Search Results (698)

Cellular senescence can occur with similar phenotypes in normal cells, during aging, and in tumor cells, spontaneously or after cytostasis. The fall or increase in proliferative activity are key aspects of the respective conditions, in which the levels of reactive oxygen species can vary, affecting the cellular redox homeostasis. This work aimed to study the relationships between senescence and transformation by comparing cells with different proliferative activities and phenotypes attributable to transformation (NIHs cultures) or senescence (NIHv cultures), before and after incubation with hydrogen peroxide. Both cultures were derived from the NIH/3T3 cell line, which was used here as a reference (NIHb), after the serum starvation. Our experimental model can be representative of the heterogeneity of cell subpopulations, with different degrees of transformation and senescence, found in some tumors. The characterization of the functional properties of NIHb, NIHs, and NIHv cells was performed by a morphocytometric analysis of the cell cycle progression, mitochondrial and lysosomal content/activity, and superoxide anion production. The efficiency of the lysosomal compartment was also assessed by estimating the autophagic activity and measuring lipofuscin autofluorescence. Comparisons of nuclear and cytoplasmic parameters before and after the incubation with hydrogen peroxide revealed differences in the expression and modulation of cellular senescence patterns. The treatment effects were very limited in the NIHb culture; the senescence condition was essentially maintained in the NIHv cells, while the most relevant changes were found in the NIHs cells. In the latter, the acquisition of the senescent phenotype, also demonstrated by the positivity of SA-β-galactosidase, was correlated with a decrease in proliferative activity and a change in the content/activity of the mitochondria and lysosomes, which showed similarities with the basal senescence conditions of NIHv cells. In NIHs cells, increased autophagy events and lipofuscin accumulation also indicate the establishment of cytoplasmic dynamics typical of senescence. The variable responses to hydrogen peroxide, besides depending on the different basal cytokinetic activity of the cultures examined, appeared to be related to the specific cell redox state resulting from the balance between endogenous ROS and those produced after treatment. Especially in NIHs cells, the slowing down of the cell cycle was linked to dynamic interconnections between the mitochondrial and lysosomal compartments. This would indicate that transformed cells, such as NIHs, may express morpho-functional aspects and markers typical of cellular senescence, as a consequence of the modulation of their redox state. Full article

In recent years, experts have associated forecasts of global energy consumption with energy transitions. This paper presents the research results of the paths and trajectories of the global transformations of world energy, including demographic, technological, energy, transport, and communication changes. After demonstrating the long-term trends in global energy consumption, fossil and renewable energy sources, and nuclear energy using neuroforecasting methods, this study explains global demographic development and its relationship with global innovation and technological processes as explained by the flow of global patent applications. The relationship between energy transition and the previously mentioned two factors is also justified based on the trajectories developed by the neural network forecasting. By leveraging the fundamental laws of energy conservation, robust patterns in the evolution and development of global energy could be identified. It is demonstrated that mankind has entered the era of four closely interconnected global transitions: demographic, energy, technological, and political–economic, all at once. According to the results, civilizational changes are currently taking place in global energy advancement, indicating an energy transition to a new quality of energy development. The permanent growth patterns of the energy density of energy sources used and their impact on labor productivity and the speed of movement of people and goods in the economy are also discussed. Finally, the contour of future developments in energy technologies is determined. It is also forecast that future energy technologies are expected to be largely associated with the exploration of outer space, development of robotics, and the expansion of artificial intelligence capabilities. Full article

As information and sensor technologies advance swiftly, data-driven approaches have emerged as a dominant paradigm in scientific research. In the petroleum industry, precise forecasting of patterns of two-phase flow involving oil and water is essential for enhancing production efficiency and ensuring safety. This study investigates the application of Kolmogorov–Arnold Networks (KAN) for predicting patterns of two-phase flow involving oil and water and compares it with the conventional Multi-Layer Perceptron (MLP) neural network. To obtain real physical data, we conducted the experimental section to simulate the patterns of two-phase flow involving oil and water under various well angles, flow rates, and water cuts at the Key Laboratory of Oil and Gas Resources Exploration Technology of the Ministry of Education, Yangtze University. These data were standardized and used to train both KAN and MLP models. The findings indicate that KAN outperforms the MLP network, achieving 50% faster convergence and 22.2% higher accuracy in prediction. Moreover, the KAN model features a more streamlined structure and requires fewer neurons to attain comparable or superior performance to MLP. This research offers a highly effective and dependable method for predicting patterns of two-phase flow involving oil and water in the dynamic monitoring of production wells. It highlights the potential of KAN to boost the performance of energy systems, particularly in the context of intelligent transformation. Full article

Resource-based cities, characterized by a prolonged dependence on resource extraction and persistent urban expansion, frequently exhibit significant imbalances between the supply and demand of ecosystem services (ESs). Understanding how various types of resource-based cities respond to urbanization in terms of ESs supply–demand relationships is crucial for advancing sustainable urban development. This study examines three representative resource-based cities in Sichuan Province—Nanchong (growing), Luzhou (declining), and Panzhihua (mature)—to analyze changes in six key ESs from 2000 to 2020, including soil retention, carbon sequestration, water yield, habitat quality, food production, and recreational services. Ordinary least squares (OLS) regression and random forest (RF) models were employed to evaluate the effects of gross domestic product (GDP) density, construction land proportion (CLP), and population (POP) density on the ecosystem service supply–demand ratio (ESDR), and to explore variations in sensitivity among these cities. The results demonstrate that (1) ESs’ supply–demand patterns differ significantly among the three city types. Nanchong exhibited a declining supply and increasing demand for regulating services; Luzhou displayed improvements in its water yield and recreational services but persistent degradation of habitat quality; and Panzhihua achieved notable gains in carbon sequestration and habitat quality. (2) Urbanization generally reduced the ESDR across all three cities. However, the GDP density positively influenced the ESDR in Nanchong, while the CLP and the POP density exerted widespread negative effects. In Luzhou, the ESDR was primarily constrained by the CLP, whereas in Panzhihua, both the CLP and the POP density significantly reduced the ratio. (3) The sensitivity analysis revealed distinct response patterns: Nanchong was most sensitive to CLP, Luzhou responded most strongly to GDP density, and Panzhihua was highly sensitive to both GDP density and POP density. These findings underscore the necessity of formulating city-type-specific development strategies—such as land restoration, population control, and industrial upgrading—tailored to different types of resource-based cities, in order to reconcile urbanization with ecosystem service dynamics, promote green transformation, and contribute to the achievement of the Sustainable Development Goals (SDGs). Full article

Breeding performance encompasses offspring production, their survival rate, fertility, overall reproductive outcome, timing of reproduction, and breeding frequency. It varies in raptor species, being affected by different biotic, abiotic, and anthropogenic factors. The Lesser Spotted Eagle is a monogamous, long-lived, slowly reproducing raptor, characterized by site-fidelity and strongly territorial behavior. In this study, we examined data collected over a 10-year period, highlighting the eagles’ main breeding parameters, analyzing whether any of them demonstrated significant trends or spatial or temporal differences over the study period. We also searched for a strict correlation between species breeding density and breeding performance. We found out that the mean occupancy rate of the territories marginally decreased β² = −0.64 ± 0.27, p = 0.047, as this process was clearly visible in Sakar Mnt. (β² = −0.66 ± 0.27, p = 0.038), where in 2022, only 67% of the monitored territories were occupied. The overall mean productivity, breeding success, and breeding frequency did not indicate any trend over the years (p > 0.05). Of all tested breeding parameters, occupancy rate (β² = 0.29 ± 0.14, p = 0.04) and breeding success (β² = −0.12 ± 0.06, p = 0.04) varied yearly, while productivity (β² = 0.25 ± 0.12, p = 0.03) and breeding frequency (β² = 0.27 ± 0.12, p = 0.03) were influenced by density. None of the tested indicators demonstrated significant regional differences, which indicated a temporally determinate, but spatially consistent pattern of breeding performance of the species in this part of its distribution. Recently, the landscape pattern in the south-eastern part of the country was marked by spectacular habitat loss, driven by human activities and natural phenomena, with entire biodiversity facing an uncertain future. Prompt action and urgent decisions are needed to prevent the negative consequences of these imminent threats to the species. Conservation efforts should be focused on the restoration of breeding and foraging habitats. Further research on the response of eagles to the effect of natural (fires) and anthropogenic (habitat transformation) factors, as well as the relationship between breeding performance and different drivers of reproduction, such as diet, weather, habitat features, and presence of intra- and interspecific competitors, would be of crucial significance. Full article

With the vigorous development of sericulture, the traditional labor-intensive small-scale silkworm rearing has been progressively transformed into a large-scale mechanized system. Consequently, silkworm factories can produce cocoons continuously throughout the year. However, this intensive production pattern generates a substantial amount of silkworm excrement. If not managed properly or disposed indiscriminately, silkworm excrement can lead to severe environmental pollution. In recent years, increasing attention has been paid to the comprehensive utilization of this bioresource. Numerous studies have explored its potential in a wide range of applications. This review systematically summarizes current research on silkworm excrement utilization, particularly focusing on its fundamental characteristics, key technologies, and application areas. Future efforts should aim to promote efficient resource recycling and support the development of sericulture. Full article

Customers heavily depend on reviews for product information. Fake reviews may influence the perception of product quality, making online reviews less effective. ChatGPT’s (GPT-3.5 and GPT-4) ability to generate human-like reviews and responses to inquiries across several disciplines has increased recently. This leads to an increase in the number of reviewers and applications using ChatGPT to create fake reviews. Consequently, the detection of fake reviews generated or rephrased by ChatGPT has become essential. This paper proposes a new approach that distinguishes ChatGPT-rephrased reviews, considered fake, from real ones, utilizing a balanced dataset to analyze the sentiment and linguistic patterns that characterize both reviews. The proposed model further leverages Explainable Artificial Intelligence (XAI) techniques, including Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP) for deeper insights into the model’s predictions and the classification logic. The proposed model performs a pre-processing phase that includes part-of-speech (POS) tagging, word lemmatization, tokenization, and then fine-tuned Transformer-based Machine Learning (ML) model DistilBERT for predictions. The obtained experimental results indicate that the proposed fine-tuned DistilBERT, utilizing the constructed balanced dataset along with a pre-processing phase, outperforms other state-of-the-art methods for detecting ChatGPT-rephrased reviews, achieving an accuracy of 97.25% and F1-score of 97.56%. The use of LIME and SHAP techniques not only enhanced the model’s interpretability, but also offered valuable insights into the key factors that affect the differentiation of genuine reviews from ChatGPT-rephrased ones. According to XAI, ChatGPT’s writing style is polite, uses grammatical structure, lacks specific descriptions and information in reviews, uses fancy words, is impersonal, and has deficiencies in emotional expression. These findings emphasize the effectiveness and reliability of the proposed approach. Full article

Digital innovation is rapidly transforming the agriculture sector, drawing attention from global development institutions, policymakers, tech firms, and scholars aimed at aligning food systems with international goals like Zero Hunger and the FAO agendas. Small and medium enterprises in agriculture (Agri-SMEs) represent a significant portion of processing and production units but face challenges in digital transformation despite their importance. Technologies such as Artificial Intelligence (AI), blockchain, cloud services, IoT, and mobile platforms offer tools to improve efficiency, access, value creation, and traceability. However, the patterns and applications of these transformations in Agri-SMEs remain fragmented and under-theorized. This paper presents a systematic review of interactions between digital transformation and innovation in Agri-SMEs based on findings from ninety-five peer-reviewed studies. Key themes identified include AI-based decision support, blockchain traceability, cloud platforms, IoT precision agriculture, and mobile technologies for financial integration. The review maps these themes against business model values and highlights barriers like capacity gaps and infrastructure deficiencies that hinder scalable adoption. It concludes with recommendations for future research, policy, and ecosystem coordination to promote the sustainable development of digitally robust Agri-SMEs. Full article

This paper presents the expected and unexpected, but typically substituent-dependent, ferrocene-catalyzed DDQ-mediated oxidative transformations of a series of 5,8-bis(methylthio)-1-aryl-1,2-dihydropyridazino[4,5-d]pyridazines and 8-(3,5-dimethyl-1H-pyrazol-1-yl)-5-(methylthio)-1-aryl-1,2-dihydropyridazino[4,5-d]pyridazines. Under noncatalytic conditions the reactions were sluggish, mainly producing a substantial amount of undefined tarry materials; nevertheless, the ferrocene-catalyzed reactions of the 5,8-bis(methylthio)-substituted precursors gave the aromatic products the expected aromatic products in low yields. Their formation was accompanied by ring transformations proceeding via aryne-generating fragmentation/Diels–Alder (DA)/N₂-releasing retro Diels–Alder (rDA) sequence to construct arene-fused phthalazines. On the other hand, neither the noncatalytic nor the catalytic reactions of the 8-pyrazolyl-5-methylthio-substituted dihydroaromatics yielded the expected aromatic products. Instead, depending on their substitution pattern, the catalytic reactions of these pyrazolyl-substituted precursors also led to the formation of dearylated arene-fused phthalazines competing with an unprecedented multistep fragmentation sequence terminated by the hydrolysis of cationic intermediates to give 4-(methylthio)pyridazino[4,5-d]pyridazin-1(2H)-one and the corresponding 3,5-dimethyl-1-aryl-1H-pyrazole. When 0.6 equivalents of DDQ were applied in freshly absolutized THF, a representative pyrazolyl-substituted model underwent an oxidative coupling to give a dimer formed by the interaction of the cationic intermediate, and a part of the N-nucleophilic precursor remained intact. A systematic computational study was conducted on these intriguing reactions to support their complex mechanisms proposed on the basis of the structures of the isolated products. Full article

The biopharmaceutical industry is undergoing a fundamental transformation from traditional batch manufacturing to continuous manufacturing (CM) for recombinant drugs and biosimilars, driven by regulatory support through the International Council for Harmonization (ICH) Q13 guidance and compelling economic advantages. This comprehensive review examines the technical, economic, and regulatory aspects of implementing continuous manufacturing specifically for recombinant protein production and biosimilar development, synthesizing validated data from peer-reviewed research, regulatory sources, and global implementation case studies. The analysis demonstrates that continuous manufacturing offers substantial benefits, including a reduced equipment footprint of up to 70%, a 3- to 5-fold increase in volumetric productivity, enhanced product quality consistency, and facility cost reductions of 30–50% compared to traditional batch processes. Leading biomanufacturers across North America, Europe, and the Asia–Pacific region are successfully integrating perfusion upstream processes with connected downstream bioprocesses, enabling the fully end-to-end continuous manufacture of biopharmaceuticals with demonstrated commercial viability. The regulatory framework has been comprehensively established through ICH Q13 guidance and region-specific implementations across the FDA, EMA, PMDA, and emerging market authorities. This review provides a critical analysis of advanced technologies, including single-use perfusion bioreactors, continuous chromatography systems, real-time process analytical technology, and Industry 4.0 integration strategies. The economic modeling presents favorable return-on-investment profiles, accompanied by a detailed analysis of global market dynamics, regional implementation patterns, and supply chain integration opportunities. Full article

The use of Internet of Things (IoT) for sports innovation has transformed the way athletes train, compete, and recover in any sports activity. This study performs a bibliometric analysis to examine research trends, collaborations, and publications in the realm of IoT and Sports. Our analysis included 780 Scopus articles and 150 WoS articles published during 2012–2025, and duplicates were removed. We analyzed and visualized the bibliometric data using R version 3.6.1, VOSviewer version 1.6.20, and the bibliometrix library. The study provides insights from a bibliometric analysis, showcasing the allocation of topics, scientific contributions, patterns of co-authorship, prominent authors and their productivity over time, notable terms, key sources, publications with citations, analysis of citations, source-specific citation analysis, yearly publication patterns, and the distribution of research papers. The results indicate that China and India have the leading scientific production in the development of IoT and Sports research, with prominent authors like Anton Umek, Anton Kos, and Emiliano Schena making significant contributions. Wearable technology and wearable sensors are the most trending topics in IoT and Sports, followed by medical sciences and artificial intelligence paradigms. The analysis also emphasizes the importance of open-access journals like ‘Journal of Physics: Conference Series’ and ‘IEEE Access’ for their contributions to IoT and Sports research. Future research directions focus on enhancing effective, lightweight, and efficient wearable devices while implementing technologies like edge computing and lightweight AI in wearable technologies. Full article

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and grid scales. Therefore, this study selects Zhejiang Province—a representative rapidly transforming region in China—to establish a “type-process-ecological effect” analytical framework. Utilizing four-period (2005–2020) 30 m resolution land use data alongside natural and socio-economic factors, four spatial scales (city, county, township, and 5 km grid) were selected to systematically evaluate multi-scale impacts of land use transition on EEQ and their driving mechanisms. The research reveals that the spatial distribution, changing trends, and driving factors of EEQ all exhibit significant scale dependence. The county scale demonstrates the strongest spatial agglomeration and heterogeneity, making it the most appropriate core unit for EEQ management and planning. City and county scales generally show degradation trends, while township and grid scales reveal heterogeneous patterns of local improvement, reflecting micro-scale changes obscured at coarse resolutions. Expansive land transition including conversions of forest ecological land (FEL), water ecological land (WEL), and agricultural production land (APL) to industrial and mining land (IML) primarily drove EEQ degradation, whereas restorative ecological transition such as transformation of WEL and IML to grassland ecological land (GEL) significantly enhanced EEQ. Regarding driving mechanisms, natural factors (particularly NDVI and precipitation) dominate across all scales with significant interactive effects, while socio-economic factors primarily operate at macro scales. This study elucidates the scale complexity of land use transition impacts on ecological environments, providing theoretical and empirical support for developing scale-specific, typology-differentiated ecological governance and spatial planning policies. Full article

A scalable synthesis of two-dimensional titanium nitride chloride (TiNCl) via flash Joule heating (FJH) using titanium tetrachloride (TiCl₄) precursor has been developed. This single-step method overcomes traditional synthesis challenges, including high energy consumption, multi-step procedures, and hazardous reagent requirements. The structural and chemical properties of the synthesized TiNCl were characterized through multiple analytical techniques. X-ray diffraction (XRD) patterns confirmed the presence of TiNCl phase, while Raman spectroscopy data showed no detectable oxide impurities. Fourier transform infrared spectroscopy (FTIR) analysis revealed characteristic Ti–N stretching vibrations, further confirming successful titanium nitride synthesis. Transmission electron microscopy (TEM) imaging revealed thin, plate-like nanostructures with high electron transparency. These analyses confirmed the formation of highly crystalline TiNCl flakes with nanoscale dimensions and minimal structural defects. The material exhibits excellent structural integrity and phase purity, demonstrating potential for applications in photocatalysis, electronics, and energy storage. This work establishes FJH as a sustainable and scalable approach for producing MXenes with controlled properties, facilitating their integration into emerging technologies. Unlike conventional methods, FJH enables rapid, energy-efficient synthesis while maintaining material quality, providing a viable route for industrial-scale production of two-dimensional materials. Full article

This study investigates the impact of rural digital economy development on agricultural carbon emission efficiency, aiming to elucidate the intrinsic mechanisms and pathways through which digital technology enables low-carbon transformation in agriculture, thereby contributing to the achievement of agricultural carbon neutrality goals. Based on provincial-level panel data from China spanning 2011 to 2022, this study examines the relationship between the rural digital economy and agricultural carbon emission efficiency, along with its underlying mechanisms, using bidirectional fixed effects models, mediation effect analysis, and Spatial Durbin Models. The results indicate the following: (1) A significant N-shaped-curve relationship exists between rural digital economy development and agricultural carbon emission efficiency. Specifically, agricultural carbon emission efficiency exhibits a three-phase trajectory of “increase, decrease, and renewed increase” as the rural digital economy advances, ultimately driving a sustained improvement in efficiency. (2) Industrial integration acts as a critical mediating mechanism. Rural digital economy development accelerates the formation of the N-shaped curve by promoting the integration between agriculture and other sectors. (3) Spatial spillover effects significantly influence agricultural carbon emission efficiency. Due to geographical proximity, regional diffusion, learning, and demonstration effects, local agricultural carbon emission efficiency fluctuates with changes in neighboring regions’ digital economy development levels. (4) The relationship between rural digital economy development and agricultural carbon emission efficiency exhibits a significant inverted N-shaped pattern in regions with higher marketization levels, planting-dominated areas of southeast China, and digital economy demonstration zones. Further analysis reveals that within rural digital economy development, production digitalization and circulation digitalization demonstrate a more pronounced inverted N-shaped relationship with agricultural carbon emission efficiency. This study proposes strategic recommendations to maximize the positive impact of the rural digital economy on agricultural carbon emission efficiency, unlock its spatially differentiated contribution potential, identify and leverage inflection points of the N-shaped relationship between digital economy development and emission efficiency, and implement tailored policy portfolios—ultimately facilitating agriculture’s green and low-carbon transition. Full article

Early and accurate detection of mechanical damage in prunes is crucial for preserving postharvest quality and enabling automated sorting. This study proposes a practical and reproducible method for identifying cumulative bruising in prunes using visible–near-infrared (Vis–NIR) reflectance spectroscopy coupled with machine learning techniques. A self-developed impact simulation device was designed to induce progressive damage under controlled energy levels, simulating realistic postharvest handling conditions. Spectral data were collected from the equatorial region of each fruit and processed using a hybrid modeling framework comprising continuous wavelet transform (CWT) for spectral enhancement, uninformative variable elimination (UVE) for optimal wavelength selection, and support vector machine (SVM) for classification. The proposed CWT-UVE-SVM model achieved an overall classification accuracy of 93.22%, successfully distinguishing intact, mildly bruised, and cumulatively damaged samples. Notably, the results revealed nonlinear reflectance variations in the near-infrared region associated with repeated low-energy impacts, highlighting the capacity of spectral response patterns to capture progressive physiological changes. This research not only advances nondestructive detection methods for prune grading but also provides a scalable modeling strategy for cumulative mechanical damage assessment in soft horticultural products. Full article