Search Results (3,174)

Pseudomonas aeruginosa poses significant health threats due to its multidrug-resistant profile, particularly affecting immunocompromised individuals. The pathogen’s ability to produce virulence factors and antibiotic-resistant biofilms, orchestrated through quorum-sensing (QS) mechanisms, complicates conventional therapeutic interventions. This review aims to critically assess the potential of anti-QS strategies as alternatives to antibiotics against P. aeruginosa infections. Comprehensive literature searches were conducted using databases such as PubMed, Scopus, and Web of Science, focusing on studies addressing QS inhibition strategies published recently. Anti-QS strategies significantly attenuate bacterial virulence by disrupting QS-regulated genes involved in biofilm formation, motility, toxin secretion, and immune evasion. These interventions reduce the selective pressure for resistance and enhance antibiotic efficacy when used in combination therapies. Despite promising outcomes, practical application faces challenges, including specificity of inhibitors, pharmacokinetic limitations, potential cytotoxicity, and bacterial adaptability leading to resistance. Future perspectives should focus on multi-target QS inhibitors, advanced delivery systems, rigorous preclinical validations, and clinical translation frameworks. Addressing current limitations through multidisciplinary research can lead to clinically viable QS-targeted therapies, offering sustainable alternatives to traditional antibiotics and effectively managing antibiotic resistance. Full article

Coal serves as the primary energy source for China, with production anticipated to reach 4.76 billion tons in 2024. However, the mining process generates a significant amount of gangue, with approximately 800 million tons produced in 2023 alone. Currently, China faces substantial gangue stockpiles, characterized by a low comprehensive utilization rate that fails to meet the country’s ecological and environmental protection requirements. The environmental challenges posed by the treatment and disposal of gangue are becoming increasingly severe. This review employs bibliometric analysis and theoretical perspectives to examine the latest advancements in gangue utilization, specifically focusing on the application of computational chemistry to elucidate the structural features and interaction mechanisms of coal gangue, and to collate how these insights have been leveraged in the literature to inform its potential utilization routes. The aim is to promote the effective resource utilization of this material, and key topics discussed include evaluating the risks of spontaneous combustion associated with gangue, understanding the mechanisms governing heavy metal migration, and modifying coal byproducts to enhance both economic viability and environmental sustainability. The case studies presented in this article offer valuable insights into the gangue conversion process, contributing to the development of more efficient and eco-friendly methods. By proposing a theoretical framework, this review will support ongoing initiatives aimed at the sustainable management and utilization of coal gangue, emphasizing the critical need for continued research and development in this vital area. This review uniquely combines bibliometric analysis with computational chemistry to identify new trends and gaps in coal waste utilization, providing a roadmap for future research. Full article

Cone Penetration Tests with pore pressure measurements (CPTu) are widely used in geotechnical site investigations due to their high-resolution profiling capabilities. However, traditional interpretation methods—such as the Soil Behavior Type Index ($I_c$)—often fail to capture the internal heterogeneity typical of mining tailings deposits. This study presents a machine learning-based approach to enhance stratigraphic interpretation from CPTu data. Four unsupervised clustering algorithms—k-means, DBSCAN, MeanShift, and Affinity Propagation—were evaluated using a dataset of 12 CPTu soundings collected over a 19-year period from an iron tailings dam in Brazil. Clustering performance was assessed through visual inspection, stratigraphic consistency, and comparison with $I_c$-based profiles. k-means and MeanShift produced the most consistent stratigraphic segmentation, clearly delineating depositional layers, consolidated zones, and transitions linked to dam raising. In contrast, DBSCAN and Affinity Propagation either over-fragmented or failed to identify meaningful structures. The results demonstrate that clustering methods can reveal behavioral trends not detected by $I_c$ alone, offering a complementary perspective for understanding depositional and mechanical evolution in tailings. Integrating clustering outputs with conventional geotechnical indices improves the interpretability of CPTu profiles, supporting more informed geomechanical modeling, dam monitoring, and design. The approach provides a replicable methodology for data-rich environments with high spatial and temporal variability. Full article

Millions of puppies are welcomed into the homes of families around the world each year. However, understanding the ways in which puppies are bred and raised by their breeders, as well as the perspectives and perceptions underpinning these practices, is still in its infancy. The current study administered an online survey to 200 Australian dog breeders to investigate their breeding program characteristics, breeding dog selection, understanding of the importance of early experiences in puppyhood, and the extent and diversity of their puppy rearing and socialisation practices. Results indicated that breeders were motivated by breed improvement and producing dogs for themselves rather than providing companion dogs, despite most of their puppies being placed in companionship roles. The participating breeders also acknowledged the important role they play in shaping puppies’ behaviour and temperament, which was reflected in both their breeding dog selection and in their rearing and socialisation practices. The majority of breeders housed their litters within their residence for the initial weeks of life but the socialisation experiences they provided were variable in type and frequency. Longer-term breeders and those with larger, more intensive programs reported providing human-focused socialisation experiences less frequently, though the correlational nature of these findings require cautious interpretation. Whilst future research should endeavor to explore these results more comprehensively among a more diverse sample, these findings provide valuable insight into the breeding, rearing, and socialisation process undertaken by dog breeders in Australia. Full article

This work contextualizes the possibility of deriving a unifying artificial intelligence framework by walking in the footsteps of General, Explainable, and Verified Artificial Intelligence (GEVAI): by considering explainability not only at the level of the results produced by a specification but also considering the explicability of the inference process as well as the one related to the data processing step, we can not only ensure human explainability of the process leading to the ultimate results but also mitigate and minimize machine faults leading to incorrect results. This, on the other hand, requires the adoption of automated verification processes beyond system fine-tuning, which are essentially relevant in a more interconnected world. The challenges related to full automation of a data processing pipeline, mostly requiring human-in-the-loop approaches, forces us to tackle the framework from a different perspective: while proposing a preliminary implementation of GEVAI mainly used as an AI test-bed having different state-of-the-art AI algorithms interconnected, we propose two other data processing pipelines, LaSSI and EMeriTAte+DF, being a specific instantiation of GEVAI for solving specific problems (Natural Language Processing, and Multivariate Time Series Classifications). Preliminary results from our ongoing work strengthen the position of the proposed framework by showcasing it as a viable path to improve current state-of-the-art AI algorithms. Full article

Sodium chloride is a chemical compound that has been encountered by people for thousands of years, and plays a significant role in their lives. The aim of this article is to provide a comprehensive review of table salt from the perspective of health, food technology, and cultural heritage. The article discusses salt extraction and production, its composition and consumption, and its effects on the human body. The authors draw attention to new trends, such as the use of micronized salt, microencapsulated salt, and salt with colors and shapes that differ from those of typical table salt. Scientific studies on the presence of undesirable substances and the use of salt additives were reviewed. The role of salt in dairy, meat, and bakery technology was illustrated. Gaps in research on salt were highlighted. In the last part, all types of salt with geographical indications are shown. The paper suggests that producers with a long tradition in the salt sector should apply for the European geographical indications to enhance their national and cultural heritage and promote their region. The review highlights the need for further research on all aspects discussed. Full article

With the increasing global emphasis on sustainable development goals, and in the context of pursuing high-quality sustainable development of the economy and enterprises, this study empirically examines the effect of digital finance on corporate financing constraints and the impact on corporate green innovation with a sample of China’s A-share-listed companies in the period of 2011–2020 and explores the issue from the perspectives of management power and corporate social responsibility (CSR) at the micro level of enterprises. The empirical results show that digital finance can indeed alleviate corporate financing constraints. Still, the synergistic effect of the two on corporate green innovation produces a “quantitative and qualitative separation” effect, which only promotes the enhancement of iconic green innovation, and the effect on substantive green innovation is not obvious. The power of management and CSR performanceshave different moderating roles in the alleviation of financing constraints by the empowerment of digital finance. Management power and corporate social responsibility have different moderating effects on digital financial empowerment to alleviate financing constraints. The findings of this study enrich the research in related fields and provide more basis for the promotion of digital financial policies and more solutions for the high-quality development of enterprises. Full article

The growing need to improve the management of end-of-life vehicle (ELV) waste and mitigate its environmental impact is a global concern. One promising approach to enhancing the recyclability of these vehicles is leveraging synergies between the automotive and construction industries as part of a circular economy strategy. In this context, ELV waste emerges as a valuable source of secondary raw materials, enabling the development of sustainable innovations that capitalize on its physical and mechanical properties. This paper aims to develop and evaluate construction industry composites incorporating waste from ELV carpets, with a focus on maintaining or enhancing performance compared to conventional materials. To achieve this, an experimental program was designed to assess cementitious composites, specifically subfloor mortars, incorporating automotive carpet waste (ACW). The results demonstrate that, beyond the physical and mechanical properties of the developed composites, the dynamic stiffness significantly improved across all tested waste incorporation levels. This finding highlights the potential of these composites as an alternative material for impact noise insulation in flooring systems. From an academic perspective, this research advances knowledge on the application of ACW in cement-based composites for construction. In terms of managerial contributions, two key market opportunities emerge: (1) the commercial exploitation of composites produced with ELV carpet waste and (2) the development of a network of environmental service providers to ensure a stable waste supply chain for innovative and sustainable products. Both strategies contribute to reducing landfill disposal and mitigating the environmental impact of ELV waste, reinforcing the principles of the circular economy. Full article

Geographical Indication labels are an increasingly popular alternative among producers and governments seeking to protect the products and producers of their countries. This trend has grown due to the opening of markets and consumers’ increasing desire to know the origin of the products they purchase. A bibliographic review was conducted, including studies on the feasibility of applying quality labels, the associated challenges, and examples. This review identifies the processes involved in obtaining Designation of Origin and presents a positive perspective on their application. It was concluded that obtaining a differentiated quality label can improve production and quality of life, provided that it is the result of an evaluation of the area’s context and the main actors in production chains. Full article

Mangoes are an important part of Hainan’s tropical characteristic agriculture. In response to the requirements of building an ecological civilization pilot demonstration zone in Hainan, China, green and sustainable development will be the future development trend of the mango planting system. However, the economic benefits and environmental impact during its planting and management process remain unclear. This paper combines emergy, life cycle assessment (LCA), and economic analysis to compare the system sustainability, environmental impact, and economic benefits of the traditional mango cultivation system (TM) in Dongfang City, Hainan Province, and the early-maturing mango cultivation system (EM) in Sanya City. The emergy evaluation results show that the total emergy input of EM (1.37 × 10¹⁶ sej ha⁻¹) was higher than that of TM (1.32 × 10¹⁶ sej ha⁻¹). From the perspective of the emergy index, compared with TM, EM exerted less pressure on the local environment and has better stability and sustainability. This was due to the higher input of renewable resources in EM. The LCA results showed that based on mass as the functional unit, the potential environmental impact of the EM is relatively high, and its total environmental impact index was 18.67–33.19% higher than that of the TM. Fertilizer input and On-Farm emissions were the main factors causing environmental consequences. Choosing alternative fertilizers that have a smaller impact on the environment may effectively reduce the environmental impact of the system. The economic analysis results showed that due to the higher selling price of early-maturing mango, the total profit and cost–benefit ratio of the EM have increased by 55.84% and 36.87%, respectively, compared with the TM. These results indicated that EM in Sanya City can enhance environmental sustainability and boost producers’ annual income, but attention should be paid to the negative environmental impact of excessive fertilizer input. These findings offer insights into optimizing agricultural inputs for Hainan mango production to mitigate multiple environmental impacts while enhancing economic benefits, aiming to provide theoretical support for promoting the sustainable development of the Hainan mango industry. Full article

In the twenty-first century, humanity is compelled to face global challenges. Such challenges involve complex systems. However, science has some cognitive and predictive limits in dealing with complex systems. Some of these limits are related to computational complexity and the recognition of variable patterns. To overcome these limits, artificial intelligence (AI) and quantum computing (QC) appear to be helpful. Even more promising is quantum AI (QAI), which emerged from the combination of AI and QC. The combination of AI and QC produces reciprocal, synergistic effects. This work describes some of these effects. It shows that QC offers new materials for implementing AI and innovative algorithms for solving optimisation problems and enhancing machine learning algorithms. Additionally, it demonstrates how AI algorithms can help overcome many of the experimental challenges associated with implementing QC. It also outlines several perspectives for the future development of quantum artificial intelligence. Full article

A multidisciplinary study was conducted to reconstruct the paleoenvironmental evolution of Maladroxia Bay, one of the principal bays of the islet of Sant’Antioco in southwestern Sardinia, over the past eight millennia. As part of an archaeological landscape project, this study explores the paleogeography and environment of the bay from a diachronic perspective to gain insights into the Holocene relative sea level history, shoreline displacements, and the environmental conditions during different phases. This study is based on an analysis of four sediment cores in conjunction with a chronological model that is based on radiocarbon dates. Four relative sea level indicators were produced. These are the first such indicators from the early and middle Holocene for the island of Sant’Antioco. The results indicate that in the early Holocene, the area was a terrestrial, fluvial environment without marine influence. In the 6th millennium BCE, the rising sea level and marine transgression resulted in the formation of a shallow inner lagoon. It reached its maximum extent in the middle of the 5th millennium BCE. Afterwards, a gradual transition from lagoon to floodplain, and a seaward shift of the shoreline occurred. The lagoon potentially served as a valuable source of food and resources during the middle Holocene. During the Nuragic period (2nd to 1st millennium BCE), the Bay of Maladroxia was very similar to how it is today. Its location was ideal for use as an anchorage, due to the calm and sheltered conditions that prevailed. Full article

Carbon cap-and-trade is a practical policy in guiding manufacturers to produce economic and environmental production plans. However, previous studies on carbon cap-and-trade are from a macro level to guide manufacturers to make production plans, rather than from a perspective of specific production scheduling, which leads to a lack of theoretical guidance for manufacturers to develop reasonable production scheduling schemes for specific production orders. This article investigates a specific scheduling problem in a flexible job-shop environment that considers the carbon cap-and-trade policy, aiming to provide guidance for specific production scheduling (i.e., resource allocation). In the proposed problem, carbon emissions have an upper limit. A penalty will be generated if the emissions overpass the predetermined cap. To satisfy the carbon emission cap, the manufacturer can trade carbon credits or adopt outsourcing strategy, that is, outsourcing partial orders to partners at the expense of outsourcing costs. To solve the proposed model, a novel and efficient memetic algorithm (NEMA) is proposed. An initialization method and four local search operators are developed to enhance the search ability. Numerous experiments are conducted and the results validate that NEMA is a superior algorithm in both solution quality and efficiency. Full article

Photovoltaic (PV) micro-installations producing renewable electricity and automatic pellet boilers producing renewable heat energy are promising solutions for single-family houses. A single-family house equipped with a prosumer 7.56 kWp PV micro-installation and a 26 kW pellet boiler was analyzed. This study aimed to analyze the production and use of electricity and heat over three successive years (from 1 January 2021 to 31 December 2023) and to identify opportunities for securing renewable energy supply for the house. Electricity production by the PV was, on average, 6481 kWh year⁻¹; the amount of energy fed into the grid was 4907 kWh year⁻¹; and the electricity consumption by the house was 4606 kWh year⁻¹. The electricity supply for the house was secured by drawing an average of 34.2% of energy directly from the PV and 85.2% from the grid. Based on mathematical modeling, it was determined that if the PV installation had been located to the south (azimuth 180°) in the analyzed period, the maximum average production would have been 6897 kWh. Total annual heat and electricity consumption by the house over three years amounted, on average, to 39,059 kWh year⁻¹. Heat energy accounted for a dominant proportion of 88.2%. From a year-round perspective, a properly selected small multi-energy installation can ensure energy self-sufficiency and provide renewable energy to a single-family house. Full article

The dramatic increase in urban construction waste poses severe environmental challenges. Utilizing waste concrete to produce recycled aggregates (RA) for manufacturing recycled concrete (RC) represents an effective strategy for resource utilization. However, inherent defects in RA, such as high porosity, microcracks, and adherent old mortar layers, lead to significant performance degradation of the resulting RC, limiting its widespread application. Traditional methods for enhancing RA often suffer from limitations, including high energy consumption, increased costs, or the introduction of new pollutants. MICP offers an innovative approach for enhancing RC performance. This technique employs the metabolic activity of specific microorganisms to induce the formation of a three-dimensionally interwoven calcium carbonate gel network within the pores and on the surface of RA. This gel network can improve the inherent defects of RA, thereby enhancing the performance of RC. Compared to conventional techniques, this approach demonstrates significant environmental benefits and enhances concrete compressive strength by 5–30%. Furthermore, embedding mineralizing microbial spores within the pores of RA enables the production of self-healing RC. This review systematically explores recent research advances in microbial mineral gel network for improving RC performance. It begins by delineating the fundamental mechanisms underlying microbial mineralization, detailing the key biochemical reactions driving the formation of calcium carbonate (CaCO₃) gel, and introducing the common types of microorganisms involved. Subsequently, it critically discusses the key environmental factors influencing the effectiveness of MICP treatment on RA and strategies for their optimization. The analysis focuses on the enhancement of critical mechanical properties of RC achieved through MICP treatment, elucidating the underlying strengthening mechanisms at the microscale. Furthermore, the review synthesizes findings on the self-healing efficiency of MICP-based RC, including such metrics as crack width healing ratio, permeability recovery, and restoration of mechanical properties. Key factors influencing self-healing effectiveness are also discussed. Finally, building upon the current research landscape, the review provides perspectives on future research directions for advancing microbial mineralization gel techniques to enhance RC performance, offering a theoretical reference for translating this technology into practical engineering applications. Full article