Search Results (5,204)

Antibiotic resistance is considered to be one of the most complex health obstacles of our time. Methicillin-resistant Staphylococcus aureus (MRSA) represents a global health challenge due to its broad treatment resistance capacity, resulting in high mortality rates. The shikimate pathway (SP) is responsible for the biosynthesis of chorismate from glycolysis and pentose phosphate pathway intermediates. This pathway plays a crucial role in producing aromatic amino acids, folates, ubiquinone, and other secondary metabolites in bacteria. Notably, SP is absent in humans, which makes it a specific and potential therapeutic target to explore for discovering new antibiotics against MRSA. The present study characterized in vitro and in silico natural products as inhibitors of the shikimate dehydrogenase from methicillin-resistant S. aureus (SaSDH). The results showed that, from the set of compounds studied, phloridzin, rutin, and caffeic acid were the most potent inhibitors of SaSDH, with IC₅₀ values of 140, 160, and 240 µM, respectively. Furthermore, phloridzin showed a mixed-type inhibition mechanism, whilst rutin and caffeic acid showed non-competitive mechanisms. The structural characterization of the SaSDH–inhibitor complex indicated that these compounds interacted with amino acids from the catalytic site and formed stable complexes. In biological activity studies against MRSA, caffeic acid showed an MIC of 2.2 mg/mL. Taken together, these data encourage using these compounds as a starting point for developing new antibiotics based on natural products against MRSA. Full article

Rapid data growth in large systems has introduced significant challenges in real-time monitoring and analysis. One of these challenges is detecting anomalies in time series data with high-dimensional inputs that contain complex inter-correlations between them. In addition, the lack of labeled data leads to the use of unsupervised learning that relies on daily system data to train models, which can contain noise that affects feature extraction. To address these challenges, we propose PCA-AAE, a novel anomaly detection model for time series data using an Adversarial Autoencoder integrated with Principal Component Analysis (PCA). PCA contributes to analyzing the latent space by transforming it into uncorrelated components to extract important features and reduce noise within the latent space. We tested the integration of PCA into the model’s phases and studied its efficiency in each phase. The tests show that the best practice is to apply PCA to the latent code during the adversarial training phase of the AAE model. We used two public datasets, the SWaT and SMAP datasets, to compare our model with state-of-the-art models. The results indicate that our model achieves an average F1 score of 0.90, which is competitive with state-of-the-art models, and an average of 58.5% faster detection speed compared to similar state-of-the-art models. This makes PCA-AAE a candidate solution to enhance real-time anomaly detection in high-dimensional datasets. Full article

Understanding the environmental drivers of radial growth in the Pinus massoniana (lamb.) is essential for improving forest productivity and carbon sequestration in subtropical ecosystems. This study used the basal area increment (BAI) as an indicator of radial growth to investigate the main factors affecting the radial growth rate of P. massoniana and the changes in BAI with these factors. A total of 58 high quality tree ring series were analyzed. Six common methods were used to comprehensively analyze the importance of nine factor variables on the BAI, including tree age, competition index, average temperature, and so on. Generalized additive models (GAMs) were developed to explore the nonlinear relationships between each selected variable and the BAI. The results revealed the following: (1) Age and Competition Index was identified as the primary driving force; (2) BAI increased with Age when tree age was below 69 years; (3) from the overall trend, the BAI of P. massoniana decreased with the increase in the Competition Index. These findings provide a scientific basis for developing management plans for P. massoniana forests. Full article

This paper selects 50 listed commercial banks in China from 2012 to 2023 as research samples, and employs the fixed effects model and Hansen’s threshold regression method to systematically examine the impact mechanism and non-linear characteristics of FinTech development on the profitability of commercial banks. The key findings are summarized as follows: (1) FinTech significantly undermines the overall profitability of commercial banks by reshaping the competitive landscape of the industry and intensifying the technology substitution effect. This is primarily reflected in the reduction in traditional interest income and the erosion of market share in intermediary business. (2) Heterogeneity analysis indicates that large state-owned banks and joint-stock banks experience more pronounced negative impacts compared to small and medium-sized banks. (3) Additional research findings reveal a significant single-threshold effect between FinTech and bank profitability, with a critical value of 4.169. When the development level of FinTech surpasses this threshold, its inhibitory effect diminishes substantially, suggesting that after achieving a certain degree of technological integration, commercial banks may partially alleviate external competitive pressures through synergistic effects. This study offers crucial empirical evidence and theoretical support for commercial banks to develop differentiated technology strategies and for regulatory authorities to design dynamically adaptable policy frameworks. Full article

This study explores whether sustainability achievements—proxied through ESG (environmental, social, and governance) reporting—are associated with superior financial performance in Latvia’s manufacturing sector, where ESG maturity remains low and institutional readiness is still emerging. Building on stakeholder, legitimacy, signal, slack resources, and agency theories, this study applies a mixed-method approach (that consists of two analytical stages) suited to the limited availability and reliability of ESG-related data in the Latvian manufacturing sector. Financial indicators from three large firms—AS MADARA COSMETICS, AS Latvijas Finieris, and AS Valmiera Glass Grupa—are compared with industry averages over the 2019–2023 period using independent sample T-tests. ESG integration is evaluated through a six-stage conceptual schema ranging from symbolic compliance to performance-driven sustainability. The results show that AS MADARA COSMETICS, which demonstrates advanced ESG integration aligned with international standards, significantly outperforms its industry in all profitability metrics. In contrast, the other two companies remain at earlier ESG maturity stages and show weaker financial performance, with sustainability disclosures limited to general statements and outdated indicators. These findings support the synergy hypothesis in contexts where sustainability is internalized and operationalized, while also highlighting structural constraints—such as resource scarcity and fragmented data—that may limit ESG-financial alignment in post-transition economies. This study offers practical guidance for firms seeking competitive advantage through strategic ESG integration and recommends policy actions to enhance ESG transparency and performance in Latvia, including performance-based reporting mandates, ESG data infrastructure, and regulatory alignment with EU directives. These insights contribute to the growing empirical literature on ESG effectiveness under constrained institutional and economic conditions. Full article

Short fiber-reinforced polymer (SFRP) has been extensively applied in structural engineering due to its exceptional specific strength and superior mechanical properties. Its mechanical behavior under medium strain rate conditions has become a key focus of ongoing research. A comprehensive understanding of the response characteristics and underlying mechanisms under such conditions is of critical importance for both theoretical development and practical engineering applications. This study proposes an innovative three-dimensional (3D) multiscale constitutive model that comprehensively integrates mesoscopic fiber–matrix interface effects and pore characteristics. To systematically investigate the dynamic response and damage evolution of SFRP under medium strain rate conditions, 3D-printed SFRP porous structures with volume fractions of 25%, 35%, and 45% are designed and subjected to drop hammer impact experiments combined with multiscale numerical simulations. The experimental and simulation results demonstrate that, for specimens with a 25% volume fraction, the strain rate strengthening effect is the primary contributor to the increase in peak stress. In contrast, for specimens with a 45% volume fraction, the interaction between damage evolution and strain rate strengthening leads to a more complex stress–strain response. The specific energy absorption (SEA) of 25% volume fraction specimens increases markedly with increasing strain rate. However, for specimens with 35% and 45% volume fractions, the competition between these two mechanisms results in non-monotonic variations in energy absorption efficiency (EAE). The dominant failure mode under impact loading is shear-dominated compression, with damage evolution becoming increasingly complex as the fiber volume fraction increases. Furthermore, the damage characteristics transition from fiber pullout and matrix folding at lower volume fractions to the coexistence of brittle and ductile behaviors at higher volume fractions. The numerical simulations exhibit strong agreement with the experimental data. Multi-directional cross-sectional analysis further indicates that the initiation and propagation of shear bands are the principal drivers of structural instability. This study offers a robust theoretical foundation for the impact-resistant design and dynamic performance optimization of 3D-printed short fiber-reinforced polymer (SFRP) porous structures. Full article

Kiwifruit (Actinidia spp.) is a globally important economic fruit with high nutritional value. Fruit peelability, defined as the mechanical ease of separating the peel from the fruit flesh, is a critical quality trait influencing consumer experience and market competitiveness and has emerged as a critical breeding target in fruit crop improvement programs. The present review systematically synthesized existing studies on kiwifruit peelability, and focused on its evolutionary trajectory, genotypic divergence, quantitative evaluation, possible underlying mechanisms, and artificial manipulation strategies. Kiwifruit peelability research has advanced from early exploratory studies in New Zealand (2010s) to systematic investigations in China (2020s), with milestones including the development of evaluation metrics and the identification of genetic resources. Genotypic variation exists among kiwifruit genera. Several Actinidia eriantha accessions and the novel Actinidia longicarpa cultivar ‘Guifei’ exhibit superior peelability, whereas most commercial Actinidia chinensis and Actinidia deliciosa cultivars exhibit poor peelability. Quantitative evaluation highlights the need for standardized metrics, with “skin-flesh adhesion force” and “peel toughness” proposed as robust, instrument-quantifiable indicators to minimize operational variability. Mechanistically, peelability is speculated to be governed by cell wall polysaccharide metabolism and phytohormone signaling networks. Pectin degradation and differential distribution during fruit development form critical “peeling zones”, whereas ethylene, abscisic acid, and indoleacetic acid may regulate cell wall remodeling and softening, collectively influencing skin-flesh adhesion. Owing to the scarcity of easy-to-peel kiwifruit cultivars, artificial manipulation methods, including manual peeling benchmarking, lye treatment, and thermal peeling, can be employed to further optimize kiwifruit peelability. Currently, shortcomings include incomplete genotype-phenotype characterization, limited availability of easy-peeling germplasms, and a fragmented understanding of the underlying mechanisms. Future research should focus on methodological innovation, germplasm development, and the elucidation of relevant mechanisms. Full article

Pimelea is one of the highly toxic plants in Australia, particularly affecting cattle. It contains simplexin, a potent toxin that can cause Pimelea poisoning (St. George Disease) in livestock. A survey was conducted to assess the current impact of Pimelea on livestock production, pasture systems, and financial losses among agricultural producers. In addition, information was also sought about the environmental conditions that facilitate its growth and the effectiveness of existing management strategies. The survey responses were obtained from producers affected by Pimelea across nine different Local Government Areas, through three States, viz., Queensland, New South Wales, and South Australia. Pimelea was reported to significantly affect animal production, with 97% of producers surveyed acknowledging its detrimental effects. Among livestock, cattle were the most severely affected (94%), when compared to sheep (13%), goats (3%), and horses (3%). The presence of Pimelea was mostly observed in spring (65%) and winter (48%), although 29% of respondents indicated that it could be present all year-round under favorable rainfall conditions. Germination was associated with light to moderate rainfall (52%), while only 24% linked it to heavy rainfall. Pimelea simplex F. Muell. was the most frequently encountered species (71%), followed by Pimelea trichostachya Lindl. (26%). Infestations were reported to occur annually by 47% of producers, with 41% noting occurrences every 2 to 5 years. Financially, producers estimated average annual losses of AUD 67,000, with 50% reporting an average of 26 cattle deaths per year, reaching up to 105 deaths in severe years. Some producers were spending up to AUD 2100 per annum to manage Pimelea. While chemical and physical controls were commonly employed, integrating competitive pastures and alternative livestock, such as sheep and goats, was considered as a potential management strategy. This study reiterates the need for further research on sustainable pasture management practices to reduce Pimelea-related risks to livestock and agricultural production systems. Full article

A novel centrifuge-less cloud point extraction (CL-CPE) method was developed for the spectrophotometric determination of copper(II) using 4-nitrocatechol (4NC) as the chelating agent. The extraction system utilizes a mixed micellar phase composed of the nonionic surfactant Triton X-114 and the ionic liquid (IL) Aliquat^® 336 (A336). The extracted ternary ion-association complex, identified as (A336⁺)₂[Cu(4NC)₂], exhibits a maximum absorbance at 451 nm, with a molar absorption coefficient of 8.9 × 10⁴ M⁻¹ cm⁻¹ and a Sandell’s sensitivity of 0.71 ng cm⁻². The method demonstrates a linear response in the copper(II) concentration range of 32–763 ng mL⁻¹ and a limit of detection of 9.7 ng mL⁻¹. The logarithmic extraction constant (log K_ex) was determined to be 7.9, indicating efficient extraction. Method performance, evaluated by the Blue Applicability Grade Index (BAGI) and the Click Analytical Chemistry Index (CACI), confirmed its feasibility, practicality, simplicity, convenience, cost-effectiveness, environmental friendliness, and analytical competitiveness. The proposed IL-CL-CPE method was successfully applied to the analysis of a dietary supplement, a solution for infusion, and synthetic mixtures simulating various copper alloys. Full article

The presence of ciprofloxacin antibiotic in water is a threat to humans and aquatic life since antibiotics are currently regarded as emerging contaminants of major concern. This work reported the use of Nexar^TM film, a sulfonated pentablock copolymer, to effectively remove ciprofloxacin antibiotic from water in a sustainable approach. The removal efficiency of Nexar film was evaluated in aqueous or salty (NaCl 0.5 M) ciprofloxacin solutions as a function of contact time and the initial ciprofloxacin concentration. In the investigated conditions, the polymeric film totally removed ciprofloxacin in MilliQ solution while its removal efficiency in salty solution was approximately 73%. This lower value is due to the presence of Na⁺ ions that compete with antibiotic molecules for adsorption on active surface sites of the polymeric film. No further release of adsorbed antibiotic molecules occurred. The kinetic studies, conducted for ciprofloxacin adsorption on Nexar film in both MilliQ and salty solutions, revealed that the overall sorption process is controlled by the rate of surface reaction between ciprofloxacin molecules and active sites on Nexar surface. Furthermore, at equilibrium conditions, the isotherm model that best fits experimental parameters was not linear. This indicates that the competition between the solute and the solvent for binding sites on the adsorbent should be considered to describe adsorption processes in both MilliQ and salty solutions. Full article

The green renovation of existing residential buildings is a key way for the construction industry to achieve sustainable development and the dual carbon goals of China, which makes it urgent to make collaborative decisions among multiple stakeholders. However, because of divergent interests and risk perceptions among governments, energy service companies (ESCOs), and owners, the implementation of green renovation is hindered by numerous obstacles. In this study, we integrated prospect theory and evolutionary game theory by incorporating core prospect-theory parameters such as loss aversion and perceived value sensitivity, and developed a psychologically informed tripartite evolutionary game model. The objective was to provide a theoretical foundation and analytical framework for collaborative governance among stakeholders. Numerical simulations were conducted to validate the model’s effectiveness and explore how government regulation intensity, subsidy policies, market competition, and individual psychological factors influence the system’s evolutionary dynamics. The findings indicate that (1) government regulation and subsidy policies play central guiding roles in the early stages of green renovation, but the effectiveness has clear limitations; (2) ESCOs are most sensitive to policy incentives and market competition, and moderately increasing their risk costs can effectively deter opportunistic behavior associated with low-quality renovation; (3) owners’ willingness to participate is primarily influenced by expected returns and perceived renovation risks, while economic incentives alone have limited impact; and (4) the evolutionary outcomes are highly sensitive to parameters from prospect theory, The system’s evolutionary outcomes are highly sensitive to prospect theory parameters. High levels of loss aversion (λ) and loss sensitivity (β) tend to drive the system into a suboptimal equilibrium characterized by insufficient demand, while high gain sensitivity (α) serves as a key driving force for the system’s evolution toward the ideal equilibrium. This study offers theoretical support for optimizing green renovation policies for existing residential buildings in China and provides practical recommendations for improving market competition mechanisms, thereby promoting the healthy development of the green renovation market. Full article

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

Cucumber, a high-yielding crop commonly grown in facility environments, is particularly susceptible to nitrogen (N) deficiency due to its rapid growth and high nutrient demand. This study used cucumber as its experimental subject and established a spectral dataset of leaves under four nutritional conditions, normal supply, nitrogen deficiency, phosphorus deficiency, and potassium deficiency, aiming to develop an efficient and robust method for quantifying N in cucumber leaves using Raman spectroscopy (RS). Spectral data were preprocessed using three baseline correction methods—BaselineWavelet (BW), Iteratively Improve the Moving Average (IIMA), and Iterative Polynomial Fitting (IPF)—and key spectral variables were selected using 4-Dimensional Feature Extraction (4DFE) and Competitive Adaptive Reweighted Sampling (CARS). These selected features were then used to develop a N content prediction model based on Partial Least Squares Regression (PLSR). The results indicated that baseline correction significantly enhanced model performance, with three methods outperforming unprocessed spectra. A further analysis showed that the combination of IPF, 4DFE, and CARS achieved optimal PLSR model performance, achieving determination coefficients (R²) of 0.947 and 0.847 for the calibration and prediction sets, respectively. The corresponding root mean square errors (RMSEC and RMSEP) were 0.250 and 0.368, while the residual predictive deviation (RPDC and RPDP) values reached 4.335 and 2.555. These findings confirm the feasibility of integrating RS with advanced data processing for rapid, non-destructive nitrogen assessment in cucumber leaves, offering a valuable tool for nutrient monitoring in precision agriculture. Full article

The competitive retention of pollutants in water tables determines their environmental fate and guides routes for their removal. To distinguish the fine differences in competitive binding at zeolite adsorption centers, a group of neonicotinoid pesticides is compared, relying on theoretical (energy of adsorption, orientation, charge distribution) and experimental (spectroscopic and thermogravimetric) analyses for quick, inexpensive, and reliable screening. The MOPAC/QuantumEspresso platform was used for theoretical calculation, indicating close adsorption energy values for acetamiprid and imidacloprid (−2.2 eV), with thiamethoxam having a lower binding energy of −1.7 eV. FTIR analysis confirmed hydrogen bonding, among different dipole-dipole interactions, as the dominant adsorption mechanism. Due to their comparable binding energies, when the mixture of all three pesticides is examined, comparative adsorption capacities are evident at low concentrations, owing to the excellent adsorption performance of the FAU zeotype. At higher concentrations, competition for adsorption centers occurs, with the expected thiamethoxam binding being diminished due to the lower bonding energy. The catalytic impact of zeolite on the thermal degradation of pesticides is evidenced through TG analysis, confirming the adsorption capacities found by UV/VIS and HPLC/UV measurements. Detailed analysis of spectroscopic results in conjunction with theoretical calculation, thermal profiles, and UV detection offers a comprehensive understanding of neonicotinoids’ adsorption and can help with the design of future adsorbents. Full article

Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO₂ emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization. Full article