifying trust as the psychological bridge linking platform design to circular consumption. Practically, it offers actionable guidance for brands and peer-to-peer platforms on authentication, information transparency, and risk-reduction strategies that strengthen consumer confidence and promote environmentally responsible resale participation. The findings advance understanding of how governance structures can accelerate sustainable fashion retailing and contribute to the circular economy. Full article

The transmission of Escherichia coli through contaminated fruits and vegetables poses serious public health risks and has led to several national outbreaks in the USA. To enhance food safety, rapid and reliable detection of E. coli on produce is essential. This study evaluated the performance of the CSI-D+ system combined with deep learning for detecting varying concentrations of E. coli on citrus and spinach leaves. Eight levels of E. coli contamination, ranging from 0 to 10⁸ colony-forming units (CFU)/mL, were inoculated onto the leaf surfaces. For each concentration level, 10 droplets were applied to 8 citrus and 12 spinach leaf samples (2 cm in diameter), and fluorescence images were captured. The images were then subdivided into quadrants, and several post-processing operations were applied to generate the final dataset, ensuring that each sample contained at least 2–3 droplets. Using this dataset, multiple deep learning (DL) models, including EfficientNetB7, ConvNeXtBase, and five YOLO11 variants (n, s, m, l, x), were trained to classify E. coli concentration levels. Additionally, Eigen-CAM heatmaps were used to visualize the spatial responses of the models to bacterial presence. All YOLO11 models outperformed EfficientNetB7 and ConvNeXtBase. In particular, YOLO11s-cls was identified as the best-performing model, achieving average validation accuracies of 88.43% (citrus) and 92.03% (spinach), and average test accuracies of 85.93% (citrus) and 92.00% (spinach) at a 0.5 confidence threshold. This model demonstrated an inference speed of 0.011 s per image with a size of 11 MB. These findings indicate that fluorescence-based imaging combined with deep learning for rapid E. coli detection could support timely interventions to prevent contaminated produce from reaching consumers. Full article

Background: Energy drink [ED] consumption is common among young adults and has been linked to adverse health effects and risky behaviors. This study compared medical and non-medical university students to assess whether health education influences knowledge, consumption, and attitudes toward EDs. Although medical and non-medical students are not minors, their opinions on the national ban on EDs sales to individuals under 18 provide valuable insight into attitudes toward regulation. Material and Methods: A cross-sectional online survey was conducted among 871 students (42.1% medical, 57.9% non-medical). The questionnaire assessed demographics, ED consumption, knowledge, motivations, and regulatory attitudes. It was pilot-tested on 30 students to ensure clarity, and internal consistency was confirmed (Cronbach’s α = 0.78 for knowledge; α = 0.81 for attitudes). Non-parametric tests (Mann–Whitney U, Kruskal–Wallis) and chi-square analyses compared groups. Results: Participants’ mean age was 22.1 years; most were female (73.2%). Medical students demonstrated significantly better knowledge of ED ingredients (simple sugars, B vitamins, L-carnitine, electrolytes; p < 0.01) and adverse effects (e.g., irritability, dizziness, nausea; p < 0.05). However, ED consumption frequency did not differ between medical and non-medical students. The main reasons for ED use were energy and concentration; social motives were less frequent. Female students more often supported the ban on ED sales to minors and additional advertising restrictions (p < 0.001), while overall confidence in enforcement was low. Conclusions: Despite greater awareness, medical students consume EDs at rates comparable to non-medical students. Educating medical students on safe caffeine use is crucial, since shift work may promote stimulant intake. Combining targeted education with stronger enforcement could enhance the impact of regulatory policies and reduce risky consumption among young adults. Full article

Background: Green tea (Camellia sinensis) has been consumed for centuries, and its beneficial effects on human health have been studied in recent decades. l-theanine, an active ingredient in green tea, has been used to improve cognition and mood. Although the effects of l-theanine on cognition have been investigated in clinical trials that have reported various results, these studies have not yet been critically evaluated in meta-analyses. Objectives: Our objective was to systematically evaluate the efficacy of l-theanine on cognitive functions compared to a placebo, in a meta-analysis based on randomized controlled trials (RCTs). Methods: PubMed, the Cochrane Central Register of Controlled Trials, Embase and Web of Science were searched for relevant studies until 31 July 2024 and registered in PROSPERO (registration number: CRD42024575122). Placebo-controlled clinical trials investigating the efficacy of l-theanine in healthy adults were included. Conference abstracts, study protocols and reports of non-RCTs were excluded. For risk of bias assessment, the Cochrane Risk of Bias Tool (version 2.0) was used. A random effects model was applied to conduct the meta-analysis. Mean differences (MD) with 95% confidence intervals (CIs) were calculated. Results: Based on the included five RCTs involving 148 healthy adults, l-theanine had a dose-dependent effect on cognitive function based on rapid visual information processing and recognition visual reaction time (MD: −15.20 ms; 95%-CI [−28.99; −1.41]). The effects of l-theanine were non-significant on reaction time to a simple stimulus (MD: −0.46 ms; 95% [CI: −15.65; 14.73]) and in the Stroop test (MD: −37.38 ms; 95%-CI [−86.39; 11.62]). Conclusions: The beneficial effects of l-theanine on cognitive performance could not be confirmed by all test methods. The contradictory results could be explained by the fact that l-theanine only affects certain cognitive domains, but also by the low number of trials and the heterogeneity of the test preparations. Further trials using standardized products with larger sample sizes are required for the accurate assessment of efficacy. Full article

The heavy environmental impact of the construction industry—responsible for 39% of world CO₂ emissions and consuming over 40% of natural resources—supports the need for evidence-based decision-making tools for sustainable material selection balancing environmental, economic, and social considerations. This research develops and evaluates an integrated decision support system that couples cradle-to-grave lifecycle assessment (LCA) with various multi-criteria decision-making (MCDM) methods to optimize climate-resilient material selection for schools. The methodology is an integration of hybrid Analytic Hierarchy Process–Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) and VIKOR techniques validated with eight case studies in hot-arid, hot-humid, and temperate climates. Environmental, economic, social, and technical performance indices were evaluated from primary experimental data and with the input from 22 international experts with climate change assessment expertise. Ten material options were examined, from traditional, recycled, and bio-based to advanced composite systems throughout full building lifecycles. The results indicate geopolymer–biofiber composite systems achieve 42% reduced lifecycle carbon emissions, 28% lower cost of ownership, and 35% improved overall sustainability performance compared to traditional equivalents. Three MCDM techniques’ cross-validation demonstrated a satisfactory ranking correlation (Kendall’s τ = 0.87), while Monte Carlo uncertainty analysis ensured framework stability across 95% confidence ranges. Climate-adaptive weighting detected dramatic regional optimization contrasts: thermal performance maximization in tropical climates and embodied impact emphasis in temperate climates. Three case studies on educational building projects demonstrated 95.8% accuracy in validation of environmental performance and economic payback periods between 4.2 and 6.8 years in real-world practice. Full article

Increasingly, attention is being paid to the underutilised wild edible nettle plant (Urtica dioica) as a healthy and sustainable food source. However, little is known about UK consumers’ acceptance of nettles and supplements containing nettles. This study explored UK consumers’ perceptions of nettles as a food source and nettle-based powder supplements, using visual focus group methodology (i.e., creative drawing tasks and group discussion). A total of n = 34 participated in the study, with each participant engaging in one of five visual focus groups. Barriers to consumption and how consumers envisaged using nettle-based supplements were also explored. Inductive thematic analysis was used to analyse group discussions and pictures were analysed using visual content analysis drawing on the principles of content analysis, semiotics, and iconography. Findings revealed limited awareness amongst consumers about nettles as a food source, with sensory properties and prior experiences negatively affecting perceptions of nettle consumption. Concerns over processing and the inclusion of carrier ingredients reduced consumer trust in a nettle powder supplement viewing these as ‘ultra-processed’ and unhealthy. A preference for natural additional ingredients was revealed, potentially signalling an opportunity to engage and educate consumers around sustainable eating. Transparency in labelling information may improve consumer confidence and trust in nettle powder supplements. Full article

Accurate inflation forecasting is of central importance for monetary authorities, governments, and businesses, as it shapes economic decisions and policy responses. While most studies focus on headline inflation, this paper analyses the Harmonised Index of Consumer Prices (HICP) and its 12 subcomponents in the euro area over the period 2000–2023, covering episodes of financial crisis, economic stability, and recent inflationary shocks. We apply a broad set of machine learning and deep learning models, systematically optimized through grid search, and evaluate their performance using the Normalized Mean Absolute Error (NMAE). To complement traditional accuracy measures, we introduce the Forecastability Index (FI) and the Interquartile Range (IQR), which jointly capture both the difficulty and robustness of forecasts. Our results show that RNN and LSTM architectures consistently outperform traditional approaches such as SVR and RFR, particularly in volatile environments. Subcomponents such as Health and Education proved easier to forecast, while Recreation and culture and Restaurants and hotels were among the most challenging. The findings demonstrate that macroeconomic stability enhances forecasting accuracy, whereas crises amplify errors and inter-model dispersion. By highlighting the heterogeneous predictability of inflation subcomponents, this study provides novel insights with strong policy relevance, showing which categories can be forecast with greater confidence and where uncertainty requires more cautious intervention. Full article

Meat juice leakage is a natural phenomenon, evident in culinary meat packaging, and is a key indicator of meat quality. This study aimed to evaluate the amount of meat juice leakage into the packaging during culinary pork, beef, and chicken storage in a refrigerated display case simulating retail conditions (2–4 °C, 12 days). The study included 1800 high-quality culinary meat samples, i.e., free of technological defects, packaged in vacuum (VAC) and modified atmosphere (MAP), with and without absorbent pads, obtained from meat processing plants. On the 12th day of storage, the leakage was determined in the meat portions using the gravimetric method, and pH and color (CIEL*a*b*) were measured using instrumental methods. It was found that the leakage level from culinary meat ranged from 2.10% for pork shoulder VAC to 10.70% for pork loin VAC, in slices, being influenced (p < 0.01) by each grouping factor: meat type, meat cut, and package type. Regardless of the packaging method, culinary chicken meat had a lower pH (p < 0.001) than pork and beef. The study also found significant negative correlations between pH and leakage in most culinary meat cuts, as shown by the results for ham VAC (r = −0.66), ham MAP (r = −0.59), and heel of round MAP (r = −0.50). Among meat color parameters, the most significant variability was observed for lightness (L*), whose mean value differed significantly depending on the type of meat (p < 0.001) and the meat cut (p < 0.001), and within the same culinary cut—except beef tenderloin and chicken breast fillet–also depending on the type of packaging (p < 0.05). Based on the results obtained in this study, covering a large number of culinary meat samples, it was suggested that recommended leakage levels, i.e., those that raise no concerns regarding meat quality, could range from 2% for shoulder and pork neck (both VAC) to just over 10% for tenderloin slices (packaged using the MAP and VAC methods). Our findings can be used by both meat producers and quality control authorities to monitor the quality of culinary meat, e.g., they may help determine maximum permissible leakage levels and design meat packaging methods to reduce leakage. Ultimately, these measures will enhance consumer confidence in meat production and quality. Additionally, the results systematize knowledge on meat leakage, providing valuable insights for scientists who support producers and retailers in their efforts to minimize this issue. Full article

(1) Background: This research aims to determine the main factors that influence: (i) purchase decisions for flour and bakery products, (ii) consumer preferences, attitudes, and consumption frequency of those products, and (iii) the degree of knowledge and confidence in innovative functional food products. (2) Methods: Questionnaires were randomly distributed to 639 Greek citizens aged 18–75 years. The statistical analysis included Chi-Square, Kruskal–Walis H, and Mann–Whitney U tests, and Spearman correlations. (3) Results: Flour purchasing decisions were influenced by age, income, marital status, and education, while bakery products were widely regarded as nutritious. Women and older individuals were more knowledgeable regarding alternative flours. Trust in functional products increased with age, marital status, household minor and adult size, and income. (4) Conclusions: Several demographic characteristics may affect the purchasing decisions and attitude towards flour, bakery, and functional food products. Full article

Background/Objective: Temporal eating patterns and ultra-processed food (UPF) consumption have independently been associated with obesity and non-communicable diseases. Little is known about the temporal patterns of UPF consumption, as data is challenging to collect. Temporal data can be extracted from mobile food records (mFRs). The aim of this study was to identify the temporal eating patterns of those consuming UPFs using an mFR. Methods: A combined sample of 243 young (18–30 years) and 148 older (>30 years) adults completed a 4-day mFR. The time of eating was extracted from the mFR image metadata. UPFs were identified using the NOVA food classification system. The proportion of total energy intake (EI) from UPFs was calculated hourly. Using chi-square tests, a day-of-the-week analysis compared weekends (Friday–Sunday) with weekdays (Monday–Thursday). A multivariate logistic regression of UPF EI terciles was conducted, expressed as odds ratios and 95% confidence intervals. Results: The proportion of total EI from UPFs was significantly different between younger adults (mean ± SD = 48.8 ± 15.6%) and older adults (36.1 ± 15.1%) (p < 0.001). Age-differentiated 24 h temporal eating pattern analysis found that younger adults had two distinct UPF EI peaks, with the highest at 8 pm, followed by 1 pm. Older adults followed a more conventional three-meal pattern with an additional peak at 7 am. Weekend UPF EI was higher than on weekdays for older adults (~560 kJ, p = 0.003), with no difference for younger adults. Multivariable logistic regression found no significant associations between UPF intake terciles and demographic variables (sex, BMI, education). Conclusions: The peak UPF EI occurred at conventional mealtimes, and UPFs accounted for a substantial proportion of energy intake, especially for younger adults. The timing of UPF EI provides important information for developing public health nutrition interventions. Full article

Conventional spectrophotometric methods used for determining total phenolic content and antioxidant activity are typically time-consuming, labor-intensive, and require large amounts of reagents. In the context of sustainable development and green chemistry, minimizing the use of hazardous substances and reducing reagent consumption have become key priorities. The implementation of microplate-based methods offers significant advantages, including reduced reagent volumes and shorter analysis times compared with traditional methods. Therefore, the aim of this study was to validate the Folin–Ciocalteu and DPPH microplate methods and compare their performance with conventional protocols. The limits of detection (LOD) for the microplate methods were lower than those for the conventional approaches, being approximately 0.7 µg/mL and 4.1 µg/mL for TPC, and 0.015 µg/mL and 0.081 µg/mL for DPPH, respectively. The relative standard deviation (RSD) of repeatability and reproducibility for both microplate methods was ≤6%. The accuracy ranged from 95.0% to 97.7% for TPC and from 95.3% to 98.7% for DPPH. Overall, the results confirm that the microplate and conventional methods are statistically equivalent at the 95% confidence level, demonstrating that microplate assays represent a reliable and environmentally friendly alternative for assessing total phenolic content and antioxidant activity. Full article