bluuebunny/crossref_metadata_2025_split huggingface dataset:
The economic optimization of lactation and fertility in dairy cows
Authors: Tohumcu Vefa , Tulan Tohumcu D. 
Published: October 2024

Abstract
Lactation and fertility are recognized as fundamental factors that directly influence the sustainability of dairy farming. For farms working with high-yielding dairy cows in particular, maintaining fertility parameters at economically optimal levels is crucial to ensuring the continued viability of such operations. This review underscores the necessity of implementing multifaceted strategies to attain optimal lactation and fertility outcomes, elucidating the requisite steps involved in the execution of these strategies. These include the careful execution of estrus monitoring plans, comprehensive staff training, systematic record-keeping, ensuring optimal fertility parameters, and the judicious interpretation of herd management mathematics. Accurate forecasting and investment necessitate consideration of current market dynamics. Understanding the complex interplay between lactation and fertility in dairy cows is a critical prerequisite for improving overall economic productivity through herd management. To this end, the review presented simulates how the optimization of these two parameters can be achieved and their target values, based on a 100-head herd. While the exemplary model is based on costs in Türkiye, readers can adapt this simulation to calculate according to their own country’s standards. Furthermore, the simulation evinced that dairy farms relying solely on milk production incur losses, highlighting the need for diversification to ensure sustainability. In conclusion, the symbiotic relationship between lactation and fertility demands a mathematical approach, and the adoption of these integrated strategies is essential for the sustainability of dairy farms. In this context, profitability can be attained by heeding all cautions regarding the optimization of fertility and lactation, while closely monitoring current market costs.
Detecting phase transitions based on siamese neural network
Authors: Shen Jianmin , Wang Shanshan , Li Wei , Deng Weibing , Xu Dian , Gao Feng 
Published: October 2024

Abstract
Machine learning has been widely applied in physics research. Although unsupervised learning can extract the critical points of phase transitions, the percolation model remains a challenge. Unsupervised learning using the raw configurations of the percolation model fails to capture the critical points. To capture the configuration characteristics of the percolation model, this paper proposes using the maximum cluster as input to the neural network. It is well understood that the order parameter of the percolation model is not simply the particle density, but rather the probability that a given site or bond belongs to the percolating cluster. Additionally, we introduce the use of a Siamese Neural Network (SNN) to detect percolation phase transitions. Unlike unsupervised dimensionality reduction methods or supervised binary classification outputs, the SNN produces a scalar output referred to as similarity. By combining the maximum cluster and the SNN, we not only successfully extract the critical value of the percolation model, but also calculate the correlation exponent via data collapse. We believe that the SNN has great potential in handling phase transition classification problems and can serve as a reference for studying other phase transition systems.
Investigation of the capabilities of an electro-optic modulator based on a temperature-noncritical KTP crystal
Authors: Istamgulova Julia R , Gagarskiy Sergey V , Grechin Sergey G , Druzhinin Petr Y , Rusov Vladimir A , Sergeev Andrey N 
Published: October 2024

Abstract
The results of theoretical and experimental investigations on angular selectivity and features of a temperature-noncritical electro-optic modulator based on the potassium titanyl phosphate crystal are presented. The influence of angular selectivity and the walk-off effect on the electro-optic modulator contrast and the inhomogeneity of the transverse distribution of modulator transmittance are investigated. The contrast value was measured for both half-wave and compensated quarter-wave schemes.
Tuning the magnetocaloric and structural properties of La0.67Sr0.28Pr0.05Mn1–xCoxO3 refrigeration materials
Authors: Xu 徐 Changji 长吉 , Jiang 姜 Xinyu 心雨 , Zou 邹 Zhengguang 正光 , Xie 谢 Zhuojia 卓家 , Zhang 张 Weijian 伟建 , Feng 冯 Min 敏 
Published: October 2024

Abstract
The structural, magnetic and magnetocaloric properties of perovskite manganites La0.67Sr0.28Pr0.05Mn1−x
Co
x
O3 (x = 0.05, 0.075 and 0.10) (LSPMCO) are investigated. LSPMCO crystallizes as a rhombohedral structure with R-3c space group. As the Co content increases, the cell volume expands, the Mn–O–Mn bond angle reduces and the length of the Mn–O bond increases. The samples show irregular submicron particles under a Zeiss scanning electron microscopy. The particle size becomes larger with increasing doping. The chemical composition of the samples is confirmed by x-ray photoelectron spectroscopy (XPS). The ferromagnetic (FM) to paramagnetic (PM) phase transition occurs near the Curie temperature (T
C), and all transitions are second-order phase transitions (SMOPT) characterized by minimal thermal and magnetic hystereses. Critical behavior analysis indicates that the critical parameters of LSPMCO closely align with those predicted by the mean-field model. The T
C declines with Co doping and reaches near room temperature (302 K) at x = 0.075. The maximum magnetic entropy change (

−
Δ

S
M

max

) at x = 0.05 is 4.27 J/kg⋅K, and the relative cooling power (RCP) peaks at 310.81 J/K. Therefore, the system holds significant potential for development as a magnetic refrigeration material, meriting further professional and objective evaluation.
Suppression of the Kelvin–Helmholtz instability by coating in the double-cone ignition scheme
Authors: Xie 谢 Yuan-Kai 元凯 , Zhang 张 Cheng-Long 成龙 , Cheng 程 Yi-Zhen 翊真 , Li 李 Ying-Jun 英骏 
Published: October 2024

Abstract
In order to address the issue of gold mixing caused by the Kelvin–Helmholtz instability (KHI) in the double-cone ignition (DCI) scheme, we investigate the growth rate of the KHI at the bi-interface of the DCI scheme after applying a coating. This is done by solving the hydrodynamic equations for an ideal incompressible fluid using linear theory. Ultimately, it is discovered that applying a coating with a thickness slightly above h = 0.5(λ + 10 μm) and a density somewhat lower than that of the target layer can effectively reduce the growth rate of interfacial KHI. This work provides theoretical references for studying the bi-interface KHI in the DCI scheme.
Deep-learning-assisted optical communication with discretized state space of structured light
Authors: Zhang 张 Minyang 敏洋 , Chen 陈 Dong-Xu 东旭 , Ruan 阮 Pengxiang 鹏祥 , Liu 刘 Jun 俊 , Fu 付 Dong-Zhi 栋之 , Zhao 赵 Jun-Long 军龙 , Yang 杨 Chui-Ping 垂平 
Published: October 2024

Abstract
The rich structure of transverse spatial modes of structured light has facilitated their extensive applications in quantum information and optical communication. The Laguerre–Gaussian (LG) modes, which carry a well-defined orbital angular momentum (OAM), consist of a complete orthogonal basis describing the transverse spatial modes of light. The application of OAM in free-space optical communication is restricted due to the experimentally limited OAM numbers and the complex OAM recognition methods. Here, we present a novel method that uses the advanced deep learning technique for LG modes recognition. By discretizing the spatial modes of structured light, we turn the OAM state regression into classification. A proof-of-principle experiment is also performed, showing that our method effectively categorizes OAM states with small training samples and the accuracy exceeds 99% from three-dimensional (3D) to fifteen-dimensional (15D) space. By assigning each category a classical information, we further apply our approach to an image transmission task, achieving a transmission accuracy of 99.58%, which demonstrates the ability to encode large data with low OAM number. This work opens up a new avenue for achieving high-capacity optical communication with low OAM number based on structured light.
Experiment and detection method for loose bolts in sensor installation
Authors: Wan Fahui , Wu Yafeng , Li Jin , Tao Zhenyu 
Published: October 2024

Abstract
Aiming at the loosening problem of the sensor connected by bolts in the process of vibration signal acquisition, the experiment is designed and the method of the problem is studied. The sensor’s different loose degree is designed by using the vibration table. The frequency response characteristics and energy distribution of the sensor under different degrees of looseness are observed by broadband white noise. The variational mode decomposition method is used to extract the vibration response characteristics of different states. The classification algorithm is used to classify the features. According to the model prediction results, it shows that the method can effectively detect the loose state of the acceleration sensor.
Multi-objective optimization design of high-speed diaphragm coupling based on RSM and NSGA-II
Authors: Cui Peizhu , Gao Chuang 
Published: October 2024

Abstract
This study conducts a comprehensive strength analysis of diaphragm couplings in gas turbines, focusing particularly on their performance under complex operating conditions and overload scenarios. The presented text introduces a methodology for optimizing the design of diaphragm couplings. This methodology utilizes response surface methodology and the NSGA-II genetic algorithm. Following the optimization process, significant improvements have been observed in the performance of the diaphragm coupling. These enhancements encompass a noteworthy reduction of 14.7% in maximum stress, a significant decrease of 19.1% in stress amplitude, and a marginal reduction in mass by 0.004 kg.
Study on the effect of ultrasonic impact on residual stress and deformation in welding arc additive manufacturing
Authors: Wu Jinfeng , Yu Chang , Huang Fei , Yuan Shuxian , Zhao Yue 
Published: October 2024

Abstract
A 2219 aluminum alloy was manufactured by ultrasonic impact arc additive welding, and well-formed multilayer and multipass deposition parts were obtained. The residual stresses on the top and substrate of 2219 aluminum alloy samples deposited by the conventional arc and ultrasonic impingement arc were measured by ultrasonic stress testing equipment. Through experiments, the following conclusions were reached: the residual stress of those specimens subjected to ultrasonic impact is lower than that of the specimens without ultrasonic impact, and the residual stress of the arcing and quenching positions is the most obvious reduction. The deformation of the substrate treated by ultrasonic impact treatment is less than that of the sample without ultrasonic impact treatment.
Three-stage flapping-wing mechanism based on double crank and double rocker
Authors: Wang Ziyu , Gao Zifan 
Published: October 2024

Abstract
To address the limitations of current flapping-wing structures, which fail to achieve complex and variable flight attitudes and lack dexterous bionic performance, this paper introduces a novel three-segment flapping-wing drive mechanism. This mechanism can simultaneously achieve flapping and secondary folding through a single motor drive. Through kinematic analysis, the kinematic model of the driving mechanism was established. By using the transmission angle and rod length conditions as constraints for the model, and the swing angles of the inner and mid-section rockers as objective functions, the optimization model of the flapping mechanism is established, leading to the optimization of the rod length parameters. Finally, the designed flapping-wing mechanism is simulated and analyzed using ADAMS, and the theoretical analysis is validated. The results align with biological flight parameters, demonstrating that the flapping-wing mechanism possesses favorable flight characteristics and bionic motion properties. The ADAMS simulation analysis curve is consistent with the MATLAB theoretical calculation analysis curve, confirming the accuracy of the theoretical analysis.
Optimization of fuzzy-PID temperature controller based on improved slime mould algorithm
Authors: Liu Xiaoma , Zhang Zhen , Peng Zhuo , Yang Jingsong 
Published: October 2024

Abstract
The temperature control system in narrow and closed spaces such as heating furnaces often has the characteristics of large hysteresis, inertia, and non-linearity. In this scenario, the classical PID controller makes it difficult to achieve a satisfactory control effect, for this reason, domestic and foreign research and practical engineering applications mostly use fuzzy PID controllers. In this paper, we first introduce Tent chaotic mapping, nonlinear feedback updating factor to improve the standard slime mould optimization algorithm (SMA), and then the quantization factor and scale factor are both optimized based on the improved SMA. The simulation is carried out in the standard test function and the typical confined space temperature control system and the results show that compared with classical PID control and fuzzy PID control methods, the proposed controller has a shorter rise time, smaller tracking error, and superior control effect.
Simulation of cooling system performance of super magnetostrictive actuator for high-speed trains
Authors: Liu Tianren , Meng Jianjun 
Published: October 2024

Abstract
Given the thermal characteristics of the super magnetostrictive actuator, a cooling system is designed for the heat dissipation characteristics of the super magnetostrictive actuator of high-speed trains. Based on the Ansys finite element analysis platform, the heat generation problem of the super magnetostrictive actuator is introduced and analyzed, the thermal performance parameters of the magnetostrictive material are studied, the Jile-Atherton hysteresis regression model based on the eddy current loss and the additional loss parameter is established, and the total loss of the super magnetostrictive actuator in the active suspension system of the high-speed train is calculated. The cooling water flow field is solved and calculated as a boundary with the help of the finite element analysis method. With the help of finite element analysis, the temperature field of the super magnetostrictive actuator is calculated by solving the cooling water flow field and using it as the boundary. A new water cooling de-heating method is proposed. Through repeated simulations, the experimental data and the calculation results are consistent. The temperature fluctuations during operation are suppressed, which confirms the feasibility of heat dissipation and cooling, reduces the probability of the GMA temperature rise effect, effectively suppresses the harmful effects of the temperature rise effect, and has a good cooling effect on the super magnetostrictive actuator of high-speed trains.
Comparison of the dynamic response of clamped plates under fully confined and unconfined air-blast loading
Authors: Chen Zengkui , Xia Yan , Liu Dong , Li Xue , Zhao Zhenyu , Lu Tianjian 
Published: October 2024

Abstract
Compared to an unconfined explosion, e.g., air blast, explosive threats in confined spaces must be carefully considered in fields such as aerospace, aviation, and shipping due to their dramatic destructive potential. This paper systematically investigates and compares the dynamic mechanical responses of monolithic plates under fully confined/unconfined blast loadings. Three-dimensional finite element (FE) simulations using the Coupled Eulerian-Lagrangian (CEL) method are validated, demonstrating a remarkable concordance with experimental observations for monolithic plates. Structural permanent deflections and deformation modes are captured by detonating the spherical TNT charge. In addition, numerical predictions further reveal additional insights into the complex interactions of blast shock waves and structure. The structural response to confined blast conditions is contrasted with that under air blast, considering an equivalent stand-off distance between the spherical charge and the specimen. The comparison reveals that the final structural deformation is four times greater in the confined blast scenario compared to the air blast case.
Feature extraction for periodic impacts based on singular gini index
Authors: Liang Lin , Cui Xujun , Liu Chengxu 
Published: October 2024

Abstract
Impulsivity and periodicity are key characteristics of bearing impact faults, which can be more advisable than energy-oriented methods when applied to develop effective singular component selection strategies. Therefore, unlike standard singular value decomposition methods, a fault feature extraction technique based on singular value sequence distribution and the Gini index is proposed. This approach employs the Gini index as a metric to assess both the impulsiveness and periodicity characteristics of individual components. It can describe the richness of fault information in singular components. Based on the proposed evaluation criteria, an effective singular component retention strategy is proposed, which can identify components with weak energy but rich fault information in vibration signals. Through simulation data analysis and application examples, the validity of the approach is confirmed.
Design of a new scintillator-based fast ion loss detector on the HL-2A tokamak
Authors: Yuxiao Han , Jinlin Xie , Jie Zhang , Xiaofei He , Yongqing Wang , Linzi Liu , Hongbing Xu , Xuwen Zhan , Kuancheng Liu , Yipo Zhang , Zhongbing Shi , Wei Chen , Wulv Zhong , Min Xu , Ge Zhuang ,   the HL-2A Team
Published: October 2024

Abstract
A new scintillator-based fast ion loss detector (FILD) has
been devised for the HL-2A tokamak, with the objective of discerning
the temporal evolution of energy and pitch angle among lost fast
ions. A code named FILD Simulation (FSC) has been developed to
assist in the design of the detector head and the interpretation of
experimental data. By optimising the geometric design, the
resolutions of energy and pitch angle are optimised to 5 keV and
3°, respectively. A branched imaging fiber bundle is used to
relay the fluorescence image on the scintillator to two distinct
instruments. One of these is a high-speed camera, while the other is
a silicon photomultiplier tube (SiPM) array with a sampling rate of
up to 1 MSamples/s. This configuration enables the attainment of
superior temporal and spatial resolution, as well as high photon
sensitivity.
Improving the representation of cattle grazing patterns in the European Union
Authors: Malek Žiga , Romanchuk Zoriana , Yaschun Orysia , Jones Gwyn , Petersen Jan-Erik , Fritz Steffen , See Linda 
Published: October 2024

Abstract
Improving the sustainability of the European cattle sector requires improved knowledge not only of the density of cattle, but also of the grazing patterns. Only in this way can the potential negative impacts of cattle related to local ecosystem degradation, as well as positive ones such as preserving cultural landscapes through grazing, be analyzed. While data on livestock distribution often used in scientific analyses can provide estimates on density, the separation between the livestock that has access to outdoor grazing and those that remain indoors is not available. This is problematic because it prevents the identification of the intensity and type of grassland management, as well as the consequential environmental impacts of grazing livestock. Here we present an approach where we combined agricultural and veterinary statistics, in-situ data, expert surveys and machine learning to develop a map of grazing cattle distribution for the wider European Union region. Our approach and the resulting data allow for the differentiation between cattle that are actually grazing versus those that do not. We also compare our method to traditional approaches that do not have a clear separation between grazing and non-grazing cattle, illustrating the implications that this can have for agricultural, land use and environmental assessments.
Data visualisation for decision making under deep uncertainty: current challenges and opportunities
Authors: Hadjimichael Antonia , Schlumberger Julius , Haasnoot Marjolijn 
Published: October 2024

Abstract
This perspective article explores the role of data visualisation in decision-making under deep uncertainty (DMDU), a growing discipline tackling complex socio-environmental challenges, such as climate impacts and adaptation, natural resource management, and preparedness for extreme events. We discuss the role of visualisation for both analysis (or exploratory) purposes, as well as communication (or explanatory) purposes, including to stakeholders and the public. We identify a lack of comprehensive guidelines on how visualisations are currently used and their potential in enhancing DMDU processes. Drawing on literature and insights from a recent workshop, we identify key challenges DMDU analysts face when visualising data: managing complexity and dimensionality, effectively communicating uncertainty, and ensuring user engagement and interpretability. We propose a research agenda to address these challenges, by taxonomising and evaluating the effectiveness of different visual forms in decision-making contexts, and fostering interdisciplinary collaboration. We argue that, through these efforts, we can improve the communication and usability of DMDU analyses, ultimately aiding in more informed and adaptive decision-making in the face of deep uncertainty.
Exact solution of long-range stabilizer Rényi entropy in the dual-unitary XXZ model*
Authors: Montañà López Jordi Arnau , Kos Pavel 
Published: October 2024

Abstract
Quantum systems can not be efficiently simulated classically due to the presence of entanglement and nonstabilizerness, also known as quantum magic. Here we study the generation of magic under evolution by a quantum circuit. To be able to provide exact solutions, we focus on the dual-unitary XXZ model and a measure of magic called stabilizer Rényi entropy (SRE). Moreover, we focus also on long-range SRE, which cannot be removed by short-depth quantum circuits. To obtain exact solutions we use a ZX-calculus representation and graphical rules for the evaluation of the required expressions. We obtain exact results for SRE after short-time evolution in the thermodynamic limit and for long-range SRE for all times and all Rényi parameters for a particular partition of the state. Since the numerical evaluation of these quantities is exponentially costly in the Rényi parameter, we verify this numerically for low Rényi parameters and accessible system sizes and provide numerical results for the long-range SRE in other partitions.