Search Results (3,405)

The rainy season characteristics are directly modulated by atmospheric circulation and moisture transport dynamics. Focusing on the characteristics of the rainy season onset date (RSOD), this study aims to advance the understanding and prediction of climate change impacts on agricultural production and disaster mitigation strategies. Based on rainfall data from 66 meteorological stations in northeast China (NEC) from 1961 to 2020, this study determined the patterns of the RSOD in the region and established its mechanistic linkages with atmospheric circulation and water vapor transport mechanisms. This study identifies a climatic regime shift around 2000, with the RSOD transitioning from low to high interannual variability in NEC. Further analysis reveals a strong correlation between the RSOD and atmospheric circulation characteristics: cyclonic vorticity amplifies before the RSOD and dissipates afterward. Innovatively, this study reveals a significant transition in the water vapor transport paths during the early rainy season in NEC around 2000, shifting from eastern Mongolia–Sea of Japan to the northwestern Pacific region. Moreover, the advance or delay of the RSOD directly influences the water vapor transport intensity—an early (delayed) RSOD is associated with enhanced (weakened) water vapor transport. These findings provide a new perspective for predicting the RSOD in the context of climate change while providing critical theoretical underpinnings for optimizing agricultural strategies and enhancing disaster prevention protocols. Full article

Precipitable water vapor (PWV) is a critical component of the Earth’s atmosphere, playing a pivotal role in weather systems, climate dynamics, and hydrological cycles. Accurate estimation of PWV is essential for numerical weather prediction, climate modeling, and atmospheric correction in remote sensing. Ground-based observation stations can only provide PWV measurements at discrete points, whereas spaceborne infrared remote sensing enables spatially continuous coverage, but its retrieval algorithm is restricted to clear-sky conditions. This study proposes an innovative approach that uses ensemble learning models to integrate infrared and microwave satellite data and other geographic features to achieve all-weather PWV retrieval. The proposed product shows strong consistency with IGRA radiosonde data, with correlation coefficients (R) of 0.96 for the ascending orbit and 0.95 for the descending orbit, and corresponding RMSE values of 5.65 and 5.68, respectively. Spatiotemporal analysis revealed that the retrieved PWV product exhibits a clear latitudinal gradient and seasonal variability, consistent with physical expectations. Unlike MODIS PWV products, which suffer from cloud-induced data gaps, the proposed method provides seamless spatial coverage, particularly in regions with frequent cloud cover, such as southern China. Temporal consistency was further validated across four east Asian climate zones, with correlation coefficients exceeding 0.88 and low error metrics. This algorithm establishes a novel all-weather approach for atmospheric water vapor retrieval that does not rely on ground-based PWV measurements for model training, thereby offering a new solution for estimating water vapor in regions lacking ground observation stations. Full article

Digital transformation (DT) has emerged as a key strategic lever for enhancing firm resilience and competitiveness, yet its influence on non-productive investment behaviors, such as corporate financial investment, remains underexplored. Existing studies have largely focused on DT’s role in innovation and operational efficiency, leaving a significant gap in understanding how DT reshapes firms’ financial asset allocation. Drawing on a unique panel dataset of A-share main board-listed firms in China from 2011 to 2023, this study provides novel empirical evidence that DT significantly restrains financial investment, with pronounced heterogeneity across ownership types. More importantly, this paper uncovers a multi-layered mechanism: DT enhances the corporate information environment, which subsequently reduces financial investment. In addition, the analysis reveals a moderated mediation mechanism wherein economic uncertainty dampens the information-enhancing effect of DT. Unlike previous research that treats corporate risk-taking as a parallel mediator, this study identifies a sequential mediation pathway, where improved information environments suppress financial investment indirectly by influencing firms’ risk-taking behavior. These findings offer new theoretical insights into the financial implications of DT and contribute to the broader understanding of enterprise behavior in the context of digitalization and economic volatility. Full article

Insect pests cause severe damage and yield losses to many agricultural crops globally. The use of chemical pesticides on agricultural crops is not recommended because of their toxic effects on the environment and consumers. In addition, pesticide toxicity reduces soil fertility, poisons ground waters, and is hazardous to soil biota. Therefore, applications of entomopathogenic nematodes (EPNs) and plant growth-promoting rhizobacteria (PGPR) are an alternative, eco-friendly solution to chemical pesticides and mineral-based fertilizers to enhance plant health and promote sustainable food security. This review focuses on the biological and ecological aspects of these organisms while also highlighting the practical application of molecular communication approaches in developing a novel plant health product. This insight will support this innovative approach that combines PGPR and EPNs for sustainable crop production. Several studies have reported positive interactions between nematodes and bacteria. Although the combined presence of both organisms has been shown to promote plant growth, the molecular interactions between them are still under investigation. Integrating molecular communication studies in the development of a new product could help in understanding their relationships and, in turn, support the combination of these organisms into a single plant health product. Full article

The growing interest in probiotic bacteria within the food industry is driven by their recognized health benefits for consumers. However, preserving their therapeutic viability and stability during gastrointestinal transit remains a formidable challenge. Hence, this research aimed to enhance the viability of Lactobacillus reuteri through microencapsulation using a binary polysaccharide mixture composed of low acyl gellan gum (LAG), high acyl gellan gum (HAG), and calcium for the microencapsulation of L. reuteri. To achieve this, the Box–Behnken design was applied, targeting the optimization of L. reuteri microencapsulated to withstand simulated gastrointestinal conditions. The microcapsules were crafted using the internal ionic gelation method, and optimization was performed using response surface methodology (RSM) based on the Box–Behnken design. The model demonstrated robust predictive power, with R² values exceeding 95% and a lack of fit greater than p > 0.05. Under optimized conditions—0.88% (w/v) LAG, 0.43% (w/v) HAG, and 24.44 mM Ca—L. reuteri reached a viability of 97.43% following the encapsulation process. After 4 h of exposure to simulated gastric fluid (SGF) and intestinal fluid (SIF), the encapsulated cells maintained a viable count of 8.02 log CFU/mL. These promising results underscore the potential of biopolymer-based microcapsules, such as those containing LAG and HAG, as an innovative approach for safeguarding probiotics during gastrointestinal passage, paving the way for new probiotic-enriched food products. Full article

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article

This study aims to evaluate eco-innovative solutions in the fertilizer industry that allow for waste valorization in the context of a resource-efficient circular economy. A comprehensive reuse strategy was developed for low-rank peat and post-cultivation horticultural mineral wool, involving the extraction of valuable humic substances from peat and residual nutrients from used mineral wool, followed by the use of both post-extraction residues to produce organic–mineral substrates. The resulting products/semifinished products were characterized in terms of their composition and properties, which met the requirements necessary to obtain the admission of this type of product to the market in accordance with the Regulation of the Minister for Agriculture and Rural Development of 18 June 2008 on the implementation of certain provisions of the Act on fertilizers and fertilization (Journal of Laws No 119, item 765). Elemental analysis, FTIR spectroscopy, and solid-state CP-MAS ¹³C NMR spectroscopy suggest that post-extraction peat has a relatively condensed structure with a high C content (47.4%) and a reduced O/C atomic ratio and is rich in alkyl-like matter (63.2%) but devoid of some functional groups in favor of extracted fulvic acids. Therefore, it remains a valuable organic biowaste, which, in combination with post-extraction waste mineral wool in a ratio of 60:40 and possibly the addition of mineral nutrients, allows us to obtain a completely new substrate with a bulk density of 264 g/m³, a salinity of 7.8 g/dm³ and a pH of 5.3, with an appropriate content of heavy metals and with no impurities, meeting the requirements of this type of product. A liquid fertilizer based on an extract containing previously recovered nutrients also meets the criteria in terms of quality and content of impurities and can potentially be used as a fertilizing product suitable for agricultural crops. This study demonstrates a feasible pathway for transforming specific waste streams into valuable agricultural inputs, contributing to environmental protection and sustainable production. The production of a new liquid fertilizer using nutrients recovered from post-cultivation mineral wool and the preparation of an organic–mineral substrate using post-extraction solid residue is a rational strategy for recycling hard-to-biodegrade end-of-life products. Full article

This theoretical essay aims to analyze some of the socio-economic innovations introduced by Platform Capitalism Specifically, it focuses on two main aspects: first, the digital platform as a radical organizational innovation. Digital platforms represent a structural novelty in the market economy, signaling a new organization of production and labor. Second, the essay examines the role of platforms in directly generating value through the concept of “network value”. To this end, it explores the function of “business intelligence” as a strategic and competitive tool. Finally, the paper discusses the key issues associated with platform capitalism, which could threaten its social sustainability and contribute to economic and financial instability. These issues include the increasing commodification of everyday activities, the devaluation of paid labor in favor of free production driven by platform users (the so-called prosumers), and the emergence of proprietary and financial monopolies. Hence, digital platforms do not inherently ensure comprehensive social and environmental sustainability unless supported by targeted economic policy interventions. Conclusively, it is emphasized that defining robust social welfare frameworks—which account for emerging value creation processes—is imperative. Simultaneously, policymakers must incentivize the proliferation of cooperative platforms capable of fostering experimental circular economy models aligned with ecological sustainability. Full article

Contact unmodified antisense DNA biotechnology (CUADb), developed in 2008, employs short antisense DNA oligonucleotides (oligos) as a novel approach to insect pest control. These oligonucleotide-based insecticides target pest mature rRNAs and/or pre-rRNAs and have demonstrated high insecticidal efficacy, particularly against sap-feeding insect pests, which are key vectors of plant DNA viruses and among the most economically damaging herbivorous insects. To further explore the potential of CUADb, this study evaluated the insecticidal efficacy of short 11-mer antisense DNA oligos against Coccus hesperidum, in comparison with long 56-mer single-stranded and double-stranded DNA sequences. The short oligos exhibited higher insecticidal activity. By day 9, the highest mortality rate (97.66 ± 4.04%) was recorded in the Coccus-11 group, while the most effective long sequence was the double-stranded DNA in the dsCoccus-56 group (77.09 ± 6.24%). This study also describes the architecture of the DNA containment (DNAc) mechanism, highlighting the intricate interactions between rRNAs and various types of DNA oligos. During DNAc, the Coccus-11 treatment induced enhanced ribosome biogenesis and ATP production through a metabolic shift from carbohydrates to lipid-based energy synthesis. However, this ultimately led to a ‘kinase disaster’ due to widespread kinase downregulation resulting from insufficient ATP levels. All DNA oligos with high or moderate complementarity to target rRNA initiated hypercompensation, but subsequent substantial rRNA degradation and insect mortality occurred only when the oligo sequence perfectly matched the rRNA. Both short and long oligonucleotide insecticide treatments led to a 3.75–4.25-fold decrease in rRNA levels following hypercompensation, which was likely mediated by a DNA-guided rRNase, such as RNase H1, while crucial enzymes of RNAi (DICER1, Argonaute 2, and DROSHA) were downregulated, indicating fundamental difference in molecular mechanisms of DNAc and RNAi. Consistently, significant upregulation of RNase H1 was detected in the Coccus-11 treatment group. In contrast, treatment with random DNA oligos resulted in only a 2–3-fold rRNA decrease, consistent with the normal rRNA half-life maintained by general ribonucleases. These findings reveal a fundamental new mechanism of rRNA regulation via complementary binding between exogenous unmodified antisense DNA and cellular rRNA. From a practical perspective, this minimalist approach, applying short antisense DNA dissolved in water, offers an effective, eco-friendly and innovative solution for managing sternorrhynchans and other insect pests. The results introduce a promising new concept in crop protection: DNA-programmable insect pest control. Full article

Background: Brain health is a growing public health priority due to the high global burden of neurological and mental disorders. Promoting brain health across the lifespan supports individual and societal well-being, creativity, and productivity. Objective: To address the need for specialized education in this field, the University of Bern developed a Certificate of Advanced Studies (CAS) in Brain Health. This article outlines the program’s rationale, structure, and goals. Program Description: The one-year, 15 ECTS-credit program is primarily online and consists of four modules: (1) Introduction to Brain Health, (2) Brain Disorders, (3) Risk Factors, Protective Factors and Interventions, and (4) Brain Health Implementation. It offers a multidisciplinary, interprofessional, life-course approach, integrating theory with practice through case studies and interactive sessions. Designed for healthcare and allied professionals, the CAS equips participants with skills to promote brain health in clinical, research, and public health contexts. Given the shortage of trained professionals in Europe and globally, the program seeks to build a new generation of brain health advocates. It aims to inspire action and initiatives that support the prevention, early detection, and management of brain disorders. Conclusions: The CAS in Brain Health is an innovative educational response to a pressing global need. By fostering interdisciplinary expertise and practical skills, it enhances professional development and supports improved brain health outcomes at individual and population levels. Full article

Environmental monitoring plays a key role in understanding and mitigating the effects of climate change, pollution, and resource mismanagement. The growth of printed sensor technologies offers an innovative approach to addressing these challenges due to their low cost, flexibility, and scalability. Printed sensors enable the real-time monitoring of air, water, soil, and climate, providing significant data for data-driven decision-making technologies and policy development to improve the quality of the environment. The development of new materials, such as graphene, conductive polymers, and biodegradable substrates, has significantly enhanced the environmental applications of printed sensors by improving sensitivity, enabling flexible designs, and supporting eco-friendly and disposable solutions. The development of inkjet, screen, and roll-to-roll printing technologies has also contributed to the achievement of mass production without sacrificing quality or performance. This review presents the current progress in printed sensors for environmental applications, with a focus on technological advances, challenges, applications, and future directions. Moreover, the paper also discusses the challenges that still exist due to several issues, e.g., sensitivity, stability, power supply, and environmental sustainability. Printed sensors have the potential to revolutionize ecological monitoring, as evidenced by recent innovations such as Internet of Things (IoT) integration, self-powered designs, and AI-enhanced data analytics. By addressing these issues, printed sensors can develop a better understanding of environmental systems and help promote the UN sustainable development goals. Full article

China’s economy is shifting from an era of rapid expansion to one focused on high-quality development, making it imperative to tackle environmental degradation linked to energy use. Understanding how New Quality Productive Forces (NQPF) interact with energy efficiency, along with the mechanisms driving this relationship, is essential for economic transformation and long-term sustainability. This study establishes an evaluation framework for NQPF, integrating technological, green, and digital dimensions. We apply fixed-effects models, the spatial Durbin model (SDM), a moderation model, and a threshold model to analyze the influence of NQPF on Green Total Factor Energy Efficiency (GTFEE) and its spatial implications. This underscores the necessity of distinguishing it from traditional productivity frameworks and adopting a new analytical perspective. Furthermore, by considering dimensions such as input, application, innovation capability, and market efficiency, we reveal the moderating role and heterogeneous effects of artificial intelligence (AI). The findings are as follows: The development of NQPF significantly enhances GTFEE, and the conclusion remains robust after tail reduction and endogeneity tests. NQPF has a positive spatial spillover effect on GTFEE; that is, while improving the local GTFEE, it also improves neighboring regions GTFEE. The advancement of AI significantly strengthens the positive impact of NQPF on GTFEE. AI exhibits a significant U-shaped threshold effect: as AI levels increase, its moderating effect transitions from suppression to facilitation, with marginal benefits gradually increasing over time. Full article

Achieving sustainable development goals remains a core issue in global development. In response, China has proposed the development of new quality productive forces (NQPFs) through innovative thinking, emphasizing that fostering NQPFs is both an intrinsic requirement and a pivotal focus for advancing high-quality development. Concurrently, the intelligent transformation of the manufacturing sector serves as a critical direction for China’s economic restructuring and upgrading. This paper places “new quality productive forces” and “intelligent transformation of manufacturing” within the same analytical framework. Starting from the logical chain of “new quality productive forces—three major mechanisms—intelligent transformation of manufacturing,” it concretizes the value implications of new quality productive forces into a systematic conceptual framework driven by the synergistic interaction of three major mechanisms: the mechanism of revolutionary technological breakthroughs, the mechanism of innovative allocation of production factors, and the mechanism of deep industrial transformation and upgrading. This study constructs a “3322” evaluation index system for NQPFs, based on three formative processes, three driving forces, two supporting systems, and two-dimensional characteristics. Simultaneously, it builds an evaluation index system for the intelligent transformation of manufacturing, encompassing intelligent technology, intelligent applications, and intelligent benefits. Using national time-series data from 2012 to 2023, this study assesses the development levels of both NQPFs and the intelligent transformation of manufacturing during this period. The study further analyzes the impact of NQPFs on the intelligent transformation of the manufacturing sector. The research results indicate the following: (1) NQPFs drive the intelligent transformation of the manufacturing industry through the three mechanisms of innovative allocation of production factors, revolutionary breakthroughs in technology, and deep transformation and upgrading of industries. (2) The development of NQPFs exhibits a slow upward trend; however, the outbreak of the pandemic and Sino-US trade frictions have caused significant disruptions to the development of new-type productive forces. (3) The level of intelligent manufacturing continues to improve; however, from 2020 to 2023, due to the impact of the COVID-19 pandemic and Sino-US trade conflicts, the level of intelligent benefits has slightly declined. (4) NQPFs exert a powerful driving force on the intelligent transformation of manufacturing, exerting a significant positive impact on intelligent technology, intelligent applications, and intelligent efficiency levels. Full article

Catalysis research is complex and interdisciplinary, involving diverse physical effects and challenging data practices. Research data often captures only selected aspects, such as specific reactants and products, limiting its utility for machine learning and the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) workflows. To improve this, semantic structuring through ontologies is essential. This work extends the established ontologies by refining logical relations and integrating semantic tools such as the Web Ontology Language or the Shape Constraint Language. It incorporates application programming interfaces from chemical databases, such as the Kyoto Encyclopedia of Genes and Genomes and the National Institute of Health’s PubChem database, and builds upon established ontologies. A key innovation lies in automatically decomposing chemical substances through database entries and chemical identifier representations to identify functional groups, enabling more generalized reaction classification. Using new semantic functionality, functional groups are flexibly addressed, improving the classification of reactions such as saponification and ester cleavage with simultaneous oxidation. A graphical interface (GUI) supports user interaction with the knowledge graph, enabling ontological reasoning and querying. This approach demonstrates improved specificity of the newly established ontology over its predecessors and offers a more user-friendly interface for engaging with structured chemical knowledge. Future work will focus on expanding ontology coverage to support a wider range of reactions in catalysis research. Full article

Achieving synergies between government-led and market-based policy instruments is critical to advancing Energy–Environmental Productivity and Sustainable Urban Development. This study investigates the effects of China’s dual-pilot energy policies (New Energy Demonstration Cities (NEDCs) and Energy Consumption Permit Trading (ECPT)) on urban environmental productivity (UEP) across 279 prefecture-level cities from 2006 to 2023. Utilizing a Non-Radial Directional Distance Function (NDDF) approach, combined with Difference-in-Differences (DID) estimation and spatial econometric models, the analysis reveals that these synergistic policies significantly enhance both comprehensive and net measures of UEP. Mechanism analysis highlights the roles of industrial restructuring, technological innovation, and energy transition in driving these improvements, while heterogeneity analysis indicates varying effects across different city types. Spatial spillover analysis further demonstrates that policy impacts extend beyond targeted cities, contributing to broader regional gains in UEP. These findings offer important insights for the design of integrated energy and environmental policies and support progress toward key Sustainable Development Goals (SDG 7, SDG 11, and SDG 12). Full article