Search Results (625)

With the growing global demand for clean energy, the accuracy of wind-power forecasting plays a vital role in ensuring the stable operation of power systems. However, wind-power generation is significantly influenced by meteorological conditions and is characterized by high uncertainty and multiscale fluctuations. Traditional recurrent neural network (RNN) and long short-term memory (LSTM) models, although capable of handling sequential data, struggle with modeling long-term temporal dependencies due to the vanishing gradient problem; thus, they are now rarely used. Recently, Transformer models have made notable progress in sequence modeling compared to RNNs and LSTM models. Nevertheless, when dealing with long wind-power sequences, their quadratic computational complexity (O(L²)) leads to low efficiency, and their global attention mechanism often fails to capture local periodic features accurately, tending to overemphasize redundant information while overlooking key temporal patterns. To address these challenges, this paper proposes a wind-power forecasting method based on dimension-transformed collaborative multidimensional multiscale attention (DTCMMA). This method first employs fast Fourier transform (FFT) to automatically identify the main periodic components in wind-power data, reconstructing the one-dimensional time series as a two-dimensional spatiotemporal representation, thereby explicitly encoding periodic features. Based on this, a collaborative multidimensional multiscale attention (CMMA) mechanism is designed, which hierarchically integrates channel, spatial, and pixel attention to adaptively capture complex spatiotemporal dependencies. Considering the geometric characteristics of the reconstructed data, asymmetric convolution kernels are adopted to enhance feature extraction efficiency. Experiments on multiple wind-farm datasets and energy-related datasets demonstrate that DTCMMA outperforms mainstream methods such as Transformer, iTransformer, and TimeMixer in long-sequence forecasting tasks, achieving improvements in MSE performance by 34.22%, 2.57%, and 0.51%, respectively. The model’s training speed also surpasses that of the fastest baseline by 300%, significantly improving both prediction accuracy and computational efficiency. This provides an efficient and accurate solution for wind-power forecasting and contributes to the further development and application of wind energy in the global energy mix. Full article

The increasing demand for plant-based cheese alternatives reflects a shift toward healthier and more sustainable food choices. This study aimed to map technological trends, formulation strategies, and major challenges in the development of plant-based cheese analogues through a systematic review of the scientific literature and patents. Following the PRISMA protocol, searches were conducted in ScienceDirect and Lens.org between December 2024 and January 2025 using keywords related to cheese analogues. A total of 1553 scientific articles and 155 patents were initially retrieved. After applying inclusion and exclusion criteria, 88 articles and 66 patents were selected for detailed analysis. The results show a growing interest in this field since 2020, peaking in 2024. Data from 2025 may be limited due to the search period. Keywords were clustered into three main areas: (1) Formulation and Composition, (2) Texture and Processing, and (3) Food Safety and Consumer Acceptance. The United States leads in patent registrations (59). Valio Company and Cargill were the most active assignees, with nine and eight patents, respectively. This study highlights the importance of integrating food science and technology to improve the quality, sensory attributes, and market competitiveness of plant-based cheese analogues compared to traditional dairy products. Full article

Under the frequent occurrence of urban waterlogging disasters globally, underground spaces, due to their unique environmental conditions and structural vulnerabilities, are facing growing flood pressure, resulting in substantial economic losses that hinder sustainable urban development. This study focused on a high-density urban area in China, investigating surface waterlogging conditions under rainfall characteristics as the primary driver of flooding. Focusing on the main nodes—entrances and exits—within the waterlogging disaster chain of underground garages, a risk assessment framework was constructed that encompasses three key dimensions: the attributes of extreme rainfall, the structural characteristics of entrances/exits, and emergency response capacities. Subsequently, a waterlogging risk assessment was conducted for selected underground garages in the study area under a 100-year return period extreme rainfall scenario. The results revealed that the flood depth at entrances/exits and the structural height of entrances/exits are the primary factors influencing flood risk in urban underground garages. Under this simulation scenario, 37.5% of the entrances and exits exhibited varying degrees of flood risk. The assessment framework and indicator system developed in this study provide valuable insights for flood risk evaluation in underground garage systems and offer decision-makers a more scientific and robust foundation for formulating improvement measures. Full article

Background: Pancreatic cancer (PC) has an extremely poor prognosis and is growing worldwide. In Kazakhstan, it is among the five leading causes of cancer death. However, local epidemiological studies of PC are scarce. A retrospective population-based study was conducted to investigate the PC incidence, mortality, and survival in Kazakhstan, using data from the Electronic Registry of Oncological Patients for the period 2014–2023. Methods: Incidence, prevalence, and crude mortality rates were calculated per 100,000 population. The all-cause mortality rate per 1000 person-years (PY) was obtained based on socio-demographic and medical characteristics and for different regions. Survival analysis was performed using the Kaplan–Meier method and Cox regression models. Results: A total of 11,934 cases were analyzed. The annual incidence rate significantly increased from 5.9 to 6.9 per 100,000. The mortality rate per 100,000 also increased from 4 to 6. The highest incidence was observed in the 60–74 age group (49.2%), with an equal sex distribution. The mortality rate was the highest in patients aged 75 and older. Northern and central regions had the highest incidence rates as of 2023. Atyrau, West Kazakhstan, Pavlodar, and Abay had the highest mortality rates per 1000 PY. The five-year survival rate was 10.9%. An older age, a male sex, advanced cancer stages, and a Russian ethnicity significantly increased the risk of death. Conclusions: PC represents a significant healthcare problem in Kazakhstan, with late diagnosis and poor survival being the main challenges. This study highlights the need to improve the timely detection of PC and address the identified disparities. Full article

Consumers are increasingly willing to pay a premium for high-quality extra virgin olive oils (HQ-EVOOs) with specific sensory or nutraceutical properties, and originating from particular botanical or geographical origins. Regarding geographic origin, Italy is one of the main producers, with many local production areas, each characterized by its own distinctive typicity. The aim of this study is the chemical, sensory, and nutraceutical profiling of HQ-EVOO produced over two production years in Montespertoli (province of Florence) by 12 producers involved in the “MontEspertOlio” project, funded by the Tuscan Region. Oils were produced based on a production process previously defined and specifically applied to this territory. The shelf-life of the oil was also evaluated over a 12-month period. Legal quality parameters were analyzed according to EU regulation. Phenolic compounds, tocopherols, fatty acid composition, and volatile compounds were analyzed using HPLC-DAD, HPLC-FLD, HS-SPME-GC-MS, and GC-FID, respectively. Finally, sensory analysis was conducted using the Panel Test method. Results showed that Montespertoli HQ-EVOO is characterized by distinctive sensory and chemical traits that fully match consumer preferences, even across two production years characterized by different growing conditions. The shelf-life performance was excellent over 12 months, also showing a protective effect of greater bottle sizes against oxidation. Full article

This study investigates the environmental regulation of sex expression and seed yield stability in four Thai dioecious hemp (Cannabis sativa L.) cultivars (RPF1, RPF2, RPF3, and RPF4) under different seasonal conditions to optimize seed production. The experiment was conducted across two planting periods (in-season and off-season) to evaluate the effects of varying day lengths and temperatures on growth, reproductive development, and yield. The results showed that shorter day lengths and lower temperatures during the off-season led to an increased proportion of female plants across all cultivars, except RPF3, which exhibited a stable female-to-male ratio. RPF4 had the highest increase in female plants (16%), followed by RPF1 and RPF2 (10%). Seed yield was significantly influenced by seasonal changes, with RPF3 and RPF4 consistently outperforming the other cultivars. In the in-season, RPF3 and RPF4 produced the highest seed yields, reaching 83.4 g/plant and 81.6 g/plant, respectively. During the off-season, both cultivars experienced a decline in seed yield (by 24–26%), primarily due to a reduction in seed production in secondary inflorescences. However, RPF3 compensated for this loss with a 31% increase in seed production at main inflorescences, ensuring yield stability. RPF4 maintained its high yield potential by increasing the proportion of female plants, offsetting the decline in seed yield per plant. Additionally, cumulative growing degree days (CGDD) at harvest were comparable between seasons, with values of 2434 °Cd (in-season) and 2502 °Cd (off-season), indicating that temperature accumulation remained within an optimal range for seed maturation. The study highlights the importance of cultivar selection based on yield component stability and adaptability to seasonal variations. These findings provide valuable insights for improving hemp seed production strategies in Thailand’s diverse agro-climatic conditions. Full article

Climate change has a complex impact on the agricultural crop system, with knowledge of the processes being necessary to assist decisions that guide the adaptation of society to profound structural changes. This study aims to highlight the main changes generated by the modification of climatic parameters (increasing air temperature, humidity and precipitation and decreasing wind speed) on agricultural crops in a region with important changes in its economic profile due to urban extension and land use modification. The analysis methodology is based on the Cropwat software to highlight the temporal variability of crop evapotranspiration, effective rain and water requirements for different crops—strawberry, sunflower and pea—and the possibility of using other types of crops with higher yield and lower water needs. The methodology used highlights this fact, showing that major changes are needed in the choice of crop schemes and future technological processes in the current context of climate change. The current results of the study, conducted over a period of 30 years (1991–2020), showed that the climatic, land use and economic changes in the study area have led to a decrease in evapotranspiration and crop water requirements due to the amounts of precipitation that can provide for the water needs of strawberry, sunflower and pea crops. The irrigation requirements during the analysis period 1991–2020 varied from <10 mm/year to 120 mm/year for strawberry crops, and can exceed 300 mm/year for sunflower and pea crops, having higher values in years with a precipitation deficit (effective rain less than 100 mm). Analyzing the irrigation requirements during the vegetation growing seasons shows that for pea and strawberry the trend is decreasing, but without a significance level. Only for the sunflower crop is an increasing trend recorded in the initial and late stages. The results obtained provide a methodological framework as well as concrete information for decision-makers in the field of agriculture who must build adaptation mechanisms for climate challenges. Full article

Concentrated apple juice (AJC) is a globally traded commodity, with major producers such as China, Poland, and the United States supplying AJC to markets worldwide. The aim of this article is to determine the competitive position of the main global exporters of concentrated apple juice. It also seeks to analyze changes in their positions over the period from 2005 to 2023. Assessing competitive position is important for several economic and business reasons, including identifying leading exporters and recognizing both growing and declining markets. The competitive position was measured using Market Share (MS) indicators, Gross and Net Export Orientation indicators (E_gr, E_net), and the Revealed Comparative Advantage (RCA) index. The results reveal significant structural shifts in global AJC trade. Most notably, China’s declining competitiveness, reflected across all indicators, led to its loss of market leadership. This raises questions about the reasons for this decline and whether it presents opportunities for other exporters. This signals a broader reconfiguration in the global AJC supply chain, driven in part by domestic economic changes, such as rising consumption and decreasing export orientation. Simultaneously, other countries, particularly in Eastern Europe, show varying degrees of competitive growth, with Moldova and Ukraine emerging as key players. These trends suggest a diversification of supply sources and a more fragmented competitive landscape. Although national differences persist, the analysis indicates that structural and economic transformations, rather than short-term price signals, are driving the evolving global competitiveness in the AJC market. The observed weak correlations between prior-year apple prices and RCA confirm that broader market and policy factors play a more decisive role. Full article

This study advances circular economy initiatives by advocating for the use of Multi-Criteria Decision-Making (MCDM). MCDM methods address the complex multi-faceted aspects of a product or process. They enable conflicting calculations of energy, cost, environmental criteria, and payback periods to be balanced. A systematic critical systematic review and bibliometric analysis were conducted to investigate the contribution of MCDM to the circular economy. The Scopus database was the primary data source reviewed. The geographical distribution, main research sources, and keyword co-occurrences were analyzed across 31 peer-reviewed book chapters, conference papers, and journal articles. The journal Sustainability (Switzerland) had the most publications (4), followed by the Journal of Business Strategy and the Environment and the Journal of Cleaner Production, each with two articles. Recently MCDM has gained popularity as a tool for evaluating the circular economy. This growing interest may be attributed to the complexity of the circular economy, as MCDM effectively balances multiple environmental criteria while integrating evaluations of economic cost and social impact. Criteria are incommensurable as each criterion has a distinct unit of measurement, making it impossible to compare outcomes across different indicators. MCDM is thus an ideal technique for assessing different options by integrating criteria within testable frameworks. However, no established patterns for selecting specific MCDM methods were identified. This is despite some options (e.g., combinations of AHP and TOPSIS) being used more frequently than others. In conclusion, all the studies identified financial factors as the most significant or highly sensitive issue in the transition toward a circular economy. Full article

Aluminum alloy AA6082 (Al-Si-Mg) is a lightweight alloy that requires thick barrier coatings to be protected from localized corrosion. Plasma Electrolytic Oxidation (PEO) coating is a common anodic surface treatment used for growing protective oxides; the main process variables of PEO are the composition of the electrolytic solution and the electrical input. This work focuses on the optimization of the electrical input by comparing different coatings produced by potentiostatic PEO at the effective potential of 350 V, applied by different combinations of voltage ramps with various slopes and maintenance times at the fixed potential. All processes lasted five minutes. The innovative character of this research work is the evaluation of the combined effect of the anodizing voltage and its different trends with time on the coating structure and morphology. The corrosion resistance of coated AA6082 is assessed in contact with chlorides, reproducing seawater. The resulting anodic coatings were compared in terms of structure, composition (thickness, XRD, SEM-EDS) and corrosion resistance (potentiodynamic polarization and electrochemical impedance spectroscopy), finding that longer maintenance at high anodizing potentials promotes localized high-energy plasma discharges, producing larger pores and thicker, but less protective coatings. Results show that the coating thickness increases with the maintenance time (maximum thickness value~17.6 μm). Shorter maintenance periods and longer voltage ramps lead to a lower surface porosity and enhanced corrosion performances of the oxide. The thinnest and least porous coating exhibits the best corrosion behavior (CR~1.1 μm/year). Full article

Understanding vegetation phenology dynamics is essential for evaluating ecosystem responses to environmental changes. While previous studies have primarily focused on the correlation between vegetation phenology and climate variables, the integrated effects of meteorological factors, topography, and greenhouse gas (GHG) have often been overlooked. This study aims to analyze the spatiotemporal variations in grassland phenology on the southern slopes of the Qilian Mountains from 2002 to 2022, investigating the combined effects of these environmental factors. Our findings reveal significant spatial heterogeneity in vegetation phenology during the study period. Specifically, the start of the growing season (SOS), length of growing season (LOS), and end of the growing season (EOS) advanced, lengthened, and delayed by 0.35, 0.55, and 0.20 days per year, respectively. Climate factors were the primary drivers of phenological changes, with annual precipitation being the main determinant of SOS and LOS, while annual minimum temperature significantly influenced EOS. Topography and GHG had indirect effects on phenology, influencing both annual precipitation and temperature. Additionally, topography affected phenology through its impact on N₂O and CO₂ emissions. This study highlights the complex interactions between climate, topography, and GHG in shaping vegetation phenology, providing new insights into the driving mechanisms behind phenological changes in semi-arid grassland ecosystems. Full article

Viticulture represents an important agricultural sector in Oltenia, which is one of the Romanian regions most affected by temperature increases. The main purpose of the present study was to analyze the changes in climate suitability for grapevine and wine production against this climate context in the region. Two specific bioclimatic indices were applied, namely the bioclimatic index and the oenoclimate aptitude index, both reflecting the cumulated influence of temperature, actual sunshine duration, and precipitation amounts on the grapevine during the growing season (1 April–30 September). The indices were calculated as average values for the period 1961–2020. In order to emphasize potential shifts in suitability, the mean, maximum, and minimum values were calculated for two distinct periods, 1961–1990 and 1991–2020. The results of the analysis underlined three distinct suitability changes: the area suitable for quality red wines shifting northwards (on average, about 30′ of latitude or 55.5 km), including the eastern part of the Getic Subcarpathians, which is not currently part of any winegrowing region; the emerging new areas suitable for quality white wine (the western part of the Subcarpathians); and a potentially overly hot climate developing in Southern Oltenia where grapevine varieties are currently grown. Thus, the development of adequate adaptation strategies for viticulture to climate change in the region should be considered in the near future. Full article

Telework has become a crucial element of the modern business landscape, driven by transformations sparked by multiple global crises. The transition from traditional, in-office work to telework, sometimes mandated by revolutionary circumstances (such as the COVID-19 pandemic), has highlighted both the advantages and challenges associated with this mode of work organization. In this context, the present study examines the effects of telework as experienced by employees and managers during two key periods: the COVID-19 pandemic and the introduction of chatbots. Through 24 interviews conducted and analyzed across these two timeframes (2021 and 2024) using NVivo 14 Windows software, the data were organized and interpreted within the framework of the Job Demands–Resources (JD-R) model. The main findings focus on organizational communication, sustainability, and work efficiency, while also highlighting associated benefits and drawbacks. The results demonstrate the importance of adapting organizational resources to meet growing job demands in order to maintain desired levels of efficiency and effectiveness while avoiding burnout, productivity declines, or other negative outcomes in the context of telework. This research contributes to understanding the evolution of telework by offering practical insights for sustaining high levels of motivation and workforce engagement in achieving organizational objectives in the hybrid work era. This paper emphasizes the significance of the JD-R Model in analyzing dynamic work environments, providing relevant perspectives for organizations on the continuously evolving dimensions of job demands, job resources, and outcomes. Full article

E-leadership has become particularly prominent in the public sector over the last five years. The urgent shift requires more remote work and management via information and communication technologies. In recognition of its ever-growing popularity, the objective of this article is to provide a systematic review of the existing literature on e-leadership within public sector organisations and identify key research approaches and outcomes. The analysis provides a framework of research on e-leadership in public sector entities, by focusing on various theoretical, methodological, empirical and contextual perspectives, specifically tailored to public sector organisations. The detailed framework, presented here, incorporates dimensions, approaches, clusters and findings of previous research (articles, published in the period 2013–2022), aiding a deeper understanding of the phenomenon and its practical implementation. The study complies with PRISMA 2020 requirements. As it shall be demonstrated, interest in the phenomenon surged during the pandemic, particularly within educational and management disciplines. The findings highlight a predominant focus on leadership within educational institutions, whilst areas such as healthcare and public governance remain under-researched. The most common theoretical approach adopted is associated with the transformational leadership theory and encompasses three main interpretations. Specifically, it evaluates e-leadership as a strategic approach, a leadership process and a leadership transformation. Qualitative methodology predominates in e-leadership research within the public sector, with quantitative and mixed-method approaches being less frequent. Addressing the challenges identified by previous research, such as competency and infrastructure deficiencies, is crucial for advancing knowledge of e-leadership in the public sector and improving sustainable performance. Full article

Nowadays, the security and stability of the global industrial chain are facing unprecedented challenges. In this context, understanding how industrial robots affect chain resilience is key to promoting high-quality economic development. This study focuses on 104 cities in the Yangtze River Delta, using data from 2006 to 2021. It applies a threshold regression model and a spatial Durbin model to examine how industrial robot penetration drives chain resilience and how its effects spread across regions. The results reveal three main findings: First, the integration of advanced manufacturing and modern services, together with strong urban innovation capacity, plays a significant role in enhancing industrial chain resilience. Second, this study evaluates policy experiments, such as Low-Carbon City and Broadband China initiatives, using a multi-period difference-in-differences model. The findings show that pilot cities involved in these programs demonstrate higher levels of chain resilience. Third, the relationship between robot penetration and chain resilience shows clear spatial and temporal patterns. Cities with higher robot usage tend to drive development in surrounding areas. This, in turn, encourages more intensive production and fosters stronger coordination across industries. Overall, this study contributes to the growing body of research on chain resilience. More importantly, it offers practical policy insights. Governments and regional firms can work together to build a new development model that enhances resilience and supports long-term economic stability. Full article