bluuebunny/crossref_metadata_2025 huggingface dataset:
Optical Simulations on the Surface Plasmon Polaritons Loss & Power Dissipation in Organic Light Emitting Diodes
Authors: Chen Guorui , Duan Jian , Liu Shuai , Yue Guiwen , Qian Min
Published: January 2022

An optical energy loss mechanism including the surface plasmon polaritons (SPPs) loss in organic light-emitting diodes (OLEDs) is introduced based on CPS theory. The theoretical calculations of power dissipation spectrum (PDS), power dissipation map (PDM) and the out-coupling efficiency (OCE) of OLEDs are proposed. MATLAB tools are applied to simulate the optical model and shows that a considerable proportion of SPP loss leads to the low EQE of the OLEDs especially when the distance from the light-emitting boundary to cathode is short, it can even account for up to 40% of the total energy. Wave guide (WG) loss and SPPs loss go aganist vs. distance from the light-emitting boundary to cathode, and there exists a optimized distance of OCE. Study of SPPs losses and power dissipation mechanism provides the theoretical basis to enhance OLED light-emitting efficiency. The OCE calculation results are <20%.
Analysis of Regularized Poisson GLM Spike-Train Modeling
Authors: Fan Yile , Li Yuanpeng , Xue Naiyang , Ding Dan
Published: January 2022

This paper introduces a method for modeling and analyzing neural impulse sequences. In this paper, we define the response value of a scale-independent neuron and construct the correlation graph of the neuron under the response value. The minimum cut algorithm is applied continuously to obtain the maximum group of neurons. According to the characteristics of the firing of neurons, a Poisson-process based model is proposed to mathematically model the neural coding, and the gradient descent method is used to optimize it. Through the modeling analysis method, information such as maximum neuron group and Inter-spike-Interval (ISI) can be effectively analyzed according to neuron impulse sequence.
Strong γc - γcl H∞
Stabilization for Networked Control System Based on Lyapunov Function and DoS Attacks
Authors: Zheng Ying , Zhou Ying
Published: January 2022

This paper is concerned with the strong γc - γcl H∞
stabilization for networked control system under DoS attacks with limited communication bandwidths. The quantizer is employed to the network transmission channel from sensor-to-controller in order to reduce the unnecessary data transmissions. In the network environment, it is assumed that there exist DoS attacks in the transmission channel from controller-to-actuator. By describing DoS attacks as the probability models subject to the Bernoulli distribution, the network control system is modeled as the system with random parameters. With this model, a dynamic output feedback controller is designed, which satisfies the given H∞ bound norm γc
. Under the action of the controller, the closed-loop system is exponential stable in the mean-square sense and satisfies H∞ bound norm γcl
. Especially, a Lyapunov function based on quantization error and attack probability is proposed in the stability analysis. Finally, the effectiveness of the proposed method is verified by a simulation example.
Detection of Auxiliary Equipment in Engine Room Based on Improved SSD
Authors: Qi Jiahao , Zhang Jundong , Meng Qingyan , Ju Jiaming , Jiang Haotian
Published: January 2022

To improve the intelligent operation and maintenance of ships, the research on the perception of engine room auxiliary equipment (A/E) will realize AUTO-0 and replace the engineers. Due to compact layout of the cabin and the different shapes of equipment, the Single Shot MultiBox Detector (SSD) that uses the traditional convolution method for feature extraction cannot adapt to the complex environment. Therefore, an improved A/E detection algorithm based on SSD is proposed. Firstly, we collected the images of actual ships, annotated them manually, and used the K-Means clustering algorithm to analyze them. Secondly, we replaced the classification loss of SSD with the focal loss, balancing the positive and negative samples in the dataset. Finally, we added repulsion loss for the overlapping targets to improve the detection effect of the model against dense occlusion & overlap. The experiment is based on the dataset containing 18185 training object boxes, and 2044 test object boxes, the mean average precision (mAP) in this paper reaches 78.95%, which is 5.63% higher than the original SSD, and the detection boxes are more suitable.
The Application of Reprogramming Technology in a Wireless Sensor Network
Authors: Huang Jianjun
Published: January 2022

Wireless sensor networks can collect physical world information in a large, long-term and real-time manner in a complex environment. Wireless sensor networks have been successfully applied in many fields. With the development of wireless sensor network, wireless sensor network applications need to update the executable code on the sensor due to the change of application requirements. The researchers call this a wireless sensor network application reprogramming, or simply reprogramming. The efficiency of reprogramming is closely related to the size of the updated code that needs to be distributed and the amount of traffic to be distributed. This paper firstly expands the classical logic language based on the characteristics of wireless sensor network, and implements the language by compiling/interpretation, which can generate the smaller update code. Secondly, the paper also makes full use of the location information of the sensor and the data distribution protocol of low message complexity of telecommunication and channel resources. The research results of this paper can effectively reduce the communication volume of the distribution process.
Design and Fabrication of QN9080DK Based Bluetooth 5.0 Fingerprint Lock Controller
Authors: Guo Yong , Xiong Cheng , Wang Yu , Wu Shikai , Luo Le , Fu Qiang
Published: January 2022

The QN9080DK is a development board from NXP specifically for the wireless access market, which has an integrated QN9080 Bluetooth system-on-a-chip (SOC) with an Arm CortexM4F core and a dedicated fusion sensor coprocessor. In this paper, with the help of MCUXpresso integrated development environment (IDE), SDK, CrotexM4F core, Bluetooth 5.0, serial communication, Arduino software and hardware and so on, a Bluetooth fingerprint lock controller is designed and fabricated. The lock controller has the functions of user Bluetooth password access and unlocking, fingerprint entry, fingerprint unlocking and fingerprint permission deletion, etc. After the joint debugging of system software and hardware, the designed Bluetooth Low Energy (BLE) 5.0 fingerprint smart electronic lock controller meets the expected requirements.
Analysis of Group Delay and Phase Delay Algorithms for Short Baseline Interferometry
Authors: Li Dong , Jiao Yiwen , Mao Feilong , Gao Zefu , Ge Pengcheng , Sun Kuanfei
Published: January 2022

As a fast direction finding technology, interferometry has the advantages of simple algorithm and high sensitivity, so it is widely used in various direction finding systems. Short baseline interferometer Angle measurement is the basic principle of phase Angle measuring method, it is using the delay difference between different receiving station in the system to obtain the target azimuth information, has the advantage of high accuracy of Angle measuring, but interferometer is inevitable during the high frequency signal direction finding Angle measuring fuzzy problems exist, in order to solve this problem in general with phase delay method improve the interferometer Angle measurement accuracy, The group delay method is used to deblur. In this paper, group delay and phase delay algorithms are simulated and analyzed, and the simulation results prove the effectiveness of the proposed method.
Structural Optimization Design Based on Improved Ant Colony Algorithm
Authors: Jun Deng Jian , Zhang Lin , Wu Da
Published: January 2022

Ant colony algorithm is a kind of bionic intelligent algorithm, which is suitable for combinatorial optimization. The principle and calculation flow of ant colony algorithm is discussed in this paper, how to use improved ant colony algorithm to solve the optimization problem of truss structure is analyzed, the optimization problem of 13-bar truss structure is calculated. The results show that ant colony algorithm has certain advantages in solving the structural optimization problem with discrete design variables.
Research on Programming Model and Compilation Optimization Technology of Multi-Core GPU
Authors: Chen Liyan
Published: January 2022

GPGPU (General Purpose Computing on Graphics Processing Units) has been widely applied to high performance computing. However, GPU architecture and programming model are different from that of traditional CPU. Accordingly, it is rather challenging to develop efficient GPU applications. This paper focuses on the key techniques of programming model and compiler optimization for many-core GPU, and addresses a number of key theoretical and technical issues. This paper proposes a many-threaded programming model ab-Stream, which would transparentize architecture differences and provide an easy to parallel, easy to program, easy to extend and easy to tune programming model. In addition, this paper proposes memory optimization and data transfer transformation according to data classification. Firstly, this paper proposes data layout pruning based on classification memory, and then proposes Ta T (Transfer after Transformed) for transferring Strided data between CPU and GPU. Experimental results demonstrate that proposed techniques would significantly improve performance for GPGPU applications.
Discrete-Time Modelling to Determine the Possible Operation Points of Incomplete-Resonance Wireless Power Transfer System
Authors: Luo Daqing , Hong Jianfeng , Chen Wenxiang
Published: January 2022

The Independent energy injection and free resonance (IEIFR) system is a type of incomplete-resonance wireless power transfer system, which has a great tolerance with control strategy. This article uses a discrete-time modelling method to determine its all possible and rational operation points. This method samples the state variables with the switching cycle and once the system achieves steady-state, the mapping between those samples is a fixed point mapping. Combined with the known mode analysis, the rationality of those possible operation points can be verified. After the experiment verification, this method is helpful to analysis the incomplete-resonance wireless power transfer system.
Modeling and Simulation of Rock Bits Based on Mega Drilling Data
Authors: Wu Zebing , Jiang Mengjie , Zheng Weixin , Gu Yabing , Zhai Xiping , Yang Chenjuan
Published: January 2022

Rock bits directly undertake the task of fracturing rock under earth during drilling operation. Accurate prediction of Rate of penetration (ROP) play an important role in reducing drilling costs and shortening the drilling cycle. This paper introduces ROP prediction methods including empirical mathematical modeling, computer simulation of bit-rock interaction and BP neural network model based on mega drilling data. The most significant factors affecting ROP are summarized as follows: weight on bit(WOB), rotation speed, rock formation properties, bit cutting structure, etc., which have a complex multi-parameter nonlinear relationship with ROP. The drilling data features complexity and big volume. Therefore machine learning is a best way to model the relationship between main factors and ROP. The advantages and disadvantages of the different ROP modeling methods are analyzed and compared. It shows that the BP neural network model based on mega drilling data demonstrates high accuracy, and is the future development direction in ROP prediction.
Modeling of Film Formation in Airless Spray
Authors: Yang Guichun , Chen Yan , Chen Shiming , Zhang Fei
Published: January 2022

Aiming at the spraying process of airless atomization spraying, a coating film forming model based on Euler-Lagrangian method is proposed. A Rosin-Rammler atomization model was established. In the spraying model, for the discrete phase, a force balance equation is established. At the same time, a continuity equation and a momentum equation are established to describe the motion of the continuous phase. The momentum equation of the continuous phase is closed by the standard k-ε model. The continuity equation and momentum equation are established in the adhesion deposition model to solve the coating thickness. PC-SIMPLE algorithm was used to solve the model. Finally, the dynamic spraying simulation is verified through experiments, and the numerical simulation results are in good agreement with the experiments as a whole. It is proved that the film forming model can be used to predict the film forming results of airless spraying.
Grid Data Inventory Model Based on Improved Redundancy Elimination and Label Extraction
Authors: Chen Ming , Ding Xue , Yuan Limin
Published: January 2022

In view of the difficulty of data inventory caused by the large amount of accumulated data of the current grid business data, multiple data sources, and complex data, this paper proposes a data inventory scheme for structured data and unstructured data. Firstly, this paper uses the YOLOv3 deep learning network to label unstructured data to convert unstructured data into structured data; Secondly, the Semantic Hypergraph Clustering (SHC) method is used to realize the identification of the same entity of the power grid data and the elimination of redundancy. This method introduces semantic information in the block; Finally, in the comparative experiments of AR and RR, 96.88% and 95.03% respectively verify the effectiveness of the scheme.
A Novel Method of Parallel Computing Based North-Finding of the Satcom-On-The-Move System and Its Simulation
Authors: Han Lei , Li Guangxia
Published: January 2022

This paper presents a new north-finding method of the Satcom-On-The-Move (SOTM) system based on parallel computing. The characteristic of this method is that sets a range for the existence of north-pointing true value according to a piece of initial north-pointing information, selects several equally divided north-pointing value within this range. Take the value of each point as multiple initial north-pointing information, then calculate the position information accumulated over time, and compare the calculated position information with the position information obtained by the Global Navigation Satellite System (GNSS). Gradually reduce the value range of the true value of the north-pointing information until the position information obtained with the GNSS is less than a certain error range, then the initial north-pointing information value of the minimum error is obtained, which is approximately equal to the accurate value of the north-pointing information. The proposed algorithm is verified by a simulation case, and the simulation results show the effectiveness of the proposed algorithm.
A State Evaluation Method of Equipment Based on Safe Operation State Space Extraction with Zero-failure Data
Authors: Li Pan , Wei Chaofan , Chang Runfeng , Liu Anying , Zhou Shenghan
Published: January 2022

For high reliability equipment and newly designed products, it is difficult to accurately evaluate the equipment status because almost no failure data will be generated during testing or using period. At present, the analysis of zero fault data mainly focuses on reliability estimation and unsupervised fault detection, and there is little research on the safe operation state of equipment to evaluate whether the equipment is in normal state. In this paper, we propose an equipment state evaluation method based on safe operation state space extraction, and verify the feasibility of this method through real data experiments. This method uses algorithms such as LOF (local outlier factor) and k-means algorithm to extract the parameter range of normal operation of the equipment from the historical zero-failure operation data, so as to judge whether the equipment is in a safe operation state. Compared with other methods, this method is simple and easy to use, and has wider applicability and stronger interpretability.
Adaptive Climbing Gait Design of Snake Robot Based on Extended Kalman Filter
Authors: Han Siwei , Xiao Wenyu , Yu Zheng-hong , Wei Wu
Published: January 2022

We propose a method of climbing pipe with different diameter, which enables snake robot to divide itself into 3 parts to complete transition on the pipe according to the joints’ state for now. To avoid controlling the robot from building dynamic model, a gait-based open-loop control framework is adopted. An extended kalman filter (EKF) is applied here to estimate the adaptive parameter of gait-based function for different 3 parts and corresponding joints. The adaptive parameter will help snake robot perceive the environment better and climb the pipe more steadily.
Theoretical Study on Dynamic Load of Harvester
Authors: Cao Shukun , Zhao Jingyuan , Chen Naijian , Shangguan Zechao , Wang Hongbin
Published: January 2022

This paper studies the dynamic load problem of the harvester, establishes the mathematical model of the load change of the harvester, also studies the coupling and decoupling of the dynamic load of the harvester, and establishes the coupling model to finally understand the load change before and after the coupling.
Research on Key Technologies of Hypersonic Vehicle
Authors: Wang Yuan , Wang Jian , Liu Chuansheng , Tian Ju
Published: January 2022

Hypersonic technology is an interdisciplinary research field, which has become the commanding point of new technology in the current aerospace field. Hypersonic vehicle is an important weapon to deal with future war and break through the missile defense system. It has great strategic deterrence significance in the military. This paper introduces the key technologies of hypersonic vehicle, such as integrated aerodynamic configuration, propulsion technology, thermal protection technology, navigation and control technology. The research status, main problems and development trends of various key technologies are summarized.
Optimal Control of Bearingless Switched Reluctance Motor Based on High Frequency Pulse Injection
Authors: Wang Hao , Yang Yan
Published: January 2022

The start and commutation of the bearingless switched reluctance motor are all through the real-time position detection of the motor rotor, while the traditional position detection relies on the displacement sensor to obtain an accurate position signal, but also brings many drawbacks and shortcomings. The first is to increase the hardware cost and reduce the economy of the system; the vibration of the motor and the vibration of the external environment may cause the sensor to loosen and fall off, reducing the reliability of the system; the harsh working environment such as high dust, high temperature, high humidity will affect the accuracy of the displacement sensor, or even damage it, reducing the environmental adaptability of the system. In order to solve this problem, this paper proposes an optimal control method without a position sensor, and compares it with the existing high-frequency pulse injection method to verify the effectiveness and feasibility of the proposed method.
Research on Monitoring Algorithm and Induction Trigger System of New Spectrophotometer
Authors: Tang Lili , Ma Hongkun
Published: January 2022

In the traditional laboratory engineering bacteria culture work, it is necessary to frequently sample the bacterial solution and judge the growth period by photometric method. These operations are accompanied by pollution risk and the change of culture environment. In this paper, a design scheme of illumination monitoring algorithm of new spectrophotometer based on single chip microcomputer is proposed, The absorbance value is calculated by single chip microcomputer and the threshold is preset to trigger the induction action, so that the whole process from the beginning of culture to the triggering induction of engineering bacteria can be intelligent, automatic and non-contact. The new spectrophotometer takes STM32F103 series processor as the main control chip, and the system is mainly composed of main control board and induced action trigger device. The main control board mainly includes optical density calculation, 12 LED light control, 12 action machine control and human-computer interaction module; The induced action trigger device is composed of motor, bh1750 module, monochrome light source and other parts, which can realize illuminance detection, absorbance calculation, preset absorbance value and trigger the action machine. The system automatically adjusts the working mode of the sensor through the matrix keyboard input, displays the image through a liquid crystal display, uses the bh1750 illuminance sensor module to convert the input illuminance signal into electrical signal for wired output, processes the sensor data through MCU, performs logical operation with the preset value and performs corresponding action. The main control part of the system is small, and the detection method is simpler and faster than the traditional detection. The logic operation part is cleverly designed, the trigger time of the induced action is flexible and adjustable, and there is an adjustable timer after the induced action is triggered.
Research on Train Dynamic Coupling Strategy Based on Distributed Model Predictive Control
Authors: Yang Yiming , Yan Fei
Published: January 2022

This paper mainly studies the problem of dynamic coupling under multiple optimization objectives and multiple constraints. Virtual coupling (VC), as a new train operation mode, effectively improves the operating efficiency of the line, but reduces the safety margin between trains, and requires higher control accuracy. As an important scenario of virtual coupling, dynamic formation has not formed a set of applicable train control strategies. Aiming at the dynamic train formation scenario of virtual coupling, propose a control architecture based on distributed model predictive control (DMPC). Numerical simulation using Matlab verifies the effectiveness of the algorithm in this paper. The simulation results show that the train is under the condition of satisfying the operating constraints. Compared with PID control, the method in this paper is more effective and more accurate.
Study of the wear parameters of the physic-chemical and exploitation indicators of the engine oil when it is supplied with biofuel
Authors: Besleaga I , Gadibadi M
Published: January 2022

The research seeks to provide the most effective techniques and methods that were used in the Laboratories of the Faculty of “Agricultural Engineering and Auto Transportation” (Department of Auto Transportation and Tractors Engineering). It provides the results of the investigation concerning on assessment of the change of physical-chemical and exploitation properties of petroleum products during engine operation and the results for testing internal combustion engines.
Photovoltaic system for E-Smart electric vehicle
Authors: Tarulescu Radu , Tarulescu Stelian , Leahu Cristian , Olaru Marius
Published: January 2022

The vehicles relied on fossil fuels are rapidly being replaced by electric and plug-in hybrid vehicles. But these types of vehicles are still faced with the problem of energy availability. The abundance of solar radiation and its use as the power source in electric vehicles is a necessary condition for environmental pollution limitation. In this study, the authors present photovoltaic systems used as an electricity supply for E-Smart electric vehicles. E-Smart is an electric vehicle obtained through conversion, of a Smart ForTwo City vehicle, from the internal combustion propulsion system to a system that uses a three-phase asynchronous motor supplied from a pack of 32 batteries of LiFePO4 type.
Comparative numerical evaluation of ECE-EUDC cycle performances of a hypothetical car equipped with three types of propulsion systems: conventional, series hybrid and parallel hybrid
Authors: Ionaş M , Argeşanu V , Lontiş N
Published: January 2022

This publication refers to the studies which were made to a compact car model to observe the behavior of the three drivetrain versions that the car can be equipped with: the version in which the vehicle model is equipped only with a Diesel engine (classic), a plug-in hybrid version with the combustion engine placed in a series circuit (pSHEV) and a second plug-in hybrid variant, where the thermal engine is arranged in parallel (pPHEV) with the electric motor (EM). The study emphasizes the behavior of three different vehicle propulsion systems equipped on the compact car on a standardized road cycle condition defined by the Urban Driving Cycle (UDC) referred as ECE 15 cycle combined with the Extra-Urban Driving Cycle (EUDC). The scope is to set up the three different powertrain systems through numerical modeling and to generate the conclusions based on the simulations results obtained in ADvanced VehIcle SimulatOR (ADVISOR).
Contributions towards improving the displacement and strain responses of an internal combustion engine piston through topology optimisation
Authors: Gaidur M , Pascal I , Rakosi E , Ulian T , Manolache Gh , Talif S
Published: January 2022

State-of-the-art parts require state-of-the-art engineering. On this occasion, in this research paper, contributions towards improving the displacement and strain responses of an internal combustion engine piston are presented. The load case scenario and the topology constraints are established in the beginning. In the following stage, the reference values are defined with the means of an FEA simulation. Afterwards, the topology of the piston is optimised. To quantify the improvements, a comparison analysis was made in the ending part of this paper. This study aims to reduce the displacement and strain responses of an internal combustion engine piston through topology optimisation.
Investigations of pressure field along a channel of a pressure wave supercharger
Authors: Costiuc I , Costiuc L , Chiru A
Published: January 2022

The aim of the paper is a numerical investigation of the evolution of the pressure field along the wave rotor channels of a pressure wave ICE supercharger. In the present literature, most of the studies are considering the fluids as incompressible and inviscid in a 2D field. The present study is using the compressible and viscous terms in the unsteady Lattice Boltzmann method for fluid in a 3D field. The geometry was drawn in CAD software using measurements made on a real model of the CX-93 pressure wave supercharger. The simulation was conducted using a code for native unsteady LBM approach to reproduce data such as pressures, temperature and mass flows, which are usually hard to be measured in a real pressure wave supercharger. The computational domain was modelled as a moving rotational domain with adaptive refinement. Results such as velocity, pressure and temperature field in the rotor channels were obtained for exhaust gas inlet pressure of 0.292 MPa and 721 K temperature at different rotational speeds. The air inlet state considered was: 0,096 MPa and 313 K. The simulated values obtained are similar to the reported experimental results found in the literature showing a good concordance with the model.
New composite polymer sensor for vehicle weighing
Authors: Dontu A I , Rakosi E , Barsanescu P D , Ulian T M
Published: January 2022

The work presented in this paper describes a new concept of the sensor for weighing-in-motion of vehicles. This sensor has small dimensions and can be used for weighing the vehicles. The sensor has four strain gauges, two of them are external and two are embedded into polymer. It’s well known that the influence of temperature can affect the measurement process and also can change the output signal of strain gauges. The hysteresis and linearity graphics of strain gauges are compared in order to establish which one has higher values. The measurements lead to interesting results which are presented in this paper.
Results concerning manufacturing of tubular car components using hydroforming and hydroperforation processes
Authors: Poiana D I , Ionel I , Popa R M , Bordeasu I
Published: January 2022

The purpose of the paper is to highlight the advantages that the automotive industry gains by using hydroforming and hydroperforation processes in automobile manufacturing. In recent years, progress has been made concerning the equipment and tools needed to carry out the hydroforming and hydroperforation processes. As these machines and tools have been perfected and produced on a large scale, becoming cheaper and more cost-effective were main scopes of the development, increasing the mass production, supporting the automotive industry, as well, is another goal. The improvement of the tools used and the equipment determined that these processes have to be extended for a quite large number of components of the vehicle, in the production of large series. A comparative analysis and advantages of the technology are presented regarding the impact on the environment of these processing, hydroforming, and hydroperforation processes, in relation to other traditional processing processes
Corroboration of the data obtained by virtual methods with the real ones in the study of road accidents
Authors: Mihai Clinciu , Stefanita Ciunel
Published: January 2022

Even though the frontal collisions occur in a much larger percentage than the lateral collisions, the lateral collisions consequences can be much more serious than the frontal collisions. This paper is meant to be a study on the importance of crush energy, which determines the mechanism that produces the severity of injuries. Using Newton laws of mechanics, we can discuss about the conservation of energy and linear momentum law which determine the impact force, speed and deformation. After, we compared the obtained data from the laboratory virtual crash tests with the determined values from the polygon experimental tests. Analytical techniques that determine the occupant and vehicle behaviour from this stage allow determining the mechanism that produces the damages and biomedical parameters, which are representative and correspond to the real applications from the practice investigation of the traffic events. The information is extremely useful to expert investigators who activates in the field of traffic events investigation and reconstruction.
A review of road traffic accidents reconstruction methods and their limitations with respect to the national legal frameworks
Authors: Duma Irina , Burnete Nicolae , Todorut Adrian
Published: January 2022

Road traffic accidents are the main issue in terms of public safety among Romania and Europe. Reconstructionists aim to ease their work and to offer results as exact as possible, by using a variety of reconstruction methods, from numerical modelling to software simulations of the collisions in which vehicles are involved. Depending on the conditions of a road traffic event, several methodologies can be used, with proper validation. However, the national legal frameworks may be considered as barriers in using a large variety of reconstruction methods. Therefore, this area of research should be further developed, in order to enlarge experts’ choice, especially in the context of rapid development of the automobile industry.
Air quality analysis on a frequently congested road section
Authors: Mustaţă D M , Popa R M , Ionel I , Balogh R M , Bisorca D , Streinu D R
Published: January 2022

This paper will focus on analysing the air quality on a frequently congested road section in the vicinity of Timisoara, Romania. The placement of the measurement equipment will be made next to a public transport station measuring the extent of different pollutants which affect the well-being of passengers waiting in these stations. The traffic congestion is present due to the unloading from the highway, reduced capacity of only a one lane road and because of the high amount of industrial area workplaces. The results presented will be part of the PhD thesis of the main author.
Nonlinear input transformations are ubiquitous in quantum reservoir computing
Authors: Govia L C G , Ribeill G J , Rowlands G E , Ohki T A
Published: January 2022

The nascent computational paradigm of quantum reservoir computing presents an attractive use of near-term, noisy-intermediate-scale quantum processors. To understand the potential power and use cases of quantum reservoir computing, it is necessary to define a conceptual framework to separate its constituent components and determine their impacts on performance. In this manuscript, we utilize such a framework to isolate the input encoding component of contemporary quantum reservoir computing schemes. We find that across the majority of schemes the input encoding implements a nonlinear transformation on the input data. As nonlinearity is known to be a key computational resource in reservoir computing, this calls into question the necessity and function of further, post-input, processing. Our findings will impact the design of future quantum reservoirs, as well as the interpretation of results and fair comparison between proposed designs.
metaboprep: an R package for preanalysis data description and processing
Authors: Hughes David A , Taylor Kurt , McBride Nancy , Lee Matthew A , Mason Dan , Lawlor Deborah A , Timpson Nicholas J , Corbin Laura J
Published: January 2022

Motivation

Metabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterize the data and to exclude errors within the context of the intended analysis. Whilst some preprocessing steps are common, there is currently a lack of standardization and reporting transparency for these procedures.

Results

Here, we introduce metaboprep, a standardized data processing workflow to extract and characterize high quality metabolomics datasets. The package extracts data from preformed worksheets, provides summary statistics and enables the user to select samples and metabolites for their analysis based on a set of quality metrics. A report summarizing quality metrics and the influence of available batch variables on the data are generated for the purpose of open disclosure. Where possible, we provide users flexibility in defining their own selection thresholds.

Availability and implementation

metaboprep is an open-source R package available at https://github.com/MRCIEU/metaboprep.

Supplementary information

Supplementary data are available at Bioinformatics online.
A Chemometric Strategy in the Development of a RP-UPLC Method for the Quantitative Resolution of a Two-Component Syrup Formulation
Authors: Rouhani Ghazal , Ertekin Zehra Ceren , Dinç Erdal
Published: January 2022

A novel chemometric strategy was implemented in the development of a new ultraperformance liquid chromatography method for the quantitative estimation of guaifenesin and pseudoephedrine hydrochloride in a two-component syrup formulation with minimal experimental effort, time and reagent. A full factorial design with three factors was investigated to find optimal working conditions of chromatographic factors (column temperature, flow rate, and 0.1 M H3PO4% in mobile phase) that affect the chromatographic separation. Then, optimum experimental conditions providing adequate separation of the analyzed drug substances within the short runtime were determined. Under optimal experimental conditions, the retention times for guaifenesin and pseudoephedrine hydrochloride were obtained as 0.817 and 1.430 min, respectively. In the optimized RP-UPLC method, chromatographic response was reported as a linear function of concentration between 5.0 and 80.0 μg/mL for guaifenesin and 10.0–90.0 μg/mL for pseudoephedrine hydrochloride. The proposed method was carefully validated and successfully applied to quality control and analysis of a cough syrup preparation containing guaifenesin and pseudoephedrine hydrochloride. Consequently, the proposed reversed-phase ultraperformance liquid chromatography method provided an opportunity to quantify relevant drugs with small amount of reagents and short runtime.
Decreased chronic kidney disease in rheumatoid arthritis in the era of biologic disease-modifying anti-rheumatic drugs
Authors: Hanaoka Hironari , Kikuchi Jun , Hiramoto Kazuoto , Saito Shuntaro , Kondo Yasushi , Kaneko Yuko
Published: January 2022

Background

We investigated the incidence of chronic kidney disease (CKD) progression and its factors relevant to patients with stable rheumatoid arthritis (RA).

Methods

We enrolled consecutive patients with RA who had initiated treatment with a biologic disease-modifying anti-rheumatic drug (bDMARD) at our institution and continued the same drug for >5 years between 2001 and 2016. Patients with CKD at bDMARD initiation were excluded. C-reactive protein (CRP) level, Clinical Disease Activity Index (CDAI) score and estimated glomerular filtration rate were measured every 6 months.

Results

We included 423 patients, with 196 on tumour necrosis factor inhibitors, 190 on tocilizumab and 37 on abatacept. Among these patients, 34 (8.0%) progressed to CKD within 5 years. The mean CRP level and CDAI score over 5 years were significantly lower in patients without CKD progression than in those with CKD progression (P < .001 and P = .008, respectively). Multivariable analysis revealed that age at bDMARD initiation [odds ratio (OR) 1.05, P = .002], non-steroidal anti-inflammatory drug use (OR 3.47, P = .004) and mean CRP >0.14 mg/dL (OR 5.89, P = .015) were independently associated with CKD progression, while tocilizumab use was associated with a decreased risk of CKD progression (OR 0.31, P = .027).

Conclusions

Controlling inflammation contributes to the inhibition of CKD progression in RA patients.
A Transformer Based Encodings for Detection of Semantically Equivalent Questions in cQA
Authors: Kumar Shobhan , Chauhan Arun
Published: January 2022

The probability of redundancy in questions has significantly increased due to the increasing influx of users on different cQA forums such as Quora, Stack overflow, etc. Because of this redundancy, the responses are scattered through various variations of the same question that results in unsatisfactory search results to a specific question. To address this issue, this work proposes the model for discovering the semantic similarity among the cQA questions. We followed two approaches (i) Feature-based: the question embedding is created using four forms of word embeddings and an ensemble of all four. Then Siamese LSTM (sLSTM) is used to find the semantic similarity among the questions. (ii) Fine-tuning: we fine-tuned BERT model on STS and SNLI data, which employs Siamese network architectures to generate semantically meaningful sentence embeddings. Then sBERT is used to assess the similarity between the questions. Experiments were carried out on Quora (QQP) and Stack Exchange cQA dataset with training sets of different sizes and word vectors of different dimensionalities. The model shows significant improvement over the state-of-the-artwork on sentence similarity tasks.
Growth Response of Ponderosa Pine to Intensive Cultural Treatments Varies with Site Quality and Plantation Age
Authors: Zhang Jianwei , Finley Kaelyn A , Young David H , Fiddler Gary O , Looney Christopher
Published: January 2022

Long-term forest experiments provide valuable knowledge in managing forests for productivity and other ecosystem services. California’s “Garden of Eden” experiment was established to determine growth potential of Pinus ponderosa plantations in response to intensive cultural treatments. We examined the 20-year growth-response of tree volume to intensive cultural treatments consisting of combinations of herbicide on competing vegetation (H), fertilization (F), and insecticide (I). We found that both H and F treatments synergistically increased tree growth at intermediate and lower-quality sites. Growth increased by 1.5–2.1 times with F, 2.1–2.5 times with H, and 2.3–3.8 times with HF treatments versus control (range = 39.3–109.2 m3 ha−1). Across the highest productive site, H and F effects on volume seemed additive at younger ages, but largely dissipated by age 20, with volume increasing by 1.6, 1.2, and 1.6 times relative to control in F, H, and HF treatments, respectively. However, 20-year mean annual increment was 21.7 m3 ha−1 yr−1 for the F treatment, the highest volume reported for ponderosa pine in California. The results underscore how site-specific cultural treatments, especially H and F, may widely enhance plantation productivity and boost stand development.

Study Implications

In Mediterranean climates, competing vegetation control is essential for ponderosa pine planation establishment and early growth, especially at intermediate and poor-quality sites. At higher-productivity sites, fertilization enhances stand growth and development, although fertilization’s beneficial effects on growth do not appear until canopy closure. Precommercial thinning in herbicide and fertilization treatments will not reduce overall stand growth 10 years postthinning. Intensively managed plantations appear to have a higher maximum stand density index compared to natural stands or unmanaged plantations. Therefore, these cultural treatments can be used to rapidly reforest areas after disturbances and subsequently promote larger trees on reforested landscapes.
Stability analysis of a standby system with an unreliable server and switching failure
Authors: Gao Chao , Chen Xing-Min
Published: January 2022

This paper is devoted to analysing stability of a standby system with an unreliable server and switching failure, where both the time-to-repair of units and the time-to-repair of server follow general distributions. By employing $C_0$ semigroup theory, we show that time-dependent solution of the system converges to steady-state solution under a rather mild condition. Further, if component’ repair rate and server’s repair rate satisfy a reasonable assumption, then the system is exponentially stable. Based on the above theoretical foundation, some steady-state reliability indices are obtained and total expected profit function per unit time is developed. Finally, a sensitivity analysis with numerical illustrations is also provided.
Variation of the Dyadic Maximal Function
Authors: Weigt Julian
Published: January 2022

We prove that for the dyadic maximal operator $\textrm {M}$ and every locally integrable function $f\in L^1_{{\textrm {loc}}}(\mathbb R^d)$ with bounded variation, also $\textrm {M} f$ is locally integrable and $\mathop {\textrm {var}}\textrm {M} f\leq C_d\mathop {\textrm {var}} f$ for any dimension $d\geq 1$. It means that if $f\in L^1_{{\textrm {loc}}}(\mathbb R^d)$ is a function whose gradient is a finite measure then so is $\nabla \textrm {M} f$ and $\|\nabla \textrm {M} f\|_{L^1(\mathbb R^d)}\leq C_d\|\nabla f\|_{L^1(\mathbb R^d)}$. We also prove this for the local dyadic maximal operator.
Evolution of cefiderocol resistance in Stenotrophomonas maltophilia using in vitro serial passage techniques
Authors: Werth Brian J. , Ashford Nathaniel K. , Penewit Kelsi , Waalkes Adam , Holmes Elizabeth A. , Bryan Andrew , Salipante Stephen J.
Published: January 2022

Objectives

Cefiderocol is a siderophore cephalosporin active against MDR Gram-negatives including Stenotrophomonas maltophilia. Cefiderocol resistance remains uncommon and incompletely understood. We selected for cefiderocol-resistant S. maltophilia in vitro and characterized the genetic mechanisms and potential for cross-resistance to other antimicrobials.

Methods

We selected cefiderocol resistance in three clinical strains of S. maltophilia by serial passage in escalating concentrations of cefiderocol. Emergent cefiderocol-resistant isolates were subjected to repeat susceptibility testing against a panel of relevant antimicrobials. Isolates with confirmed MIC changes were whole genome sequenced.

Results

Each parent strain was initially susceptible to cefiderocol (MICs of 0.03125, 0.03125 and 0.125 mg/L), and one initially tested susceptible to ceftazidime/avibactam (MIC 4 mg/L). We recovered evolved isolates achieving cefiderocol resistance at MICs of 8–32 mg/L from each parental strain. Some cefiderocol resistant isolates reverted following one to four drug-free passages. Ceftazidime/avibactam MICs of passaged isolates repeatedly increased to ≥256 mg/L, and while other MICs were largely unchanged, trimethoprim/sulfamethoxazole MICs declined 4-fold in two strains. WGS revealed one evolved isolate carrying six coding mutations, while four were isogenic mutants of tonB, tolQ, smf-1 and the smeT promoter. Mutation of the smeT promoter downregulated the smeDEF efflux pump and reduced susceptibility to penicillins but increased susceptibility to several other classes including sulphonamides. Other mutations occurred in genes putatively involved in iron metabolism including smlt1148 and cirA.

Conclusions

S. maltophilia strains evolved cefiderocol resistance through different genetic pathways, but often involved iron transport. Future work is required to fully understand the role(s) of other genes in cefiderocol resistance.
Associations of Glycated Albumin and HbA1c with Chronic Kidney Disease in US Adults
Authors: Kim Hyunju , Tang Olive , Rebholz Casey M , Grams Morgan E , Coresh Josef , Christenson Robert H , Selvin Elizabeth
Published: January 2022

Background

Glycated albumin may provide complementary information to hemoglobin A1c (HbA1c). We compared cross-sectional associations of HbA1c and glycated albumin with chronic kidney disease (CKD) in US adults.

Methods

We included 10 923 adults (9955 without diagnosed diabetes, 968 with a diabetes diagnosis) from the National Health and Nutrition Examination Survey 1999–2004. We examined continuous associations and clinical cut points for HbA1c among those without diabetes (<5.0%, 5.0%–5.6% (reference), 5.7%–6.4%, ≥6.5%) and among those with diagnosed diabetes (<7.0%, 7.0%–8.9%, ≥9.0%) and percentile equivalents for glycated albumin. We used logistic regression to compare associations with prevalent CKD, adjusting for traditional risk factors. We used likelihood ratio tests to assess whether adding glycated albumin improved the model with HbA1c.

Results

There were J-shaped associations for both glycated albumin and HbA1c with CKD. Persons without a history of diabetes and very low glycated albumin or HbA1c were more likely to have CKD compared to those without diabetes and normoglycemia. The odds ratios (ORs) for CKD were 1.32 (95% CI, 1.12–1.55) for HbA1c 5.7% to 6.4% and 2.04 (95% CI, 1.28–3.25) for HbA1c ≥6.5%. The ORs for glycated albumin were 1.27 (95% CI, 1.06–1.51) and 2.48 (95% CI, 1.50–4.08) for glycated albumin 14.4% to 17.8% and ≥17.9%, respectively. The inclusion of glycated albumin in the model with HbA1c and traditional risk factors modestly but significantly improved the model fit (P value = 0.006).

Conclusions

Glycated albumin and HbA1c were similarly associated with prevalent CKD. Glycated albumin provides complementary information to HbA1c for prevalent CKD.