bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of mental health symptoms in Austrian veterinarians and examination of influencing factors
Authors: Neubauer Viktoria , Dale Rachel , Probst Thomas , Pieh Christoph , Janowitz Katharina , Brühl Deianira , Humer Elke 
Published: June 2024

AbstractAlthough previous studies point to a high mental health burden in veterinarians, little is known about mental health in Austrian veterinarians as well as potential underlying factors of poor mental health. We assessed mental health in Austrian veterinarians, compared it to the mental health of the general population, and explored potential risk factors for poor mental health in veterinarians. A total of n = 440 veterinarians (72.0% women; mean age: 44.53 ± 11.25 years) took part in an online survey in 2022 in which validated screening tools for symptoms of depression (PHQ-9), anxiety (GAD-7), sleep disorders (ISI-2), perceived stress (PSS-4), and alcohol abuse (CAGE) were applied. Multivariable logistic regression revealed higher adjusted odds for exceeding cut-offs for clinically relevant depressive, anxiety, and insomnia symptoms in veterinarians (1.35–2.70) compared to the general population. Mental health symptoms in veterinarians were associated with female gender, physical inactivity, higher smartphone usage, higher working hours, less professional experience, and working with pets. In conclusion, it appears that veterinarians encounter mental health challenges that are more pronounced than those experienced in the general population. The teaching of strategies to improve mental hygiene as part of the curricula of veterinary education and targeted training and mentoring of employers and their team should be implemented to improve mental health in the veterinary profession.
Preparation of a self-matting, anti-fingerprint and skin-tactile wood coating via biomimetic self-wrinkling patterns
Authors: Sun Yingchun , Liu Ru , Long Ling , Sun Yuhui 
Published: June 2024

AbstractInspired by natural wrinkled surfaces, artificial surfaces with biomimetic wrinkled structures have been widely used to improve optical properties, wettability, and antibacterial properties. However, the preparation of wrinkled structures has the disadvantages of long-time consumption and complex processes. Herein, we prepared a self-wrinkling polyurethane-acrylate (PUA) wood coating via biomimetic self-wrinkling patterns by using a light-emitting diode (LED)/excimer/mercury lamp curing system, which was capable of self-matting, anti-fingerprint and skin-tactile performance. By adjusting the irradiation intensity in the curing system, the wavelength (λ) and amplitude (A) of wrinkles on the coating surface were controlled to enhance the coating performance. After curing by the LED, excimer, and mercury lamps at energy intensities of 500, 30, and 300 mW/cm2 respectively, the self-wrinkling coating showed excellent surface performance. The self-wrinkling coating represented low gloss of 4.1 GU at 85°, high hardness of 4H. Interestingly, the coating surface had a high hydrophobicity (104.5°) and low surface energy (29–30 mN/m) and low coefficient (COF) of friction (0.1–0.2), which were consistent with those of the human skin surface. Besides, the wrinkled structure also improved the thermal stability of the coating samples. This study provided a promising technique for the mass production of self-wrinkling coatings that could be used in wood-based panels, furniture, and leather.
The optimization of the vault-predicting formula based on the anterior segment measurements from artemis insight 100
Authors: Wang Hao , Zhang Bo , Du Wenwen , Sun Zaohe , Fan Qi , Pang Chenjiu 
Published: June 2024

AbstractTo optimize and evaluate the accuracy of the vault-predicting formula generated from a very high-frequency digital ultrasound robotic scanner (Artemis Insight 100). The relationship between the achieved lens vault (LVa) at one month after intraocular collamer lens (ICL) implantation surgery and the predicted vault (LVp) was analyzed by a retrospective study, and an optimized formula was built up. Then, the accuracy of the optimized vault-predicting formula was evaluated in a prospective study by comparing the LVa and the predicted vault from the optimized formula (LVop). The retrospective study included 77 patients (133 eyes) while the prospective study enrolled 90 patients (170 eyes). The difference between LVp and LVa at one month after surgery was statistically significant (P < 0.05), and the linear regression analysis of LVa against LVp yielded a good fit (R2 = 0.68). The optimized vault-predicting formula was LVop (μm) = 1.21 × LVp (μm) + 124.73. In the validation study, the difference between LVop and LVa was not statistically significant (P = 0.10), and a good agreement between LVop and LVa was shown by Bland–Altman analysis. The optimized vault-predicting formula could predict the actual LV after ICL implantation surgery, help to select an appropriate ICL size and reduce the need for re-operation.
A machine learning ensemble approach for predicting solar-sensitive hybrid photocatalysts on hydrogen evolution
Authors: Bakır Rezan , Orak Ceren , Yüksel Aslı 
Published: June 2024

Abstract
Hydrogen, as the lightest and most abundant element in the universe, has emerged as a pivotal player in the quest for sustainable energy solutions. Its remarkable properties, such as high energy density and zero emissions upon combustion, make it a promising candidate for addressing the pressing challenges of climate change and transitioning towards a clean and renewable energy future. In an effort to improve efficiency and reduce experimental costs, we adopted machine learning techniques in this study. Our focus turned to predictive analyses of hydrogen evolution values using three photocatalysts, namely, graphene-supported LaFeO3 (GLFO), graphene-supported LaRuO3 (GLRO), and graphene-supported BiFeO3 (GBFO), examining their correlation with varying levels of pH, catalyst amount, and H2O2 concentration. To achieve this, a diverse range of machine learning models are used, including Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), XGBoost, Gradient Boosting, and AdaBoost—each bringing its strengths to the predictive modeling arena. An important step involved combining the most effective models—Random Forests, Gradient Boosting, and XGBoost—into an ensemble model. This collaborative approach aimed to leverage their collective strengths and improve overall predictability. The ensemble model emerged as a powerful tool for understanding photocatalytic hydrogen evolution. Standard metrics were employed to assess the performance of our ensemble prediction model, encompassing R squared, Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). The yielded results showcase exceptional accuracy, with R squared values of 96.9%, 99.3%, and 98% for GLFO, GBFO, and GLRO, respectively. Moreover, our model demonstrates minimal error rates across all metrics, underscoring its robust predictive capabilities and highlighting its efficacy in accurately forecasting the intricate relationships between GLFO, GBFO, and GLRO values and their influencing factors.
Predictive analytics of wear performance in high entropy alloy coatings through machine learning
Authors: Sivaraman S , Radhika N 
Published: June 2024

Abstract
High-entropy alloys (HEAs) are increasingly renowned for their distinct microstructural compositions and exceptional properties. These HEAs are employed for surface modification as coatings exhibit phenomenal mechanical characteristics including wear and corrosion resistance which are extensively utilized in various industrial applications. However, assessing the wear behaviour of the HEA coatings through conventional methods remains challenging and time-consuming due to the complexity of the HEA structures. In this study, a novel methodology has been proposed for predicting the wear behaviour of HEA coatings using Machine Learning (ML) algorithms such as Support Vector Machine (SVM), Linear Regression (LR), Gaussian Process Regression (GPR), Least Absolute Shrinkage and Selection Operator (LASSO), Bagging Regression (BR), Gradient Boosting Regression Tree (GBRT), and Robust regressions (RR). The analysis integrates of 75 combinations of HEA coatings with processing parameters and wear test results from peer-reviewed journals for model training and validation. Among the ML models utilized, the GBRT model was found to be more effective in predicting wear rate and Coefficient of Friction (COF) with the highest correlation coefficient of R2 value of 0.95 ∼ 0.97 with minimal errors. The optimum model is used to predict the unknown wear properties of HEA coatings from the conducted experiments and validate the results, making ML a crucial resource for engineers in the materials sector.
Effect of heat treatment on microstructure and mechanical properties of AG728 steel joints welded with ER90S-G wires
Authors: Feng Yizheng , Xu Xiangping , Wang Xiling , Wang Lingyu , Zou Jiasheng , Wang Ziqing 
Published: June 2024

Abstract
This study utilised self-developed ER90S-G wires for butt welding tests on AG728 plates to investigate the influence of heat treatment on the microstructure and mechanical properties of welded joints. Furthermore, it aimed to analyse the microstructure and metallurgical mechanisms of these joints. The findings reveal that the microstructure of the welded joints primarily consists of acicular ferrite with a minor presence of granular bainite. Following heat treatment, there is a noticeable growth in acicular ferrite and the emergence of tempered sorbite and massive ferrite; concurrently, austenite grain boundaries vanish, carbide aggregation increases, the quantity of large angular grain boundaries diminishes, and the martensite–austenite constituent elements gradually disappear. The physical phase of the base material, the heat-affected zone (HAZ), and the welded joints uniformly transition to α-Fe. Additionally, inclusions measuring 0.5 μm, predominantly MnSiO3, evidently promote the formation of ferrite. The tensile strength and impact toughness experience a minor reduction while the hardness of the HAZ and weld seam significantly decreases. The micro-morphology of the welded joint’s tensile fracture is predominantly characterised by dimples, within which inclusions or precipitated phase particles are distinctly visible, indicating a microporous coalescence-type fracture. At −45 °C, the impact test of welded joints reveals that the HAZ impact fracture micro-morphology exhibits brittle deconstructive fracture patterns, which, through heat treatment, transition to quasi-cleavage characteristics with reduced and shorter river patterns. The base material and weld fracture micro-morphology are primarily defined by the presence of dimples.
Entangled multiplets, asymmetry, and quantum Mpemba effect in dissipative systems
Authors: Caceffo Fabio , Murciano Sara , Alba Vincenzo 
Published: June 2024

AbstractRecently, the entanglement asymmetry emerged as an informative tool to understand dynamical symmetry restoration in out-of-equilibrium quantum many-body systems after a quantum quench. For integrable systems the asymmetry can be understood in the space-time scaling limit via the quasiparticle picture, as it was pointed out in Areset al(2023Nat. Commun.142036) . However, a quasiparticle picture for quantum quenches from generic initial states was still lacking. Here we conjecture a full-fledged quasiparticle picture for the charged moments of the reduced density matrix, which are the main ingredients to construct the asymmetry. Our formula works for quenches producing entangled multiplets of an arbitrary number of excitations. We benchmark our results in theXXspin chain. First, by using an elementary approach based on the multidimensional stationary phase approximation we provide anab initiorigorous derivation of the dynamics of the charged moments for the quench treated in Areset al(2023SciPost Phys.15089). Then, we show that the same results can be straightforwardly obtained within our quasiparticle picture. As a byproduct of our analysis, we obtain a general criterion ensuring a vanishing entanglement asymmetry at long times. Next, by using the Lindblad master equation, we study the effect of gain and loss dissipation on the entanglement asymmetry. Specifically, we investigate the fate of the so-called quantum Mpemba effect (QME) in the presence of dissipation. We show that dissipation can induce QME even if unitary dynamics does not show it, and we provide a quasiparticle-based interpretation of the condition for the QME.
Entanglement Hamiltonian in the non-Hermitian SSH model
Authors: Rottoli Federico , Fossati Michele , Calabrese Pasquale 
Published: June 2024

Abstract
Entanglement Hamiltonians provide the most comprehensive characterisation of entanglement in extended quantum systems. A key result in unitary quantum field theories is the Bisognano-Wichmann theorem, which establishes the locality of the entanglement Hamiltonian. In this work, our focus is on the non-Hermitian Su-Schrieffer-Heeger (SSH) chain. We study the entanglement Hamiltonian both in a gapped phase and at criticality. In the gapped phase we find that the lattice entanglement Hamiltonian is compatible with a lattice Bisognano-Wichmann result, with an entanglement temperature linear in the lattice index. At the critical point, we identify a new imaginary chemical potential term absent in unitary models. This operator is responsible for the negative entanglement entropy observed in the non-Hermitian SSH chain at criticality.
Mathematical model of explosion-proof performance of pressure container packaging based on dimension analysis
Authors: Wen Quan , Zhu Jiale , Mi Chenxi 
Published: June 2024

Abstract
As the protective body of the pressure container, the reliability of pressure container packaging directly determines the safety of the pressure container. Therefore, the explosion-proof performance of pressure container packaging is crucial. In order to measure the explosion-proof performance of pressure container packaging, witness plate pressure is used to measure the explosion-proof performance of pressure container packaging, and a method based on dimension analysis is proposed to establish a mathematical model of the explosion-proof performance of pressure container packaging. This model quantitatively solves the nonlinear relationship between the peak pressure of the witness plate and the number of pressure container packaging layers, pressure container packaging thickness, and packaging materials. Applying this to the design of pressure container packaging can provide a reference for improving the explosion-proof performance of pressure container packaging.
Experimental study on strength and carbonation performance of hybrid fibre lightweight aggregate concrete in precast structures
Authors: Zhao Xiaolang , Zheng Xiuhua , Zhong Wei , Jiang Wei , Hu Dingyu 
Published: June 2024

Abstract
To improve the brittle failure characteristics and carbonation performance of lightweight aggregate concrete, basalt fibre, and polyacrylonitrile fibre were incorporated. The effects of the two fibres on the compression strength and carbonation depth were studied through compression tests and rapid carbonation tests. The effects of mineral admixture proportion were also studied. The results show that when the mass content of basalt fibre and polyacrylonitrile fibre is 2.8 kg/m3 and 0.9 kg/m3, respectively, the average increase of compression strength for different ages is approximately 40%, and the average decrease of carbonation depth for different ages is approximately 8%. Furthermore, when the mass content of mineral admixture is 30%, the higher proportion of slag contributed to the greater compression strength, but smaller carbonation depth. As supported by the experimental results, the improvements in strength and carbonation performance of lightweight aggregate concrete will make it more competitive in the application of precast buildings and long-span bridges.
Composite manufacturing of metal porous thin strip with metal wire mesh and powder
Authors: Lin Shengcun , Feng Wenxiu , Shi Fusheng 
Published: June 2024

Abstract
Porous metal materials are applied in various industries, among which powder rolling is the most widely used process for preparing porous metal materials. Then, metal porous materials prepared solely from powder as raw materials have the disadvantage of low mechanical properties, while wire mesh as reinforcement can effectively improve tensile strength. The preparation process of wire mesh powder composite is complex and requires the addition of adhesives. In this article, the mechanical properties of thin metal strips prepared by powder and wire mesh composite vertical rolling were much higher than those prepared by pure powder. Moreover, this thin strip had porous characteristics, and the preparation process was simple and easy to promote. This research could provide a reference for the powder metallurgy field, especially for the preparation of metal porous materials by vertical rolling.
Synthesis of thiophene-isoindigo receptor small molecules and its application in photodetectors
Authors: Guan Sheng , Guo Pengzhi 
Published: June 2024

Abstract
Organic photodetectors (OPDs) have attracted wide attention from researchers on account of their characteristics such as easy to manufacture, low cost, lightweight, and flexible detectors. Many efforts have been made to improve the performance of OPDs. Scientists have made many efforts to improve the performance of organic photodetectors. Among them, narrow-band-gap organic photoelectric functional materials with wide spectral response exhibit application prospects in photoelectric detection. In this paper, a series of narrow-band-gap thienoisoindigo receptor small molecules were synthesized by using thienoisoindigo, and electron deficient terminal octyl cyanoacetate, 3-ethylrhodanine, and 2-(3-ethyl-4-oxothiazolidine-2-ylidene) malonitrile as receptor units, and 3-dodecylthiophene as donor unit, The photodetector with wide spectral response and high detection rate is fabricated using a Bulk Heterojunction (BHJ) structure.
Study on the microstructure and mechanical properties of W-wire/TiBe, ZrBe, and ZrTiBe alloy composites
Authors: Chu Shaochen , Wang Jinhe , Zhang Bo , Li Zhengkun , Fu Huameng , Li Hong , Zhu Zhengwang , Zhang Haifeng 
Published: June 2024

Abstract
The microstructure and mechanical performance of W wire/Ti70Be30, Zr65Be35, and Zr37.5Ti26Be36.5 alloy composites were investigated in this study using X-ray diffractometer, scanning electron microscopy, and mechanical universal testing machine. These composites were prepared through the melt impregnation method under optimized processing conditions. The results show that the compressive strength of the three composites is all above 2600 MPa. The Ti70Be30-W composites diffuse violently at the interface, the W-Ti phase is formed at the interface, and the cracks of the composites under the action of applied load show a stepped pattern. The Zr65Be35-W composite reacts violently at the interface, resulting in a W2Zr interfacial product, which adheres to the surface of the W filament and presents a continuous interfacial reaction layer. When subjected to external load, the crack will expand rapidly along the interfacial reactive layer. The addition of Ti in Zr37.5Ti26Be36.5-W composites effectively inhibited the W-Zr reaction, the interface reactant W2Zr disappeared, and the W-Ti interface product presented a discontinuous interfacial reaction layer on the surface of the W filament, and the material split under the action of external load, and the crack showed step-like propagation.
Hydrodynamic characterization of the surfacing attitude of the manned deep-sea submersible
Authors: Huang Jiaxin , Zhang Gangqing , Kong Weiyu 
Published: June 2024

Abstract
Hydrodynamic characteristics of manned deep-sea submersibles are important for optimizing design, increasing safety, and improving handling and control. To study the hydrodynamic characteristics of manned deep-sea submersibles in different surfacing attitudes, this paper carries out hydrodynamic tests on the scaled-down simplified model of “Jiaolong” submersible of 1:36. The drag, lift, and pitching moment of the manned deep-sea submersible in different surfacing attitudes are obtained by six-component sensors, and the time-averaged streamlines, turbulence kinetic energy, normal velocity and Reynolds stress distribution are obtained by photographing the wake flow field of the submersible using PIV particle image velocimetry. The results show that compared with the vertical surfacing attitude, the drag decreased by 38.2%, the lift magnitude rose by 98.9%, the pitching moment decreased by 20.8%, the vortex disappeared in the stern wake area, and the maximum turbulent kinetic energy decreased by 33.6% when surfacing at a 30° rake angle.
Characterization of mechanical properties of carbon nanotube fibers prepared by chemical vapor deposition
Authors: Li Shuping , wang Yan 
Published: June 2024

Abstract
A chemical vapor deposition (CVD) method for preparing carbon nanotube fibers was proposed. This method used ethanol/acetone as the carbon source, ferrocene as the catalyst and thiophene as the promoter. It used a high-temperature gas-phase flow reaction to spin out carbon tube fibers. Subsequently, the mechanical properties of carbon tube fibers prepared under different conditions (carbon source, gas flow and raw material ratio) were characterized and analyzed. The results demonstrated that the carbon fiber prepared with ethanol as the carbon source under specific synthesis conditions has good continuity and can be prepared for 3 hours in succession. In a feasible condition (Fe, S, C ratio, air flow ratio, and growth temperature), using pure acetone as the carbon source can prepare carbon nanotube fibers with fiber-specific strength > 1.5N / tex.
Energy absorption behaviour and shape change effects of 3D printed polyurethane hexagonal honeycombs
Authors: Liu Yangzuo , Wang Zelin , Tang Ziruo , Li Haotian , Xu Cheng , Ma Wuning 
Published: June 2024

Abstract
Honeycombs have been used in a wide range of repeatable energy-absorbing elements due to their light weight and high energy absorption capacity. In the engineering environment, honeycombs will produce a shape change effect and rebound under multiple loading and unloading, so it is of great importance to investigate the energy-absorbing properties of honeycombs under the shape change effect for the application of honeycombs. In this study, the deformation process and energy absorption properties of 3D printed honeycombs under multiple loading were obtained through multiple quasi-static compression tests. On this basis, the coupling between shape change effects and honeycomb energy absorption is revealed. It is shown that the number of compressions does not affect the four-stage force-displacement curve characteristics of the honeycombs, but only the energy absorption efficiency of the honeycombs. There is an inverse relationship between the resilience of honeycombs and the energy absorption capacity of honeycombs, and the change of honeycomb stiffness under repeated compression is the direct cause of this relationship. The research results provide a reference for the application of honeycombs in the field of repetitive energy absorption.