bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging Machine Learning for Weed Management and Crop Enhancement: Vineyard Flora Classification
Authors: Corceiro Ana , Pereira Nuno , Alibabaei Khadijeh , Gaspar Pedro D.
Published: December 2023

The global population’s rapid growth necessitates a 70% increase in agricultural production, posing challenges exacerbated by weed infestation and herbicide drawbacks. To address this, machine learning (ML) models, particularly convolutional neural networks (CNNs), are employed in precision agriculture (PA) for weed detection. This study focuses on testing CNN architectures for image classification tasks using the PyTorch framework, emphasizing hyperparameter optimization. Four groups of experiments were carried out: the first one trained all the PyTorch architectures, followed by the creation of a baseline, the evaluation of a new and extended dataset in the best models, and finally, the test phase was conducted using a web application developed for this purpose. Of 80 CNN sub-architectures tested, the MaxVit, ShuffleNet, and EfficientNet models stand out, achieving a maximum accuracy of 96.0%, 99.3%, and 99.3%, respectively, for the first test phase of PyTorch classification architectures. In addition, EfficientNet_B1 and EfficientNet_B5 stood out compared to all other models. During experiment 3, with a new dataset, both models achieved a high accuracy of 95.13% and 94.83%, respectively. Furthermore, in experiment 4, both EfficientNet_B1 and EfficientNet_B5 achieved a maximum accuracy of 96.15%, the highest one. ML models can help to automate crop problem detection, promote organic farming, optimize resource use, aid precision farming, reduce waste, boost efficiency, and contribute to a greener, sustainable agricultural future.
Optimization Design and Experiment of High-Speed Drag-Reducing Trencher Based on Conservation Tillage
Authors: Zhang Weipeng , Liu Suchun , Ji Yuxi , Gao Shengbo , Zhao Bo , Zhou Liming , Xie Ping , Jin Xin , Qiu Zhaomei , Ma Yanwu
Published: December 2023

In the realm of high-speed precision broadcasting, the existing seeder opener proves inadequate for the speed of the seeding operation. We focus on the duckbill opener and employ the quadratic regression orthogonal rotation combination test design method to optimize the structural parameters of the opener. Throughout the experiment, the primary performance metrics encompassed the opener’s working resistance and the side dumping distance. The selected experimental factors comprised the penetration angle, the angle of soil entry gap, the shovel body width, and the shovel length. The optimal arrangement of structural parameters has been determined: a penetration angle, a soil entry gap angle, a shovel body width of 21 mm, and a shovel length of 142 mm. These parameters contribute to increased velocity, reduced operational resistance, and minimal soil disturbance. Under this combination, the relative deviations between the recorded measurements and the theoretical outcomes for working resistance and the side dumping distance stand at 4.24% and 1.06%, respectively; these confirm the credibility of the optimization results. We performed adaptability testing and conducted a comparative analysis under various operational conditions to assess the innovative opener’s ability to reduce force, minimize soil disruption, and maintain depth stability. The findings are as follows: At a depth of 5 cm and velocities ranging from 6 km/h to 8 km/h, an average working resistance reduction of 19.73%, a 5.64% decrease in the side dumping distance, and an average depth stability of 89.5% were observed. When operated at a speed of 7 km/h with a depth ranging from 3 cm to 5 cm, an average reduction of 19.66% in operational resistance, a 2.59% decrease in the side dumping distance, and an average depth stability of 91.1% were recorded. These results illustrate the innovative opener’s capacity to significantly reduce working resistance and side dumping distance while satisfying the depth stability requisites.
Research on Micro Gap Flow Field Characteristics of Cylindrical Gas Film Seals Based on Experimental and Numerical Simulation
Authors: Xu Zhen , Xu Lianjiang , Sun Junfeng , Liu Meihong , Liao Taohong , Hu Xiangping
Published: December 2023

Flexible support cylindrical gas film seals (CGFSs) adapt well to rotor whirling and have a good gas lubrication effect during thermal deformation. However, when a CGFS operates under the “three high” (high interface slip speed, high-pressure differential, and high ambient temperature) operating conditions, the complex deformation of the support structure is a crucial factor affecting the stability of the CGFS. A thorough and systematic analysis of the micro gap flow field characteristics of flexible support CGFSs is a fundamental problem when we study the deformation of the support structure under multiple physical field conditions. This study uses a cylindrical gas film high-speed rotor test rig to study and compare the sealing characteristics of experiments and numerical simulations and then optimizes and verifies the accuracy and effectiveness of the simulation model. A cross-scale gas film grid model is used to analyze the flow field characteristics and seal ability of different groove models and compare the mechanical characteristics and sealing performance. We also analyze the gas film pressure distribution in micro gaps and explore the impact of dynamic pressure groove microstructure on flow field characteristics. Results show that micro gaps are the primary conditions for generating hydrodynamic effects, and high rotational speed, high-pressure differential, and large eccentricity have a significant effect on improving hydrodynamic effects and enhancing gas film stability. However, an increase in these parameters can cause an increase in leakage rate. A single flow channel makes it easier to improve the hydrodynamic effect, gas film load-bearing ability, and gas film stability while reducing leakage rate. The analyses in this study supplement and improve the theory of the flow field characteristics of cylindrical annular micro gaps and provide a theoretical basis for exploring the relation between the support structural parameters of the CGFS and the mechanical characteristics of the micro gap flow field. This study provides important guidance to the establishment of a quantitative design theory of supporting structures.
Numerical Investigation of a Vortex Diverter Designed for Improving the Performance of the Submerged Inlet
Authors: Zhang Junyao , Zhan Hao , Mi Baigang
Published: December 2023

The submerged inlet exhibits good stealth characteristics and lower drag, but it has a low total pressure recovery coefficient and high distortion rate, which limits its widespread application. This paper proposes a vortex diverter aimed at enhancing the performance of the submerged inlet and investigates the aerodynamic coupling mechanism between the vortex diverter and the submerged inlet in detail. Firstly, based on the flow field characteristics of the submerged inlet, the design principles of the vortex diverter are proposed. Then, the impact of the vortex diverter on the flow field of the submerged inlet is analyzed using the numerical method. Finally, the matching design between the vortex diverter and the submerged inlet is explored. The results show that the vortex diverter improves the average total pressure of the airflow inside the inlet by exhausting the low-energy flow from the larger radius side of the inlet, thereby suppressing flow separation and enhancing flow field uniformity. The vortex diverter improves the intake performance of the submerged inlet under different incoming flow Mach numbers, inlet exit Mach numbers, angles of attack, and small sideslip angles. The maximum increase in the total pressure recovery coefficient is 3.1099%, and the maximum reduction in the circumferential total pressure distortion is 49.5207%. Among the design parameters, the horizontal distance between the leading edge of the vortex diverter and the inlet lip has the greatest influence on the intake performance, and the best control effect is achieved when the vortex diverter is installed at the throat position. Furthermore, after installing the vortex diverter, reducing the side-edge angle of the entrance appropriately can effectively reduce the intensity of the secondary flow, thereby improving the total pressure recovery at the exit and reducing the distortion rate.
Airfoil Lift Coefficient Optimization Using Genetic Algorithm and IGP Parameterization: Volume 1
Authors: Tejeda-del-Cueto María Elena , Flores-Alfaro Manuel Alberto , Toledo-Velázquez Miguel , Santos-Cortes Lorena del Carmen , Hernández-Hernández José , Vigueras-Zúñiga Marco Osvaldo
Published: December 2023

The objective of this study is to develop a genetic algorithm that uses the IGP parameterization to increase the lift coefficient (CL) of three airfoils to be used on wings of unmanned aerial vehicles (UAVs). The geometry of three baseline airfoils was modified by developing a genetic algorithm that operates with the IGP parameterization and performs the aerodynamic analysis using XFOIL in the MATLAB environment. Subsequently, a numerical model was made for each baseline and optimized airfoil using a commercial computational fluid dynamics (CFD) code to analyze the behavior of the lift coefficient. An increase in the average CL was obtained for the Eppler 68, MH 70, and Wortmann FX 60-126 airfoils for angles of attack ranging from 0 to 10, obtaining increments of 17.243%, 14.967%, and 10.708%, respectively. Additionally, an average 5.027% uncertainty was obtained in lift coefficient calculations between XFOIL and CFD. The utility of the IGP method and genetic algorithms for parameterizing and optimizing airfoils was demonstrated. In addition, airfoils could be tailored for a specific UAV depending on the mission profile. Volume 2 of this study will include experimental data from wind tunnel.
Validation of an IoT System Using UHF RFID Technology for Goose Growth Monitoring
Authors: Černilová Barbora , Linda Miloslav , Kuře Jiří , Hromasová Monika , Chotěborský Rostislav , Krunt Ondřej
Published: December 2023

Regular weight measurement is important in fattening geese to assess their health status. Failure to gain weight may indicate a potential illness. Standard weight gain analysis involves direct contact with the animal, which can cause stress to the animal, resulting in overall negative impacts on animal welfare. The focus of this study was to design a smart solution for monitoring weight changes in the breeding of farm animals. The proposed IoT system with a weighing device equipped with RFID technology for animal registration aimed to minimize the negative aspects associated with measuring in contact with humans. The proposed system aims to incorporate modern approaches in animal husbandry and use these obtained data for the potential development of husbandry approaches for different breeds of animals and enhanced managerial decision-making within husbandry. The system consisted of three main components: a data acquisition system, a weighing system with RFID, and an environmental monitoring system. In this study, the RFID system accuracy for detecting geese in the weighing system environment was assessed. The entire system evaluation yielded a sensitivity of 95.13%, specificity of 99.89%, accuracy of 99.78%, and precision of 95.01%. Regression analysis revealed a good correlation between observed feeding and RFID registrations with a determination coefficient of R2 = 0.9813.
The Exceptionally Large Genomes of the Fabeae Tribe: Comparative Genomics and Applications in Abiotic and Biotic Stress Studies
Authors: Santos Carmen , Leitão Susana Trindade
Published: December 2023

The Fabeae tribe comprises five legume genera, which include some of the most ancient and important crops, like peas, lentils, and faba beans. Biotic and environmental stresses are major threats to the stable and high productivity of Fabeae crops. The use of omics resources can provide breeders with the tools needed to develop new crop varieties in a more efficient and sustainable way. However, the genomic efforts on Fabeae crops have lagged behind compared to other legume species, mainly due to their large genome size and repeat content. The first annotated chromosome-level reference genome assembly in Fabeae was published for pea (Pisum sativum cv. Caméor) in 2019. Since then, many efforts have been made to sequence the genome of other species from this tribe. Currently, 17 genomes of Fabeae species are available for the scientific community; five of them are at the chromosome level. Fundamental knowledge and molecular tools for breeding have been boosted on the legume resistance/tolerance against biotic and abiotic stresses by the availability of some of these recent reference genomes, especially the pea cv. Caméor genome. This review provides a comparison of the Fabeae tribe genomes available and an overview of recent accomplishments in their application in abiotic and biotic stress research.
Linear and Nonlinear Mixed Models to Determine the Growth Curves of Weaned Piglets and the Effect of Sex on Growth
Authors: Besteiro Roberto , Arango Tamara , Rodríguez Manuel R. , Fernández María D.
Published: December 2023

This study characterizes the growth of weaned Large White × Landrace hybrid piglets from 6 to 20 kg live body weight (BW) under real farm conditions. Batches of 50 castrated male pigs and 50 gilts were weighed repeatedly over two 6-week breeding cycles. The data was fitted to various linear (quadratic and exponential) and nonlinear (Gompertz, Richards, logistic, Von-Bertalanffy) mixed models to find the best-performing model. During the postweaning phase, animal growth was modelled, and the effect of sex on growth was determined by incorporating the variable, sex, into the mixed models and using t-tests for paired samples. The average BW at weaning was 6.86 kg, and the average BW by the end of the cycle was 19.46 kg, with an average daily gain (ADG) of 0.324 kg/day. Over the study period, the variable, sex, did not show a significant effect (p < 0.05) on piglet growth. The nonlinear mixed models performed better than the linear mixed models, with the Gompertz (RMSE = 0.296) and Von-Bertalanffy (RMSE = 0.288) curves as the best-performing models. When fitted to the Gompertz curve, the data showed a maximum ADG of 0.508 kg/day on day 27 postweaning. Accordingly, nonlinear mixed models can provide useful information to farmers about the evolution of weaned piglet growth and can be used for the early detection of growth anomalies.
Evaluation of the Essential Oils Used in the Production of Biopesticides: Assessing Their Toxicity toward Both Arthropod Target Species and Beneficial Pollinators
Authors: Gostin Irina Neta , Popescu Irinel Eugen
Published: December 2023

Biopesticides, alongside the expansive growth of conventional agriculture, emerged as a hopeful avenue for mitigating the environmental impact of synthetic chemicals. Essential oils derived from various plant species are regarded as environmentally friendly and have been suggested by numerous researchers for combating the pest species. However, in addition to their detrimental effects on harmful species, these essential oils exert varying degrees of impact on non-target species with which they share ecological relationships. This review serves the dual purpose of updating data on the use of the essential oils as biopesticides, considering the substantial increase in research output in the recent years. Simultaneously, it aims to provide a focused synthesis on the essential oils currently approved for commercial use as biopesticides, and shedding light on their impact on beneficial pollinator species, which may inadvertently suffer from the application of substances deemed safe by most users.
Use of Union Funds in Developing Agricultural Entrepreneurship between 2014 and 2020 in Poland
Authors: Wojcieszak-Zbierska Monika Małgorzata , Sadowski Arkadiusz
Published: December 2023

The purpose of this paper was to examine the differences in using agricultural entrepreneurship support and how it relates to characteristics such as the agrarian structure, socioeconomic development level, and land use across the Polish territory. The analyses were carried out at the district (poviat) level which is an intermediate administrative unit. This study found that the decisions on co-financing the measures dedicated to non-agricultural economic activity heavily depended on the agrarian structure. The highest levels of activity were witnessed in districts where the agrarian structure was particularly fragmented.
Cold Climate Factors in Nitrogen Management for Maize
Authors: van Es Harold
Published: December 2023

Among essential crop nutrients, nitrogen is the greatest management challenge in maize (Zea mays L.) production due to high requisite rates as well as dynamic transformations and losses. Climate plays a role in N management through changes in crop calendars, soil properties, agronomic practices, and yield effects. This study focuses on climate influences on maize N management and the objectives are to (i) review cold climate factors impacting economic optimum N rates (EONR), (ii) discuss approaches and climate considerations in estimating optimum N rates, and (iii) illustrate unexplored climate aspects related to optimum N rate assessment. Cold climate effects are expressed through inherent soil properties, agronomic management, and N fertilizer management. Most current N rate calculators do not explicitly account for climate factors, but implicitly integrate them through regional calibrations. Yield and EONR data from the US Corn Belt region indicate a positive correlation where lower means are associated with colder climates. High variability within climate regions is explained by differences in annual production environments, notably seasonal weather. Soil health models show that colder climates in the US are associated with higher stocks of soil organic matter, especially labile fractions. Adapt-N model simulations of a colder (North Central Wisconsin; 45.50, −89.70) and warmer (South Central Illinois; 38.50, −89.70) Corn Belt location show that higher soil organic N stocks do not increase crop N availability, presumably due to temperature-constrained N mineralization rates. The EONR for the colder site is 58 kg N ha−1 lower than the warmer site, which is well explained by differences in yield potential. Overall, abductive inferences suggest that colder climates are generally associated with higher levels of organic N stocks, but lower yields and crop N demands lessen EONRs. Seasonal weather and interactions with soil and agronomic factors also critically impact EONR, which can be assessed with model-based decision tools.
Effect of Form of Silicon and the Timing of a Single Foliar Application on Sugar Beet Yield
Authors: Siuda Alicja , Artyszak Arkadiusz , Gozdowski Dariusz , Ahmad Zahoor
Published: December 2023

The aim of the study was the evaluation of silicon foliar application on sugar beet yield. In the years 2017–2019, the effect of a single foliar application of various forms of silicon (potassium silicate—PS, calcium silicate—CS, sodium metasilicate—SM, and orthosilicic stabilized acid—OSA) applied in the six-leaf phase of sugar beet, 7 and 14 days later on yield and technological quality of sugar beet roots was assessed. It was found that the form of silicon does not have a significant effect on the yield of sugar beet roots, and significantly modifies the biological yield of sugar and the pure sugar yield. The highest biological yield of sugar is achieved by the foliar application of PS, and the pure sugar yield by PS and OSA. The date of foliar application as well as the interaction of the date of application and silicon forms do not have a significant effect on the root yield, biological yield of sugar, and pure sugar yield. The form of silicon has a significant effect on the technological quality of sugar beet roots (sugar, α-amino nitrogen, potassium, and sodium content). The most beneficial effect on the sugar content and reduction of sodium content in sugar beet roots is the foliar application of OSA, and the reduction of α-amino nitrogen and potassium content—PS. The timing of the application of various forms of silicon has a significant effect on the sugar and potassium content in sugar beet roots. The most beneficial effect on the sugar content in the roots is the application carried out 7 days after the six-leaf phase of sugar beet, and the potassium content is most limited by the treatment 14 days after reaching this phase. The interaction of the timing of foliar application and the form of silicon significantly modifies the technological quality features of sugar beet roots: the content of sugar, α-amino nitrogen, potassium, and sodium. The results of the study proved the significant effect of silicon foliar application on the physiological parameters of plants, such as leaf area index (LAI), absorption of photosynthetically active radiation (PAR) and normalized difference vegetation index (NDVI) which are related to yield and sugar beet productivity.
The Impact of Soil and Water Pollutants Released from Poultry Farming on the Growth and Development of Two Plant Species
Authors: Krupka Magdalena , Olkowska Ewa , Klimkowicz-Pawlas Agnieszka , Łęczyński Leszek , Tankiewicz Maciej , Michalczyk Dariusz J. , Wolska Lidia , Piotrowicz-Cieślak Agnieszka I.
Published: December 2023

Intensive poultry production may result in substantial emissions of pollutants into the environment, including pharmaceuticals and other chemicals used in poultry farming. The objective of this study was to verify the presence of ciprofloxacin, enrofloxacin, carbamazepine, metoclopramide, trimethoprim, diflufenican, flufenacet, and p,p′-DDE in soil and water in the immediate vicinity of a poultry manure heap. The influence of soil contaminants on the growth and selected physiological parameters of seed peas and common duckweed (as indicator plants) was tested. It has been proven that the cultivation of pea plants on soil coming from the close proximity of a heap of manure results in a deterioration of both morphological parameters (root length, shoot length) and physiological parameters (chlorophyll absorption, aminolevulinic acid dehydrogenase (ALAD) activity, aminolevulinic acid (ALA) content, lipid peroxidation, mitochondrial damage or production of HSP70 proteins). Similarly, water extracts from cultivated soils had a significant effect on duckweed, and it was found that contaminant leachates are indeed detectable in soil, groundwater, and deep water. Special attention should, therefore, be paid to the location, methods of storage, and use of poultry fertilizer.
Lupinus mutabilis Breeding in the Andes of Ecuador, Peru, and Bolivia: A Review
Authors: Rodríguez-Ortega Diego , Zambrano José Luis , Pereira-Lorenzo Santiago , Torres Andrés , Murillo Ángel
Published: December 2023

Lupinus mutabilis, also known as tarwi or chocho, is an important agricultural species that has been cultivated in South America since ancient times. Tarwi is native to the Andean regions of Peru, Bolivia, and Ecuador and has very high protein content. Despite its high nutritional value and promotion efforts by regional researchers and breeders, tarwi is not a widely cultivated crop in its center of origin. In this review, we present the work carried out by public breeding programs of L. mutabilis at national agricultural research institutes, universities, and other institutions in Ecuador, Peru, and Bolivia. The main breeding method used in the Andes to improve local landraces has been mass selection to adapt lines to specific environments. At least 25 cultivars or ecotypes have been selected and released over the last 40 years using this breeding system. Nevertheless, breeders are currently struggling to develop new varieties that are high yielding, suitable for mechanized harvesting, have a low content of alkaloids or other anti-nutritional properties, and resistant to anthracnose (Colletotrichum acutatum). Therefore, it is necessary to reassess the potential of this crop and invest in its research to incorporate new techniques and breeding strategies to optimize the development of new varieties in the Andes which address the current cultivation challenges of the species.
Mechanisms and Mitigation Strategies for the Occurrence of Continuous Cropping Obstacles of Legumes in China
Authors: Ma Lei , Ma Shaoying , Chen Guiping , Lu Xu , Chai Qiang , Li Sheng
Published: December 2023

Legumes have important nutritional and economic values, but their production faces continuous cropping obstacles that seriously affect their yield formation. In order to reduce the negative impact of the continuous cropping obstacles of legumes, it is necessary to understand the response mechanisms of legumes to continuous cropping, the causes of continuous cropping obstacles and the measures to alleviate continuous cropping obstacles. This review aimed to identify the current knowledge gap in the field of continuous cropping obstacles of legumes and provide direction and focus for future research. The continuous cropping obstacles of legumes start with soil degradation, leading to oxidative stress in the plants. This triggers the expression of plant-hormone- and signal-molecule-related genes, activating the defense system and causing continuous cropping obstacles. Although there has been progress in researching these challenges in legume crops, many questions remain. We believe that the exploration of molecular mechanisms of legume crops responding to continuous cropping, rhizosphere signal exchange and soil environment repair mechanisms after long-term continuous cropping of soybean, and the excavation of candidate genes and functional loci related to continuous cropping obstacles in legume crops are breakthroughs for proposing effective continuous cropping obstacle management strategies in the future.
Exploring Infant Physical Activity Using a Population-Based Network Analysis Approach
Authors: Thelagathoti Rama Krishna , Chaudhary Priyanka , Knarr Brian , Schenkelberg Michaela , Ali Hesham H. , Dinkel Danae
Published: December 2023

Background: Physical activity (PA) is an important aspect of infant development and has been shown to have long-term effects on health and well-being. Accurate analysis of infant PA is crucial for understanding their physical development, monitoring health and wellness, as well as identifying areas for improvement. However, individual analysis of infant PA can be challenging and often leads to biased results due to an infant’s inability to self-report and constantly changing posture and movement. This manuscript explores a population-based network analysis approach to study infants’ PA. The network analysis approach allows us to draw conclusions that are generalizable to the entire population and to identify trends and patterns in PA levels. Methods: This study aims to analyze the PA of infants aged 6–15 months using accelerometer data. A total of 20 infants from different types of childcare settings were recruited, including home-based and center-based care. Each infant wore an accelerometer for four days (2 weekdays, 2 weekend days). Data were analyzed using a network analysis approach, exploring the relationship between PA and various demographic and social factors. Results: The results showed that infants in center-based care have significantly higher levels of PA than those in home-based care. Moreover, the ankle acceleration was much higher than the waist acceleration, and activity patterns differed on weekdays and weekends. Conclusions: This study highlights the need for further research to explore the factors contributing to disparities in PA levels among infants in different childcare settings. Additionally, there is a need to develop effective strategies to promote PA among infants, considering the findings from the network analysis approach. Such efforts can contribute to enhancing infant health and well-being through targeted interventions aimed at increasing PA levels.
Molecular and Serological Studies on Potential SARS-CoV-2 Infection among 43 Lemurs under Human Care—Evidence for Past Infection in at Least One Individual
Authors: Musoles-Cuenca Beatriz , Aguiló-Gisbert Jordi , Lorenzo-Bermejo Teresa , Canales Rocío , Ballester Beatriz , Romani-Cremaschi Umberto , Martínez-Valverde Rosa , Maiques Elisa , Marteles Diana , Rueda Pablo , Rubio Vicente , Villanueva-Saz Sergio , Rubio-Guerri Consuelo
Published: December 2023

In the setting of the recent COVID-19 pandemic, transmission of SARS-CoV-2 to animals has been reported in both domestic and wild animals and is a matter of concern. Given the genetic and functional similarities to humans, non-human primates merit particular attention. In the case of lemurs, generally considered endangered, they are believed to be susceptible to SARS-CoV-2 infection. We have conducted a study for evidence of SARS-CoV-2 infection among the 43 lemurs of Mundomar, a zoological park in Benidorm, Spain. They belong to two endangered lemur species, 23 black-and-white ruffed lemurs (Varecia variegata) and 20 ring-tailed lemurs (Lemur catta). Health assessments conducted in 2022 and 2023 included molecular analyses for SARS-CoV-2 RNA of oral and rectal swabs using two different RT-qPCR assays, always with negative results for SARS-CoV-2 in all animals. The assessment also included serological testing for antibodies against the receptor-binding domain (RBD) of the spike protein (S) of SARS-CoV-2, which again yielded negative results in all animals except one black-and-white ruffed lemur, supporting prior infection of that animal with SARS-CoV-2. Our data, while not indicating a high susceptibility of lemurs to SARS-CoV-2 infection, show that they can be infected, adding to the existing information body on potential ways for SARS-CoV-2 virus spreading in zoos, highlighting the need for animal surveillance for the virus.
Epidemiological Features of Postpartum Subclinical Ketosis in Dairy Herds in Hokkaido, Japan
Authors: Chisato Kyoko , Yamazaki Takerou , Kayasaki Shuji , Fukumori Rika , Oikawa Shin
Published: December 2023

This study was carried out as an observational study in order to determine the prevalence of postpartum subclinical ketosis (SCK) in dairy herds in Hokkaido, Japan. From April 2012 to March 2014, blood β-hydroxybutyrate (BHBA) concentration was measured once within 3–88 days in milk (DIM) in 1394 apparently healthy cows from 108 farms to diagnose SCK (≥1.2 mM). In cows within 14 DIM, this was classified as SCK II, and from 15 DIM, this was classified as SCK I. Herds with a combined percentage of SCK I and SCK II of less than 10% were classified as SCK-negative herds, those with percentages of 10–25%, were classified as alert herds, and those with one of 25% or more, we classified as positive herds. The prevalence of SCK in the entire DIM was 17.6%. The prevalence of SCK II (20.2%) tended to occur more frequently than SCK I (16.5%, p = 0.094). The frequency of SCK I was higher at the fourth parity. The number of milking cows in SCK-positive herds was significantly smaller than those of the other two types of herds (p = 0.004). The frequency of SCK-positive herds in tie stalls and with component feeding was higher than for free stall or free barn and with total mixed ration (p = 0.054 and p = 0.002). This study reveals the prevalence of SCK in Hokkaido, Japan, and shows that SCK is associated with parity and the management system.
Prevalence, Virulence, and Antimicrobial Resistance of Major Mastitis Pathogens Isolated from Taiwanese Dairy Farms
Authors: Dhital Bigya , Chuang Shih-Te , Hsieh Jui-Chun , Hsieh Ming-Hsiu , Chiang Hsin-I
Published: December 2023

Mastitis, a highly prevalent disease in dairy cows, is responsible for massive financial losses due to decreased milk yield, milk quality, and costly medication. This research paper investigates antimicrobial susceptibility in cows and the role played by both resistance and virulence gene distribution in bovine mastitis. A total of 984 raw milk samples were collected from five different dairy farms and cultured on sheep blood agar plates. Antimicrobial susceptibility was determined by disc diffusion, and corresponding resistance and virulence genes were detected by PCR. Among the collected milk samples, 73, 32, and 19 isolates of Streptococcus spp., Staphylococcus spp., and coliforms were identified, respectively. The antimicrobial susceptibility results showed that Streptococcus spp. were resistant to tetracycline (86.30%), neomycin (79.45%), and oxacillin (73.97%). Staphylococcus spp. were resistant to tetracycline (59.37%) and oxacillin (53.12%). Lastly, coliforms were resistant to oxacillin (100%) and bacitracin (68.42%). The genotyping results showed that Streptococcus spp. carried the resistance genes tetM (46.57%) against tetracycline, bcrB (41.09%) against bacitracin, and aph(3)-II (39.72%) against neomycin. Staphylococcus spp. carried the resistance genes bcrB (40.62%) and tetM (18.75%), and coliforms carried the resistance genes tetM (42.10%) and bcrB (57.89%). Moreover, 57.53%, 75.0%, and 63.15% of Streptococcus spp., Staphylococcus spp., and coliforms carried lmb, fib, and ompC virulence genes, respectively. All three tested bacterial genera showed no significant association between antimicrobial resistance genes and virulence factors, although they were negatively correlated (p > 0.05). The combination of resistance gene identification and susceptibility tests as components of the diagnosis of bovine mastitis can help in selecting effective antimicrobial agents to treat it.
Genotypic Characterization of Uropathogenic Escherichia coli from Companion Animals: Predominance of ST372 in Dogs and Human-Related ST73 in Cats
Authors: Aurich Sophie , Wolf Silver Anthony , Prenger-Berninghoff Ellen , Thrukonda Lakshmipriya , Semmler Torsten , Ewers Christa
Published: December 2023

Extraintestinal pathogenic Escherichia coli (ExPEC) account for over 80% and 60% of bacterial urinary tract infections (UTIs) in humans and animals, respectively. As shared uropathogenic E. coli (UPEC) strains have been previously reported among humans and pets, our study aimed to characterize E. coli lineages among UTI isolates from dogs and cats and to assess their overlaps with human UPEC lineages. We analysed 315 non-duplicate E. coli isolates from the UT of dogs (198) and cats (117) collected in central Germany in 2019 and 2020 utilizing whole genome sequencing and in silico methods. Phylogroup B2 (77.8%), dog-associated sequence type (ST) 372 (18.1%), and human-associated ST73 (16.6%), were predominant. Other STs included ST12 (8.6%), ST141 (5.1%), ST127 (4.8%), and ST131 (3.5%). Among these, 58.4% were assigned to the ExPEC group and 51.1% to the UPEC group based on their virulence associated gene (VAG) profile (ExPEC, presence of ≥VAGs: papAH and/or papC, sfa/focG, afaD/draBC, kpsMTII, and iutA; UPEC, additionally cnf1 or hlyD). Extended-spectrum cephalosporin (ESC) resistance mediated by extended-spectrum β-lactamases (ESBL) and AmpC-β-lactamase was identified in 1.9% of the isolates, along with one carbapenemase-producing isolate and one isolate carrying a mcr gene. Low occurrence of ESC-resistant or multidrug-resistant (MDR) isolates (2.9%) in the two most frequently detected STs implies that E. coli isolated from UTIs of companion animals are to a lesser extent associated with resistance, but possess virulence-associated genes enabling efficient UT colonization and carriage. Detection of human-related pandemic lineages suggests interspecies transmission and underscores the importance of monitoring companion animals.
The Klebsiella pneumoniae carbapenemase (KPC) β-Lactamase Has Evolved in Response to Ceftazidime Avibactam
Authors: Garsevanyan Sona , Barlow Miriam
Published: December 2023

Klebsiella pneumoniae carbapenemase KPC is an important resistance gene that has disseminated globally in response to carbapenem use. It is now being implicated as a resistance determinant in Ceftazidime Avibactam (CAZ-AVI) resistance. Given that CAZ-AVI is a last-resort antibiotic, it is critical to understand how resistance to this drug is evolving. In particular, we were interested in determining the evolutionary response of KPC to CAZ-AVI consumption. Through phylogenetic reconstruction, we identified the variable sites under positive selection in the KPC gene that are correlated with Ceftazidime Avibactam (CAZ-AVI) resistance. Our approach was to use a phylogeny to identify multiple independent occurrences of mutations at variable sites and a literature review to correlate CAZ-AVI resistance with the mutations we identified. We found the following sites that are under positive selection: P104, W105, A120, R164, L169, A172, D179, V240, Y241, T243, Y264, and H274. The sites that correlate with CAZ-AVI resistance are R164, L169, A172, D179, V240, Y241, T243, and H274. Overall, we found that there is evidence of positive selection in KPC and that CAZ-AVI is the major selective pressure.
The Effectiveness of Swiveling Seats in Protecting Reclined Occupants in Highly Autonomous Driving Environments during Frontal Crashes
Authors: Tong Fang , Wang Yuchao , Jian Qifei , Lan Fengchong , Chen Jiqing
Published: December 2023

High-tilt reclined seats are one of the most popular configurations in highly automated vehicles; however, current restraint systems cannot protect out-of-position occupants in this type of seat. To reduce the risk of injury to reclined occupants, this study proposes a swiveling seat driven by occupant inertia and rotated in the sagittal plane during impact. The effectiveness of the swiveling seat was evaluated based on kinematics and injury to a human biomechanical model in a frontal sled test. A simulation matrix was constructed to design and optimize various safety devices, including the belt, pre-tensioner, knee constraint, and rotation stiffness for the swiveling seat. The results showed that (1) submarining occurred when the reclined occupant was on a fixed seat with a normal three-point belt during impact; (2) a fixed seat with a dynamic locking tongue and passenger lap pretension prevented the submarining, but produced a high lumbar force of 5359 N, which was higher than the spine injury criterion; and (3) the proposed swiveling seat with a matched restraint system could prevent submarining and produce lumbar force of 1787 N. The results demonstrated that the swiveling seat has high potential for occupant protection in intelligent driving scenarios.
FLGQM: Robust Federated Learning Based on Geometric and Qualitative Metrics
Authors: Liu Shangdong , Xu Xi , Wang Musen , Wu Fei , Ji Yimu , Zhu Chenxi , Zhang Qurui
Published: December 2023

Federated learning is a distributed learning method that seeks to train a shared global model by aggregating contributions from multiple clients. This method ensures that each client’s local data are not shared with others. However, research has revealed that federated learning is vulnerable to poisoning attacks launched by compromised or malicious clients. Many defense mechanisms have been proposed to mitigate the impact of poisoning attacks, but there are still some limitations and challenges. The defense methods are either performing malicious model removal from the geometric perspective to measure the geometric direction of the model or adding an additional dataset to the server for verifying local models. The former is prone to failure when facing advanced poisoning attacks, while the latter goes against the original intention of federated learning as it requires an independent dataset; thus, both of these defense methods have some limitations. To solve the above problems, we propose a robust federated learning method based on geometric and qualitative metrics (FLGQM). Specifically, FLGQM aims to metricize local models in both geometric and qualitative aspects for comprehensive defense. Firstly, FLGQM evaluates all local models from both direction and size aspects based on similarity calculated by cosine and the Euclidean distance, which we refer to as geometric metrics. Next, we introduce a union client set to assess the quality of all local models by utilizing the union client’s local dataset, referred to as quality metrics. By combining the results of these two metrics, FLGQM is able to use information from multiple views for accurate poisoning attack identification. We conducted experimental evaluations of FLGQM using the MNIST and CIFAR-10 datasets. The experimental results demonstrate that, under different kinds of poisoning attacks, FLGQM can achieve similar performance to FedAvg in non-adversarial environments. Therefore, FLGQM has better robustness and poisoning attack defense performance.
Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and Machine Learning Approaches
Authors: Ramaswamy Viswambari Devi , Keidar Michael
Published: December 2023

Plasma technology shows tremendous potential for revolutionizing oncology research and treatment. Reactive oxygen and nitrogen species and electromagnetic emissions generated through gas plasma jets have attracted significant attention due to their selective cytotoxicity towards cancer cells. To leverage the full potential of plasma medicine, researchers have explored the use of mathematical models and various subsets or approaches within machine learning, such as reinforcement learning and deep learning. This review emphasizes the significant application of advanced algorithms in the adaptive plasma system, paving the way for precision and dynamic cancer treatment. Realizing the full potential of machine learning techniques in plasma medicine requires research efforts, data sharing, and interdisciplinary collaborations. Unraveling the complex mechanisms, developing real-time diagnostics, and optimizing advanced models will be crucial to harnessing the true power of plasma technology in oncology. The integration of personalized and dynamic plasma therapies, alongside AI and diagnostic sensors, presents a transformative approach to cancer treatment with the potential to improve outcomes globally.
Enhancing Self-Care Prediction in Children with Impairments: A Novel Framework for Addressing Imbalance and High Dimensionality
Authors: Alyasin Eman Ibrahim , Ata Oguz , Mohammedqasim Hayder , Mohammedqasem Roa’a
Published: December 2023

Addressing the challenges in diagnosing and classifying self-care difficulties in exceptional children’s healthcare systems is crucial. The conventional diagnostic process, reliant on professional healthcare personnel, is time-consuming and costly. This study introduces an intelligent approach employing expert systems built on artificial intelligence technologies, specifically random forest, decision tree, support vector machine, and bagging classifier. The focus is on binary and multi-label SCADI datasets. To enhance model performance, we implemented resampling and data shuffling methods to tackle data imbalance and generalization issues, respectively. Additionally, a hyper framework feature selection strategy was applied, using mutual-information statistics and random forest recursive feature elimination (RF-RFE) based on a forward elimination method. Prediction performance and feature significance experiments, employing Shapley value explanation (SHAP), demonstrated the effectiveness of the proposed model. The framework achieved a remarkable overall accuracy of 99% for both datasets used with the fewest number of unique features reported in contemporary literature. The use of hyperparameter tuning for RF modeling further contributed to this significant improvement, suggesting its potential utility in diagnosing self-care issues within the medical industry.
Optimal Deception Asset Deployment in Cybersecurity: A Nash Q-Learning Approach in Multi-Agent Stochastic Games
Authors: Kong Guanhua , Chen Fucai , Yang Xiaohan , Cheng Guozhen , Zhang Shuai , He Weizhen
Published: December 2023

In the face of an increasingly intricate network structure and a multitude of security threats, cyber deception defenders often employ deception assets to safeguard critical real assets. However, when it comes to the intranet lateral movement attackers in the cyber kill chain, the deployment of deception assets confronts the challenges of lack of dynamics, inability to make real-time decisions, and not considering the dynamic change of an attacker’s strategy. To address these issues, this study introduces a novel maze pathfinding model tailored to the lateral movement context, in which we try to find out the attacker’s location to deploy deception assets accurately for interception. The attack–defense process is modeled as a multi-agent stochastic game, by comparing it with random action policy and Minimax-Q algorithm, we choose Nash Q-learning to solve the deception asset’s deployment strategy to achieve the optimal solution effect. Extensive simulation tests reveal that our proposed model exhibits good convergence properties. Moreover, the average defense success rate surpasses 70%, attesting to the model’s efficacy.
Comparative Study of Carbon Nanotubes and Lignosulfonate as Polyvinyl Acetate (PVAc) Wood Adhesive-Reinforcing Agents
Authors: Vidal-Vega Marcela , Núñez-Decap Mario , Hernández-Durán Javier , Catricura-Muñoz Pedro , Jara-Briones Catalina , Moya-Rojas Boris , Opazo-Carlsson Camila
Published: December 2023

This study aimed to reinforce a polyvinyl acetate-D3 (PVAc-D3) adhesive to improve its mechanical and thermal properties. The goal was to reach a polyvinyl acetate-D4 (PVAc-D4) adhesive performance that could make PVAc-D3 more attractive and add value to wood products. PVAc-D3 was modified by adding 0.05% and 0.5% (wt.) of multi-walled carbon nanotube particles (MWCNTs) as well as 0.5% and 2.5% (wt.) of lignosulfonate (LIGNO) particles. Adhesive blends were compared to neat PVAc-D3 and PVAc-D4, evaluating their physical–chemical properties. Also, they were analyzed using Fourier transform infrared spectroscopy (FT-IR) and mechanical dynamic analysis (DMA) with a storage module (E′). The blends were used to fabricate laminated wood pieces, pressed at 60 and 120 min (min), to be tested at shear strength under dry, elevated temperature and vacuum-pressure conditions. Delamination and adhesive penetration were determined by microscopy. Incorporating fillers into PVAc resulted in a decrease in viscosity. FT-IR evidenced that the PVAc-D4 adhesive had a bigger cross-linked degree than the other adhesive samples. The DMA showed that LIGNO and MWCNT fillers help increase E′ at the bond line, reaching a higher stiffness level than neat PVAc-D3. In dry conditions, specimens glued with D3-LIGNO 0.5% at 120 min reached shear strengths that were 100%, 28%, and 3% higher than the standard requirement, PVAc-D4, and neat PVAc-D3, respectively. Also, those glued with D3-MWNTC 0.05% reached shear strengths that were 91%, 21%, and 3% higher than the standard requirement, D4, and neat D3, respectively. Only PVAc-D4 reached the standard requirement for elevated temperature and vacuum-pressure conditions. Delamination of ≤5% (standard requirement) was achieved by wood specimens glued with neat PVAc-D3, D3-MWNTC 0.5%, D3-LIGNO 0.5%, and PVAc D4 adhesive samples. In this study, it was found specific ranges of average penetration (AP) to ensure a glue line good quality. To conclude, LIGNO and MWCNT particles improved the PVAc-D3 adhesive’s performance in dry conditions, but they were not very relevant to the D3 adhesive’s behavior. At high temperatures, the LIGNO filler worked very well as a thermic stabilizer compared to the MWCNT filler. The solubility of the reinforcing agent can affect an adhesive’s blend quality and its cohesion properties. An adequate penetration depth procures a good quality bond between an adhesive and substrate with less possibilities of delamination. An extensive pressing time may cause a weak interphase and poor mechanical properties in an adhesive bond in the presence of humidity.