bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigations on the Interaction of EDTA with Calcium Silicate Hydrate and Its Impact on the U(VI) Sorption
Authors: Maragkou Eleni , Pashalidis Ioannis
Published: August 2021

The interaction of EDTA with calcium silicate hydrate (C-S-H) and its impact on the sorption of U(VI) by C-S-H in the presence of EDTA at varying concentrations has been investigated under N2 and ambient atmosphere. The solid phase characterization was performed by FTIR, XRD and TGA measurements and the uranium concentration in solution has been determined by alpha-spectroscopy. At increased EDTA concentrations ([EDTA] > 0.1 M) calcium is complexed and extensively extracted from the solid resulting in a quantitative dissolution of the Ca(OH)2 phase and deterioration of C-S-H. At lower EDTA concentrations ([EDTA] ≤ 0.01 M), EDTA is sorbed into the solid phase and the associated adsorption capacity (qmax = 0.67 mol/kg) has been evaluated by fitting the corresponding data with the Langmuir isotherm model. The incorporation of EDTA in the C-S-H matrix was corroborated by FTIR, XRD and TGA measurements. Regarding the effect of EDTA on the U(VI) sorption by C-S-H, evaluation of the experimental data reveal a significant decrease of the Kd values in the presence of EDTA most probably due to the stabilization of U(VI) in the form of U(VI)-EDTA complexes in solution. Under ambient conditions a further decrease of the Kd values is observed because of the formation of U(VI)-carbonato complexes related to CO2 dissolution and hydrolysis.
Theoretical Analysis of Si2H6 Adsorption on Hydrogenated Silicon Surfaces for Fast Deposition Using Intermediate Pressure SiH4 Capacitively Coupled Plasma
Authors: Park Hwanyeol , Kim Ho Jun
Published: August 2021

The rapid and uniform growth of hydrogenated silicon (Si:H) films is essential for the manufacturing of future semiconductor devices; therefore, Si:H films are mainly deposited using SiH4-based plasmas. An increase in the pressure of the mixture gas has been demonstrated to increase the deposition rate in the SiH4-based plasmas. The fact that SiH4 more efficiently generates Si2H6 at higher gas pressures requires a theoretical investigation of the reactivity of Si2H6 on various surfaces. Therefore, we conducted first-principles density functional theory (DFT) calculations to understand the surface reactivity of Si2H6 on both hydrogenated (H-covered) Si(001) and Si(111) surfaces. The reactivity of Si2H6 molecules on hydrogenated Si surfaces was more energetically favorable than on clean Si surfaces. We also found that the hydrogenated Si(111) surface is the most efficient surface because the dissociation of Si2H6 on the hydrogenated Si(111) surface are thermodynamically and kinetically more favorable than those on the hydrogenated Si(001) surface. Finally, we simulated the SiH4/He capacitively coupled plasma (CCP) discharges for Si:H films deposition.
Surface Modification and Functional Structure Space Design to Improve the Cycle Stability of Silicon Based Materials as Anode of Lithium Ion Batteries
Authors: Di Fang , Zhou Weimin , Yang Haiming , Sun Chengguo , Geng Xin , Chen Yiqing , Li Lixiang , Liu Zunfeng , An Baigang
Published: August 2021

Silicon anode is considered as one of the candidates for graphite replacement due to its highest known theoretical capacity and abundant reserve on earth. However, poor cycling stability resulted from the “volume effect” in the continuous charge-discharge processes become the biggest barrier limiting silicon anodes development. To avoid the resultant damage to the silicon structure, some achievements have been made through constructing the structured space and pore design, and the cycling stability of the silicon anode has been improved. Here, progresses on designing nanostructured materials, constructing buffered spaces, and modifying surfaces/interfaces are mainly discussed and commented from spatial structure and pore generation for volumetric stress alleviation, ions transport, and electrons transfer improvement to screen out the most effective optimization strategies for development of silicon based anode materials with good property.
Glassy Polymers—Diffusion, Sorption, Ageing and Applications
Authors: Arya Raj Kumar , Thapliyal Devyani , Sharma Jyoti , Verros George D.
Published: August 2021

For the past few decades, researchers have been intrigued by glassy polymers, which have applications ranging from gas separations to corrosion protection to drug delivery systems. The techniques employed to examine the sorption and diffusion of small molecules in glassy polymers are the subject of this review. Diffusion models in glassy polymers are regulated by Fickian and non-Fickian diffusion, with non-Fickian diffusion being more prevalent. The characteristics of glassy polymers are determined by sorption isotherms, and different models have been proposed in the literature to explain sorption in glassy polymers over the last few years. This review also includes the applications of glassy polymers. Despite having many applications, current researchers still have difficulty in implementing coating challenges due to issues such as physical ageing, brittleness, etc., which are briefly discussed in the review.
A Study of the Composition and Dissolution of Jianshui Purple Pottery in Yunnan, China
Authors: Liu Chang , Xie Heng , Nie Lei , Wang Hong , He Yuanyuan
Published: August 2021

Pottery is a gem in the history of human civilization and a crystallization of human wisdom. Yunnan Jianshui purple pottery is one of the four famous types of pottery in China, with a long history and superb craftsmanship. Used as tableware, research on the composition and element dissolution of pottery is extremely significant for production and health. This paper takes Jianshui purple pottery as its research object, samples its raw ores and finished products, and conducts X-ray fluorescence, scanning electron microscopy, inductively coupled plasma mass spectrometry experiments, and dissolution tests. The chemical composition, microstructure, and trace element concentrations of pottery before and after firing were measured. Results show that the dissolution of purple pottery under various use scenarios is low and meets health requirements. Combined with the characteristics of purple pottery, the composition changes and the mechanism of change before and after firing are discussed, which can be used as the theoretical basis for improving pottery production in the future.
Deep NIR-I Emissive Iridium(III) Complex Bearing D-A Ligand: Synthesis, Photophysical Properties and DFT/TDDFT Calculation
Authors: Jiang Jia-Yang , Xu Zi-Han , Li Tang , Cai Da-Hua , Zhou Hui , Chen Ze-Jing
Published: August 2021

Near-infrared (NIR) phosphorescent iridium(III) complexes have been demonstrated to possess photophysical properties superior to those of traditional NIR dyes. However, the NIR emission wavelength is restricted in the range of 700–800 nm. For realizing deeper NIR emission, a novel type of iridium(III) complex was designed and synthesized in this work. The main ligand of the iridium(III) complex was constructed using a donor-acceptor structure containing benzothiophene as the donor and quinoxaline as the acceptor. The β-diketone derivative was chosen as the auxiliary ligand owing to its symmetrical structure and p-donating character. The complex exhibits deep NIR-I phosphorescence (764 nm in CH2Cl2, 811 nm in aqueous solution) and broad full width at half maximum (108 nm in CH2Cl2, 154 nm in aqueous solution). Theoretical calculations based on the density function and time-dependent density function were carried out to support the experimental data. Moreover, in vitro biological performance of the complex was determined as well. This work supports the possibility that via a systematic transformation between the D and A units, the photophysical performance of NIR emissive iridium(III) complexes can be greatly improved.
The Effect of Incorporating Ultra-Fine Spherical Particles on Rheology and Engineering Properties of Commercial Ultra-High-Performance Grout
Authors: Lin Wei-Ting , Zhao Wen-Que , Chang Yi-Hua , Yang Jiann-Shi , Cheng An
Published: August 2021

In this study, ultra-fine spherical particles of silica fume and reactive ultra-fine fly ash were added to a mixture of commercial ultra-high-performance grout (UHPG) with the aim of enhancing the rheological properties, compressive strength, compactness, and permeability. This commercial UHPG study was conducted in collaboration with Triaxis Corporation (Changsha city, Hunan province, China). A water-to-binder ratio of 0.21 and a binder-to-fine aggregates ratio of 1.17 were used as fixed parameters, and the binders were a combination of type-II Portland cement, sulphoaluminate cement, silica fume, and reactive ultra-fine fly ash (RUFA). Polycarboxylate superplasticizer powder was used to control the rheology. The results revealed excellent compressive strength, volume stability, and resistance to chloride penetration. Mercury intrusion porosimetry and scanning electron microscopy tests revealed that the medium-sized RUFA particles with small silica fume particles completely filled the spaces between large cement particles to achieve optimal densification. This mixture also produced dense hydration and calcium-silicate-hydrates colloids, which filled the microstructures of the UHPG resulting in excellent engineering properties and durability. This commercially available UHPG mix responded to excellent compressive strengths approaching 120 MPa and exhibited good workability with a loss of slump-flow rate up to 33% after 60 min. It also exhibited very low abrasion resistance (0.5%), stable shrinkage and expansion rates (stabilization over 10 days), very low chloride diffusion coefficient (less than 0.1 × 10−14 m2/s) with a denser microstructure. This commercial UHPG (UHPG-120) has been developed to meet the needs of the market.
X-ray Single Crystal Structure, Tautomerism Aspect, DFT, NBO, and Hirshfeld Surface Analysis of a New Schiff Bases Based on 4-Amino-5-Indol-2-yl-1,2,4-Triazole-3-Thione Hybrid
Authors: Boraei Ahmed , Soliman Saied , Haukka Matti , El Tamany El , Al-Majid Abdullah , Barakat Assem
Published: August 2021

Four different new Schiff basses tethered indolyl-triazole-3-thione hybrid were designed and synthesized. X-ray single crystal structure, tautomerism, DFT, NBO and Hirshfeld analysis were explored. X-ray crystallographic investigations with the aid of Hirshfeld calculations were used to analyze the molecular packing of the studied systems. The H···H, H···C, S···H, Br···C, O···H, C···C and N···H interactions are the most important in the molecular packing of 3. In case of 4, the S···H, N···H, S···C and C···C contacts are the most significant. The results obtained from the DFT calculations indicated that the thione tautomer is energetically lower than the thiol one by 13.9545 and 13.7464 kcal/mol for 3 and 4, respectively. Hence, the thione tautomer is the most stable one which agree with the reported X-ray structure. In addition, DFT calculations were used to compute the electronic properties while natural bond orbital calculations were used to predict the stabilization energies due to conjugation effects. Both compounds are polar where 4 (3.348 Debye) has a higher dipole moment than 3 (2.430 Debye).
Improvement of Organic Soil Shear Strength through Calcite Precipitation Method Using Soybeans as Bio-Catalyst
Authors: Putra Heriansyah , Erizal  , Sutoyo  , Simatupang Minson , Yanto Dede Heri Yuli
Published: August 2021

Organic soil has a high content of water and compressibility. Besides that, it has a low specific gravity, density, and shear strength. This study evaluates the applicability of the soybean crude urease for calcite precipitation (SCU-CP) method and its effectiveness in organic soil as a soil-amelioration technique. Various soybean concentrations were mixed with a reagent composed of urea and calcium chloride to produce the treatment solution. Its effect on the hydrolysis rate, pH, and amount of precipitated calcite was evaluated through test-tube experiments. SEM-EDS tests were performed to observe the mineralogy and morphology of the untreated and treated samples. The treatment solution composed of the reagent and various concentrations of soybeans was applied to organic soil. The increasing strength of the organic soil was evaluated using direct shear (DS) and unconfined compression (UCS) tests. The test-tube results show that a hydrolysis rate of 1600 u/g was obtained when using 50 g/L of soybeans with a precipitation ratio of 100%. The mechanical tests show a significant enhancement in the parameters of the organic soil’s shear strength. A shear strength improvement of 50% was achieved in this study. A UCS of 148 kPa and cohesion of 50 kPa was obtained in the treated samples of organic soil. This research elucidates that the SCU-CP is an effective technique for improving organic soil’s shear strength.
Deep-Level Traps Responsible for Persistent Photocurrent in Pulsed-Laser-Deposited β-Ga2O3 Thin Films
Authors: Tak Bhera Ram , Yang Ming-Min , Alexe Marin , Singh Rajendra
Published: August 2021

Gallium oxide (β-Ga2O3) is emerging as a promising wide-bandgap semiconductor for optoelectronic and high-power electronic devices. In this study, deep-level defects were investigated in pulsed-laser-deposited epitaxial films of β-Ga2O3. A deep ultraviolet photodetector (DUV) fabricated on β-Ga2O3 film showed a slow decay time of 1.58 s after switching off 250 nm wavelength illumination. Generally, β-Ga2O3 possesses various intentional and unintentional trap levels. Herein, these traps were investigated using the fractional emptying thermally stimulated current (TSC) method in the temperature range of 85 to 473 K. Broad peaks in the net TSC curve were observed and further resolved to identify the characteristic peak temperature of individual traps using the fractional emptying method. Several deep-level traps having activation energies in the range of 0.16 to 1.03 eV were identified. Among them, the trap with activation energy of 1.03 eV was found to be the most dominant trap level and it was possibly responsible for the persistent photocurrent in PLD-grown β-Ga2O3 thin films. The findings of this current work could pave the way for fabrication of high-performance DUV photodetectors.
Current Overview of Treatment for Metastatic Bone Disease
Authors: Tsukamoto Shinji , Kido Akira , Tanaka Yasuhito , Facchini Giancarlo , Peta Giuliano , Rossi Giuseppe , Mavrogenis Andreas F.
Published: August 2021

The number of patients with bone metastasis increases as medical management and surgery improve the overall survival of patients with cancer. Bone metastasis can cause skeletal complications, including bone pain, pathological fractures, spinal cord or nerve root compression, and hypercalcemia. Before initiation of treatment for bone metastasis, it is important to exclude primary bone malignancy, which would require a completely different therapeutic approach. It is essential to select surgical methods considering the patient’s prognosis, quality of life, postoperative function, and risk of postoperative complications. Therefore, bone metastasis treatment requires a multidisciplinary team approach, including radiologists, oncologists, and orthopedic surgeons. Recently, many novel palliative treatment options have emerged for bone metastases, such as stereotactic body radiation therapy, radiopharmaceuticals, vertebroplasty, minimally invasive spine stabilization with percutaneous pedicle screws, acetabuloplasty, embolization, thermal ablation techniques, electrochemotherapy, and high-intensity focused ultrasound. These techniques are beneficial for patients who may not benefit from surgery or radiotherapy.
Endemic and Threatened Amazona Parrots of the Atlantic Forest: An Overview of Their Geographic Range and Population Size
Authors: Zulian Viviane , Miller David A. W. , Ferraz Gonçalo
Published: August 2021

Amazona is the largest genus of the Psittacidae, one of the most threatened bird families. Here, we study four species of Amazona (Amazona brasiliensis, A. pretrei, A. vinacea, and A. rhodocorytha) that are dependent on a highly vulnerable biome: the Brazilian Atlantic Forest. To examine their distribution and abundance, we compile abundance estimates and counts, and develop site-occupancy models of their geographic range. These models integrate data from formal research and citizen science platforms to estimate probabilistic maps of the species’ occurrence throughout their range. Estimated range areas varied from 15,000 km2 for A. brasiliensis to more than 400,000 km2 for A. vinacea. While A. vinacea is the only species with a statistical estimate of abundance (~8000 individuals), A. pretrei has the longest time series of roost counts, and A. rhodocorytha has the least information about population size. The highest number of individuals counted in one year was for A. pretrei (~20,000), followed by A. brasiliensis (~9000). Continued modeling of research and citizen science data, matched with collaborative designed surveys that count parrots at their non-breeding roosts, are essential for an appropriate assessment of the species’ status, as well as for examining the outcome of conservation actions.
Molecular Diversity of Methicillin-Resistant and -Susceptible Staphylococcus aureus Detected in Animals: A Focus on Aquatic Animals
Authors: Silva Vanessa , Monteiro Andreia , Porto Maria , Sampaio Ana , Maltez Luís , Pereira José Eduardo , Aonofriesei Florin , Capelo José Luis , Igrejas Gilberto , Poeta Patrícia
Published: August 2021

Staphylococcus aureus (S. aureus) are one of the best-known opportunistic pathogens capable of causing different types of infections in animals. Furthermore, it has the ability to acquire resistance to various antibiotics very easily. Methicillin-resistant S. aureus (MRSA) are currently of great concern as they are the leading cause of infections in humans and animals, with a major impact on health and the economy. Several studies already demonstrate that the spread of MRSA is constantly increasing due to its ability to form reservoirs in humans, animals and the environment. In fact, several works have already identified the presence of these bacteria in animals, including domestic animals, farm animals and even wild animals. Furthermore, the incidence of various S. aureus strains in aquatic animals has also been reported by different authors, although it is still a rarely discussed topic. Some of these strains have previously been associated with humans and other animals. Strain 398 is the strain that manages to infect a wider spectrum of hosts, having been identified in several different species. Aside from this strain, many others have yet to be identified. In addition, many of these strains have virulence factors and antibiotic resistance genes that worsen the situation. The present work is a review of studies that intend to investigate the epidemiology of this agent in samples of aquatic animals from different origins, in order to better understand its distribution, prevalence and the molecular lineages associated with these species.
Novel Mutation in APC Gene Associated with Multiple Osteomas in a Family and Review of Genotype-Phenotype Correlations of Extracolonic Manifestations in Gardner Syndrome
Authors: Antohi Cristina , Haba Danisia , Caba Lavinia , Ciofu Mihai Liviu , Drug Vasile-Liviu , Bărboi Oana-Bogdana , Dobrovăț Bogdan Ionuț , Pânzaru Monica-Cristina , Gorduza Nicoleta Carmen , Lupu Vasile Valeriu , Dimofte Doina , Gug Cristina , Gorduza Eusebiu Vlad
Published: August 2021

Gardner syndrome is a neoplasic disease that associates intestinal polyposis and colorectal adenocarcinoma with osteomas and soft tissue tumors determined by germline mutations in the APC gene. The early diagnosis and identification of high-risk individuals are important because patients have a 100% risk of colon cancer. We present the case of a family with Gardner syndrome. Cephalometric, panoramic X-rays and CBCT of the proband and her brother showed multiple osteomas affecting the skull bones, mandible and paranasal sinuses. The detailed family history showed an autosomal dominant transmission with the presence of the disease in the mother and maternal grandfather of the proband. Both had the typical signs of disease and died in the fourth decade of life. Based on these aspects the clinical diagnosis was Gardner syndrome. By gene sequencing, a novel pathogenic variant c.4609dup (p.Thr1537Asnfs*7) in heterozygous status was identified in the APC gene in both siblings. We reviewed literature data concerning the correlation between the localization of mutations in the APC gene and the extracolonic manifestations of familial adenomatous polyposis as well as their importance in early diagnosis and adequate oncological survey of patients and families based on abnormal genomic variants.
Structured Reporting of Lung Cancer Staging: A Consensus Proposal
Authors: Granata Vincenza , Grassi Roberto , Miele Vittorio , Larici Anna Rita , Sverzellati Nicola , Cappabianca Salvatore , Brunese Luca , Maggialetti Nicola , Borghesi Andrea , Fusco Roberta , Balbi Maurizio , Urraro Fabrizio , Buccicardi Duccio , Bortolotto Chandra , Prost Roberto , Rengo Marco , Baratella Elisa , De Filippo Massimo , Barresi Carmelo , Palmucci Stefano , Busso Marco , Calandriello Lucio , Sansone Mario , Neri Emanuele , Coppola Francesca , Faggioni Lorenzo
Published: August 2021

Background: Structured reporting (SR) in radiology is becoming necessary and has recently been recognized by major scientific societies. This study aimed to build CT-based structured reports for lung cancer during the staging phase, in order to improve communication between radiologists, members of the multidisciplinary team and patients. Materials and Methods: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi exercise was used to build the structural report and to assess the level of agreement for all the report sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to perform a quality analysis according to the average inter-item correlation. Results: The final SR version was built by including 16 items in the “Patient Clinical Data” section, 4 items in the “Clinical Evaluation” section, 8 items in the “Exam Technique” section, 22 items in the “Report” section, and 5 items in the “Conclusion” section. Overall, 55 items were included in the final version of the SR. The overall mean of the scores of the experts and the sum of scores for the structured report were 4.5 (range 1–5) and 631 (mean value 67.54, STD 7.53), respectively, in the first round. The items of the structured report with higher accordance in the first round were primary lesion features, lymph nodes, metastasis and conclusions. The overall mean of the scores of the experts and the sum of scores for staging in the structured report were 4.7 (range 4–5) and 807 (mean value 70.11, STD 4.81), respectively, in the second round. The Cronbach’s alpha (Cα) correlation coefficient was 0.89 in the first round and 0.92 in the second round for staging in the structured report. Conclusions: The wide implementation of SR is critical for providing referring physicians and patients with the best quality of service, and for providing researchers with the best quality of data in the context of the big data exploitation of the available clinical data. Implementation is complex, requiring mature technology to successfully address pending user-friendliness, organizational and interoperability challenges.
Histological Hallmarks of Mucosal Healing in Inflammatory Bowel Diseases in the Era of Monoclonal Antibodies Therapy: New Insights and Perspectives
Authors: Cazzato Gerardo , Colagrande Anna , Andriola Valeria , Lettini Teresa , Cicco Sebastiano , Candance Pragnell Mary Victoria , Resta Leonardo , Vincenti Leonardo , Ingravallo Giuseppe
Published: August 2021

Background: Chronic inflammatory bowel diseases (IBDs) are gaining increasing attention, both because they can severely reduce the quantity and quality of life, and because the advent of monoclonal antibodies has profoundly changed the natural history of these diseases. In recent years, the concept of mucosal healing has assumed a certain importance, and there are more and more clinical and pharmacological trials that consider this parameter among their endpoints, so much so that it may soon be included among the desirable clinical outcomes of patients with IBD. Methods: We performed a literature review of the Pubmed, Medline, and Web of Science (WoS) databases. Results: We selected 88 articles and then removed 6 duplicates; the final sample after accurate application of the inclusion criteria numbered 73 articles, with a level of evidence rating of three or four, according to Oxfords Evidence-based medicine. Our aim was to study the histological impact of monoclonal antibody therapies on mucosal healing, taking into consideration the few studies present in the literature. To perform this review, we compared studies that examined patients with Crohn’s disease (CD) and/or ulcerative colitis (UC) undergoing monoclonal therapy versus patients undergoing other non-biological therapies (PICO statements). Conclusions: We try to delineate how monoclonal antibodies have changed the natural history of IBD, acting at the microscopic level, and we believe that a careful analysis of the histopathology and the definition of the objective criteria for “Mucosa Healing” should enable this concept to be included among the clinical endpoints of patients affected by IBD, thus contributing to a better therapeutic management of these patients.
A Fetus with Congenital Microcephaly, Microphthalmia and Cataract Was Detected with Biallelic Variants in the OCLN Gene: A Case Report
Authors: Ng Vivian Kwun Sin , Lau Tze Kin , Kan Anita Sik Yau , Chung Brian Hon Yin , Luk Ho Ming , Ng Wai Fu , Shi Mengmeng , Choy Kwong Wai , Cao Ye , Leung Wing Cheong
Published: August 2021

Microcephaly and microphthalmia are both rare congenital abnormalities, while concurrently, these two are even rarer. The underlying etiology would be complex interplaying between heterogeneous genetic background and the environmental pathogens, particularly during critical periods of early tissue development. Here, we reported a prenatal case with microcephaly, microphthalmia, and bilateral cataracts detected by ultrasonography and confirmed by autopsy. Various routine infection-related tests and invasive genetic testing were negative. Whole genome sequencing of fetus and parents revealed OCLN gene defects may be associated with these multiple congenital abnormalities.
Dimensionality Reduction of SPD Data Based on Riemannian Manifold Tangent Spaces and Isometry
Authors: Gao Wenxu , Ma Zhengming , Gan Weichao , Liu Shuyu
Published: August 2021

Symmetric positive definite (SPD) data have become a hot topic in machine learning. Instead of a linear Euclidean space, SPD data generally lie on a nonlinear Riemannian manifold. To get over the problems caused by the high data dimensionality, dimensionality reduction (DR) is a key subject for SPD data, where bilinear transformation plays a vital role. Because linear operations are not supported in nonlinear spaces such as Riemannian manifolds, directly performing Euclidean DR methods on SPD matrices is inadequate and difficult in complex models and optimization. An SPD data DR method based on Riemannian manifold tangent spaces and global isometry (RMTSISOM-SPDDR) is proposed in this research. The main contributions are listed: (1) Any Riemannian manifold tangent space is a Hilbert space isomorphic to a Euclidean space. Particularly for SPD manifolds, tangent spaces consist of symmetric matrices, which can greatly preserve the form and attributes of original SPD data. For this reason, RMTSISOM-SPDDR transfers the bilinear transformation from manifolds to tangent spaces. (2) By log transformation, original SPD data are mapped to the tangent space at the identity matrix under the affine invariant Riemannian metric (AIRM). In this way, the geodesic distance between original data and the identity matrix is equal to the Euclidean distance between corresponding tangent vector and the origin. (3) The bilinear transformation is further determined by the isometric criterion guaranteeing the geodesic distance on high-dimensional SPD manifold as close as possible to the Euclidean distance in the tangent space of low-dimensional SPD manifold. Then, we use it for the DR of original SPD data. Experiments on five commonly used datasets show that RMTSISOM-SPDDR is superior to five advanced SPD data DR algorithms.
Distance-Based Knowledge Measure for Intuitionistic Fuzzy Sets with Its Application in Decision Making
Authors: Wu Xuan , Song Yafei , Wang Yifei
Published: August 2021

Much attention has been paid to construct an applicable knowledge measure or uncertainty measure for Atanassov’s intuitionistic fuzzy set (AIFS). However, many of these measures were developed from intuitionistic fuzzy entropy, which cannot really reflect the knowledge amount associated with an AIFS well. Some knowledge measures were constructed based on the distinction between an AIFS and its complementary set, which may lead to information loss in decision making. In this paper, knowledge amount of an AIFS is quantified by calculating the distance from an AIFS to the AIFS with maximum uncertainty. Axiomatic properties for the definition of knowledge measure are extended to a more general level. Then the new knowledge measure is developed based on an intuitionistic fuzzy distance measure. The properties of the proposed distance-based knowledge measure are investigated based on mathematical analysis and numerical examples. The proposed knowledge measure is finally applied to solve the multi-attribute group decision-making (MAGDM) problem with intuitionistic fuzzy information. The new MAGDM method is used to evaluate the threat level of malicious code. Experimental results in malicious code threat evaluation demonstrate the effectiveness and validity of proposed method.
Parent Enablers of Education Support for Young People with Hearing Impairment in Pakistan
Authors: Hammad Tehmina
Published: August 2021

This article examines the support received by young people with hearing impairment from parent enablers of education in Pakistan. In this ethically designed research, the society’s learning pathways of strong and weak knowledge and education centralised the voice of young people with hearing impairment as a methodology to evaluate society’s influence on parent enablers support, including from for-profit and not-for-profit education. The semi-structured interviews were conducted with 20 young people with hearing impairment, 10 each from for-profit and not-for-profit education. The case-by-case analysis of young peoples’ voice showed that in strong pathway, the binding together of family support in education with society formed young peoples’ equal but different identity that shaped an imbalance in gender and social choice of impairment over poverty with restricted translation of for-profit education in employment outside the family. In weak pathway, the family support in education disconnected from society formed young peoples’ same but unequal identity that shaped conflict in gender and social choice of poverty over impairment with limited conversion of not-for-profit education in local employment. In conclusion, alignment of society and parent enablers of education with reference to gender is required for young peoples’ entry in outside and local employment for sustainable development in Pakistan.
Unsupervised Feature Learning for Speech Emotion Recognition Based on Autoencoder
Authors: Ying Yangwei , Tu Yuanwu , Zhou Hong
Published: August 2021

Speech signals contain abundant information on personal emotions, which plays an important part in the representation of human potential characteristics and expressions. However, the deficiency of emotion speech data affects the development of speech emotion recognition (SER), which also limits the promotion of recognition accuracy. Currently, the most effective approach is to make use of unsupervised feature learning techniques to extract speech features from available speech data and generate emotion classifiers with these features. In this paper, we proposed to implement autoencoders such as a denoising autoencoder (DAE) and an adversarial autoencoder (AAE) to extract the features from LibriSpeech for model pre-training, and then conducted experiments on the Interactive Emotional Dyadic Motion Capture (IEMOCAP) datasets for classification. Considering the imbalance of data distribution in IEMOCAP, we developed a novel data augmentation approach to optimize the overlap shift between consecutive segments and redesigned the data division. The best classification accuracy reached 78.67% (weighted accuracy, WA) and 76.89% (unweighted accuracy, UA) with AAE. Compared with state-of-the-art results to our knowledge (76.18% of WA and 76.36% of UA with the supervised learning method), we achieved a slight advantage. This suggests that using unsupervised learning benefits the development of SER and provides a new approach to eliminate the problem of data scarcity.
Efficient Opponent Exploitation in No-Limit Texas Hold’em Poker: A Neuroevolutionary Method Combined with Reinforcement Learning
Authors: Xu Jiahui , Chen Jing , Chen Shaofei
Published: August 2021

In the development of artificial intelligence (AI), games have often served as benchmarks to promote remarkable breakthroughs in models and algorithms. No-limit Texas Hold’em (NLTH) is one of the most popular and challenging poker games. Despite numerous studies having been conducted on this subject, there are still some important problems that remain to be solved, such as opponent exploitation, which means to adaptively and effectively exploit specific opponent strategies; this is acknowledged as a vital issue especially in NLTH and many real-world scenarios. Previous researchers tried to use an off-policy reinforcement learning (RL) method to train agents that directly learn from historical strategy interactions but suffered from challenges of sparse rewards. Other researchers instead adopted neuroevolutionary (NE) method to replace RL for policy parameter updates but suffered from high sample complexity due to the large-scale problem of NLTH. In this work, we propose NE_RL, a novel method combing NE with RL for opponent exploitation in NLTH. Our method contains a hybrid framework that uses NE’s advantage of evolutionary computation with a long-term fitness metric to address the sparse rewards feedback in NLTH and retains RL’s gradient-based method for higher learning efficiency. Experimental results against multiple baseline opponents have proved the feasibility of our method with significant improvement compared to previous methods. We hope this paper provides an effective new approach for opponent exploitation in NLTH and other large-scale imperfect information games.
A Review of Low-Voltage Renewable Microgrids: Generation Forecasting and Demand-Side Management Strategies
Authors: Aybar-Mejía Miguel , Villanueva Junior , Mariano-Hernández Deyslen , Santos Félix , Molina-García Angel
Published: August 2021

It is expected that distribution power systems will soon be able to connect a variety of microgrids from residential, commercial, and industrial users, and thus integrate a variety of distributed generation technologies, mainly renewable energy sources to supply their demands. Indeed, some authors affirm that distribution networks will propose significant changes as a consequence of this massive integration of microgrids at the distribution level. Under this scenario, the control of distributed generation inverters, demand management systems, renewable resource forecasting, and demand predictions will allow better integration of such microgrid clusters to decongest power systems. This paper presents a review of microgrids connected at distribution networks and the solutions that facilitate their integration into such distribution network level, such as demand management systems, renewable resource forecasting, and demand predictions. Recent contributions focused on the application of microgrids in Low-Voltage distribution networks are also analyzed and reviewed in detail. In addition, this paper provides a critical review of the most relevant challenges currently facing electrical distribution networks, with an explicit focus on the massive interconnection of electrical microgrids and the future with relevant renewable energy source integration.
Practical Challenges of High-Power IGBT’s I-V Curve Measurement and Its Importance in Reliability Analysis
Authors: Alavi Omid , Van Cappellen Leander , De Ceuninck Ward , Daenen Michaël
Published: August 2021

This paper examines the practical challenges of simplified setups aimed at achieving high-power IGBTs’ IC–VCE curve. The slope of this I–V curve (which is defined as on-resistance RCE) and the point where the VCE–VGE curve visibly bends (threshold gate voltage) can be suitable failure precursor parameters to determine an IGBT’s health condition. A simplified/affordable design for these specific measurements can be used for in-situ condition monitoring or field testing of switching devices. First, the possible I–V curve measurement methods are discussed in detail in order to prevent self-heating. The selected design includes two IGBTs in which the high-side IGBT was the device under test (DUT) with a constant gate voltage (VGE) of 15 V. Then, the low-side IGBT was switched by a short pulse (50 μs) to impose a high-current pulse on the DUT. The VCE–VGE curve was also extracted as an important failure-precursor indicator. In the next stage, a power-cycling test was performed, and the impact of degradation on the IGBT was analyzed by these measurement methods. The results show that after 18,000 thermal cycles, a visible shift in I–V curve can be seen. The internal resistance increased by 13%, while the initial collector-emitter voltage and voltage at the knee point in the VCE–VGE curve slightly changed. It is likely that in our case, during the performed power-cycling test and aging process, the bond wires were most affected, but this hypothesis needs further investigation.
Credit Decision Support Based on Real Set of Cash Loans Using Integrated Machine Learning Algorithms
Authors: Ziemba Paweł , Becker Jarosław , Becker Aneta , Radomska-Zalas Aleksandra , Pawluk Mateusz , Wierzba Dariusz
Published: August 2021

One of the important research problems in the context of financial institutions is the assessment of credit risk and the decision to whether grant or refuse a loan. Recently, machine learning based methods are increasingly employed to solve such problems. However, the selection of appropriate feature selection technique, sampling mechanism, and/or classifiers for credit decision support is very challenging, and can affect the quality of the loan recommendations. To address this challenging task, this article examines the effectiveness of various data science techniques in issue of credit decision support. In particular, processing pipeline was designed, which consists of methods for data resampling, feature discretization, feature selection, and binary classification. We suggest building appropriate decision models leveraging pertinent methods for binary classification, feature selection, as well as data resampling and feature discretization. The selected models’ feasibility analysis was performed through rigorous experiments on real data describing the client’s ability for loan repayment. During experiments, we analyzed the impact of feature selection on the results of binary classification, and the impact of data resampling with feature discretization on the results of feature selection and binary classification. After experimental evaluation, we found that correlation-based feature selection technique and random forest classifier yield the superior performance in solving underlying problem.
An Ultra-Low-Cost Soft Error Protection Scheme Based on the Selection of Critical Variables
Authors: Ko Yohan
Published: August 2021

The exponentially increasing occurrence of soft errors makes the optimization of reliability, performance, hardware area, and power consumption one of the main concerns in modern embedded processors. Since the design cost of hardware techniques aimed at improving the reliability of microprocessors is quite expensive for resource-constrained embedded systems, software-level fault tolerance mechanisms have been proposed as an attractive solution for soft error threats. However, many software-level redundancy-based schemes are accompanied by considerable performance overhead, which is not acceptable for many embedded applications. In this work, we have introduced an ultra-low-cost soft error protection scheme for embedded applications, which works based on source-code analysis and identifying critical variables. After identification, these vital variables are adequately protected by placing runtime checks at critical points of execution. Our experimental results based on several applications demonstrate that the proposed scheme can mitigate the failure rate by 47% with negligible performance degradation.
Virtualization of Self-Driving Algorithms by Interoperating Embedded Controllers on a Game Engine for a Digital Twining Autonomous Vehicle
Authors: Yun Heuijee , Park Daejin
Published: August 2021

Computer simulation based on digital twin is an essential process when designing self-driving cars. However, designing a simulation program that is exactly equivalent to real phenomena can be arduous and cost-ineffective because too many things must be implemented. In this paper, we propose the method using the online game GTA5 (Grand Theft Auto5), as a groundwork for autonomous vehicle simulation. As GTA5 has a variety of well-implemented objects, people, and roads, it can be considered a suitable tool for simulation. By using OpenCV (Open source computer vision) to capture the GTA5 game screen and analyzing images with YOLO (You Only Look Once) and TensorFlow based on Python, we can build a quite accurate object recognition system. This can lead to writing of algorithms for object avoidance and lane recognition. Once these algorithms have been completed, vehicles in GTA5 can be controlled through codes composed of the basic functions of autonomous driving, such as collision avoidance and lane-departure prevention. In addition, the algorithm tested with GTA5 has been implemented with a programmable RC car (Radio control car), DonkeyCar, to increase reliability. By testing those algorithms, we can ensure that the algorithms can be conducted in real time and they cost low power and low memory size. Therefore, we have found a way to approach digital twin technology one step more easily.
A Conceptual Model to Investigate the Role of Mobile Game Applications in Education during the COVID-19 Pandemic
Authors: Al Mulhem Ahmed , Almaiah Mohammed
Published: August 2021

During the COVID-19 pandemic, educational mobile games may play a significant role to facilitate students’ learning. Several studies have indicated that these games using mobile phones may improve students’ learning motivation and effectiveness when they are equipped with appropriate learning strategies. However, investigating the impact of learning strategies in students’ utilization of educational mobile games has received little scholarly attention during the COVID-19 pandemic. Hence, this research proposed two learning games scenarios to fill this gap. In the first scenario, students were offered an educational mobile game with a learning strategy called ‘scaffolding strategy’; while in the second scenario, the same game was offered without the strategy. To achieve this objective, an experimental design with a research model was developed to examine the role of scaffolding learning strategy in students’ use of educational mobile games. In this experimental study, 43 students from two classes participated in the two learning scenarios. The results indicate that educational mobile gaming with the scaffolding learning strategy significantly influenced students’ utilization of the mobile game. In addition, the adoption of the learning strategy significantly affected students’ perceived enjoyment, perceived usefulness, perceived ease of use, and behavioural intention to use, compared with the same game without the learning strategy. The results also indicate that the introduction of the scaffolding learning strategy into the educational mobile game will increase students’ learning effectiveness and motivation.
Stochastic Generation of District Heat Load
Authors: Menapace Andrea , Santopietro Simone , Gargano Rudy , Righetti Maurizio
Published: August 2021

Modelling heat load is a crucial challenge for the proper management of heat production and distribution. Several studies have tackled this issue at building and urban levels, however, the current scale of interest is shifting to the district level due to the new paradigm of the smart system. This study presents a stochastic procedure to model district heat load with a different number of buildings aggregation. The proposed method is based on a superimposition approach by analysing the seasonal component using a linear regression model on the outdoor temperature and the intra-daily component through a bi-parametric distribution of different times of the day. Moreover, an empirical relationship, that estimates the demand variation given the average demand together with a user aggregation coefficient, is proposed. To assess the effectiveness of the proposed methodology, the study of a group of residential users connected to the district heating system of Bozen-Bolzano is carried out. In addition, an application on a three-day prevision shows the suitability of this approach. The final purpose is to provide a flexible tool for district heat load characterisation and prevision based on a sample of time series data and summary information about the buildings belonging to the analysed district.
Configuration Method and Multi-Functional Strategy for Embedding Energy Storage into Wind Turbine
Authors: Chen Changqing , Li Xinran
Published: August 2021

This paper proposes a Configuration method for energy storage (ES), in which the ES inertia of ES is equal to an equal capacity synchronous generator. The purpose is to enhance the frequency modulation capability of double-fed induction generator (DFIG) and wind power consumption. Through the proposed method, the system inertia can remain unchanged after the DFIGs replacing the conventional turbines. During the DFIG rotor speed recovery, the ES releases energy to compensate for sudden changes in active power. On this basis, the DFIG and ES structure model is created, and the ES control strategy is optimized, thereby effectively improving the DFIG frequency modulation capability. Besides, in the non-frequency modulation period, the ES is used to suppress wind power fluctuations, thereby improving system wind power consumption and ES utilization. Simulation results indicate, in the ES-embedded wind turbine structure model, the combination of the ES Configuration method and multi-functional strategy significantly improves the frequency modulation ability and anti-interference performance of a single DFIG. Moreover, the wind power consumption and ES utilization are improved, and the ES achieves additional value.