bluuebunny/crossref_metadata_2025 huggingface dataset:
A Piecewise Linear Regression Model Ensemble for Large-Scale Curve Fitting
Authors: Moreno-Carbonell Santiago , Sánchez-Úbeda Eugenio F.
Published: March 2024

The Linear Hinges Model (LHM) is an efficient approach to flexible and robust one-dimensional curve fitting under stringent high-noise conditions. However, it was initially designed to run in a single-core processor, accessing the whole input dataset. The surge in data volumes, coupled with the increase in parallel hardware architectures and specialised frameworks, has led to a growth in interest and a need for new algorithms able to deal with large-scale datasets and techniques to adapt traditional machine learning algorithms to this new paradigm. This paper presents several ensemble alternatives, based on model selection and combination, that allow for obtaining a continuous piecewise linear regression model from large-scale datasets using the learning algorithm of the LHM. Our empirical tests have proved that model combination outperforms model selection and that these methods can provide better results in terms of bias, variance, and execution time than the original algorithm executed over the entire dataset.
Invariant Kalman Filter Design for Securing Robust Performance of Magnetic–Inertial Integrated Navigation System under Measurement Uncertainty
Authors: Lee Taehoon , Lee Byungjin , Sung Sangkyung
Published: March 2024

This study proposes an enhanced integration algorithm that combines the magnetic field-based positioning system (MPS—Magnetic Pose Estimation System) with an inertial system with the advantage of an invariant filter structure. Specifically, to mitigate the nonlinearity of the propagation model and perturbing effect from the estimated uncertainty, the formulation of the invariant Kalman filter was derived in detail. Then, experiments were conducted to validate the algorithm with an unmanned vehicle equipped with an IMU and MPS receiver. As a result, the navigation performance of the IEKF-based inertial and magnetic field integration system was presented and compared with the conventional Kalman filter results. Furthermore, the convergence and navigation performance were evaluated in the presence of state variable initialization errors. The findings indicate that the inertial and magnetic field coupled with the IEKF outperforms the typical KF approach, particularly when dealing with initial estimate uncertainties.
Parameterized Reduced-Order Models for Probabilistic Analysis of Thermal Protection System Based on Proper Orthogonal Decomposition
Authors: Zhang Kun , Yao Jianyao , Zhu Wenxiang , Cao Zhifu , Li Teng , Xin Jianqiang
Published: March 2024

The thermal protection system (TPS) represents one of the most critical subsystems for vehicle re-entry. However, due to uncertainties in thermal loads, material properties, and manufacturing deviations, the thermal response of the TPS exhibits significant randomness, posing considerable challenges in engineering design and reliability assessment. Given that uncertain aerodynamic heating loads manifest as a stochastic field over time, conventional surrogate models, typically accepting scalar random variables as inputs, face limitations in modeling them. Consequently, this paper introduces an effective characterization approach utilizing proper orthogonal decomposition (POD) to represent the uncertainties of aerodynamic heating. The augmented snapshots matrix is used to reduce the dimension of the random field by the decoupling method of independently spatial and temporal bases. The random variables describing material properties and geometric thickness are also employed as inputs for probabilistic analyses. An uncoupled POD Gaussian process regression (UPOD-GPR) model is then established to achieve highly accurate solutions for transient heat conduction. The model takes random heat flux fields as inputs and thermal response fields as outputs. Using a typical multi-layer TPS and thermal structure as two examples, probabilistic analyses are conducted. The mean square relative error of a typical multi-layer TPS is less than 4%. For the thermal structure, the averaged absolute error of the radiation and insulation layer is less than 25 °C and 6 °C when the maximum reaches 1200 °C and 150 °C, respectively. This approach can provide accurate and rapid predictions of thermal responses for TPS and thermal structures throughout their entire operating time when furnished with input heat flux fields and structural parameters.
Investigations on Hot Air Anti-Icing Characteristics with Internal Jet-Induced Swirling Flow
Authors: Liu Yuyang , Yi Xian
Published: March 2024

The tangential jet-induced swirling flow is a highly efficient technology for enhancing heat transfer. This paper explores the application of swirling flow of an airfoil/aero-engine in a hot air anti-icing chamber, aiming to improve the anti-icing performance and achieve a more uniform temperature on the surface. A series of numerical computations adopting the SST k − ω turbulent model was carried out to obtain the internal flow and heat transfer characteristics, as well as the surface temperature distributions, considering water evaporation and solid heat conduction. Three jet arrangements, including impingement jets, offset jets, and swirl jets, were studied and compared, which evidently showed that the swirling effect was helpful to elevate the internal heat transfer. Compared to the impingement jets at the Reynolds number of 40,000, the Nusselt number with the offset jets is increased by 19.5%, while the corresponding Nusselt number of the swirl jets is augmented by 44.3%. The swirling flow significantly elevates the swirl number within the internal chamber, intensifying the vortex strength near the wall and increasing the circumferential velocity, which also results in an augmentation of internal pressure loss. By adopting the swirling internal flow, the temperature distribution on the anti-icing surface is more uniform and is increased by up to about 4.1 K in the leading edge when the internal-to-external temperature difference is 80 K. Simultaneously, the heat absorption of water evaporation and the matches between the internal heat transfer and external icing load are of particular importance to determine the anti-icing performance, and this has been discussed in this paper.
Design and Experimental Study of a Drilling Tool for Mars Rock Sampling
Authors: Liu Yafang , Zhang Lu , Tian Ye , Zhang Weiwei , Tang Junyue , Zhang Jiahang , Duan Zhangqing , Ji Jie
Published: March 2024

Martian rocks contain crucial information about the genesis of Mars and the historical evolution of Martian climate change. Consequently, extracting and examining Martian rocks are pivotal in advancing our comprehensive understanding of the red planet. However, the current core drill string is prone to wear and tear, and the samples are susceptible to thermal denaturation. To address these challenges, we introduce two novel types of drill bits, the conical straight junk slot and the conical spiral junk slot, both employing impregnated diamond as the primary material. Comparative experiments were meticulously conducted to evaluate the influence of different junk configurations on drilling parameters, including speed, abrasion resistance, drilling force loading, and sample temperature rise. The findings unequivocally demonstrate the superior performance of the spiral junk slot. Furthermore, simulations were performed to examine the drilling process on basalt using a fixed configuration drill bit, validating the occurrence of the sample temperature rise. The research presented in this paper offers valuable programmatic references and essential data support for future Martian rock coring drilling missions.
A Framework for Aircraft Conceptual Design and Multidisciplinary Optimization
Authors: Hosseini Saeed , Vaziry-Zanjany Mohammad Ali , Ovesy Hamid Reza
Published: March 2024

In this research, the architecture and the functionalities of the LAMBDA (Laboratory of Aircraft Multidisciplinary Knowledge-Based Design and Analysis) framework for the design, analysis, and optimization of civil aircraft are presented. The framework is developed in MATLAB R2022a and comprises a modular architecture, which gives the potential for the use of different methods and fidelities for each discipline. The methods can be selected from a set of built-in methods or custom user-defined scripts. Disciplinary modules of the LAMBDA are Requirements, Weight, Sizing, Geometry, Aerodynamics, Engine, Performance, Cost, Emission, and Optimization. This framework has been used for different types of design and optimization problems. When it is applied for the design and optimization of a novel regional TBW (Truss-Braced Wing) aircraft, the operating cost has been reduced by 7.7% in the optimum configuration compared to the base configuration.
Wind Tunnel Investigation of Transient Propeller Loads for Non-Axial Inflow Conditions
Authors: Moreira Catharina , Herzog Nikolai , Breitsamter Christian
Published: March 2024

Recent developments in electrical Vertical Take-off and Landing (eVTOL) vehicles show the need for a better understanding of transient aero-mechanical propeller loads for non-axial inflow conditions. The variety of vehicle configurations conceptualized with different propellers in terms of blade geometry, number of blades, and their general integration concept results in aerodynamic loads on the propellers which are different from those on conventional fixed-wing aircraft propellers or helicopter rotors. Such varying aerodynamic loads have to be considered in the vehicle design as a whole and also in the detailed design of their respective electric propulsion systems. Therefore, an experimental approach is conducted on two different propeller blade geometries and a varying number of blades with the objective to explore the characteristics at non-axial inflow conditions. Experimental data are compared with calculated results of a low-fidelity Blade Element Momentum Theory (BEMT) approach. Average thrust and side force coefficients are shown to increase with inflow angle, and this trend is captured by the implemented numerical method. Measured thrust and in-plane forces are shown to oscillate at the blade passing frequency and its harmonics, with higher amplitudes at higher angles of inflow or lower number of blades.
A Review of Novel Heat Transfer Materials and Fluids for Aerospace Applications
Authors: Nobrega Glauco , Cardoso Beatriz , Souza Reinaldo , Pereira José , Pontes Pedro , Catarino Susana O. , Pinho Diana , Lima Rui , Moita Ana
Published: March 2024

The issue of thermal control for space missions has been critical since the early space missions in the late 1950s. The demands in such environments are heightened, characterized by significant temperature variations and the need to manage substantial densities of heat. The current work offers a comprehensive survey of the innovative materials and thermal fluids employed in the aerospace technological area. In this scope, the materials should exhibit enhanced reliability for facing maintenance and raw materials scarcity. The improved thermophysical properties of the nanofluids increase the efficiency of the systems, allowing the mass/volume reduction in satellites, rovers, and spacecraft. Herein are summarized the main findings from a literature review of more than one hundred works on aerospace thermal management. In this sense, relevant issues in aerospace convection cooling were reported and discussed, using heat pipes and heat exchangers, and with heat transfer ability at high velocity, low pressure, and microgravity. Among the main findings, it could be highlighted the fact that these novel materials and fluids provide enhanced thermal conductivity, stability, and insulation, enhancing the heat transfer capability and preventing the malfunctioning, overheating, and degradation over time of the systems. The resulting indicators will contribute to strategic mapping knowledge and further competence. Also, this work will identify the main scientific and technological gaps and possible challenges for integrating the materials and fluids into existing systems and for maturation and large-scale feasibility for aerospace valorization and technology transfer enhancement.
Analysis of Wave Propagation with Different Magnetic Configurations in Helicon Plasmas
Authors: Tian Bin , Xie Kan , An Bingchen , Wang Jing , Yang Su-Lan , Cao Yong
Published: March 2024

A two-dimensional plasma–wave interaction model, which is based on the cold collisional plasma dielectric tensor, is applied to investigate the wave propagation and power depositions under different magnetic configurations in helicon plasmas. The varied magnetic configurations are formed by changing the radius of the magnetic coil. When the magnetic coil was positioned closer to the plasma, the magnetic field within the plasma became stronger and more curved. Consequently, the simulation results show that the wave propagation and power deposition in plasmas follow the curved magnetic field lines. In the axial direction, the periodic distribution of wave fields and power deposition are clearly observed and keep consistency in helicon plasmas due to the eigenmodes of helicon waves. Furthermore, a concave dark area where the wave cannot propagate is observed in the closest magnetic coil case and leads to limited power deposition.
Virtual Full Scale Static Test of a Civil Tilt Rotor Composite Wing in Non-Linear Regime
Authors: Chiariello Antonio , Perillo Gaetano , Linari Mauro , Russo Raffaele , Orlando Salvatore , Vitale Pasquale , Belardo Marika
Published: March 2024

This study addresses the crucial role of post-buckling behavior analysis in the structural design of composite aeronautical structures. Traditional engineering practices tend to result in oversized composite components, increasing structural weight. EASA AMC 20-29’s Building Block Approach suggests phased testing, but its time and cost challenges necessitate a shift to high-fidelity post-buckling analyses, exemplified by MSC NASTRAN SOL 400. This approach, showcased in the analysis of the Next Generation Civil Tilt Rotor Technology Demonstrator’s wing (NGTCTR-TD), effectively de-risks static tests, contributing to a more efficient certification process. The study demonstrates how advanced simulations provide detailed insights into local buckling phenomena, allowing precise stress distribution analysis. These analyses eliminate the risk of structural failure, paving the way for safer, more efficient, and cost-effective airframe structures. Future developments aim to validate numerical analyses with experimental data, further emphasizing the reliability and benefits of high-fidelity simulations.
Smart Ground Support Equipment—The Design and Demonstration of Robotic Ground Support Equipment for Small Spacecraft Integration and Verification
Authors: Kottmeier Sebastian , Wittje Philipp , Klinkner Sabine , Essmann Olaf , Suhr Birgit , Kirchler Jan-Luca , Ho Tra-Mi
Published: March 2024

In order to reduce the costs of integration and verification processes and to optimize the assembly, integration and verification (AIV) flow in the prototype development of small- and medium-sized spacecrafts, an industrial six-axis robot was used as a universal mechanical ground support equipment instead of a tailored prototype specific ground support equipment (GSE). In particular, a robotic platform offers the possibility of embedding verification steps such as mass property determination into the integration process while offering a wider range of ergonomic adaption due to the enhanced number of degrees of freedom compared to a classical static Mechanical GSE (MGSE). This reduces development costs for projects and enhances the flexibility and ergonomics of primarily mechanical AIV operations. In this paper, the robotic MGSE system is described, the operational prospects for in-line verification are elaborated and an example is given showing the possibilities and challenges of its operational use as well as its in-line mass determination capabilities. For this purpose, a method has been developed that allows for the precise measurement of the spacecraft mass using the robot’s existing technology without the need for additional hardware. Subsequent work will extend this to determine the center of gravity and the moments of inertia of the payload on the robotic MGSE.
Spike Device with Worm Gear Unit for Driving Wheels to Improve the Traction Performance of Compact Tractors on Grass Plots
Authors: Abrahám Rudolf , Majdan Radoslav , Kollárová Katarína , Tkáč Zdenko , Matejková Eva , Masarovičová Soňa , Drlička Róbert
Published: March 2024

In general, energy loss reduction via the interaction of tires with the ground improves tractor traction performance when a drawbar pull is generated. This paper is examines the driving wheels with steel spikes for a tractor equipped with modern radial tires. An improved design of the spike device that allows for the change between an active and inactive position of the spikes is presented. The traction performance of a compact articulated tractor with the spike device was tested on a grass plot with two soil moisture contents (SMC). The highest difference in the drawbar pull in the range from 14.2% to 40.5% and from 17.1% to 36.8% was reached by the spikes in the active position in comparison with the tires without spikes, which were at the slip range from 45% to 5% in the case of the low SMC when the test tractor was in the 3rd and 1st gear. The motion resistance difference between the spikes in the active position and the tires without spikes was 11.8% and 2.5% at the low and medium SMC, respectively. At the low and medium SMC, the highest tractive efficiency of 0.765 (0.721) and 0.757 (0.731) was reached by the spikes in the active position when the test tractor was in the 1st (3rd) gear in comparison with 0.736 (0.7) and 0.723 (0.708) in the case of the tires without spikes. The results indicated that the spike device allowed for the improvement of tractor tractive performance.
Review of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana
Authors: Moomen Abdul-Wadood , Yevugah Lily Lisa , Boakye Louvis , Osei Jeff Dacosta , Muthoni Francis
Published: March 2024

This paper assesses evidence-based applications of Remote Sensing for Sustainable and Precision Agriculture in the Northern Savanna Regions of Ghana for three decades (1990–2023). During this period, there have been several government policy intervention schemes and pragmatic support actions from development agencies towards improving agriculture in this area with differing level of success. Over the same period, there have been dramatic advances in remote sensing (RS) technologies with tailored applications to sustainable agriculture globally. However, the extent to which intervention schemes have harnessed the incipient potential of RS for achieving sustainable agriculture in the study area is unknown. To the best of our knowledge, no previous study has investigated the synergy between agriculture policy interventions and applications of RS towards optimizing results. Thus, this study used systematic literature review and desk analysis to identify previous and current projects and studies that have applied RS tools and techniques to all aspects of agriculture in the study area. Databases searched include Web of Science, Google Scholar, Scopus, AoJ, and PubMed. To consolidate the gaps identified in the literature, ground-truthing was carried out. From the 26 focused publications found on the subject, only 13 (54%) were found employing RS in various aspects of agriculture observations in the study area. Out of the 13, 5 studies focused on mapping the extents of irrigation areas; 2 mapped the size of crop and pasturelands; 1 focused on soil water and nutrient retention; 1 study focused on crop health monitoring; and another focused on weeds/pest infestations and yield estimation in the study area. On the type of data, only 1 (7%) study used MODIS, 2 (15%) used ASTER image, 1 used Sentinel-2 data, 1 used Planetscope, 1 used IKONOS, 5 used Landsat images, 1 used Unmanned Aerial Vehicles (UAVs) and another 1 used RADAR for mapping and monitoring agriculture activities in the study area. There is no evidence of the use of LiDAR data in the area. These results validate the hypothesis that failing agriculture in the study area is due to a paucity of high-quality spatial data and monitoring to support informed farm decision-making.
Crop Classification Combining Object-Oriented Method and Random Forest Model Using Unmanned Aerial Vehicle (UAV) Multispectral Image
Authors: Deng Hui , Zhang Wenjiang , Zheng Xiaoqian , Zhang Houxi
Published: March 2024

The accurate and timely identification of crops holds paramount significance for effective crop management and yield estimation. Unmanned aerial vehicle (UAV), with their superior spatial and temporal resolution compared to satellite-based remote sensing, offer a novel solution for precise crop identification. In this study, we evaluated a methodology that integrates object-oriented method and random forest (RF) algorithm for crop identification using multispectral UAV images. The process involved a multiscale segmentation algorithm, utilizing the optimal segmentation scale determined by Estimation of Scale Parameter 2 (ESP2). Eight classification schemes (S1–S8) were then developed by incorporating index (INDE), textural (GLCM), and geometric (GEOM) features based on the spectrum (SPEC) features of segmented objects. The best-trained RF model was established through three steps: feature selection, parameter tuning, and model training. Subsequently, we determined the feature importance for different classification schemes and generated a prediction map of vegetation for the entire study area based on the best-trained RF model. Our results revealed that S5 (SPEC + GLCM + INDE) outperformed others, achieving an impressive overall accuracy (OA) and kappa coefficient of 92.76% and 0.92, respectively, whereas S4 (SPEC + GEOM) exhibited the lowest performance. Notably, geometric features negatively impacted classification accuracy, while the other three feature types positively contributed. The accuracy of ginger, luffa, and sweet potato was consistently lower across most schemes, likely due to their unique colors and shapes, posing challenges for effective discrimination based solely on spectrum, index, and texture features. Furthermore, our findings highlighted that the most crucial feature was the INDE feature, followed by SPEC and GLCM, with GEOM being the least significant. For the optimal scheme (S5), the top 20 most important features comprised 10 SPEC, 7 INDE, and 3 GLCM features. In summary, our proposed method, combining object-oriented and RF algorithms based on multispectral UAV images, demonstrated high classification accuracy for crops. This research provides valuable insights for the accurate identification of various crops, serving as a reference for future advancements in agricultural technology and crop management strategies.
Smart Pig Farming—A Journey Ahead of Vietnam
Authors: Sharifuzzaman Md , Mun Hong-Seok , Ampode Keiven Mark B. , Lagua Eddiemar B. , Park Hae-Rang , Kim Young-Hwa , Hasan Md Kamrul , Yang Chul-Ju
Published: March 2024

Vietnam heavily relies on pork as its primary source of animal protein. Traditional farming methods, characterized by small-scale operations, dominate the industry. However, challenges such as rising feed costs, disease outbreaks, and market volatility are prompting many farmers to abandon their businesses. Recognizing the pivotal role of the swine sector in both economic development and nutrition, authorities must intervene to prevent its collapse. In developed nations, smart pig farming, utilizing technologies like sensors and cameras for data collection and real-time decision-making, has significantly improved health and productivity. These technologies can detect subtle indicators of animal well-being, enabling prompt intervention. This review aims to analyze the drivers of Vietnam’s swine farming, identify existing production system flaws, and explore innovative precision farming methods worldwide. Embracing precision farming promises to enhance Vietnam’s competitiveness in export markets and bolster consumer confidence. However, reliance solely on expensive foreign technologies may benefit large-scale farms, leaving smaller ones behind. Therefore, fostering local innovation and validating cost-effective solutions will be crucial for the sustainable growth of small- and medium-scale pig farming in Vietnam.
The Role of the ADF Gene Family in Maize Response to Abiotic Stresses
Authors: Yang Ruisi , Wang Fei , Luo Ping , Xu Zhennan , Wang Houwen , Zhang Runze , Li Wenzhe , Yang Ke , Hao Zhuanfang , Gao Wenwei
Published: March 2024

The highly conserved actin depolymerizing factor (ADF) plays an important role in plant growth, development and responses to biotic and abiotic stresses. A total of 72 ADF genes in Arabidopsis, wheat, rice and sorghum can be divided into four groups. The multicollinearity analysis revealed that the maize ADF gene family exhibited more collinearity events with closely related gramineous plants. Fifteen ADF genes in maize were screened from the latest database, and bioinformatics analysis showed that these ADF genes were distributed across seven chromosomes in maize. The gene structure of the ADF gene family in maize exhibits significant conservation and cluster consistency. The promoter region contains rich regulatory elements that are involved in various regulations related to growth, development and adverse stresses. The drought-tolerant ZmADF5 gene in maize was further studied, and it was found that the allelic variations in ZmADF5 were mainly concentrated in its promoter region. A superior haplotype, with drought tolerance, was identified by candidate-gene association analysis of 115 inbred lines. By comparing the phenotypes of anthesis silking interval, grain yield and ear height, it was found that Hap2 performed better than Hap1 under drought stress. This study provides a theoretical reference for understanding the function of the ADF gene family and proposes further investigation into the role of ZmADF5 in abiotic-stress tolerance.
An Overview of Machine Learning Applications on Plant Phenotyping, with a Focus on Sunflower
Authors: Centorame Luana , Gasperini Thomas , Ilari Alessio , Del Gatto Andrea , Foppa Pedretti Ester
Published: March 2024

Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, machine learning can be applied to agriculture. Better crop management, plant health assessment, and early disease detection are some of the main challenges facing the agricultural sector. Plant phenotyping can play a key role in addressing these challenges, especially when combined with machine learning techniques. Therefore, this study reviews available scientific literature on the applications of machine learning algorithms in plant phenotyping with a specific focus on sunflowers. The most common algorithms in the agricultural field are described to emphasise possible uses. Subsequently, the overview highlights machine learning application on phenotyping in three primaries areas: crop management (i.e., yield prediction, biomass estimation, and growth stage monitoring), plant health (i.e., nutritional status and water stress), and disease detection. Finally, we focus on the adoption of machine learning techniques in sunflower phenotyping. The role of machine learning in plant phenotyping has been thoroughly investigated. Artificial neural networks and stacked models seems to be the best way to analyse data.
Physiological Mechanisms of Titanium Regulation of Growth, Photosynthesis, and Mineral Absorption in Tartary Buckwheat
Authors: Qi Anyin , Wang Zhengshan , Jiang Liangzhen , Wang Qiang , Ren Yuanhang , Liang Chenggang , Wang Yan , Liu Changying , Ye Xueling , Fan Yu , Wu Qi , Wu Xiaoyong , Peng Lianxin , Xiang Dabing , Guo Laichun , Zhao Gang , Zou Liang , Huang Jingwei , Wan Yan
Published: March 2024

Titanium has been reported to have positive effects on crop growth and production in various species. However, the impact of titanium on the Tartary buckwheat crops has not yet been studied. Therefore, an experiment was conducted to investigate the effect of spraying different concentrations of ionic titanium on the growth, photosynthesis, and uptake of mineral nutrients in Tartary buckwheat. The results showed that the application of titanium significantly improved dry matter accumulation, internode diameter, main stem node, root length, root average diameter, root surface area, root volume, grains per plant, and weight of grains per plant. Additionally, chlorophyll and photosynthetic parameters showed improvement regardless of the concentration of titanium used. The study found that titanium accumulation was mainly in leaves. The content of titanium in leaves showed a significant positive correlation with K, Ca, Mg, Mn, Cu, Zn, and B. This suggests a potential synergistic relationship between titanium and minerals in Tartary buckwheat leaves. Furthermore, the study also observed a significant increase in the total accumulation of P, K, Ca, Mg, Mn, Cu, Zn, and B in Tartary buckwheat plants. Overall, this study provides evidence for the positive effects of titanium on Tartary buckwheat and offers a theoretical foundation for practical production.
Fruit Crop Species with Agrivoltaic Systems: A Critical Review
Authors: Magarelli Andrea , Mazzeo Andrea , Ferrara Giuseppe
Published: March 2024

As the world seeks alternatives to fossil fuels, agrivoltaics offer a promising solution by integrating solar panels with farming practices. This review examines three key agrivoltaic setups—static tilted, full-sun tracking, and agronomic tracking—dissecting their engineering features’ roles in optimizing both the electricity yield and the fruit productivity of some fruit crops. We emphasize the microclimatic modifications induced by agrivoltaic systems, mainly encompassing changes in solar radiation, air temperature, humidity, and wind. The data collected in this survey reveal a strong spatial heterogeneity distribution over different locations and a significant influence on fruit crops’ growth, yield, and quality, with variations among species. Such findings on the overall performance recommend a 30% shading threshold to prevent substantial declines in fruit characteristics, i.e., fruit yield and quality. Shading conditions over this threshold influence the leaf morphophysiological characteristics, impacting the photosynthesis capacity and fruit dry matter accumulation. This emphasizes the importance of further investigation into spectral radiation quality and carbon assimilation kinetics as daily responses for different fruit species to be cultivated in such new environments. Starting from this point, this review underscores the need to extend studies on various fruit crops, particularly those cultivated in semi-arid horticultural regions (i.e., for saving water), and suggests the use of comprehensive and standardized indicators for comparability across studies. Finally, the authors conclude that engineering improvements, along with new research programs on agrivoltaic systems, could lead to agricultural, environmental, and economic sustainability, as well as their practical implementation and attractiveness to farmers in the coming years.
An Illustrated Scoping Review of the Magnetic Resonance Imaging Characteristics of Canine and Feline Brain Tumors
Authors: May James L. , Garcia-Mora Josefa , Edwards Michael , Rossmeisl John H.
Published: March 2024

Magnetic resonance imaging (MRI) is used pervasively in veterinary practice for the antemortem diagnosis of intracranial tumors. Here, we provide an illustrated summary of the published MRI features of primary and secondary intracranial tumors of dogs and cats, following PRISMA scoping review guidelines. The PubMed and Web of Science databases were searched for relevant records, and input from stakeholders was solicited to select data for extraction. Sixty-seven studies of moderate to low-level evidence quality describing the MRI features of pathologically confirmed canine and feline brain tumors met inclusion criteria. Considerable variability in data inclusion and reporting, as well as low case numbers, prohibited comparative data analyses. Available data support a holistic MRI approach incorporating lesion number, location within the brain, shape, intrinsic signal appearances on multiparametric sequences, patterns of contrast enhancement, and associated secondary changes in the brain to prioritize differential imaging diagnoses, and often allows for accurate presumptive diagnosis of common intracranial tumors. Quantitative MRI techniques show promise for improving discrimination of neoplastic from non-neoplastic brain lesions, as well as differentiating brain tumor types and grades, but sample size limitations will likely remain a significant practical obstacle to the design of robustly powered radiomic studies. For many brain tumor variants, particularly in cats, there remains a need for standardized studies that correlate clinicopathologic and neuroimaging data.
Comparative Metabolomic Profiling of L-Histidine and NEFA Treatments in Bovine Mammary Epithelial Cells
Authors: Sun Wenqiang , Li Mengze , Ren Hanjun , Chen Yang , Zeng Wei , Tan Xiong , Jia Xianbo , Chen Shiyi , Wang Jie , Lai Songjia
Published: March 2024

Non-esterified fatty acids (NEFAs) are pivotal in energy metabolism, yet high concentrations can lead to ketosis, a common metabolic disorder in cattle. Our laboratory observed lower levels of L-histidine in cattle suffering from ketosis, indicating a potential interaction between L-histidine and NEFA metabolism. This relationship prompted us to investigate the metabolomic alterations in bovine mammary epithelial cells (BMECs) induced by elevated NEFA levels and to explore L-histidine’s potential mitigating effects. Our untargeted metabolomic analysis revealed 893 and 160 metabolite changes in positive and negative models, respectively, with VIP scores greater than 1 and p-values below 0.05. Notable metabolites like 9,10-epoxy-12-octadecenoic acid were upregulated, while 9-Ethylguanine was downregulated. A pathway analysis suggested disruptions in fatty acid and steroid biosynthesis pathways. Furthermore, L-histidine treatment altered 61 metabolites in the positive model and 34 in the negative model, with implications for similar pathways affected by NEFA. Overlaying differential metabolites from both conditions uncovered a potential key mediator, 1-Linoleoylglycerophosphocholine, which was regulated in opposite directions by NEFA and L-histidine. Our study uncovered that both NEFA L- and histidine metabolomics analyses pinpoint similar lipid biosynthesis pathways, with 1-Linoleoylglycerophosphocholine emerging as a potential key metabolite mediating their interaction, a discovery that may offer insights for therapeutic strategies in metabolic diseases.
Estimation of Weight and Body Measurement Model for Pigs Based on Back Point Cloud Data
Authors: Liu Yao , Zhou Jie , Bian Yifan , Wang Taishan , Xue Hongxiang , Liu Longshen
Published: March 2024

Pig farming is a crucial sector in global animal husbandry. The weight and body dimension data of pigs reflect their growth and development status, serving as vital metrics for assessing their progress. Presently, pig weight and body dimensions are predominantly measured manually, which poses challenges such as difficulties in herding, stress responses in pigs, and the control of zoonotic diseases. To address these issues, this study proposes a non-contact weight estimation and body measurement model based on point cloud data from pig backs. A depth camera was installed above a weighbridge to acquire 3D point cloud data from 258 Yorkshire–Landrace crossbred sows. We selected 200 Yorkshire–Landrace sows as the research subjects and applied point cloud filtering and denoising techniques to their three-dimensional point cloud data. Subsequently, a K-means clustering segmentation algorithm was employed to extract the point cloud corresponding to the pigs’ backs. A convolutional neural network with a multi-head attention was established for pig weight prediction and added RGB information as an additional feature. During the data processing process, we also measured the back body size information of the pigs. During the model evaluation, 58 Yorkshire–Landrace sows were specifically selected for experimental assessment. Compared to manual measurements, the weight estimation exhibited an average absolute error of 11.552 kg, average relative error of 4.812%, and root mean square error of 11.181 kg. Specifically, for the MACNN, incorporating RGB information as an additional feature resulted in a decrease of 2.469 kg in the RMSE, a decrease of 0.8% in the MAPE, and a decrease of 1.032 kg in the MAE. Measurements of shoulder width, abdominal width, and hip width yielded corresponding average relative errors of 3.144%, 3.798%, and 3.820%. In conclusion, a convolutional neural network with a multi-head attention was established for pig weight prediction, and incorporating RGB information as an additional feature method demonstrated accuracy and reliability for weight estimation and body dimension measurement.
Whole-Genome Sequencing for Identifying Candidate Genes Related to the Special Phenotypes of the Taihu Dianzi Pigeon
Authors: Zhang Rui , Mu Chunyu , Chang Lingling , Shen Xinyue , Bu Zhu , Yang Mingjun , Fu Shengyong , Tang Qingping , Liu Peiyao , Yang Xiaoming
Published: March 2024

The Taihu Dianzi pigeon is a breed native to China, and its special piebalding, crest, and polydactyly phenotypes are the result of artificial and natural selection. Here, we analyzed the genetic differences among three kinds of pigeons with different phenotypes at the genomic level. A selective sweep was conducted based on the fixation index (FST) and nucleotide diversity (π) ratio, and the results revealed that MC1R was related to the formation of the distinctive piebalding of the Taihu Dianzi pigeon. Combined with the results of genome-wide association studies, we identified candidate genes associated with the crest (SMYD and STOX2) and polydactyly (SLC52A3 and ANGPT4). The candidate genes identified in this study and their variants may be useful for understanding the genetic mechanism underlying the special phenotypes of the Taihu Dianzi pigeon. This study provides new insights into the genetic factors that may influence the formation of the special piebalding, crest, and polydactyly characteristics in pigeons.
Clinical, Ovulatory and Histological Effect of a Postnatal Testosterone Treatment in Female Dogs
Authors: Marchetti Cynthia , Grisolia-Romero Mariela , Priotto Marcelo , Faya Marcela , Gobello Cristina
Published: March 2024

It has been described in some female mammalian species that postnatal androgenization causes reproductive structural and functional abnormalities. The objective of this study was to describe the clinical, ovulatory and genital effects of postnatal androgens in female dogs. Ten newborn female crossbred puppies were randomly assigned to: testosterone enanthate 18 mg/100 g sc (TE; n = 5) or placebo sc (PL; n = 5). The puppies were physically followed up until puberty when ovulation was tested by serum progesterone. Then, ovariohysterectomies were performed, and genital tracts were grossly and histomorphometrically examined. At puberty, all the females had normal estrous behavior and ovulated without age and body weight differences. All TE puppies presented mild clitoris enlargement. Gross and microscopical ovarian examination did not reveal differences. Conversely, the endometrial area occupied by uterine glands as well as the height of the glandular and luminal epithelium were higher in the TE than in the PL group (<0.01). The height of the endometrium and myometrial thickness did not differ between groups. It was concluded that a supraphysiological postnatal dose of testosterone did not affect ovulatory capacity, nor did it provoke gonadal histological alterations, although it caused an increased area of endometrial glands and a higher uterine epithelium.
The Effects of Slaughter Age and Sex on Carcass Traits, Meat Quality, and Leg Bone Characteristics of Farmed Common Pheasants (Phasianus colchicus L.)
Authors: Kokoszyński Dariusz , Żochowska-Kujawska Joanna , Kotowicz Marek , Piątek Hubert , Włodarczyk Karol , Arpášová Henrieta , Biesiada-Drzazga Barbara , Wegner Marcin , Saleh Mohamed , Imański Maciej
Published: March 2024

The aim of this study was to determine the effects of slaughter age and sex on the carcass characteristics, meat quality parameters, and leg bone dimensions of common pheasants. The study material consisted of 40 common pheasants, including 10 males and 10 females at 12 weeks of age and 10 males and 10 females at 15 weeks of age. The birds were kept on a farm in a semi-intensive system. The slaughter age had significant effects on the eviscerated carcass weight; the percentage of skin with subcutaneous fat; the wings percentage; electrical conductivity (EC24); the work required to cut the samples (cutting work); redness (a*); the intramuscular fat content in the breast meat; and the protein, intramuscular fat, water, and collagen contents in the leg meat. The sex of the pheasants had significant effects on the eviscerated carcass weight; the contents of leg muscles, skin with subcutaneous fat, and wings in the carcasses; and the electrical conductivity, thermal loss, lightness (L*), and redness (a*) of the breast muscles. It also significantly affected the protein and water contents of the pectoral and leg muscles, the intramuscular fat contents of the leg muscles, the texture traits of the pectoralis major muscle, and all femur and tibia bone dimensions. The results indicate a greater influence of sex compared to slaughter age on the pheasant traits studied. We confirmed the occurrence of a clearly marked sexual dimorphism in birds of this species. Both factors (slaughter age and gender) have significant effects on the nutritional and technological value of pheasant meat. The few studies on meat texture and the dimensions of pheasant leg bones indicate a need for continued research in this area in the future.
Welfare Implications for Tigers in Travelling Circuses
Authors: Davies Emily , Knight Andrew
Published: March 2024

There are very few studies that have focused on species-specific welfare implications for tigers in a travelling circus. The absence of scientific evidence to inform nationwide legislation means that tigers are still commonly used in travelling circuses across the world. A systematic review of relevant published studies was conducted using the bibliographic databases Web of Science and Scopus, supplemented by a narrative search. In total, 42 relevant studies were identified that assessed the welfare of tigers in captivity, including circuses and zoos. Only eight papers assessed the welfare implications for tigers in circuses directly, evidencing the lack of research in this area. Given that circuses provide a sub-optimal environment compared to zoos, implications for tiger welfare were also inferred from zoo research, within the Five Domains framework. Collectively, these papers infer that the travelling nature of a circus often negatively impacts the welfare domains of nutrition, physical environment, health, and mental state. This is due to limitations in enclosure size, as well as in both environmental and behavioural enrichment. There is also often difficulty in sourcing appropriate food and specialised routine veterinary care. The literature is divided concerning behavioural interactions, specifically whether training can improve welfare by offering mental stimulation. However, circus performances are often associated with negative welfare due to noise disruption from spectators. The collective scientific evidence indicates that tigers are not well suited to circus living, due to the inability of a travelling circus to provide for their species-specific psychological, physiological, and behavioural needs.
Effects of Nutrient Source, Temperature, and Salinity on the Growth and Survival of Three Giant Clam Species (Tridacnidae)
Authors: Lee Rod Ping-Tsan , Lin Yu-Ru , Huang Chih-Yang , Nan Fan-Hua
Published: March 2024

The habitats of giant clams are undergoing environmental changes, and giant clam populations are declining. The present study was conducted to facilitate clam conservation. We conducted three 18-week trials to investigate the effects of nutrient, temperature, and salinity on the growth performance and survival rates (SRs) of juvenile Tridacna noae, adult Tridacna crocea, and subadult Tridacna derasa, respectively. Regarding nutrient sources, no significant differences were observed in shell length gain, specific growth rate, or SR between clams fed with Chaetoceros muelleri or commercial feed (hw nanotip) and those in a control group (juvenile phototrophs). Regarding temperature, clams cultivated at 27 °C exhibited significantly better growth performance and SR than did those cultivated at 19 °C or 31 °C (p < 0.05). By week 6, all clams in the 19 °C and 31 °C groups had died, indicating that suboptimal growth temperatures have severe adverse effects. Regarding salinity, clams cultivated at 34‰ exhibited significantly higher length gains and specific growth rates than did those cultivated at 20‰ or 25‰ (p < 0.05). SR was not significantly affected by salinity. Understanding how environmental factors affect giant clam populations may help researchers devise effective clam conservation strategies.
Study of the Milkability of the Mediterranean Italian Buffalo and the Tunisian Maghrebi Camel According to Parity and Lactation Stage
Authors: Atigui Moufida , Brahmi Marwa , Marnet Pierre-Guy , Ben Salem Wiem , Campagna Maria Concetta , Borghese Antonio , Todde Giuseppe , Caria Maria , Hammadi Mohamed , Boselli Carlo
Published: March 2024

While considered as hard milkers, both buffaloes and camels are milked with equipment destined for dairy cows based on external morphological similarities with this species. This work aimed to study similarities and differences in milkability traits between Mediterranean buffaloes and Maghrebi she-camels and to evaluate the effect of parity and lactation stage. A total of 422 milk flow curves recorded with an electronic milkmeter (Lactocorder®) for both species were accessed. Milking characteristics including milk yield per milking, peak milk flow, average milk flow, duration of the main milking phase, duration of total milking, duration of various phases of milk flow, lag time and time to milk ejection, stripping yield, overmilking time and incidence of bimodal milk flow curves were evaluated for both species. Results showed that the values of milk yield per milking, duration of the main milking phase and duration of total milking were higher in buffaloes (3.98 ± 0.10 kg; 4.07 ± 0.11 min; 9.89 ± 0.21 min, respectively) compared to camels (3.51 ± 0.08 kg; 3.05 ± 0.09 min; 3.76 ± 0.09 min, respectively). However, camels had significantly higher peak and average milk flow (2.45 ± 0.07 kg/min and 1.16 ± 0.03 kg/min, respectively). Camels took significantly less time for milk ejection to occur. Only 15.49% of recorded curves were bimodal in buffaloes while 34.93% of bimodal curves were recorded for camels. Overmilking was significantly higher in buffaloes (3.64 ± 0.21 min vs. 0.29 ± 0.02 min). Parity and lactation stage had a significant effect on most studied milking traits suggesting the need for some particular practices with primiparous animals and animals at different levels of lactation for both species.