bluuebunny/crossref_metadata_2025 huggingface dataset:
Hetero-Epitaxial Growth of AlN Deposited by DC Magnetron Sputtering on Si(111) Using a AlN Buffer Layer
Authors: Riah Badis , Camus Julien , Ayad Abdelhak , Rammal Mohammad , Zernadji Raouia , Rouag Nadjet , Djouadi Mohamed Abdou
Published: September 2021

This paper reports the effect of Silicon substrate orientation and Aluminum nitride buffer layer deposited by molecular beam epitaxy on the growth of aluminum nitride thin films deposited by a DC magnetron sputtering technique at low temperatures. The structural analysis has revealed a strong (0001) fiber texture for both Si(100) and (111) substrates, and a hetero-epitaxial growth on a AlN buffer layer, which is only a few nanometers in size, grown by MBE onthe Si(111) substrate. SEM images and XRD characterization have shown an enhancement in AlN crystallinity. Raman spectroscopy indicated that the AlN film was relaxed when it deposited on Si(111), in compression on Si(100) and under tension on a AlN buffer layer grown by MBE/Si(111) substrates, respectively. The interface between Si(111) and AlN grown by MBE is abrupt and well defined, contrary to the interface between AlN deposited using PVD and AlN grown by MBE. Nevertheless, AlN hetero-epitaxial growth was obtained at a low temperature (<250 °C).
Improved Adhesion of the DLC Coating Using HiPIMS with Positive Pulses and Plasma Immersion Pretreatment
Authors: Gómez Iñigo , Claver Adrián , Santiago José Antonio , Fernandez Iván , Palacio Jose Fernandez , Diaz Cristina , Mändl Stephan , Garcia Jose Antonio
Published: September 2021

Diamond-like carbon (DLC) coatings are used due to their extraordinary tribomechanical properties, great hardness, high elastic modulus, high wear resistance, low friction coefficient and chemical inertness, which provide them with biocompatibility. Compared to other physical vapor deposition (PVD) coatings of transition nitrides and carbonitrides, DLC has limited adhesion, so it is necessary to develop new techniques to overcome this limitation. This work reports the results of scratch testing for the measurement of adhesion and of tests for wear resistance and nanoindentation in AISI 316L stainless steel coated with a WC:C coating, produced using novel high-power impulse magnetron sputtering (HiPIMS) technology with positive pulses. In addition, the use of a preceding surface modification technique, specifically plasma immersion ion implantation (PIII), was studied with the aim of optimizing the adhesion of the coating. The results show how the coating improved the tribomechanical properties through the use of positive pulse HiPIMS compared to conventional HiPIMS, with an adhesion result that reached critical load values of 48.5 N and a wear coefficient of 3.96 × 10−7 mm3/nm.
High Response of Ethanol Gas Sensor Based on NiO-Doped Apple Pectin by the Solution Process
Authors: Jian Jia-Cheng , Chang Yu-Chi , Chang Sheng-Po , Chang Shoou-Jinn
Published: September 2021

Novel gas sensor devices, based on biomaterial apple pectin film (APN) doped with NiO, were fabricated for the first time using a solution processing technique. The device was then annealed in a microwave chamber. The structural, elemental, and surface morphology of the device was investigated, using TEM, XPS, and AFM, respectively. The as-fabricated film sensor possessed a superior sensing performance regarding ethanol gas, compared to the pure apple pectin film sensor. The response of the device was recorded at a maximum efficiency of 161. For a 10 ppm concentration of ethanol gas at an operational temperature of 250 °C, the response time was 1.379 s. Nevertheless, the sensing mechanism for the sensor device is also described thoroughly.
Effects of Pine Bark Extract on Physicochemical Properties and Biological Activity of Active Chitosan Film by Bionic Structure of Dragonfly Wing
Authors: Wan Kang , Cong Mengdi , Teng Xu , Feng Miao , Ren Lili , Wang Liyan
Published: September 2021

Bionic and active films based on chitosan were developed with the bionic structure of dragonfly wings incorporating pine bark extract (PBE). Physicochemical properties of the films, including thickness, opacity, moisture content, color, mechanical properties, and water vapor permeability were measured. Antioxidant activity of the films was characterized by DPPH free radical scavenging activity. The interaction between chitosan and PBE was explored by attenuated total reflectance Fourier transform infrared spectrometry, X-ray diffraction, and differential scanning calorimetry. The results indicated that the addition of PBE gave rise to the films greater opacity, redness, and darker appearance. Compared with pure chitosan film, the thickness, opacity, mechanical properties, and oxidation resistance of the bionic chitosan–PBE film increased, and the water vapor permeability decreased. The films based on chitosan incorporated PBE and with the bionic structure of dragonfly wings can potentially be applied to food packaging.
The Electrochemical Mechanism of Preparing Mn from LiMn2O4 in Waste Batteries in Molten Salt
Authors: Liang Jinglong , Zhang Rui , Li Hui , Wang Le , Cai Zongying , Yan Hongyan , Cao Weigang
Published: September 2021

The electrochemical reduction mechanism of Mn in LiMn2O4 in molten salt was studied. The results show that in the NaCl-CaCl2 molten salt, the process of reducing from Mn (IV) to manganese is: Mn (IV)→Mn (III)→Mn (II)→Mn. LiMn2O4 reacts with molten salt to form CaMn2O4 after being placed in molten salt for 1 h. The reaction of reducing CaMn2O4 to Mn is divided into two steps: Mn (III)→Mn (II)→Mn. The results of constant voltage deoxidation experiments under different conditions show that the intermediate products of LiMn2O4 reduction to Mn are CaMn2O4, MnO, and (MnO)x(CaO)(1−x). As the reaction progresses, x gradually decreases, and finally the Mn element is completely reduced under the conditions of 3 V for 9 h. The CaO in the product can be removed by washing the sample with deionized water at 0 °C.
Fabrication and Characterization of Clay-Polyethylene Composite Opted for Shielding of Ionizing Radiation
Authors: Olukotun S. F. , Gbenu S. T. , Oyedotun K. O. , Fasakin O. , Sayyed M. I. , Akindoyin G. O. , Shittu H. O. , Fasasi M. K. , Khandaker Mayeen Uddin , Osman Hamid , Elesawy Basem H.
Published: September 2021

This study fabricated and characterized a self-sustaining hydrogenous content clay-polyethylene composite opted for ionizing radiation shielding. Composites designated A–G were fabricated each containing 0–30 wt% of recycled low density polyethylene (LDPE), respectively. To know the effects of the incorporated LDPE on the morphology, microstructural, compressive strength, thermal property and displacement effect on the vital elements were studied using scanning electron microscopy (SEM), X-ray diffractometry (XRD), universal mechanical testing machine, differential thermal analysis (DTA), Rutherford backscattering (RBS) technique and particle induced X-ray emission (PIXE), respectively. The bulk densities of the clay composites ranged between 1.341 and 2.030 g/cm3. The samples’ XRD analysis revealed similar patterns, with a sharp and prominent peak at angle 2θ equals ~26.11°, which matched with card number 16-0606 of the Joint Committee on Powder Diffraction Standards (JCPDS) that represents Aluminum Silicate Hydroxide (Al2Si2O5(OH)4), a basic formula for Kaolin clay. The compressive strength ranged between 2.52 and 5.53 MPa. The ratio of Si to Al in each composite is about 1:1. The dehydroxylation temperature for samples ranged between 443.23 °C and 555.23 °C.
Processing and Characterization of BCZT-Modified BiFeO3-BaTiO3 Piezoelectric Ceramics
Authors: Malik Rizwan Ahmed , Alrobei Hussein
Published: September 2021

The synthesis of non-lead piezoelectric ceramics (1–z)(0.65Bi1.05Fe2O3-0.35BaTiO3)-z Ba(Ti0.8Zr0.2)O3-(Ba0.7Ca0.3)TiO3 using a solid state method and a quenching strategy was investigated. The processing conditions such as the sintering temperature and soaking time were optimized. The patterns of X-ray diffraction (XRD) displayed a pure perovskite structure with no secondary phases. The ferroelectric and piezoelectric characteristics of the samples were considerably improved as a result of the lattice strain. The findings of the experiment revealed that the quenching technique increases the piezoelectric sensor constant of 152 pC/N in optimized conditions. The enhanced piezoelectric sensor constant (d33) value at z = 0.020 was ascribed to the incorporation of multi-cationic BCZT, which modified the bond lengths at a unit cell level and gave rise to more flexibility in complex domain switching. This facilitated easier domain alignment in response to the applied field and resulted in an improvement in the electrical properties.
Enhancement of Planar Orientation of Reactive Mesogen Molecules for Optical Retarder Film by Anisotropic Surface Plasma Treatment
Authors: Kim Jiyeon , Lee Ji-Hoon
Published: September 2021

We proposed a method for enhancing the planar orientation of reactive mesogen (RM) molecules by means of anisotropic plasma treatment. Anisotropic surface plasma, of which energy density is dependent on the azimuthal angle, was generated by column-shaped ceramic electrodes. The anisotropic plasma was discharged on the surface of a polyvinyl alcohol (PVA) alignment layer before the rubbing process began. The contact angle of the surface was increased from 12° to 83° after plasma treatment, indicating a hydrophobic property of the surface. From the atomic force microscopy (AFM) measurement, it was found that the grain size of the PVA layer was reduced and that the grooved patterns were formed provided that the plasma direction was parallel to the rubbing direction of the surface. Consequently, the planar orientation was enhanced, and the in-plane retardation of the photo-polymerized RM films increased when the parallel plasma was treated on the surface.
Polychaete (Annelida) Diversity Patterns in Southern Gulf of Mexico: The Influence of Spatial Structure and Environmental Variables
Authors: Quiroz-Martínez Benjamín , Hernández-Alcántara Pablo , Salas-de-León David Alberto , Solís-Weiss Vivianne
Published: September 2021

A comprehensive database was built to examine the spatial diversity patterns of polychaete species from the continental shelf in Southern Gulf of Mexico. Using Cluster and nMDS analysis we found the composition of polychaete species to be different between the terrigenous and carbonate regions of the Gulf. To test the relative importance of spatial and environmental components in the polychaetae community structure in the Southern Gulf of Mexico, we examined the spatial relationships between polychaetae assemblages and environmental variables over broad geographical scales. A distance-based redundancy analysis (dbRDA) and variation partitioning was used to quantify the relative importance of these explanatory variables on the spatial variations of species richness and composition. Variation partitioning is an important tool to investigate the importance of spatial structure to species distribution in communities, but it has not yet been used in marine ecosystems. The significance level of spatial and environmental components to the distribution of polychaete species showed that the combined effect of spatial processes and sediment characteristics explained a higher percentage of variance than those parameters could alone.
Biodiversity of the Huautla Cave System, Oaxaca, Mexico
Authors: Francke Oscar F. , Monjaraz-Ruedas Rodrigo , Cruz-López Jesús A.
Published: September 2021

Sistema Huautla is the deepest cave system in the Americas at 1560 m and the fifth longest in Mexico at 89,000 m, and it is a mostly vertical network of interconnected passages. The surface landscape is rugged, ranging from 3500 to 2500 masl, intersected by streams and deep gorges. There are numerous dolinas, from hundreds to tens of meters in width and depth. The weather is basically temperate subhumid with summer rains. The average yearly rainfall is approximately 2500 mm, with a monthly average of 35 mm for the driest times of the year and up to 500 mm for the wettest month. All these conditions play an important role for achieving the highest terrestrial troglobite diversity in Mexico, containing a total of 35 species, of which 27 are possible troglobites (16 described), including numerous arachnids, millipedes, springtails, silverfish, and a single described species of beetles. With those numbers, Sistema Huautla is one of the richest cave systems in the world.
Lessons Learnt from Engineering Science Projects Participating in the Horizon 2020 Open Research Data Pilot
Authors: Austin Timothy , Bei Kyriaki , Efthymiadis Theodoros , Koumoulos Elias
Published: September 2021

Trends in the sciences are indicative of data management becoming established as a feature of the mainstream research process. In this context, the European Commission introduced an Open Research Data pilot at the start of the Horizon 2020 research programme. This initiative followed the success of the Open Access pilot implemented in the prior (FP7) research programme, which thereafter became an integral component of Horizon 2020. While the Open Access phenomenon can reasonably be argued to be one of many instances of web technologies disrupting established business models (namely publication practices and workflows established over several centuries in the case of Open Access), initiatives designed to promote research data management have no established foundation on which to build. For Open Data to become a reality and, more importantly, to contribute to the scientific process, data management best practices and workflows are required. Furthermore, with the scientific community having operated to good effect in the absence of data management, there is a need to demonstrate the merits of data management. This circumstance is complicated by the lack of the necessary ICT infrastructures, especially interoperability standards, required to facilitate the seamless transfer, aggregation and analysis of research data. Any activity aiming to promote Open Data thus needs to overcome a number of cultural and technological challenges. It is in this context that this paper examines the data management activities and outcomes of a number of projects participating in the Horizon 2020 Open Research Data pilot. The result has been to identify a number of commonly encountered benefits and issues; to assess the utilisation of data management plans; and through the close examination of specific cases, to gain insights into obstacles to data management and potential solutions. Although primarily anecdotal and difficult to quantify, the experiences reported in this paper tend to favour developing data management best practices rather than doggedly pursue the Open Data mantra. While Open Data may prove valuable in certain circumstances, there is good reason to claim that managed access to scientific data of high inherent intellectual and financial value will prove more effective in driving knowledge discovery and innovation.
Automatized Detection and Categorization of Fissure Sealants from Intraoral Digital Photographs Using Artificial Intelligence
Authors: Schlickenrieder Anne , Meyer Ole , Schönewolf Jule , Engels Paula , Hickel Reinhard , Gruhn Volker , Hesenius Marc , Kühnisch Jan
Published: September 2021

The aim of the present study was to investigate the diagnostic performance of a trained convolutional neural network (CNN) for detecting and categorizing fissure sealants from intraoral photographs using the expert standard as reference. An image set consisting of 2352 digital photographs from permanent posterior teeth (461 unsealed tooth surfaces/1891 sealed surfaces) was divided into a training set (n = 1881/364/1517) and a test set (n = 471/97/374). All the images were scored according to the following categories: unsealed molar, intact, sufficient and insufficient sealant. Expert diagnoses served as the reference standard for cyclic training and repeated evaluation of the CNN (ResNeXt-101-32x8d), which was trained by using image augmentation and transfer learning. A statistical analysis was performed, including the calculation of contingency tables and areas under the receiver operating characteristic curve (AUC). The results showed that the CNN accurately detected sealants in 98.7% of all the test images, corresponding to an AUC of 0.996. The diagnostic accuracy and AUC were 89.6% and 0.951, respectively, for intact sealant; 83.2% and 0.888, respectively, for sufficient sealant; 92.4 and 0.942, respectively, for insufficient sealant. On the basis of the documented results, it was concluded that good agreement with the reference standard could be achieved for automatized sealant detection by using artificial intelligence methods. Nevertheless, further research is necessary to improve the model performance.
Using Machine Learning Algorithms to Predict Hospital Acquired Thrombocytopenia after Operation in the Intensive Care Unit: A Retrospective Cohort Study
Authors: Cheng Yisong , Chen Chaoyue , Yang Jie , Yang Hao , Fu Min , Zhong Xi , Wang Bo , He Min , Hu Zhi , Zhang Zhongwei , Jin Xiaodong , Kang Yan , Wu Qin
Published: September 2021

Hospital acquired thrombocytopenia (HAT) is a common hematological complication after surgery. This research aimed to develop and compare the performance of seven machine learning (ML) algorithms for predicting patients that are at risk of HAT after surgery. We conducted a retrospective cohort study which enrolled adult patients transferred to the intensive care unit (ICU) after surgery in West China Hospital of Sichuan University from January 2016 to December 2018. All subjects were randomly divided into a derivation set (70%) and test set (30%). ten-fold cross-validation was used to estimate the hyperparameters of ML algorithms during the training process in the derivation set. After ML models were developed, the sensitivity, specificity, area under the curve (AUC), and net benefit (decision analysis curve, DCA) were calculated to evaluate the performances of ML models in the test set. A total of 10,369 patients were included and in 1354 (13.1%) HAT occurred. The AUC of all seven ML models exceeded 0.7, the two highest were Gradient Boosting (GB) (0.834, 0.814–0.853, p < 0.001) and Random Forest (RF) (0.828, 0.807–0.848, p < 0.001). There was no difference between GB and RF (0.834 vs. 0.828, p = 0.293); however, these two were better than the remaining five models (p < 0.001). The DCA revealed that all ML models had high net benefits with a threshold probability approximately less than 0.6. In conclusion, we found that ML models constructed by multiple preoperative variables can predict HAT in patients transferred to ICU after surgery, which can improve risk stratification and guide management in clinical practice.
Alteration in Nasopharyngeal Microbiota Profile in Aged Patients with COVID-19
Authors: Kolhe Ravindra , Sahajpal Nikhil Shri , Vyavahare Sagar , Dhanani Akhilesh S. , Adusumilli Satish , Ananth Sudha , Mondal Ashis K. , Patterson G. Taylor , Kumar Sandeep , Rojiani Amyn M. , Isales Carlos M. , Fulzele Sadanand
Published: September 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is an infectious virus that causes coronavirus disease 2019 (COVID-19) transmitted mainly through droplets and aerosol affecting the respiratory tract and lungs. Little is known regarding why some individuals are more susceptible than others and develop severe symptoms. In this study, we analyzed the nasopharyngeal microbiota profile of aged patients with COVID-19 (asymptomatic vs. symptomatic) vs. healthy individuals. We examined the nasopharynx swab of 84 aged-matched patients, out of which 27 were negative asymptomatic (NegA), 30 were positive asymptomatic (PA), and 27 patients were positive symptomatic (PSY). Our analysis revealed the presence of abundant Cyanobacterial taxa at phylum level in PA (p-value = 0.0016) and PSY (p-value = 0.00038) patients along with an upward trend in the population of Litoricola, Amylibacter, Balneola, and Aeromonas at the genus level. Furthermore, to know the relationship between the nasal microbiota composition and severity of COVID-19, we compared PA and PSY groups. Our data show that the nasal microbiota of PSY patients was significantly enriched with the signatures of two bacterial taxa: Cutibacterium (p-value = 0.045) and Lentimonas (p-value = 0.007). Furthermore, we also found a significantly lower abundance of five bacterial taxa, namely: Prevotellaceae (p-value = 7 × 10−6), Luminiphilus (p-value = 0.027), Flectobacillus (p-value = 0.027), Comamonas (p-value = 0.048), and Jannaschia (p-value = 0.012) in PSY patients. The dysbiosis of the nasal microbiota in COVID-19 positive patients might have a role in contributing to the severity of COVID-19. The findings of our study show that there is a strong correlation between the composition of the nasal microbiota and COVID-19 severity. Further studies are needed to validate our finding in large-scale samples and to correlate immune response (cytokine Strome) and nasal microbiota to identify underlying mechanisms and develop therapeutic strategies against COVID-19.
VIRDENTOPSY: Virtual Dental Autopsy and Remote Forensic Odontology Evaluation
Authors: Nuzzolese Emilio
Published: September 2021

The identification of human remains relies on the comparison of post-mortem data, collected during the autopsy, with the ante-mortem data gathered from the missing persons’ reports. DNA, fingerprints, and dental data are considered primary identifiers and are usually collected during any human identification process. Post-mortem dental data should be collected and analyzed by forensic odontologists, as a dental autopsy must not be confused with a dental examination. The virdentopsy project was inaugurated in 2020, during the COVID-19 pandemic, to allow the correct process of human remains by collecting dental data from teeth and jaws, which was then transmitted to forensic odontologists remotely for an expert opinion to achieve a generic profile of the unidentified human remains. The post-mortem dental biography is paramount to narrow the search for compatible missing persons but requires knowledge and experience of forensic odontologists. The virdentopsy process uses radiographic imaging (periapical X-rays, CT scans, panoramics), 2D/3D photos and video recording, photogrammetry documentation, 3D scanning, and live streaming where possible. This registered term was created by merging the terms “virtual” and “dental autopsy” but with no commercial benefits. The proposed process combines research topics under the field of the human rights of the dead and humanitarian forensic odontology services. It should enhance and accelerate the human identification process of the deceased, age estimation of the living, analysis of panoramic X-ray images, and be an educational tool for remote live training in forensic odontology and anatomy of skulls. This paper presents an overview of the virdentopsy process in the field of forensic odontology as a remote consultation as well as an educational tool for undergraduates and postgraduates.
Argon Bioactivation of Implants Installed Simultaneously to Maxillary Sinus Lifting without Graft. An Experimental Study in Rabbits
Authors: Omori Yuki , Botticelli Daniele , Ferri Mauro , Delgado-Ruiz Rafael , Ferreira Balan Vitor , Porfirio Xavier Samuel
Published: September 2021

Background: The treatment of the surface of titanium implants with argon plasma improved its hydrophilicity and cell adhesion, resulting in higher bone apposition on implant and graft surfaces. The spontaneous perforation over time of the sinus mucosa after sinus augmentation has been documented in experimental studies at both implants and graft particles. The aim of the present study was to evaluate the influence of plasma argon treatment of the implant surface on bone apposition and on the rate of sinus mucosa perforations. Methods: A sinus lifting procedure was performed bilaterally in sixteen rabbits, and implants, either treated with argon plasma or left without treatment (control), were placed simultaneously without grafts. After 8 weeks, histological analyses were carried out. Results: A collapse of the sinus mucosa was observed at all implants. Twenty-four out of thirty-two implants presented sinus mucosa perforations at the apex. Several perforations were also found at the threads. Thinned mucosa sites (width < 40 µm) were found around almost all implants. About 2.6–2.9 mm of the apical regions of the implant did not present signs of osseointegration and about 1.3 mm were exposed to the sinus cavity. No statistically significant differences were found between plasma and control sites. Conclusions: In conclusion, the sinus mucosa was damaged and perforated by direct contact with treated and non-treated implant surfaces. The treatment of the implant surface with argon plasma did not affect the outcomes.
Cognitive Styles, Gender, and Student Academic Performance in Engineering Education
Authors: Alalouch Chaham
Published: September 2021

Cognitive styles affect the learning process positively if tasks are matched to the cognitive style of learners. This effect becomes more pronounced in complex education, such as in engineering. We attempted to critically assess the effect of cognitive styles and gender on students’ academic performance in eight engineering majors to understand whether a cognitive style preference is associated with certain majors. We used the Cognitive Style Indicator (CoSI) with a sample of n = 584 engineering students. Multiple standard statistical tests, regression tree analysis, and cluster analysis showed that none of the three cognitive styles was exclusively associated with better performance. However, students who had a stronger preference for a cognitive style were more likely to perform better. Gender, the major, and students’ clarity about their cognitive style were shown to be the best predictors of academic performance. Female students performed better and were clearer about their preferred cognitive style, whereas male students were more capable of adapting to different learning tasks. Furthermore, certain engineering majors were shown to be associated with certain cognitive styles. We concluded the study with theoretical and practical implications for engineering education and suggestions for further research.
Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
Authors: Varol Serkan , Catma Serkan
Published: September 2021

Student retention is a wide-reaching issue that causes a concern to postsecondary institutions and policy-makers. This research aimed to examine the impact of a geo-spatial factor—distance to the closest metropolitan area—on student retention from a multi-institutional perspective, through the data collected from the Integrated Postsecondary Education Data System (2017) of the U.S. Department of Education. Using the K-means clustering technique, 329 geographically dispersed higher education institutions with similar characteristics were identified. A spatial lag model was adopted to account for spatial autocorrelation detected within the dataset. A series of hierarchical regression was then conducted to measure how well the spatial variable explained student retention rate after accounting for institutional level attributes. The student retention rate was found to decrease as a university is located away from the closest metropolitan area. This finding has crucial policy and administrative implications if analyzed within the context of rural–urban discrepancies in higher education. Extending the spatial scope of retention analysis is an important step in accurately determining the set of factors that provides a better understanding of this complex problem.
Inclusive Leadership of School Management from the View of Families: Construction and Validation of LEI-Q
Authors: López-López María del Carmen , León Guerrero María José , Crisol-Moya Emilio
Published: September 2021

The purpose of this study was to validate a questionnaire aimed at assessing, from the point of view of families, the degree to which school administrations foster inclusion in compulsory education. In order to determine the psychometric properties of the “Cuestionario liderando la educación inclusiva en centros de educación obligatoria-Familias” [Leading inclusive education in compulsory-education schools Questionnaire] (LEI-Q-Families), we carried out descriptive, exploratory, and confirmatory factor analysis. For the sample used in this study, 150 families participated. The results confirmed that it is a valid and reliable scale with a two-factor structure. One of these factors included the initiatives carried out by the school management teams to enhance the openness of each school to the community and the surrounding area. The second factor encompassed actions aimed at promoting participation in the school and turning it into an inclusive space. LEI-Q-Families proved to be an instrument of great theoretical and practical worth that has made it possible to expand our currently slender knowledge on the perceptions families have of the work done by school managers to encourage inclusion in their institutions. It facilitates family participation in processes of improvement and provides a useful self-assessment tool for school administrations that wish to improve their schools and turn them into inclusive environments.
Generator Design Considering Mover Action to Improve Energy Conversion Efficiency in a Free-Piston Engine Generator
Authors: Sato Mitsuhide , Irie Shoma , Zheng Jianping , Mizuno Tsutomu , Nishimura Fumiya , Naganuma Kaname
Published: September 2021

In a free-piston engine generator (FPEG), the power of the engine can be directly regenerated by linear generators without a crank. The mover motion of this system is interrelated with engine and power generation efficiencies due to the direct connection between the mover of the generator and the piston of the engine. The generator should be designed to improve the overall energy conversion efficiency. The dimensions and mass of the mover limit its operating stroke and drive frequency. Herein, we propose a method for designing linear generators and constructing FPEG systems, considering the mover operation to improve engine efficiency. We evaluated the effect of mover operation on the engine and generation efficiencies using thermal and electromagnetic field analysis software. The proposed design method improves the overall energy conversion efficiency compared with a generator that considers only the maximization of generation efficiency. Setting the mover operation for higher engine efficiency and designing a linear generator to realize the operation can effectively improve the energy conversion efficiency of FPEGs.
Adaptive On-Time Control Buck Converter with a Novel Virtual Inductor Current Circuit
Authors: Chou Hsiao-Hsing , Chen Hsin-Liang , Fan Yang-Hsin , Wang San-Fu
Published: September 2021

This study presents a new virtual inductor current circuit to reduce circuit complexity, which is not necessary to sense inductance current directly. The buck converter was designed to produce an output voltage of 1.0–2.5 V for a 3.0–3.6 V input voltage. The load current range was from 100 mA to 500 mA. It was simulated and verified by SIMPLIS and MathCAD. The simulation results of this buck converter show that the voltage error is within 1%, and the recovery time is smaller than 2 ms for step-up and step-down load transients. Additionally, it achieves less than 26 mV overshoot at full-load step transient response. The circuit topology would be able to fabricate using TSMC 0.35 mm 2P4M CMOS technology. The control mechanism, implementation, and design procedure are presented in this paper.
Identifying Communication Topologies on Twitter
Authors: Kustudic Mijat , Xue Bowen , Zhong Huifen , Tan Lijing , Niu Ben
Published: September 2021

Social networks are known for their decentralization and democracy. Each individual has a chance to participate and influence any discussion. Even with all the freedom, people’s behavior falls under patterns that are observed in numerous situations. In this paper, we propose a methodology that defines and searches for common communication patterns in topical networks on Twitter. We analyze clusters according to four traits: number of nodes the cluster has, their degree and betweenness centrality values, number of node types, and whether the cluster is open or closed. We find that cluster structures can be defined as (a) fixed, meaning that they are repeated across datasets/topics following uniform rules, or (b) variable if they follow an underlying rule regardless of their size. This approach allows us to classify 90% of all conversation clusters, with the number varying by topic. An increase in cluster size often results in difficulties finding topological shape rules; however, these types of clusters tend to exhibit rules regarding their node relationships in the form of centralization. Most individuals do not enter large-scale discussions on Twitter, meaning that the simplicity of communication clusters implies repetition. In general, power laws apply for the influencer connection distribution (degree centrality) even in topical networks.
Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment
Authors: Kim Svetlana , Kang Jieun , Yoon YongIk
Published: September 2021

With the evolution of the Internet of Things (IoT), edge computing technology is using to process data rapidly increasing from various IoT devices efficiently. Edge computing offloading reduces data processing time and bandwidth usage by processing data in real-time on the device where the data is generating or on a nearby server. Previous studies have proposed offloading between IoT devices through local-edge collaboration from resource-constrained edge servers. However, they did not consider nearby edge servers in the same layer with computing resources. Consequently, quality of service (QoS) degrade due to restricted resources of edge computing and higher execution latency due to congestion. To handle offloaded tasks in a rapidly changing dynamic environment, finding an optimal target server is still challenging. Therefore, a new cooperative offloading method to control edge computing resources is needed to allocate limited resources between distributed edges efficiently. This paper suggests the LODO (linked-object dynamic offloading) algorithm that provides an ideal balance between edges by considering the ready state or running state. LODO algorithm carries out tasks in the list in the order of high correlation between data and tasks through linked objects. Furthermore, dynamic offloading considers the running status of all cooperative terminals and decides to schedule task distribution. That can decrease the average delayed time and average power consumption of terminals. In addition, the resource shortage problem can settle by reducing task processing using its distributions.
NDF and PSF Analysis in Inverse Source and Scattering Problems for Circumference Geometries
Authors: Sekehravani Ehsan Akbari , Leone Giovanni , Pierri Rocco
Published: September 2021

This paper aims at discussing the resolution achievable in the reconstruction of both circumference sources from their radiated far-field and circumference scatterers from their scattered far-field observed for the 2D scalar case. The investigation is based on an inverse problem approach, requiring the analysis of the spectral decomposition of the pertinent linear operator by the Singular Value Decomposition (SVD). The attention is focused upon the evaluation of the Number of Degrees of Freedom (NDF), connected to singular values behavior, and of the Point Spread Function (PSF), which accounts for the reconstruction of a point-like unknown and depends on both the NDF and on the singular functions. A closed-form evaluation of the PSF relevant to the inverse source problem is first provided. In addition, an approximated closed-form evaluation is introduced and compared with the exact one. This is important for the subsequent evaluation of the PSF relevant to the inverse scattering problem, which is based on a similar approximation. In this case, the approximation accuracy of the PSF is verified at least in its main lobe region by numerical simulation since it is the most critical one as far as the resolution discussion is concerned. The main result of the analysis is the space invariance of the PSF when the observation is the full angle in the far-zone region, showing that resolution remains unchanged over the entire source/investigation domain in the considered geometries. The paper also poses the problem of identifying the minimum number and the optimal directions of the impinging plane waves in the inverse scattering problem to achieve the full NDF; some numerical results about it are presented. Finally, a numerical application of the PSF concept is performed in inverse scattering, and its relevance in the presence of noisy data is outlined.
Development and Verification of Infrastructure-Assisted Automated Driving Functions
Authors: Rudigier Martin , Nestlinger Georg , Tong Kailin , Solmaz Selim
Published: September 2021

Automated vehicles we have on public roads today are capable of up to SAE Level-3 conditional autonomy according to the SAE J3016 Standard taxonomy, where the driver is the main responsible for the driving safety. All the decision-making processes of the system depend on computations performed on the ego vehicle and utilizing only on-board sensor information, mimicking the perception of a human driver. It can be conjectured that for higher levels of autonomy, on-board sensor information will not be sufficient alone. Infrastructure assistance will, therefore, be necessary to ensure the partial or full responsibility of the driving safety. With higher penetration rates of automated vehicles however, new problems will arise. It is expected that automated driving and particularly automated vehicle platoons will lead to more road damage in the form of rutting. Inspired by this, the EU project ESRIUM investigates infrastructure assisted routing recommendations utilizing C-ITS communications. In this respect, specially designed ADAS functions are being developed with capabilities to adapt their behavior according to specific routing recommendations. Automated vehicles equipped with such ADAS functions will be able to reduce road damage. The current paper presents the specific use cases, as well as the developed C-ITS assisted ADAS functions together with their verification results utilizing a simulation framework.
On Analyzing Beamforming Implementation in O-RAN 5G
Authors: Mohsin Mustafa , Batalla Jordi Mongay , Pallis Evangelos , Mastorakis George , Markakis Evangelos K. , Mavromoustakis Constandinos X.
Published: September 2021

The open radio access network (O-RAN) concept is changing the landscape of mobile networks (5G deployment and 6G research). O-RAN Alliance’s suggestions that O-RAN can offer openness and intelligence to the traditional RAN vendors will enable the capability for multi-vendors to re-shape the RAN structure and optimize the network. This paper positions the main research challenges of the O-RAN approach in regards to the implementation of beamforming. We investigate the O-RAN architecture and the configurations of the interfaces between O-RAN units and present the split options between the radio and distributing units in terms of O-RAN specification and 3GPP standards. From this point, we discuss the beamforming methods in O-RAN, addressing challenges and potential solutions, and suggest the introduction of the zero-forcing equalizer as a precoding vector in the channel-information-based beamforming method. This may be one of the solutions for achieving flexibility in a high-traffic communication environment while reducing the radio unit interferences caused by implanting the precoding in the open radio unit.
Dimming Techniques Focusing on the Improvement in Luminous Efficiency for High-Brightness LEDs
Authors: Ho Kun-Che , Wang Shun-Chung , Liu Yi-Hua
Published: September 2021

The pulse width modulation (PWM) dimming mode features good dimming linearity and has been widely used for driving high-brightness light-emitting diodes (HBLEDs), in which the brightness change is reached by modulating the duty cycle of the dimming signal to regulate the average current flowing through LEDs. However, the current-illuminance characteristic curve of most LEDs is nonlinear in nature. Namely, under the same lighting power fed, the conventional PWM dimming cannot make the LED exert its best luminous efficiency (LE) specified in datasheets. This paper focuses on the study of further improving LED luminous efficacy via dimming manipulation. Thereby, two multilevel current dimming techniques with varied dimming signal voltage and varied current sensing resistance are presented. With limited dimming capability, the proposed dimming strategies can efficiently raise the luminous flux ratio without increasing the power consumption. A prototype constructed for a 115 W HBLED driver is developed and the devised dimming schemes are realized by a digital signal controller (DSC). Experimental results exhibited with illuminance-power curves and CIE1931 and CIE1976 chromaticity diagrams are given to validate the theoretical derivation and effectiveness. Compared with conventional PWM dimming, under the same illuminance, the driver average output power is respectively reduced by 17.08% and 13.17%; the improvement in average illuminance under the same output power is 13.66% and 11.17%, respectively. In addition, the entire average LE boost has respectively increased by 21.36% and 16.37%.
Deep Learning-Based Indoor Two-Dimensional Localization Scheme Using a Frequency-Modulated Continuous Wave Radar
Authors: Park Kyungeun , Lee Jeongpyo , Kim Youngok
Published: September 2021

In this paper, we propose a deep learning-based indoor two-dimensional (2D) localization scheme using a 24 GHz frequency-modulated continuous wave (FMCW) radar. In the proposed scheme, deep neural network and convolutional neural network (CNN) models that use different numbers of FMCW radars were employed to overcome the limitations of the conventional 2D localization scheme that is based on multilateration methods. The performance of the proposed scheme was evaluated experimentally and compared with the conventional scheme under the same conditions. According to the results, the 2D location of the target could be estimated with a proposed single radar scheme, whereas two FMCW radars were required by the conventional scheme. Furthermore, the proposed CNN scheme with two FMCW radars produced an average localization error of 0.23 m, while the error of the conventional scheme with two FMCW radars was 0.53 m.
Automatic Multilingual Stopwords Identification from Very Small Corpora
Authors: Ferilli Stefano
Published: September 2021

Tools for Natural Language Processing work using linguistic resources, that are language-specific. The complexity of building such resources causes many languages to lack them. So, learning them automatically from sample texts would be a desirable solution. This usually requires huge training corpora, which are not available for many local languages and jargons, lacking a wide literature. This paper focuses on stopwords, i.e., terms in a text which do not contribute in conveying its topic or content. It provides two main, inter-related and complementary, methodological contributions: (i) it proposes a novel approach based on term and document frequency to rank candidate stopwords, that works also on very small corpora (even single documents); and (ii) it proposes an automatic cutoff strategy to select the best candidates in the ranking, thus addressing one of the most critical problems in the stopword identification practice. Nice features of these approaches are that (i) they are generic and applicable to different languages, (ii) they are fully automatic, and (iii) they do not require any previous linguistic knowledge. Extensive experiments show that both are extremely effective and reliable. The former outperforms all comparable approaches in the state-of-the-art, both in terms of performance (Precision stays at 100% or nearly so for a large portion of the top-ranked candidate stopwords, while Recall is quite close to the maximum reachable in theory.) and in smooth behavior (Precision is monotonically decreasing, and Recall is monotonically increasing, allowing the experimenter to choose the preferred balance.). The latter is more flexible than existing solutions in the literature, requiring just one parameter intuitively related to the balance between Precision and Recall one wishes to obtain.
A Wide-Angle Scanning Sub-Terahertz Leaky-Wave Antenna Based on a Multilayer Dielectric Image Waveguide
Authors: Torabi Yalda , Dadashzadeh Gholamreza , Hadeie Milad , Oraizi Homayoon , Lalbakhsh Ali
Published: September 2021

This paper presents a new layered dielectric leaky-wave antenna (LWA) for the sub-terahertz (THz) frequency range capable of efficient operation at the broadside with a wide beam scanning angle and stable gain. It consists of a conductor-backed alumina dielectric image line (DIL) with two different dielectric layers mounted on top of each other for performance improvement. The upper layer is a high permittivity RO6010 substrate to enhance the directivity as a superstrate and the lower layer is a low-permittivity RT/duroid 5880 substrate stacked on the alumina DIL to prevent the probable excitation of higher-order modes in the DIL channel. A 15-element linear array of radiating overlapped discs is used to mitigate the open stop-band (OSB) problem, fed by the mentioned waveguide, was designed and simulated at frequencies around 170 GHz. The dominant mode of the layered dielectric waveguide is perturbed by the infinite space harmonics generated by two sets of overlapped discs periodically sandwiched between the layers. It exhibited a relatively wide impedance bandwidth of 28.19% (157.5–206 GHz). Its radiation mechanism has been widely studied through simulations. The results revealed that the antenna provides a wide scanning capability through the broadside from −23° to 38°, covering the frequency range between 157.5 GHz and 201.5 GHz. For an array with 15 radiating elements, the simulated peak gain in the band is 15 dBi and the broadside gain is 13.6 dBi at 172 GHz.
Modeling and Analysis of Electromagnetic Field and Temperature Field of Permanent-Magnet Synchronous Motor for Automobiles
Authors: Jia Meixia , Hu Jianjun , Xiao Feng , Yang Ying , Deng Chenghao
Published: September 2021

In order to study the interaction of electromagnetic fields and temperature fields in a motor, the iron loss curve at different frequencies of silicon steel and the B-H curve at different temperatures of the permanent magnet (PM) were obtained to establish the electromagnetic model of the permanent magnet synchronous motor (PMSM). Then, unidirectional and bidirectional coupling models were established and analyzed based on the multi-physical field. By establishing a bidirectional coupling model, the temperature field distribution and electromagnetic characteristics of the motor were analyzed. The interaction between temperature and electromagnetic field was studied. Finally, the temperature of the PMSM was tested. The results showed that the bidirectional coupling results were closer to the test result because of the consideration of the interaction between electromagnetic and thermal fields.