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Found 6374 publications
Future of Agrivoltaic projects: A review from the technological forecasting perspective
Publication Name: Cleaner Engineering and Technology
Publication Date: 2025-09-01
Volume: 28
Issue: Unknown
Page Range: Unknown
Description:
Agrivoltaic systems integrate photovoltaic (PV) energy generation with agricultural production, creating synergies that enhance land-use efficiency and environmental sustainability. This article reviews agrivoltaic technologies to identify key trends and the most promising future research and development directions. The method applied involves selecting and analysing relevant literature sources and filtering them with regard to the essential questions that need to be answered for the climates of Central Europe and China. These include global development, current applications, and technological progress. The analysis reveals growing attention to system design, performance optimisation, and crop compatibility. Innovations such as bifacial and spectrally selective PV modules boost energy yields while maintaining suitable conditions for shade-tolerant crops like leafy greens and berries. The analysis confirmed the high potential of sustainability benefits (societal, economic, and environmental) and revealed the need for systematic investigations of significant performance factors, including location and system design. A relatively underinvestigated factor is the protection of crops from excessive sunlight, which has become increasingly important. The modelling and optimisation of system operation is also necessary to provide decision-makers with robust tools for project assessment. A roadmap is proposed to guide future research and development.
Open Access: Yes
Navigating AI-Driven Financial Forecasting: A Systematic Review of Current Status and Critical Research Gaps
Publication Name: Forecasting
Publication Date: 2025-09-01
Volume: 7
Issue: 3
Page Range: Unknown
Description:
This systematic literature review explores the application of artificial intelligence (AI) and machine learning (ML) in financial market forecasting, with a focus on four asset classes: equities, cryptocurrencies, commodities, and foreign exchange markets. Guided by the PRISMA methodology, the study identifies the most widely used predictive models, particularly LSTM, GRU, XGBoost, and hybrid deep learning architectures, as well as key evaluation metrics, such as RMSE and MAPE. The findings confirm that AI-based approaches, especially neural networks, outperform traditional statistical methods in capturing non-linear and high-dimensional dynamics. However, the analysis also reveals several critical research gaps. Most notably, current models are rarely embedded into real or simulated trading strategies, limiting their practical applicability. Furthermore, the sensitivity of widely used metrics like MAPE to volatility remains underexplored, particularly in highly unstable environments such as crypto markets. Temporal robustness is also a concern, as many studies fail to validate their models across different market regimes. While data covering one to ten years is most common, few studies assess performance stability over time. By highlighting these limitations, this review not only synthesizes the current state of the art but also outlines essential directions for future research. Specifically, it calls for greater emphasis on model interpretability, strategy-level evaluation, and volatility-aware validation frameworks, thereby contributing to the advancement of AI’s real-world utility in financial forecasting.
Open Access: Yes
Integrating Behavioral and Technical Competencies: An Exploratory Project Management Model for Automotive R&D
Publication Name: International Journal of Research in Industrial Engineering
Publication Date: 2025-09-01
Volume: 14
Issue: 4
Page Range: 669-704
Description:
The study addresses the growing demand for evidence-based methods to assess the effectiveness of project managers in engineering-intensive industries. An exploratory competency model was developed in a German automotive R&D service division, integrating both behavioral and technical dimensions into a quantifiable measure termed the competency coefficient (K). Ten project managers, classified as either superior or average performers, were evaluated across 20 individual competencies. Behavioral Event Interview (BEI) results revealed substantial differences between the two groups, with effect sizes exceeding d = 2.0 for competencies such as concern for order, customer orientation, and impact and influence, while core cognitive competencies Analytical thinking (AT), conceptual thinking (CT), information seeking (INFO) demonstrated significant but more variable effects (d = 1.2–2.0). Expert panel evaluations (n = 33) showed strong consensus (Kendall’s W = 0.59, p <.001), with average relevance scores above 80%. Sensitivity analyses of alternative weighting schemes for the K metric (e.g., 3–2–1; 4–2–1; 5–3–1) yielded highly stable rankings (Spearman’s ρ ≥ 0.97), indicating robustness of the results. Initial validation against project performance indicators suggested significant positive correlations (r = 0.65–0.88, p <.01) between K values and Key Performance Indicators (KPIs). Within the examined automotive R&D division, the findings suggest that individual competencies—particularly cognitive and INFO skills—were the most distinctive differentiators of high-performing project managers, whereas technical expertise alone did not explain performance differences. The competency coefficient provides a structured, quantifiable framework for linking competencies to project outcomes, though further validation across broader datasets and organizational contexts remains necessary.
Open Access: Yes
Unlocking energy efficiency: Exploring the dynamic evolution and regional correlations in the Huaihe Eco-economic Belt
Publication Name: Gondwana Research
Publication Date: 2025-09-01
Volume: 145
Issue: Unknown
Page Range: 57-70
Description:
Energy is the cornerstone of today's social development, and it is of great significance to comprehensively and objectively reflect the level of energy efficiency (EE) and regional differences. Taking the Huaihe Eco-economic Belt (HEB) as an example, the EE of 28 cities in the HEB from 2008 to 2021 was measured and analyzed by using the super-efficiency SBM model with non-expected outputs; Using Dagum Gini coefficient to explore regional differences in EE levels and their sources; It also explores the dynamic evolutionary pattern and spatial correlation of EE levels using kernel density estimation, Markov transfer probability matrix, and Moran index. The results are as follows: (1) The value of EE in the HEB shows a trend of change that first declines and then rises, with relatively small changes; (2) Regional differences in EE show a fluctuating and increasing trend, with hypervariable density being the most important source of overall regional differences, which are much greater within regions than between regions; (3) The development of EE has been polarized, and the hierarchy of EE levels is relatively stable, with the phenomenon of “club convergence”; (4) There is spatial agglomeration in the level of EE development, with cities in the midwest parts of the country mostly falling in the high-value agglomeration area of the first quadrant, and cities in the northern part of the country mostly falling in the low-value agglomeration area of the third quadrant, with a few cities experiencing spatial and temporal jumps. This paper will be valuable to the government in identifying energy-inefficient cities, formulating targeted policy measures, and promoting the synergistic sustainable development of HEB.
Open Access: Yes
Towards the synthesis of reliable and resilient complex networks
Publication Name: Current Opinion in Chemical Engineering
Publication Date: 2025-09-01
Volume: 49
Issue: Unknown
Page Range: Unknown
Description:
Process synthesis methodologies have traditionally focused on optimizing the economic criteria. However, owing to the complexity of real systems, external factors, such as expected or unexpected events or disturbances, negatively affect the performance of optimal networks. In this context, it becomes essential to consider the effect of such events on the performance of the network in the early design stages. This work presents a comprehensive review of the contributions related to this relevant topic, focusing on two widely utilized indicators: reliability and resilience. Reliability focuses on the probability of system failures due to disturbances, and resilience analyzes the behavior of the system after disturbances and its capacity to recover over time. Relevant contributions are reviewed, which present deterministic and stochastic methods to estimate these indicators, with a special focus on the design phase. Moreover, this work also presents a perspective on using machine learning methods on complex systems datasets as an emerging direction for enhancing the estimation of these properties. This contribution highlights recent advancements in this field and emphasizes the relevance of resilience and reliability as key metrics for developing safer processes with improved operability.
Open Access: Yes
Genetic Strategies for Improving Pig Robustness: Reducing Antibiotic Use Through Enhanced Resilience and Disease Resistance
Publication Name: Animals
Publication Date: 2025-09-01
Volume: 15
Issue: 18
Page Range: Unknown
Description:
This review investigates genetic strategies aimed at improving robustness in pigs to enhance disease resistance and reduce reliance on antibiotics. Robustness refers to a pig’s ability to stay healthy and productive under stressful or challenging conditions. The review outlines current breeding practices focused on key traits such as maternal ability, growth, immune function, and survival, and highlights that these robustness-related traits show measurable heritability, making them suitable for genetic improvement. Special attention is given to resistance against porcine reproductive and respiratory syndrome (PRRS), a major disease in swine. We also evaluate breed-specific differences, environmental influences, and immune response profiles, emphasizing their impact on breeding outcomes. The development of robust pig lines emerges as a sustainable strategy to reduce antibiotic dependence and enhance herd health. A distinctive contribution of this work is the integration of genetic robustness and resilience strategies with antibiotic stewardship objectives. We link genomic selection, advanced phenotyping, and targeted management interventions within a One Health framework to outline actionable, system-level pathways for reducing antimicrobial inputs. To our knowledge, this combined genetic and public health perspective has not been comprehensively addressed previously.
Open Access: Yes
DOI: 10.3390/ani15182753
Comparison of Interlimb Coordination During Soccer Instep Kicking Between Elite and Amateur Players
Publication Name: European Journal of Sport Science
Publication Date: 2025-09-01
Volume: 25
Issue: 9
Page Range: Unknown
Description:
This study investigates how interlimb joint coordination influences foot speed during soccer instep kicking, using continuous relative phase (CRP) as a quantitative method. The sample includes 15 elite and 15 amateur players to examine potential differences in coordination patterns and their impact on performance. Specifically, we focused on the coordination between hip, knee, and ankle joints in the forefoot-back kicking motion. Results indicated that elite players exhibited significantly higher hip-knee CRP in the coronal plane during 62%–81% of movement duration (p = 0.015) and higher knee-ankle CRP in the vertical plane during 78%–100% (p = 0.013). Moreover, elite players had significantly greater hip-knee mean absolute relative phase (MARP) and deviation phase (DP) in the coronal plane (p < 0.001), as well as increased knee-ankle DP (p = 0.04). In the horizontal plane, hip-knee MARP was also greater in the elite players compared to amateurs (p < 0.001). Further analysis revealed a significant negative correlation between hip-knee CRP and foot velocity in the sagittal plane (R = −0.66, p < 0.001), whereas a significant positive correlation was observed between knee-ankle CRP and foot velocity in the horizontal plane (R = 0.56, p = 0.002). These findings suggest that elite players have superior joint coordination, which contributes to a faster foot velocity at the moment of ball impact. Understanding these coordination patterns provides valuable insights into optimizing kicking techniques. The findings of this study suggest that joint coordination may play an important role in enhancing kicking foot speed, which could inform future training approaches aimed at improving soccer performance.
Open Access: Yes
DOI: 10.1002/ejsc.70041
All Roads Lead to Excellence: A Comparative Scientometric Assessment of French and Dutch European Research Council Grant Winners’ Academic Performance in the Domain of Social Sciences and Humanities
Publication Name: Publications
Publication Date: 2025-09-01
Volume: 13
Issue: 3
Page Range: Unknown
Description:
This study investigates how differing national research governance models impact academic performance by comparing European Research Council (ERC) grant winners in the social sciences and humanities from France and the Netherlands. Situated within the broader context of centralized versus decentralized research systems, the analysis aims to understand how these structures shape publication trends, thematic diversity, and collaboration patterns. Drawing on Scopus and SciVal data covering 9996 publications by 305 ERC winners between 2019 and 2023, we employed a multi-method approach, including latent Dirichlet allocation for topic modeling, compound annual growth rate analysis, and co-authorship network analysis. The results show that neuroscience, climate change, and psychology are dominant domains, with language and linguistics particularly prevalent in France and law and political science in the Netherlands. French ERC winners are more likely to be affiliated with national or sectoral institutions, whereas in the Netherlands, elite universities dominate. Collaboration emerged as a key success factor, with an average of four co-authors per publication and network analyses revealing central figures who bridge topical clusters. International collaborations were consistently linked with higher visibility, while single-authored publications showed limited impact. These findings suggest that institutional context and collaborative practices significantly shape research performance in both countries.
Open Access: Yes
An effective reduction method with Caughey damping for spurious oscillations in dynamic problems
Publication Name: Meccanica
Publication Date: 2025-09-01
Volume: 60
Issue: 9
Page Range: 2927-2946
Description:
The numerical solution of dynamic problems often results spurious oscillations. In order to eliminate them, a damping effect must be included in the numerical scheme. However, the concrete shape of the damping characteristics has a great importance in the efficiency of oscillation reduction. In this article, a novel approach has been introduced with adjustable damping character. The damping effect is exerted as viscous damping according to the formulation of Caughey damping. Using the proposed method, a wide range of damping curves can be approximated with high accuracy. The newly developed method is mainly useful for contact-impact and wave propagation problems.
Open Access: Yes
