bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atomic simulation for the effect of nano-cutting parameters on the 3D surface morphology of polycrystalline γ-TiAl alloy
Authors: Guo Zhaoting , Cao Hui , Fu Rong , Yu Zhaoliang , Zhou Baocheng , Li Haiyan , Liu Jianhui , Feng Ruicheng 
Published: July 2023

Abstract

γ-TiAl alloy is one of the most potentially lightweight and high-temperature structural materials, and its machined surface quality has a significant effect on member service performance. Despite the extensive research on plastic removal and defect evolution under different cutting parameters, the forming mechanism of surface topography is not perfect under different cutting parameters. It is necessary to study the variation law of surface topography under the influence of different cutting parameters from the atomic scale. To this end, the influence of cutting depths and cutting speeds on the machined surface topography is investigated during nano-cutting of polycrystalline γ-TiAl alloys based on molecular dynamics simulation methods, and the effect of defective grain boundaries on cutting force fluctuations is analyzed. The results show that the effect of grain boundary on material deformation and dislocation obstruction is the main reason for the peak cutting force; with the increase of cutting depth, the average cutting force and friction coefficient increase, and both Sa and Sq show an increasing trend, which is the result of the joint action of plowing effect and grain boundary distribution; Sa and Sq show a decreasing and then increasing trend with the increase of cutting speed, and the critical cutting speed is 200 m s−1. This indicates that a smaller cutting depth and an appropriately higher cutting speed can effectively improve the surface quality of the polycrystalline γ-TiAl alloy, and optimize its nano-cutting process.
Theoretical study on the interaction between acetone and BN monolayer doped with Ni for the clinical diagnosis of diabetes mellitus
Authors: Cao Zhengqin , Jing Renjun , Ma Shouxiao , Wang Jia , Hu Gang , Wei Gang , Luo Qiming 
Published: July 2023

Abstract
Endogenous volatile organic compounds (VOCs) in human exhaled gases can reflect human health status and be used for clinical diagnosis and health monitoring. Acetone is the sign VOC gases of diabetes mellitus. In order to find a potential material for the detection of acetone in the application of the clinical diagnosis of diabetes mellitus. The adsorption properties, including adsorption energy, adsorption distance, charge transfer, density of states, electron localization function and electrons density difference, of acetone on BN monolayer doped with Ni were comprehensively investigated based on density functional theory. The results show that there could be chemisorption between acetone and Ni-BN monolayer and Ni-BN monolayer is probably suitable gas sensitive material for the detection of acetone in the application of diabetes mellitus monitoring and clinical diagnosis.
Reduction of the external resonant magnetic perturbation threshold for 2/1 locked mode excitation by the pre-excited mode on J-TEXT
Authors: Zhang Qi , Wang Nengchao , Huang Zhuo , Mao Feiyue , He Ying , Ren Zhengkang , Li Da , Yang Zhoujun , Chen Zhipeng , Chen Zhongyong , Ding Yonghua , Wang Lu , Zhuang Ge , Pan Yuan 
Published: July 2023

Abstract
A significant reduction of the external resonant magnetic perturbation (RMP) required for exciting the locked mode (LM) has been observed experimentally due to the presence of an existing LM on J-TEXT. In a plasma with edge safety factor q
a slightly smaller than 3, 3/1 and 2/1 modes are observed to be destabilized successively by a rotating RMP field. The 3/1 mode is excited first and identified as an external kink mode, whose excitation threshold decreases with the operating q
a increasing from 2.67 to 2.8 with the absence of a 3/1 rational surface. Shortly after excitation of the 3/1 external kink mode, 2/1 field penetration occurs and the 2/1 mode is excited, as identified by the phase between the 2/1 magnetic response and the RMP field jumping by π. The 2/1 mode is excited with a dominant kink structure and then converts into tearing mode for a duration of several milliseconds. During the excitation of the 2/1 mode, the phase difference between the 2/1 and 3/1 modes evolves from π to around 0 and the 2/1 mode amplitude grows to a saturation value comparable with that of the 3/1 mode. The presence of the 3/1 mode leads to a remarkable reduction of the external RMP current required for the 2/1 mode excitation, which can be explained by the contribution of a 2/1 resonant field from the 3/1 mode via the toroidal coupling effect. The larger 3/1 mode amplitude can lead to a greater reduction. This work reveals that the mode can be excited more easily with a reduced amplitude of RMP or error field due to the impact of the pre-existing mode and this might be a new consideration for error field correlation predictions and active magnetohydrodynamics control actuator designs.
Strong–laser–field physics, non–classical light states and quantum information science
Authors: Bhattacharya U , Lamprou Th , Maxwell A S , Ordóñez A , Pisanty E , Rivera-Dean J , Stammer P , Ciappina M F , Lewenstein M , Tzallas P 
Published: July 2023

Abstract
Strong–laser–field physics is a research direction that relies on the use of high-power lasers and has led to fascinating achievements ranging from relativistic particle acceleration to attosecond science. On the other hand, quantum optics has been built on the use of low photon number sources and has opened the way for groundbreaking discoveries in quantum technology, advancing investigations ranging from fundamental tests of quantum theory to quantum information processing. Despite the tremendous progress, until recently these directions have remained disconnected. This is because the majority of the interactions in the strong-field limit have been successfully described by semi-classical approximations treating the electromagnetic field classically, as there was no need to include the quantum properties of the field to explain the observations. The link between strong–laser–field physics, quantum optics, and quantum information science has been developed in the recent past. Studies based on fully quantized and conditioning approaches have shown that intense laser–matter interactions can be used for the generation of controllable entangled and non-classical light states. These achievements open the way for a vast number of investigations stemming from the symbiosis of strong–laser–field physics, quantum optics, and quantum information science. Here, after an introduction to the fundamentals of these research directions, we report on the recent progress in the fully quantized description of intense laser–matter interaction and the methods that have been developed for the generation of non-classical light states and entangled states. Also, we discuss the future directions of non-classical light engineering using strong laser fields, and the potential applications in ultrafast and quantum information science.
Hydrogen bonds determine the nonbonding adhesion at HMX-based PBX interface
Authors: Zhang Xinke , Li Shuang , Kang Jun , Su Jiaye , Deng Kaiming 
Published: July 2023

Abstract
Polymer bonded explosives (PBXs) are kind of composite materials consisting of multi-layers structures, where the interfacial interactions can significantly affect their structures, properties and performance. To investigate the determinant factors affecting the interfacial interactions, in this work, the adhesion works at different interfaces are studied by molecular dynamics simulations. A key observation is that the hydrogen bonds are found to be a decisive factor that directly affects the interfacial interactions. When the fluoropolymers change from F2321 to F2319, the adhesion works with the HMX and coupling agent layer present a monotonous decrease and increase, respectively, corresponding to the changes in the number of weak hydrogen bonds. Thus the hydrogen bonds can be utilized to benchmark the nonvalent interfacial interactions. Moreover, the coupling agent layer as an intermediary enhances the adsorption between the explosive crystal and the binder, whose thickness significantly impacts the interfacial interactions. Its interactions with the HMX and fluoropolymers both show a similar increase with respect to its thickness and then stabilize at the thickness above 2.5 nm, corresponding to a surface density of six KH550 chains per nm2. This study provides a basic understanding of the nonbonding adhesion mechanisms in the PBXs and is helpful for the material selection and structure design.
Effect of amphiphilic polymers and sodium alginate on the activity of methylene blue in photogeneration of singlet oxygen 1О2
Authors: Kuryanova A S , Kardumyan V V , Kaplin V S , Aksenova N A , Chernyak A V , Timofeeva V A , Glagolev N N , Timashev P S , Solovieva A B 
Published: July 2023

Abstract
The influence of amphiphilic polymers (APs): poly-N-vinylpyrrolidone, polyethylene glycol and pluronics F127, F108, as well as sodium alginate (SA) on the activity of methylene blue (MB) in the photogeneration of singlet oxygen 1О2, specifically, in a model photooxidation reaction of tryptophan in water was studied. It was shown that in the presence of all the above-mentioned AP, an increase in the effective rate constant (k
eff) of tryptophan photooxidation is observed. It was suggested that the observed effect is associated with the interaction of MB with APs, which leads to disaggregation of dye associates. Such disaggregation leads to an increase in the optical density and intensity of MB luminescence. It was also shown that the photocatalytic activity of MB decreases by a factor of 1.5–3.5 in the presence of SA, which is due to the ionic interaction of the cationic MB with polyanionic SA. The interaction of MB with polysaccharide is confirmed by changes in the absorption and fluorescence spectra of the dye. The introduction of APs into a solution containing MB and SA prevents the interaction between MB and polysaccharide, which leads to an increase in the k
eff values of tryptophan photooxidation in the presence of MB-AP-SA system, as well as to an increase in the optical density and fluorescence intensity of MB when AP and SA are added. The existence of weak interactions between the hydrophobic groups of MB molecules and the AP (polyvinylpyrrolidone) is also evidenced by the data obtained through 1H-NMR spectroscopy and the degree of MB fluorescence anisotropy. The AFM method shows the change in the surface structure of a thin film obtained by evaporating an aqueous solution of MB-F108-SA compared to the corresponding structure of a film obtained by evaporating an aqueous solution of MB-SA. MB-AP and MB-AP-SA systems may be promising for practical application in the aPDT treatment of chronic microbial superficial infections.
Heavy ion fusion of spherical nuclei
Authors: Manjunatha H.C. , Sowmya N. , Seenappa L. , Damodara Gupta P.S. , Manjunatha N. 
Published: July 2023

Abstract
We study the experimental and theoretical fusion reactions of compound nuclei synthesized using different projectile-target systems, among which at least one projectile/target nucleus is spherical. The first part of this study analyses the fusion cross sections obtained using different projectile-target combinations in the synthesis of polonium (Po), thorium (Th), and nobelium (No). In the second part of this study, we suggest the fusion reaction to synthesize the superheavy element Z = 122. We select three nuclei, polonium (Po), thorium (Th), and nobelium (No), which are synthesized using various projectile-target combinations. We also investigate fusion reactions such as

Zr(

Pb, 2n)

122 . This study may be a milestone in the synthesis of the superheavy element Z = 122.
Predictive SOLPS-ITER simulations to study the role of divertor magnetic geometry in detachment control in the MAST-U Super-X configuration
Authors: Myatra O. , Lipschultz B. , Moulton D. , Verhaegh K. , Dudson B. , Orchard S. , Fil A. , Cowley C. 
Published: July 2023

Abstract
The SOLPS-ITER code has been utilised to study the movement of the detachment front location from target towards the X-point for MAST-U Super-X plasmas. Two sets of detached steady state solutions are obtained by either varying the deuterium (D
2) fuelling rate or the nitrogen (N) seeding rate to scan the corresponding ‘control’ parameters of outboard midplane density,

n

u

, and the divertor impurity concentration,

f

I

. At seeding and fuelling rates ∼10× and ∼5× that required to start detachment at the divertor target, the detachment front only reaches ∼50% of the poloidal distance to the X-point,

l

p
o
l

, corresponding to a region of strong parallel gradients in the total magnetic field B. The region of strong total field gradients correlates with where the detachment front location becomes less sensitive to control parameter variation. This result is qualitatively consistent with the predictions of a simple, analytic detachment location sensitivity (DLS) model (Lipschultz et al 2016 Nucl. Fusion
56 056007) which is based in a scaled parallel-to-B space, z. While the DLS model predictions are in agreement with SOLPS-ITER results in terms of where the front location becomes less sensitive to controls (i.e. in the region of strong parallel gradients in B), the DLS model predicts a higher sensitivity in the region of weak parallel gradients in B downstream as compared to the simulation results. Potential sources of differences between the SOLPS-ITER and DLS model predictions were explored: The DLS model does not include energy sinks beyond radiation from a single impurity nor cross-field energy transport. Momentum and particle balance are also not included in the DLS model. The tight opening into the divertor for flux surfaces could lead to variations in plasma-neutral pressure balance as the detachment front reaches that region, exactly how this affects the front movement needs further investigation.
Housing market dynamics of the post-Sandy Hudson estuary, Long Island Sound, and New Jersey coastline are explained by NFIP participation
Authors: Poudel Sandeep , Caridad Conner , Elliott Rebecca , Knighton James 
Published: July 2023

Abstract
How flooding affects home values can determine the path of economic recovery for communities and have lasting impacts on national and global financial systems. Yet, our understanding of how flood insurance, community risk perception, and past flooding events shape future housing prices (HPs) remains limited. To explore this, we used a socio-environmental (SE) model and studied the temporal impacts of flooding on mean housing values across 496 coastal census tracts of New York, Connecticut, and New Jersey, US, from 1970 to 2021. The modeling exercise demonstrated that the initial economic impact of Hurricane Sandy was largely absorbed by the National Flood Insurance Program (NFIP); however, the region then exhibited a long-term decline in home values, which was well described by an interrupted time series model. We found significant correlations between SE model parameters describing HP change and those describing tract-scale behaviors and perceptions, suggesting that the salience of past flooding events and NFIP participation may be important regional drivers of HPs. Tracts with greater post-flood change in active insurance policies exhibited larger decreases in mean home values than those with more stable NFIP participation. An improved understanding of relationships between HPs, flood insurance, and community perceptions could support more equitable distributions of resources and improved policy interventions to reduce flooding risk.
Generation of synthetic CT from CBCT using deep learning approaches for head and neck cancer patients
Authors: Aouadi Souha , Yoganathan SA , Torfeh Tarraf , Paloor Satheesh , Caparrotti Palmira , Hammoud Rabih , Al-Hammadi Noora 
Published: July 2023

Abstract

Purpose. To create a synthetic CT (sCT) from daily CBCT using either deep residual U-Net (DRUnet), or conditional generative adversarial network (cGAN) for adaptive radiotherapy planning (ART). Methods. First fraction CBCT and planning CT (pCT) were collected from 93 Head and Neck patients who underwent external beam radiotherapy. The dataset was divided into training, validation, and test sets of 58, 10 and 25 patients respectively. Three methods were used to generate sCT, 1. Nonlocal means patch based method was modified to include multiscale patches defining the multiscale patch based method (MPBM), 2. An encoder decoder 2D Unet with imbricated deep residual units was implemented, 3. DRUnet was integrated to the generator part of cGAN whereas a convolutional PatchGAN classifier was used as the discriminator. The accuracy of sCT was evaluated geometrically using Mean Absolute Error (MAE). Clinical Volumetric Modulated Arc Therapy (VMAT) plans were copied from pCT to registered CBCT and sCT and dosimetric analysis was performed by comparing Dose Volume Histogram (DVH) parameters of planning target volumes (PTVs) and organs at risk (OARs). Furthermore, 3D Gamma analysis (2%/2mm, global) between the dose on the sCT or CBCT and that on the pCT was performed. Results. The average MAE calculated between pCT and CBCT was 180.82 ± 27.37HU. Overall, all approaches significantly reduced the uncertainties in CBCT. Deep learning approaches outperformed patch-based methods with MAE = 67.88 ± 8.39HU (DRUnet) and MAE = 72.52 ± 8.43HU (cGAN) compared to MAE = 90.69 ± 14.3HU (MPBM). The percentages of DVH metric deviations were below 0.55% for PTVs and 1.17% for OARs using DRUnet. The average Gamma pass rate was 99.45 ± 1.86% for sCT generated using DRUnet. Conclusion. DL approaches outperformed MPBM. Specifically, DRUnet could be used for the generation of sCT with accurate intensities and realistic description of patient anatomy. This could be beneficial for CBCT based ART.
On the effect of the poisson’s ratio on samples subjected to shearing
Authors: Attard Daphne , Caruana-Gauci Roberto , Cerasola Dario , Grima-Cornish James N , Bezzina Daniel S , Ficarra Giovanni , Grima Joseph N 
Published: July 2023

Abstract
The effect of shearing on finite-sized auxetic and non-auxetic samples was examined through finite element simulations. It was shown that when shear was applied in a manner representative of a common shear-testing setup, which is not dissimilar to the situation encountered in sports applications, auxetics manifested very different characteristics compared to their non-auxetic counterparts; with very pronounced edge effects. These included extensive lateral expansion of the samples and the formation of non-insignificant concave creases on their exposed lateral faces. It was shown that these creases became even more pronounced when the samples were subjected to combined shear and compressive loads and need to be taken into consideration when assessing the suitability, or otherwise, of auxetics for practical applications where shear loading may be present to a certain extent.
Prior information-assisted integrative analysis of multiple datasets
Authors: Wang Feifei , Liang Dongzuo , Li Yang , Ma Shuangge 
Published: July 2023

Abstract

Motivation
Analyzing genetic data to identify markers and construct predictive models is of great interest in biomedical research. However, limited by cost and sample availability, genetic studies often suffer from the “small sample size, high dimensionality” problem. To tackle this problem, an integrative analysis that collectively analyzes multiple datasets with compatible designs is often conducted. For regularizing estimation and selecting relevant variables, penalization and other regularization techniques are routinely adopted. “Blindly” searching over a vast number of variables may not be efficient.

Results
We propose incorporating prior information to assist integrative analysis of multiple genetic datasets. To obtain accurate prior information, we adopt a convolutional neural network with an active learning strategy to label textual information from previous studies. Then the extracted prior information is incorporated using a group LASSO-based technique. We conducted a series of simulation studies that demonstrated the satisfactory performance of the proposed method. Finally, data on skin cutaneous melanoma are analyzed to establish practical utility.

Availability and implementation
Code is available at https://github.com/ldz7/PAIA. The data that support the findings in this article are openly available in TCGA (The Cancer Genome Atlas) at https://portal.gdc.cancer.gov/.
ipaPy2: Integrated Probabilistic Annotation (IPA) 2.0—an improved Bayesian-based method for the annotation of LC–MS/MS untargeted metabolomics data
Authors: Del Carratore Francesco , Eagles William , Borka Juraj , Breitling Rainer 
Published: July 2023

Abstract

Summary
The Integrated Probabilistic Annotation (IPA) is an automated annotation method for LC–MS-based untargeted metabolomics experiments that provides statistically rigorous estimates of the probabilities associated with each annotation. Here, we introduce ipaPy2, a substantially improved and completely refactored Python implementation of the IPA method. The revised method is now able to integrate tandem MS fragmentation data, which increases the accuracy of the identifications. Moreover, ipaPy2 provides a much more user-friendly interface, and isotope peaks are no longer treated as individual features but integrated into isotope fingerprints, greatly speeding up the calculations. The method has also been fully integrated with the mzMatch pipeline, so that the results of the annotation can be explored through the newly developed PeakMLViewerPy tool available at https://github.com/UoMMIB/PeakMLViewerPy.

Availability and implementation
The source code, extensive documentation, and tutorials are freely available on GitHub at https://github.com/francescodc87/ipaPy2
CSI: Contrastive data Stratification for Interaction prediction and its application to compound–protein interaction prediction
Authors: Kalia Apurva , Krishnan Dilip , Hassoun Soha 
Published: July 2023

Abstract

Motivation
Accurately predicting the likelihood of interaction between two objects (compound–protein sequence, user–item, author–paper, etc.) is a fundamental problem in Computer Science. Current deep-learning models rely on learning accurate representations of the interacting objects. Importantly, relationships between the interacting objects, or features of the interaction, offer an opportunity to partition the data to create multi-views of the interacting objects. The resulting congruent and non-congruent views can then be exploited via contrastive learning techniques to learn enhanced representations of the objects.

Results
We present a novel method, Contrastive Stratification for Interaction Prediction (CSI), to stratify (partition) a dataset in a manner that can be exploited via Contrastive Multiview Coding to learn embeddings that maximize the mutual information across congruent data views. CSI assigns a key and multiple views to each data point, where data partitions under a particular key form congruent views of the data. We showcase the effectiveness of CSI by applying it to the compound–protein sequence interaction prediction problem, a pressing problem whose solution promises to expedite drug delivery (drug–protein interaction prediction), metabolic engineering, and synthetic biology (compound–enzyme interaction prediction) applications. Comparing CSI with a baseline model that does not utilize data stratification and contrastive learning, and show gains in average precision ranging from 13.7% to 39% using compounds and sequences as keys across multiple drug–target and enzymatic datasets, and gains ranging from 16.9% to 63% using reaction features as keys across enzymatic datasets.

Availability and implementation
Code and dataset available at https://github.com/HassounLab/CSI.