bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of 2D material anodes with different anions for lithium ion batteries: comparison of MoO2, MoS2 and MoSe2
Authors: Chen Tianrui 
Published: August 2022

Abstract
The energy storage devices used in today’s society are mainly lithium batteries. At present, the anode material of commercial lithium batteries is generally graphite. Although lithium battery has superior performance compared with other energy storage methods, it still has many problems, such as poor safety, low specific capacity, and slow charging speed. In recent years, although some researchers have proposed graphene as anode material, the results show that although graphene can partly alleviate the above problems, it cannot meet the needs of industrial and domestic applications. Therefore, we investigate the properties of MoO2, MoS2 and MoSe2 as battery anode materials. These three materials have good conductivity, and anions are the same main group. The effects of anionic electronegativity on battery performance can be compared and discussed. We obtain the binding energy, diffusion barrier, voltage, stable adsorption site and corresponding charge transfer of Li on the above three materials by first-principles calculations. We find that MoO2, MoS2 and MoSe2 have their own advantages and disadvantages as battery anode materials. MoO2 has the strongest binding capacity with lithium ion and the closest adsorption degree. MoS2 is slightly inferior and MoSe2 has the weakest binding capacity. This feature will lead to MoO2 having higher specific capacity and the ability to prevent lithium dendrite growth. However, considering the lower diffusion barrier, lithium ion in MoSe2 is easier to diffuse and the charging rate of the MoSe2 based lithium battery would be higher, while lithium ion in MoO2 is not easy to diffuse and the charging rate could be low. In general, the three anode can improve the battery performance in different aspects, and have a wide application prospect.
Numerical Investigation on the Atomization Characteristics of An Aerosol Spray Nozzle
Authors: Liu Liang , Wu Xingwei , Wang Dian , Yin Yue 
Published: August 2022

Abstract
Inlet air filtration of ships and coastal installations is mainly used to filter out salt aerosol particles, so researches on the inlet filter needs to simulate spray aerosol state in the marine environment. The sea salt aerosol particles have multiple sizes, thus salt aerosol generator should have the ability to produce salt aerosol particles of various diameters. This paper investigates the factors that affect the particle diameter of a salt aerosol generating device. Numerical simulations on the two-phase flow in a salt aerosol nozzle are conducted and the influence of air inlet pressure and droplet mass flow rate on the particle diameter is discovered. The results show that the particle diameter of the aerosol nozzle decreases with the air inlet pressure increasing and the droplet mass flow rate decreasing.
New beam position detectors for NA61/SHINE experiment
Authors: Balkova Y. , Urbaniak M. , Makhnev A. , Puławski S. , Kowalski S. , Kulawik J. , Guber F. , Serebryakov D. 
Published: August 2022

Abstract
NA61/SHINE is a multi-purpose fixed-target experiment located at the Super Proton Synchrotron at CERN. The main goals of the experiment include studies for physics of strong interactions, neutrino physics, and cosmic-rays physics. After the upgrade of the detector system, the experiment will collect data up to 1 kHz event rate. The development of new detectors, used to measure the positions of incoming beam particles in the transverse plane, is a crucial part of the upgrade. Two new kinds of beam position detectors are prepared and tested. One of them is the scintillating fiber detector with a multi-anode photomultiplier readout. It is built of two perpendicularly arranged ribbons, each consisting of two shifted layers of green-emitting scintillating fibers with a diameter of 250 μm. The second type of detector is based on single-sided silicon strip detector (Hamamatsu S13804). The paper gives an overview of both detectors’ design and readout concepts.
Overview on the progress of the conceptual studies of a gamma ray spectrometer instrument for DEMO
Authors: Giacomelli L. , Nocente M. , Perelli Cippo E. , Rebai M. , Rigamonti D. , Tardocchi M. , Cazzaniga C. , Cecconello M. , Conroy S. , Hjalmarsson A. , Ericsson G. , Franke T. , Biel W. 
Published: August 2022

Abstract
The future DEMO tokamak will be equipped with a suite of diagnostics which will operate as sensors to monitor and control the position and operation parameters of DT plasmas. Among the suite of sensors, an integrated neutron and gamma-ray diagnostic system is also studied to verify its capability and performance in detecting possible DEMO plasma position variations and contribute to the feedback system in maintaining DEMO DT plasma in stable conditions. This work describes the progress of the conceptual study of the gamma-ray diagnostic for DEMO reactor performed during the first Work-Package contract 2015–2020. The reaction of interest for this Gamma-Ray Spectrometer Instrument (GRSI) consists of D(T, γ)5He with the emission of 16.63 MeV γ rays. Due to DEMO tokamak design constraints, the gamma and neutron diagnostics are integrated, both featuring multi-line of sight (camera type), viewing DEMO plasma radially with vertical (12) and horizontal (13) viewing lines to diagnose the γ and neutron emission from the DT plasma poloidal section. The GRSI design is based on the investigation of the reaction cross sections, on the calculations performed with GENESIS and MCNP simulation codes and on the physics and geometry constrains of the integrated instrument. GRSI features long collimators which diameters are constrained by the neutron flux at the neutron detectors of the Radial Neutron Camera (RNC) system placed in front, which are key to control DEMO DT plasma position. For these reasons, only few GRSI parameters can be independently selected to optimize its performance. Among these, the choice of the collimator diameters at the back side of the neutron detector box up to the GRSI detector, the use of LiH neutron attenuators in front of the GRSI detectors, the GRSI detector material and shielding. The GRSI detector is based on commercial LaBr3(Ce) inorganic scintillating crystal coupled with a photomultiplier tube or a silicon photomultiplier. They are designed to operate at high count rate although GRSI geometry constraints severely impact on this feature. The GRSI can also provide an independent assessment of DEMO DT fusion power and T burning.
Flow-induced self-sustained oscillations in a straight channel with rigid walls and elastic supports
Authors: Alviso Dario , Sciamarella Denisse , Gronskis Alejandro , Artana Guillermo 
Published: August 2022

Abstract
This work considers the two-dimensional flow field of an incompressible viscous fluid in a parallel-sided channel. In our study, one of the walls is fixed whereas the other one is elastically mounted, and sustained oscillations are induced by the fluid motion. The flow that forces the wall movement is produced as a consequence that one of the ends of the channel is pressurized, whereas the opposite end is at atmospheric pressure. The study aims at reducing the complexity of models for several physiological systems in which fluid-structure interaction produces large deformation of the wall. We report the experimental results of the observed self-sustained oscillations. These oscillations occur at frequencies close to the natural frequency of the system. The vertical motion is accompanied by a slight trend to rotate the moving mass at intervals when the gap height is quite narrow. We propose a simplified analytical model to explore the conditions under which this motion is possible. The analytical approach considers asymptotic solutions of the Navier–Stokes equation with a perturbation technique. The comparison between the experimental pressure measured at the midlength of the channel and the analytical result issued with a model neglecting viscous effects shows a very good agreement. Also, the rotating trend of the moving wall can be explained in terms of the quadratic dependence of the pressure with the streamwise coordinate that is predicted by this simplified model.
Energy exchanges in a damped Langevin-like system with two thermal baths and an athermal reservoir
Authors: Nascimento E S , Morgado W A M 
Published: August 2022

Abstract
We study a Langevin-like model which describes an inertial particle in a one-dimensional harmonic potential and subjected to two heat baths and one athermal environment. The thermal noises are white and Gaussian, and the temperatures of heat reservoirs are different. The athermal medium act through an external non-Gaussian noise of Poisson type. We calculate exactly the time-dependent cumulant-generating function of position and velocity of the particle, as well as an expression of this generating function for stationary states. We discuss the long-time behavior of first cumulants of the energy injected by the athermal reservoir and the heat exchanged with thermal baths. In particular, we find that the covariance of stochastic heat due to distinct thermal reservoirs exhibits a complex dependence on properties of athermal noise.
An artificial pathway for trans-4-hydroxy-L-pipecolic acid production from L-lysine in Escherichia coli
Authors: Cheng Jie , Luo Zhou , Wang Bangxu , Yan Lixiu , Zhang Suyi , Zhang Jiamin , Lu Yao , Wang Wei 
Published: August 2022

ABSTRACT
Trans-4-hydroxy-L-pipecolic acid (trans-4-HyPip) is a hydroxylated product of L-pipecolic acid, which is widely used in the pharmaceutical and chemical industries. Here, a trans-4-HyPip biosynthesis module was designed and constructed in Escherichia coli by overexpressing lysine α-oxidase, Δ1-piperideine-2-carboxylase reductase, glucose dehydrogenase, lysine permease, catalase and L-pipecolic acid trans-4-hydroxylase for expanding the lysine catabolism pathway. A total of 4.89 g/L of trans-4-HyPip was generated in shake flasks from 8 g/L of L-pipecolic acid. By this approach, 14.86 g/L of trans-4-HyPip was produced from lysine after 48 h in a 5 L bioreactor. As far as we know, this is the first multi-enzyme cascade catalytic system for the production of trans-4-HyPip using E. coli from L-lysine. Therefore, it can be considered as a potential candidate for the industrial production of trans-4-HyPip in microorganisms.
Relationship between flavor compounds and changes of microbial community in the solid fermented vinegar
Authors: Zhang Xuelin , Zhang Xingrong , Yan Yongheng , Liu Yang , Zhao Xiangying , Xu Hui , He Lianzhi , Huang Yanhong 
Published: August 2022

ABSTRACT
The relationship between volatile compounds of vinegar and microorganisms is not clear, especially pyrazine, a trace component. In order to reveal their potential relationship, high throughput sequencing, solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) and Spearman's correlation analysis were used. Results showed that Acetobacter and Lactobacillus with opposite abundance trends were the predominant bacteria, and the total abundance of them exceeds 98%, while the predominant fungal genera were Aspergillus and Malassezia, their highest abundances are 75.4% and 81.5%, respectively. In the whole process of microbial community succession, 6 pyrazines were detected including trimethylpyrazine and tetramethylpyrazine, etc., and Spearman's correlation analysis showed that they were positively correlated with the presence of Vibrionimonas, Paraburkholderia, Paucibacter, Komagataeibacter, Acinetobacter, and Slinibacter. In general, this study further revealed more species related to pyrazines, it will be helpful to understand the formation of pyrazines and promote the improvement of vinegar quality.
A comparative analysis of amino acid encoding schemes for the prediction of flexible length linear B-cell epitopes
Authors: Sahu Tanmaya Kumar , Meher Prabina Kumar , Choudhury Nalini Kanta , Rao Atmakuri Ramakrishna 
Published: August 2022

Abstract
Linear B-cell epitopes have a prominent role in the development of peptide-based vaccines and disease diagnosis. High variability in the length of these epitopes is a major reason for low accuracy in their prediction. Most of the B-cell epitope prediction methods considered fixed length of epitope sequences and achieved good accuracy. Though a number of tools are available for the prediction of flexible length linear B-cell epitopes with reasonable accuracy, further improvement in the prediction performance is still expected. Thus, here we made an attempt to analyze the performance of machine learning approaches (MLA) with 18 different amino acid encoding schemes in the prediction of flexible length linear B-cell epitopes. We considered B-cell epitope sequences of variable lengths (11–56 amino acids) from well-established public resources. The performances of machine learning algorithms with the encoded epitope sequence datasets were evaluated. Besides, the feasible combinations of encoding schemes were also explored and analyzed. The results revealed that amino-acid composition (AC) and distribution component of composition–transition–distribution encoding schemes are suitable for heterogeneous epitope data, whereas amino-acid-anchoring-pair-composition (APC), dipeptide-composition and amino-acids-pair-propensity-scale (APP) are more appropriate for homogeneous data. Further, two combinations of peptide encoding schemes, i.e. APC + AC and APC + APP with random forest classifier were identified to have improved performance over the state-of-the-art tools for flexible length linear B-cell epitope prediction. The study also revealed better performance of random forest over other considered MLAs in the prediction of flexible length linear B-cell epitopes.
ANCA-associated vasculitis flare might be provoked by COVID-19 infection: a case report and a review of the literature
Authors: Ozcan Seyda , Sonmez Ozge , Karaca Cebrail , Ozdede Ayse , Seyahi Nurhan 
Published: August 2022

ABSTRACTMesangial immunoglobulin A (IgA) deposition is the hallmark of IgA nephropathy (IgAN). In some cases, crescentic involvement that might be associated with systemic leucocytoclastic vasculitis is documented. In such cases, the disease is called Henoch–Schönlein purpura (IgA vasculitis). Even more rarely, the coexistence of IgAN and anti-neutrophil cytoplasmic antibody (ANCA) seropositivity has been reported.IgAN might be complicated by acute kidney injury (AKI) due to different causes. Herein we present a patient with mesangial IgA deposition and ANCA seropositivity who developed AKI, haematuria and haemoptysis during the course of coronavirus disease 2019 (COVID-19) disease and was diagnosed with ANCA-associated vasculitis based on clinical, laboratory and radiological findings. The patient was treated successfully with immunosuppressive therapy. We also made a systematic review of the literature to reveal and present the cases with COVID-19 and ANCA-associated vasculitis.
Comparison of the profiles of patients defined by age-adapted and fixed threshold CKD criteria: a nationwide, cross-sectional study
Authors: Ma Yixin , Lin Jianfeng , Xia Peng , Zheng Hua , Cheng Xinqi , Ji Peili , Wu Wei , Hou Lian , Wang Li , Zhu Guangjin , Qiu Ling , Zheng Yali , Chen Limeng 
Published: August 2022

ABSTRACT

Background
Kidney function declines naturally with advancing age. Therefore an age-adapted estimated glomerular filtration rate (eGFR) threshold has been proposed instead of the fixed threshold for CKD definition. This study aims to describe and compare the profile of CKD patients defined by these two criteria in a Chinese population.

Method
We recruited adult participants with selected biochemical tests from the Chinese Physiological Constant and Health Condition survey conducted from 2007 to 2011, with the GFR estimated by the Chronic Kidney Disease Epidemiology Collaboration formula. The age-adapted threshold of eGFR is 75, 60 and 45 ml/min/1.73 m2 for the population &lt;40 years of age, 40–64 years and &gt;64 years, respectively. The fixed threshold is 60 ml/min/1.73 m2 for all ages.

Results
Among the recruited 23 438 participants, 480 were diagnosed with CKD by fixed threshold criteria, while 391 were diagnosed with CKD by age-adapted criteria. Patients diagnosed by fixed threshold criteria were significantly older (66.4 versus 43.4 years; P &lt; .001) and had a higher prevalence of all CVD risk factors compared with the non-CKD population. In contrast, age-adapted criteria defined a younger patient group and were not significantly associated with diabetes or obesity. When adjusted by age and gender, fixed threshold–defined CKD was not significantly associated with the number of coexisting CVD risk factors, while age-adapted-defined CKD was significantly associated. We also found that the CKD patients defined by age-adapted criteria matched well with the 2.5th percentile of eGFR in Chinese individuals. When compared with their age- and gender-matched controls, patients included by age-adapted criteria but excluded by fixed threshold criteria had a significantly higher prevalence of hypertension (23.2% versus 7.7%; P &lt; .001) and hyperuricaemia (25.0% versus 5.5%; P &lt; .001), while patients included only by the fixed threshold criteria were not significantly different in the prevalence of CVD risk factors and CKD-related disturbance except for hyperuricaemia (41.2% versus 14.0%; P &lt; .001).

Conclusion
An age-adapted criterion is more closely associated with CVD risk factors and CKD-related diseases compared with fixed threshold criteria.
Myocardial fibrosis detection using kernel methods: preliminary results from a cardiac magnetic resonance study
Authors: Campese S , Agostini F , Sciarretta T , Pizzi M , Cipriani A , Zanetti M 
Published: August 2022

Abstract

Funding Acknowledgements
Type of funding sources: None.

Background
Asserting the presence of myocardial fibrosis from cardiac magnetic resonance (CMR) images is sometimes a complex task, even for experienced cardiac imagers. The application of artificial intelligence models to the evaluation process can be of help for enhancing diagnostic accuracy.

Purpose
In this work, we tested two different Machine Learning (ML) algorithms, namely kernel methods with Support Vector Machine (SVM) and Convolutional Neural Network (CNN) to a cohort of consecutive CMR studies. The goal was a binary classification task, aimed to identify myocardial scar (present/absent).

Methods
Dataset consisted of 642 CMR scans, equally divided into healthy and fibrosis-affected. Raw DICOM files were preprocessed through an automated pipeline, in order to retrieve only short-axis post contrast acquisitions. Heart regions were then individuated using a YOLO network, in order to remove the background and focus only on data of interest. Finally, for each subject 10 slices were extracted through interpolation, and all images resized to 128 by 128 pixels. Dataset was divided into training and test sets, with proportions 80%-20%.

Results
The first analysis was based on state-of-the-art CNN models, pre-trained on the ImageNet dataset. The training of the models was optimized using "reduce learning rate on the plateau", "early stopping", and standard data augmentation techniques. Experiments showed that CNNs-based models led to poor performances.
The second attempt was based on kernel methods and SVM. Before feeding the input to the algorithm, dimensionality reduction was implemented using a Principal Component Analysis retaining 99% of the variance. The resulting 335 features were passed as input to an SVM, testing different kernels (e.g. Linear, Gaussian, Cossim). Models were trained and optimized using a Grid Search with a 5-fold Cross-Validation. The best SVM configuration displayed an accuracy of 68% and a sensitivity of 60%.
Improved results could be obtained using state-of-the-art Multiple Kernel Learning algorithms, leading to 71% accuracy and sensitivity of 72% (with a 12% increment with respect to the previous algorithm).

Conclusions
Our preliminary results of this study showed the possibility for a ML system to learn to identify myocardial fibrosis, directly from raw CMR images. In particular, kernel methods were able to achieve good and significant results, even with small amounts of data, suggesting room for improvement. In future works, we plan to furtherly explore kernel methods to improve the results and to build an end-to-end solution for cardiac imagers.
Preliminary data on a fully automated left ventricular late gadolinium enhancement detection by a convolutional neuronal network in chronic myocardial infarction
Authors: Schwab M , Pamminger M , Kremser C , Obmann D , Haltmeier M , Mayr A 
Published: August 2022

Abstract

Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): FWF- Der Wissenschaftsfonds

Aim
To compare a fully automated segmentation of left ventricular late gadolinium enhancement (LGE) as evaluated by a convolutional neuronal network (CNN) with manual segmentation in chronic myocardial infarction.

Methods
Cardiac magnetic resonance imaging including two-dimensional LGE imaging was performed in 191 patients on a 1.5 T clinical scanner 12 months after ST-elevation myocardial infarction. LGE images were presented to a trained CNN for automated determination of left ventricular myocardium and consequently absolute LGE volume. Manual LGE segmentation according to the +5-SD method was used as reference standard. Image quality was assessed according to a 3-point Likert scale (2 = perfect image quality, 1 = some artifacts witout impaired LGE delineation, 0 = strong artifacts with impaired LGE delineation). Regression and Bland-Altman analysis were performed.

Results
In 191 included patients (182 male, mean age 57 years) LGE volume was 9.7 [IQR 3.6 to 16.2] ml according to manual segmentation and 8.3 [3.2 to 17.6] ml according to CNN segmentation. Bland-Altman analysis showed little average difference (-0.5 ml, p=0.257), however, limits of agreement ranged from -18.4 ml to 17.5 ml. Linear correlation was fair (0.57, p&lt;0.001). Subgroup analysis according to image quality showed comparable performance of CNN segmentation in all three groups.

Conclusion
Our fully automated LGE segmentation based on a CNN in two-dimensional data sets provides measurements with little average difference compared to very time-consuming manual segmentations. However, dispersion is substantially and limits the current application of this approach on a per-patient basis. Image quality does not affect CNN performance.