Search Results (2,355)

The endurance and vitality of European agriculture are threatened by the aging of farmers, together with the lack of generational change. The small share of young farmers also impacts on the innovative capacity and competitiveness of the sector. The Common Agricultural Policy of the European Union started addressing the issue long ago by providing financial aid to help young farmers to start up. Over time, the aid increased and packages of measures were set to reinforce the aid and to promote investments, innovations, and networks at the farm level. While the literature focuses on analyzing the effectiveness of the start-up aid in fostering new entries, this paper assumes an original perspective as it seeks to assess whether this aid has actually promoted innovations and networks in the beneficiary farms. The analysis relies on sample data collected in 2021 in Italy and Poland via interviews of 500 farmers under 40 who had entered the sector both with and without the aid. A probit model estimates whether the beneficiaries have a higher probability to innovate and network. Then, the contribution of the aid to the intensity of the adoption of innovations and networks is estimated via an Average Treatment Effect on the Treated model (ATT). Results suggest that the start-up aid increased the adoption of innovations and networks. The ATT indicates that this positive effect holds even after correcting for self-selection bias. By adopting an original perspective, our analysis suggests that the start-up aid for young farmers goes beyond rejuvenating agriculture by fostering innovation at the farm level and by promoting networking, thus enhancing agricultural change. However, farmer behaviors in the two countries are different, suggesting quite complex patterns for the impact of this measure. Full article

This article proposes a methodology for establishing a relationship between the change rate of a given gene (relative to a given taxon) together with the amino acid composition of the proteins encoded by this gene and the traits of the species containing this gene. The methodology is illustrated based on the mammalian genes responsible for regulating the circadian rhythms that underlie a number of human disorders, particularly those associated with aging. The methods used are statistical and bioinformatic ones. A systematic search for orthologues, pseudogenes, and gene losses was performed using our previously developed methods. It is demonstrated that the least conserved Fbxl21 gene in the Euarchontoglires superorder exhibits a statistically significant connection of genomic characteristics (the median of dN/dS for a gene relative to all the other orthologous genes of a taxon, as well as the preference or avoidance of certain amino acids in its protein) with species-specific lifespan and body weight. In contrast, no such connection is observed for Fbxl21 in the Laurasiatheria superorder. This study goes beyond the protein-coding genes, since the accumulation of amino acid substitutions in the course of evolution leads to pseudogenization and even gene loss, although the relationship between the genomic characteristics and the species traits is still preserved. The proposed methodology is illustrated using the examples of circadian rhythm genes and proteins in placental mammals, e.g., longevity is connected with the rate of Fbxl21 gene change, pseudogenization or gene loss, and specific amino acid substitutions (e.g., asparagine at the 19th position of the CRY-binding domain) in the protein encoded by this gene. Full article

Background: After myocardial infarction (MI), adverse left ventricular (LV) remodeling may occur. This is followed by LV hypertrophy and eventually heart failure. The remodeling process is complex and goes through multiple phases. The aim of this study was to investigate the expression of HMGB1, TGF-β1, BIRC3, ADAM17, CDKN1A, and FTO, each involved in a specific step of LV remodeling, in association with the change in the echocardiographic parameters of LV structure and function used to assess the LV remodeling process in the peripheral blood mononuclear cells (PBMCs) of patients six months after the first MI. The expression of selected genes was also determined in PBMCs of controls. Methods: The study group consisted of 99 MI patients, who were prospectively followed-up for 6 months, and 25 controls. Cardiac parameters, measured via conventional 2D echocardiography, were evaluated at two time points: 3–5 days and 6 months after MI. The mRNA expression six-months-post-MI was detected using TaqMan^® technology (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA). Results:HMGB1 mRNA was significantly higher in patients with adverse LV remodeling six-months-post-MI than in patients without adverse LV remodeling (p = 0.04). HMGB1 mRNA was significantly upregulated in patients with dilated LV end-diastolic diameter (LVEDD) (p = 0.03); dilated LV end-diastolic volume index (LVEDVi) (p = 0.03); severely dilated LV end-systolic volume index (LVESVi) (p = 0.006); impaired LV ejection fraction (LVEF) (p = 0.01); and LV enlargement (p = 0.03). It was also significantly upregulated in PBMCs from patients compared to controls (p = 0.005). TGF-β1 and BIRC3 mRNA were significantly lower in patients compared to controls (p = 0.02 and p = 0.05, respectively). Conclusions: Our results suggest that HMGB1 is involved in adverse LV remodeling six-months-post-MI, even on the mRNA level. Further research and validation are needed. Full article

This article addresses the scanning path plan strategy of a rover team composed of three rovers, such that the team explores unknown dark outer space environments. This research considers a dark outer space, where a rover needs to turn on its light and camera simultaneously to measure a limited space in front of the rover. The rover team is deployed from a symmetric base station, and the rover team’s mission is to scan a bounded obstacle-rich workspace, such that there exists no remaining detection hole. In the team, only one rover, the hauler, can locate itself utilizing stereo cameras and Inertial Measurement Unit (IMU). Every other rover follows the hauler, while not locating itself. Since Global Navigation Satellite System (GNSS) is not available in outer space, the localization error of the hauler increases as time goes on. For rover’s location estimate fix, one occasionally makes the rover home to the base station, whose shape and global position are known in advance. Once a rover is near the station, it uses its Lidar to measure the relative position of the base station. In this way, the rover fixes its localization error whenever it homes to the base station. In this research, one makes the rover team fully scan a bounded obstacle-rich workspace without detection holes, such that a rover’s localization error is bounded by letting the rover home to the base station occasionally. To the best of our knowledge, this article is novel in addressing the scanning path plan strategy, so that a rover team fully scans a bounded obstacle-rich workspace without detection holes, while fixing the accumulated localization error occasionally. The efficacy of the proposed scanning and localization strategy is demonstrated utilizing MATLAB-based simulations. Full article

Detection of stress and the development of innovative platforms for stress monitoring have attracted significant attention in recent years due to the growing awareness of the harmful effects of stress on mental and physical health. Stress is a widespread issue affecting individuals and often goes unnoticed as a health concern. It can lead to various negative physiological conditions, including anxiety, depression, cardiovascular diseases and cognitive impairments. The aim of this paper is to provide an overview of studies focusing on embedded devices for non-invasive stress detection, primarily in the form of a modified computer mouse or keyboard. This study not only fills a critical gap in the literature but also provides valuable insights into the design and implementation of hardware-based stress-detection methods. By focusing on embedded devices, specifically computer peripherals, this research highlights the potential for integrating stress monitoring into everyday workplace tools, thereby offering practical solutions for improving occupational health and well-being. Full article

Background/Objectives: Frequent poor dietary choices can have significant consequences. To understand the underlying decision-making processes, most food choice tasks present a binary choice between a tasty but less healthy option and a healthy but less tasty option. It is assumed that people come to a decision by trading off the respective health and taste values. However, it is unclear whether and to what extent food choice goes beyond this. Methods: We use a novel eye-tracking experiment where we compare a typical food choice task (image condition) with an abstract value-based decision-making task using pre-matched percentages of health and taste (text condition; e.g., 10% healthy and 80% tasty) in 78 participants. Results: We find a higher frequency of unhealthy choices and reduced response times in the image condition compared to the text condition, suggesting more impulsive decision making. The eye-tracking analysis shows that, in the text condition, the item corresponding to the subsequent choice receives more attention than the alternative option, whereas in the image condition this only applies to the healthy item. Conclusions: Our findings suggest that decision-making in typical food choice tasks goes beyond a mere value-based trade-off. These differences could be due to the involvement of different attentional processes in typical food choice tasks or due to the modality of stimulus presentation. These results could help to understand why people prefer tasty but unhealthy food options even when health is important to them. Full article

Pesticide use in crops is a severe problem in some countries. Each country has its legislation for use, but they differ in the degree of tolerance for these broadly toxic products. Several synthetic pesticides can cause air, soil, and water pollution, contaminating the human food chain and other living beings. In addition, some of them can accumulate in the environment for an indeterminate amount of time. The agriculture sector must guarantee healthy food with sustainable production using environmentally friendly methods. In this context, biological biopesticides from microbes and plants are a growing green solution for this segment. Several pests attack crops worldwide, including weeds, insects, nematodes, and microorganisms such as fungi, bacteria, and viruses, causing diseases and economic losses. The use of bioproducts from microorganisms, such as microbial biopesticides (MBPs) or microorganisms alone, is a practice and is growing due to the intense research in the world. Mainly, bacteria, fungi, and baculoviruses have been used as sources of biomolecules and secondary metabolites for biopesticide use. Different methods, such as direct soil application, spraying techniques with microorganisms, endotherapy, and seed treatment, are used. Adjuvants like surfactants, protective agents, and carriers improve the system in different formulations. In addition, microorganisms are a tool for the bioremediation of pesticides in the environment. This review summarizes these topics, focusing on the biopesticides of microbial origin. Full article

Unmanned Surface Vehicles (USVs) are rapidly becoming mission-indispensable for a variety of naval operations, from search and rescue to environmental monitoring and surveillance. Path planning lies at the heart of the operational effectiveness of USVs, since it represents the key technology required to enable the vehicle to transit the unpredictable dynamics of the marine environment in an efficient and safe way. The paper develops a critical review of the most recent advances in USV path planning and a novel classification of algorithms according to operational complexity: Basic Pathfinders, Responsive Pathfinders, and Advanced Strategic Pathfinders. Each category can adapt to different requirements, from environmental predictability to the desired degree of human intervention, and from stable and controlled environments to highly dynamic and unpredictable conditions. The review includes current methodologies and points out the state-of-the-art algorithmic approaches in their experimental validations and real-time applications. Particular attention is paid to the description of experimental setups and navigational scenarios showing the realistic impact of these technologies. Moreover, this paper goes through the key, open challenges in the field and hints at the research direction to leverage in order to enhance the robustness and adaptability of path planning algorithms. This paper, by offering a critical analysis of the current state-of-the-art, lays down the foundation of future USV path planning algorithms. Full article

Rotor dynamics plays a crucial role in the performance and safety of rotating machinery, with disk position and unbalance significantly impacting system behavior. This study investigates the dynamic characteristics of two rotor configurations: a centrally mounted unbalanced disk (Rotor05un) and an off-center unbalanced disk (Rotor025un). Using numerical simulations and Monte Carlo analysis, we examined critical speeds and orbital patterns for both configurations. Probability distributions of shaft orbital positions revealed distinct patterns for each configuration. Quantile analysis revealed approximate linear trends for Rotor025un, suggesting higher system stiffness and more predictable behavior near critical speeds. Cross-sectional analyses of the orbits provided insights into the complex interactions between disk position, gyroscopic effects, and system natural frequencies. These findings provide valuable insights for rotor system design, particularly for applications with non-ideal mass distributions. The study goes beyond traditional critical speed analysis to examine orbital patterns and point on orbit occurrence from a probabilistic perspective. Based on the simulation of the orbits, an orbital is determined that allows the probability of the shaft occurring at the analyzed distance from the origin to be determined. The paper also offers insights into the complex interaction behavior of chosen rotor configurations and highlights the importance of considering disk position in predicting and optimizing rotor dynamic behavior, contributing to the development of more robust and efficient rotating machinery. Full article

While strong islands generally constitute domains from which extraction is not possible, it has been observed that under certain conditions, they may allow DP but not PP gaps. Based on the recent literature on Asante Twi (Kwa, Ghana) and on novel data from Limbum (Grassfields Bantu, Cameroon), this paper shows that strong island configurations in these two African languages are permeable to nominal extractees without restrictions, but the otherwise admissible movement of VPs and PPs is blocked. As DP-displacement from islands shows properties of A¯-movement; an explanation in terms of base-generation and binding of a covert resumptive pronoun, which is only available for nominal elements, is not feasible. Taking into account the overall distribution of overt and covert resumptive pronouns, for Asante Twi, an account of the selective island permeability in terms of repair by resumption, as suggested in previous literature, might be possible. For the Limbum pattern, however, this paper argues that such an approach seems implausible. It then goes on to develop an analysis of selective island permeability based on the distribution of ϕ-features and their interaction with complementizer agreement. Full article

The role of autophagy goes far beyond the elimination of damaged cellular components and the quality control of proteins. It also cleanses cells from inclusions, including pathogenic viruses, and provides energy-forming components. The liver, which is an organ with increased metabolism, is made up of cells that are particularly vulnerable to damage. Therefore, detoxification of liver cells in the process of autophagy has become a very important issue clinically. The aim of this study was an immunohistochemical evaluation of proteins activated in rat liver cells at different stages of hyperbaric autophagy. The rats used for the study were randomly divided into six equivalent groups—three control groups and three experimental groups. Animals from the experimental groups were subjected to hyperbaric treatment in a hyperbaric chamber, with a pressure of 1.6 ATA for 120 min. They breathed atmospheric air. Rats were decapitated within 5 or 10 days after removal from the chamber. Immunohistochemical reactions with beclin 1, LC3B, RAB7, and HSC73 proteins were carried out on preparations made from liver slices. A three-step labeled streptavidin–biotin detection method of paraffin blocks (LSAB three-step) was used for immunohistochemical research. The results were evaluated using computer programs for morphometric analysis of microscopic images by calculating the mean surface areas occupied by a positive immunohistochemical reaction in individual groups for all antibodies tested. Increased closure of substrates in the autophagosome (beclin 1) induced late endosome transport and accelerated autophagosome maturation process (RAB7). Furthermore, a larger number of autophagosomes (LC3B) was observed in liver cells immediately after the cessation of hyperbaric activity; however, this decreased after 5 days. During this time, chaperone-mediated autophagy (HSC73) was observed on a larger scale. This means that increased macroautophagy induced by hyperbaric treatment weakens with time that has elapsed since the cessation of high pressure, whereas similarly induced chaperone-mediated autophagy intensifies over time. Full article

Carbonate formation is the key reservoir in Sichuan Basin for natural gas development. Compared with the early stage of development, the burial depth of targeted formation becomes deeper, and the formation temperature gets higher. So, the characteristics of acidizing effectiveness in high-temperature carbonate formations make this evaluation slightly difficult. Currently, it is common that a single parameter is considered to study acidizing effectiveness by simulation and experiment methods. In this paper, for a more accurate investigation of acidizing effectiveness, multiple parameters, including permeability change rate, fracture conductivity, and surface roughness, were introduced by a series of experiments. It is revealed that the permeability change rate is more than 57% when using gelled acid. As the amount of diverting agent increases in diverting acid, the viscosity of the acid grows to its peak with the reaction, making it easier to block the high permeability core temporarily and divert to acidify the low permeability core, where the permeability change rate of the low permeability core goes from 51.6% to 64.2%, which shows well acidizing effectiveness. In addition, the short-term and long-term conductivity of the samples from the three different formations are more than 200 mD∙m under high closure stress. The conductivity of Maokou Formation is the largest due to its high content of carbonate minerals and high dissolution rate. And the results of long-term conductivity are consistent with those of surface roughness, making the evaluation results more reliable for acidizing effectiveness. It is worth noting that temperature is a factor that cannot be ignored in the evaluation of acidizing effectiveness because it has a great influence on the performance of the acid system, such as viscosity and the reaction-reduced rate, leading to an acidizing effectiveness affect. So, the temperature resistance of an acid system is important as well. Full article

Agricultural productivity is one of the critical factors towards ensuring food security across the globe. However, some of the main crops, such as potato, tomato, and mango, are usually infested by leaf diseases, which considerably lower yield and quality. The traditional practice of diagnosing disease through visual inspection is labor-intensive, time-consuming, and can lead to numerous errors. To address these challenges, this study evokes the AgirLeafNet model, a deep learning-based solution with a hybrid of NASNetMobile for feature extraction and Few-Shot Learning (FSL) for classification. The Excess Green Index (ExG) is a novel approach that is a specified vegetation index that can further the ability of the model to distinguish and detect vegetative properties even in scenarios with minimal labeled data, demonstrating the tremendous potential for this application. AgirLeafNet demonstrates outstanding accuracy, with 100% accuracy for potato detection, 92% for tomato, and 99.8% for mango leaves, producing incredibly accurate results compared to the models already in use, as described in the literature. By demonstrating the viability of a deep learning/IoT system architecture, this study goes beyond the current state of multi-crop disease detection. It provides practical, effective, and efficient deep-learning solutions for sustainable agricultural production systems. The innovation of the model emphasizes its multi-crop capability, precision in results, and the suggested use of ExG to generate additional robust disease detection methods for new findings. The AgirLeafNet model is setting an entirely new standard for future research endeavors. Full article

This research investigates the possible influence of students’ perceptions of emerging AI technologies on university courses, focusing on their knowledge and perceived usefulness within engineering design. An evaluation tool implemented in a Microsoft Excel workbook was developed and tested to perform the process of data collection through well-known questionnaires, data analysis, and the generation of results, facilitating attention to class compositions and measuring AI awareness and perceived usefulness. The study considers traditional aspects such as roles within design teams and the psychological factors that may influence these roles, alongside contemporary topics like Large Language Models (LLMs). Questionnaires based on well-established theories were administered during courses on product innovation and representation, assessing both primary and secondary design roles. Primary roles focus on technical skills and knowledge, while secondary roles emphasize problem-solving approaches. The Big Five questionnaire was used to characterize students’ psychological profiles based on the main personality traits. Students’ perceptions of AI involvement and usefulness in engineering design were evaluated using questionnaires derived from the consolidated literature as well. Data were collected via Google forms from both in-class and off-line students. The first results of the workbook adoption highlight some relationships between personality traits, perceived roles in design teams, and AI knowledge and usefulness. These findings aim to help educators enhance course effectiveness and align courses with current AI advancements. The workbook is available to the readers to collect data and perform analyses in different countries, education disciplines, and as time goes by, in order to add the longitudinal point of view to the research. Full article