bluuebunny/crossref_metadata_2025 huggingface dataset:
Ti-doping of hematite films with multilayered particle size distribution by magnetron sputtering
Authors: Demirov A P , Sergevnin V S , Volkhonskii A O
Published: June 2021

α-Fe2O3 films with a layered distribution of nano and submicron particles were synthesized and Ti-doped successfully. Morphology, element and phase composition, electrochemical properties of one-layered, multilayered, and Ti-doped films were investigated. Doped multilayered hematite films have higher catalytic water oxidation efficiency than both undoped films.
Si-containing diamond-like carbon coatings to improve the wear resistance of solid ceramic end mills
Authors: Grigoriev S N , Volosova M A , Fyodorov S V , Mustafaev E S
Published: June 2021

The study’s purpose is to determine the rational Si content in the DLC-Si external layer of (CrAlSi)N/DLC-Si coatings deposited on α/β-SiAlON + TiN ceramics. The influence of Si content on physical and mechanical properties of coatings such as microhardness, modulus of elasticity, and friction coefficient, and wear resistance of solid ceramic end mills in machining nickel alloy NiCr20TiAl is determined.
Study of the adhesion of metal coatings on synthetic textile materials
Authors: Karnoukhov A E , Timoshina Y A , Voznesensky E F , Sysoev V A , Krasina I V , Tikhonova N V
Published: June 2021

This paper is devoted to the study of the adhesion of metal coatings on synthetic textile materials based on polyester, polyamide and polypropylene. The metal coating was applied to the surface of textile materials by magnetron sputtering. To assess the adhesion of the metal coating to the substrate, the method of delamination testing using a tape with constant stickiness was used.
Electro-physical properties of porous anodic alumina films for sensitive elements of MEMS
Authors: Korobova N E , Batalova M S , Alpysbayeva B E
Published: June 2021

The results of a comprehensive study of porous alumina film electrical properties obtained by anodizing in acid electrolytes have been presented. The relationship was established between the structure of oxide films, the mechanism of their formation, as well as physicochemical characteristics. A targeted effect on the microstructure of the films made it possible to control their properties by varying the technological parameters without a radical change in the method. This made it possible to predict the behavior of nanostructures and properties for sensitive MEMS elements.
Hydrophilization of the polyethyleneterephthalate ion track membrane surfaces
Authors: Melnikova G B , Salamianski A E , Korolkov I V , Tolstaya T N , Akulova V M , Chizhik S A , Zdorovets M V , Muslimova I B , Kotov D V
Published: June 2021

Results of polyethylenterephtalate ion track membranes hydrophilization by (Chytozan/Dextran)4 multilayers with using Layer-by-Layer method and by Nafion monolayer with using Langmuir – Blodgett and spin-coating methods are presented in articles. The structure, contact angles and polar component of specific surface energy of modified membranes has been researched.
Pulsed methods of thin film coatings deposition
Authors: Panfilov Y V , Gurov A V
Published: June 2021

The most known methods of pulsed thin film deposition such as magnetron sputtering HIPIMS, pulsed laser deposition PLD, vacuum arc pulsed deposition, high-intensity pulsed ion beams deposition HIPIB, as well, were described and analysed. It was shown that the stream of material, generated by means of a pulsed action, impacts to substrate and creates preconditions for nanocrystalline amorphous coating manufacture with superhigh hardness.
Electrochemical stability of nitride coatings for a steel – carbon fiber tribopair under conditions of imitation of a marine environment
Authors: Sergevnin V S , Anisimov A V , Chernogor A V , Voklhonskii A O , Demirov A P , Lishevich I V , Sobolev M Yu , Kayamutdinov Sh D
Published: June 2021

The paper presents the results of comparative studies of TiCrNiN and TiCrMoNiN coatings deposited on X20Cr13 steel used in the manufacture of bearings for friction units of ship mechanisms operating in a friction pair with carbon fiber reinforced plastic. Using of the investigated coatings significantly improves the resistance of the product to corrosion in seawater.
Deposition of AlMgB14 films by sputtering in a non-self-sustained high-frequency discharge
Authors: Shugurov V V , Akhmadeev Yu H , Zhukov I A , Nikitin P Yu
Published: June 2021

The paper presents the method of plasma-assisted deposition of AlMgB14 films in a discharge system that consisted of a large volume gas plasma generator with a thermionic and a hollow cathode. An electrode with a BAM powder was placed in plasma. High-frequency voltage of 13.56 MHz was applied to the electrode with a BAM powder. In contrast to traditional RF magnetron deposition, the use of the discharge system made it possible to significantly increase the deposition rate for BAM films and reduce the pressure of the working gas. The modes of plasma generation and the properties of the films were investigated.
Electrochemical studies of ceramic-like MAO-coatings on the E110 alloy
Authors: Sivtsova G V , Savushkina S V , Ashmarin A A , Gerasimov M V , Suminov I V , Vinogradov A V
Published: June 2021

Ceramic-like coatings with the thickness up to 35 μm were formed on E110 zirconium alloy by microarc oxidation in electrolyte with the addition of yttrium oxide powder with average particle size 0.28 μm. The electrochemical behavior in 0.2M LiOH, structure, and phase composition of the obtained coatings have been studied. Polarization study in 0.2MLiOH at room temperature showed the anode currents on the coating up to 4 times less than on the uncoated alloy. Increasing the electrolyte temperature to 100 °C leads to growth in the anode currents on the coated samples, but current density values still correspond to the passive state.
Development of TiO2- and MWCNT based photocatalysts with Au and Cu clusters by electrophoretic deposition
Authors: Sorokina L I , Lebedev E A , Dubkov S V , Savitskiy A I , Maniecki T , Kedziora A , Gromov D G
Published: June 2021

This paper presents the features of electrophoretic deposition of TiO2, TiO2-$$$MWCNT composites. The influence of various dispersant additives in the suspension on the electrophoretic mobility of TiO2 particles and the morphology of the formed layer has been studied. The effect of modification by Au and Cu clusters on the photocatalytic activity was investigated.
Composition of glaze layer of the 18th century tiles
Authors: Vakhrushev V O , Wainstein D L , Kovalev A I , Konovalov E P , Mukhsinova A D , Shlykova T V
Published: June 2021

There were studied glaze layers of fragments of painted tiles estimated by art historians basing on external signs as fabricated in the Netherlands in the 18th century. The paper presents results of glaze surface composition measurements by X-ray fluorescence (XRF) and X-ray photoelectron spectroscopy (XPS), time-of-flight mass-spectroscopy (TOF-$$$SIMS) methods in comparison with literature data. Information on composition of glaze layers including pigments will be used obtained in this research will be used in further conservation efforts.
Mutual mass transfer between the target and the substrate in the process of ion sputtering. Flat and cylindrical target
Authors: Volpian O D , Dronsky R V , Alybin K V , Kuzmichev A I , Melnichenko M S
Published: June 2021

The ion sputtering process for the deposition of coatings from alternating layers of light and heavy metals are considered, taking into account the mutual mass transfer from the target to the substrate and from the substrate to the target as the result of resputtering the coating matter by reflected fast neutral gas atoms (former primary bombarding ions, backscattered from the target towards the substrate). The resputtering effect is more important in the case of deposition of a heavy metal of Ta type on layer from a light matter of Si type since it forms the intermediate layer of mixing composition “Ta + Si” between layers of pure metals.
Numerical model of the structural element complex geometry with a coating
Authors: Yakupov S N , Kiyamov H G , Yakupov N M
Published: June 2021

A model of the composition of complex geometry based on three-dimensional elements with a cubic approximation of the desired variables for the structural element and two-dimensional elements with a cubic approximation of the desired variables for the coating is described. An example of calculating the stress-strain state of a plate with thin steel coatings is considered.
Artificial intelligence and database technology work together
Authors: Wang Xinyi , Zhang Liyu , Yang Luhan
Published: June 2021

Ai - database integration is an effective application for many artificial intelligence technologies as well as major technologies for database development, and for the next generation of computing It supports intelligent information systems based on distributed cooperative tasks. The relationship between AI and large data and the potential values of Bayes in AI are described.
Application of Data Mining Based on Computer Algorithm in Personalized Recommendation Service of University Smart Library
Authors: Jing Zhang
Published: June 2021

Smart library is an important channel to improve the reading ability of college students. It is an important means to cultivate students’ reading interest and cultivate the reading style of the whole people. The wisdom library focuses on wisdom, including service intelligence, management intelligence, and facility intelligence. In the process of promoting smart libraries, big data computing is at an important position, and computer algorithms are the core technology support. Therefore, it is of great significance to combine computer algorithm data mining with computer algorithms to analyze the application of data mining in the personalized recommendation service of university libraries. This paper analyzes the application of computer algorithm and big data mining technology in the personalized recommendation service of smart library, analyzes readers’ reading preferences and behavior habits, and proposes three measures for reference.
Research on the impact of R&D investment on the performance of equipment manufacturing enterprises
Authors: Zhao Xiangtong , Yu Zipeng
Published: June 2021

R&Dinvestment is a key factor for enterprises to enhance core competitiveness and achieve sustainable development, and also a key factor to improve the performance of equipment manufacturing enterprises. Taking 292 listed companies in equipment manufacturing industry as the research object, this paper explores the impact of R&D investment intensity and R&D personnel ratio on enterprise performance by analyzing the impact of R&D investment intensity and R&D personnel ratio on enterprise performance. The R&D input intensity of Listed Companies in China’s equipment manufacturing industry is at a medium level, and their competitiveness is not strong. There is a significant negative correlation between the current R&D input intensity and the current performance of the enterprise. There is a significant positive correlation between the current R&D input intensity and the current business performance of the enterprise. However, there is no significant relationship between the current R&D personnel ratio and the current performance of the enterprise.
Analysis of the Smart Library Construction in Colleges Based Big Data and Artificial Intelligence
Authors: Chen Zesheng , Zhou Min , Feng Lichun
Published: June 2021

With the rapid development of artificial intelligence in recent years, colleges and universities committed to information construction are seeking to transform from digital to intelligent. Among them, the smart library is an important part of university information construction. However, set up smart libraries face such problems as low rate of library entry and poor sense of experience. This paper analyses the status and difficulties of research and practices in smart libraries by crawler technology and questionnaire, and puts forward a smart library information construction scheme. The results show setting up a smart campus is in line with the new trend of education.
(λ, μ) Hesitant fuzzy subalgebras of Boolean algebras
Authors: Man Jiang
Published: June 2021

In this paper, the concept of (λ, μ)-hesitant fuzzy subalgebras is introduced in Boolean algebra. Some properties of (λ, μ)-hesitant fuzzy subalgebras are discussed. Finally, we proved that the intersection and direct product of two (λ, μ)-hesitant fuzzy subalgebras are also (λ, μ)-hesitant fuzzy subalgebras in Boolean algebra.
Evolving Data Monitoring Algorithm based on Data Stream Clustering
Authors: Yang Chunhua , Wang Cong , Hu Xiao , You Niankang , Yang Xuguang
Published: June 2021

Clustering is one of the most important methods in the data stream mining. The nature of evolving data streams puts forward the following requirements for clustering: discovery of clusters with arbitrary shape, determination of the optimal number of clusters, anomaly detection and processing the influence of time. In the communication process, timely detection of anomalies is very important for the coordination of various devices. In this paper, we propose an adaptive density-based approach for clustering in evolving data streams(SagsDStream), which automatically updates parameters in subsequent stages based on the offline clustering result, so that the parameters can adapt to the change of data stream. In the online mode, the judging rules are saved in Improved Time Cluster Feature (ITCF). In the offline model, we use the density of the data distribution and the cluster distance to set the parameters of clustering algorithm, which overcome the sensitivity of Density-Based Spatial Clustering of Applications with Noise (DBSCAN) threshold setting. Experimental results show that SagsDStream has better processing efficiency and clustering effect when dealing with data streams.
Air Quality Index Monitoring Based on Profile-MEWMA Control Chart
Authors: Liu Yingjie , Zi Xuemin
Published: June 2021

At present, due to the rapid development of domestic economy, the environmental pollution problems are becoming increasingly serious, especially the pollution problems such as PM2.5 and PM10 caused by industrial emissions and waste gas pollution are most urgent. The general linear profile model and multivariate exponential weighted moving average control chart (MEWMA) is designed to perform monitoring and evaluating the air quality index (AQI) in Tianjin, so as to provide some statistical information for the relevant departments. Six main pollutants SO2,NO2,PM10,PM2.5,O3,CO in Tianjin were collected which taken as factors affecting AQI under consider establish a general linear profile model where AQI was taken as the response variable. The coefficients of the model are monitoring by an MEWMA control chart.
MLU-Net: Efficient Segmentation for Retinal Layers In Optical Coherence Tomography Images
Authors: Xu Xiangcong , Wang Xuehua , Han Dingan , Guo Xuedong , Lin Jingyi , Xiong Ke , Zheng Yixu , Zeng Yaguang
Published: June 2021

The automatic segmentation of retinal images obtained by optical coherence tomography is increasingly important for ophthalmologists to diagnose and monitor many kinds of ophthalmic diseases. U-Net is the most widely used deep learning network in retinal segmentation, but the limited number of data-flow paths made it hard to capture complex features. We proposed here an optimized Mobile Ladder U-Net (MLU-Net), which consists of a Ladder Connection for increasing the network’s data-flow paths and a depthwise separable convolution for reducing the model’s parameters. Experiments on 100 B-scans from 10 human eyes demonstrated that the 9 retinal layer boundaries can be segmented accurately with the MLU-Net. In addition, compared with the original U-Net and LadderNet, the segmentation result of our method is closest to the expert label.
Enhancing the Transferability of Adversarial Attacks with Input Transformation
Authors: Yang Bo , Zhang Hengwei , Xu Kaiyong
Published: June 2021

Deep neural networks (DNNs) are challenged by their vulnerability to adversarial examples, which are crafted by adding small, human-imperceptible perturbations to the original images, but make the model output inaccurate predictions. Adversarial attacks can thus be an important tool to evaluate and select robust models before they are deployed. However, under the challenging black-box setting, most of existing adversarial attacks can only fool a model with a low success rate. Based on image augmentation methods, we found that random transformation of image size can eliminate overfitting in the generation of adversarial examples and improve their transferability. To this end, we propose an adversarial example generation method based on this phenomenon, which can be integrated with Fast Gradient Sign Method (FGSM)-related methods to build a stronger gradient-based attack and generate adversarial examples with better transferability. Extensive experiments on the ImageNet dataset demonstrate that our methods attack both normally trained models and adversarially trained models with higher attack success rates than existing baseline attacks. We hope that our proposed attack method can serve as a benchmark for evaluating the robustness of networks to adversaries and the effectiveness of different defense methods.
The Representation of Large-Scale Graph Based on Semi-Supercised Learning
Authors: Tian-qing Yang , Jing-zong Yang , Hui Wang
Published: June 2021

With the development of artificial intelligence, the technology of graph representation has been widely used in graph structure data mining. The traditional graph representation mostly uses adjacency matrix. The representation of adjacency matrix is faced with two major challenges. One reason is extremely inefficient in the storage and computing of large graphs with the massive growth of data; the other is that the characterized data is difficult to retain the original structural information of graphs. Aiming at the above two points, an efficient graph representation method is proposed in this paper. The first-order similarity and second-order similarity of the graph are used as constraints to train the original graph structure data, and the nodes in the graph are mapped to a low-dimensional space, which greatly reduces the cost of storage space and computing while retaining the graph structure information. Experimental results show that the proposed method is significantly better than the Deepwalk and spectral clustering methods in different proportion of label data. Meanwhile, the proposed method can be applied to the semi-supervised learning task with a small number of labels, which provides convenience for the subsequent data analysis.
The Impact of Assets Accelerated Depreciation on Enterprise Investment Based on Statistical Analysis
Authors: Wang Chaofan
Published: June 2021

With the continuous upgrade of consumption structure, the supply and demand contradictions continue to deepen, and the Ministry of Finance issued by the Ministry of Finance in October 2014 stipulates that the six major industries can adopt accelerated depreciation of newly purchased fixed assets. The purpose of item initiative is to further promote the reform of the supply side. Based on the newly purchased fixed assets in 2010-2017, this paper discovered the research of difference-in-difference model analysis by using statistical methods. The policy significantly reduced the tax burden of the pilot industry, significantly improved the fixed asset investment in the pilot industry, further Promote the structural reform of the supply side of the company, and promoting the company’s improvement efficiency. This paper helps to deepen the exploration of the impact of relevant depreciation policies, which provides a reference for China’s better supply side structural reform, and promoting the development of enterprises, which is helpful to the development of deep application research of mathematical economics
The Theoretical Breakthrough of Self-Supervised Learning : Variational Autoencoders and Its Application In Big Data Analysis
Authors: Ji Yanqiu , Lu Zhiyi
Published: June 2021

In the study of big data statistics, a large number of unknown latent variables bring great difficulties to modeling. Variational autoencoders(VAE) can overcome the shortcomings of traditional variational methods such as low efficiency and poor generality, and provide an efficient and extensible framework for variational posteriori inference and approximate maximum likelihood learning based on gradient. On the basis of reviewing the development history of variational autoencoders and taking the deep latent variable model(DLVM) as an example, this paper introduces the basic principle of variational autoencoders and analyzes its application under the background of big data. The problems in theory and application of variational autoencoders are presented, as well as the topics to be further studied. The combination of variational autoencoders and other statistical modeling methods may become a new idea for big data research.
An ensemble learning method for variable selection and its application on Railroad Fatal Accidents.
Authors: Chen Jing , Yan Yan , Chen Xi
Published: June 2021

Scalars based on linear and generalized linear models are commonly used in fatality and disease predictions. Currently, standard approaches for variable selection in linear and generalized linear models are not explored well with high dimensional data. This manuscript proposed a new variable selection method for logistics models with inspiration from heterogeneous ensemble methods. The goal of this study is to extend classical variables selection methods such as stepwise, lasso, or RF in the case of high dimensional accident data with missing values. Real world accidents-collated data sets are collected from the official website of US Railroad Administration and US Police Department from 2000 to 2015. Preprocessing includes log transformation and z score transformation. Simulated sampling was applied due to the imbalanced outcome. The base variables was selected from the Empirical Model (EM) [1], Lasso model[2], Xgboost[3] and the traditional stepwise backward. An intermediate selection was proposed by ensemble training of base variables. Final models built by variables selected improved Area Under the Curve (AUC) from 0.79 to 0.84 and from 0.79 to 0.84 in test data compared to arbitrary APS model. Comparison with the existing model shows that the logistics model based on selected variables has high accuracy.
Study of cell clustering optimization algorithm for load balancing in 5G scenario
Authors: Wang Yuhan
Published: June 2021

In the context of 5G networks at this stage, massive data transmission and highly dense deployment of base stations make severe interference and huge load volumes an inevitable new challenge. The traditional interference coordinated cell-clustering scheme only considers the inter-micro base station path loss without jointly considering load balancing, an important factor affecting system performance. This paper first introduces the existing cell-clustering schemes, and then proposes a cell-clustering optimization algorithm that combines path loss and load balancing on the basis of 5G cellular network architecture, and then simulate the optimization algorithm and compare the results with the traditional schemes to verify its ability to balance the load, increase the amount of transceiver data, and optimize the resource allocation and performance effects.
Link Prediction Algorithm Based on Node Structure Similarity Measured by Relative Entropy
Authors: Yuyu Meng , Jing Guo
Published: June 2021

To solve the problem that the link prediction method based on local information ignores the influence of neighbor structure information on the similarity measurement of nodes, a link prediction method based on relative entropy and local structure of nodes is proposed. Firstly, the second-order local network is introduced to describe the local structure of nodes; then, the structural similarity between nodes is described by redefining the relative entropy; finally, the structural similarity of nodes is measured based on relative entropy, and the structural similarity index of the node structure is proposed considering the structure information of the neighbor. Experimental results on 7 real network data sets show that the proposed method can achieve better results and can be applied to networks with a small average aggregation coefficient compared with other similarity indexes based on local and global information, and also have better performance on large-scale networks.
Research on equipment health diagnosis system of railway passenger station based on cloud-edge collaboration
Authors: He Xiaoling , Xu Chunjie , Chen Ruifeng , Wang Jing , Li Jun
Published: June 2021

In view of the current operation and maintenance mode for railway station equipment, the method of traditional manual and post-diagnosis for the equipment faults is still used, which cannot meet the reliability requirements of equipment operation and maintenance management. A health diagnosis system based on cloud-edge collaboration for railway station equipment is proposed. Firstly, it collects online operation information of multi-source perception equipment, which realized through edge intelligent gateway by componentized micro- service and Docker technology. Moreover, it realizes data storage and publishing, edge detection, monitoring online and early warning through the intellectual server models. Secondly, a life prediction model is established based on HSMM to calculate the health status and service life of the equipment. Finally, the cloud-edge collaboration model is designed based on KubeEdge to realize the cloud-edge communication and collaborative service of resources. It effectively solves the problems of remote condition monitoring, health diagnosis and predictive maintenance for railway station equipment, and it provides technical support for the safe operation of railway station.
Attack path prediction based on Bayesian game model
Authors: Sun Pengyu , Zhang Hengwei , Li Chenwei
Published: June 2021

The current network risk assessment model often ignores the impact of attack cost and intrusion intention on network security. In order to better solve the problem of information security defense strategy selection and accurately assess the target network risk, this paper proposes an attack path prediction method based on game model.The atomic attack probability is calculated by vulnerability value, attack cost and attack benefit. The static risk assessment model is established combined with Bayesian belief network quantitative attack graph. And the dynamic update model of intrusion intention is used to realize the effective prediction of attack action under rational assumption, which provides the basis for dynamic defense measures of attack surface. The experimental results verify the feasibility and effectiveness of the model and method.
Research on the spatio-temporal characteristics of hornets’ nests based on K-means clustering
Authors: Mijia Li , Lei Ma , Zhejun Cai
Published: June 2021

Asia giant hornet is a predator of European honeybees, invading and destroying their nests. Nowadays, the State of Washington is suffering the attack of this hornet. Due to the potential severe impact on local honeybee populations, it will probably cause a great deal of anxiety.

The most informative factors we consider are Detection Date,latitude and longitude. We propose a “time-space-state model” to evaluate the information evaluated by these two indicators. The time-space-state model can be divided into two kinds: the general model of time discretization and space continuum; The general model of space discretization and time semi-continuity. In the previous model, we mainly use K-means algorithm to determine the nest position in discrete time. In the latter model, we use the improved K-means algorithm to obtain the distribution model of hornets with seasonal variation.

Through research, we have discovered the temporal and spatial laws of hornets’ nests, which are of great significance for maintaining the stability of agricultural production.
ACORE: A Query Optimization Approach for Spark SQL Based on Cost Model and Markov Prediction Model
Authors: Su Lanxin , Liu Huiyong
Published: June 2021

Spark SQL is Spark’s module for working with structured data. However, there exist two problems that may impact its query execution efficiency: 1) Users may attempt to cache datasets used multiple times in a query to speed up the execution, but due to the predicate pushdown optimization and the overhead of writing cached data, the cached plan may turn out to have worse performance. 2) When using Spark dynamic resource allocation strategy, the release of idle executors would lead to the loss of cached data, introducing recalculation cost. To address these, we present an approach, named ACORE, which adaptively cache datasets and optionally release executors to optimize query execution of Spark SQL. The approach includes two models: a cost model and a Markov chain prediction model. The cost model is applied to estimate the execution cost for cached and un-cached plans, and decide which one to be the actual execution plan. The Markov prediction model is used to predict the changing trend of intervals between queries, guiding to optionally release executors to save cached data. We test the efficiency of our approach with data generated by TPC-H tool and the experimental results show that the execution performance can be improved by up to 51%.
An optimal combination prediction method of turnover spare parts consumption based on certain weight
Authors: Lin Chai , Feng Guo , Zishuo Wang
Published: June 2021

Aimed at the situation that the first, second and third exponential smoothing method and the three and four term moving average method are used to forecast the consumption of spare parts separately, the combined prediction model is established by optimizing the combination of these single prediction methods, and the result with the minimum prediction error is taken as the predicted value of consumption. A concrete example shows that the combined prediction model is more accurate and has higher practicability and generalization.
The secondary electron yields and related surface properties evolution of laser treated stainless steel induced by different ultrasonic cleaning duration
Authors: Wang J. , Wu Y. , You Z. , Gao Y. , Zhang J. , Zhang T. , Hu Y. , Wang S. , Li H. , Xu Z. , Liu Y. , Li W.
Published: June 2021

As a novel method, laser treatment was proposed to be applied on the surface modification of stainless steel 316L commonly used in accelerator vacuum system to mitigate the secondary electron emission. However, the final property of the material surfaces, especially the secondary electron yield (SEY) property depends on a rather large number of factors, among them are the surface cleaning scenarios needed before installation. In particular, the surface morphologies and surface chemical states may be changed during the ultrasonic cleaning used for laser treated stainless steel surfaces. Therefore, the influence of ultrasonic cleaning duration on the surface composition, surface morphology and secondary electron characteristics of stainless steel were studied for the first time. The secondary electron yield test results demonstrated that the maximum SEY (δ
max) of laser treated stainless steel samples increased with the increase of ultrasonic cleaning time. After ultrasonic cleaning in acetone and absolute ethyl alcohol each for 3 minutes, 10 minutes and 15 minutes, respectively, the δ
max of laser treated stainless steel samples increased about 0.7%–1.7%, 1.3%–2.4% and 4.9%–15.3%, respectively, compared with that of uncleaned laser treated ones. The surface morphologies, surface roughness, surface chemical states related to the SEY evolution were also evaluated and analyzed.
Impact of COVID-19 restrictions on carers of persons with dementia in the UK: a qualitative study
Authors: Sriram Vimal , Jenkinson Crispin , Peters Michele
Published: June 2021

Background

informal carers provide the majority of the support for persons with dementia living at home. Restrictions imposed due to COVID-19 have had a profound impact on the daily life of the entire population. This study provides insight into the impact of these restrictions on carers of people with dementia living at home.

Design

qualitative semi-structured interviews.

Participants

purposive sample of carers who provide at least 10 hours of care a week for the person with dementia living at home.

Setting

UK.

Results

twenty-three carers were interviewed, and thematic analysis identified three main themes—Changes to daily life, impact on carer health and wellbeing and reduced support from health and social support networks. The results highlight the impact of restrictions imposed on daily life and routines due to the pandemic, wellbeing of carers, reduced social support, lack of access to health and care professionals and respite for carers. The restrictions have had negative consequences on carers’ wellbeing, and they have experienced difficulties in accessing formal care services and respite care.

Conclusion

carers attempt to continue to provide physical, emotional and practical support for persons with dementia in the community throughout the COVID-19 restrictions. To prevent a future carer crisis, carers need better support systems including formal carer services, telecare solutions that work for them and additional support for respite, as the restrictions from this pandemic continue.
Tracking cell wall changes in wine and table grapes undergoing Botrytis cinerea infection using glycan microarrays
Authors: Weiller Florent , Schückel Julia , Willats William G T , Driouich Azeddine , Vivier Melané A , Moore John P
Published: June 2021

Background and Aims

The necrotrophic fungus Botrytis cinerea infects a broad range of fruit crops including domesticated grapevine Vitis vinifera cultivars. Damage caused by this pathogen is severely detrimental to the table and wine grape industries and results in substantial crop losses worldwide. The apoplast and cell wall interface is an important setting where many plant–pathogen interactions take place and where some defence-related messenger molecules are generated. Limited studies have investigated changes in grape cell wall composition upon infection with B. cinerea, with much being inferred from studies on other fruit crops.

Methods

In this study, comprehensive microarray polymer profiling in combination with monosaccharide compositional analysis was applied for the first time to investigate cell wall compositional changes in the berries of wine (Sauvignon Blanc and Cabernet Sauvignon) and table (Dauphine and Barlinka) grape cultivars during Botrytis infection and tissue maceration. This was used in conjunction with scanning electron microscopy (SEM) and X-ray computed tomography (CT) to characterize infection progression.

Key Results

Grapes infected at veraison did not develop visible infection symptoms, whereas grapes inoculated at the post-veraison and ripe stages showed evidence of significant tissue degradation. The latter was characterized by a reduction in signals for pectin epitopes in the berry cell walls, implying the degradation of pectin polymers. The table grape cultivars showed more severe infection symptoms, and corresponding pectin depolymerization, compared with wine grape cultivars. In both grape types, hemicellulose layers were largely unaffected, as was the arabinogalactan protein content, whereas in moderate to severely infected table grape cultivars, evidence of extensin epitope deposition was present.

Conclusions

Specific changes in the grape cell wall compositional profiles appear to correlate with fungal disease susceptibility. Cell wall factors important in influencing resistance may include pectin methylesterification profiles, as well as extensin reorganization.
JBrowseR: an R interface to the JBrowse 2 genome browser
Authors: Hershberg Elliot A , Stevens Garrett , Diesh Colin , Xie Peter , De Jesus Martinez Teresa , Buels Robert , Stein Lincoln , Holmes Ian
Published: June 2021

Motivation

Genome browsers are an essential tool in genome analysis. Modern genome browsers enable complex and interactive visualization of a wide variety of genomic data modalities. While such browsers are very powerful, they can be challenging to configure and program for bioinformaticians lacking expertise in web development.

Results

We have developed an R package that provides an interface to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown documents.

Availability and implementation

JBrowseR is available for download from CRAN, and the source code is openly available from the Github repository at https://github.com/GMOD/JBrowseR/.
The association between cardiac intensive care unit mechanical ventilation volumes and in-hospital mortality
Authors: Nandiwada Shiva , Islam Sunjidatul , Jentzer Jacob C , Miller P Elliott , Fordyce Christopher B , Lawler Patrick , Alviar Carlos L , Sun Louise Y , Dover Douglas C , Lopes Renato D , Kaul Padma , van Diepen Sean
Published: June 2021

Aims

The incidence of respiratory failure and use of invasive or non-invasive mechanical ventilation (MV) in the cardiac intensive care units (CICUs) is increasing. While institutional MV volumes are associated with reduced mortality in medical and surgical ICUs, this volume–mortality relationship has not been characterized in the CICU.

Methods and results

National population-based data were used to identify patients admitted to CICUs (2005–2015) requiring MV in Canada. CICUs were categorized into low (≤100), intermediate (101–300), and high (>300) volume centres based on spline knots identified in the association between annual MV volume and mortality. Outcomes of interest included all-cause in-hospital mortality, the proportion of patients requiring prolonged MV (>96 h) and CICU length of stay (LOS). Among 47 173 CICU admissions requiring MV, 89.5% (42 200) required invasive MV. The median annual CICU MV volume was 43 (inter-hospital range 1–490). Compared to low-volume centres (35.9%), in-hospital mortality was lower in intermediate [29.2%, adjusted odds ratio (aOR) 0.84, 95% confidence interval (CI) 0.72–0.97, P = 0.019] and high-volume (18.2%; aOR 0.82, 95% CI 0.66–1.02, P = 0.076) centres. Prolonged MV was higher in low-volume (29.2%) compared to high-volume (14.8%, aOR 0.70, 95% CI 0.55–0.89, P = 0.003) and intermediate-volume (23.0%, aOR 0.85, 95% CI 0.68–1.06, P = 0.14] centres. Mortality and prolonged MV were lower in percutaneous coronary intervention (PCI)-capable and academic centres, but a shorter CICU LOS was observed only in subgroup of PCI-capable intermediate- and high-volume hospitals.

Conclusions

In a national dataset, we observed that higher CICU MV volumes were associated with lower incidence of in-hospital mortality, prolonged MV, and CICU LOS. Our data highlight the need for minimum MV volume benchmarks for CICUs caring for patients with respiratory failure.
Dental Plaque Concentrations of Methadone, Morphine and Their Metabolites in Opioid Replacement Therapy and in Postmortem Cases
Authors: Henkel Kerstin , Klima Miriam , Auwärter Volker , Altenburger Markus J , Neukamm Merja A
Published: June 2021

Non-mineralized dental biofilm (plaque) has potential as a novel alternative matrix in forensic toxicology to prove drug use. The incorporation of illicit and medicinal drugs in dental plaque could take place through direct contact after oral or nasal intake, which can lead to high drug levels in the oral cavity, or indirectly via the secretion of drug-containing saliva, e.g., after intravenous application. Therefore, plaque samples from patients in opioid replacement therapy (ORT) and postmortem plaque samples were analyzed and the drug concentrations were compared. The study comprised 26 plaque samples from ORT patients with different daily doses, which were analyzed for methadone, morphine and their respective metabolites. Plaque samples were taken directly before the oral administration of the regular daily dose. Seventeen postmortem plaque samples were analyzed, either from cases of lethal drug intoxications or after pain therapy with morphine. Plaque analysis was performed using liquid chromatography--tandem mass spectrometry after liquid extraction with acetonitrile. Plaque concentrations in ORT for methadone and its metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP) ranged from 42 to approximately 49,000 pg/mg (median 1,300 pg/mg) and from below 10 to 610 pg/mg (median 31 pg/mg), respectively. Morphine plaque concentrations in ORT ranged from 120 to 480 pg/mg (median 400 pg/mg). In lethal intoxication cases, plaque concentrations were generally at least one order of magnitude higher than those in the study groups with therapeutic substance use. These data will help to interpret drug findings in plaque. Furthermore, the EDDP/methadone concentration ratio in plaque was lower after oral intake with contamination of the oral cavity (e.g., syrup) compared to cases with suspected intravenous application of methadone. Therefore, the EDDP/methadone concentration ratio could therefore indicate the drug administration route.
Factors Associated With Social Participation in Persons Living With Inflammatory Bowel Disease
Authors: Su Samuel , Marrie Ruth Ann , Bernstein Charles N
Published: June 2021

Background

Inflammatory bowel disease (IBD) including Crohn’s disease (CD) and ulcerative colitis (UC) imposes a significant burden on health-related quality of life, particularly in social domains. We sought to investigate the factors that limit social participation in patients with IBD.

Methods

We assessed a cohort of 239 Manitobans with IBD. We collected sociodemographic information, medical comorbidities, disease phenotype, symptom activity and psychiatric comorbidity (using the Structured Clinical Interview for DSM-IV). Participants completed the eight-item Ability to Participate in Social Roles and Activities (APSRA) questionnaire, which assesses participation restriction, including problems experienced in social interaction, employment, transportation, community, social and civic life.

Results

Poorer social participation scores were associated with earning less than $50,000 CAD income annually (P < 0.001), actively smoking (P = 0.006), higher symptom scores (P < 0.001 for CD, P = 0.004 for UC), and having an increasing number of chronic medical conditions (R = −0.30). History of depression (P < 0.001) and anxiety (P = 0.001) and having active depression (P < 0.001) and anxiety (P = 0.001) all predicted poor social participation scores. IBD phenotype or disease duration was not predictive. Based on multivariable linear regression analysis, significant predictors of variability in social participation were medical comorbidity, psychiatric comorbidity, psychiatric symptoms and IBD-related symptoms.

Conclusions

The factors that predict social participation by IBD patients include income, smoking, medical comorbidities, IBD symptom burden, and psychiatric comorbidities. Multivariable linear regression suggests that the most relevant factors are medical comorbidity, psychiatric comorbidity, psychiatric symptoms and IBD symptoms.
Venetoclax plus low-dose cytarabine in Japanese patients with untreated acute myeloid leukaemia ineligible for intensive chemotherapy
Authors: Yamauchi Takahiro , Yoshida Chikashi , Usuki Kensuke , Takada Satoru , Matsumura Itaru , Dobashi Nobuaki , Miyazaki Yasushi , Miyamoto Toshihiro , Iida Hiroatsu , Asou Norio , Kuroda Junya , Ichikawa Satoshi , Komatsu Norio , Mendes Wellington , Honda Hideyuki , Okubo Sumiko , Kurokawa Misaki , Jiang Qi , Wei Andrew , Ishizawa Kenichi
Published: June 2021

Background

In a multinational phase 3 trial (VIALE-C), venetoclax plus low-dose cytarabine prolonged overall survival vs placebo plus low-dose cytarabine in patients with newly diagnosed acute myeloid leukaemia ineligible for intensive chemotherapy, although it was not statistically significant. Herein, we assess the benefit of venetoclax plus low-dose cytarabine in the Japanese subgroup of VIALE-C patients (n = 27).

Methods

VIALE-C, a randomized (2:1), double-blind study (NCT03069352), enrolled untreated patients (≥18 years) with acute myeloid leukaemia. Patients received venetoclax (600 mg days 1–28, 4-day ramp-up in cycle 1) or placebo in 28-day cycles with low-dose cytarabine (20 mg/m2 days 1–10). The primary endpoint was median overall survival.

Results

In the Japanese subgroup, at a 6-month follow-up from the primary analysis, median overall survival for venetoclax (n = 18) and placebo (n = 9), plus low-dose cytarabine, was 4.7 and 8.1 months, respectively (hazard ratio, 0.928, 95% confidence intervals : 0.399, 2.156). The rate of complete remission plus complete remission with incomplete blood count recovery was higher with venetoclax plus low-dose cytarabine (44.4%) vs placebo plus low-dose cytarabine (11.1%). All patients experienced at least 1 adverse event. The most common grade ≥3 adverse events with venetoclax or placebo, plus low-dose cytarabine, were febrile neutropenia (50.0% vs 44.4%, respectively) and thrombocytopenia (27.8% vs 44.4%, respectively). Serious adverse events were reported in 50.0 and 33.3% of patients in the venetoclax and placebo, plus low-dose cytarabine arms, respectively; pneumonia was the most common (22.2% each).

Conclusions

Limited survival benefit in the Japanese subgroup can be attributed to small patient numbers and to baseline imbalances observed between treatment arms, with more patients in the venetoclax plus low-dose cytarabine arm presenting poor prognostic factors. Venetoclax plus low-dose cytarabine was well tolerated in Japanese patients with acute myeloid leukaemia ineligible for intensive chemotherapy.
A laparoscopic pancreaticoduodenectomy for pancreatic adenocarcinoma in a patient with situs inversus totalis
Authors: Hussan Maher Al , Yang Zhen , Dong Xinhua , Yang Hongwei , Li Nanpeng , Qiao Shishi
Published: June 2021

Situs inversus totalis (SIT) is a congenital disorder in which the thoracic and abdominal viscera organs are mirrored from their normal anatomical position. Thus, the presence of any cancerous mass in one of the visceral organs of patients with SIT represents a great challenge due to the anatomical variation. We report a 52-year-old male with SIT who presented with obstructive jaundice and pancreatic-head mass. After preoperative examinations, it was decided to perform a laparoscopic pancreaticoduodenectomy. In this case, we aim to demonstrate the diagnosis and management of pancreatic cancer in an SIT patient, in addition to presenting the advantages and difficulties of laparoscopic surgery in this case.
Synchronous breast invasive ductal carcinoma and clear cell renal carcinoma: case report and a review of literature
Authors: Elgazar Amr , Awad Ahmed K , Mnadal Debvarsha , Elbadawy Merihan A , Elseidy Sheref A
Published: June 2021

Multiple primary tumors' incidence is rare, yet more rare is the incidence of multiple primary malignant tumors. Co-occurring tumors can be divided into synchronous and non-synchronous. Synchronous tumors are those tumors that present within a period not >6 months from each other. To define synchronous malignant tumors: metastasis should not be present, both tumors have to show criteria of malignancy, and they should differ pathologically from each other. Breast cancer is the most common tumor to be associated with other primaries especially; colorectal cancer, endometrial and ovarian cancer, yet the occurrence of invasive ductal carcinoma with clear cell renal cancer is uncommon. In our case, we present a 59-year-old female with invasive ductal carcinoma and clear cell renal carcinoma.