bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart Contract Generation Assisted by AI-Based Word Segmentation
Authors: Tong Yu , Tan Weiming , Guo Jingzhi , Shen Bingqing , Qin Peng , Zhuo Shuaihe
Published: May 2022

In the last decade, blockchain smart contracts emerged as an automated, decentralized, traceable, and immutable medium of value exchange. Nevertheless, existing blockchain smart contracts are not compatible with legal contracts. The automatic execution of a legal contract written in natural language is an open research question that can extend the blockchain ecosystem and inspire next-era business paradigms. In this paper, we propose an AI-assisted Smart Contract Generation (AIASCG) framework that allows contracting parties in heterogeneous contexts and different languages to collaboratively negotiate and draft the contract clauses. AIASCG provides a universal representation of contracts through the machine natural language (MNL) as the common understanding of the contract obligations. We compare the design of AIASCG with existing smart contract generation approaches to present its novelty. The main contribution of AIASCG is to address the issue in our previous proposed smart contract generation framework. For sentences written in natural language, existing framework requires editors to manually split sentences into words with semantic meaning. We propose an AI-based automatic word segmentation technique called Separation Inference (SpIn) to fulfill automatic split of the sentence. SpIn serves as the core component in AIASCG that accurately recommends the intermediate MNL outputs from a natural language sentence, tremendously reducing the manual effort in contract generation. SpIn is evaluated from a robustness and human satisfaction point of view to demonstrate its effectiveness. In the robustness evaluation, SpIn achieves state-of-the-art F1 scores and Recall of Out-of-Vocabulary (R_OOV) words on multiple word segmentation tasks. In addition, in the human evaluation, participants believe that 88.67% of sentences can be saved 80–100% of the time through automatic word segmentation.
Typhoon-Induced Fragility Analysis of Transmission Tower in Ningbo Area Considering the Effect of Long-Term Corrosion
Authors: Li Qiang , Jia Hongtao , Qiu Qing , Lu Yongzhu , Zhang Jun , Mao Jianghong , Fan Weijie , Huang Mingfeng
Published: May 2022

The purpose of this paper was to investigate the influence of long-term corrosion on the deterioration of wind resistance of a steel transmission tower during its service life. An analytical model for predicting the long-term corrosion depth of carbon steel was established, and the corrosion depth of carbon steel in the Ningbo area was predicted based on the local atmospheric environment data. With the help of typhoon full-track simulation and wind field simulation technology, a joint probability distribution model of multidirectional extreme wind speeds was constructed using the t-Copula function to determine the typhoon climate of the transmission tower site. Finite element models of the ZM4 cathead transmission tower under 30/60/90 corrosion years were then established, respectively, according to the predicted corrosion depth of carbon steel in Ningbo. Three damage modes, i.e., minor damage, moderate damage and severe damage, corresponding to the transmission tower under wind loads, were defined, and pushover analyses were used to determine the limit values of each damage mode so as to obtain the typhoon-induced fragility curves of the transmission tower within 30/60/90 corrosion years. The results show that the increase in corrosion age leads to a deterioration in the nominal mechanical properties of the transmission tower components, making the damage probability to the transmission tower increase. Under the typhoon wind loads of a 50-year return period in the most unfavorable wind direction in Ningbo, the probability of moderate damage of the tower is within 10% and the probability of minor damage is controlled between 10% and 40%.
A Full Ka-Band CMOS Amplifier Using Inductive Neutralization with a Flat Gain of 13 ± 0.2 dB
Authors: Kim Byungwook , Jeon Sanggeun
Published: May 2022

This paper presents a CMOS wideband amplifier operating in the full Ka-band, with a low gain variation. An inductive neutralization is applied to the amplifier to compensate for the gain roll-off in the high-frequency region. Neutralization inductance is carefully determined considering the tradeoff between stability and gain. To achieve a low gain variation over the full Ka-band, the amplifier employs the frequency staggering technique in which impedance matching for three gain stages is performed at different frequencies of 26, 34, and 42 GHz. The experimental results show that a peak gain of 13.2 dB is achieved at 39.2 GHz. The 3 dB bandwidth is from 23.5 to 41.7 GHz, which fully covers the Ka-band. Especially, the gain ripple of the amplifier is only 13 ± 0.2 dB over a wide bandwidth from 26.2 to 40.2 GHz. The input and output return loss values are better than −10 dB from 26.3 to 40.1 GHz and from 25.3 to 50 GHz, respectively. The DC power consumption is 18.6 mW.
Sports Information Needs in Chinese Online Q&A Community: Topic Mining Based on BERT
Authors: Ning Chuanlin , Xu Jian , Gao Hao , Yang Xi , Wang Tianyi
Published: May 2022

The online Question and Answering (Q&A) community has grown globally, allowing users to ask, discuss, and answer questions based on shared interests. As a gathering place for people’s knowledge production, collaboration, and dissemination in the current Internet scene, the online Q&A community can intuitively reflect the public’s information needs and behavior. It also collects many sports-related data and becomes an effective vehicle for comprehending mass sports information needs and disseminating sports knowledge. However, sports-related studies on the online Q&A community have rarely been reported. This study took the sports information in Zhihu, the largest Q&A community in China, as the research object to explore the public needs for sports information in China. We introduced the BERT model through a self-compiled python program and collected 391,092 sports-topic answers in the online Q&A community of Zhihu. Then, we explored the topic content, evolution trend, and user attributes of these answers. We found that the overall trend of sports information needs in Zhihu can be divided into three cycles: the London 2012 Olympic period, the Rio 2016 Olympic period, and the Tokyo 2020 Olympic period in general. The diversified content of information needs included 40 second-level themes and eight first-level themes. Male and female users had similarities and differences in sports information needs. The male and female users had the same information needs for fitness-related information. However, men were more concerned with confrontational solid sports such as basketball and football; women were more likely to care about weight loss, shape effect, and self-protection while doing sports activities. In addition, compared with men, women preferred to emphasize their gender attributes when expressing their needs for sports information to obtain more practical knowledge. In conclusion, our finding reveals that the sports community formed by the current online Q&A community in China is still a male-dominated information field.
Multimodal Classification of Teaching Activities from University Lecture Recordings
Authors: Sapena Oscar , Onaindia Eva
Published: May 2022

The way of understanding online higher education has greatly changed due to the worldwide pandemic situation. Teaching is undertaken remotely, and the faculty incorporate lecture audio recordings as part of the teaching material. This new online teaching–learning setting has largely impacted university classes. While online teaching technology that enriches virtual classrooms has been abundant over the past two years, the same has not occurred in supporting students during online learning. To overcome this limitation, our aim is to work toward enabling students to easily access the piece of the lesson recording in which the teacher explains a theoretical concept, solves an exercise, or comments on organizational issues of the course. To that end, we present a multimodal classification algorithm that identifies the type of activity that is being carried out at any time of the lesson by using a transformer-based language model that exploits features from the audio file and from the automated lecture transcription. The experimental results will show that some academic activities are more easily identifiable with the audio signal while resorting to the text transcription is needed to identify others. All in all, our contribution aims to recognize the academic activities of a teacher during a lesson.
Bending Behavior of a Frictional Single-Layered Spiral Strand Subjected to Multi-Axial Loads: Numerical and Experimental Investigation
Authors: Zhou Biwen , Hu Yumei , Zheng Xingyuan , Zhu Hao
Published: May 2022

Bending deformation gives rise to interwire slippage for spiral strands subjected to multi-axial loads, and further induces wear or fatigue phenomena in practice. The interwire friction would resist bending deformation and lead to uneven tension distribution of individual constituent wires but little research has quantified these effects. To figure out this issue, a beam finite element (FE) is established, into which a penalty stiffness algorithm and a Coulomb friction model are incorporated. A series of free bending simulations are developed for parametric study on deflection near the terminations and tension distribution of individual wire for strands with different levels of length and friction coefficient as well as external loads. Based on the simulation results, it is found that strand length has little influence on bending deformation and tension distribution if the strand length exceeds six times the pitch length. A deflection formula extended from the classical Euler beam model well predicts the sag deflections and the relative error with respect to experimental measurements is less than 10%. Furthermore, additional axial tension induced by the friction is clearly characterized and an approximate expression is proposed to estimate tension distribution for outer layer wires. Its predictions are encouraging for longer strands.
Research on Influence of Switching Angle on the Vibration of Switched Reluctance Motor
Authors: Ling Xiao , Zhou Chenhao , Yang Lianqiao , Zhang Jianhua
Published: May 2022

Switched Reluctance Motors (SRMs) have emerged as a viable competitor to other established electrical machines. Although SRMs have many advantages, such as a rare earth free nature, simple structure, high fault tolerance capability and low cost, vibration problems due to radial force variations is still a major issue faced by SRMs. Hence, aimed at the problem of vibration suppression for SRMs, this paper proposes a method that focuses on the influence of the change of the turn-on angle and turn-off angle on the vibration of the SRM under the switching angle control (SAC) strategy. Firstly, the influence of the turn-on and turn-off angles on the harmonic components of the current is analyzed in detail. Then, the vibration caused by the frequency of the harmonic components of the current and the natural frequency of the motor is mainly studied. The results show that the harmonic order affecting vibration is related to the rotational speed, and by analyzing the value of this harmonic order, the variation law of vibration with the switching angle can be obtained. When the turn-off angle is constant, the amplitudes of the current harmonic component and vibration first decrease and then increase with the increase of the turn-on angle. Additionally, when the turn-on angle is constant, the current harmonic and vibration show the tendency of periodic oscillation with the variation of the turn-off angle, and the oscillation period is related to the harmonic order. The combination of switching angles that minimizes the certain current harmonic component also minimizes vibration. The effectiveness of the variation law was verified on a 12/8 poles and 1.5 KW SRM drive system test bench, which provide a new perspective on vibration suppression of SRMs.
Buckwheat Disease Recognition Based on Convolution Neural Network
Authors: Liu Xiaojuan , Zhou Shangbo , Chen Shanxiong , Yi Zelin , Pan Hongyu , Yao Rui
Published: May 2022

Buckwheat is an important cereal crop with high nutritional and health value. Buckwheat disease greatly affects the quality and yield of buckwheat. The real-time monitoring of disease is an essential part of ensuring the development of the buckwheat industry. In this research work, we proposed an automated way to identify buckwheat diseases. It was achieved by integrating a convolutional neural network (CNN) with the image processing technology. Firstly, the proposed approach would detect the buckwheat disease area accurately. Then, to improve the accuracy of classification, a two-level inception structure was added to the traditional convolutional neural network for accurate feature extraction. It also helps to handle low-quality image problems, which includes complex imaging environment and leaf crossing in sampling buckwheat image, etc. At the same time, instead of the traditional convolution, the convolution based on cosine similarity was adopted to reduce the influence of uneven illumination during the imaging. The experiment proved that the revised convolution enabled better feature extraction within samples with uneven illumination. Finally, the experiment results showed that the accuracy, recall, and F1-measure of the disease detection reached 97.54, 96.38, and 97.82%, respectively. For identifying disease categories, the mean values of precision, recall, and F1-measure were 84.86, 85.78, and 85.4%. Our method has provided important technical support for realizing the automatic recognition of buckwheat diseases.
A Method for Safety Evaluation of Train Braking System Considering Multiple Types of Preventive Maintenance Cycles
Authors: Zhang Lilei , Guo Linhan , Li Ruiyang , Wang Yu
Published: May 2022

The train braking system with redundant components has an essential effect on driver safety. In this paper, we consider the failure of K-out-of-N brake motors during operation and the redundant recovery by preventive maintenance. Two Continuous Time Markov Chains (CTMC) are used to model the working process and the preventive maintenance process of the braking system corresponding to the real situation of the train. Considering the maintenance effect of intermittent daily and cyclical overhaul with nested relationships, a new operation risk assessment model of the K-out-of-N system is developed to evaluate the effectiveness of the preventive maintenance of the train. Some safety parameters are solved based on the two coupled preventive maintenance periods, which conveniently design the safety of the train braking system. Finally, a case study illustrates the effectiveness of the safety evaluation method. The results show that we can trade off the effects of the multiple PM intervals on train safety considering the redundancy structure of the braking system by the proposed model.
Initiation and Fracture Characteristics of Different Width Cracks of Concretes under Compressional Loading
Authors: Wu Lizhou , Zhou Jianting , Yang Jun , Xin Jingzhou , Zhang Hong , Li Bu
Published: May 2022

A stress concentration at a crack tip may cause fracture initiation even under low-stress conditions. The maximum axial stress theory meets the challenges of explaining the fracture propagation of a non-closed fracture of cracked concretes under compressional loading. Uniaxial loading tests of single-crack concrete specimens were carried out and a numerical simulation of fracture propagation under uniaxial compression was performed. The radial shear stress criterion for a mode-II fracture is proposed to examine the stress intensity factor (SIF) of the pre-crack specimens under compressional loading. When the maximum radial shear stress at the crack tip is larger than the maximum axial tensile stress, and the maximum dimensionless SIFs can satisfy frθmax/fθmax > 1 and frθmax/fθmax > KIIC/KIC (fθmax=KIe/σyπa and frθmax=KIIe/σyπa are maximum dimensionless mode-I and mode-II SIFs, respectively), the crack will extend along the direction of the maximum radial shear stress. The influence of the single-crack angle and width on the mechanical properties of the specimens was examined. The experimental and numerical results indicate that the existence of cracks can considerably weaken the strength of the specimen. The distribution and width of the cracks had a significant effect on the specimen strength. The strength of the concrete specimen initially decreased and then increased with increasing fracture angle. The failure mechanism and rupture angle of pre-crack brittle material while considering crack width will be discovered.
Evaluating 3D Human Motion Capture on Mobile Devices
Authors: Reimer Lara Marie , Kapsecker Maximilian , Fukushima Takashi , Jonas Stephan M.
Published: May 2022

Computer-vision-based frameworks enable markerless human motion capture on consumer-grade devices in real-time. They open up new possibilities for application, such as in the health and medical sector. So far, research on mobile solutions has been focused on 2-dimensional motion capture frameworks. 2D motion analysis is limited by the viewing angle of the positioned camera. New frameworks enable 3-dimensional human motion capture and can be supported through additional smartphone sensors such as LiDAR. 3D motion capture promises to overcome the limitations of 2D frameworks by considering all three movement planes independent of the camera angle. In this study, we performed a laboratory experiment with ten subjects, comparing the joint angles in eight different body-weight exercises tracked by Apple ARKit, a mobile 3D motion capture framework, against a gold-standard system for motion capture: the Vicon system. The 3D motion capture framework exposed a weighted Mean Absolute Error of 18.80° ± 12.12° (ranging from 3.75° ± 0.99° to 47.06° ± 5.11° per tracked joint angle and exercise) and a Mean Spearman Rank Correlation Coefficient of 0.76 for the whole data set. The data set shows a high variance of those two metrics between the observed angles and performed exercises. The observed accuracy is influenced by the visibility of the joints and the observed motion. While the 3D motion capture framework is a promising technology that could enable several use cases in the entertainment, health, and medical area, its limitations should be considered for each potential application area.
Thermal Performance Evaluation of a Tubular Heat Exchanger Fitted with Combined Basket–Twisted Tape Inserts
Authors: Khafaji Hayder Q. A. , Abdul Wahhab Hasanain A. , Alsaedi Sajda S. , Al-Maliki Wisam Abed Kattea , Alobaid Falah , Epple Bernd
Published: May 2022

Features of the tubular type of heat exchanger were examined experimentally in the current study. A rig is fitted with a novel insert as a negative heat transfer increase technique. The core fluid used is air under steady heat flux and a turbulent discharge state (6000 ≤ Re ≤ 19,500) conditions. Two heat transfer augmentation inserts are employed; one is the basket turbulators utilized as a turbulator and placed inside the heat exchanger with a constant pitch ratio (PR = 150 mm), and the other is the basket turbulators together with twisted tape that are installed at the core of the basket turbulators. The measurements illustrated that the Nusselt number (Nu) was found to be higher by about 131.8%, 169.5%, 187.7%, and 206.5% in comparison with the plain heat exchanger for basket turbulators and the combined basket–twisted tape inserts with y/w = 6, 3, and 2, respectively. The highest thermal efficiency factor of the increased tubular heat exchanger is 1.63 times more elevated than that of the simple heat exchanger on average, due to a binary basket-quirky strip for a twisting percentage y/w equal to 2 under steady pumping energy. Further, practical correlations for the Nusselt number, as well as friction characteristics, were established and presented.
Cognitive Diagnostic Assessment in University Statistics Education: Valid and Reliable Skill Measurement for Actionable Feedback Using Learning Dashboards
Authors: Maas Lientje , Brinkhuis Matthieu J. S. , Kester Liesbeth , Wijngaards-de Meij Leoniek
Published: May 2022

E-learning is increasingly used to support student learning in higher education, facilitating administration of online formative assessments. Although providing diagnostic, actionable feedback is generally more effective, in current practice, feedback is often given in the form of a simple proportion of correctly solved items. This study shows the validation process of constructing detailed diagnostic information on a set of skills, abilities, and cognitive processes (so-called attributes) from students’ item response data with diagnostic classification models. Attribute measurement in the domain of statistics education is validated based on both expert judgment and empirical student data from a think-aloud study and large-scale assessment administration. The constructed assessments provide a valid and reliable measurement of the attributes. Inferences that can be drawn from the results of these formative assessments are discussed and it is demonstrated how this information can be communicated to students via learning dashboards to allow them to make more effective learning choices.
Use Electroencephalogram Entropy as an Indicator to Detect Stress-Induced Sleep Alteration
Authors: Lo Yun , Hsiao Yi-Tse , Chang Fang-Chia
Published: May 2022

An acute stressor can cause sleep disruptions. Electroencephalography (EEG) is one of the major tools to measure sleep. In rats, sleep stages are classified as rapid-eye movement (REM) sleep and non-rapid-eye movement (NREM) sleep, by different characteristics of EEGs. Sleep alterations after exposure to an acute stress are regularly determined by the power spectra of brain waves and the changes of vigilance stages, and they all depend on EEG analysis. Herein, we hypothesized that the Shannon entropy can be employed as an indicator to detect stress-induced sleep alterations, since we noticed that an acute stressor, the footshock stimulation, causes certain uniformity changes of the spectrograms during NREM and REM sleep in rats. The present study applied the Shannon entropy on three features of brain waves, including the amplitude, frequency, and oscillation phases, to measure the uniformities in the footshock-induced alterations of sleep EEGs. Our result suggests that the footshock stimuli resulted in a smoother and uniform amplitude as well as varied frequencies of EEG waveforms during REM sleep. In contrast, the EEGs during NREM sleep exhibited a smoother, but less uniform, amplitude after the footshock stimuli. The result depicts the change property of brain waves after exposure to an acute stressor and, also, demonstrates that the Shannon entropy could be used to detect EEG alteration in sleep disorders.
Quality Assurance for Performing Arts Education: A Multi-Dimensional Analysis Approach
Authors: Li Qingyun , Li Zihao (Michael) , Han Jie , Ma Huimin
Published: May 2022

Senior management in tertiary institutions desires an efficient system that could help them assess and evaluate learning outcomes so that effective policies can be implemented to enhance teaching and learning. This gets intensified as broader issues arise and higher expectations are put on tertiary education—build a creative workforce and adapt to new technologies to analyze the large volume of teaching and learning data. Government and higher education policymakers have to rapidly adjust relevant policies to surmount the challenges from the pandemic and also to keep up with technological advancement. This demands a novel and efficient way for policymakers and senior management to see and gain insights from a large volume of data (e.g., student course and teacher evaluation). In this study, the researchers present such a system through various examples. The findings generated from this study contribute to the scholarship, and they provide a solution to senior management in tertiary institutions wanting to implement effective policies efficiently. The use of online analytical processing, virtual campus, online, and machine learning in education is growing. However, the use of these technology-enhanced approaches is rare in performing arts education. There has been no in-depth study, especially on technology-enhanced learning that leads to the improvement of teaching. This study utilizes a multi-dimensional analysis approach on the course student evaluation, a key aspect of the teaching and learning quality assurance for higher education. A novel analytical framework is developed and implemented at a leading performing arts university in Asia. It analyzes the course evaluation data of all courses (669 courses and 2664 responses) in the academic year 2018/2019 to make evidence-based recommendations. Such a framework provides an easy and effective visualization for senior management to identify courses that need closer scrutiny to ascertain whether and what areas of course enhancement measures are warranted.
High-Efficiency Continuous-Wave Ti:Sapphire Laser with High-Intensity Pumping Using a Commercially Available Crystal
Authors: Kawato Sakae , Kawashima Toshiki
Published: May 2022

Despite the importance of improving the efficiency of lasers in order to expand their utility range, the improvement of the efficiency of Ti:sapphire lasers has not progressed due to their high crystal losses. Therefore, we improved the efficiency of CW Ti:sapphire lasers by high-intensity pumping, which is one of the most effective methods of suppressing the efficiency reduction due to losses. Using a easily commercially available 0.25 wt.%, figure of merit (FOM) 200 Ti:sapphire crystal, optics and a pump source, we achieved an optical-to-optical conversion efficiency of 32.4% with a slope efficiency of 42.5% at an incident pump power of 5.0 W which corresponds the maximum pumping intensity of 860 kW/cm2. Furthermore, we ensured the reliability of our theoretical analysis by reproducing the experimental results. From this reliable theory, double-pass pumping and increasing the pump power to 25 W resulted in the highest optical-to-optical conversion and slope efficiencies for the incident pump power of 55.9% and 59.6%, respectively, at a high intrinsic residual loss of 4.0%. Even if losses doubled or deviated from the optimum condition for the highest efficiency, the efficiency reduction due to these factors was only a few percent. These results show that with high-intensity pumping, lasers with efficiencies well exceeding half of the quantum limit can be achieved even if all components, including Ti:sapphire crystals, are easily commercially available.
Identification of Wiener Box-Jenkins Model for Anesthesia Using Particle Swarm Optimization
Authors: Aljamaan Ibrahim , Alenany Ahmed
Published: May 2022

Anesthesia refers to the process of preventing pain and relieving stress on the patient’s body during medical operations. Due to its vital importance in health care systems, the automation of anesthesia has gained a lot of interest in the past two decades and, for this purpose, several models of anesthesia are proposed in the literature. In this paper, a Wiener Box-Jenkins model, consisting of linear dynamics followed by a static polynomial nonlinearity and additive colored noise, is used to model anesthesia. A set of input–output data is generated using closed-loop simulations of the Pharmacokinetic–Pharmacodynamic nonlinear (PK/PD) model relating the drug infusion rates, in [μgkg−1min−1], to the Depth of Anesthesia (DoA), in [%]. The model parameters are then estimated offline using particle swarm optimization (PSO) technique. Several Monte Carlo simulations and validation tests are conducted to evaluate the performance of the identified model. The simulation showed very promising results with a quick convergence in less than 10 iterations, with a percentage error less than 1.5%.
Functionalities, Benchmarking System and Performance Evaluation for a Domestic Service Robot: People Perception, People Following, and Pick and Placing
Authors: Basiri Meysam , Pereira João , Bettencourt Rui , Piazza Enrico , Fernandes Emanuel , Azevedo Carlos , Lima Pedro
Published: May 2022

This paper describes the development of three main functionalities for a domestic mobile service robot and an automatic benchmarking system used for the systematic performance evaluation of the robot’s functionalities. Three main robot functionalities are addressed: (1) People Perception, (2) People Following and (3) Pick and Placing, where the hardware and software systems developed for each functionality are described and demonstrated on an actual mobile service robot, with the goal of providing assistance to an elderly person inside the house. Furthermore, a set of innovative benchmarks and an automatic performance evaluation system are proposed and used to evaluate the performance of the developed functionalities. These benchmarks are now made publicly available and is part of the European Robotics League (ERL)-Consumer to systematically evaluate the performance of service robot solutions at different testbeds around Europe.
Double-Cycling AGV Scheduling Considering Uncertain Crane Operational Time at Container Terminals
Authors: Zhang Hongchang , Qi Liang , Luan Wenjing , Ma Huijuan
Published: May 2022

Container terminals (CTs) play an important role in the modern logistics and transportation industry. The utilization of automated guided vehicles (AGVs) can be effectively facilitated by reducing their empty running. The existing strategies cannot guarantee the full load of AGVs during their transportation because of the complex constraints of container scheduling. This work proposes a double-cycling AGV scheduling model that ensures a full load of AGVs between the quayside and the yard. The objective is to minimize the total waiting time of AGVs and ensure a high loading rate of AGVs by scheduling loading/unloading containers. Furthermore, it takes the randomness of the quay crane’s operational time into consideration. By assigning a time interval to AGVs’ arrival at a quayside, a container scheduling sequence is obtained based on a Hybrid Particle Swarm Optimization (HPSO) algorithm with a penalty function. Via experiments, it shows that the proposed model can obtain the least number of AGVs for container transportation, minimize AGVs’ total waiting time, and ensure the high loading rate of AGVs.
Method of Optical Diagnostics of Grain Seeds Infected with Fusarium
Authors: Belyakov Mikhail V. , Moskovskiy Maksim N. , Litvinov Maksim A. , Lavrov Aleksander V. , Khamuev Victor G. , Efremenkov Igor Yu. , Gerasimenko Stanislav A.
Published: May 2022

Optical sensors have shown good capabilities for detecting and monitoring plant diseases, including fusariosis. The spectral characteristics of the excitation and luminescence of wheat, oat and barley seeds were measured using a diffraction spectrofluorimeter in the range of 180–700 nm. It was found that during infection, the spectral density of the absorption capacity increases and the curve ηe(λ) shifts upwards in the range of 380–450 nm. The shift to the left is also noticeable for the wheat and barley spectra. The photoluminescence flux at λe = 232 nm increased by 1.71 times when oat seeds were infected, by 2.63 times when wheat was infected and by 3.14 times when barley was infected. The dependences of the infection degree on the photoluminescence flux are statistically and reliably approximated by linear regression models with determination coefficients R2 = 0.83–0.95. The method of determining the degree of infection can include both absolute measurements of photoluminescence flux in the range of 290–380 nm and measurements of the flux ratios when excited by radiation of 232 nm and 424 nm for wheat and 485 nm for barley. An optoelectronic device for remote monitoring can be designed in order to implement the methodology for determining the degree of infection of agricultural plant seeds.
A Deep Learning-Based Diagnosis System for COVID-19 Detection and Pneumonia Screening Using CT Imaging
Authors: Mahmoudi Ramzi , Benameur Narjes , Mabrouk Rania , Mohammed Mazin Abed , Garcia-Zapirain Begonya , Bedoui Mohamed Hedi
Published: May 2022

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a global threat impacting the lives of millions of people worldwide. Automated detection of lung infections from Computed Tomography scans represents an excellent alternative; however, segmenting infected regions from CT slices encounters many challenges. Objective: Developing a diagnosis system based on deep learning techniques to detect and quantify COVID-19 infection and pneumonia screening using CT imaging. Method: Contrast Limited Adaptive Histogram Equalization pre-processing method was used to remove the noise and intensity in homogeneity. Black slices were also removed to crop only the region of interest containing the lungs. A U-net architecture, based on CNN encoder and CNN decoder approaches, is then introduced for a fast and precise image segmentation to obtain the lung and infection segmentation models. For better estimation of skill on unseen data, a fourfold cross-validation as a resampling procedure has been used. A three-layered CNN architecture, with additional fully connected layers followed by a Softmax layer, was used for classification. Lung and infection volumes have been reconstructed to allow volume ratio computing and obtain infection rate. Results: Starting with the 20 CT scan cases, data has been divided into 70% for the training dataset and 30% for the validation dataset. Experimental results demonstrated that the proposed system achieves a dice score of 0.98 and 0.91 for the lung and infection segmentation tasks, respectively, and an accuracy of 0.98 for the classification task. Conclusions: The proposed workflow aimed at obtaining good performances for the different system’s components, and at the same time, dealing with reduced datasets used for training.
Correction: Elnumin et al. Evaluating the Performance of IRI-2016 Using GPS-TEC Measurements over the Equatorial Region. Atmosphere 2021, 12, 1243
Authors: Elmunim Nouf Abd , Abdullah Mardina , Bahari Siti Aminah
Published: May 2022

In the original publication [...]
Influence of Relative Humidity on the Characteristics of Filter Cake Using Particle Flow Code Simulation
Authors: Shi Dinglian , Li Jianlong , Du Yongnan , Wu Quanquan , Huang Shan , Huang Hong , Wu Daishe
Published: May 2022

To study the effect of air humidity on particle filtration performance, the Particle Flow Code (PFC) calculation program was used to numerically simulate the formation process of filter cake. The effects of relative air humidity on the deposition morphology, porosity and filtration resistance characteristics of the filter cake were revealed. The results show that relative humidity (RH) is mainly reflected in the density and surface viscosity of the particles. It was found that the higher the relative humidity, the higher the particle moisture content, the greater the density, and the greater the surface viscosity. With an increase in the particle density or with a decrease in the viscosity, the bridging phenomenon of particle deposition became more obvious; the dendritic deposition phenomenon became weaker; and, therefore, the filter cake structure became denser; the porosity decreased; and the total filtration resistance increased. As the humidity changed, the actual density and viscosity of the particles changed simultaneously with different degrees, which caused different variation trends of the filter cake characteristics. Three different types of particles, DM828 (Starch), PVA1788 (Polyvinyl Alcohol) and Polyacrylamide (Polyacrylic acid), were selected for comparison. For the studied PVA1788 and Polyacrylamide particles, with an increase in relative humidity, the porosity of the filter cake increased monotonously, while the total filtration resistance decreased monotonously. For DM828 particles, the cake porosity first decreased and then increased, and the total filtration resistance first increased and then decreased, with an inflection point at 30% RH. By combining these results with existing reports, three kinds of variations of the filtration performance with humidity could be determined: (1) as the humidity increased, the filtration resistance first increased and then decreased; (2) the filtration resistance decreased; and (3) the filtration resistance increased.
The Navigation Ability Test (NAT 2.0): From Football Player Performance to Balance Rehabilitation in Chronic Unilateral Vestibular Loss
Authors: Gamba Paolo , Guidetti Riccardo , Balzanelli Cristiano , Bavazzano Maurizio , Laborai Andrea
Published: May 2022

Aim of the Study: in humans, spatial orientation consists of the ability to move around the environment through memorized and pre-programmed movements, according to the afferent sensory information of the body and environmental analysis of the Central Nervous System (CNS). The purpose of this study is to analyze the abilities of professional athletes, such as footballers, to use mental navigation systems, cognitive maps, and memorized motor patterns in order to obtain better physical performance and to obtain useful information for training both non-sports subjects and vestibular patients for rehabilitation purposes. Materials and Methods: all the motor performances of sportsmen, healthy non-sporting subjects, or vestibular patients are based on the acquisition of visual–spatial and training information. In this study, we analyzed the visual–spatial performance of 60 trained sportsmen (professional footballers), 60 healthy non-sports subjects, and 48 patients affected by chronic unilateral vestibular loss by means of the Navigation Ability Test 2.0. A score based on the number of targets correctly reached in the various tests quantifies the degree of performance of the subjects. Results: NAT 2.0 scores progressively improve from vestibular subjects to healthy non-sporting subjects to footballers. NAT 2.0 scores improve in all three subject groups as the number of tasks performed in all patient groups increases, regardless of gender and age. Conclusions: the analysis of performance data through NAT 2.0 in athletes (footballers) opens new perspectives for rehabilitation purposes, regardless of age, sex, and training conditions, both in healthy non-sporting subjects to improve their sporting potential and in patients affected by chronic vestibular dysfunction, in order to optimize their motor skills and prevent falls.
Characterizing Forbidden Pairs for the Edge-Connectivity of a Connected Graph to Be Its Minimum Degree
Authors: Du Junfeng , Huang Ziwen , Xiong Liming
Published: May 2022

Let H be a class of given graphs. A graph G is said to be H-free if G contains no induced copies of H for any H∈H. In this article, we characterize all connected subgraph pairs {R,S} guranteeing the edge-connectivity of a connected {R,S}-free graph to have the same minimum degree. Our result is a supplement of Wang et al. Furthermore, we obtain a relationship of forbidden sets when those general parameters have the recurrence relation.
New Fuzzy Extensions on Binomial Distribution
Authors: Sirbiladze Gia , Kacprzyk Janusz , Manjafarashvili Teimuraz , Midodashvili Bidzina , Matsaberidze Bidzina
Published: May 2022

The use of discrete probabilistic distributions is relevant to many practical tasks, especially in present-day situations where the data on distribution are insufficient and expert knowledge and evaluations are the only instruments for the restoration of probability distributions. However, in such cases, uncertainty arises, and it becomes necessary to build suitable approaches to overcome it. In this direction, this paper discusses a new approach of fuzzy binomial distributions (BDs) and their extensions. Four cases are considered: (1) When the elementary events are fuzzy. Based on this information, the probabilistic distribution of the corresponding fuzzy-random binomial variable is calculated. The conditions of restrictions on this distribution are obtained, and it is shown that these conditions depend on the ratio of success and failure of membership levels. The formulas for the generating function (GF) of the constructed distribution and the first and second order moments are also obtained. The Poisson distribution is calculated as the limit case of a fuzzy-random binomial experiment. (2) When the number of successes is of a fuzzy nature and is represented as a fuzzy subset of the set of possible success numbers. The formula for calculating the probability of convolution of binomial dependent fuzzy events is obtained, and the corresponding GF is built. As a result, the scheme for calculating the mathematical expectation of the number of fuzzy successes is defined. (3) When the spectrum of the extended distribution is fuzzy. The discussion is based on the concepts of a fuzzy-random event and its probability, as well as the notion of fuzzy random events independence. The fuzzy binomial upper distribution is specifically considered. In this case the fuzziness is represented by the membership levels of the binomial and non-binomial events of the complete failure complex. The GF of the constructed distribution and the first-order moment of the distribution are also calculated. Sufficient conditions for the existence of a limit distribution and a Poisson distribution are also obtained. (4) As is known, based on the analysis of lexical material, the linguistic spectrum of the statistical process of word-formation becomes two-component when switching to vocabulary. For this, two variants of the hybrid fuzzy-probabilistic process are constructed, which can be used in the analysis of the linguistic spectrum of the statistical process of word-formation. A fuzzy extension of standard Fuchs distribution is also presented, where the fuzziness is reflected in the growing numbers of failures. For better representation of the results, the examples of fuzzy BD are illustrated in each section.
Aspects of Differential Calculus Related to Infinite-Dimensional Vector Bundles and Poisson Vector Spaces
Authors: Glöckner Helge
Published: May 2022

We prove various results in infinite-dimensional differential calculus that relate the differentiability properties of functions and associated operator-valued functions (e.g., differentials). The results are applied in two areas: (1) in the theory of infinite-dimensional vector bundles, to construct new bundles from given ones, such as dual bundles, topological tensor products, infinite direct sums, and completions (under suitable hypotheses); (2) in the theory of locally convex Poisson vector spaces, to prove continuity of the Poisson bracket and continuity of passage from a function to the associated Hamiltonian vector field. Topological properties of topological vector spaces are essential for the studies, which allow the hypocontinuity of bilinear mappings to be exploited. Notably, we encounter kR-spaces and locally convex spaces E such that E×E is a kR-space.
Low Holding Densities Increase Stress Response and Aggression in Zebrafish
Authors: Andersson Marica , Roques Jonathan A. C. , Aliti Geoffrey Mukisa , Ademar Karin , Sundh Henrik , Sundell Kristina , Ericson Mia , Kettunen Petronella
Published: May 2022

With laboratory zebrafish (Danio rerio) being an established and popular research model, there is a need for universal, research-based husbandry guidelines for this species, since guidelines can help promote good welfare through providing appropriate care. Despite the widespread use of zebrafish in research, it remains unclear how holding densities affect their welfare. Previous studies have mainly evaluated the effects of holding densities on a single parameter, such as growth, reproductive output, or social interactions, rather than looking at multiple welfare parameters simultaneously. Here we investigated how chronic (nine weeks) exposure to five different holding densities (1, 4, 8, 12, and 16 fish/L) affected multiple welfare indicators. We found that fish in the 1 fish/L density treatment had higher free water cortisol concentrations per fish, increased vertical distribution, and displayed aggressive behaviour more frequently than fish held at higher densities. On the other hand, density treatments had no effect on anxiety behaviour, whole-brain neurotransmitter levels, egg volume, or the proportion of fertilised eggs. Our results demonstrate that zebrafish can be held at densities between 4 and 16 fish/L without compromising their welfare. However, housing zebrafish in the density of 1 fish/L increased their stress level and aggressive behaviour.
A Noninvasive Gas Exchange Method to Test and Model Photosynthetic Proficiency and Growth Rates of In Vitro Plant Cultures: Preliminary Implication for Cannabis sativa L.
Authors: Pepe Marco , Leonardos Evangelos D. , Marie Telesphore R. J. G. , Kyne Sean T. , Hesami Mohsen , Jones Andrew Maxwell Phineas , Grodzinski Bernard
Published: May 2022

Supplemental sugar additives for plant tissue culture cause mixotrophic growth, complicating carbohydrate metabolism and photosynthetic relationships. A unique platform to test and model the photosynthetic proficiency and biomass accumulation of micropropagated plantlets was introduced and applied to Cannabis sativa L. (cannabis), an emerging crop with high economic interest. Conventional in vitro systems can hinder the photoautotrophic ability of plantlets due to low light intensity, low vapor pressure deficit, and limited CO2 availability. Though exogenous sucrose is routinely added to improve in vitro growth despite reduced photosynthetic capacity, reliance on sugar as a carbon source can also trigger negative responses that are species-dependent. By increasing photosynthetic activity in vitro, these negative consequences can likely be mitigated, facilitating the production of superior specimens with enhanced survivability. The presented methods use an open-flow/force-ventilated gas exchange system and infrared gas analysis to measure the impact of [CO2], light, and additional factors on in vitro photosynthesis. This system can be used to answer previously overlooked questions regarding the nature of in vitro plant physiology to enhance plant tissue culture and the overall understanding of in vitro processes, facilitating new research methods and idealized protocols for commercial tissue culture.