Search Results (1,296)

High-quality development highlights the importance of environmental protection and green low-carbon development. The high-quality development of the manufacturing industry is not only the key content for achieving green transformation, but also an important cornerstone for building a modern national industrial system. Current research focuses on companies and governments, ignoring the important value of suppliers and consumers. As a result, existing mechanisms have failed to deliver the desired results. This paper constructs an evolutionary game model involving manufacturing enterprises, local governments, suppliers, and consumers, and systematically analyzes the strategy selection process of the four participating populations. On this basis, the impact of exogenous and endogenous factors on the evolutionarily stable strategy is studied at the microscopic level using numerical simulation methods. The results show that (1) increasing any of the endogenous factors, such as innovative capability, organization building, and industrial resources, can accelerate the evolution of manufacturing enterprises evolve to smart upgrade strategy. (2) Increasing any one of the exogenous factors, such as policy environment, industrial cooperation, and market demand, can accelerate the rate at which manufacturing enterprises choose to adopt the strategy of smart upgrade. The purpose of this paper is to provide a theoretical reference for the behavioral strategies of manufacturing enterprises, and to provide a realistic reference for local governments to build a mechanism to promote the high-quality development of the manufacturing industry. Full article

Plant-based extracts and elicitors (signaling molecules that activate the fruit’s innate defense responses) have emerged as promising and sustainable alternatives to synthetic chemicals for preserving postharvest fruit quality and extending shelf life. This review provides a comprehensive analysis, uniquely complemented by a bibliometric assessment of the research landscape from 2005 to 2025, to identify key trends and effective solutions. This review systematically examined the efficacy of various natural compounds including essential oils (complex volatile compounds with potent antimicrobial activity such as lemongrass and thyme), phenolic-rich botanical extracts like neem and aloe vera, and plant-derived elicitors such as methyl jasmonate and salicylic acid. Their preservative mechanisms are multifaceted, involving direct antimicrobial activity by disrupting microbial membranes, potent antioxidant effects that scavenge free radicals, and the induction of a fruit’s innate defense systems, enhancing the activity of enzymes like superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD). Applications of edible coatings of chitosan or aloe vera gel, nano-emulsions, and pre- or postharvest treatments effectively reduce decay by Botrytis cinerea and Penicillium spp.), delay ripening by suppressing ethylene production, minimize water loss, and alleviate chilling injury. Despite their potential, challenges such as sensory changes, batch-to-batch variability, regulatory hurdles, and scaling production costs limit widespread commercialization. Future prospects hinge on innovative technologies like nano-encapsulation to improve stability and mask flavors, hurdle technology combining treatments synergistically, and optimizing elicitor application protocols. This review demonstrates the potential of continued research and advanced formulation to create plant-based preservatives, that can become integral components of an eco-friendly postharvest management strategy, effectively reducing losses and meeting consumer demands for safe, high-quality fruit. Full article

Paulownia trees are grown globally for their robust timber, agroforestry, and effective carbon dioxide drawdown. China possesses rich Paulownia germplasm resources, offering favorable material for the genetic improvement. Understanding the taxonomy and phylogenetic relationships of Paulownia species is essential for the advancement of germplasm innovation. In this study, we re-sequenced 67 typical accessions of 11 species within the Paulownia genus. A total of 16,163,790 high-quality single nucleotide polymorphisms (SNPs) were identified. Based on these markers, these accessions were classified into three groups: P. fortunei and P. lampropylla (Group I); P. tomentosa, P. fargesii, and P. kawakamii (Group II); and P. taiwaniana, P. jianshiensis, P. catalpifolia, P. elongata, P. ichangensis, and P. albiphloea (Group III). Using maximum likelihood estimation, population genetic structure analysis revealed that the 11 species originated from four different ancestral populations. The two predominant breeding species—P. fortunei and P. tomentosa—exhibit divergent origins: P. fortunei arose from hybridization between two ancestral species followed by complex admixture, whereas P. tomentosa retains a predominantly singular ancestral lineage, with traces of P. kawakamii. The genetic diversity (π) of P. tomentosa was 0.002588, which was considerably lower than that of P. fortune (0.004181) suggesting that P. tomentosa is subjected to a stronger breeding selection during the evolution than P. fortune. A total of 59 selected regions and 65 genes were identified by selective sweep analysis. These genes may be involved in biological processes such as morphological development and response to abiotic stress and hormonal activity regulation. These findings provide valuable references for further research on the genetic differentiation and adaptive evolutionary mechanisms of Paulownia species, laying a foundation for future germplasm innovation and variety improvement. Full article

The advancement of sports science has heightened demands for precise monitoring of athletes’ technical movements, physiological status, and performance. Optical fiber sensing (OFS) technology, with its unique advantages including high sensitivity, immunity to electromagnetic interference, capability for distributed sensing, and strong biocompatibility, demonstrates significant application potential in sports science. This review systematically examines the technical principles, innovative breakthroughs, and practical application cases of optical fiber sensors in various domains: monitoring key human physiological parameters such as respiration, heart rate, and body temperature; capturing motion and analyzing movement covering muscle activity, joint angles, and gait; integrating within smart sports equipment and protective gear; and monitoring sports apparatus and environments. The value of OFS technology is further analyzed in areas including sports biomechanics analysis, training load monitoring, injury prevention, and rehabilitation optimization. Concurrently, current technical bottlenecks such as the need for enhanced sensitivity, advancements in flexible packaging technologies, cost control, system integration, and miniaturization are discussed. Future development trends involving the integration of OFS with artificial intelligence, the Internet of Things, and new materials are explored, aiming to provide a theoretical foundation for sports medicine and training optimization. Full article

The development of a multifunctional invention requires several refinements for optimizing each function. This study presents a Theory of Inventive Problem Solving (TRIZ)-based conceptual framework for enhancing an innovative multifunctional assistive technology device that integrates the functionalities of a rollator walker, wheelchair, Pilates chair, and stepladder. The limitations of the multifunctional rollator walker were identified from the user feedback of a foundational work and were then addressed by identifying the engineering and physical contradictions and problem modeling using Su-field analysis. Through TRIZ Inventive Principles, the proposed design eliminates common trade-offs between portability, stability, and usability. The conceptual enhancement incorporates features such as deployable steps, the utilization of high strength–to–weight ratio material, foldability, a passive mechanical brake-locking system, retractable armrests, the incorporation of spring-assist hinges, and the use of large tires with vibration-dampening hubs. This study contributes a novel, user-focused, and space-saving mobility solution that aligns with the evolving demands of assistive technology, laying the groundwork for future iterations involving smart control, power assist, and modular enhancements. Full article

Background: Sustained-release (SR) formulations of non-steroidal anti-inflammatory drugs (NSAIDs) aim to prolong therapeutic activity, reduce dosing frequency, and improve patient adherence. However, currently marketed SR NSAIDs exhibit persistent limitations, including incomplete control over release kinetics, high interpatient variability in bioavailability, limited reduction in gastrointestinal adverse effects, and insufficient dose flexibility for individualized therapy. In many cases, conventional excipients and release mechanisms remain predominant, leaving drug-specific physicochemical and pharmacokinetic constraints only partially addressed. These gaps highlight the need for a comprehensive synthesis of recent technological advances to guide the development of more effective, patient-centered delivery systems. Methods: A narrative literature review was conducted using Web of Science and PubMed databases to identify original research articles and comprehensive technological studies on oral SR formulations of NSAIDs and paracetamol published between January 2020 and March 2025. Inclusion criteria focused on preclinical and technological research addressing formulation design, excipient innovations, and manufacturing approaches. Results: Sixty-four studies met the inclusion criteria, encompassing polymeric matrices (31%), lipid-based carriers (18%), microspheres/hydrogel beads/interpenetrating polymer networks (30%), nanostructured systems (11%), and hybrid platforms (10%). The most common strategies involved pH-dependent release, mucoadhesive systems, and floating drug delivery, aiming to optimize release kinetics, minimize mucosal irritation, and sustain therapeutic plasma levels. Advances in manufacturing—such as hot-melt extrusion, 3D printing, electrospinning, and spray drying—enabled enhanced control of drug release profiles, improved stability, and in some cases up to 30–50% prolongation of release time or reduction in Cmax fluctuations compared with conventional formulations. Conclusions: Recent formulation strategies show substantial potential to overcome long-standing limitations of SR NSAID delivery, with expected benefits for patient compliance and quality of life through reduced dosing frequency, better tolerability, and more predictable therapeutic effects. Nevertheless, integration of in vitro performance with pharmacokinetic and clinical safety outcomes remains limited, and the translation to clinical practice is still in its early stages. This review provides a comprehensive overview of current technological trends, identifies persisting gaps, and proposes future research directions to advance SR NSAID systems toward safer, more effective, and patient-focused therapy. Full article

The electrification of agricultural equipment is a critical pathway to address the dual challenges of increasing global food production and ensuring sustainable agricultural development. As the core power unit, the permanent magnet synchronous motor (PMSM) drive system faces severe challenges in achieving high performance, robustness, and reliable control in complex farmland environments characterized by sudden load changes, extreme operating conditions, and strong interference. This paper provides a comprehensive review of key technological advancements in PMSM drive systems for agricultural electrification. First, it analyzes solutions to enhance the reliability of power converters, including high-frequency silicon carbide (SiC)/gallium nitride (GaN) power device packaging, thermal management, and electromagnetic compatibility (EMC) design. Second, it systematically elaborates on high-performance motor control algorithms such as Direct Torque Control (DTC) and Model Predictive Control (MPC) for improving dynamic response; robust control strategies like Sliding Mode Control (SMC) and Active Disturbance Rejection Control (ADRC) for enhancing resilience; and the latest progress in fault-tolerant control architectures incorporating sensorless technology. Furthermore, the paper identifies core challenges in large-scale applications, including environmental adaptability, real-time multi-machine coordination, and high reliability requirements. Innovatively, this review proposes a closed-loop intelligent control paradigm encompassing environmental disturbance prediction, control parameter self-tuning, and actuator dynamic response. This paradigm provides theoretical support for enhancing the autonomous adaptability and operational quality of agricultural machinery in unstructured environments. Finally, future trends involving deep AI integration, collaborative hardware innovation, and agricultural ecosystem construction are outlined. Full article

Background/Objectives: The increasing global population and rising demand for protein-rich foods present significant challenges for the agri-food system. Cultivated meat, produced through cellular agriculture, is emerging as a promising alternative to traditional livestock farming, offering potential environmental and ethical benefits. However, its adoption remains controversial due to concerns about sustainability, safety, and cultural acceptance. This study investigates Italian consumers’ perceptions, knowledge, and willingness to purchase cultivated meat, considering psychological, demographic, and social factors. Methods: A structured online survey was conducted involving 437 Italian meat consumers, integrating established psychometric scales to assess key attitudes. Logistic regression analysis was applied to identify determinants of consumer acceptance. Results: Findings reveal that while awareness of cultivated meat is relatively high (81.92%), willingness to purchase it is low, at just 35.47%. The main motivations for interest are environmental sustainability (54.61%) and innovation appeal (25.00%), while the primary barriers are health concerns (31.58%) and doubts about production processes (34.59%). The results also show that food neophobia, environmental awareness, and inclination toward food innovation significantly influence purchasing decisions. Additionally, demographic factors, such as age, gender, income, and household size, play a crucial role. Conclusions: This study provides insights into consumer behavior toward food innovations, informing policymakers and industry stakeholders on strategies to enhance acceptance and promote sustainable food alternatives. Full article

Achieving climate protection goals in the transport sector requires the adoption of innovative mobility solutions and new vehicle concepts. In Germany, commercial transport accounts for one-quarter of the total car mileage. Many of these trips are comparatively short, often involve a single passenger, and require the transport of only small or lightweight goods—yet they are typically carried out by car. Substituting cars with small and light electric vehicles (LEVs) wherever feasible could make commercial transport more efficient and environmentally friendly. LEVs combine a favorable weight-to-payload ratio with the high efficiency of electric drivetrains. This study estimates the share of car trips in commercial transport in Germany that could theoretically be substituted by LEVs. The analysis is based on a comparison of trip characteristics from a national travel survey with the technical capabilities of selected LEV categories. Our results indicate that up to 73% of commercial car trips and 44% of mileage could theoretically be covered by LEVs, with particularly high potential for trips in commercial passenger transport. Although limitations in range and payload restrict the universal applicability of LEVs, the findings reveal substantial opportunities to make commercial transport cleaner and more sustainable. These insights highlight the relevance of LEVs for sustainable commercial transport and offer a data-driven basis for further discussion of their potential and for guiding targeted policy and planning. Full article

Wildfires pose a regularly increasing threat to ecosystems and critical infrastructure. The severity of this threat is steadily increasing. The growing threat necessitates the development of technologies for rapid and accurate early detection. However, the prevailing fire point detection algorithms, including several deep learning models, are generally constrained by the inherent hard threshold limitations in their decision-making logic. As a result, these methods lack adaptability and robustness in complex and dynamic real-world scenarios. To address this challenge, the present paper proposes an innovative two-stage, semi-supervised anomaly detection framework. The framework initially employs a Transformer-based autoencoder, which serves to transform raw fire-free time-series data derived from satellite imagery into a multidimensional deep anomaly feature vector. Self-supervised learning achieves this transformation by incorporating both reconstruction error and latent space distance. In the subsequent stage, a semi-supervised XGBoost classifier, trained using an iterative pseudo-labeling strategy, learns and constructs an adaptive nonlinear decision boundary in this high-dimensional anomaly feature space to achieve the final fire point judgment. In a thorough validation process involving multiple real-world fire cases in Yunnan Province, China, the framework attained an F1 score of 0.88, signifying a performance enhancement exceeding 30% in comparison to conventional deep learning baseline models that employ fixed thresholds. The experimental results demonstrate that by decoupling feature learning from classification decision-making and introducing an adaptive decision mechanism, this framework provides a more robust and scalable new paradigm for constructing next-generation high-precision, high-efficiency wildfire monitoring and early warning systems. Full article

The increase in electrification and desire for greater electrical motor efficiency under a range of operating conditions for different products (e.g., household appliances, automotive and aerospace) is driving innovative motor designs and demands for higher performing electrical steels. Improvements in the magnetic, electrical and/or mechanical properties of electrical steels are required for high-volume electric motors and recent advances include steels with increased silicon (Si) content (from <3.5 wt% Si up to 6.5 wt%). Whilst the 6.5 wt% Si steels provide increased motor performance at high frequencies, the formation of a brittle BCC B2/D03 phase means that they cannot be cold-rolled, and therefore the production route involves siliconization after the required thickness strip is produced. The advances in computationally driven alloy design, coupled with physical metallurgical understanding, allow for more adventurous alloy design for electrical steels, outside the traditional predominantly Fe-Si compositional space. Two alloys representing a new alloy family called HiPPES (High-Performing and Processable Electrical Steel), based on low cost commonly used steel alloying elements, have been developed, cast, rolled, heat-treated, and both magnetically and mechanically tested. These alloys (with nominal compositions of Fe-3.2Mn-3.61Si-0.63Ni-0.75Cr-0.15Al-0.4Mo and Fe-2Mn-4.5Si-0.4Ni-0.75Cr-0.09Al) offer improvements compared to current ≈3 wt% Si grades: in magnetic performance (>25% magnetic loss reduction at >1 kHz), and in tensile strength (>33% increase in tensile strength with similar elongation value). Most importantly, they are maintaining processability to allow for full-scale commercial production using traditional continuous casting, hot and cold rolling, and annealing. The new alloys also showed improved resilience to grain size, with the HiPPES materials showing a <5% variance in loss at frequencies greater than 400 Hz for grain sizes between 55 and 180 µm. Comparatively, a commercial M250-35A material showed a 40% increase in loss for the same range. The paper reports on the alloy design approach used, the microstructures, and the mechanical, electrical and magnetic properties of the developed novel electrical steels compared to conventional ≈3 wt% Si and 6.5 wt% Si material. Full article

Advancements in unmanned aerial vehicle (UAV) multispectral systems offer robust technical support for the precise and efficient estimation of japonica rice yield in cold regions within the framework of precision agriculture. These innovations also present a viable alternative to conventional yield estimation methods. However, recent research suggests that reliance solely on vegetation indices (VIs) may result in inaccurate yield estimations due to variations in crop cultivars, growth stages, and environmental conditions. This study investigated six fertilization gradient experiments involving two conventional japonica rice varieties (KY131, SJ22) and two hybrid japonica rice varieties (CY31, TLY619) at Yanjiagang Farm in Heilongjiang Province during 2023. By integrating UAV multispectral data with machine learning techniques, this research aimed to derive critical phenotypic parameters of rice and estimate yield. This study was conducted in two phases: In the first phase, models for assessing phenotypic traits such as leaf area index (LAI), canopy cover (CC), plant height (PH), and above-ground biomass (AGB) were developed using remote sensing spectral indices and machine learning algorithms, including Random Forest (RF), XGBoost, Support Vector Regression (SVR), and Backpropagation Neural Network (BPNN). In the second phase, plot yields for hybrid rice and conventional rice were predicted using key phenotypic parameters at critical growth stages through linear (Multiple Linear Regression, MLR) and nonlinear regression models (RF). The findings revealed that (1) Phenotypic traits at critical growth stages exhibited a strong correlation with rice yield, with correlation coefficients for LAI and CC exceeding 0.85 and (2) the accuracy of phenotypic trait evaluation using multispectral data was high, demonstrating practical applicability in production settings. Remarkably, the R² for CC based on the RF algorithm exceeded 0.9, while R² values for PH and AGB using the RF algorithm and for LAI using the XGBoost algorithm all surpassed 0.8. (3) Yield estimation performance was optimal at the heading (HD) stage, with the RF model achieving superior accuracy (R² = 0.86, RMSE = 0.59 t/ha) compared to other growth stages. These results underscore the immense potential of combining UAV multispectral data with machine learning techniques to enhance the accuracy of yield estimation for cold-region japonica rice. This innovative approach significantly supports optimized decision-making for farmers in precision agriculture and holds substantial practical value for rice yield estimation and the sustainable advancement of rice production. Full article

Triple-negative breast cancer (TNBC) remains one of the most aggressive and treatment-resistant forms. TNBC is an aggressive and therapeutically resistant subtype of breast cancer, marked by the absence of estrogen, progesterone, and HER2 receptors. The lack of defined molecular targets significantly limits treatment options and contributes to high recurrence rates. Among the key pathways involved in TNBC progression and resistance, the CXCR4/CXCL12 chemokine axis has emerged as a critical player. CXCR4, a G-protein-coupled receptor, binds specifically to its ligand CXCL12, promoting tumour cell proliferation, metastasis, immune evasion, and stromal remodelling. Its overexpression is frequently associated with poor prognosis, disease progression, and resistance to conventional therapies in TNBC. This review explores how the chemokine receptor type 4 (CXCR4/CXCL12) axis facilitates drug resistance through mechanisms such as epithelial–mesenchymal transition (EMT), cancer stemness, and microenvironmental interactions. Notably, CXCR4 antagonists like plerixafor, balixafortide, and POL5551 have shown encouraging preclinical and clinical results, particularly when combined with chemotherapy or immunotherapy. Additionally, innovative strategies, including radiopharmaceuticals, peptide inhibitors, and nanotechnology-based delivery platforms, offer expanded therapeutic avenues. Despite persistent challenges such as tumour heterogeneity and potential toxicity, growing clinical evidence supports the translational relevance of this axis. This manuscript provides an in-depth analysis of CXCR4/CXCL12-mediated drug resistance in TNBC and evaluates current and emerging therapeutic interventions. Full article

The global push toward digital transformation in education presents both opportunities and challenges for achieving sustainability goals. While digital technologies promise enhanced learning experiences and reduced environmental impacts, their implementation often overlooks complex trade-offs between pedagogical effectiveness, resource efficiency, and social equity. This study examines these critical intersections through a comprehensive investigation of geography education in Chinese secondary schools, comparing traditional, fully digital, and hybrid models across diverse urban, suburban, and rural contexts. Through a mixed-methods comparative design involving 262 participants (pilot) and 810 students (main study) and analysis of 17 geography textbooks, we assessed the environmental impacts, learning outcomes, economic viability, and social equity dimensions of each approach. Our findings reveal that thoughtfully designed hybrid models—which strategically combine digital tools for high-impact activities with traditional methods for local engagement—achieve optimal sustainability performance. These hybrid approaches reduced carbon emissions by 72.7% compared to traditional methods while improving learning outcomes and maintaining cost parity over five-year periods. Importantly, hybrid models demonstrated superior adaptability across different socioeconomic contexts, addressing equity concerns that purely digital approaches often exacerbate in resource-limited settings. This research challenges the prevailing technology-first narratives in educational reform, demonstrating that sustainable education transformation requires nuanced, context-sensitive integration strategies rather than wholesale digital transformation. The empirical evidence from this research provides robust support for achieving the United Nations Sustainable Development Goals through educational innovation. The hybrid model’s 73% carbon reduction and simultaneous improvement of learning outcomes by 35% directly support SDG 4 (Quality Education) and SDG 13 (Climate Action). The 78% reduction in paper consumption advances SDG 12 (Responsible Consumption and Production), while successful implementation across urban, suburban, and rural contexts addresses SDG 10 (Reduced Inequalities). These findings demonstrate that sustainable educational transformation can effectively balance technological innovation with environmental stewardship and social equity. Full article

Human papillomavirus (HPV) integration is recognized as a hallmark event in cervical carcinogenesis. However, it does not represent a routine phase of the viral life cycle but rather a stochastic occurrence, often constituting a dead-end pathway for the virus. High-risk human papillomavirus (hr-HPV) exhibits a greater propensity for integration. The progression from initial infection to genomic integration constitutes a dynamic multi-step oncogenic process in the development of cervical cancer (CC). This process involves viral entry, immune evasion, persistent infection, and ultimately integration. This article innovatively provides a comprehensive overview of this multi-stage mechanism: HPV, via the L1/L2 proteins, mediates internalization and establishes infection. Subsequently, under the influence of factors such as the host’s genetic background, vaginal microbiota imbalance, and immune evasion, the host’s DNA damage response (DDR) pathways are activated. Viral DNA integrates into host genome vulnerable sites (e.g., 3q28 and 8q24) through microhomology-mediated end joining (MMEJ) or other alternative pathways. Following integration, the expression of viral oncogenes persists, triggering host genomic rearrangements, aberrant epigenetic modifications, and immune microenvironment remodeling, all of which collectively drive cervical cancer progression. The study further reveals the clinical potential of HPV integration as a highly specific molecular biomarker, offering new perspectives for precision screening and targeted therapy. This dynamic model deepens our understanding of the HPV carcinogenic mechanism and provides a theoretical basis for intervention strategies. Full article