bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermoforming Characteristics of PLA/TPU Multi-Material Specimens Fabricated with Fused Deposition Modelling under Different Temperatures
Authors: Sorimpuk Neilson Peter , Choong Wai Heng , Chua Bih-Lii
Published: October 2022

Multi-material products are required in fused deposition modelling (FDM) to meet a desired specification such as a rigid structure with soft material for impact protection. This paper focuses on the thermoformability and shape recovery characteristics of three-dimensional (3D)-printed multi-material specimens under different thermoforming temperatures. The multi-material specimens consist of polylactic acid (PLA) and thermoplastic polyurethane (TPU). The PLA/TPU specimens were prepared by depositing the TPU component on top of the PLA component using a fused deposition modelling (FDM) machine. Simple thermoforming tests were proposed, where the specimens were bent under load and molded into a circular shape at different thermoforming temperatures. The bent specimens were then reheated at 60 °C to evaluate their shape memory ability. The test results were quantified into apparent bending modulus and shape recovery percentage. The PLA/TPU specimens showed a better apparent bending modulus of 143 MPa than a PLA specimen at a temperature between 60 °C to 90 °C. However, only the PLA/TPU specimens being thermoformed into a circular shape at 100 °C or greater showed good shape retention accuracy and interfacial surface bonding. The PLA/TPU specimens that were thermoformed at 60 °C to 90 °C showed reasonable shape memory of about 60% recovery when reheated. Finally, suitable thermoforming temperatures for thermoforming PLA/TPU specimens were suggested based on design needs.
Silver-Coated Silica Nanoparticles Modified with MPS: Potential Antimicrobial Biomaterials Applied in Glaze and Soft Reliner
Authors: Rossi Natália Rivoli , de Menezes Beatriz Rossi Canuto , Sampaio Aline da Graça , da Silva Diego Morais , Koga-Ito Cristiane Yumi , Thim Gilmar Patrocínio , Paes-Junior Tarcisio José de Arruda
Published: October 2022

Soft reliner and glaze are materials used over full or partial dental prosthesis to prevent excessive pressure on the supporting tissues. They are also indicated as supportive treatment for dental stomatitis, especially when modified by the addition of medications. The objective of the work was to evaluate the antimicrobial effect of silver-coated silica nanoparticles in a glaze and a soft reliner. The nanoparticles were synthesized, characterized, and tested by minimum inhibitory concentration (MIC) for C. albicans SC5314. Then, the nanoparticles were incorporated to a glaze and a soft reliner, which were called nanocomposites. Then, the nanocomposites were divided into six groups (n = 12): CG: glaze/reliner; CR: reliner; G1: glaze + 1% nanoparticles/reliner; G2: glaze + 2.5% nanoparticles/reliner; R1: reliner + 1%; R2: reliner + 2.5%. The nanocomposites were characterized by a goniometer and by a scanning electron microscope. The antibiofilm test was performed against C. albicans SC5314. According to the MIC results, the non-functionalized nanoparticles reduced fungal growth at 1000 μg/mL and the functionalized nanoparticles at 2000 μg/mL. The functionalized nanoparticle had a superior dispersion being selected for the antibiofilm test. There was a reduction of 64% in CFU/specimen count for the glaze, not statistically significant (p = 0.244). For the soft reliner, there was an increase in CFU/specimen with the presence of nanoparticles, still not statistically significant (p = 0.264). In conclusion, it is necessary to conduct new studies to increase the release of silver, thus improving nanoparticles’ antifungal potential.
A Review of Biomaterials and Associated Performance Metrics Analysis in Pre-Clinical Finite Element Model and in Implementation Stages for Total Hip Implant System
Authors: Soliman Md Mohiuddin , Chowdhury Muhammad E. H. , Islam Mohammad Tariqul , Musharavati Farayi , Nabil Mohammad , Hafizh Muhammad , Khandakar Amith , Mahmud Sakib , Nezhad Erfan Zal , Shuzan Md Nazmul Islam , Abir Farhan Fuad
Published: October 2022

Total hip replacement (THR) is a common orthopedic surgery technique that helps thousands of individuals to live normal lives each year. A hip replacement replaces the shattered cartilage and bone with an implant. Most hip implants fail after 10–15 years. The material selection for the total hip implant systems is a major research field since it affects the mechanical and clinical performance of it. Stress shielding due to excessive contact stress, implant dislocation due to a large deformation, aseptic implant loosening due to the particle propagation of wear debris, decreased bone remodeling density due to the stress shielding, and adverse tissue responses due to material wear debris all contribute to the failure of hip implants. Recent research shows that pre-clinical computational finite element analysis (FEA) can be used to estimate four mechanical performance parameters of hip implants which are connected with distinct biomaterials: von Mises stress and deformation, micromotion, wear estimates, and implant fatigue. In vitro, in vivo, and clinical stages are utilized to determine the hip implant biocompatibility and the unfavorable local tissue reactions to different biomaterials during the implementation phase. This research summarizes and analyses the performance of the different biomaterials that are employed in total hip implant systems in the pre-clinical stage using FEA, as well as their performances in in vitro, in vivo, and in clinical studies, which will help researchers in gaining a better understanding of the prospects and challenges in this field.
Effect of Special-Shaped Nozzle Structure on Water Jet Performance
Authors: Chen Lihuan , Gao Dianrong , Cheng Muzheng , Cai Yi , Guo Liwen
Published: October 2022

The impact force and effective impact area of are water jet are two important indexes for evaluating jet performance, and the outlet shape of the nozzle has a great influence on jet performance. In this study, five nozzles with different outlet shapes were designed, and water jet test experiments were conducted at different inlet pressures using an independently built water jet impact test platform, and the influence law of nozzle shape on the center impact pressure and flow coefficient of the water jet was investigated. The influence of nozzle shape on the effective impact area and entrainment rate of water jet was further investigated by numerical simulation. The results showed that the center impact pressure of the circular nozzle was the greatest when the inlet pressure and the target distance were small. The center impact pressure, the flow coefficient, and the effective area of the triangular nozzle with sharp edges were better than the traditional circular nozzle when the inlet pressure and the target distance were increased. Although the center impact pressure of the square nozzle is lower than that of the circular nozzle, its flow coefficient and effective impact area are higher than those of the circular nozzle with increasing target distance. The water jets of the elliptical and cross nozzles were the most divergent, and the jet performance was poor.
Design, Scale-Up, and Construction of Drinking Water Recarbonization Fluidized Bed Reactor System
Authors: Dudáš Jozef , Derco Ján , Kurák Tomáš , Šoltýsová Nikola , Jelemenský Ľudovít , Vrabeľ Martin
Published: October 2022

The lack of calcium and magnesium in drinking water affects people’s health, especially cardiovascular and oncologic diseases, and causes corrosion problems. The aim of this paper is to present the methodology of the design, scale-up, and construction of a fluidized bed reactor (FBR) system for drinking water recarbonization with biogenic elements in real conditions. Half-calcined dolomite (HCD) in combination with CO2 was identified as a suitable source of Mg2+ and Ca2+. The experimental results confirmed that an FBR reactor with a water tank is an efficient system for Mg and Ca2+ ion concentrate production. The main process parameters and dimensions of the equipment were determined based on the experimental data and the data obtained showed that the system can be used in real conditions to produce Mg2+ and Ca2+ ions concentrate, which is mixed with soft water in required proportions. The FBR with an internal diameter of 0.16 m and a total height of 3.7 m was designed. The proposed methodology of the recarbonization process design was used in a further system scale-up for a ten times larger capacity. Long-term experiments indicate that the HCD recarbonization process is robust and can return to the steady state even after significant changes in the process parameters for providing the desired concentration of Mg2+ and Ca2+ ions in drinking water.
Cost Optimal Production-Scheduling Model Based on VNS-NSGA-II Hybrid Algorithm—Study on Tissue Paper Mill
Authors: Zhang Huanhuan , Li Jigeng , Hong Mengna , Man Yi , He Zhenglei
Published: October 2022

With the development of the customization concept, small-batch and multi-variety production will become one of the major production modes, especially for fast-moving consumer goods. However, this production mode has two issues: high production cost and the long manufacturing period. To address these issues, this study proposes a multi-objective optimization model for the flexible flow-shop to optimize the production scheduling, which would maximize the production efficiency by minimizing the production cost and makespan. The model is designed based on hybrid algorithms, which combine a fast non-dominated genetic algorithm (NSGA-II) and a variable neighborhood search algorithm (VNS). In this model, NSGA-II is the major algorithm to calculate the optimal solutions. VNS is to improve the quality of the solution obtained by NSGA-II. The model is verified by an example of a real-world typical FFS, a tissue papermaking mill. The results show that the scheduling model can reduce production costs by 4.2% and makespan by 6.8% compared with manual scheduling. The hybrid VNS-NSGA-II model also shows better performance than NSGA-II, both in production cost and makespan. Hybrid algorithms are a good solution for multi-objective optimization issues in flexible flow-shop production scheduling.
A Failed Cross-Validation Study on the Relationship between LIWC Linguistic Indicators and Personality: Exemplifying the Lack of Generalizability of Exploratory Studies
Authors: Martínez-Huertas José Ángel , Moreno José David , Olmos Ricardo , Martínez-Mingo Alejandro , Jorge-Botana Guillermo
Published: October 2022

(1) Background: Previous meta-analytic research found small to moderate relationships between the Big Five personality traits and different linguistic computational indicators. However, previous studies included multiple linguistic indicators to predict personality from an exploratory framework. The aim of this study was to conduct a cross-validation study analyzing the relationships between language indicators and personality traits to test the generalizability of previous results; (2) Methods: 643 Spanish undergraduate students were tasked to write a self-description in 500 words (which was evaluated with the LIWC) and to answer a standardized Big Five questionnaire. Two different analytical approaches using multiple linear regression were followed: first, using the complete data and, second, by conducting different cross-validation studies; (3) Results: The results showed medium effect sizes in the first analytical approach. On the contrary, it was found that language and personality relationships were not generalizable in the cross-validation studies; (4) Conclusions: We concluded that moderate effect sizes could be obtained when the language and personality relationships were analyzed in single samples, but it was not possible to generalize the model estimates to other samples. Thus, previous exploratory results found on this line of research appear to be incompatible with a nomothetic approach.
Secularisation and Spirituality among Lapsed-Christian Young Adults in Nairobi: An Exploratory Study of the Antecedents, Triggers, and Response
Authors: Selvam Sahaya G. , Githinji Ngure
Published: October 2022

African scholars have claimed that African peoples are “notoriously religious”. Is this still the case? Empirical literature on the subject is meagre. Therefore, the objective of this study was to examine the antecedents, triggers and response of secularisation and spirituality among lapsed-Christian young adults in Nairobi, Kenya, the participants were aged between 18 and 35, who were baptised but have abandoned Christian faith in favour of secularisation or non-affiliated spirituality. Qualitative data, from semi-structured in-depth interviews among the 14 participants, sampled through a snowball process, was recorded, transcribed verbatim, and analysed by the two authors. Eleven emerging themes were identified from 10 h of data. The first two themes suggest that mixed faith backgrounds of parents and discordant relationship within the family act as antecedents in adopting a secular perspective. The next two themes relate to the role of Christianity itself in terms of lack of faith formation and exaggeration of religiosity. The fifth and sixth themes revolve around trauma in Africa/Kenya, historical and contemporary. There were two themes pertaining to ill-treatment meted out by Christianity. The rest of the themes relate to how these individuals maintain meaning, value and spiritual systems. The findings are likely to generate an evidence-based discussion among religious leaders in Africa/Kenya.
A Perspective on the Impact of Grassland Degradation on Ecosystem Services for the Purpose of Sustainable Management
Authors: Lyu Xin , Li Xiaobing , Dang Dongliang , Dou Huashun , Wang Kai , Gong Jirui , Wang Hong , Liu Shiliang
Published: October 2022

Grassland degradation seriously threatens the ability of grassland to provide ecosystem services. Grassland ecological restoration and sustainable management decision making depends on an accurate understanding of the impacts of grassland degradation on ecosystem services. Based on the assessment of grassland degradation and four key ecosystem services, including the net primary production (NPP), ecosystem carbon pool (EC), soil conservation (SC), and soil loss by wind (SL), the impacts of grassland degradation on ecosystem services and their relationships were analyzed. The impacts of climate change and grazing pressure on the relationship between grassland degradation and ecosystem services were revealed. Based on the “climate change and grazing pressure-grassland degradation-ecosystem services” network, the study puts forward specific suggestions on grassland ecological restoration and sustainable management under the premise of fully balancing ecological restoration and stakeholder relationships. The results showed that grassland degradation had a significant impact on ecosystem services and their relationships, but it varied with the types of ecosystem services. Although the degraded grassland in the study area has been in a state of recovery and ecosystem services have been improving in the past 20 years, the degradation of grassland in some areas has intensified, and there are still ecological risks, so it is necessary to continue to carry out ecological restoration work. On this basis, taking the local conditions into consideration, grassland ecological restoration and sustainable management policy suggestions were proposed. The study can provide a scientific reference for ecological protection and sustainable development in arid and semi-arid areas, and help to improve human well-being.
Research on the Reliability of a Core Control Unit of Highway Electromechanical Equipment Based on Virtual Sensor Data
Authors: Lin Shan , Luo Mi , Niu Jun , Xu Hongke
Published: October 2022

The printed circuit board (PCB) is the core control unit of electromechanical equipment. In order to determine the influence of the coupling vibration caused by vehicle–road interaction on the PCB reliability of roadside electromechanical equipment, first, the dynamic load of the vehicle tire is solved by establishing the dynamic model of a vehicle road. Then, the acceleration response data generated by road vibration are obtained by solving the road finite element model. Finally, the power density spectrum of the acceleration response is taken as input excitation, and the deformation response of the PCB under vehicle–road coupling vibration is analyzed. The experimental results show that when the vehicle is driving close to the roadside, the vibration caused by vehicle–road coupling will lead to a large deformation of the PCB, and the deformation value reaches 0.170 mm, which can cause structural damage to the PCB. This shows that the vehicle–road coupling vibration can affect the reliability of the roadside electromechanical equipment; thus, the optimal design of the PCB layout is created. After optimization, the first-order modal frequency of the PCB is increase by 5.4%, which reduces the risk of the components breaking away from the PCB substrate.
Structural Design of Ocean Temperature and Depth Sensor with Quick Response and High Sensitivity
Authors: Liu Zhaoyue , Zhang Yuanchong , Zeng Lina , Li Zaijin , Chen Hao , Qiao Zhongliang , Qu Yi , Liu Guojun , Li Lin
Published: October 2022

The electrical sensing elements used in the traditional XBT (Expendable Bathythermograph) have problems such as low sensitivity and slow response time, and it is difficult to overcome the complex marine environment using the time–depth formula. In this paper, an ocean temperature depth sensor based on brass diaphragm and liquid filling is designed. The stress response time of FBGs with different lengths and the heat transfer time of different liquid materials are compared, and it is found that a fast response of 51 ms can be obtained by using GaInSn liquid for temperature sensing. The center deflection changes of brass diaphragms with different radii are analyzed, and the brass diaphragms with radius and thickness of 10 mm and 1 mm are selected, which still have good elastic properties under the pressure of 5 MPa. The influence of the inner metal shell section radius on the temperature and depth sensitivity is analyzed. When the final section radius is 3 mm, the temperature sensitivity of the sensor is 1.065 nm/°C, the pressure sensitivity is 1.245 nm/MPa, and the response time of temperature and depth is relatively close. Compared with the traditional temperature and depth sensors using empirical formulas for calculation, the data accuracy is improved, and a wide range of sensitivity can be tuned by adjusting the size of the internal metal shell, which can meet the needs of ocean temperature and depth data detection with high sensitivity and fast response time.
A Design Method of Two-Dimensional Subwavelength Grating Filter Based on Deep Learning Series Feedback Neural Network
Authors: Guo Jun-Hua , Zhang Ying-Li , Zhang Shuai-Shuai , Cai Chang-Long , Liang Hai-Feng
Published: October 2022

Subwavelength grating structure has excellent filtering characteristics, and its traditional design method needs a lot of computational costs. This work proposed a design method of two-dimensional subwavelength grating filter based on a series feedback neural network, which can realize forward simulation and backward design. It was programed in Python to study the filtering characteristics of two-dimensional subwavelength grating in the range of 0.4–0.7 µm. The shape, height, period, duty cycle, and waveguide layer height of two-dimensional subwavelength grating were taken into consideration. The dataset, containing 46,080 groups of data, was generated through numerical simulation of rigorous coupled-wave analysis (RCWA). The optimal network was five layers, 128 × 512 × 512 × 128 × 61 nodes, and 64 batch size. The loss function of the series feedback neural network is as low as 0.024. Meanwhile, it solves the problem of non-convergence of the network reverse design due to the non-uniqueness of data. The series feedback neural network can give the geometrical structure parameters of two-dimensional subwavelength grating within 1.12 s, and the correlation between the design results and the theoretical spectrum is greater than 0.65, which belongs to a strong correlation. This study provides a new method for the design of two-dimensional subwavelength grating, which is quicker and more accurate compared with the traditional method.
A High Gain Embedded Helix and Dielectric Rod Antenna with Low Side Lobe Levels for IoT Applications
Authors: Nasir Muhammad , Xia Yulong , Sharif Abu Bakar , Guo Guangjun , Zhu Qi , Ur Rehman Masood , Abbasi Qammer Hussain
Published: October 2022

In this paper, a novel embedded helix dielectric rod antenna is presented for high gain radiation with circular polarization (CP) and low side lobe levels for IoT Applications. Different from the conventional dielectric rod antennas, this proposed antenna is an integrated structure that combines the advantages of the helix and dielectric rod antennas. The presented antenna mainly consists of three parts: a tapered helix as primary feeding for CP, a dielectric rod with printed loops embedded for higher directivity, and a dielectric rod end for improving the gain further. After studying and analyzing the working principles of each part, an optimum design operating at 8–9.7 GHz is carried out as an example. A prototype is also fabricated and tested. The measured results show that the prototype can provide 18.41 dB maximum gain within the length of 7.7 λ. The side lobe level is below −20 dB, and the axial ratio is better than 1.14 dB in the whole frequency band. Compared with the traditional helix antenna and dielectric rod antenna with the same electric length, the presented antenna has a higher gain with a lower side lobe level and with good polarization purity.
Rolling Circle Enhanced Detection of Specific Restriction Endonuclease Activities in Crude Cell Extracts
Authors: Petersen Kamilla Vandsø , Tesauro Cinzia , Hede Marianne Smedegaard , Pages Camilla , Marcussen Lærke Bay , Keller Josephine Geertsen , Bugge Magnus , Holm Kasper , Bjergbæk Lotte , Stougaard Magnus , Wejse Christian , Knudsen Birgitta R.
Published: October 2022

Restriction endonucleases are expressed in all bacteria investigated so far and play an essential role for the bacterial defense against viral infections. Besides their important biological role, restriction endonucleases are of great use for different biotechnological purposes and are indispensable for many cloning and sequencing procedures. Methods for specific detection of restriction endonuclease activities can therefore find broad use for many purposes. In the current study, we demonstrate proof-of-concept for a new principle for the detection of restriction endonuclease activities. The method is based on rolling circle amplification of circular DNA products that can only be formed upon restriction digestion of specially designed DNA substrates. By combining the activity of the target restriction endonuclease with the highly specific Cre recombinase to generate DNA circles, we demonstrate specific detection of selected restriction endonuclease activities even in crude cell extracts. This is, to our knowledge, the first example of a sensor system that allows activity measurements of restriction endonucleases in crude samples. The presented sensor system may prove valuable for future characterization of bacteria species or strains based on their expression of restriction endonucleases as well as for quantification of restriction endonuclease activities directly in extracts from recombinant cells.
Classification of Tea Leaves Based on Fluorescence Imaging and Convolutional Neural Networks
Authors: Wei Kaihua , Chen Bojian , Li Zejian , Chen Dongmei , Liu Guangyu , Lin Hongze , Zhang Baihua
Published: October 2022

The development of the smartphone and computer vision technique provides customers with a convenient approach to identify tea species, as well as qualities. However, the prediction model may not behave robustly due to changes in illumination conditions. Fluorescence imaging can induce the fluorescence signal from typical components, and thus may improve the prediction accuracy. In this paper, a tea classification method based on fluorescence imaging and convolutional neural networks (CNN) is proposed. Ultra-violet (UV) LEDs with a central wavelength of 370 nm were utilized to induce the fluorescence of tea samples so that the fluorescence images could be captured. Five kinds of tea were included and pre-processed. Two CNN-based classification models, e.g., the VGG16 and ResNet-34, were utilized for model training. Images captured under the conventional fluorescent lamp were also tested for comparison. The results show that the accuracy of the classification model based on fluorescence images is better than those based on the white-light illumination images, and the performance of the VGG16 model is better than the ResNet-34 model in our case. The classification accuracy of fluorescence images reached 97.5%, which proves that the LED-induced fluorescence imaging technique is promising to use in our daily life.
A Cotraining-Based Semisupervised Approach for Remaining-Useful-Life Prediction of Bearings
Authors: Yan Xuguo , Xia Xuhui , Wang Lei , Zhang Zelin
Published: October 2022

The failure of bearings can have a significant negative impact on the safe operation of equipment. Recently, deep learning has become one of the focuses of RUL prediction due to its potent scalability and nonlinear fitting ability. The supervised learning process in deep learning requires a significant quantity of labeled data, but data labeling can be expensive and time-consuming. Cotraining is a semisupervised learning method that reduces the quantity of required labeled data through exploiting available unlabeled data in supervised learning to boost accuracy. This paper innovatively proposes a cotraining-based approach for RUL prediction. A CNN and an LSTM were cotrained on large amounts of unlabeled data to obtain a health indicator (HI), then the monitoring data were entered into the HI and the RUL prediction was realized. The effectiveness of the proposed approach was compared and analyzed against individual CNN and LSTM and the stacking networks SAE+LSTM and CNN+LSTM in the existing literature using RMSE and MAPE values on a PHM 2012 dataset. The results demonstrate that the RMSE and MAPE value of the proposed approach are superior to individual CNN and LSTM, and the RMSE value of the proposed approach is 54.72, which is significantly lower than SAE+LSTM (137.12), and close to CNN+LSTM (49.36). The proposed approach has also been tested successfully on a real-world task and thus has strong application value.
Application of Prussian Blue in Electrochemical and Optical Sensing of Free Chlorine
Authors: Valiūnienė Aušra , Ziziunaite Gerda , Virbickas Povilas
Published: October 2022

In this paper, an electrochemical free chlorine (FCL) sensor was formed by modifying a fluorine-doped tin oxide-coated glass slide (glass|FTO) with a layer of Prussian blue (glass|FTO|PB). The glass|FTO|PB sensor exhibited a wide linear detection range from 1.7 to 99.2 μmol L−1 of FCL with a sensitivity of ~0.8 µA cm−2 μmol−1 L and showed high selectivity for FCL. However, ClO3−, ClO4− and NO3− ions have induced only a negligible amperometric response that is highly beneficial for a real-life sample analysis as these ions are commonly found in chlorine-treated water. Moreover, in this work, optical absorption measurement-based investigations of partially reduced PB were carried out as a means to characterize PB catalytic activity towards FCL and to investigate the possibility of applying PB for the optical detection of FCL.
Tracking Efficiency Improvement According to Incident Beam Size in QPD-Based PAT System for Common Path-Based Full-Duplex FSO Terminals
Authors: Park Siwoong , Yeo Chan Il , Heo Young Soon , Ryu Ji Hyoung , Kang Hyun Seo , Lee Dong-Seon , Jang Jae-Hyung
Published: October 2022

Free space optical (FSO) communication can support various unmanned aerial vehicles’ (UAVs) applications that require large capacity data transmission. In order to perform FSO communication between two terminals, it is essential to employ a pointing, acquisition, and tracking (PAT) system with an efficient and optimal performance. We report on the development of a common optical-path-based FSO communication system, tailored for applications in UAVs. The proposed system is equipped with a quadrant photodiode (QPD)-based PAT system without an additional beacon beam subsystem. The presented approach reduced the structural complexity and improved the tracking efficiency for the same size, weight, and power (SWaP). To achieve a robust FSO link in a dynamic UAV environment, the observability and controllability were obtained based on the linearized control according to the incident beam size on the QPD, which was verified by optical simulation and experiments. As a result, the QPD-based PAT system for implementing FSO links demonstrated an up to 4.25 times faster tracking performance. Moreover, the FSO link experimentally confirmed the 1.25 Gbps full-duplex error-free communication at a 50 m distance.
An Intelligent Model-Based Effective Approach for Glycemic Control in Type-1 Diabetes
Authors: Khaqan Ali , Nauman Ali , Shuja Sana , Khurshaid Tahir , Kim Ki-Chai
Published: October 2022

Type-1 diabetes mellitus (T1DM) is a challenging disorder which essentially involves regulation of the glucose levels to avoid hyperglycemia as well as hypoglycemia. For this purpose, this research paper proposes and develops control algorithms using an intelligent predictive control model, which is based on a UVA/Padova metabolic simulator. The primary objective of the designed control laws is to provide an automatic blood glucose control in insulin-dependent patients so as to improve their life quality and to reduce the need of an extremely demanding self-management plan. Various linear and nonlinear control algorithms have been explored and implemented on the estimated model. Linear techniques include the Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR), and nonlinear control strategy includes the Sliding Mode Control (SMC), which are implemented in this research work for continuous monitoring of glucose levels. Performance comparison based on simulation results demonstrated that SMC proved to be most efficient in terms of regulating glucose profile to a reference level of 70 mg/dL compared to the classical linear techniques. A brief comparison is presented between the linear techniques (PID and LQR), and nonlinear technique (SMC) for analysis purposes proving the efficacy of the design.
Reducing Operational Expenses of LoRaWAN-Based Internet of Remote Things Applications
Authors: Finochietto Mariano , Santos Rodrigo , Ochoa Sergio F. , Meseguer Roc
Published: October 2022

LoRaWAN has become the most widely used low-power wide-area network technology to implement monitoring solutions based on the Internet of remote things (IoRT) paradigm. Typically, these solutions interconnect remote sensing areas and data processing infrastructure located in urban centers. The operation expenses of these solutions depend mainly on the traffic sent through the network backhaul, i.e., the link that connects the remote sensing area and the urban area where the data are usually processed and stored. This service is provided by telecommunication companies and represents the main operation cost of IoRT solutions. These expenses usually limit the affordability of IoRT-based systems in developing countries, and also in scenarios where the operational cost is an issue to address. This paper presents an extension to the LoRaWAN protocol, named Node-Aware-LoRaWAN (NA-LoRaWAN), that reduces the traffic in the backhaul, thus decreasing the operational expenses of IoRT-based systems. In order to evaluate the performance of NA-LoRaWAN, it was compared to a regular LoRaWAN implementation. Depending on the network scenario, the proposed extension reduced the traffic through the backhaul in the range of 12–34%. This extension opens several opportunities to use IoRT solutions in application domains with a low operational budget, e.g., precision agriculture, environmental monitoring and natural hazards’ early detection.
Pruning the Communication Bandwidth between Reinforcement Learning Agents through Causal Inference: An Innovative Approach to Designing a Smart Grid Power System
Authors: Zhang Xianjie , Liu Yu , Li Wenjun , Gong Chen
Published: October 2022

Electricity demands are increasing significantly and the traditional power grid system is facing huge challenges. As the desired next-generation power grid system, smart grid can provide secure and reliable power generation, and consumption, and can also realize the system’s coordinated and intelligent power distribution. Coordinating grid power distribution usually requires mutual communication between power distributors to accomplish coordination. However, the power network is complex, the network nodes are far apart, and the communication bandwidth is often expensive. Therefore, how to reduce the communication bandwidth in the cooperative power distribution process task is crucially important. One way to tackle this problem is to build mechanisms to selectively send out communications, which allow distributors to send information at certain moments and key states. The distributors in the power grid are modeled as reinforcement learning agents, and the communication bandwidth in the power grid can be reduced by optimizing the communication frequency between agents. Therefore, in this paper, we propose a model for deciding whether to communicate based on the causal inference method, Causal Inference Communication Model (CICM). CICM regards whether to communicate as a binary intervention variable, and determines which intervention is more effective by estimating the individual treatment effect (ITE). It offers the optimal communication strategy about whether to send information while ensuring task completion. This method effectively reduces the communication frequency between grid distributors, and at the same time maximizes the power distribution effect. In addition, we test the method in StarCraft II and 3D environment habitation experiments, which fully proves the effectiveness of the method.
Research of Maritime Object Detection Method in Foggy Environment Based on Improved Model SRC-YOLO
Authors: Zhang Yihong , Ge Hang , Lin Qin , Zhang Ming , Sun Qiantao
Published: October 2022

An improved maritime object detection algorithm, SRC-YOLO, based on the YOLOv4-tiny, is proposed in the foggy environment to address the issues of false detection, missed detection, and low detection accuracy in complicated situations. To confirm the model’s validity, an ocean dataset containing various concentrations of haze, target angles, and sizes was produced for the research. Firstly, the Single Scale Retinex (SSR) algorithm was applied to preprocess the dataset to reduce the interference of the complex scenes on the ocean. Secondly, in order to increase the model’s receptive field, we employed a modified Receptive Field Block (RFB) module in place of the standard convolution in the Neck part of the model. Finally, the Convolutional Block Attention Module (CBAM), which integrates channel and spatial information, was introduced to raise detection performance by expanding the network model’s attention to the context information in the feature map and the object location points. The experimental results demonstrate that the improved SRC-YOLO model effectively detects marine targets in foggy scenes by increasing the mean Average Precision (mAP) of detection results from 79.56% to 86.15%.
An Augmented Reality Serious Game for Learning Intelligent Wheelchair Control: Comparing Configuration and Tracking Methods
Authors: Maio Rafael , Marques Bernardo , Alves João , Santos Beatriz Sousa , Dias Paulo , Lau Nuno
Published: October 2022

This work proposes an augmented reality serious game (ARSG) for supporting individuals with motor disabilities while controlling robotic wheelchairs. A racing track was used as the game narrative; this included restriction areas, static and dynamic virtual objects, as well as obstacles and signs. To experience the game, a prior configuration of the environment, made through a smartphone or a computer, was required. Furthermore, a visualization tool was developed to exhibit user performance while using the ARSG. Two user studies were conducted with 10 and 20 participants, respectively, to compare (1) how different devices enable configuring the ARSG, and (2) different tracking capabilities, i.e., methods used to place virtual content on the real-world environment while the user interacts with the game and controls the wheelchair in the physical space: C1—motion tracking using cloud anchors; C2—offline motion tracking. Results suggest that configuring the environment with the computer is more efficient and accurate, in contrast to the smartphone, which is characterized as more engaging. In addition, condition C1 stood out as more accurate and robust, while condition C2 appeared to be easier to use.
How to Detect Online Hate towards Migrants and Refugees? Developing and Evaluating a Classifier of Racist and Xenophobic Hate Speech Using Shallow and Deep Learning
Authors: Arcila-Calderón Carlos , Amores Javier J. , Sánchez-Holgado Patricia , Vrysis Lazaros , Vryzas Nikolaos , Oller Alonso Martín
Published: October 2022

Hate speech spreading online is a matter of growing concern since social media allows for its rapid, uncontrolled, and massive dissemination. For this reason, several researchers are already working on the development of prototypes that allow for the detection of cyberhate automatically and on a large scale. However, most of them are developed to detect hate only in English, and very few focus specifically on racism and xenophobia, the category of discrimination in which the most hate crimes are recorded each year. In addition, ad hoc datasets manually generated by several trained coders are rarely used in the development of these prototypes since almost all researchers use already available datasets. The objective of this research is to overcome the limitations of those previous works by developing and evaluating classification models capable of detecting racist and/or xenophobic hate speech being spread online, first in Spanish, and later in Greek and Italian. In the development of these prototypes, three differentiated machine learning strategies are tested. First, various traditional shallow learning algorithms are used. Second, deep learning is used, specifically, an ad hoc developed RNN model. Finally, a BERT-based model is developed in which transformers and neural networks are used. The results confirm that deep learning strategies perform better in detecting anti-immigration hate speech online. It is for this reason that the deep architectures were the ones finally improved and tested for hate speech detection in Greek and Italian and in multisource. The results of this study represent an advance in the scientific literature in this field of research, since up to now, no online anti-immigration hate detectors had been tested in these languages and using this type of deep architecture.
Comparative Study and Optimal Design of Subsynchronous Damping Controller in Doubly Fed Induction Generator
Authors: Xiang Song , Su Peng , Wu Xiaodan , Yang Hanlu , Wang Chaoqun
Published: October 2022

The subsynchronous damping controller (SSDC) has been widely recognized for its excellent performance and low cost in subsynchronous oscillation (SSO) mitigation for the doubly fed induction generator (DFIG)-based wind power system. However, the existing SSDCs are various and lack a systematic comparison. To fill this gap, the structures and parameter design methods of common SSDCs are sorted and compared in this paper. It is found that the rotor-current-based method performs best in terms of dynamic performance and robustness, as it can mitigate SSO for all working conditions in the test, while the feasibility range of other methods is much smaller. Therefore, the influence of different parameters in a rotor-current-based SSDC on SSO mitigation is further researched, leading to a guideline for parameter selection. More importantly, to address the challenge of time-varying oscillation frequency, an adaptive frequency selection method is proposed based on the eigensystem realization algorithm, which can accurately track the SSO frequency within 5~45 Hz. The results of the root locus analysis and hardware-in-the-loop experiment demonstrate that the improved rotor-current-based SSDC performs better than other existing methods, and it does not affect the normal operation of the DFIG.
Comparative Assessment of Microplastics in Surface Water and Sediments of Meishe River, Haikou, China
Authors: Wen Shaobai , Yu Chunwei , Lin Fang , Diao Xiaoping
Published: October 2022

Meishe River is the longest urban river in Haikou. The level of microplastics pollution in this river may affect the ecological balance, and can have an adverse effect on human health. Thus, it is essential to gain a comprehensive understanding of the microplastics pollution in the river to ensure safety of the human living environment. Microscopic examination and Micro-Fourier Transform Infrared Spectroscopy (μ-FTIR) were used to investigate the distribution and characteristics of microplastic pollution in surface water and sediments of the Meishe River. The results revealed that microplastics extracted from Meishe River mainly consisted of polyethylene (PE) and poly octadecyl acrylate (POA), and the abundance of microplastics in the surface water and sediments lay in the range of 3–10 items/L and 61–205 items/100 g dry weight, respectively. With respect to shapes and colors of microplastics, among the micro plastics found in the surface water, 74% were fiber and 57% were white colored, while among those in the sediments, 88% were fiber and 55% were of white colored. In terms of particle size, microplastics with the particle size of 0.1–0.5 mm were the most abundant (49% approximately) in surface water, while the microplastics with particle size 1.0–5.0 mm were dominant (74%) in the sediments. The results clearly showed that the Meishe River was polluted by microplastics, which may eventually flow into the nearby sea and adversely affect the sea environment. Consequently, some organisms in the urban river may be adversely affected.
Sustainability Perspectives in Organizational and Workplace Learning Studies
Authors: Brandi Ulrik , Collin Kaija , Lemmetty Soila
Published: October 2022

The association between sustainability and learning in organizations and workplaces represents a current articulated grand challenge for human resource development (HRD) and learning studies and practice, which calls for integrated inquiries. However, studies of learning in organizations and workplaces deal with sustainability in scattered and diverse ways that promote calls for more integrated understandings of the different approaches and associations. This article outlines the results from a scoping thematic review mapping out leading perspectives within the research fields of HRD, organizational learning (OL) and workplace learning (WPL). This article thus explores the perspectives that have been used in approaching sustainability in OL and WPL studies. The analysis of the identified studies shows that OL and WPL research has utilized four different perspectives in the approach to sustainability associated with learning: (1) balance perspective, (2) dimensional perspective, (3) integral perspective, and (4) outcome perspective. Findings are discussed with the purpose of producing a deeper understanding of how sustainability and OL and WPL are associated. In so doing, this scoping review clarifies and deepens existing knowledge and themes, and provides potential for future practical action and theoretical advancement for HRD and learning studies.
Research on the Coordinated Development of Economic Development and Ecological Environment of Nine Provinces (Regions) in the Yellow River Basin
Authors: Zhang Zhongwu , Li Huimin , Cao Yongjian
Published: October 2022

An important manifestation of high-quality regional development is the coordination of economic development and the ecological environment. We used night light data and the net primary productivity (NPP) of vegetation to quantitatively analyze the economic development and ecological environment of nine provinces (regions) in the Yellow River Basin in 2005, 2010, 2015 and 2020, and explored the coupling coordination relationship between the two from temporal and spatial scales. The analysis results showed that: (1) The ecological value of the Yellow River Basin showed a declining–rising trend. In 2005, 2010, 2015 and 2020, the ecological value of the Yellow River Basin was 2290.67 billion yuan, 2140.11 billion yuan, 2304.49 billion yuan and 2387.55 billion yuan. (2) The light density was related to the economic development of the city, and the light density showed a steady increase. The light index increased from 0.0001–1.6534 in 2005 to 0.0029–5.055 in 2020. The hot spots of light density were concentrated in the capital cities of the provinces with relatively good economic development and were concentrated in the east; the cold spots were mainly concentrated in the relatively slow economic development areas in the west. (3) The degree of coordination between economy and ecology in the Yellow River Basin increased from 0.1757 in 2005 to 0.2529 in 2020. However, the coordination degree of the ecological economy in the basin has been in an unbalanced state for a long time, with huge development potential. (4) There was a huge gap in the degree of ecological coordination in the basin. In 2020, the most coordinated ecological economy was 0.519 in Chengdu, and the most unbalanced was 0.053 in the Yushu Tibetan Autonomous Prefecture.
Exact Eco-Efficiency Measurement in the Yellow River Basin: A New Non-Parametric Approach
Authors: Xia Chuanxin , Zhao Yu , Zhao Qingxia , Wang Shuo , Zhang Ning
Published: October 2022

Frontier-based approaches to eco-efficiency measures have long been controversial because no normative definition is provided. Previous studies have used technical efficiency, environmental efficiency, and other variables as a proxy. To standardize its definition, we propose a formal eco-efficiency indicator, the ratio of actual gross domestic product (GDP) to environmental impact to potential GDP to environmental impact. To quantify it, we develop the biennial meta-frontier non-radial directional distance function (BMNDDF), which addresses the potential threats of technology heterogeneity, the slack variable, and linear programming infeasibility. Using this new indicator, we assess the city-level eco-efficiency in the Yellow River Basin from 2008 to 2017 to identify the harmonious relationship between ecological protection and economic development. The empirical results show a 5.73% increase in eco-efficiency per year, with the technology leadership effect as the main contributor. Because the central region is defined by heavy emissions and many underdeveloped cities, it suffers from more severe conflicts between outputs and emissions than other regions.