Search Results (1,118)

Chitosanases are glycoside hydrolases (GHs) that catalyze the endo- or exo-type cleavage of β-1,4-glycosidic linkages in chitosan, enabling the selective production of chitooligosaccharides (COSs) with well-defined structures and diverse bioactivities. Owing to their substrate specificity and environmentally friendly catalytic action, chitosanases have garnered increasing attention as sustainable biocatalysts for COS production, with broad application potential in agriculture, food, medicine, and cosmetics. This review provides a comprehensive overview of recent advances in chitosanase research, focusing on the catalytic mechanisms and structure–function relationships that govern substrate selectivity and functional divergence across different GH families. Microbial diversity and heterologous expression systems for chitosanase production are discussed in parallel with biochemical characterization to support the rational selection of enzymes for specific biotechnological applications. Advances in protein engineering and computational approaches are highlighted as strategies to improve catalytic efficiency, substrate range, and stability. In addition, bioprocess optimization is addressed, with emphasis on fermentation using low-cost substrates and the application of immobilized enzymes and nano-biocatalyst systems for green and efficient COS production. Summarizing and discussing previous findings are essential to support future research and facilitate the development of next-generation chitosanases for sustainable industrial use. Full article

Efficient and rational utilization of mineral resources significantly impacts economic and technological development. Image segmentation is a pivotal process in ore sorting, as its results directly affect the accuracy of mineral classification. Traditional segmentation methods often fail to meet the requirements for noise suppression, segmentation precision, and robustness in ore sorting. To address these issues, we propose an ore image segmentation method based on concavity matching via region retrieval, which comprises a contour approximation module, a concavity matching module, and a segmentation detection module. It introduces the concepts of single-contour, multi-contour, and segmentation regions in ore images, offering tailored segmentation approaches for varying adhesion forms and quantities. A significant contribution of this study lies in the contour approximation module, which simplifies the edge information of ore images via curve fitting, effectively removing the influence of edge noise points. The concavity matching module restricts candidate areas for matching concavity points through the construction of search regions, significantly improving matching accuracy. Finally, paired concavity points are connected to completing the segmentation process. Experimental comparisons using X-ray images of tungsten ores demonstrate that the proposed method can effectively suppress noise-induced concavity interference, achieving a noise reduction efficiency of 94.77% and a concavity region search accuracy of 93.60%, thus meeting the precision requirements for segmenting X-ray ore images. Given its high efficiency and accuracy, industrial sectors involved in mineral processing are recommended to incorporate this segmentation method into intelligent ore sorting equipment upgrading and renovation projects, enhancing the overall efficiency of mineral resource sorting and promoting the sustainable development of the mineral industry. Full article

Bioactive peptides have significant potential for applications in pharmaceuticals, the food industry, and cosmetics due to their wide spectrum of biological activities. However, their pronounced structural and functional heterogeneity complicates the classification and prediction of biological activity. This study uses data from the PepLab platform, comprising 2748 experimentally confirmed bioactive peptides distributed across 15 functional classes, including ACE inhibitors, antimicrobial, anticancer, antioxidant, toxins, and others. For each peptide, the amino acid sequence and key physicochemical descriptors are provided, calculated via the integrated DMPep module, such as GRAVY index, aliphatic index, isoelectric point, molecular weight, Boman index, and sequence length. The dataset exhibits class imbalance, with class sizes ranging from 14 to 524 peptides. An innovative methodology is proposed, combining descriptive statistical analysis, structural modeling via DEMATEL, and structural equation modeling with neural networks (SEM-NN), where SEM-NN is used to capture complex nonlinear causal relationships between descriptors and functional classes. The results of these dependencies are integrated into a multi-class machine learning model to improve interpretability and predictive performance. Targeted data augmentation was applied to mitigate class imbalance. The developed classifier achieved predictive accuracy of up to 66%, a relatively high value given the complexity of the problem and the limited dataset size. These results confirm that integrating structured dependency modeling with artificial intelligence is an effective approach for functional peptide classification and supports the rational design of novel bioactive molecules. Full article

As urbanization progresses rapidly, cities face growing challenges of land resource scarcity and the pressure on green ecological spaces. This not only affects the sustainable development of cities but also presents a major challenge to the resilience of urban ecosystems (UER). As an emerging land use model, land financialization (LF), which involves the circulation and financing of land as a financial asset, has become an important means to promote UER. Therefore, this paper examines 221 prefecture-level cities across mainland China to explore the impact of land financialization on urban ecological resilience and aims to reveal the specific pathways through which land financialization improves urban ecological resilience through mechanisms like resource reallocation, industrial structure rationalization, green innovation, green signals, and environmental regulation. This paper employs a two-way fixed effects model, robustness tests, and endogeneity tests, supplemented by mechanism and heterogeneity analysis, to explore the impact of LF on UER. The findings show that LF plays a significant role in improving UER. Mechanism analysis reveals that LF significantly boosts UER by optimizing the distribution of land and financial resources, as well as enhancing the rationalization of the industrial structure. Additionally, enterprise green technology innovation, green value, and the intensity of environmental regulation play a positive moderating role in this process. In addition, the heterogeneity analysis reveals the inclusive characteristics of LF on urban ecological transformation. In cities with higher levels of land price distortion, as well as in old industrial cities, small cities, and peripheral cities with poorer resource characteristics and administrative resources, LF has a more significant impact on promoting the improvement of UER. Based on the findings, this paper proposes policy recommendations to promote the improvement of urban green ecology and support the innovation of land financialization. These insights contribute to the theoretical discourse on greenization and provide essential, practical guidance for optimizing the allocation of land and financial resources, as well as establishing a framework for green and high-quality development. Full article

The purpose of this study is to systematically examine the impact of technological innovation on the coordinated development of regional economies and its internal mechanism. It is aimed at revealing whether and how technological innovation promotes the coordinated development of regional economies, and further identifying its heterogeneity characteristics and boundary conditions in the space–time dimension. The research was conducted using panel data for 258 prefecture-level cities in China from 2011 to 2021. This study found that technological innovation significantly promoted the coordinated development of regional economies; this effect was more prominent in China’s eastern region and the Yangtze River Economic Belt. The mechanism test shows that technological innovation can optimize regional resource allocation and narrow the development gap by promoting industrial structure upgrades and rationalization. Further analysis shows that the level of marketization has a nonlinear regulatory effect on the coordination effect of technological innovation, with two threshold levels. A heterogeneity analysis reveals significant differences in the effects of technological innovation in different regions in China, especially in the western region and the northwest side of the Hu Changyong line. The research leads to four key policy recommendations. First, it is important to strengthen the core driving role of technological innovation and implement regionally differentiated innovation support policies. Second, industrial structure upgrades should be encouraged through industrial chain coordination. The third recommendation is to improve the market-oriented institutional environment and minimize barriers to factor flow. Fourth, supporting coordinated policies, such as optimizing human capital and introducing high-quality foreign capital, is necessary to establish a sustainable long-term mechanism for regional coordinated development. Full article

This study investigated the impact of green tea addition on microbial community dynamics during Daqu fermentation, a critical process in traditional baijiu production. Four Daqu variants (0%, 10%, 20%, 30% tea) were analyzed across six fermentation periods using 16S rRNA/ITS sequencing, coupled with STR, TDR, Sloan neutral model, and phylogenetic analyses. Results showed time-dependent increases in bacterial/fungal richness, with 30% tea maximizing species richness. Tea delayed bacterial shifts until day 15 but accelerated fungal reconstruction from day 6, expanding the temporal response window. While stochastic processes dominated initial assembly (77–94% bacteria, 88–99% fungi), deterministic processes intensified with tea concentration, particularly in fungi (1% → 12%). Tea increased bacterial dispersal limitation and reduced phylogenetic conservatism of endogenous factors. This work proposed a framework for rationally engineering fermentation ecosystems by decoding evolutionary-ecological rules of microbial assembly. It revealed how plant-derived additives can strategically adjust niche partitioning and ancestral constraints to reprogram microbiome functionality. These findings provided a theoretical foundation in practical strategies for optimizing industrial baijiu production through targeted ecological interventions. Full article

The development and implementation of scientifically substantiated solutions for the improvement and modernization of electromechanical devices, systems, and complexes, including electric drives, is an urgent theoretical and applied task for energetics, industry, transport, and other key areas, both in global and national contexts. The aim of this paper is to identify a rational model of an induction motor that balances computational simplicity and control system performance based on predictive approaches while ensuring maximum energy efficiency and reference tracking during the operation in dynamic modes. Five main mathematical models of an induction machine with different levels of detail have been selected. Three predictive control models have been implemented using GRAMPC (v 2.2), Matlab MPC Toolbox (v 24.1), and fmincon (R2024a) (from Matlab Optimization Toolbox). It has been established that in the dynamic mode of operation, the equivalent induction motor circuit with parameters $R_{fe} =const$, $L_{\mu }=f\left(I_{1d}\right)$, and $T_F=f\left({\omega }_{Rm}\right)$ is the most appropriate in terms of the following criteria: accuracy of control action generation, computation speed, and calculation of energy consumption. Full article

The aim of this study was to investigate microstructure and the mechanical and operational characteristics of thick and thin walls 3D-built by electron beam additive manufacturing (EBAM). In addition, the milling parameters (rotation speed, feed, and cutting width) were optimized based on simultaneous assessments of Ra roughness on the machined surfaces and material removing rate values. The wall dimensions did not exert a noticeable effect on their chemical compositions, as compared with the original wires used for 3D printing. In comparison, the strength characteristics of the wrought steel (cold-rolled plate) were higher due to finer grains, with both ferrite content and dislocation density being greater as well. In the 3D building process, multiple thermal cycles gave rise to the formation of elongated columnar grains, reducing the strength characteristics. The corrosion rate of the wrought steel was almost twice those of the 3D-printed blanks because of the higher content of both ferrite and twins. By assessing the machinability of the EBAM-built blanks using the stationary milling machine, the cutting forces were comparable due to similar mechanical properties (including microhardness). To improve the removing rate values and reduce the cutting forces, it is recommended to enhance the cutting speeds while not increasing the feeds. For the semi-industrial milling machine, both linear multiple regression and nonlinear neural network models were applied. An integrated approach was proposed that rationally determined both additive manufacturing and post-processing parameters based on a combination of express assessment and analysis of the mechanical, operational, and technological characteristics of built products within a single laboratory complex. Full article

As a key component of new infrastructure, smart logistics is becoming an essential driver for reducing foreign trade costs and risks and promoting the sustainable development of foreign trade. Using panel data from 286 prefecture level and above cities from 2014 to 2023, this article attempts to refine the measurement of smart logistics level from provincial to municipal levels, construct a two-way fixed effect model and a mediation effect model, and deeply explore the inherent relationship between smart logistics, industrial structure upgrading, and sustainable development of foreign trade. The results reveal that: (1) smart logistics significantly promotes the sustainable development of foreign trade. (2) Rationalization and advancement of industrial structure play an intermediary role between the two. (3) Market integration has a positive moderating effect on the path of “smart logistics—industrial structure rationalization”, but the moderating effect is not significant in other paths. It has been confirmed that there is a “siphon effect” in the advantageous regions. (4) Heterogeneity analysis shows that the effect of smart logistics on foreign trade promotion is more significant in the central and inland regions. This study provides a theoretical basis and practical inspiration for optimizing regional smart logistics layout and deepening industrial structure adjustment. Full article

Zearalenone (ZEN), a mycotoxin produced by Fusarium species, widely contaminates grains and feed, posing a serious threat to animal and human health. Traditional physical and chemical detoxification methods face challenges, including low efficiency, high costs, and nutrient loss. In contrast, enzymatic biodegradation has emerged as a research hotspot due to its high efficiency, specificity, and environmental friendliness. Lactone hydrolase can specifically hydrolyze the lactone ring of ZEN, converting it into a low-toxicity or non-toxic degradation product, thereby demonstrating significant potential for application in ensuring the safety of food, feed, and agricultural products. In recent years, with advancements in enzyme engineering and various biological technologies, remarkable progress has been made in ZEN-degrading enzyme research. Novel and highly efficient enzyme genes have been discovered through gene mining, while directed evolution and rational design have improved catalytic efficiency and stability. Additionally, immobilization techniques and formulation optimization have enhanced industrial applicability. This review, based on practical application needs, establishes a comprehensive evaluation system integrating enzyme characteristics, modification technologies, and process applicability, aiming to provide actionable theoretical guidance for the large-scale application of biological detoxification technologies. Full article

The development of highly efficient catalysts for the hydrogenation of dicyclopentadiene (DCPD) remains a critical challenge. In this study, we designed a series of bimetallic Ce–Ni metal–organic framework (MOF)-derived nanocatalysts by precisely tuning the Ce/Ni ratio and calcination temperatures. The optimized catalyst, Ni–CeO_2(7:3) @C–400 °C, featuring highly dispersed carbon-coated Ni nanoparticles, achieved complete hydrogenation of DCPD to tetrahydrodicyclopentadiene (THDCPD) with 100% conversion and nearly 100% selectivity within 2 h under 100 °C and 2 MPa. The porous carbon framework significantly facilitated the diffusion and accessibility of DCPD molecules, combined with Ce species reconstructing the electronic structure of Ni active centers through electronic interactions, synergistically enhancing the hydrogenation efficiency. Furthermore, the catalyst demonstrated good structural stability. This work not only provides a robust strategy for the rational design of bimetallic MOF-derived catalysts but also highlights their potential for practical applications in industrial hydrogenation processes. Full article

In the conditions of modern production, the choice of a rational technological process is crucial for the competitiveness and efficiency of enterprises. Traditional decision-making methods are often accompanied by subjectivity and insufficient precision, which determines the need for the implementation of modern information technologies. This paper addresses the selection of an optimal technological process through the application of a developed web-based software application. The software application integrates an algorithm in which a multi-criteria decision-making (MCDM) method—FUCOM (Full Consistency Method)—is implemented, which allows the evaluation and comparison of alternative technological processes according to criteria such as price, time to produce, accuracy, roughness, shape deviation, etc. To confirm the effectiveness of the application, real production data is used, and the results show a significant reduction in time and subjectivity in decision-making. The developed application can be successfully implemented in enterprises of different industries, contributing to the increase in the efficiency of production processes and the optimization of resources. Full article

Mastitis, an inflammatory disease caused by the invasion of various pathogenic microorganisms into mammary gland tissue, is a core health issue plaguing the global dairy industry. The consequences of this disease are manifold. In addition to directly compromising the health and welfare of dairy cows, it also precipitates a substantial decline in lactation function, a precipitous drop in raw milk production, and alterations in milk composition (e.g., increased somatic cell counts and imbalanced ratios of milk protein to fat). These changes result in a marked degradation of milk quality and safety, and in turn, engender significant economic losses for the livestock industry. Therefore, the establishment and implementation of a comprehensive prevention and control system is a key strategy to effectively curb the occurrence of mastitis, reduce its incidence rate, and minimise economic losses. This review systematically explores the complex etiological factors and pathogenic mechanisms of mastitis in dairy cows, and summarises various diagnostic methods, including milk apparent indicators monitoring, pathogen detection, physiological parameter monitoring, omics technologies, and emerging technologies. Furthermore, it undertakes an analysis of treatment protocols for mastitis in dairy cows, with a particular emphasis on the significance of rational antibiotic use and alternative therapies. Moreover, it delineates preventive measures encompassing both environmental and hygiene management, and dairy cow health management. The objective of this paper is to provide a comprehensive and scientific theoretical basis and practical guidance for dairy farming practices. This will help to improve the health of dairy cows, ensure a stable supply of high-quality dairy products, and promote the sustainable and healthy development of the dairy farming industry. Full article

Thiosemicarbazones and thiocarbohydrazones are key sulfur-containing organic compounds known for their diverse biological, pharmaceutical, and industrial applications. Beyond their well-established therapeutic potential, their strong chelating ability allows them to form stable complexes with transition metals, enabling uses in catalysis, corrosion inhibition, and dyeing processes. Their structural characteristics and dynamic conformations critically influence both biological activity and industrial performance, making nuclear magnetic resonance (NMR) spectroscopy an indispensable tool for their analysis. This review provides a comprehensive overview of the conformational and functional properties of bioactive thiosemicarbazones and thiocarbohydrazones, with a focus on how experimental NMR techniques are used to investigate their conformational behavior. In addition to experimental findings, available computational data are discussed, offering complementary insights into their structural dynamics. The integration of experimental and theoretical approaches offers a robust framework for predicting the behavior and interactions of these compounds, thereby informing the rational design of novel derivatives with improved functionality. By highlighting key structural features and application contexts, this work addresses a critical gap in the current understanding of these promising agents across both biomedical and industrial domains. Full article

Potted cultivation serves as a vital strategy for industrialized production of standardized tree peonies, engineering seedlings capable of year-round and off-site transplantation. However, the limited root zone in potted conditions restricts root development, resulting in suboptimal seedling quality and hindering commercial-scale production. This study aimed to investigate the relationship between the accumulation characteristics of non-structural carbohydrates (NSCs) and growth performance in potted tree peonies, while also optimizing the transplantation technologies for potted cultivation. Using two-year-old grafted seedlings of ‘Luoyanghong’ as experimental material, the effects of root pruning, rooting agent, and Metarhizium anisopliae application on morphological development and NSCs accumulation in potted tree peony seedlings were investigated. The results showed that old roots serve as the primary storage organs for NSCs in the potted tree peony. Slight root pruning (25%) was beneficial for fibrous root growth, whereas excessive root pruning (50%) resulted in reduced biomass and NSCs accumulation. The application of a high concentration of rooting agents effectively promoted root growth and mitigated the adverse effects of root pruning. Furthermore, Metarhizium anisopliae significantly increased the stem number in potted tree peonies. The optimal protocol identified through range analysis involved 25% root pruning, followed by irrigation with a solution containing 750 mg·L⁻¹ rooting agent and 20 million spores·mL⁻¹ of Metarhizium anisopliae. The rational distribution of NSCs and coordinated growth across different organs enhanced NSCs accumulation in potted tree peonies. These results demonstrate that combining root pruning with the application of rooting agent and Metarhizium anisopliae can effectively increase NSCs accumulation, optimize plant morphology, and ultimately improve the quality of potted tree peony seedlings. Full article