bluuebunny/crossref_metadata_2025 huggingface dataset:
The Study of Rice Shell Ash Precipitation Legal System for Silica
Authors: Zhang Peng , Liu Ao , Zuo Huimin , Zhou Mingyuan
Published: July 2021

Using rice husk ash as raw material, low modulus sodium silicate was prepared and high dispersion white carbon black was prepared by chemical precipitation method. The effects of sulfuric acid concentration, reaction temperature and aging time on the oil absorption value (DBP). The high dispersion white carbon black was characterized by laser particle size analyzer, X-ray diffractometer, DBP and scanning electron microscope (SEM). The results show that when the sulfuric acid concentration is 5%, the temperature is 85°C, and the aging time is 60min, the silica morphology is spherical, and the average particle size is about 5 micron, the oil absorption value is 2.82.
Effect of TiO2 content on microstructure and properties of Ti-24Nb-4Zr-8Sn alloy for biomedical applications prepared by powder metallurgy
Authors: Tingzhuo Chen , Shuan Chao
Published: July 2021

Ti-24Nb-4Zr-8Sn (TNZS) as an important material in biomedical field, has ushered in broader application space and proposed higher performance requirements. This paper presents the experimental investigation of the effecct of TiO2 content on the microstructure and properties of TNZS prepared by powder metallurgy, aiming to optimize the additional amount of TiO2 (0wt.%, 3wt.%, 6wt.% and 9wt.%), improve the microstructure uniformity and properties. The phase, microstructure, hardness, elastic modulus were measured. The results indicate that nTiO2/TNZS alloy was composed of α-Ti, β-Ti, Rutile TiO2 and Anatase TiO2. Meanwhile, the diffraction peals intensity of α-Ti and Rutile TiO2 were enhanced obviously with the increasing of TiO2 content. With the increase of TiO2, the size of grain was refined and the distribution became homogenized. As the TiO2 content rises, the hardness first decrease and then increase. The results show that the micro-hardness of nTiO2/TNZS alloys were 579.8 HV, 452.9 HV, 983.2 HV and 1219.9 HV, the micro-hardness of 9wt.%TiO2/TNZS alloy reach the maximum. The elastic modulus of nTiO2/TNZS alloys were 43.29 GPa, 50.44 GPa, 57.62 GPa and 85.37 GPa.
The Study on Plastic Flow Behavior and Constitutive model of GCr15 Steel in Isothermal Compression
Authors: Guo Junhang , Li Yanli , Zhai Renpei , Yang Jianwei
Published: July 2021

The plastic deformation behavior of GCr15 steel under temperatures ranging from 700°C to 900°C and strain rates ranging from 0.01s-1 to 10s-1 was researched by isothermal hot compression testing. The strain stress curves obtained by tests show that the maximum stress decreases with the temperature while increases with the strain rate. In the beginning of plastic strain, the stress increases with the strain to maximum stress showing strain hardening, then decreases with strain showing strain softening. The flow behavior is modeled by a combination of exponential and linear functions with 3 parameters and the parameters were obtained by regressions. The effect of temperature and strain rate on the maximum stress was studied by an Arrhenius-type equation. The new constitutive model was verified in this paper.
Experimental Research on the Mixing Performance of Follow-up Dynamic Mixing Equipment
Authors: Liu Haiyan
Published: July 2021

From the current application, the mixing equipment often used includes stirred tank, impinging stream mixing equipment, jet mixing equipment, dynamic mixing equipment and static mixing equipment. There are also certain differences in the mixing performance and application effects of different mixing equipment. This article analyzes the related content of the follow-up dynamic mixing equipment. Through the study of the solid-liquid mixing performance experiment and the mixing time performance experiment of the follow-up dynamic mixing equipment, the purpose is to accumulate reliable experimental data for the smooth progress of other subsequent activities. for reference.
Failure Analysis and protection Suggestions of a Leakage Condenser Tubes in Thermal Power Plants
Authors: Li Xiuneng , Yang Chao , Wang Yunan , Hou Shuang , Wu Yuan Jian
Published: July 2021

The methods of chemical composition analysis, macroscopic morphology inspection, metallographic inspection, scanning electron microscope and energy spectrum analysis are used to analyze the failed condenser brass tubes. The results show that the alloy composition of the condenser tube meets the requirements of the HSn70-1A brass standard. There are many traces of pitting corrosion on the inner surface. The metallographic observation shows that the pitting corrosion is cracking along thegrain boundary, only about 1-3 grains deep. Energy spectrum analysis shows that the content of O, Ca, and P, and a small amount of Cl and S in the corrosion pits are greatly increased, and the zinc content is significantly decreased. Condenser tube leakage is mainly caused by circulating water pollution, until the corrosion penetrates to form a leak. According to the corrosion characteristics, this article puts forward relevant suggestions for the protection of condenser tubes.
Temperature Rise Experiment and Prediction Modeling for Key Position of Preload Adjustable Motorized Spindle
Authors: Songsheng Li , Tongxu Yang , Yangyang Liu , Zhiqiang Zheng , Guoqing He
Published: July 2021

High-speed motorized spindle is one of the key components of CNC machine tools. The temperature rise prediction and control of motorized spindle is an important technology for the development of intelligent machine tools. The influence of gas supply pressure and spindle speed on the temperature rise of the outer ring of the front bearing of the motorized spindle was experimentally studied by using the established test platform for online regulation of the motorized spindle under pre-load. The results show that the steady-state temperature rise of the high-speed motorized spindle increases with the increase of its speed and gas supply pressure. It further indicates that the online control of the pre-load of the bearing can realize the active control of the thermal characteristics of the motorized spindle. The BP neural network temperature rise prediction model was established to predict the temperature rise at the key position of the high-speed motorized spindle under specific rotational speed, air supply pressure and ambient temperature. The reliability and accuracy of the model are verified by comparing the predicted results with the experimental results. The predicted results can be used as the basis for studying the thermal characteristics of high-speed motorized spindle.
Numerical simulation of free liquid surface sloshing characteristics in liquid chamber
Authors: Fu Benshuai , Zhang Jianbin , Xiao Haiyan , Li Guanghua , Qin Liping , Lu Bingju
Published: July 2021

It is of great significance to study that the liquid chamber of the submarine-borne missile launching power system is adapted to the swinging environment after liquid injection in engineering application. In this paper, the VOF method and k-ε turbulence model are adopted, and the UDF is used to simulate external load. The simulation results show that the model established in this paper can be used to simulate the sloshing characteristics of the free liquid surface in the liquid chamber of the submarine borne missile launching power system; Under the action of a given swinging load, the free liquid surface of the liquid chamber is within the allowable range of the design, and will not cause adverse effects on the liquid chamber or even the whole launching power system of the submarine-borne missile.
Failure Analysis of Worm Gear in Worm Transmission
Authors: Tao Zhijian , Chen Hongbo , Zhang Xiaomin , Jiang Yu
Published: July 2021

The failure cause of the worm drive in the NMRV reducer of the grounding knife-switch mechanism of State Grid was analyzed in this paper. The macroscopic analysis, chemical composition inspection, microscopic metallographic observation, hardness test, SEM analysis were carried out to evaluate the worm gear failure mechanism. The stress distributions of the tooth flank using dynamic contact finite element simulation were obtained based on ANSYS Workbench software. The results showed that an initial crack at the root position of softer worm gear was caused by excessively high impact at the initial stage of meshing in the worm drive, whose value was 308MPa higher than the allowable contact stress of 220MPa. The main reason for the hardness of the worm gear decreasing was that the amount of (α+δ) eutectoids fell and distributed unevenly.
Robotic Trajectory Planning for Non-Destructive Testing Based on Surface 3D Point Cloud Data
Authors: Zhang Zhen , Zhang Hualiang , Yu Xiaolong , Deng Yongsheng , Chen Zheng
Published: July 2021

Robotics has been widely used in the field of non-destructive testing in recent years. However, for complex surfaces, manual teaching or offline programming is time-consuming and difficult to ensure high precision for non-destructive testing robot trajectory planning. Therefore, this work proposes a new method to generate non-destructive testing trajectory of the robot based on the pre-processed point cloud data. The workpiece surface is measured by 3D sensor to obtain the point cloud data. The trajectory line on workpiece surface is obtained by slicing pre-processed point cloud data. The dense trajectory points are obtained by isometric discretizing trajectory lines, and then they are compressed by Douglas-Peucker algorithm. The Principal Component Analysis (PCA) method is used to estimate the normal vector of the optimized trajectory points and unify their orientation. The pose of non-destructive testing robot can be obtained by biasing the trajectory points along their normal vectors finally.
Vibration Test and Analysis of Variable Frequency Power Supply Motor Based on LMS Test.lab
Authors: Zhao-jian WANG , Xian-bin TENG , Fa-xin ZHU , Qi-jiang YANG , Kong-xing DING , Wen-xiang CHEN
Published: July 2021

Based on the Test.lab modal test system of the Belgian LMS company, the three-phase asynchronous motor of the swing test bench is tested and analyzed, and the reliability of the motor is verified by using the vibration data of the motor collected under the swing condition by spectrum analysis.
The Modal Analysis of the parallel bars of the crankshaft of a Mini Air Compressor on ANSYS
Authors: Qu Zhenzhen
Published: July 2021

As an important part of the air compressor, the crankshaft is subjected to complex loads and it is important to analyze the adaptability of the crankshaft to the environment. To solve this problem, we must first understand the inherent characteristics of the crankshaft, and modal analysis is an important means to understand the inherent characteristics of the part. It is used to determine the vibration characteristics of the design mechanism or machine components, that is the natural frequency and vibration mode of the structure. They are important parameters in the design of dynamic load mechanisms and the starting point for other dynamic analysis problems.
Application of portable measuring equipment in the field of industrial measurement
Authors: Hu Chang’an , Xing Rui , Hu Song , Li Jiangang
Published: July 2021

With the continuous improvement of measurement requirements, the changing and immovable characteristics of the measured object, the application of portable measuring equipment is gradually increasing. The paper takes the bearing platform, flat plate, industrial robot, fixture, leveling rod verification device and complex system as the typical application cases. This paper presents the multiple applications of three kinds of portable measuring equipment: laser tracker, laser interferometer and joint arm coordinate measuring machine.
Mask R-CNN-based Cat Class Recognition and Segmentation
Authors: Dai Yile , Liu Yunqing , Zhang Siyuan
Published: July 2021

Aiming at the low accuracy of the traditional Mask R-CNN applied to the image segmentation of different cats, an improved Mask R-CNN recognition and segmentation algorithm was proposed. The third channel of the FPN feature extraction path is added to obtain more comprehensive feature information, improve the accuracy of the segmentation mask and reduce the training time. The experimental results show that the method achieves 87.54% segmentation accuracy on the Kaggle dog and cat classification detection dataset, which is 13.57% better than the accuracy of the traditional Mask R-CNN algorithm on the same dataset, and has better detection and segmentation performance, providing a new method for the study of instance segmentation.
Bridge Temperature Prediction Model Based on Long-Short Term Memory Neural Network
Authors: Shu Jingxiao , Zhao Dongyue , Zheng Xuda , Li Yiwen , Zhang Yufeng
Published: July 2021

Based on the pavement temperature data of Sutong Bridge, a prediction model based on Long-Short Term Memory neural network was proposed and optimized in this study, in an effort to improve the prediction and early warning reliability of bridge state. Next, sufficient time was guaranteed for the sake of fault processing by dividing the data model into three parts: observation window, warning window and prediction window. The experimental results show that in comparison with the traditional time series prediction model, the proposed prediction model based on LSTM network is more accurate in the peak prediction, and it can effectively reduce the occurrence of false early warning. Moreover, the comparison results of root mean square error manifest that the proposed model displays a better stability in the long-term prediction.
Red wine quality prediction through active learning
Authors: Tingwei Zhou
Published: July 2021

General machine learning requires a large number of training samples, meaning a lot of manpower and material resources. To solve this problem, active learning and its algorithms are often used. Active learning is a form of semi-supervised machine learning where the algorithm can choose which data it wants to learn from and then use the smallest and most effective labeled data set to make predictions or classifications. This article will show an example of using active learning to predict red wine quality. The predictive modeling approach the author chose was the K-Nearest Neighbor and the active learning algorithm was ranked batch-mode sampling. By observing the learning curve, the author found that generally the prediction accuracy of active learning would increase as the number of iterations increased. The author compared the experiment with another case using classic iris flower data set, and concluded that the prediction accuracy of active learning for different data sets depends on many factors, such as the correlation between the independent and dependant variables, the size of the data set and the number of iterations.
Research on Intelligent Inspection Method of Transmission Channel Satellite Remote Sensing Environmental Changes
Authors: Yang Zhi , Li Mengxuan , Liu Bin , Wang Shenghe , Gao Yun , Huang Jie , Zhao Binbin , Luo Meng
Published: July 2021

With the shortage of transmission channel resources and the increase of human activities, the inspection of transmission channel environment changes is of great significance to the protection of line breakage, the management of transmission channel resources and the detection of hidden dangers in advance. In order to explore a fast and intelligent extraction method of environmental change information in the transmission channel, this paper takes a transmission line section in Tongzhou District of Beijing as the experimental area, takes two high-resolution satellite images of Beijing No.2 as the data source, and conducts principal component analysis and vegetation index processing analysis on the two satellite image data. An intelligent patrol method for transmission channel environmental change based on multi-source feature multi-scale segmentation technology and object-oriented classification algorithm is proposed. The results show that the satellite remote sensing environmental change intelligent patrol method proposed in this paper is sensitive and effective to the human activity change patrol of the transmission channel, and can be extended to the large-scale and normal intelligent patrol operation of the transmission channel against external breach.
Application of Digital Media Interactive Technology in Post-production of Film and Television Animation
Authors: Li Feng , Wang Zhihong
Published: July 2021

With the improvement of domestic economic level and the development of high-tech technology, many computer technologies, image processing technologies, digital media technologies, etc. are constantly developing and becoming more and more popular. Among them, digital media technology has spread to all fields of society, and at the same time, the influence brought by digital media technology is constantly increasing and expanding. With the development of digital media technology, many works of art and works expressed in art form have gradually become diverse, adding many new tricks to the art world and enriching the expression and presentation types of works of art to a great extent.
Research on The Construction Form of Internet of Things Data Information Platform
Authors: Pan Guangyang
Published: July 2021

When the Internet of things system is applied, it is necessary to build a data information platform. The perception layer devices, intelligent terminals and network terminal devices are connected to form the system platform, and the corresponding software is installed on the software management information platform to manage the data of the Internet of things system. We set up a data and information processing software platform to achieve the tasks and objectives of the Internet of things system. The data collected by the perception layer is calculated, stored, classified, analyzed, mined and understood, and the data of the perception layer is analyzed. So as to achieve the purpose of real-time control, accurate calculation, accurate management and scientific decision-making of the Internet of things system. Through the intelligent man-machine interface, the Internet of things smart grid, environmental monitoring, warehousing and logistics, industrial control, smart supermarket, smart medical, smart home, smart agriculture and extended function access can be realized.
Fixed-Time Neural Control for Hypersonic Flight Vehicles with Asymmetric Time-Varying Constraints
Authors: Dong Zehong , Li Yinghui , Xu Haojun , Li Zhe , Pei Binbin , Zheng Wuji
Published: July 2021

This paper presents a novel fixed-time adaptive tracking control scheme for the hypersonic flight vehicles (HFVs) subject to asymmetric time-varying constraints, uncertain dynamics and unknown external disturbances. By incorporating the back-stepping technique and radial basis function neural networks (RBFNNs), the uncertain dynamics of HFVs are estimated. Note that most existing results only achieve practical fixed-time stability but not fixed-time stability, or require specific knowledge of all the dynamics of HFVs. To remove such restrictions, a fixed-time controller is newly constructed by means of a tuning functions and a projection operator-based adaptation mechanism. In consequence, the tracking errors can asymptotically converge to the preassigned compact set within fixed-time and the asymmetric time-varying constraints of HFVs never are violated. Finally, the effectiveness and superiority of the proposed control strategy is demonstrated by numerical simulations.
Ranking links in a combat network based on mission
Authors: Zhang Hao , Yang Zhiwei
Published: July 2021

In this paper, a practical method and process for evaluating the importance of the links in combat system oriented to soft killing is proposed, which fully considers the current mission requirements faced by combat commanders, and integrates the theory of operation loop. Decision makers can easily use this assessment method to prioritize communications link upgrades for combat systems. Firstly, the network model of the combat system is constructed by analyzing the structure of the combat system and the correlation between the components. Secondly, the subtask composition and relevant information of the mission needed to be executed by the current combat system are analyzed, and the evaluation index of mission participation on the link is introduced. Then, the combat capability evaluation method of combat system based on operation loop is used for evaluating the influence degree of combat network link on the survivability of combat system. Finally, the importance degree of link is analyzed and evaluated by combining these two indexes, and the key communication links between entities within the combat system are found by using these two indexes as evaluation indexes.
Application of Virtual Reality Technology in the Maintenance of Steam Turbine
Authors: Pan Zijie , Sun Hairong , Li Li
Published: July 2021

Traditional steam turbine maintenance work has many shortcomings, such as poor effectiveness, high cost, and long cycle. In order to solve this problem and improve the professional skills and maintenance efficiency of steam turbine maintenance personnel, we first collect steam turbine equipment drawings and 3D dimension data of parts, and use 3D modeling software to establish augmented reality scene model. Then combined with the virtual reality technology and image fusion technology to realize the maintenance procedure training and maintenance auxiliary guidance of the steam turbine unit. The practical application results show that this technology can realize the virtual and real operation of the model by users in augmented reality scenes, bring interactive and immersive experience to operators, and improve the work efficiency of maintenance personnel.
Projected response of global runoff to El Niño-Southern oscillation
Authors: Le Thanh , Ha Kyung-Ja , Bae Deg-Hyo
Published: July 2021

The El Niño-Southern Oscillation (ENSO) is a major mode of interannual climate variability and is expected to affect runoff variations at a global scale. While previous studies focused on the correlation analysis between ENSO and runoff and ENSO-induced amplitude changes of runoff, causal analysis considering the confounding impacts of other major climate modes is lacking. As more extreme ENSO events are projected in the future, it is crucial to enhance our understanding of the impacts of ENSO on global runoff. Here we examine the causal influences of ENSO on runoff over the future period 2015–2100 using outputs from Coupled Modeling Intercomparison Project Phase 6 model simulations. Our analyses account for the possible confounding effects of the Southern Annular Mode, the North Atlantic Oscillation and the Indian Ocean Dipole. We find that the signature of ENSO is detectable in future total runoff over various regions including limited areas in central and eastern Asia, large parts of Southeast Asia, limited areas in the eastern and southern Africa, western and eastern Australia, parts of southern and western North America, eastern Antarctica and large parts of South America. There is a high agreement across models for the causal influences of ENSO over central Asia, the eastern coast of Australia, southcentral North America and South America. Multi-model future projections demonstrate higher impacts of ENSO on total runoff over western and central Asia, the western coast of North America and southeastern South America compared to the historical period 1915–2000. All regions with substantial ENSO impacts account for 3.6% land-area in historical simulation and this fraction increases to 5.6% in the future scenario. In addition, the results underscore that surface runoff is less sensitive to ENSO compared to total runoff in most regions. These results may have implications for future water management planning based on ENSO.
Tropical cloud-radiative changes contribute to robust climate change-induced jet exit strengthening over Europe during boreal winter
Authors: Albern Nicole , Voigt Aiko , Pinto Joaquim G
Published: July 2021

The North Atlantic jet stream is projected to extend eastward towards Europe in boreal winter in response to climate change. We show that this response is robust across a hierarchy of climate models and climate change scenarios. We further show that cloud-radiative changes contribute robustly to the eastward extension of the jet stream in three atmosphere models, but lead to model uncertainties in the jet stream response over the North Atlantic. The magnitude of the cloud contribution depends on the model, consistent with differences in the magnitude of changes in upper-tropospheric cloud-radiative heating. We further study the role of regional cloud changes in one of the three atmosphere models, i.e. the ICON model. Tropical cloud-radiative changes dominate the cloud impact on the eastward extension of the jet stream in ICON. Cloud-radiative changes over the Indian Ocean, western tropical Pacific, and eastern tropical Pacific contribute to this response, while tropical Atlantic cloud changes have a minor impact. Our results highlight the importance of upper-tropospheric tropical clouds for the regional circulation response to climate change over the North Atlantic-European region and uncertainty therein.
Quasi-inversion of quantum and classical channels in finite dimensions
Authors: Shahbeigi Fereshte , Sadri Koorosh , Moradi Morteza , Życzkowski Karol , Karimipour Vahid
Published: July 2021

We introduce the concept of quasi-inverse of quantum and classical channels, prove general properties of these inverses and determine them for a large class of channels acting in an arbitrary finite dimension. Therefore we extend the previous results of Karimipour et al (2020 Phys. Rev. A 101 032109) to arbitrary dimensional channels and to the classical domain. We demonstrate how application of the proposed scheme can increase on the average the fidelity between a given random pure state and its image transformed by the quantum channel followed by its quasi-inversion.
Getting into hot water: Water quality in tropical lakes in relation to their utilisation
Authors: May L , Aura C Mulanda , Becker V , Briddon C L , Carvalho L R , Dobel A J , Jamwal P , Kamphuis B , Marinho M M , McGowan S , Nandini S , Nyamweya C , Ongore C , Sarma S S S , Wishart M J
Published: July 2021

Over-exploitation of tropical lakes and reservoirs (‘lakes’) causes water quality problems that occur as a result of competing socio-economic demands and the presence of feedback loops within the system that exacerbate the situation. We review well documented case studies from Brazil, India, Indonesia, Kenya, Malaysia and Mexico to examine the effect that changes in water quality and quantity have had on the utilisation of these tropical lakes. By comparing the different approaches used to improve their sustainable management, we have found that nutrient enrichment is one of the most important and widespread water quality problems, causing adverse effects such as algal blooms, nuisance levels of aquatic plants, low oxygen levels and elevated greenhouse gas emissions. These effects restrict the use of these lakes for water supply, fisheries, recreation, tourism and wildlife. We conclude that tropical lakes require better management, urgently, to restore the ecosystem services that they deliver to man and nature. However, to be effective, the development of sustainable management programmes needs to be underpinned by reliable scientific evidence and the results of extensive stakeholder engagement activities. We note that, currently, there is little information available on how tropical lakes respond to management interventions that can be used to guide these activities. Further research is needed to address this knowledge gap.
Study on Hot Spot Detection Algorithm based on K-Means
Authors: ChenghaoDeng  , YuShen  , KanjianZhang
Published: July 2021

Solar energy is a widely used clean energy at present, and it is inexhaustible. As the main power generation device, photovoltaic modules play an important role in solar power generation. Among the various abnormalities of photovoltaic modules, the hot spot effect will not only reduce the power generation efficiency of photovoltaic modules, but even cause fires due to high temperatures. In this paper, k-means algorithm is adopted for photovoltaic hot spot detection. K-means is an unsupervised machine learning clustering algorithm, which clusters the pixel points of the image, and extracting the connected domain with the points with the shape similar to rectangular rectangle in the clustering, that is, obtaining the hot spot area. At the same time, this paper also uses the traditional computer vision MSER algorithm for experiments, compares the MSER algorithm with the K-means algorithm, and draws the conclusion that the traditional computer vision algorithm has low accuracy but high speed. Machine learning algorithms are accurate but fast.
New EOR Technology: Simultaneous Gas Alternating Gas (SGAG) injection
Authors: Edouard Mvomo N. , Dong Pingchuan , Okere Chinedu J.
Published: July 2021

A new oil recovery method known as Simultaneous Gas Alternating Gas (SGAG) injection that is based on the principle of the conventional Simultaneous Water Alternating Gas (SWAG) injection has been proposed in this study. The performance was observed via a simulation process based on data from an oil field of a shale oil reservoir. The effectiveness of SGAG was evaluated through a sensitivity analysis, and by observing its effect on oil recovery factor and ultimate oil recovery. The results of the sensitivity analysis show that (1) SGAG technique will improve the ultimate recovery factor compared to continuous gas injection; (2) Based on gravity segregation between two gases, oil recovery is enhanced; and (3) Because the produced CH4 can be reinjected and based on the availability of CO2, the possible SGAG combination of (CH4 + CO2) is more economically and feasible for a tank of Shale Oil reserve. This study provides a reliable basis for minimizing operating costs per unit CO2 injection volume and insight into cost-effectively enhanced oil recovery (EOR) technique.
Simulaneous Determination of Heavey Metals in 6 Kind of Mineral Water by ICP-MS
Authors: Yu Y D , Zhao M S , Li S G , Li Z Y , Zhu Y
Published: July 2021

A method for simultaneous determination of nine kinds of inorganic elements including Be, B, Ti, Co, V, Ni, Mo, Sb, Ba and Tl in mineral of six different mountains was established by inductively coupled plasma mass spectrometry (ICP-MS). The samples were analyzed directly after equilibration treatment. The results showed that the linearity ranged well among 0-200 ug/L with correlation coefficient above 0.9999.and the limit of detection was 0.03, 0.90, 0.40, 0.07, 0.03, 0.07, 0.06, 0.07, 0.30, 0.10 ug/L。 While the recoveries of spiked samples were between 88-110 % and the relative standard deviation (RSD) were 0 to 0.888 %. The method has simple operation, good reproducibility, no complicated pre-treatment steps, high sensitivity and reliable data, and can provide a reference for scientific selection of drinks to the residents.
Simultaneous multi-location wireless monitoring of sweat lactate trends
Authors: Gillan Liam , Teerinen Tuija , Suhonen Mika , Kivimäki Liisa , Alastalo Ari
Published: July 2021

Wearable device technologies for sweat analytics present a versatile application for monitoring physiological state, which can circumvent the requirement for inconvenient and invasive blood sampling. This paper reports a miniature electrochemical sensor platform for non-invasive and wireless real-time monitoring of lactate in exercise-induced human sweat. The conformal and low profile sensor platform is composed of (a) a flexible electronic readout tag with wireless charging and data acquisition, and (b) a disposable enzymatic amperometric biosensor patch with electrodes fabricated using high throughput roll-to-roll processing. Data were generated in real time from sensor response to lactate in exercise-induced sweat from multiple body regions simultaneously. The biosensor demonstrates current response proportional to lactate at physiological concentration range between 5 and 30 mM. This developed platform can be adapted for sensing of other sweat constituents including ions or metabolites, and therefore advances wearable technology for personalized physiological monitoring
What gets recorded, counts: dementia recording in primary care compared with a specialist database
Authors: Davis Katrina A S , Mueller Christoph , Ashworth Mark , Broadbent Matthew , Jewel Amelia , Molokhia Mariam , Perera Gayan , Stewart Robert J
Published: July 2021

Background

databases of electronic health records are powerful tools for dementia research, but data can be influenced by incomplete recording. We examined whether people with dementia recorded in a specialist database (from a mental health and dementia care service) differ from those recorded in primary care.

Methods

a retrospective cohort study of the population covered by Lambeth DataNet (primary care electronic records) between 2007 and 2019. Documentation of dementia diagnosis in primary care coded data and linked records in a specialist database (Clinical Records Interactive Search) were compared.

Results

3,859 people had dementia documented in primary care codes and 4,266 in the specialist database, with 2,886/5,239 (55%) documented in both sources. Overall, 55% were labelled as having Alzheimer’s dementia and 29% were prescribed dementia medication, but these proportions were significantly higher in those documented in both sources. The cohort identified from the specialist database were less likely to live in a care home (prevalence ratio 0.73, 95% confidence interval 0.63–0.85), have multimorbidity (0.87, 0.77–0.98) or consult frequently (0.91, 0.88–0.95) than those identified through primary care codes, although mortality did not differ (0.98, 0.91–1.06).

Discussion

there is under-recording of dementia diagnoses in both primary care and specialist databases. This has implications for clinical care and for generalizability of research. Our results suggest that using a mental health database may under-represent those patients who have more frailty, reflecting differential referral to mental health services, and demonstrating how the patient pathways are an important consideration when undertaking database studies.
The duties of impartiality, disclosure, and confidentiality: lessons from a London-seated arbitration
Authors: Leung Samuel Yee Ching , Chan Alex Chun Hei
Published: July 2021

Halliburton Company v Chubb Bermuda Insurance Ltd (formerly known as Ace Bermuda Insurance Ltd [2020] UKSC 48 is an important case not only to the UK but also to the international arbitration community for several reasons: first, it examines indispensable duties in international arbitration and for the first time recognises and explicates upon the duty of disclosure at the highest court of the United Kingdom; secondly, it addresses and clarifies key concepts in international arbitration; thirdly, it confirms the objective nature of the test of justifiable doubts which has wider implications for other arbitral forums; fourthly, it illustrates how the duties of impartiality, disclosure, and confidentiality interact with and affect each other and how the key concepts should be applied to this interaction; and finally, it lays down useful guidance for arbitrators. For these reasons, this case deserves close and careful examination. This article aims to explain the significance of the aforesaid and suggests that, in addition to what has been addressed, further judicial explanations are warranted in what other aspects.
Selecting gene features for unsupervised analysis of single-cell gene expression data
Authors: Sheng Jie , Li Wei Vivian
Published: July 2021

Single-cell RNA sequencing (scRNA-seq) technologies facilitate the characterization of transcriptomic landscapes in diverse species, tissues, and cell types with unprecedented molecular resolution. In order to evaluate various biological hypotheses using high-dimensional single-cell gene expression data, most computational and statistical methods depend on a gene feature selection step to identify genes with high biological variability and reduce computational complexity. Even though many gene selection methods have been developed for scRNA-seq analysis, there lacks a systematic comparison of the assumptions, statistical models, and selection criteria used by these methods. In this article, we summarize and discuss 17 computational methods for selecting gene features in unsupervised analysis of single-cell gene expression data, with unified notations and statistical frameworks. Our discussion provides a useful summary to help practitioners select appropriate methods based on their assumptions and applicability, and to assist method developers in designing new computational tools for unsupervised learning of scRNA-seq data.
The role of mTORC1 activation in seizure-induced exacerbation of Alzheimer's disease
Authors: Gourmaud Sarah , Stewart David A , Irwin David J , Roberts Nicholas , Barbour Aaron J , Eberwine Grace , O’Brien William T , Vassar Robert , Talos Delia M , Jensen Frances E
Published: July 2021

The risk of seizures is 10-fold higher in patients with Alzheimer’s disease than the general population, yet the mechanisms underlying this susceptibility and the effects of these seizures are poorly understood. To elucidate the proposed bidirectional relationship between Alzheimer’s disease and seizures, we studied human brain samples (n = 34) from patients with Alzheimer’s disease and found that those with a history of seizures (n = 14) had increased amyloid-β and tau pathology, with upregulation of the mechanistic target of rapamycin (mTOR) pathway, compared with patients without a known history of seizures (n = 20).

To establish whether seizures accelerate the progression of Alzheimer’s disease, we induced chronic hyperexcitability in the five times familial Alzheimer’s disease mouse model by kindling with the chemoconvulsant pentylenetetrazol and observed that the mouse model exhibited more severe seizures than the wild-type. Furthermore, kindled seizures exacerbated later cognitive impairment, Alzheimer’s disease neuropathology and mTOR complex 1 activation. Finally, we demonstrated that the administration of the mTOR inhibitor rapamycin following kindled seizures rescued enhanced remote and long-term memory deficits associated with earlier kindling and prevented seizure-induced increases in Alzheimer’s disease neuropathology.

These data demonstrated an important link between chronic hyperexcitability and progressive Alzheimer’s disease pathology and suggest a mechanism whereby rapamycin may serve as an adjunct therapy to attenuate progression of the disease.
Network-constrained technique to characterize pathology progression rate in Alzheimer’s disease
Authors: Powell Fon , Tosun Duygu , Raj Ashish ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: July 2021

Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer’s disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient’s longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer’s Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject’s degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications.
Presence of dysfunction and myocardial remodeling in patients with premature ventricular complex-induced cardiomyopathy - a cardiovascular MR study
Authors: Kirchgaessner N , Salatzki J , Lugenbiel P , Ochs A , Hund H , Katus HA , Frey N , Giannitsis E , Friedrich MG , Andre F , Scholz E , Ochs MM
Published: July 2021

Funding Acknowledgements

Type of funding sources: None.

Background

Premature ventricular complexes (PVCs) in the absence of underlying structural heart disease are considered to be benign. However, cardiac dysfunction has been observed in patients with a high PVC burden. The characterization of a PVC-induced cardiomyopathy with structural remodeling including myocardial fibrosis and the determination of a specific PVC burden leading to subclinical cardiac dysfunction remains to be determined.

Objectives

We aimed to evaluate cardiac function, remodeling and myocardial fibrosis patterns in patients with PVCs using cardiac magnetic resonance imaging (CMR). Additionally, we aimed to determine a PVC cut-off value leading to subclinical cardiac dysfunction.

Methods

Patients who underwent CMR and 24-hour, 12-lead ECG monitoring (Holter ECG) within six months were retrospectively studied. Patients with evidence of structural heart disease were excluded. The cohort was subdivided based on the number of PVCs in Holter ECG; Group-1 = 0-100, Group-2 = 100-5000 and Group-3 > 5000 PVCs. CMR parameters were extracted from our local databank. Myocardial strain was measured using feature tracking. For quantification of myocardial fibrosis, T1 mapping and late gadolinium enhancement (LGE) were investigated. Z-scores were calculated in order to combine T1 values from a 1.5 and 3Tesla CMR vendor.

Results

443 patients (52 ± 20 years, 45% females) were included in the study. Compared to Group-1, Group-3 revealed a significantly reduced LV-EF, an increased indexed LV-EDV and increased indexed LV-ESV, indicating cardiac dysfunction and LV enlargement. PVCs frequency was inversely correlated with LV-EF (r=-0.23, p < 0.001) and positively correlated with indexed LV-EDV (r = 0.13; p < 0.01). Feature tracking showed significantly higher global circumferential strain (GCS) indicating subclinical dysfunction. Global T1 times were significantly prolonged in Group-3. Elevated global T1 Z-scores were found in Group-2 and Group-3 compared to Group-1. Significantly more intramural LGE was present in Group-2. The PVC cut-off value characterized by reduced GCS was defined by 216 PVCs (AUC = 0.61, p = 0.02). 

Conclusion

CMR revealed cardiac dysfunction, left ventricular enlargement and diffuse myocardial fibrosis in patients with PVC in the absence of structural heart disease. These changes indicate the development of a PVC-induced cardiomyopathy depending on the PVC burden. Interestingly, subclinical myocardial dysfunction was determined at already low PVC frequencies. Further investigations are necessary in order to examine the influence of different origins of PVCs and the development of structural remodeling.
Variant anatomy of the renal arteries with anastomosis variants in kidney transplantation
Authors: Kolsanov A , Nazaryan A , Khakimiy T , Kopaeva N , Kosolapov A
Published: July 2021

Funding Acknowledgements

Type of funding sources: None.

One of the most important tasks of morphology as an integral part of practical medicine is comprehensive development of theoretical knowledge pertaining to the variants and anomalies of the renal arteries anatomy.

One of the main conditions required for the normal functioning and viability of the renal transplant is its adequate perfusion. Due to the variant anatomy of the renal arteries and the presence of several adjacent vessels with which anastomosis can be performed, there are many strategies for arterial allograft anastomosis.

The goal of the study was to identify patterns of variant topography and anatomy of the human renal arteries according to CT angiography with three-dimensional modeling which would be further used to optimize the technique of forming vascular anastomosis during kidney transplantation.

Materials and methods. The study included an assessment of computed tomograms of the abdominal organs of 130 patients, which were used to build three-dimensional models. Morphometry was carried out using the Autoplan and Luch-S programs. Based on the results of the CT scans of the kidneys and renal arteries in patients who underwent kidney transplantation, computer 3D models of the renal artery and arterial renal bed were constructed when anastomoses of the renal artery were performed with:  the external iliac (group I), the internal iliac (group II) and common iliac (group III) arteries, and in the cases of  multiple arteries - during the formation of a common trunk (IIa subgroup) or separate anastomosis with the common iliac artery (IIb). Afterwards, using the Abaqus program, analysis of hemodynamic parameters of intravascular blood flow was conducted, namely: volumetric blood flow rate, partial renal blood flow (the ratio of volumetric blood flow rate to graft weight), visual assessment of the blood flow turbulence.

Results

volumetric renal blood flow in group II (594 cm3/min) and group III (610 cm3/min) was greater than in group I (550 cm3/min); specific renal blood flow in group III exceeded groups I and II by 0.34 cm3/min/g; high turbulence was observed in the anastomosis angle region in groups I and III. The volumetric renal blood flow in subgroups IIa and IIb was 615 and 585 cm3/min respectively, and in the presence of an extra artery extending from the lower pole, a decrease in the linear blood flow velocity in the inferior polar segmental artery was visually assessed. Based on the results of the study, we can conclude that in the presence of a single renal artery, the best perfusion outcome is achieved when performing anastomosis with the common and internal iliac arteries. With multiple kidney arteries, the best perfusion option is obtained when a single renal artery fistula is formed.