bluuebunny/crossref_metadata_2025_split huggingface dataset:
GH3536 superalloy prepared by selective laser melting: microstructure and properties
Authors: Zhang Y , Wang Y , Zhang B , Song M , Li Y , Li Y 
Published: November 2023

Abstract
In this paper, GH3536 superalloy was prepared by selective laser melting (SLM) using plasma rotating electrode powder as raw material. The effects of forming and heat treatment processes on the microstructure and mechanical properties of GH3536 superalloy were studied. The results show that there were obvious micro-cracks on the laser scanning plane of SLM samples, and the length of micro-cracks was between 10-100μm. The micro-cracks originated from the inside of the molten pools and penetrated the melting channels, and the heat treatment could not eliminate the cracks. With the increase of volume energy density (VED), the tensile strength and yield strength of SLM samples increased first and then decreased. The maximum values of tensile strength and yield strength reached 772.3MPa and 613.3MPa, respectively. However, with the increase of VED, the elongation of SLM samples decreased to 27.3%. After heat treatment, the tensile strength and yield strength of the material increased (up to 789MPa and 410MPa), but the elongation decreased.
Study on Hot Deformation Behavior and Microstructure Evolution of MgAlCuZnMnCe Alloy
Authors: Chunyu Ma , Nan Zhou , Tongyu Liu , Quan Dong , Chenghao Hou , Kaihong Zheng 
Published: November 2023

Abstract
The Mg79Al12.5Cu2.5Zn4MnCe multi-principal element alloys was prepared by induction melting under a high-purity argon. The true stress-strain curves at deformation temperatures of 250-350°C and strain rates of 0.001-1s−1 were used to establish the constitutive equations as well as the thermal processing map. The optimal hot processing parameters for the alloy were determined as a deformation temperature of 320-350°C and a strain rate of 0.1-1s−1. Further investigation into the impact of various deformation parameters on the microstructure and macrotexture of the alloy during hot compression was conducted. The findings indicate that at a deformation rate of 1s−1, the second phase of the alloy is broken and deformed. The texture intensity follows a pattern of initially decreasing and then increases as the temperature rises. The change in grain size is influenced by the deformation crushing effect, initiation of the non-substrate slip system, and grain growth. When the strain rate increases, the changes in texture intensity and distribution are not pronounced, indicating that the strain rate has minimal influence on the macro texture.
Preparation and characterization of Mg-P coatings on Mg-Zn-Y-Nd alloy for corrosion protection
Authors: Pan Y , Tan C , Han J , Liu G 
Published: November 2023

Abstract
To improve the corrosion resistance of Mg-Zn-Y-Nd alloy, Mg-P coatings were prepared on the surface by a simple chemical conversion method. The Mg-P coatings were optimized by regulating the reaction conditions such as the pH value of the conversion solution (4.2, 5, 6, and 7), treatment temperature (20 °C, 40 °C, and 80 °C), and treatment time (1 h, 2 h, and 3 h) in this study. Scanning electron microscopy (SEM) showed that the optimized Mg-P coating has a uniform surface structure. X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) results demonstrated that the Mg-P coating consists of MgNH4PO4·6H2O and MgHPO4·3H2O. The cross-sectional morphology revealed that the Mg-P coating has a rough structure with a thickness of 8 μm. The effect of Mg-P coating on the corrosion resistance of Mg-Zn-Y-Nd alloy was investigated by in vitro immersion test, and it was found that the corrosion rate was effectively decelerated within 10 days. In summary, we studied the effects of reaction conditions for preparing Mg-P coatings on the surface of Mg-Zn-Y-Nd alloy by a chemical conversion method and effectively improving the corrosion resistance of Mg-Zn-Y-Nd alloy.
Effects of graphene and carbon nanotubes on mechanical enhancement and heat generation of rubber composites
Authors: Liu Y , Chen W D , Jiang D Z 
Published: November 2023

Abstract
Carbon nanofillers can enhance both thermal and mechanical properties of rubbers due to their high thermal conductivity and tensile strength at the nanoscale. But the effects of CNTs and GR on heat generation of rubber composites are yet unclear. In this paper, carbon nanotubes/carbon black/nature rubber (CNTs/CB/NR) composites and graphene/carbon black/nature rubber (GR/CB/NR) composites were prepared by using GR and CNTs as partial replacements for carbon black, respectively. The interfacial interactions between fillers and the rubber matrix were calculated by the contact angle test, the filler-matrix network was characterized by rubber processing analyzer, and the glass transition temperature of the composite was measured by dynamic mechanical analysis. Compared with CNT or CB, GR can be well wetted by NR and uniformly distributed in NR, so there was a strong interfacial interaction between them. The better interfacial interaction will promote the formation of a good network structure between the filler and the NR, and the network structure between the filler and NR further restricts the movement of rubber molecule chains. Therefore, the heat generation by the movement of the molecule chains is decreased, and the mechanical properties of the rubber composites are increased.
Methods for preparing high-quality powder for targets
Authors: Ren Zehua , He Jinjiang , Luo Junfeng , Ding Zhaochong , Yang Wenkui 
Published: November 2023

Abstract
Powder metallurgy process can produce excellent quality magnetic targets, in which powder quality affects the quality of the target to a large extent, the production of high-quality target has an important role. This paper mainly introduces the preparation methods of powder for targets, summarizes the preparation methods of fine powder and the characteristics of different preparation methods. Finally, it summarizes the shortcomings of the current research on powder for targets, proposes new research ideas, and prospects its future development.
Two-dimensional MSi2N4 (M = Ge, Sn, and Pb) monolayers: promising new materials for optoelectronic applications
Authors: Jahangirzadeh Varjovi Mirali , Ershadrad Soheil , Sanyal Biplab , Tosoni Sergio 
Published: November 2023

Abstract
The recent growth of two-dimensional (2D) layered crystals of MoSi2N4 and WSi2N4 has sparked significant interest due to their outstanding properties and potential applications. This development has paved the way for a new and large family of 2D materials with a general formula of MA
2
Z
4. In this regard, motivated by this exciting family, we propose two structural phases (1T- and 1H-) of MSi2N4 (M = Ge, Sn, and Pb) monolayers and investigate their structural, vibrational, mechanical, electronic and optical properties by using first-principles methods. The two phases have similar cohesive energies, while the 1T structures are found to be more energetically favorable than their 1H counterparts. The analysis of phonon spectra and ab initio molecular dynamics simulations indicate that all the suggested monolayers, except for 1H-GeSi2N4, are dynamically and thermally stable even at elevated temperatures. The elastic stability and mechanical properties of the proposed crystals are examined by calculating their elastic constants (C

ij
), in-plane stiffness (

Y

2D

), Poisson’s ratio (ν), and ultimate tensile strain (UTS). Remarkably, the considered systems exhibit prominent mechanical features such as substantial in-plane stiffness and high UTS. The calculated electronic band structures reveal that both the 1T- and 1H-MSi2N4 nanosheets are wide-band-gap semiconductors and their energy band gaps span from visible to ultraviolet region of the optical spectrum, suitable for high-performance nanoelectronic device applications. Lastly, the analysis of optical properties shows that the designed systems have isotropic optical spectra, and depending on the type of the system, robust absorption of ultraviolet and visible light (particularly in 1H-PbSi2N4 monolayer) is predicted. Our study not only introduces new members to the family of 2D MA
2
Z
4 crystals but also unveils their intriguing physical properties and suggests them as promising candidates for diverse nanomechanical and optoelectronic applications.
Multimodality radiomics prediction of radiotherapy-induced the early proctitis and cystitis in rectal cancer patients: a machine learning study
Authors: Abbaspour Samira , Barahman Maedeh , Abdollahi Hamid , Arabalibeik Hossein , Hajainfar Ghasem , Babaei Mohammadreza , Iraji Hamed , Barzegartahamtan Mohammadreza , Ay Mohammad Reza , Mahdavi Seied Rabi 
Published: November 2023

Abstract

Purpose. This study aims to predict radiotherapy-induced rectal and bladder toxicity using computed tomography (CT) and magnetic resonance imaging (MRI) radiomics features in combination with clinical and dosimetric features in rectal cancer patients. Methods. A total of sixty-three patients with locally advanced rectal cancer who underwent three-dimensional conformal radiation therapy (3D-CRT) were included in this study. Radiomics features were extracted from the rectum and bladder walls in pretreatment CT and MR-T2W-weighted images. Feature selection was performed using various methods, including Least Absolute Shrinkage and Selection Operator (Lasso), Minimum Redundancy Maximum Relevance (MRMR), Chi-square (Chi2), Analysis of Variance (ANOVA), Recursive Feature Elimination (RFE), and SelectPercentile. Predictive modeling was carried out using machine learning algorithms, such as K-nearest neighbor (KNN), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), Gradient Boosting (XGB), and Linear Discriminant Analysis (LDA). The impact of the Laplacian of Gaussian (LoG) filter was investigated with sigma values ranging from 0.5 to 2. Model performance was evaluated in terms of the area under the receiver operating characteristic curve (AUC), accuracy, precision, sensitivity, and specificity. Results. A total of 479 radiomics features were extracted, and 59 features were selected. The pre-MRI T2W model exhibited the highest predictive performance with an AUC: 91.0/96.57%, accuracy: 90.38/96.92%, precision: 90.0/97.14%, sensitivity: 93.33/96.50%, and specificity: 88.09/97.14%. These results were achieved with both original image and LoG filter (sigma = 0.5–1.5) based on LDA/DT-RF classifiers for proctitis and cystitis, respectively. Furthermore, for the CT data, AUC: 90.71/96.0%, accuracy: 90.0/96.92%, precision: 88.14/97.14%, sensitivity: 93.0/96.0%, and specificity: 88.09/97.14% were acquired. The highest values were achieved using XGB/DT-XGB classifiers for proctitis and cystitis with LoG filter (sigma = 2)/LoG filter (sigma = 0.5–2), respectively. MRMR/RFE-Chi2 feature selection methods demonstrated the best performance for proctitis and cystitis in the pre-MRI T2W model. MRMR/MRMR-Lasso yielded the highest model performance for CT. Conclusion. Radiomics features extracted from pretreatment CT and MR images can effectively predict radiation-induced proctitis and cystitis. The study found that LDA, DT, RF, and XGB classifiers, combined with MRMR, RFE, Chi2, and Lasso feature selection algorithms, along with the LoG filter, offer strong predictive performance. With the inclusion of a larger training dataset, these models can be valuable tools for personalized radiotherapy decision-making.
Research on the path extraction method of shoe upper grinding based on 3D vision
Authors: Zhang Yuewei , Wei Honglei , Lv Yan 
Published: November 2023

Abstract
Shoe upper grinding is a crucial step in the shoe manufacturing process, impacting both the bonding quality between the sole and the upper and the overall appearance of the shoe. Presently, many shoe companies rely on manual or semi-automated grinding methods for shoe uppers, resulting in low production efficiency and subpar grinding quality. This study proposes a 3D vision-based shoe upper grinding path extraction method for guiding a robotic arm to polish the shoe upper and address this issue. Initially, the RGB-D camera was used to obtain the point cloud data of the shoe surface, which was then preprocessed using point cloud filtering, smoothing and registration methods. Second, by combining RGB images with 3D point clouds, we propose a point-cloud region of interest (ROI) extraction method based on RGB information to obtain the feature point cloud of the shoe upper grinding line. Finally, we slice the feature point cloud of the shoe upper grinding line, extract the grinding points using an intersection algorithm, and fit them with a non-uniform rational B-spline curve (NURBS) to obtain the shoe’s upper grinding path. The research demonstrates that this method can effectively extract the shoe upper grinding trajectory curve, significantly reduce the time required to obtain the shoe upper grinding trajectory, and achieve good accuracy, with promising application prospects.
Rights and Votes
Authors: Levinson Daryl J 
Published: November 2023

Abstract
This chapter considers how state power, once it has been built, can be controlled, focusing on the two primary tools designed for doing so. Particular uses of state power can be prohibited by legal restrictions to protect vulnerable subjects against abuse (“rights”). Alternatively, the users of state power can be selected or influenced through a system of politics that empowers vulnerable subjects to protect themselves (“votes”). This simple way of assimilating rights and votes will come as counterintuitive to constitutionalists, who are accustomed to viewing rights and democracy as opposing forces. Internationalists, in contrast, have been more inclined to see political power and legal protections as working in parallel. Constitutional law has much to learn from that perspective. Conceiving of rights and votes as comparable tools illuminates how both can be best used to regulate and guard against state power, from the inside as well as the outside.
Epistles
Authors: Morgan Llewelyn 
Published: November 2023

Abstract
This chapter discusses the relationship of these poetic letters to Horace’s earlier satires, and explains how they adopt a poetic style appropriate to the kind of conversation pursued in a letter, slightly more formal than the style of the conversational satires, but still self-consciously less than overtly poetic. This kinship to satire is complemented by similarities to the lyrics of the Odes, especially the element of life advice, in these poems typically directed at younger men rising through Roman society. Horace’s characterization of himself as a man retired from active life—and even from writing real poetry—reinforces that claim of philosophical value. Alongside the appealingly humane letters of book 1, the longer poems addressed to Augustus and Florus are discussed, and the Ars Poetica. The latter in particular has foxed scholars seeking to pin down its literary purpose, but like all Horace’s work Epistles is full of brilliantly formulated and highly memorable statements of ethical and aesthetic principle.
How big and small are big and small?
Authors: Close Frank 
Published: November 2023

Abstract
This chapter considers the size, temperature, and characteristics of matter. It mentions how quarks and electrons are too small for people to measure even if they have intrinsic sizes. Thus, instruments like telescopes and special microscopes can help extend people’s senses and reveal Nature over a vast range of distance scales. The chapter then discusses the correspondence between scales of temperature and energy in electronvolts (eV). It details how the universe expanded after the explosive eruption of the Big Bang, which correlates with the measure of the temperature of the universe as a function of time and the Higgs field filling and stabilizing the vacuum.
The forces of Nature
Authors: Close Frank 
Published: November 2023

Abstract
This chapter elaborates on the fundamental forces of Nature that rule the universe: gravity, electromagnetic force, and the relative strengths of strong and weak. Quantum theory implies that forces manage to spread their effects across space through the action of intermediate agents, such as the exchange of particles. Additionally, the relative strengths of the various forces when acting between fundamental particles at low energies are typical of room temperature and change radically at very high temperature and energies. The chapter considers the mathematical structures underpinning the gauge theory that describes electromagnetic, weak, and strong forces to be generalized straightforwardly. It cites the significance of the Higgs field in the formation of the structure after the Big Bang.
Questions for the post-Higgs era
Authors: Close Frank 
Published: November 2023

Abstract
This chapter examines the queries after the discovery of the Higgs field. The standard model of the fundamental particles and the forces that act among them explains mass by proposing that it is due to the Higgs field, which permeates all of space. Studying the Higgs boson with high precision is expected to unveil some deviations from theoretical expectations and thereby point the way to further progress. The chapter looks into electromagnetic radiation being outweighed by some mysterious dark matter that does not show up at any wavelength in telescopes. It also elaborates on the concept of supersymmetry and the possible role of massive neutrinos in solving the mystery of the missing antimatter.
A cross-sectional study on occupational exposure to microorganisms, endotoxin, hydrogen sulfide, and dust during work at drilling waste treatment plants
Authors: Daae Hanne Line , Graff Pål , Foss Oda Astrid Haarr , Kofoed Victor Carp , Afanou Anani Komlavi , Frederiksen Margit Wagtberg , Madsen Anne Mette 
Published: November 2023

Abstract
This cross-sectional study aims to obtain knowledge about workers’ exposure to airborne dust, bacterial and fungal species, endotoxin, biofilm formation, and hydrogen sulfide (H2S) in drilling waste treatment plants. In total, 408 full-shift personal samples, 66 work areas, 40 drilling waste, and reference (outdoor air and seawater) samples were analyzed. Some workers were exposed to high levels of endotoxin (207 EU/m3), bacteria (3.8 × 104 colony forming units (CFU)/m3 and 9.8 × 104 DNA copies/m3), or fungi (1.4 × 107 CFU/m3 and 3,600 copies/m3). The exposure levels to endotoxin, bacteria, and peaks of H2S were dependent on the treatment technique. All types of drilling waste contained large concentrations of bacteria compared to the seawater references. Elevated concentrations of airborne bacteria were found close to drilling waste basins. In total, 116, 146, and 112 different bacterial species were found in workers’ exposure, work areas, and the drilling waste, respectively. An overlap in bacterial species found in the drilling waste and air (personal and work area) samples was found. Of the bacterial species found, 49 are classified as human pathogens such as Escherichia coli, Enterobacter cloacae, and Klebsiella oxytoca. In total, 44 fungal species were found in the working environment, and 6 of these are classified as human pathogens such as Aspergillus fumigatus. In conclusion, across the drilling waste treatment plants, human pathogens were present in the drilling waste, and workers’ exposure was affected by the drilling waste treated at the plants with elevated exposure to endotoxin and bacteria. Elevated exposure was related to working as apprentices or chemical engineers, and working with cleaning, or slop water, and working in the daytime.
Adversarial training improves model interpretability in single-cell RNA-seq analysis
Authors: Sadria Mehrshad , Layton Anita , Bader Gary D 
Published: November 2023

AbstractMotivationPredictive computational models must be accurate, robust, and interpretable to be considered reliable in important areas such as biology and medicine. A sufficiently robust model should not have its output affected significantly by a slight change in the input. Also, these models should be able to explain how a decision is made to support user trust in the results. Efforts have been made to improve the robustness and interpretability of predictive computational models independently; however, the interaction of robustness and interpretability is poorly understood.ResultsAs an example task, we explore the computational prediction of cell type based on single-cell RNA-seq data and show that it can be made more robust by adversarially training a deep learning model. Surprisingly, we find this also leads to improved model interpretability, as measured by identifying genes important for classification using a range of standard interpretability methods. Our results suggest that adversarial training may be generally useful to improve deep learning robustness and interpretability and that it should be evaluated on a range of tasks.Availability and implementationOur Python implementation of all analysis in this publication can be found at: https://github.com/MehrshadSD/robustness-interpretability. The analysis was conducted using numPy 0.2.5, pandas 2.0.3, scanpy 1.9.3, tensorflow 2.10.0, matplotlib 3.7.1, seaborn 0.12.2, sklearn 1.1.1, shap 0.42.0, lime 0.2.0.1, matplotlib_venn 0.11.9.
AdmixPipe v3: facilitating population structure delimitation from SNP data
Authors: Mussmann Steven M , Douglas Marlis R , Chafin Tyler K , Douglas Michael E 
Published: November 2023

Abstract

Summary
Quantifying genetic clusters (=populations) from genotypic data is a fundamental, but non-trivial task for population geneticists that is compounded by: hierarchical population structure, diverse analytical methods, and complex software dependencies. AdmixPipe v3 ameliorates many of these issues in a single bioinformatic pipeline that facilitates all facets of population structure analysis by integrating outputs generated by several popular packages (i.e. CLUMPAK, EvalAdmix). The pipeline interfaces disparate software packages to parse Admixture outputs and conduct EvalAdmix analyses in the context of multimodal population structure results identified by CLUMPAK. We further streamline these tasks by packaging AdmixPipe v3 within a Docker container to create a standardized analytical environment that allows for complex analyses to be replicated by different researchers. This also grants operating system flexibility and mitigates complex software dependencies.

Availability and implementation
Source code, documentation, example files, and usage examples are freely available at https://github.com/stevemussmann/admixturePipeline. Installation is facilitated via Docker container available from https://hub.docker.com/r/mussmann/admixpipe. Usage under Windows operating systems requires the Windows Subsystem for Linux.