Search Results (875)

Recent advances in computational biology have provided powerful tools for analyzing, modeling, and optimizing probiotic microorganisms, thereby supporting their development as promising agents for improving human health. The essential role of the microbiota in regulating physiological processes and preventing disease has driven interest in the rational design of next-generation probiotics. This review highlights progress in in silico approaches for enhancing the functionality of probiotic strains. Particular attention is given to genome-scale metabolic models, advanced simulation algorithms, and AI-driven tools that provide deeper insight into microbial metabolism and enable precise probiotic optimization. The integration of these methods with multi-omics data has greatly improved our ability to predict strain behavior and design probiotics with specific health benefits. Special focus is placed on modeling probiotic–prebiotic interactions and host–microbiome dynamics, which are essential for the development of functional food products. Despite these achievements, key challenges remain, including limited model accuracy, difficulties in simulating complex host–microbe systems, and the absence of unified standards for validating in silico-optimized strains. Addressing these gaps requires the development of integrative modeling platforms and clear regulatory frameworks. This review provides a critical overview of current advances, identifies existing barriers, and outlines future directions for the application of computational strategies in probiotic research. Full article

The growing number of senior experts leaving the workforce (especially in more developed economies, such as in Europe), combined with the ubiquitous access to artificial intelligence (AI), is triggering organizations to review their knowledge transfer programs, motivated by both financial and management perspectives. Our study aims to contribute to the field by analyzing options to integrate intergenerational tacit knowledge transfer (InterGenTacitKT) with AI-driven approaches, offering a novel perspective on sustainable Knowledge and Human Resource Management in organizations. We will do this by building on previous research and by extracting findings from 36 in-depth semi-structured interviews that provided success factors for junior/senior tandems (JuSeTs) as one notable format of tacit knowledge transfer. We also refer to the literature, in a grounded theory iterative process, analyzing current findings on the use of AI in tacit knowledge transfer and triangulating and critically synthesizing these sources of data. We suggest that adding AI into a tandem situation can facilitate collaboration and thus aid in knowledge transfer and trust-building. We posit that AI can offer strong complementary services for InterGenTacitKT by fostering the identified success factors for JuSeTs (clarity of roles, complementary skill sets, matching personalities, and trust), thus offering organizations a powerful means to enhance the effectiveness and sustainability of InterGenTacitKT that also strengthens employee productivity, satisfaction, and loyalty and overall organizational competitiveness. Full article

Fibrate pharmaceuticals (fibrates), as a widespread class of emerging contaminants, pose potential risks to both ecological systems and human health. The photocatalytic system based on nitrogen (N) and fluorine (F) co-doped TiO₂ nanotube arrays (NF-TNAs) provides a renewable solution for fibrate pharmaceutical removal from water, powered by inexhaustible sunlight. In this study, the degradation of two typical fibrates, i.e., bezafibrate (BZF) and ciprofibrate (CPF), under simulated sunlight irradiation through NF-TNAs were investigated. The photocatalytic degradation of BZF/CPF was achieved through combined radical and non-radical oxidation processes, while the generation and reaction mechanisms of associated reactive oxygen species (ROS) were examined. Electron paramagnetic resonance detection and quenching tests confirmed the existence of h⁺, •OH, O₂^•−, and ¹O₂, with O₂^•− playing the predominant role. The transformation products (TPs) of BZF/CPF were identified through high-resolution mass spectrometry analysis combined with quantum chemical calculations to elucidate the degradation pathways. The influence of co-existing ions and typical natural organic matters (NOM) on BZF/CPF degradation were also tested. Eventually, the ecological risk of BZF/CPF transformation products was assessed through quantitative structure–activity relationship (QSAR) modeling, and the results showed that the proposed photocatalytic system can largely alleviate fibrate toxicity. Full article

This article addresses the epistemic and political problem of self-referentiality in theology within the context of post-secular societies as a demand for public relevance of faculties of theology within the 21st-century university. It focuses on the epistemological emergence of public theology as a distinct knowledge, such as human rights, and ecological thinking, contributing to the public mission of knowledge production and interdisciplinary engagement. This study applies Michel Foucault’s archaeological and genealogical methods in dialogue with Michel de Certeau’s insights into the archaeology of religious practices through a multi-layered analytical approach, including archaeology of knowledge, apparatuses of power, pastoral government, and spirituality as a genealogy of ethics. As a result of the analysis, it examines the historical conditions of possibility for the emergence of a public theology and how it needs to be thought synchronously with other formations of knowledge, allowing theology to move beyond its self-referential model of approaching dogma and the social practices derived from it. This article concludes programmatically that the development of public theology requires an epistemological reconfiguration to displace its self-referentiality through critical engagement with a public rationality framework as an essential task for the public relevance and contribution of theology within contemporary universities and plural societies. Full article

Background: A critical review of the literature demonstrates that masticatory apparatus with an artificial oral environment is of interest in the fields including (i) dental science; (ii) food science; (iii) the pharmaceutical industries for drug release. However, apparatus that closely mimics human chewing and oral conditions has yet to be realised. This study investigates the vital role of dental morphology and form–function connections using two-bite test parameters for effective drug release from medicated chewing gum (MCG) and compares them to human chewing efficiency with the aid of a humanoid chewing robot and a bionics product lifecycle management (PLM) framework with built-in reverse biomimetics—both developed by the first author. Methods: A novel, bio-engineered two-bite testbed is created for two testing machines with compression and torsion capabilities to conduct two-bite tests for evaluating the mechanical properties of MCGs. Results: Experimental studies are conducted to investigate the relationship between biting force and crushing/shearing and understand chewing efficiency and effective mastication. This is with respect to mechanochemistry and power stroke for disrupting mechanical bonds releasing the active pharmaceutical ingredients (APIs) of MCGs. The manuscript discusses the effect and the critical role that jaw physiology, dental morphology, the Bennett angle of mandible (BA) and the Frankfort-mandibular plane angle (FMA) on two-bite test parameters when FMA = 0, 25 or 29.1 and BA = 0 or 8. Conclusions: The impact on other scientific fields is also explored. Full article

The current research trends of production engineering are based on optimizing the machining process concerning human and environmental factors. High-performance materials, such as hardened steels, nickel-based alloys, fiber-reinforced polymer (FRP) composites, and titanium alloys, are classified as hard-to-cut due to their ability to maintain strength at high operating temperatures. Due to these characteristics, such materials are employed in applications such as aerospace, marine, energy generation, and structural. The purpose of this article is to investigate the machinability of these alloys under various cutting conditions. The purpose of this article is to compare cryogenic cooling and cryogenic processing from the perspective of machinability and sustainability in the manufacturing process. Compared to conventional machining, hybrid techniques, which mix cryogenic and minimal quantity lubricant, led to significantly reduced cutting forces of 40–50%, cutting temperatures and surface finishes by approximately 20–30% and more than 40%, respectively. A carbon footprint is determined by several factors including power consumption, energy requirements, and carbon dioxide emissions. As a result of the cryogenic technology, the energy consumption, power consumption, and CO₂ emissions were reduced by 40%, 28%, and 35%. Full article

Background/Objectives: The oral cavity represents a convenient route of administration for drugs that exhibit significant hepatic first-pass extraction. In this study, the mucosal permeation properties of selected active pharmaceutical ingredients (APIs) incorporated into oral cavity drug products that are approved by the U.S. Food and Drug Administration were quantified using the human-derived sublingual HO-1-u-1 and buccal EpiOral™ in vitro tissue models. Methods: Epithelial barrier properties were monitored using propranolol and Lucifer Yellow as prototypic transcellular and paracellular markers. APIs were dissolved in artificial saliva, pH 6.7, and transepithelial flux from the apical to the basolateral compartment was quantified using HPLC. Results: Apparent permeability coefficients (Papp) calculated for these APIs in the sublingual HO-1-u-1 tissue model varied from Papp = 2.72 ± 0.06 × 10⁻⁵ cm/s for asenapine to Papp = 6.21 ± 2.60 × 10⁻⁵ cm/s for naloxone. In contrast, the buccal EpiOral™ tissue model demonstrated greater discrimination power in terms of permeation properties for the same APIs, with values ranging from Papp = 3.31 ± 0.83 × 10⁻⁷ cm/s for acyclovir to Papp = 2.56 ± 0.68 × 10⁻⁵ cm/s for sufentanil. The tissue-associated dose fraction recovered at the end of the transport experiment was significantly increased in the buccal EpiOral™ tissue model, reaching up to 8.5% for sufentanil. Conclusions: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. Following a robust in vitro–in vivo correlation analysis, it is expected that such innovative in silico modeling strategies will the accelerate development of generic oral cavity products by facilitating the utility of model-integrated evidence to support decision making in generic drug development and regulatory approval. Full article

In the era of low-carbon economy, green mergers and acquisitions (green M&As) have emerged as a pivotal strategic pathway for heavily polluting enterprises to not only carve out a competitive edge in the market but also contribute significantly to the achievement of Sustainable Development Goal 12 (SDG 12)—Responsible Consumption and Production. Based on the data of China’s heavily polluting enterprises listed on the Shanghai and Shenzhen A-share markets from 2010 to 2022, this study applies the multi-temporal difference-in-differences method to analyze the impact of green M&As on the market power of heavily polluting enterprises. The findings suggest that the adoption of green M&As by heavily polluting enterprises in China can enhance market power, and this conclusion remains valid after a series of robustness tests. The mediation effect analysis shows that green M&As promote the market power of heavily polluting enterprises by increasing green total factor productivity, optimizing human capital structure and enhancing brand capital. Meanwhile, according to the heterogeneity study conducted, the implementation of green M&As by non-state-owned heavily polluting enterprises and heavily polluting enterprises within the growth period has a more pronounced effect on market power promotion. In addition, domestic green M&As have a stronger effect on the market power of heavily polluting enterprises. By bridging the theoretical gap between green M&As and the driving mechanisms of market power, this study not only enriches the academic literature but also provides actionable insights for heavily polluting enterprises seeking to enhance their market competitiveness while adhering to sustainable development principles. Full article

Recent advances highlight the crucial role of the gut microbiota in human health and disease, with dietary components emerging as powerful modulators of microbial communities. This review synthesizes current evidence on the effects of olive-derived bioactive compounds, including polyphenols (e.g., hydroxytyrosol, oleuropein or tyrosol), triterpenes and other phytochemicals on gut microbiota composition and function. These compounds have been shown to enhance beneficial bacterial populations such as Lactobacillus and Bifidobacterium, reduce potentially pathogenic taxa, and promote the production of short-chain fatty acids and other health microbial metabolites, reinforcing intestinal barrier integrity. In vitro, in vivo, and clinical studies also reveal the potential of olive bioactives to ameliorate metabolic, inflammatory, and neurocognitive disorders through gut-microbiota-brain axis modulation. Despite promising results, key challenges remain, including interindividual microbiota variability, lack of standardized intervention protocols, and limited human clinical trials. Addressing these gaps through robust translational research could pave the way for microbiota-targeted, personalized nutritional strategies based on olive-derived compounds. Full article

The rapid progress of Large Language Models (LLMs) has greatly improved natural language tasks like code generation, boosting developer productivity. However, challenges persist. Generated code often appears “pseudo-correct”—passing functional tests but plagued by inefficiency or redundant structures. Many models rely on outdated methods like greedy selection, which trap them in local optima, limiting their ability to explore better solutions. We propose AnnCoder, a multi-agent framework that mimics the human “try-fix-adapt” cycle through closed-loop optimization. By combining the exploratory power of simulated annealing with the targeted evolution of genetic algorithms, AnnCoder balances wide-ranging searches and local refinements, dramatically increasing the likelihood of finding globally optimal solutions. We speculate that traditional approaches may struggle due to narrow optimization focuses. AnnCoder addresses this by introducing dynamic multi-criteria scoring, weighing functional correctness, efficiency (e.g., runtime/memory), and readability. Its adaptive temperature control dynamically modulates the cooling schedule, slowing cooling when solutions are diverse to encourage exploration, then accelerating convergence as they stabilize. This design elegantly avoids the pitfalls of earlier models by synergistically combining global exploration with local optimization capabilities. After conducting thorough experiments with multiple LLMs analyses across four problem-solving and program synthesis benchmarks—AnnCoder showcased remarkable code generation capabilities—HumanEval 90.85%, MBPP 90.68%, HumanEval-ET 85.37%, and EvalPlus 84.8%. AnnCoder has outstanding advantages in solving general programming problems. Moreover, our method consistently delivers superior performance across various programming languages. Full article

In the shift toward sustainable and resource-efficient manufacturing, Artificial Intelligence (AI) is playing a transformative role in overcoming the limitations of traditional production scheduling methods. This study, based on a Systematic Literature Review (SLR), explores how AI techniques enhance Advanced Planning and Scheduling (APS) systems, particularly under finite-capacity constraints. Traditional scheduling models often overlook real-time resource limitations, leading to inefficiencies in complex and dynamic production environments. AI, with its capabilities in data fusion, pattern recognition, and adaptive learning, enables the development of intelligent, flexible scheduling solutions. The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. These AI-powered APS systems enhance scheduling accuracy, reduce lead times, improve resource utilization, and enable the proactive identification of production bottlenecks. Especially relevant in high-variability sectors like fashion, these approaches support Industry 5.0 goals by enabling agile, sustainable, and human-centered manufacturing systems. The findings have been highlighted in a structured framework for AI-based APS systems supported by metaheuristics that compares the Industry 4.0 and Industry 5.0 perspectives. The study offers valuable implications for both academia and industry: academics can gain a synthesized understanding of emerging trends, while practitioners are provided with actionable insights for deploying intelligent planning systems that align with sustainability goals and operational efficiency in modern supply chains. Full article

This paper examines the relationship between investment in water education and economic performance, focusing on the context of widening countries (EU Member States and Associated Countries with lower research and innovation performance). Through time-series data and panel regression analysis, the study investigates whether increased spending on education correlates with Gross Domestic Product (GDP) growth. While the initial static model indicates a positive but statistically insignificant association, a dynamic model with lagged GDP significantly improves explanatory power, suggesting that educational investments may influence growth with a temporal delay. Complementing the macroeconomic data, the paper analyses how targeted investments in educational innovation, especially in digital technologies such as virtual reality (VR) applications, enhance teaching quality and student engagement. Examples from partner universities involved in the WATERLINE project (Horizon Europe, 101071306) show how custom-built VR modules, aligned with existing hydraulic labs, contribute to advanced water-related skills. The paper also presents a cost-benefit analysis of VR applications in water education, highlighting their economic efficiency compared to traditional laboratory equipment. Additionally, it explores how micro-level innovations in education can generate macroeconomic benefits through widespread adoption and systemic impact. Ultimately, the research highlights the long-term value of education and innovation in strengthening both economic and human capital across diverse regions. Full article

The reduction of environmental pollutant emissions—including greenhouse gases, particulate matter, and other harmful substances—represents one of the foremost challenges in climate policy, economics, and industrial management today. Excessive emissions of CO₂, NO_X, and suspended particulates exert significant impacts on climate change as well as human health and welfare. Consequently, numerous studies and regulatory and technological initiatives are underway to mitigate these emissions. One critical area is intra-plant transport within manufacturing facilities, which, despite its localized scope, can substantially contribute to a company’s total emissions. This paper aims to assess the potential of computer simulation using FlexSim software as a decision-support tool for planning inter-operational transport, with a particular focus on environmental aspects. The study analyzes real operational data from a selected production plant (case study), concentrating on the optimization of the number of transport units, their routing, and the layout of workstations. It is hypothesized that reducing the number of trips, shortening transport routes, and efficiently utilizing transport resources can lead to lower emissions of carbon dioxide (CO₂) and nitrogen oxides (NO_X). The findings provide a basis for a broader adoption of digital tools in sustainable production planning, emphasizing the integration of environmental criteria into decision-making processes. Furthermore, the results offer a foundation for future analyses that consider the development of green transport technologies—such as electric and hydrogen-powered vehicles—in the context of their implementation in the internal logistics of manufacturing enterprises. Full article

This study quantitatively evaluates the effects of human activities (HAs) and climate change (CC) on the terrestrial ecosystem carbon cycle, providing a scientific basis for ecosystem management and the formulation of sustainable development policies in urban agglomerations located in arid and ecotone regions. Using the LanXi urban agglomeration in China as a case study, we simulated the spatiotemporal variation of vegetation net primary productivity (NPP) from 2000 to 2023 based on MODIS remote sensing data and the CASA model. Trend analysis and the Hurst index were employed to identify the dynamic trends and persistence of NPP. Furthermore, the Geographical Detector model with optimized parameters, along with nonlinear residual analysis, was employed to investigate the driving mechanisms and relative contributions of HAs and CC to NPP variation. The results indicate that NPP in the LanXi urban agglomeration exhibited a fluctuating upward trend, with an average annual increase of 4.26 gC/m² per year. Spatially, this trend followed a pattern of “higher in the center, lower in the east and west,” with more than 95% of the region showing an increase in NPP. Precipitation, mean annual temperature, evapotranspiration, and land use types were identified as the primary driving factors of NPP change. The interaction among these factors demonstrated a stronger explanatory power through factor coupling. Compared with linear residual analysis, the nonlinear model showed clear advantages, indicating that vegetation NPP in the LanXi urban agglomeration was jointly influenced by HAs and CC. These findings can further act as a basis for resource and environmental research in similar ecotone regions globally, such as Central Asia, the Mediterranean Basin, the southwestern United States, and North Africa. Full article

In the present study, the primary by-products of the hemp-seed oil process—hemp seed cake flour and hemp seed protein concentrate—underwent enzymatic hydrolysis using proteases and carbohydrases, either individually or in combination. The effectiveness of these enzymatic treatments in releasing bioactive compounds was evaluated by assessing the antioxidant and anti-inflammatory properties of the aqueous extracts of both hydrolysed and untreated hemp by-products. The aim was to explore their potential senotherapeutic properties and promote their application as dietary supplements. Secondary metabolites such as flavonoids, phenolic acids, and catechins were analysed using high-performance liquid chromatography. Total phenolic, flavonoid, and protein contents were determined using spectrophotometric methods. Scavenging activity (2,2-Diphenyl-1-picrylhydrazyl scavenging assay (DPPH assay)), antioxidant power (Ferric reducing antioxidant power assay (FRAP assay)), and lipid peroxidation-reducing activity (thiobarbituric acid-reactive substance analysis) were assessed through in vitro assays. Possible anti-inflammatory effects were evaluated by assessing haemolysis inhibition. The impact of extracts on albumin glycation induced by exposure to fructose was also determined. To assess the toxicity of extracts, a zebrafish larvae model was employed. All extracts contained significant amounts of phenolic compounds, flavonoids, and proteins, and they exhibited notable activities in reducing lipid peroxidation and stabilising erythrocyte cell membranes. However, they did not significantly influence protein glycation (the glycation inhibition was only in the range of 15–40%). Our research demonstrates the substantial health-promoting potential, including senescence delay, of aqueous extracts from by-products of the hemp-seed oil process, which are available in large quantities and can serve as valuable supplements to support the health of animals, including humans, rather than being discarded as waste from oil production. Full article