Heteroatom-doped Co-N-C single-atom catalysts achieve robust peracetic acid activation for sustainable water decontamination.

This article examines an applied methodology for reengineering and standardizing manual culinary processes during the transition from an auteur, chef-driven model to a high-volume chain format, using Laghman Express as a case study. The relevance of the study is conditioned by the need to scale authentic ethnic cuisines amid a shortage of qualified personnel, rising operating costs, and the U.S. market’s demand for consistent quality at high service speed. The purpose of the article is to develop and provide theoretical substantiation for a methodology that enables formalizing and replicating complex manual techniques without forfeiting the product’s gustatory identity. The scientific novelty of the work lies in the proposed model, which combines the decomposition of culinary competencies, the adaptive standardization of process physics, the conveyor-based organization of a kitchen without semifinished products, and a management system that synchronizes staff motivation with quality standards. It is concluded that translating chefly intuition into measurable parameters, station-based certification, an open kitchen, and multifactor KPI metrics enables overcoming scaling barriers, increasing productivity, and preserving product authenticity in a chain format. The article will be useful to HoReCa researchers, operations managers, restaurateurs, and developers of scalable gastronomic concepts.

As the demand for better educational quality and improved student performance grows, institutions face increasing challenges in making their teaching methods more effective to ensure successful learning outcomes. Most practical recommendations tend to focus on isolated effects, but learning success usually results from interconnected factors that work together. Drawing on constructivist Learning Theory, this study examines pedagogical and motivational factors that can positively impact learning results in higher education within Moroccan universities. The main goal is to identify and evaluate the nonlinear individual effects and the interactive causal configurations involving multiple conditions, such as teacher motivation, pedagogical leadership, self-efficacy, instructional innovation, ICT use, and student motivation, on learning outcomes. Empirical data were gathered through a questionnaire completed by 349 Moroccan university students, using measurement scales for key variables. The analysis employed the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, which helps identify different combinations and causal pathways that lead to high academic achievement. Findings suggest that excellent learning outcomes are not caused by a single factor but by the interaction of several interdependent conditions. Different "recipes" can produce similar strong results. Certain combinations, especially those with strong teacher motivation, effective leadership, and strategic ICT use, proved to be reliable configurations, showing that technology is most impactful when integrated into supportive pedagogical and motivational environments. These results can help redefine and evaluate integrated educational policies, considering the complex interactions among individual, pedagogical, and technological factors. This approach promotes more effective and equitable learning environments through coherent bundles of mutually reinforcing interventions, instead of isolated efforts. Ultimately, this research enables educators and policymakers to develop more targeted strategies, utilize resources more efficiently, and improve overall educational effectiveness.

A systematic approach to organizing control at all stages of production plays an important role in ensuring food safety and quality. The modern development of the food industry, the expansion of global supply chains, growing consumer demands for product quality, and stricter international safety standards necessitate the improvement of approaches to risk management in industrial food production. Ensuring an adequate level of product safety requires quality control of the finished product and systematic management of potential hazards at all stages of the production process: from the supply of raw materials to the sale of finished products. Modern approaches to the organization of food safety and quality control in industrial production are considered. Particular attention is paid to a systematic approach to the classification of types of control according to the nature of possible hazards and stages of the production process. The main categories of risks that may arise during food production, in particular biological, chemical, and physical hazards, are analysed, and the features of their control within the technological processes of food industry enterprises are determined. The study aims to systematize the types of food safety and quality control in industrial production and determine their role in the formation of an effective risk management system. The features of the organization of incoming control of raw materials, technological control during production, control of finished products, and sanitary and hygienic control of the production environment are considered. It has been established that the combination of different types of control and their integration into the food safety management system contributes to increasing the efficiency of the production process, minimizing the risks of hazardous factors, and ensuring stable product quality. The implementation of a systematic approach to food safety and quality control ensures comprehensive risk management, increases consumer confidence in products, and contributes to the competitiveness of food industry enterprises in domestic and international markets. The use of integrated food safety management systems, the introduction of modern technologies for monitoring production processes, and the improvement of control procedures create the conditions for improving the efficiency of enterprises and ensuring the sustainable development of the food industry.

Abstract As products become more sophisticated and quality demands grow, manufacturing systems are becoming increasingly complex. In particular, for small and medium enterprises (SMEs) operating complex, high-mix, low-volume production systems, manufacturing layout significantly impacts productivity and operational costs. Given this impact, accurate prediction of production performance becomes essential for optimizing layout configurations and resource allocation. In this article, the objective is to develop a decision-support framework for selecting the best production layouts in labor-intensive SME manufacturing systems. The framework uses discrete event simulation (DES) with cellular manufacturing system (CMS) models to generate datasets. And, Gaussian process regression (GPR) is applied to provide probabilistic predictions for key performance variables while accounting for inherent uncertainties. When GPR-based production volume predictions for different layouts result in overlapping prediction ranges, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) is then utilized to systematically rank the alternatives using multiple key variables as evaluation criteria. A case study demonstrates the framework's effectiveness by comparing three alternative layouts with GPR-based production volume predictions and fuzzy TOPSIS-based decision-making. The multicriteria evaluation systematically ranks the alternatives using key performance variables including adjusted cycle time, total buffer capacity, average manpower efficiency, and number of cells.

ABSTRACT With the increasing demand for food quality and safety, the innovative development of food preservation technologies is crucial. Spatial electric field combined with low‐temperature storage technology has become a research hotpot in the field of food preservation due to its unique mechanism and significant preservation effect. This paper systematically reviews the research progress of food preservation technology using spatial electric field combined with low‐temperature storage. Firstly, it introduces the definition, classification, and characteristics of spatial electric fields and deeply analyzes the preservation mechanisms of this technology in inhibiting microbial growth, regulating enzyme activity, managing moisture and ice crystals, and retaining antioxidants. Subsequently, it summarizes the achievements in the application of this technology in fruits and vegetables, aquatic products, livestock and poultry products domestically and abroad. Meanwhile, it discusses the development trends of technology integration and equipment intelligence, as well as the main challenges in large‐scale application costs, electric field uniformity control, and long‐term food safety verification. Studies have shown that spatial electric field combined with low‐temperature storage technology exhibits good application potential in food preservation, but further research is still needed in technology optimization and mechanism exploration.

Purpose The purpose of this study is to examine internationalisation processes among micro, small and medium enterprises involved in a leading industry and operating in emerging economies. The study uses a cross-national approach and considers the conceptual underpinnings of the dynamic capabilities approach as its conceptual background. Design/methodology/approach The perspectives of enterprise leaders operating in five coffee-producing nations were gathered through semi-structured, open-ended interviews. Findings Opportunities in internationalisation processes include the rising global demand, value-adding potential, image enhancement and self-initiated improvements in the production processes. However, participants also recognise existing inadequate business models to cope with higher quality demands or the market's competitiveness. To evolve, developing stronger adaptive processes is crucial for meeting the continuous pressures of quality standards, supply consistency and perennially unpredictable factors, including prices and the climate. Conceptually, the analysis uncovered 13 conceptual dimensions that inspired a conceptual framework, reinforcing and extending the dynamic capabilities framework. Originality/value While research on firm internationalisation processes is a mature area of inquiry, the focus on micro, small- and medium-sized firms operating in emerging economies using a cross-national approach has been more limited. This study helps narrow this gap, providing original and valuable insights into business processes concerning a global product. The study's analysis and resulting conceptual contributions underscore important implications associated with firm and industry internationalisation processes among emerging economies operating in a significant industry.

Palm oil is a strategic agricultural crop in Indonesia, Malaysia, and Thailand, contributing significantly to national economies and requiring continuous improvements in harvesting efficiency and mill operations. The growing demand for higher efficiency and consistent quality in palm oil mills has accelerated the adoption of advanced technologies, particularly artificial intelligence (AI), which is increasingly applied across agricultural sectors, including oil palm production. This review aims to examine the development of convolutional neural network (CNN)-based approaches for ripeness grading of oil palm fresh fruit bunches (FFB) using CNN techniques. It provides an overview of research trends and technical progress in this field, showing that Malaysia leads scientific publications related to palm oil ripeness detection, followed by Indonesia. Most existing studies employ 1-stage object detectors, especially YOLO-based architectures, due to their real-time capability and relatively high performance. However, these methods are often trained and evaluated using datasets limited to specific environments, plantation conditions, or fruit varieties, which constrains generalization and large-scale deployment. Key research gaps are identified, including limited dataset diversity, high computational requirements, insufficient integration with Internet of Things (IoT)–based plantation and mill management systems, and the lack of real-time estimation of quality indicators such as free fatty acid (FFA) content and kernel-related attributes. Future research directions highlight the need for multimodal sensing, multi-camera systems, and multi-task learning frameworks that integrate ripeness grading with oil extraction rate (OER) estimation to support more effective operational decision-making in palm oil production systems. HIGHLIGHTS Research on CNN in palm oil has increased since 2017 with the adoption of DL. Malaysia leads publications in palm oil ripeness research, followed by Indonesia and Thailand. One-stage detectors, particularly YOLO-based models, are most commonly used for real-time grading. Most CNN-based systems rely on external visual features for ripeness classification. Multimodal approaches for real-time biochemical assessment remain limited. GRAPHICAL ABSTRACT

Aquatic environments under anthropogenic pressure serve as critical hotspots for the rapid development of microbial populations, including the growth of antibiotic-resistant bacteria (ARB). This study evaluates the efficiency of natural lagooning wastewater treatment systems at two sites in Settat and Ouled Said, Morocco, focusing on physicochemical characteristics and ARB prevalence in treated effluents. A substantial reduction in total bacterial counts, including coliforms, Enterococcus spp., and Pseudomonas spp., was observed following treatment, demonstrating overall system performance. However, a considerable proportion of resistant strains persisted, with coliforms demonstrating resistance rates of 27.5% to ampicillin and 45.98% to ciprofloxacin. A total of 535 bacterial isolates were detected, demonstrating the presence of human pathogenic species such as Escherichia coli , Klebsiella pneumoniae , and Pseudomonas aeruginosa . These isolates revealed substantial resistance to numerous antibiotics, including ceftazidime and imipenem. Correlation analyses revealed significant associations between physicochemical parameters and antibiotic resistance patterns, with dissolved oxygen and pH showing strong negative correlations with resistant bacterial populations. Low dissolved oxygen levels and high organic load were associated with increased resistance rates. Factor analysis indicated four major components explaining 90.53% of the overall variance, underlining the pivotal importance of temperature, nitrate, and chemical oxygen demand for water quality and ARB dynamics. Spatial and seasonal variations further affected ARB prevalence, with higher resistance rates seen during colder months and in downstream regions. Effluents from wastewater treatment and urban runoff largely contribute to the emergence and spread of ARB. This study provides valuable insights into ARB dynamics in treated wastewater, underlining the necessity for advanced wastewater treatment strategies.

Rising global demand for food quantity and quality requires precision strategies on fine-tuning trait-related gene expression targeting crop improvement. Dynamic covalent modifications on mRNA add a reversible layer of post-transcriptional regulation on gene expression, yet their trait-level logic in crops remains fragmented. Recent studies connect epitranscriptomic enzymes and readers to yield components, quality traits and stress resilience. Here, we summarize regulatory mechanisms of covalent modifications emerging from 13 functionally validated crop cases across cereals, fiber and horticultural species, focusing on how m6A, m5C, m1A, ac4C, and Ψ reprogramme mRNA molecular functions, such as stability, translation, and RNA compartmentalization. We further discuss the sufficiency and insufficiency of applying current Arabidopsis-based mechanisms to crop improvements, where whole-genome duplication and paralog specialization diversify writer-eraser-reader repertoires and enable species-specific control circuits. Finally, we highlight future directions to transform descriptive maps into predictive breeding tools, emphasizing the need for quantitative, base-resolution profiling with stoichiometric accuracy and the development of programmable, site-specific perturbation systems that can test causal relationships in defined tissues and developmental stages. These advances position epitranscriptomic reprogramming as a complementary route to precision engineering of crop yield and quality.

This study comprehensively investigated the effects of different dietary energy levels-low energy (LE, 10.62 MJ/kg), medium energy (ME, 11.87 MJ/kg), and high energy (HE, 13.06 MJ/kg)-on growth performance, meat quality, muscle metabolite profiles, and cecal microbiota in a local Chinese chicken breed (Guangyuan gray chicken). Growth and carcass traits, including interpubic width and liver weight, responded positively to increasing dietary energy. Compared to the ME control, the HE diet significantly increased drip loss, whereas the LE diet reduced both intramuscular fat and protein content (P <0.05). Untargeted metabolomic analysis identified 188 differentially abundant muscle metabolites across the dietary groups, revealing distinct metabolic profiles. The biosynthesis of the amino acids pathway was significantly affected by different dietary energy levels. Targeted metabolomics further demonstrated the differences in muscle amino acid composition: essential, sweet-taste, and umami-taste amino acids increased progressively with dietary energy, with the HE group achieving the most favorable profile for flavor and nutrition. Cecal microbiota analysis indicated that dietary energy levels significantly altered microbial community structure. Specific bacterial taxa, including Spirochaetota and Bacteroides, were positively correlated with muscle amino acid concentrations. Our findings demonstrate that dietary energy level modulated the cecal microbiota, which in turn influenced muscle amino acid deposition and overall meat quality. This study provides a comparative multi-omics perspective for optimizing dietary energy strategies in local chicken production to meet varying market demands for meat quality and nutritional value.IMPORTANCEThis comparative study established a crucial link between dietary energy intake and the final quality of poultry meat through a multi-omics lens. We demonstrate that low, medium, and high dietary energy levels elicit distinct phenotypic, metabolic, and microbial profiles in a local chicken breed. The findings provide a scientific framework for selecting dietary energy strategies tailored to specific market demands: HE for premium quality segments, LE for lean or cost-driven production, and ME for efficient conventional production. We identified specific correlations between the cecal bacteria (Spirochaetota, Bacteroides) and muscle metabolites (key amino acids). Thus, this work offered the scientific data to optimize meat quality through targeted feeding interventions.

Potato (Solanum tuberosum L.), the fourth most important food crop worldwide, serves as a multi-purpose resource for food, feed and industrial raw materials, and plays a pivotal role in safeguarding food security, diversifying dietary structure and boosting the development of agricultural economy. With increasing consumer demand for nutritional quality, elucidating the regulatory mechanisms of potato quality traits has become a research priority. In this study, three potato cultivars with distinct coloration were employed as materials. Metabolomic profiling identified a total of 1128 metabolites, and revealed that pigmented potato cultivars accumulated higher levels of flavonoids and linoleic acid derivatives compared with the white-fleshed cultivar. Transcriptomic analysis uncovered numerous differentially expressed genes (DEGs) among the three cultivars; notably, DEGs in pigmented cultivars were significantly enriched in pathways related to terpenoid backbone biosynthesis, flavonoid biosynthesis, linoleic acid metabolism, and starch and sucrose metabolism. Integrated multi-omics analysis revealed that the high expression of structural genes in the flavonoid biosynthesis pathway is strongly associated with flavonoid accumulation in pigmented potatoes, suggesting that transcriptional upregulation of these genes may be a key driver of flavonoid biosynthesis. Furthermore, several MYB and WD40 family transcription factors were identified as potential regulators of flavonoid and anthocyanin biosynthesis in potato. Collectively, our study provides insight into the regulatory mechanisms underlying the biosynthesis of secondary metabolites in potato by combining transcriptomic and metabolomic approaches, and the findings provide a valuable theoretical basis for the genetic improvement of potato nutritional quality in future breeding programs.

Assessing cosmetic quality, safety, and effectiveness demands advanced in situ, real-time, and multi-dimensional analytical technologies, while conventional methods suffer from complex sample preparation and incomplete analysis. Raman spectroscopy, with its non-invasiveness, specific molecular fingerprint, and micron-level spatial resolution, has become a key tool for cosmetic analysis. Based on a comprehensive review of the literature from 2000 to 2025, this article systematically examined the application of Raman spectroscopy in cosmetic analysis. The systematic search and screening process ensured the comprehensiveness and rigor of the review’s research foundation, as the 69 high-quality studies covered all core application areas of Raman spectroscopy in cosmetic analysis, providing solid literature support for subsequent technical summaries and trend analysis. This article systematically reviews the application of Raman spectroscopy in the cosmetic industry for ingredient detection (approved ingredients and hazardous substances), quality control (authenticity verification and production traceability), transdermal mechanism analysis (penetration pathways and interaction with skin barriers), and efficacy assessment. Combined with typical research cases, this study examined the technical principles and practical value, as well as the limitations and shortcomings of Raman technology applications. It ultimately provides suggestions for future developments in terms of portability, intelligence, and standardization, offering references for researchers to enable technological innovation and regulatory improvements in the cosmetics industry.

ABSTRACT Supplier selection and transportation are critical to supply chain management, as they directly affect purchasing performance and material flow efficiency. However, balancing procurement and transportation costs while ensuring supply reliability remains insufficiently addressed in the literature. This paper explores the impact of transportation on supplier selection and order allocation by proposing a multi-criteria decision support model based on mathematical programming. The model minimises total costs, including purchasing, ordering, transportation, and inventory, while considering delivery quality, supplier capacity, and buyer demand, with inventory managed across multiple stages encompassing suppliers, transit, and buyer. It then determinesefficient suppliers and optimal order quantities assigned to each. To validate the model, it was applied to a real-world case in the French railway sector. The results demonstrate that integrating transportation planning into the supplier selection process reduces costs while enhancing supply chain reliability and overall performance. The study also highlights relevant directions for future research.

Hospitals are healthcare service organizations with complex characteristics, as the services provided are directly related to patient safety, clinical quality, and quality of life. In recent years, hospital service characteristics have evolved in response to increasing demands for service quality, greater attention to patient experience, and the accelerated adoption of digital technologies in healthcare delivery. These developments require a more comprehensive understanding from a hospital management perspective. This article aims to analyze the characteristics of hospital services from a hospital management perspective, with particular emphasis on the integration of service quality, patient experience, patient-centered care, and service digitalization. This article employs a conceptual-analytic approach based on a literatur review. The analysis is conducted through the examination and synthesis of concepts and findings from previous studies related to hospital service characteristics and hospital management published between 2020 and 2025. The literature is used as a theoretical foundation and conceptual reference to build an analytical framework, rather than as the object of a systematic review. The analysis indicates that service quality remains a fundamental foundation of hospital services, particularly in ensuring patient safety and clinical quality. However, service quality alone is no longer sufficient to explain the overall value of hospital services. Patient experience has emerged as a strategic dimension influencing patient satisfaction, trust, and hospital reputation. Furthermore, the implementation of patient-centered care strengthens the shift in service orientation toward patient needs, while digitalization reshapes interactions between patients and healthcare providers. In conclusion, hospital service characteristics are multidimensional and need to be managed in an integrated manner. Hospital management is required to combine clinical quality, service processes, patient experience, and organizational readiness for digital transformation in order to deliver patient-oriented and sustainable healthcare services.

Nanoengineering of two-dimensional materials in the baijiu brewing industry: A review.

There are radical transformations in the governance of higher education in South Asia, largely because of the challenges posed by demography, competitiveness, the increase in the number of private institutions and demands for accountability and quality. Despite such changes, the governance architecture in Bangladesh, India and Sri Lanka still faces entrenched issues, such as political meddling, bureaucratic delay, divergence in accreditation capacity and lack of autonomy. The article presents an in-depth, comparative investigation of reforms and innovations in the governance architecture in the three South Asian nations. Based on the framework of governance theory, new public management and postcolonial institutionalism, the article takes a qualitative, comparative approach, using document studies, policy analyses and institutional-level investigations. The article finds that, although the India National Education Policy (NEP) 2020 initiative appears to be the ‘boldest’ in South Asia, there are still wider, uneven implementation issues. There are issues in Bangladesh related to accreditation and digital governance, but the presence of political patronage and regulatory restrictions. There appears in Sri Lanka a stable regime, albeit heavily centralised, with enduring quality assurance and sluggish responsiveness in terms of innovations. The article culminates with the presentation of a governance architecture framework specifically designed and contextualised in South Asia, focusing on autonomy in the perspective of accountability, autonomous regulatory bodies, student and faculty performance credentials in terms of accreditation, digital governance and regional linkage and networking.

Abstract Quality standards require a balance between the demand for clean water and good water quality. The purpose of this study is to delineate the quality of shallow well water in Denpasar City. Using a portable water quality parameter measuring instrument and laboratory tests, data were collected in the field by observing and evaluating the quality of shallow well water. The Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method was utilised to assess the current state of water quality requirements. Based on the specifications established by PERMENKES RI No. 32/2017, this study’s output is the creation of a groundwater quality map for shallow wells in Denpasar (TDS, PH, EC, Salinity, BOD, COD parameters). The characteristics evaluated allowed for the determination of the shallow well water quality value in Denpasar City. Using the kriging method and a geographic information system analysis, the water quality test data were identified to produce the following results: TDS = 426,5 mg/L, pH = 7,24, EC = 854,5 µS/cm, salinity = 0,036 mg/L, BOD = 3,513 mg/L, and COD = 8,897 mg/L. According to the CCME WOI method’s computation, which yielded a value of 57,99, Denpasar City’s groundwater falls into the medium water category, is frequently polluted, and frequently deviates from quality norms.

Objective:The incidence of chronic rhinosinusitis （CRS） is notably high. Common symptoms include nasal obstruction, rhinorrhea, facial pain, and hyposmia or anosmia. As societal demands for quality of life continue to rise, olfactory dysfunction has emerged as a primary driver for CRS patients seeking medical attention. Pharmacotherapy and surgical treatment remain the principal treatment modalities for CRS, with surgery being the preferred option for individuals who fail to respond adequately to medication. Since its inception in the 1970s, nasal endoscopic surgery has undergone rapid evolution, revolutionizing the surgical treatment of CRS. In recent years, as understanding of the pathophysiological mechanisms and intrinsic subtypes of CRS has deepened, innovations in nasal endoscopic techniques have been introduced, aiming to refine personalized treatment strategies with greater precision. This article systematically reviews the improvement rates and potential mechanisms underlying olfactory function improvement following various endoscopic sinus surgeries. It will be crucial to develop individualized treatment plans prospectively based on the distinct intrinsic subtypes of patients.

This study investigates the employment quality and development trends of local teacher trainees by applying a system dynamics model to capture the complex interactions among individual, institutional, societal, and policy factors. Drawing on a mixed dataset — comprising questionnaire responses from 406 teacher trainees at Zhengzhou Normal University and official educational statistics — the model integrates variables such as career aspirations, family support, curriculum quality, and labor market demand. The analysis emphasizes the critical roles of career services, curriculum quality, and government policies in shaping employment outcomes. Simulation of alternative policy scenarios suggests that enhancements in these areas can lead to substantial improvements in employment quality. By integrating system dynamics modeling into the study of teacher employment, this research offers a holistic perspective on the causal mechanisms and feedback loops underlying employment decisions, providing actionable insights for policy design and educational planning in the Chinese context.