bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of Plastic Mould for One-way Valve Seat of Barrel Sailor Pressure Pumping Device
Authors: Zhang Hao , Wang Jianfeng , Chen Zhen , Zhang Jiarui 
Published: March 2023

Abstract
Many plastic products in our lives are produced mainly by special moulds. If there is no good mould, the quality of the product will be significantly reduced. A good set of moulds can reduce labour time and save costs, solve the problem of injection mould in the production of one-way valve seats, make it easy to take off and reduce bubbles, and improve the quality of products. It is of great significance to study and design related moulds. This paper analyzes the process of a one-way valve seat, studies the moulding principle of plastic parts, analyzes the appearance and shape of plastic parts, and optimizes the parting surface design. The reasonable choice of mould frame makes the structure more straightforward to produce and manufacture.
An 8B/10B parallel encoder design for the polarity pre-processing
Authors: Song Siqi , Yin Heguo , Zhao Jianzhong , Zhan Yi , Poechmueller Peter 
Published: March 2023

Abstract
To tackle the high latency and slow encoding speed of 8B/10B encoder circuits in high-speed serial interfaces, a parallel structure for polarity pre-processing based on logic operations is proposed to optimize encoder performance in this article. Firstly, the encoding process is divided into polarity pre-processing and coding two pipeline stages. This method equals each stage’s delay and decreases the coding waiting period. Additionally, the structure employs polarity pre-processing to optimize the critical delay paths into multi-stage heterodyne gates in series. Therefore, the effect of the number of input bytes on the critical delay path can be significantly reduced. The effectiveness of our proposed encoder is demonstrated to encode 4-byte loads by VCS simulation and synthesized using Synopsys’ Design Compiler tool upon the SMIC 65nm process. Results show that a high operating frequency of 909MHz with a 2245.68µm2 footprint area can be achieved. Compared with the cascaded and polarity-selective structures, the proposed framework has advantages in terms of speed and resource usage. These advantages greatly help to meet the high-speed transmission requirement.
Simulation study on the trajectory planning of table tennis robot arm by applying polynomial interpolation algorithm
Authors: Qiang Xugui , Wen Wangde 
Published: March 2023

Abstract
As the table tennis robotic arm is operated, it is easy to have problems such as discontinuity and instability, which lead to a decrease in work efficiency and thus increase the maintenance cost of the machine. Therefore, to improve the stability of the robotic arm, the study constructs the relationship model of the robotic arm linkage of the table tennis robotic arm and solves such difficulties by using a 4-5-4 polynomial interpolation algorithm. The experimental results show that, compared with the traditional 3-5-3 polynomial interpolation algorithm, the 4-5-4 polynomial interpolation is used to achieve continuous and smooth changes of angular displacement, angular velocity, angular acceleration, and torque of the robot, and there is no abrupt change. The 4-5-4 polynomial interpolation algorithm is used to achieve the stability of the robot and smooth operation of the robot arm.
Deep Learning-based Defect Detection Method for Textile Materials
Authors: Yuan Minghang , Gu Juanjuan , Xu Wenwen , Zhao Yao 
Published: March 2023

Abstract
Knitted fabric defect detection is an engineering application based on artificial intelligence and machine vision. This paper introduces the core technologies of fabric defect detection and briefly analyzes and compares them. An attempt is made to design a system for image pre-processing and seam detection using image processing techniques. And experiments on system construction, image pre-processing, image detection and segmentation, and feature extraction are carried out.
Electrical Appliance Recognition Algorithm Based on Neural Network and Kernel Density Estimation
Authors: Zheng Huatong , Liu Yufeng , Zhou Lei 
Published: March 2023

Abstract
With the rapid development of the social economy, the need for social intelligent transformation is increasingly urgent. In order to identify the electrical equipment quickly and accurately and reduce the false recognition rate, we propose a new identification algorithm, which uses the neural network model to pre-identify the connected electrical equipment and then conducts a secondary test through the kernel density estimation model. The experimental results show that the algorithm has a high recognition rate for the trained model and, at the same time, solves the misrecognition problem of the new electrical appliance neural network model in the production environment.
Estimation of State of Charge and State of Health of Marine Lithium Battery based on BP Neural Network
Authors: Zhang Yueying , Guo Yi 
Published: March 2023

Abstract
For the sake of better ensure the safety of a marine system reliability, economy, and power, on the basis of marine lithium battery discharge data, BP neural network is able to grasp the state of charge and health in this battery module. Owing to some stochastic factors of BP neural network weights and limens, the error fluctuates greatly, so a genetic algorithm is lead into improve its results. The improved GA-BP algorithm reduces the error of SOC estimation from 4.2% to 2.3% and of SOH from 0.52% to 0.24%. It indicates that the GA-BP neural network method for forecasting SOC and SOH of the marine battery management system has minor errors and high stability, which is feasible.
High Concurrency Response Strategy based on Kubernetes Horizontal Pod Autoscaler
Authors: Huo Qizheng , Li Chengyang , Li Shaonan , Xie Yongqiang , Li Zhongbo 
Published: March 2023

Abstract
The automatic scaling of resources in the cluster can reduce costs while satisfying resource usage. This is one of the salient features of cloud computing. The current service scenarios are diverse, and the default policy of Horizontal Pod Autoscaling (HPA) is difficult to meet the demand. In the face of high concurrent traffic, the default strategy has the problem of long expansion time and slow speed. Based on HPA, this paper proposes the High Concurrency Response Strategy. It can cope with high concurrency usage scenarios and ensure that services can still be accessed in the face of large traffic concurrency. Compared with the default HPA, the customized HPA strategy reduces the number of service requests by over 20 ms or 19%.
Adaptive Adjustment of Factor’s Weight for a Multi-Sensor SLAM
Authors: Zhu Zihan , Zhang Yi , Wang Weijun , Feng Wei , Luo Haowen , Zhang Yaojie 
Published: March 2023

Abstract
A multi-sensor fusion simultaneous localization and mapping(SLAM) method based on factor graph optimization that can adaptively modify the weight of the graph factor is proposed in this study, to enhance the localization and mapping capability of autonomous robots in tough situations. Firstly, the algorithm fuses multi-lines lidar, monocular camera, and inertial measurement unit(IMU) in the odometry. Second, the factor graph is constructed using lidar and visual odometry as the unary edge and binary edge constraints, respectively, with the motion determined by IMU odometry serving as the primary odometry in the system. Finally, different increments of IMU odometry, lidar odometry and visual odometry are computed as favor factors to realize the adaptive adjustment of the factor’s weight. The suggested method has greater location accuracy and a better mapping effect in complex situations when compared to previous algorithms.
A study of lateral trajectory tracking control under fused slip rate and road random inputs
Authors: Lu Peng , Zhou Yunbo , Zhang Ming 
Published: March 2023

Abstract
To improve the maneuvering stability of uncrewed armored vehicles during emergency steering and obstacle avoidance under high-speed driving conditions in off-road undulating terrain, in this paper, we establish a 7DOF dynamics model based on the time-varying trajectory curvature for the lateral and vertical motion of the spring-loaded mass and the vertical jump of the unsprung mass. Also, we consider two slip motion states with tires in the linear zone and tire slip nonlinear zone based on the Dugoff model and use trip and non-trip rollover under random road input as rollover warning constraint, and conduct flat road DLC test, 20° side slope test, JLTV twisted road respectively by Carsim-Simulink jointly according to NATO double shift line test standard. The improved LTV-MPC algorithm solves the optimal tracking control sequences of 2DOF and 7DOF kinetic models, and the trajectory tracking is completed, compared, and analyzed.
The characteristic of East Kalimantan’s low-rank coal as an adsorbent for Methylene Blue (MB) dye removal from simulated textile wastewater
Authors: Patmawati Y , Shreeshivadasan C 
Published: March 2023

Abstract
As the interest in developing and applying low-cost adsorbents is growing, the purpose of this paper is to introduce East Kalimantan’s low-rank coal as an adsorbent that is abundant in nature but underutilized. This adsorbent was used in a batch adsorption process to remove Methylene Blue (MB) from simulated textile wastewater. The study was conducted at a range of pH values (from 3 to 13) using a variety of low-rank coal adsorbents (60, 80, 100, 120, 140, and 160 mg). Approximately 100 mg/L of MB was added to 100 mL of simulated textile wastewater over 60 minutes using a shaker set to 150 rpm. The pH value and the amount of adsorbent used have a significant effect on removing MB dye. The pH results indicated that the removal of MB dye is relatively constant between pH 3 and 11. However, the removal rate increased when the pH was increased to 12—increased the pH to 13, which resulted in a significant decrease in MB dye removal. Meanwhile, as the adsorbent dosage increased from 60 to 100 mg at pH 12, the removal of MB dye increased and then decreased. At pH 12 and adsorbent dosage of 100 mg, the maximum removal of MB dye was 99.40 %. Thus, East Kalimantan’s low-rank coal is an intriguing alternative for removing MB dye from simulated textile wastewater.
Effect of trace rare earth elements (Ce) on corrosion resistance of high strength steel used for offshore platform
Authors: Xiaoyu Zhang , Ruifeng Dong , Bo Gao , Jiquan Chen , Zhipeng Mu , Weizhe Zhang , Xiong Yang 
Published: March 2023

Abstract
In this study, a high-strength, offshore platform steel, EH420, was used as the original steel. By observing the original austenite morphology, the corrosion resistance of three experimental steels with different rare Earth contents in a simulated marine splash zone was compared and studied using cyclic immersion corrosion and electrochemical corrosion tests. The macro- and micromorphologies of three experimental steels in different cycles of corrosion, as well as the composition of rust layers, were observed and studied by employing an optical microscope, scanning electron microscope (SEM) and X-ray diffraction (XRD). The crystal microstructure of the three experimental of steels was analyzed by EBSD, and the electrochemical behavior of the three experimental of steels after corrosion was analyzed by electrochemical polarization curve and electrochemical impedance spectroscopy. The results show that the trace additions of Ce ( less than 20ppm ) in the steel can refine the grain size, reduce the grain boundary energy, promote the formation of the protective phase α-FeOOH and Fe3O4 of the rust layer, improve the compactness of the rust layer, and reduce the corrosion rate. In addition, the charge transfer resistance ( Rct ) and open circuit potential are increased, and the corrosion current density is reduced. Moreover, the higher the content of Ce is added in the steel, the more obvious its effect.Therefore, the trace additions of Ce improves the corrosion resistance of high strength offshore platform steel.
Lossy SU(1,1) interferometers in the single-photon-pair regime
Authors: Santandrea Matteo , Luo Kai-Hong , Stefszky Michael , Sperling Jan , Herrmann Harald , Brecht Benjamin , Silberhorn Christine 
Published: March 2023

Abstract
The success of quantum technologies is intimately connected to the possibility of using them in real-world applications. This requires the system to be comprehensively modeled including various relevant experimental parameters. To this aim, in this paper, we study the performance of lossy SU(1,1) interferometers in the single-photon pair regime, posing particular attention to the different amount of information contained in the measurement of single counts and of coincidences at the output of the interferometer. To this aim, we derive the classical Fisher information (FI) of both single and coincidence events, and study it as a function of the internal and external losses of the system. Our analysis shows that, in the absence of external losses, the FI of the coincidence events is always higher or equal than the one of single events. On the other hand, in the presence of external losses, the FI of the singles can increase above the one of the coincidences. Moreover, our analysis shows that coincidence measurement can be exploited to partially mitigate the effect of internal losses in the absence of external losses. Finally, comparing SU(1,1) and classical SU(2) interferometers, we find that the former can outperform the classical systems when the internal losses are above 50%.
Preclinical evaluation of ISH0339, a tetravalent broadly neutralizing bispecific antibody against SARS-CoV-2 with long-term protection
Authors: Yang Huabing , Chen Yuxin , Jiang Dongcheng , Feng Xiaoli , Xu Ying , Wei Jiayu , Zou Qingcui , Yang Qiaojiang , Chen Jihong , Jiang Xiaoling , Qin Chunling , Huang Zhenzhen , Wu Chongbing , Zhou Ying , Li Minghua , Yin Liusong 
Published: March 2023

AbstractBackground: Ending the global COVID-19 pandemic requires efficacious therapies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nevertheless, the emerging Omicron sublineages largely escaped the neutralization of current authorized monoclonal antibody therapies. Here we report a tetravalent bispecific antibody ISH0339, as a potential candidate for long-term and broad protection against COVID-19.Methods: We report here the making of ISH0339, a novel tetravalent bispecific antibody composed of a pair of non-competing neutralizing antibodies that binds specifically to two different neutralizing epitopes of SARS-CoV-2 receptor-binding domain (RBD) and contains an engineered Fc region for prolonged antibody half-life. We describe the preclinical characterization of ISH0339 and discuss its potential as a novel agent for both prophylactic and therapeutic purposes against SARS-CoV-2 infection.Results: ISH0339 bound to SARS-CoV-2 RBD specifically with high affinity and potently blocked the binding of RBD to the host receptor hACE2. ISH0339 demonstrated greater binding, blocking and neutralizing efficiency than its parental monoclonal antibodies, and retained neutralizing ability to all tested SARS-CoV-2 variants of concern. Single dosing of ISH0339 showed potent neutralizing activity for treatment via intravenous injection and for prophylaxis via nasal spray. Preclinical studies following single dosing of ISH0339 showed favorable pharmacokinetics and well-tolerated toxicology profile.Conclusion: ISH0339 has demonstrated a favorable safety profile and potent anti-SARS-CoV-2 activities against all current variants of concern. Furthermore, prophylactic and therapeutic application of ISH0339 significantly reduced the viral titer in lungs. Investigational New Drug studies to evaluate the safety, tolerability and preliminary efficacy of ISH0339 for both prophylactic and therapeutic purposes against SARS-CoV-2 infection have been filed.
Evaluation of the Rapid Quidel Sofia 2 Lyme Immunoassay as a First-Tier Test in a Two-Tier Testing Algorithm for Lyme Disease: Comparison to the Zeus ELISA Borrelia VlsE1/pepC10 IgG/IgM Assay Followed by Immunoblot
Authors: Lewandrowski Elizabeth Lee , Branda John A , Lewandrowski Kent , Turbett Sarah 
Published: March 2023

Abstract

Objectives
Two-tiered serologic testing for Lyme disease is usually performed using an enzyme-linked immunosorbent assay (ELISA) as the first-tier test. The Quidel Sofia 2 Lyme test is a relatively new lateral flow method to provide more rapid turnaround time. We evaluated its performance in comparison to an established ELISA method. The test can be performed on demand rather than batching assays in a central laboratory.

Methods
We compared the Sofia 2 assay to the Zeus VlsE1/pepC10 IgG/IgM test in a standard two-tiered testing algorithm.

Results
Comparison of the Sofia 2 to the Zeus VlsE1/pepC10 IgG/IgM showed an overall agreement of 89.9% (κ statistic of 0.750, indicating “substantial agreement”). When the tests were followed by immunoblot in a two-tier algorithm, the agreement was 98.9% (κ statistic of 0.973, indicating “almost perfect” agreement).

Conclusions
The Sofia 2 Lyme test performs well when compared with the Zeus VlsE1/pepC10 IgG/IgM in a two-tiered testing algorithm.
8(R)-Hydroxyeicosapentaenoic acid (8R-HEPE) induces transcription of cholesterol efflux receptors via activation of liver X receptor in macrophages
Authors: Yamada Hidetoshi , Uemura Aiko , Miyasaka Raimu 
Published: March 2023

ABSTRACT
Dyslipidemia is a risk factor for the development of atherosclerotic cardiovascular disease. 8-Hydroxyeicosapentaenoic acid (8-HEPE) from North Pacific krill (Euphausia pacifica) is known to reduce plasma low-density lipoprotein (LDL) cholesterol levels and increase plasma high-density lipoprotein cholesterol levels in LDL receptor knock-out mice fed a western diet. Moreover, 8-HEPE also reduces the area of aortic atherosclerosis in apoE knock-out mice fed the same diet. In this study, we examined the stereochemical-specific activity of 8-HEPE for inducing expression of cholesterol efflux receptors (Abca1 and Abcg1) in J774.1 cells. Our findings show 8R-HEPE induces the expression of Abca1 and Abcg1 via activation of liver X receptor, whereas 8S-HEPE elicits no such activity. These results suggest that 8R-HEPE derived from North Pacific krill may have beneficial effects against dyslipidemia.
promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling
Authors: Ranathunge Chathurani , Patel Sagar S , Pinky Lubna , Correll Vanessa L , Chen Shimin , Semmes O John , Armstrong Robert K , Combs C Donald , Nyalwidhe Julius O 
Published: March 2023

AbstractSummaryWe present promor, a comprehensive, user-friendly R package that streamlines label-free quantification proteomics data analysis and building machine learning-based predictive models with top protein candidates.Availability and implementationpromor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN) (https://CRAN.R-project.org/package=promor) and distributed under the Lesser General Public License (version 2.1 or later). Development version of promor is maintained on GitHub (https://github.com/caranathunge/promor) and additional documentation and tutorials are provided on the package website (https://caranathunge.github.io/promor/).Supplementary informationSupplementary data are available at Bioinformatics Advances online.
The hypokalaemia that came from the cold
Authors: Elsayed Mohamed E , Schick Benedikt , Woywodt Alexander , Palmer Biff F 
Published: March 2023

ABSTRACT
While electrolyte disorders are common in nephrologists’ clinical practice, hypothermia is a condition that nephrologists rarely encounter. Hypothermia can induce several pathophysiological effects on the human body, including hypokalaemia, which is reversible with rewarming. Despite growing evidence from animal research and human studies, the underlying mechanisms of hypothermia-induced hypokalaemia remain unclear. Boubes and colleagues recently presented a case series of hypokalaemia during hypothermia and rewarming, proposing a novel hypothesis for the underlying mechanisms. In this editorial, we review the current knowledge about hypothermia and associated electrolyte changes with insights into the effects of hypothermia on renal physiology.
Ransomware Detection by Distinguishing API Call Sequences through LSTM and BERT Models
Authors: Lin Tu-Liang , Chang Hong-Yi , Chiang Yuan-Yao , Lin Shu-Cheng , Yang Tsung-Yen , Zhuang Chun-Jun , Tseng Wha-Lee , Zhang Bo-Hao 
Published: March 2023

Abstract
Nowadays, ransomware evolved rapidly and the prevention of ransomware has become an important issue. The threat of ransomware is much more sophisticated than before for governments and enterprises; breaches or corruption of sensitive data will cause huge impact on the organization. Early detection is one of the effective method to prevent the ransomware attack. Modern ransomware detection technologies can be divided into two categories: static analysis and dynamic analysis. Dynamic analysis observes the behavior of the running program. Previous research adopted machine learning approach for dynamic analysis and API sequence dataset were used to trained machine learning models for dynamic analysis. In this research, we collected the API calls of the ransomware from reports generated by Cuckoo Sandbox and proposed two detecting models using BERT and LSTM. The result shows that both BERT and LSTM models can successfully predict ransomware with 95% high accuracy. We aimed to compare the performance of two text-based learning model, LSTM and BERT, and analyze the pros and cons. The result shows that API sequence data can be used to train effective ransomware detection models in text-based manner.
A method based on link prediction for identifying set of super-spreaders in complex networks
Authors: Hosseini Bayan , Veisi Farshid , Sheikhahmdi Amir 
Published: March 2023

AbstractIdentifying a group of key nodes with enormous capability for spreading information to other network nodes is one of the favourable research topics in complex networks. In most existing methods, only the current status of the network is used for identifying and selecting the member of these groups. The main weakness of these methods is a lack of attention to the highly dynamic nature of complex networks and continuous changes in them in terms of creating and eliminating nodes and links. This matter makes the selected group have no proper performance in spreading information relative to other nodes. Therefore, this article presents a novel method for identifying spreader nodes and selecting a superior set from them. In the proposed method, the diffusion power of network nodes is calculated in the first step, and some are selected as influential nodes. In the following steps, it is tried to modify the list of selected nodes by predicting the network variation. Six datasets gathered from real-world networks are utilized for evaluation. The proposed method and other methods are tested to evaluate their spread of influence and time complexity. Results show that using the link prediction in the proposed method can enhance the spread of influence by the selected set compared to other methods so that the spread of influence in some datasets is more than 30$\%$. On the other hand, the time complexity of the proposed method confirms its utility in very large networks.