Search Results (4,187)

Knowledge gaps in the context of agriculture contribute to mistrust and negative worldviews of the animal agriculture sector. The purpose of this quasi-experimental survey study was to quantify the perceived connection of participants to food production, assess their understanding, knowledge, and perceptions of animal agriculture (AA) and food production (FP), and determine predictors that may have contributed to their knowledge and perceptions of animal food production. The convenience sample for this study was a southeastern land grant institution, n = 265. An Animal Agricultural Knowledge and Perceptions Questionnaire and a Food Familiarity Index Questionnaire were included in the electronic survey. The study reported that nearly 50% of the participants showed negative perceptions of animal agriculture (p < 0.05) regardless of the food familiarity scores. Natural and self-identified demographic characteristics impacted the knowledge and perceptions of AA including gender, ethnicity, dietary preference, perceived connection to FP, and affiliation with the College of Agriculture (p < 0.05). By identifying topics and ideas that are of great concern and little understanding, future perceptions and purchase intentions can be improved. Additional research should replicate the findings with broader question pools and other demographic groups to identify areas that need improvement in agriculture communication efforts designed to dispel misinformation. Full article

Background: With the increasing popularity and diversification of cosmetic products, an expanding number of retail stores are providing in-store testers to allow consumers to try products before purchasing. However, growing concerns have been raised about microbial contamination and the associated risk of infection due to the shared use of these testers. This study aimed to investigate consumer awareness and perceived susceptibility to microbial infection associated with the use of lip cosmetic testers, and to identify major pathogenic bacteria, thereby offering evidence to support the need for improved hygiene management practices. Methods: The survey examined the use of lip cosmetic testers and related side effects, as well as perceptions of product hygiene and microbial contamination. Awareness of microbial infection and consumer sensitivity to product safety were measured using a five-point Likert scale. Microorganisms were detected through PCR analysis of genomic DNA. Results: Among 134 respondents, 95% had previously used lip cosmetic testers, and 90% recognized the potential for microbial contamination. Sensitivity to product safety was not significantly associated with sociodemographic factors. However, susceptibility to microbial infection from tester use was significantly higher among participants of older age and with higher education levels. PCR analysis of lip cosmetic testers revealed frequent detection of Staphylococcus epidermidis and Pseudomonas aeruginosa. Other detected bacteria included Streptococcus oralis, Streptococcus salivarius, Streptococcus pneumoniae, and Escherichia coli, all of which are known to cause oral and respiratory infections. Conclusions: The analysis revealed that the majority of individuals who have used lip cosmetic testers expressed a high level of concern regarding product contamination and the potential for infection. Multiple pathogenic bacteria linked to oral and respiratory diseases were identified in the opened tester products. These findings underscore the necessity of establishing regulatory guidelines for the management of lip cosmetic testers and highlight the importance of enhancing consumer awareness regarding hygiene practices. Full article

As digital media companies pursue sustainable revenue, AI-based strategies like personalized advertising and dynamic paywalls have become prevalent. These monetization models involve different forms of consumer data collection, raising distinct privacy concerns. This study investigates how digital news users perceive privacy trade-offs between these two AI-driven models. Based on Communication Privacy Management Theory and Privacy Calculus Theory, we conducted a survey of 336 Korean news consumers. Findings indicate that perceived control and risk significantly affect users’ willingness to disclose data. Moreover, users with different privacy orientations prefer different monetization models. Those favoring dynamic paywalls tend to be more privacy-sensitive and show a higher willingness to pay for personalized, ad-free content. While personalization benefits are broadly acknowledged, the effectiveness of privacy control mechanisms remains limited. These insights highlight the importance of ethical, user-centered AI monetization strategies in journalism and contribute to theoretical discussions around algorithmic personalization and digital news consumption. Full article

Consumer demand for organic and nitrite-free meat products has stimulated the search for sustainable alternatives to synthetic curing agents. Conventional nitrites are effective in stabilizing color, inhibiting lipid oxidation, and suppressing pathogens, but their use raises health concerns due to potential nitrosamine formation. This study investigated the application of Portulaca oleracea powder as a multifunctional ingredient to fully replace sodium nitrite in organic cooked frankfurters. Two formulations were produced: control frankfurters with sodium nitrite and experimental frankfurters with purslane powder 1.2%. Physicochemical, oxidative, proteomic, and antioxidant parameters were monitored during refrigerated storage. Purslane incorporation improved the lipid profile by increasing α-linolenic acid and lowering the ω-6/ω-3 ratio, while peroxide, thiobarbituric acid reactive substances (TBARS), and acid values remained significantly lower than in nitrite-containing controls after 10 days. Protein oxidation was also reduced, and SDS-PAGE profiles confirmed that the major structural muscle proteins remained stable, indicating that purslane addition did not disrupt the core proteome. Antioxidant assays showed strong ferric-reducing antioxidant power (FRAP) activity 13.7 mg GAE/g and enhanced 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical-scavenging capacity 22.3%, highlighting purslane’s contribution to oxidative stability. Although redness (a*) was lower than in nitrite controls, overall color stability (L*, b*) remained high. Taken together, purslane enhanced oxidative stability and quality attributes of nitrite-free organic frankfurters; microbiological validation is ongoing and will be reported separately. Full article

The Personal Care Products (PCP) industry, encompassing cosmetics, hygiene, and personal care items, serves millions of consumers daily and operates under constant pressure for innovation, agility, and sustainability. Within this context, supply chains are viewed as complex and integrated systems, composed of interrelated elements whose interactions determine overall performance and are influenced by external factors. Disruptions—particularly those involving indirect suppliers—can propagate throughout the network, affecting operations, reputation, and business outcomes. Despite the importance of the topic, empirical studies that systematically identify and prioritize these risks in the PCP sector remain scarce, which motivated the conduct of this study. Thus, the aim of this research is to identify, analyze, and evaluate the main supply risks faced by the PCP industry, considering severity, occurrence, and detection capability. Methodologically, the research employed an exploratory multi-case design, carried out in three steps: a literature review to identify key supply chain risks; structured interviews with industry experts to analyze and evaluate these risks; and the application of Gray Relational Analysis (GRA) to aggregate expert judgments and construct a prioritized risk ranking. This combination of qualitative and quantitative techniques provided a detailed foundation for analyzing and interpreting the main risks in the Brazilian PCP sector. The results indicate that indirect supplier failure is the most critical risk, prioritized by 70% of the companies studied. Other significant risks include the inability to meet changes in demand, import issues, lack of supply chain visibility, natural and social disasters, and sustainability or reputational concerns. Consequently, this study contributes to a systemic understanding of risk management in the PCP industry supply chain, providing managers with a practical mapping of critical points and highlighting concrete opportunities to strengthen integration, anticipate disruptions, and enhance operational resilience and performance across the sector. Full article

Power systems are undergoing a transformative transition as consumers seek greater participation in managing electricity systems. This shift has given rise to the concept of “prosumers,” individuals who both consume and produce electricity, primarily through renewable energy sources. While renewables offer undeniable environmental benefits, they also introduce significant energy management challenges. One major concern is the variability in energy consumption patterns within households, which can lead to inefficiencies. Also, improper energy management can result in economic losses due to unbalanced energy control or inefficient systems. Home Energy Management Systems (HEMSs) have emerged as a promising solution to address these challenges. A well-designed HEMS enables users to achieve greater efficiency in managing their energy consumption, optimizing asset usage while ensuring cost savings and system reliability. This paper presents a comprehensive systematic review of optimization techniques applied to HEMS development between 2019 and 2024, focusing on key technical and computational factors influencing their advancement. The review categorizes optimization techniques into two main groups: conventional methods, emerging techniques, and machine learning methods. By analyzing recent developments, this study provides an integrated perspective on the evolving role of HEMSs in modern power systems, highlighting trends that enhance the efficiency and effectiveness of energy management in smart grids. Unifying taxonomy of HEMSs (2019–2024) and integrating mathematical, heuristic/metaheuristic, and ML/DRL approaches across horizons, controllability, and uncertainty, we assess algorithmic complexity versus tractability, benchmark comparative evidence (cost, PAR, runtime), and highlight deployment gaps (privacy, cybersecurity, AMI/HAN, and explainability), offering a novel synthesis for AI-enabled HEMS. Full article

Sugarcane juice (SJ) is a naturally sweet beverage rich in sucrose but prone to microbial contamination, raising concerns among health-conscious consumers. This study aimed to develop a functional SJ enriched with fructooligosaccharides (FOS) using enzymatic treatment, followed by high-pressure processing (HPP) to enhance its safety and quality. The enzymatic conversion of sucrose to FOS was achieved using Pectinex^® Ultra SP-L (commercial enzyme), with varying enzyme concentrations, temperatures and incubation times to identify the optimal conditions via response surface methodology (RSM). Under optimal conditions (1000 U/g enzyme concentration, 48 °C, 13 h), sucrose in raw SJ (124.33 g/L) decreased by 59.17 g/L, resulting in maximum reducing sugars (16.02 ± 0.58 g/L) and enhanced FOS yields, notably kestose (2.37 g/L) and nystose (9.35 g/L). After being treated with HPP at 600 MPa for 3 min, E. coli K12 and L. innocua were effectively inactivated by achieving > 5 log reduction, meeting USFDA standards. Furthermore, it was also observed that HPP could reduce yeast (6.56 × 10² CFU/mL). Meanwhile, mold, E. coli, and coliforms were not detected. Additionally, HPP maintained the juice’s physicochemical properties, outperforming thermal pasteurization (85 °C for 10 min) in quality preservation. This study highlights the potential of enzymatic treatment and HPP in improving SJ safety and functionality. Full article

Artificial intelligence tools are quickly being applied in many areas of science, including learning sciences. Learning requires various types of thinking, sustained by distinct sets of neural networks in the brain. Labelling these systems gives us tools to manage them. This paper presents a pilot application of Large Language Models (LLMs) to physics textbook analysis, grounded in a well-developed neural network theory known as the Five Pillars of the Mind. The domain-specific networks, innate sense, and the five pillars provide a framework with which to examine how physics is learnt. For example, one can identify which pillars are active when discussing a physics concept. Identifying which pillars belong to which physics concept may be significantly influenced by the bias of the author and could be too time-consuming for longer, more complex texts involving physics concepts. Therefore, using LLMs to identify pillars could enhance the application of this framework to physics education. This article presents a case study in which we used selected Large Language Models to identify pillars within eight pages of learning material concerning forces aimed at 12- to 14-year-old pupils. We used GPT-4o and o4-mini, as well as MAXQDA AI Assist. Results from these models were compared with the authors’ manual analysis. Precision, recall, and F1-Score were used to evaluate the results quantitatively. MAXQDA AI Assist obtained the best results with 1.00 precision, 0.67 recall, and an F1-Score of 0.80. Both products by OpenAI hallucinated and falsely identified several concepts, resulting in low precision and, consequently, low F1-Score. As predicted, ChatGPT o4-mini scored twice as high as ChatGPT 4o. The method proved to be promising, and its future development has the potential to provide research teams with analysis not only of written learning material, but also of pupils’ written work and their video-recorded activities. Full article

Shell-like housing structures for motors and compressors can be found in everyday products. Consumers significantly evaluate acoustic emissions during the first usage of products. Unpleasant sounds may raise concerns and cause complaints to be issued. A prevention strategy is a holistic acoustic design, which includes predicting the emitted sound power as part of end-of-line testing. The hybrid experimental-simulative sound power prediction based on laser scanning vibrometry (LSV) is ideal in acoustically harsh production environments. However, conducting vibroacoustic testing with laser scanning vibrometry is time-consuming, making it difficult to fit into the production cycle time. This contribution discusses how the time-consuming sampling process can be accelerated to estimate the radiated sound power, utilizing adaptive sampling. The goal is to predict the acoustic signature and its uncertainty from surface velocity data in seconds. Fulfilling this goal will enable integration into a product assembly unit and final acoustic quality control without the need for an acoustic chamber. The Gaussian process regression based on PyTorch 2.6.0 performed 60 times faster than the preliminary reference implementation, resulting in a regression estimation time of approximately one second for each frequency bin. In combination with the Equivalent Radiated Power prediction of the sound power, a statistical measure is available, indicating how the uncertainty of a limited number of surface velocity measurement points leads to predictions of the uncertainty inside the acoustical signal. An adaptive sampling algorithm reduces the prediction uncertainty in real-time during measurement. The method enables on-the-fly error analysis in production, assessing the risk of violating agreed-upon acoustic sound power thresholds, and thus provides valuable feedback to the product design units. Full article

Nano-sanitizers, which exploit the unique physicochemical properties of nanomaterials, are being increasingly investigated as innovative tools to promote food safety. In this argumentative review, we compare and contrast nano-sanitizers with conventional sanitation methods by examining their underlying antimicrobial mechanisms, multifaceted benefits, inherent challenges, and wide-ranging public health implications. We evaluate regulatory conundrums and consumer perspectives alongside future outlooks for integration with advanced technologies such as artificial intelligence. Through selective synthesis of the published literature, our argumentative discussion demonstrates that nano-sanitizers not only promise superior performance in pathogen inactivation but could also contribute to overall food system sustainability, provided safety and regulatory concerns are adequately addressed. Full article

Sustainability concerns and rising consumer environmental awareness (CEA) have fundamentally reshaped competitive dynamics in modern supply chains. This study examines the influence of CEA on pricing and environmental effort competition between store brand (SB) and national brand (NB) products in a two-stage supply chain with one manufacturer and one retailer. We develop a mathematical model to evaluate strategic interactions under three power structures: Manufacturer Stackelberg (MS), Retailer Stackelberg (RS), and Vertical Nash (VN), considering two environmental investment scenarios: NB-only investment and bilateral SB-NB investment. Our findings indicate that (i) when only NB products invest environmentally, CEA increases environmental effort levels, wholesale prices, and retail prices for both brands, expanding total channel value rather than merely redistributing profits; (ii) CEA and channel competition on jointly determine optimal channel power structure, with MS dominating in differentiated markets with low CEA while RS yields superior outcomes under high competition and high CEA; (iii) retailers consistently achieve maximum profits under VN structure through balanced negotiation positions; and (iv) bilateral environmental investment causes price convergence across structures, shifting competitive focus from governance to operational excellence. By integrating environmental investment, channel power structure, and channel competition into a unified framework, this study offers managers practical decision tools for selecting optimal channel structures based on observable market conditions. Furthermore, it demonstrates how grocery retail chains and consumer goods manufacturers can transform environmental initiatives from compliance costs into value creation mechanisms that enhance both profitability and sustainability. Full article

Taeniasis and neurocysticercosis (NCC), caused by Taenia solium, are significant public health concerns recognised by the World Health Organization (WHO) in developing countries across the Americas, Asia, and Africa. Taeniasis occurs in humans after consuming undercooked pork containing the larval stage (Cysticerci), which matures into the adult reproductive form in the intestine, releasing eggs through faeces. Accidental ingestion of these eggs by humans is the primary cause of NCC, a principal contributor to acquired epilepsy in endemic regions. Interrupting this transmission cycle is crucial to reducing the incidence of human NCC and porcine cysticercosis, thereby underscoring the need for accurate diagnosis and timely treatment of taeniasis. Current diagnostic tests for taeniasis, including microscopy, serology, copro-DNA, and coproantigen assays, exhibit variability in sensitivity, reproducibility, cross-reactivity, and accessibility. To overcome these limitations, bioinformatics tools were integrated with recombinant DNA technology to identify protein sequences with immunological potential. These sequences were evaluated in silico and used to construct an expression system. Subsequently, the antigens were expressed in a eukaryotic system, yielding two purified recombinant protein variants of 21 and 30 kDa. Their purification validated via Western blotting of the molecular tag, paves the way for the development of a direct immunological assay for the specific detection of Taenia solium carriers. Full article

Rapid advancements in artificial intelligence and the Internet of Things (IoT) have fueled the growth of furniture, transforming traditional home environments into intelligent living spaces. As consumer adoption accelerates, understanding user concerns and sentiment trends becomes crucial for brands to refine product offerings and enhance market competitiveness. This study systematically investigates consumer concerns and sentiment trends toward furniture products by analyzing user-generated reviews across two major e-commerce platforms: Jingdong and Taobao. Leveraging advanced text-mining methods including TF-IDF keyword extraction, hierarchical clustering, Graph of Words–Latent Dirichlet Allocation (GoW-LDA) topic modeling, and BERT-based sentiment analysis, this research identifies critical user preferences, product satisfaction factors, and platform-specific behavioral patterns. Results reveal distinct cross-platform differences; Jingdong users prioritize service quality, brand trust, and logistical efficiency, whereas Taobao users emphasize product aesthetics, material selection, and cost-effectiveness. The sentiment analysis demonstrates that Jingdong users exhibit more consistent and positive feedback, while sentiment on Taobao displays higher variability due to product-quality discrepancies and price sensitivity. Full article

The contribution of meal kits to the waste problem has become a significant concern, leading consumers to demand sustainable practices from meal-kit companies. This study proposes a framework to understand customer behavior toward sustainable meal-kit brands that promote practices such as recycling and waste reduction. This study applies warm glow theory to investigate how pure and impure altruism affect consumers’ perceptions of a meal-kit brand’s sustainability, perceived price fairness, and continuance intention. The findings confirmed that meal-kit brands’ sustainable practices significantly enhanced consumers’ perceptions of brand sustainability, which in turn influenced their perceived price fairness and continuance intention. Furthermore, warm glow and altruistic values were found to significantly moderate the relationship between consumers’ perceptions of brand sustainability and their continuance intention. However, no significant moderating effects were observed between consumers’ perceptions of brand sustainability and perceived price fairness. This study contributes to a deeper understanding of the psychological mechanisms underlying consumer attitudes and behaviors toward meal-kit brands’ sustainability efforts. Full article

Background/Objectives: Currently, clinicians and physiotherapists pay only limited attention to spinal deformities in children with cerebral palsy (CP). To enhance awareness, a tool based on a traffic light system (TLS-Spine) was developed for use by pediatricians and physiotherapists caring for children with CP. The objective of the study was to evaluate the applicability of this assessment tool in routine clinical practice. Methods: A review group consisting of 48 pediatricians and physiotherapists was recruited. Each participant was asked to apply the TLS-Spine to a minimum of 10 CP patients and to complete a questionnaire concerning its value and applicability in daily practice. Responses were rated on a scale from 1 (complete agreement) to 6 (complete disagreement). Results: The TLS-Spine was correctly applied in 96.3% cases. The questionnaires of 48 reviewers based on 537 completed survey sheets were analyzed. Overall, reviewers reported no difficulties with the introduction and use of the TLS-Spine in daily clinical routine practice (median/range: 1/1–4). The tool was considered straightforward to use (1/1–3), not time consuming (1/1–4), helpful in performing the clinical examination (2/1–6), understanding the findings (2/1–6) and deciding on further management of the patients (2/1–5). Physicians rated the TLS-Spine significantly higher than physiotherapists in four of nine dimensions. Conclusions: The TLS-Spine is a practical and user-friendly assessment tool. It may increase the awareness for spinal deformities and support early referral to orthopedic specialists for early detection and treatment. Full article