bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of agricultural machinery services on farmland transfer: a analytical perspective based on the profitability of grain production
Authors: Zhang Wenrui
Published: October 2024

Introduction

In the context of the deceleration of farmland scale management, a crucial question arises in agricultural development theory and practice: will service driven scale management in the production process become a viable alternative to farmland scale management, serving as the secondary pathway to achieve scale management in China?

Methods

To address this issue, an empirical analysis on the impact of agricultural machinery services on farmland transfer was conducted in this article using data from the China Rural Revitalization Survey database comprising 302 villages and 2,871 micro-farmers in 2020 by utilizing the ordinary least squares method and instrumental variable method.

Results and discussion

The results show that the implementation of agricultural machinery services will increase the rate of farmland transfer in villages. The effect of agricultural machinery services on increasing the profitability of large-scale farmers surpasses its effect on smallholder farmers, thereby motivating smallholder farmers to transfer farmland to large-scale farmers, consequently fostering the consolidation of farmland. In addition, power-intensive service links are more effective in increasing the rate of farmland transfer and fostering the concentration of farmland transfer compared to control-intensive service links. The impact of agricultural machinery services on enhancing the rate of farmland transfer and fostering the consolidation of farmland transfer is more pronounced on the plain areas compared to the hillmountainous areas. Consequently, this article demonstrates that service-driven scale management and farmland scale management are not merely alternatives but rather complementary strategies that mutually reinforce each other.
Analytical Solution for the Problem of Point Location in Arbitrary Planar Domains
Authors: Santos Vitor
Published: October 2024

This paper presents a general analytical solution for the problem of locating points in planar regions with an arbitrary geometry at the boundary. The proposed methodology overcomes the traditional solutions used for polygonal regions. The method originated from the explicit evaluation of the contour integral using the Residue and Cauchy theorems, which then evolved toward a technique very similar to the winding number and, finally, simplified into a variant of ray-crossing approach slightly more informed and more universal than the classic approach, which had been used for decades. The very close relation of both techniques also emerges during the derivation of the solution. The resulting algorithm becomes simpler and potentially faster than the current state of the art for point locations in arbitrary polygons because it uses fewer operations. For polygonal regions, it is also applicable without further processing for special cases of degeneracy, and it is possible to use in fully integer arithmetic; it can also be vectorized for parallel computation. The major novelty, however, is the extension of the technique to virtually any shape or segment delimiting a planar domain, be it linear, a circular arc, or a higher order curve.
Improving the Generalization Abilities of Constructed Neural Networks with the Addition of Local Optimization Techniques
Authors: Tsoulos Ioannis G. , Charilogis Vasileios , Tsalikakis Dimitrios , Tzallas Alexandros
Published: October 2024

Constructed neural networks with the assistance of grammatical evolution have been widely used in a series of classification and data-fitting problems recently. Application areas of this innovative machine learning technique include solving differential equations, autism screening, and measuring motor function in Parkinson’s disease. Although this technique has given excellent results, in many cases, it is trapped in local minimum and cannot perform satisfactorily in many problems. For this purpose, it is considered necessary to find techniques to avoid local minima, and one technique is the periodic application of local minimization techniques that will adjust the parameters of the constructed artificial neural network while maintaining the already existing architecture created by grammatical evolution. The periodic application of local minimization techniques has shown a significant reduction in both classification and data-fitting problems found in the relevant literature.
Entrepreneurship and Kinship: An Integrative Review of a Nascent Domain
Authors: Chakuzira Wellington , Mkansi Marcia , Okoche John Micheal Maxel
Published: October 2024

Contrary to the widely accepted adage ‘do not engage in business activities with relatives’, individuals from Chinese, Indian, and Pakistani backgrounds are achieving significant progress, while individual groups experience stagnation. While prior research offers substantial insights into the relationship between kinship and entrepreneurial ventures, there exists a paucity of information regarding the mechanisms through which certain kin individuals attain success while others do not. The principal inquiries revolve around the question, ‘In what ways do kinship networks contribute to entrepreneurial success?’ Furthermore, within a multicultural and heterogeneous framework, how might kinship networks serve as essential resources that promote entrepreneurial development, or do they instead pose additional challenges to such advancement? To address these inquiries, this study conducts an integrative review of entrepreneurship through the conceptual framework of kinship (kin-entrepreneurship), a notion distinctly from emerging disciplines. The contextual backdrop of this study is firmly anchored in the rising incidence of business failures and their resultant ramifications for sustainable economic development on a global scale. By employing an integrative review methodology that encompasses both bibliometric and content analyses of extant literature, adhering to the PRISMA guidelines, this research elucidates the fundamental components relevant to kin-entrepreneurship. In tackling this issue, the present investigation explores the trends, trajectories, and potential futures concerning the nexus of kinship and entrepreneurship. A bibliometric analysis was conducted on a dataset comprising 292 scholarly articles focused on kin-entrepreneurship, published between 1980 and 2023, sourced from the Scopus and Web of Science databases. Significant findings highlight “kinship-based business influencers” and “entrepreneurial environment and consequences”, as crucial themes. Subsequent to the discovery of the themes, this paper advocates for a paradigm shift from a narrow familial perspective on business to a more expansive kinship viewpoint, which can enhance comprehension of the complex dynamics within business environments where kinship-based business influencers are multifaceted, affecting economic performance (where entrepreneurs capitalize on these affiliations for economic advantage), decision-making (which improves business sustainability through resource allocation among kin), and employee relations (as kin connections foster both formal and informal employment opportunities) for entrepreneurs. Consequently, this study posits that kinship-oriented business dynamics play a crucial role in influencing entrepreneurial decision-making by offering social capital, resources, and strategic guidance, which are essential for mitigating existing entrepreneurial attrition rates and, in turn, are fundamental for fostering economic development.
Artificial Neural Network Model for Predicting Carrot Root Yield Loss in Relation to Mechanical Heading
Authors: Rybacki Piotr , Przygodziński Przemysław , Osuch Andrzej , Osuch Ewa , Kowalik Ireneusz
Published: October 2024

Modelling and predicting agricultural production processes have high cognitive and practical values. Plant growth, the threat of pathogens and pests, and the structure of agricultural machinery treatments are mostly non-linear, measurable processes that can be described mathematically. In this paper, a multiple regression analysis was carried out in the first step to check the non-linearity of the data and yielded a coefficient of determination of R2 = 0.9741 and the coefficient of determination corrected for degrees of freedom was R2adj = 0.9739. An artificial neural network model, called CH-NET, is then presented to predict the yield loss of carrot roots by leaving root mass in the field during harvest at the mechanical heading stage. The proposed network model has an architecture consisting of an input layer, three hidden layers with 12 neurons each, and an output layer with one neuron. Twelve input criteria were defined for the analysis and testing of the network, eight of which related to carrot root parameters and four to the heading machine. The training, testing, and validation database of the CH-NET network consisted of the results of field trials and tests of the operation of the patented (P.242097) root heading machine. The proposed CH-NET neural network model achieved global error (GE) values of 0.0931 t·ha−1 for predicting carrot root yield losses for all twelve criteria adopted. However, when the number of criteria is reduced to eight, the error increased to 0.0991 t·ha−1. That is, the prediction was realised with an accuracy of 90.69%. The developed CH-NET model allows the prediction of economic losses associated with root mass left in the field or contamination of the raw material with undercut leaves. The simulations carried out showed that minimum root losses (0.263 t·ha−1) occur at an average root head projection height of 38 mm and a heading height of 20 mm from the ridge surface.
Analysis of the Impact of Treatments Stimulating Branching on the Quality of Maiden Apple Trees
Authors: Kapłan Magdalena , Klimek Kamila E. , Buczyński Kamil
Published: October 2024

Nursery material intended for establishing intensive apple orchards should be characterised by a dominant and straight leader with an appropriate number of shoots that develop at the right height and are regularly spaced along the leader. The use of well-branched trees can lead to fruiting in the first year after planting. However, many apple varieties have difficulty forming lateral shoots due to strong apical dominance. The aim of the study was to assess the effectiveness of treatments stimulating the branching of maiden apple trees of the ‘Gloster’ variety. The research was carried out in 2017–2019 at a private nursery farm located in eastern Poland. The studied trees were subjected to a mechanical branching stimulation treatment, which consisted of pinching off 4–5 of the youngest leaves located below the growth cone, and chemical branching stimulation treatments, which consisted of applying growth regulator mixtures in the form of an aqueous solution, i.e., BA+GA3 and BA+GA4+7. The conducted studies showed that the type of branching-stimulating treatment had a significant effect on the height and trunk diameter of the maiden trees, the number of lateral shoots, the average length of one shoot and the sum of the lengths of all sylleptic shoots. The maiden trees treated with BA+GA3 were characterised by the best quality among the analysed combinations. Maiden apple trees treated with BA+GA3 were the tallest (2017—167.7 cm; 2018—175.3 cm; 2019—164.4 cm), produced the largest number of shoots (2017—6.5 pcs; 2018—6.8 pcs; 2019—6.3 pcs) and had the largest sum of lateral shoot lengths (2017—148.0 cm; 2018—155.4 cm; 2019—140.6 cm) among the evaluated combinations. The number of treatments and the concentration of applied growth regulators had a significant effect on the structure of the crown of the maiden apple trees of the ‘Gloster’ cultivar.
An Investigation on a Comprehensive Calibration Technique to Determine the Discrete Elemental Characteristics of Unrotted Sheep Dung at Varying Water Concentrations
Authors: Wang Jian , Ren Kailin , Li Zhe , Zhang Longfei
Published: October 2024

An experimental study was undertaken to investigate the problem of the substantial variability in water content in unrotted sheep dung, which leads to a lack of universality and practicality in calibrating its discrete element simulation parameters. The stacking angle was used as the response value in these experiments. The objective of this study was to establish precise simulation parameters for the composting process. A model for water content-stacking angle was established using the cylinder-lifting technique, resulting in a correlation value of 0.997. Utilizing the Hertz–Mindlin with JKR bonding model, three EDEM particle models were developed, each with distinct particle sizes, based on the particle size distribution of sheep dung. The JKR surface energy was determined using the Plackett–Burman test, the steepest-climbing test, and the Box–Behnken test using a set of 10 parameters. A subsequent study was conducted on the JKR surface energy, rolling friction factor, and static friction factor utilizing the Plackett–Burman test and Box–Behnken test. A parameter model for stacking angle–discrete elements was developed that achieved a p-value below 0.0001 and a relative inaccuracy of 3.46% or less. The regression model for the water content–discrete element parameter was derived by combining the water content–stacking angle model with the stacking angle–discrete element parameter model. Validation of this model was conducted using both the pumping plate technique and the hopper approach, resulting in a relative error of 4.89% or less. The findings demonstrate that the specific characteristics of sheep manure may be accurately anticipated by considering its water content. This approach offers a valid and universally applicable way of predicting the specific characteristics of sheep dung in the simulation of composting equipment.
The Impact of Digital Capabilities on Peasants’ Wage Growth: Evidence from Chinese Farmer Entrepreneurs
Authors: Zhang Shanhu , Yang Jinxiu , Shen Yun , Li Zhuoli
Published: October 2024

The gradual integration of digital technology into traditional Chinese villages has triggered a shift in income distribution from labor to capital, posing challenges to the wage growth of employed peasants. Based on the theory of empowerment, this paper explores the mechanisms of credit availability and talent loss in the interplay between digital capabilities and wage augmentation among employed peasants. This study empirically examines or validates the mechanism of digital capabilities on wage growth for employed peasants through the entropy weight method, the OLS linear model, the mediation effect model, and propensity score matching while using survey data from 490 farmer entrepreneurs as samples. The findings are as follows. (1) The digital capabilities of farmer entrepreneurs have a significant positive impact on the wage growth of employed peasants, and this result remains robust after a series of robustness checks. In terms of hierarchical effects, digital foundational capabilities > digital application capabilities > digital innovation capabilities. (2) Credit availability and talent loss mediate the relationship between digital capabilities and wage growth for employed peasants. (3) The digital capabilities of farmer entrepreneurs who are young, highly educated, and have a low family-dependency ratio exert a more pronounced influence on the wage growth of employed peasants. Additionally, lower policy uncertainty enhances the effect of digital capabilities on wage growth for employed peasants. The study uncovers the empowerment mechanism of digital advancements embedded during the entrepreneurial journey, enriches research on digital capabilities and common prosperity, and provides a feasible path for governments to formulate reasonable entrepreneurship and digital promotion policies.
Canopy Characteristics of Gamba Grass Cultivars and Their Effects on the Weight Gain of Beef Cattle under Grazing
Authors: Braga Gustavo José , Ramos Allan Kardec Braga , Carvalho Marcelo Ayres , Fonseca Carlos Eduardo Lazarini , Karia Claudio Takao
Published: October 2024

Gamba grass (Andropogon gayanus Kunth) is a tussock-forming forage species adapted to acid soils of Brazilian savannas and cultivated for grazing pastures. Four decades since its release, Planaltina prevails as the most commercialized cultivar of the species, even though the new cultivar BRS Sarandi could be a better alternative for Gamba-grass-based farms by presenting a greater leaf:stem ratio. The objective of this study was to evaluate the average daily live weight gain (ADG) of Nellore bulls (Bos indicus) for two Gamba grass cultivars—Planaltina and Sarandi. The experiment was conducted in Planaltina, Federal District, Brazil, for 3 years, namely 2018, 2018–2019, and 2020. The experimental design was a completely randomized block design with two treatments and three replicates, each one continuously stocked at three stocking rates (SR)—1.3, 2.6, and 4 young bulls/ha. Canopy height (CH), forage mass (FM), plant-part proportion (green leaf, stem, and dead material), and nutritive value were evaluated. In 2018, mean ADG for Sarandi pastures was greater (0.690 kg/bull/d) than that of Planaltina (0.490 kg/bull/d) (p < 0.10). In the subsequent year (2018–2019), there was no effect of cultivar (p > 0.10), while in 2020 the ADG was again affected by cultivar (p < 0.10), confirming the advantage of Sarandi (0.790 kg/bull/d) over Planaltina (0.650 kg/bull/d). In 2018 and 2020, the percentage of stems for Sarandi was about 3–6 pp less than for Planaltina (p < 0.10). As well as for stems, Sarandi pastures presented a shorter CH in 2028 and 2020 (6–7%) (p < 0.10). The positive high correlation of leaf:stem ratio with ADG (r = 0.70) probably predisposed the superiority of Sarandi over Planaltina. The distinguishing plant-part composition of Sarandi canopy promotes increasing weight gain of beef cattle when compared to cv. Planaltina.
Screening of Ecotypes and Construction of Evaluation System for Drought Resistance during Seed Germination in Kudouzi (Sophora alopecuroides)
Authors: Huang Xiang , Luo Cunkai , Zhang Xingxin , Liu Lin , Zhou Xiangcheng , Niu Panxin , Jiang Ping , Wang Mei , Chu Guangming
Published: October 2024

Drought is a major limiting factor in the cultivation of Sophora alopecuroides in China’s arid and semi-arid regions. This study aimed to identify drought-resistant S. alopecuroides ecotypes and explore key drought tolerance indicators during germination by simulating drought conditions with a 10% PEG-6000 solution, using pure water as a control. Determination of seven germination indicators for S. alopecuroides, including germination rate (GR), germination energy (GE), germination index (GI), vigor index (VI), promptness index (PI), fresh weight (FW), and dry weight (DW), was conducted. Principal component analysis (PCA), membership function, cluster analysis, and linear regression were employed to comprehensively evaluate the drought resistance of thirty-five S. alopecuroides ecotypes. The results showed that drought stress caused reductions in six of the seven indicators across all ecotypes, except for DW, compared to the control. Correlation analysis revealed varying relationships among the indicators, with most showing significant or highly significant correlations. PCA reduced the seven indicators to two independent comprehensive factors, with a cumulative contribution rate of 83.99%. Based on the D-value and cluster analysis, the thirty-five ecotypes were ranked for drought resistance and classified into four categories. The top five drought-tolerant genotypes during the germination stage were identified as Yutian, Alar, Jinghe, Baoding, and Guyuan. Moreover, the stepwise regression model was established and demonstrated that GR, GE, PI, FW, and DW are key indicators for screening and identifying drought-resistant S. alopecuroides ecotypes. This study offers a comprehensive and reliable method for evaluating drought resistance in S. alopecuroides ecotypes and provides a reference for selecting ecotypes for artificial cultivation in Northwestern China.
Pesticides Risk Assessment Review: Status, Modeling Approaches, and Future Perspectives
Authors: El Afandi Gamal , Irfan Muhammad
Published: October 2024

Pesticide exposure poses significant environmental and human health concerns, particularly given its extensive use in agricultural activities. The assessment of pesticide risks is a multifaceted and resource-intensive process, often requiring time-consuming toxicity studies. In response to this challenge, advanced computational models, remote sensing, and GIS (geographic information systems) have emerged as efficient and precise tools for evaluating pesticide exposure risks. This comprehensive review aims to provide an in-depth examination of the latest research methodologies for assessing the risks associated with pesticide exposure and their practical applications. These methodologies encompass the assessment of pesticide exposure in air, soil, and water, offering a comprehensive understanding of potential environmental pathways. The paper also delves into the effective utilization of these tools for pesticide risk assessment and examines the potential implications of their findings. The approaches outlined in this review hold promise for a thorough and insightful assessment of pesticide risks and are positioned to equip researchers and policymakers with valuable knowledge to mitigate the impacts of pesticide exposure on human health and the environment.
Pest Detection Based on Lightweight Locality-Aware Faster R-CNN
Authors: Li Kai-Run , Duan Li-Jun , Deng Yang-Jun , Liu Jin-Ling , Long Chen-Feng , Zhu Xing-Hui
Published: October 2024

Accurate and timely monitoring of pests is an effective way to minimize the negative effects of pests in agriculture. Since deep learning-based methods have achieved good performance in object detection, they have been successfully applied for pest detection and monitoring. However, the current pest detection methods fail to balance the relationship between computational cost and model accuracy. Therefore, this paper proposes a lightweight, locality-aware faster R-CNN (LLA-RCNN) method for effective pest detection and real-time monitoring. The proposed model uses MobileNetV3 to replace the original backbone, reduce the computational complexity, and compress the size of the model to speed up pest detection. The coordinate attention (CA) blocks are utilized to enhance the locality information for highlighting the objects under complex backgrounds. Furthermore, the generalized intersection over union (GIoU) loss function and region of interest align (RoI Align) technology are used to improve pest detection accuracy. The experimental results on different types of datasets validate that the proposed model not only significantly reduces the number of parameters and floating-point operations (FLOPs), but also achieves better performance than some popular pest detection methods. This demonstrates strong generalization capabilities and provides a feasible method for pest detection on resource-constrained devices.
Long-Term Effects of Nitrogen and Tillage on Yields and Nitrogen Use Efficiency in Irrigated Corn
Authors: Delgado Jorge A. , D’Adamo Robert E. , Villacis Alexis H. , Halvorson Ardell D. , Stewart Catherine E. , Floyd Bradley A. , Del Grosso Stephen J. , Manter Daniel K. , Alwang Jeffrey
Published: October 2024

By tonnage, corn (Zea mays L.) is the #1 crop produced globally, and recent research has suggested that no-till (NT) systems can lead to reduced yields of this important crop. Additionally, there is a lack of long-term data about the effects of tillage and N management on cropping systems. Corn is the most nitrogen (N)-fertilized crop in the USA, and N losses to the environment contribute to significant impacts on air and water quality. We conducted long-term studies on conventional tillage (CT) and conservation tillage systems, such as strip tillage (ST) and NT, under different N rates. We found that immediately after conversion to NT, yields from NT were significantly lower than yields from CT (p < 0.1), but after five years of NT, the NT yields were 1.5% higher than the CT yields (p < 0.1). Initially, the NT yields were lower than the ST (p < 0.01), but after seven years of NT, the NT yields were comparable to ST grain yields. Although the total aboveground N uptake with NT immediately after conversion to NT was lower than with CT and ST, these differences were not significant in the long run. The nitrogen use efficiency (NUE) with NT increased over time. The present work highlights the importance of long-term research for determining the cumulative impacts of best management practices such as NT. We found that NT becomes a more viable practice after five or seven years of implementation, demonstrating the high importance of long-term research.
Evaluation of ‘In-Parlour Scoring’ (IPS) to Detect Lameness in Dairy Cows during Milking
Authors: Laschinger Jasmin , Fuerst-Waltl Birgit , Fuerst Lisa , Linnenkohl Sophie , Pesenhofer Robert , Kofler Johann
Published: October 2024

The objective of this study was to evaluate the potential of ‘In-Parlour Scoring’ (IPS) as an alternative to locomotion scoring in herringbone, side-by-side, and tandem milking parlours in Austria. Between January and May 2023, a total of 990 observations were conducted on 495 cows across eleven Austrian dairy farms by two investigators working simultaneously but independently of each other. The observation criteria included shifting weight, claw conformation, and obvious disorders of the distal limb. Locomotion scoring was conducted on all cows within 24 h of assessment in the milking parlour using a scale of 1 to 5 (LCS 1: not lame; LCS 5: severely lame). Functional hoof trimming was performed within ten days after IPS. The following indicators were identified as useful for predicting lameness (LCS ≥ 3): shifting weight, abnormal weight distribution, swollen heel, hock joint or interdigital space, skin lesion on the lateral hock, claw position score, digital dermatitis lesions, short dorsal claw wall, and hyperextension of one claw. The reliability of the individual indicators for intra- and inter-rater assessment exhibited considerable variation ((weighted) kappa values: −0.0020–0.9651 and −0.0037–1.0, respectively). The specificity and sensitivity for the prediction of lame cows were calculated to be ≥ 96% and ≤ 24%, respectively. It was demonstrated that a one-time IPS has limited suitability for lameness assessment on Austrian dairy farms with herringbone, side-by-side, and tandem milking parlours.
Evaluation of Two Levels of Trace Mineral Supplementation to Beef Calves Prior to Weaning
Authors: Hernandez Gracia M. P. , Dos Santos Aline C. R. , Ferreira Matheus F. L. , Bohnert David , Ranches Juliana
Published: October 2024

In this 2-year study, approximately 84 days prior to weaning, 24 calves/year (Angus × Hereford) were randomly assigned to one of two treatments: trace mineral (Cu, Se, and Zn) supplementation following NASEM (2016) recommendations (Control) or trace mineral supplementation above NASEM (2016) recommendations (Super). Calves were individually fed, and trace minerals were provided in 0.5 kg of dry distiller’s grains three times weekly. Body weight (BW), blood, and liver samples were collected on d 0 and at weaning (d 84). Additional BW and blood samples were collected post-weaning on d 85, 87, 88, 91, 95, and 99 during the preconditioning phase. Initial liver concentrations of Se, Cu, and Zn were similar between treatments (p ≥ 0.69). At weaning, a year effect (p < 0.001) and a tendency for treatment × year effect (p = 0.09) were observed for Cu liver concentration. In year 2, but not in year 1, calves assigned to the Super treatment tended to have greater liver Cu concentration than calves assigned to the Control treatment. Except for Cu, a notoriously limited trace mineral in multiple geographical locations, the supplementation of trace minerals above the NASEM (2016) recommendations did not improve the mineral status of calves in this environment.
A20 Alleviates the Inflammatory Response in Bovine Endometrial Epithelial Cells by Promoting Autophagy
Authors: Dong Junsheng , Ji Bowen , Jiang Yeqi , Fei Fan , Guo Long , Liu Kangjun , Cui Luying , Meng Xia , Li Jianji , Wang Heng
Published: October 2024

Endometritis represents a prevalent condition in perinatal dairy cows. Bovine endometrial epithelial cells (BEECs), as the primary interface between cavity and the external environment, are particularly vulnerable to infection by pathogenic bacteria following parturition. A20 is essential for regulating inflammation and modulating immune responses. Nevertheless, the exact role of A20 in the BEECs in response to inflammatory response is not fully understood. An endometritis model infected by Escherichia coli (E. coli) in vivo and a BEECs inflammation model induced with lipopolysaccharide (LPS) in vitro were built to investigate the function and governing mechanisms of A20 in endometritis. The results showed that infection with E. coli resulted in endometrial damage, inflammatory cell infiltration, and upregulation of inflammatory factors in dairy cows. Furthermore, A20 expression was upregulated in the endometrium of cows with endometritis and in BEECs following LPS stimulation. A20 overexpression attenuated the level of proinflammatory cytokines in LPS-stimulated BEECs; conversely, A20 knockdown lead to an exacerbated response to LPS stimulation. The overexpression of A20 was shown to activate autophagy and suppress the NF-κB signaling pathway in LPS-stimulated BEECs. However, blocking autophagy with chloroquine notably attenuated the anti-inflammatory effect of A20, leading to the activation of the NF-κB signaling pathway. In summary, the study demonstrated that A20’s suppression of inflammation in LPS-stimulated BEECs is associated with the activation of autophagy. Therefore, the A20 protein showed potential as a novel treatment focus for managing endometritis in dairy cows.
Detection and Localization of IL-8 and CXCR1 in Rainbow Trout Larvae in Response to Pseudomonas aeruginosa Lipopolysaccharide
Authors: Santana Paula A. , Forero Juan C. , Guzmán Fanny , Gaete Sandra , Acosta Félix , Mercado Luis A. , Álvarez Claudio A.
Published: October 2024

The salmonid industry faces challenges due to the susceptibility of fish to opportunistic pathogens, particularly in early developmental stages. Understanding the immunological capacity during these stages is crucial for developing effective disease control strategies. IL-8R, a member of the G-protein-coupled receptor family, acts as a receptor for Interleukin 8 (IL-8). The binding of IL-8 to IL-8R plays a major role in the pathophysiology of a wide spectrum of inflammatory conditions. This study focused on the immune response capacity of rainbow trout (Oncorhynchus mykiss) larvae by analyzing IL-8/CXCR1 response to lipopolysaccharide (LPS) from Pseudomonas aeruginosa. Previous research demonstrated that LPS from P. aeruginosa acts as a potent immunostimulant in teleost, enhancing pro-inflammatory cytokines. The methodology included in silico analysis and the synthesis and characterization of an omCXCR1-derived epitope peptide, which was used to produce omCXCR1-specific anti98 serum in mice. The research revealed that rainbow trout larvae 19 days post-hatching (dph) exhibited pronounced immune responses post-stimulation with 1 µg/mL of LPS. This was evidenced by the upregulated protein expression of IL-8 and omCXCR1 in trout larvae 2 and 8 h after LPS challenge, as analyzed by ELISA and immunohistochemistry. Furthermore, fluorescence microscopy successfully revealed the colocalization of IL-8 and its receptor in cells from mucosal tissues after LPS challenge in larvae 19 dph. These findings underscore the efficacy of LPS immersion as a method to activate the innate immune system in trout larvae. Furthermore, we propose IL-8 and its receptor as molecular markers for evaluating immunostimulation in the early developmental stages of salmonids.
Tiletamine/Zolazepam and Ketamine with Dexmedetomidine (TKD) Cocktail Is as Effective as Tiletamine/Zolazepam and Ketamine with Xylazine (TKX) in Providing Pig General Anesthesia
Authors: Akaraphutiporn Ekkapol , Durongphongtorn Sumit , Jampachaisri Katechan , Sharp Patrick , Pacharinsak Cholawat , Wangdee Chalika
Published: October 2024

This study aimed to evaluate dexmedetomidine as an alternative to xylazine in pigs. We compared TKD (0.05 mL/kg) to TKX (0.05 mL/kg) in 20 male pigs undergoing unilateral cryptorchid castration (short-term, 45-min) or bilateral cryptorchid castration (long-term, 90-min). We hypothesized that TKD would be comparable to TKX for both short-term and long-term anesthesia. Monitored parameters were classified into duration and physiological categories, including induction and recovery times, reflexes, heart rate (HR), respiratory rate (RR), arterial blood pressure, oxygen saturation (%SpO2), end-tidal carbon dioxide (ETCO2), and body temperature (TEMP). Isoflurane levels were also recorded, if used. Results showed no significant differences in duration parameters between TKD and TKX for either short-term or long-term anesthesia (induction: 1 min; recovery: 18–35 min). Physiological parameters were mostly similar between groups, although TKD caused slightly higher blood pressure during short-term anesthesia. Isoflurane levels (0.1–0.6%) were comparable between groups. Overall, the results suggest that TKD provides anesthesia comparable to TKX in pigs undergoing unilateral or bilateral cryptorchid surgery requiring short-term and long-term anesthesia.
Small Ruminant Parturition Detection Based on Inertial Sensors—A Review
Authors: Gonçalves Pedro , Marques Maria R. , Nyamuryekung’e Shelemia , Jorgensen Grete H. M.
Published: October 2024

The birth process in animals, much like in humans, can encounter complications that pose significant risks to both offspring and mothers. Monitoring these events can provide essential nursing support, but human monitoring is expensive. Although there are commercial monitoring systems for large ruminants, there are no effective solutions for small ruminants, despite various attempts documented in the literature. Inertial sensors are very convenient given their low cost, low impact on animal life, and their flexibility for monitoring animal behavior. This study offers a systematic review of the literature on detecting parturition in small ruminants using inertial sensors. The review analyzed the specifics of published research, including data management and monitoring processes, behaviors indicative of parturition, processing techniques, detection algorithms, and the main results achieved in each study. The results indicated that some methods for detecting birth concentrate on classifying unique animal behaviors, employing diverse processing techniques, and developing detection algorithms. Furthermore, this study emphasized that employing techniques that include analyzing animal activity peaks, specifically recurrent lying down and getting up occurrences, could result in improved detection precision. Although none of the studies provided a completely valid detection algorithm, most results were promising, showing significant behavioral changes in the hours preceding delivery.
Amoxicillin/Clavulanic Acid in Transrectal Biopsy of the Prostate—An Alternative in Times of Ciprofloxacin Obsolescence and Fosfomycin Limitation?
Authors: Spachmann Philipp J. , Fischer Sophie E. , Goßler Christopher , Denzinger Stefan , Burger Maximilian , Breyer Johannes , Otto Wolfgang , Schnabel Marco J. , Bründl Johannes , Rosenhammer Bernd
Published: October 2024

Recently, the German Federal Institute for Medicines and Medical Products restricted the use of fosfomycin in transrectal biopsy of the prostate (TRBP). Accordingly, the need for other antibiotic agents for prophylaxis in TRBP is urgent since antibiotic prophylaxis is mandatory in accordance with these guidelines. After the restriction of the use of ciprofloxacin, and before the use of fosfomycin in Germany was falsely allowed, amoxicillin/clavulanic acid was evaluated as an alternative for antibiotic prophylaxis in TRBP. Regarding hospitalization for post-interventional infections, 359 patients at the Department of Urology of the University of Regensburg, at Caritas-St. Josef Medical Center as a single center, underwent TRBP between 2 July 2019 and 30 June 2020. Regarding antibiotic prophylaxis, the post-interventional hospitalization rate due to bacterial complications was relevant. Of the 359 patients, 10 (2.8%) had an infection requiring hospitalization post-TRBP. A total of 349 (97.2%) patients had no infection-related hospitalization. This corresponds to an incidence rate of only 2.8%. Referring to the previous infection rates under the now obsolete ciprofloxacin, amoxicillin/clavulanic acid can show a similar, if not tendentially even lower, risk of infection, and so this substance can be an alternative for antibiotic prophylaxis in TRBP. Another advantage is that, according to the WHO’s AWaRe classification, amoxicillin/clavulanic acid is one of the so-called Access antibiotics. This study is limited as rectal swabs and urine cultures were not performed on every patient before TRBP.
Antioxidant Function and Application of Plant-Derived Peptides
Authors: Zhu Zhengqing , Xu Ziwu , Li Yuhang , Fan Yutong , Zhou Yingqian , Song Kaixin , Meng Lei
Published: October 2024

With the development of society and the improvement of people’s health consciousness, the demand for antioxidants is increasing. As a natural antioxidant with no toxic side effects, antioxidant peptides are widely used in food, cosmetics, medicine, and other fields because of their strong antioxidant capacity and easy absorption by the human body. Plant-derived antioxidant peptides have attracted more attention than animal-derived antioxidant peptides because plants are more diverse than animals and produce a large number of protein-rich by-products during the processing of their products, which are the main source of antioxidant peptides. In this review, we summarize the source, structure and activity, other biological functions, mechanism of action, and comprehensive applications of plant antioxidant peptides, and look forward to their future development trends, which will provide a reference for further research and development of plant antioxidant peptides.
Predicting and Analyzing Electric Bicycle Adoption to Enhance Urban Mobility in Belgrade Using ANN Models
Authors: Komarica Jelica , Glavić Draženko , Kaplanović Snežana
Published: October 2024

The development of alternative environmentally friendly modes of transportation is becoming an increasingly promising solution in traffic-congested and polluted urban areas. E-bikes, as one of them, are recognized as an ecologically sustainable means of transportation that has significant potential to replace motorized modes of transportation that can improve urban mobility. Relying on artificial intelligence and considering an ecological approach when considering the acceptability of e-bikes by setting a direct question for users influences the development of an innovative way of understanding and evaluating the use of more sustainable modes of transportation. In this regard, this study aims to elucidate the main variables influencing the acceptability of e-bike use using artificial neural network (ANN) models—multilayer perceptron (MLP) and radial basis function (RBF). For training and testing the models, data from a random sample obtained through an online questionnaire, which was answered by 626 residents of Belgrade (Serbia), were used. A multilayer perceptron with nine and seven neurons in two hidden layers, respectively, hyperbolic tangent activation function in the hidden layer and identity function in the output layer, gave better results than the radial basis function model. With an accuracy of 89%, a precision of 83%, a recall of 79%, and an area under the receiver operating characteristic (ROC) curve of 0.927, the multilayer perceptron model recognized the influential variables in predicting acceptability. The results of the model indicate that the mileage traveled, the frequency of motorcycle use, the respondents’ awareness of the pollution in Belgrade, and the age of the respondents have the greatest influence on the acceptability of using e-bikes. In addition to majority acceptability (69.8%), the results obtained by the model can represent a useful basis for decision-makers when defining strategies for the development and application of e-bikes while reducing traffic congestion and environmental pollution in Belgrade.
High-Temperature Short-Time and Ultra-High-Temperature Processing of Juices, Nectars and Beverages: Influences on Enzyme, Microbial Inactivation and Retention of Bioactive Compounds
Authors: Polak Natalia , Kalisz Stanisław , Kruszewski Bartosz
Published: October 2024

HTST (high-temperature short-time) pasteurization and UHT (ultra-high-temperature) sterilization are techniques commonly used in the dairy industry. Although the use of these methods in fruit and vegetable processing is also well known, the multitude of diverse food matrices determines the need to test and adjust process parameters in order to obtain the best quality of the final product. HTST and UHT are methods that provide effective inactivation of microorganisms and enzymes. Despite the fact that UHT and HTST are thermal processes that cause degradation of bioactive ingredients or color change, in many cases, these two methods are superior to traditional pasteurization, which uses significantly longer exposures to high temperatures. Therefore, this article aims to review the effect of HTST and UHT processing on the quality of juices, nectars and beverages, taking into consideration the quality characteristics, like the presence of microorganisms, pH, titratable acidity, total soluble solids, turbidity, color parameters, contents of bioactive components, antioxidant activity, enzymatic activity and volatile compounds. The impacts of HTST and UHT methods on various food products are discussed, including the food matrix, preservation parameters and the mechanism of interaction. The ability to modify the processing parameters can allow for the selection of adequate preservation parameters for individual products and better results than other unconventional methods, such as HPP (high-pressure processing) or PEF (pulsed electric field). Based on the cited literature, it can be concluded that pH, titratable acidity and TSS most often experience slight changes. As for the other parameters considered, it is extremely important to choose the right temperature and duration for a specific food matrix.
The Role of AC Resistance of Bare Stranded Conductors for Developing Dynamic Line Rating Approaches
Authors: Riba Jordi-Roger
Published: October 2024

Overhead transmission line conductors are usually helically stranded. The current-carrying section is made of aluminum and/or aluminum alloys. Several factors affect their electrical resistance, such as the conductivity of the conductor material, the cross-sectional area, the lay length of the different layers of aluminum, and the presence of a steel core used to increase the mechanical strength of the conductor. The direct current (DC) and alternating current (AC) resistances per unit length of stranded conductors are different due to the effect of the eddy currents. In steel-reinforced conductors, there are other effects, such as the transformer effect due to the magnetization of the steel core, which make the AC resistance dependent on the current. Operating temperature also has an important effect on electrical resistance. Resistive losses are the main source of heating in transmission line conductors, so their temperature rise is highly dominated by such power losses, making it critical to know the value of the AC resistance per unit length when applying dynamic line rating (DLR) methods. They are of great interest especially in congested lines, as by applying DLR approaches it is possible to utilize the full line capacity of the line. This paper highlights the difficulty of accurately calculating the electrical resistance of helically stranded conductors, especially those with a magnetic core, and the importance of accurate measurements for the development of conductor models and DLR approaches.
Microstructure Evolution and Forming Characteristics of Post-Weld Composite Treatment of 6061 Aluminum Alloy Tailor Welded Blanks
Authors: Dong Xiaonan , Song Gang , Liu Liming
Published: October 2024

The mechanical properties and cross-sectional geometric dimensions of the fusion zone (FZ), heat affected zone (HAZ), and base metal (BM) of 6xxx series aluminum alloys are inconsistent after filler wire welding, which reduces the formability of aluminum alloy tailor welded blanks (TWBs). This paper proposes a post-weld cold rolling-solution heat treatment (PWCR-SHT) composite process, and the effects of weld excess metal, plastic deformation, and SHT on the formability of aluminum alloy TWBs are studied. The results show that the PWCR-SHT composite process eliminates the weld excess metal and internal pores, reduces the stress concentration at the weld toe, eliminates the local strain hardening behavior, and causes recrystallization in the FZ region. The cupping value of aluminum alloy TWBs using SHT is 105% of BM, in comparison, the cupping value of aluminum alloy TWBs using the PWCR-SHT composite process is 119% of BM, which is the result of the combined effect of geometric dimensions consistency and mechanical properties consistency.
Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 2: Implementation
Authors: Lliso-Ferrando Josep Ramon , Martínez-Ibernón Ana , Ramón-Zamora José Enrique , Gandía-Romero José Manuel
Published: October 2024

The economic cost of repairing corrosion-affected reinforced concrete structures (RCSs) means that reliable and accurate assessment and early detection methods must be sought after. Conventional techniques, such as visual inspections, or measuring either cover layer resistivity or the corrosion potential, are methods that require accessibility and involve personnel having to travel to take in situ measurements. Monitoring by embedded sensors is a much more efficient approach that allows early detection by remote sensing. This work presents the implementation of a new measurement protocol regarding the existing monitoring system called INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring). Along with the corrosion intensity measurement in embedded sensors, it also proposes monitoring the double layer capacity of the sensors’ responses. It aims to determine, along with the rebars’ corrosion rate, the triggering agent of the corrosion process. This study was carried out using three reinforced concrete scaled columns that were exposed to different environments. The results demonstrate with this new protocol that the remote INESSCOM monitoring system can establish the corrosion rate and identify the precursor agent of corrosion (carbonation or chlorides), even when the recorded corrosion rates are similar.