bluuebunny/crossref_metadata_2025 huggingface dataset:
oneM2M-Enabled Prediction of High Particulate Matter Data Based on Multi-Dense Layer BiLSTM Model
Authors: Prihatno Aji Teguh , Utama Ida Bagus Krishna Yoga , Jang Yeong Min
Published: February 2022

High particulate matter (PM) concentrations in the cleanroom semiconductor factory have become a significant concern as they can damage electronic devices during the manufacturing process. PM can be predicted before becoming more concentrated based on its historical data to support factory management in regulating the air quality in the cleanroom. In this paper, a Multi-Dense Layer BiLSTM model is proposed to predict PM2.5 concentrations in the indoor environment of the cleanroom. To obtain reliability, validity, and interoperability data, the datasets containing temperature, humidity, PM0.3, PM0.5, PM1, PM2.5, PM5, and PM10 were retrieved in a standardized manner via oneM2M-defined representational state transfer application programmable interfaces by employing software platforms compliant with the Internet of Things (IoT) standard. Based on the proposed model, an algorithm was built providing short-term PM2.5 concentration predictions (one hour ahead, two hours ahead, and three hours ahead). The proposed model outperformed the RNN, LSTM, CNN-LSTM, and Single-Dense Layer BiLSTM models in terms of MSE, MAE, and MAPE values. The model created in this study could predict high PM2.5 concentration levels more accurately, thus providing vital support for operation and maintenance for the semiconductor industry.
Data-Driven Robust Control Using Reinforcement Learning
Authors: Ngo Phuong D. , Tejedor Miguel , Godtliebsen Fred
Published: February 2022

This paper proposes a robust control design method using reinforcement learning for controlling partially-unknown dynamical systems under uncertain conditions. The method extends the optimal reinforcement learning algorithm with a new learning technique based on the robust control theory. By learning from the data, the algorithm proposes actions that guarantee the stability of the closed-loop system within the uncertainties estimated also from the data. Control policies are calculated by solving a set of linear matrix inequalities. The controller was evaluated using simulations on a blood glucose model for patients with Type 1 diabetes. Simulation results show that the proposed methodology is capable of safely regulating the blood glucose within a healthy level under the influence of measurement and process noises. The controller has also significantly reduced the post-meal fluctuation of the blood glucose. A comparison between the proposed algorithm and the existing optimal reinforcement learning algorithm shows the improved robustness of the closed-loop system using our method.
Laboratory Test Campaign Aimed at the Analysis of an Uncommon Wear Phenomenon in a Marble Quarry
Authors: Di Giovanni Alfio , Todaro Carmine , Cardu Marilena , Bianchini Stefano , Forfori Brunello
Published: February 2022

The use of ornamental stones has a historical value that makes them strategically precious in Italy; marble can offer high performance in architectural applications, even though the variability of the rock mass requires detailed studies to optimize the exploitation techniques and reduce waste. Italy is world famous for its marble, which is extracted mainly through chainsaw cutting machines, which are currently used intensively due to their high-safety working conditions compared to alternative techniques and for their great versatility, especially in underground applications. Although this cutting technique is well-rooted, an uncommon problem of tool wear was found in the quarry under study, which strongly affected productivity. A series of laboratory test were carried out to estimate the wear potential of the rock and the suitability of the tools. The Cerchar abrasivity test highlighted a mean wear potential for the marble of 2.77, while microhardness outcomes pointed out the presence of quartz veins in the tested material (values over 10,000 MPa). Finally, additives typically used in the conditioning process of EPB machines in tunneling were tested with the purpose of reducing the extent of wear. A reduction of about 50% in the wear (in terms of weight lost) was obtained for a moisture content of 9%.
Generalized k-Fractional Chebyshev-Type Inequalities via Mittag-Leffler Functions
Authors: Zhang Zhiqiang , Farid Ghulam , Mehmood Sajid , Jung Chahn-Yong , Yan Tao
Published: February 2022

Mathematical inequalities have gained importance and popularity due to the application of integral operators of different types. The present paper aims to give Chebyshev-type inequalities for generalized k-integral operators involving the Mittag-Leffler function in kernels. Several new results can be deduced for different integral operators, along with Riemann–Liouville fractional integrals by substituting convenient parameters. Moreover, the presented results generalize several already published inequalities.
Measuring Biosignals with Single Circuit Boards
Authors: Ehrmann Guido , Blachowicz Tomasz , Homburg Sarah Vanessa , Ehrmann Andrea
Published: February 2022

To measure biosignals constantly, using textile-integrated or even textile-based electrodes and miniaturized electronics, is ideal to provide maximum comfort for patients or athletes during monitoring. While in former times, this was usually solved by integrating specialized electronics into garments, either connected to a handheld computer or including a wireless data transfer option, nowadays increasingly smaller single circuit boards are available, e.g., single-board computers such as Raspberry Pi or microcontrollers such as Arduino, in various shapes and dimensions. This review gives an overview of studies found in the recent scientific literature, reporting measurements of biosignals such as ECG, EMG, sweat and other health-related parameters by single circuit boards, showing new possibilities offered by Arduino, Raspberry Pi etc. in the mobile long-term acquisition of biosignals. The review concentrates on the electronics, not on textile electrodes about which several review papers are available.
Cytoprotective Effect of Idebenone through Modulation of the Intrinsic Mitochondrial Pathway of Apoptosis in Human Retinal Pigment Epithelial Cells Exposed to Oxidative Stress Induced by Hydrogen Peroxide
Authors: Clementi Maria Elisabetta , Pizzoferrato Michela , Bianchetti Giada , Brancato Anna , Sampaolese Beatrice , Maulucci Giuseppe , Tringali Giuseppe
Published: February 2022

Idebenone is a ubiquinone short-chain synthetic analog with antioxidant properties, which is believed to restore mitochondrial ATP synthesis. As such, idebenone is investigated in numerous clinical trials for diseases of mitochondrial aetiology and it is authorized as a drug for the treatment of Leber’s hereditary optic neuropathy. Mitochondria of retinal pigment epithelium (RPE) are particularly vulnerable to oxidative damage associated with cellular senescence. Therefore, the aim of this study was to explore idebenone’s cytoprotective effect and its underlying mechanism. We used a human-RPE cell line (ARPE-19) exposed to idebenone pre-treatment for 24 h followed by conditions inducing H2O2 oxidative damage for a further 24 h. We found that idebenone: (a) ameliorated H2O2-lowered cell viability in the RPE culture; (b) activated Nrf2 signaling pathway by promoting Nrf2 nuclear translocation; (c) increased Bcl-2 protein levels, leaving unmodified those of Bax, thereby reducing the Bax/Bcl-2 ratio; (d) maintained the mitochondrial membrane potential (ΔΨm) at physiological levels, preserving the functionality of mitochondrial respiratory complexes and counteracting the excessive production of ROS; and (e) reduced mitochondrial cytochrome C-mediated caspase-3 activity. Taken together, our findings show that idebenone protects RPE from oxidative damage by modulating the intrinsic mitochondrial pathway of apoptosis, suggesting its possible role in retinal epitheliopathies associated with mitochondrial dysfunction.
IGF-1 as a Potential Therapy for Spinocerebellar Ataxia Type 3
Authors: Lin Yong-Shiou , Cheng Wen-Ling , Chang Jui-Chih , Lin Ta-Tsung , Chao Yi-Chun , Liu Chin-San
Published: February 2022

Although the effects of growth hormone (GH) therapy on spinocerebellar ataxia type 3 (SCA3) have been examined in transgenic SCA3 mice, it still poses a nonnegligible risk of cancer when used for a long term. This study investigated the efficacy of IGF-1, a downstream mediator of GH, in vivo for SCA3 treatment. IGF-1 (50 mg/kg) or saline, once a week, was intraperitoneally injected to SCA3 84Q transgenic mice harboring a human ATXN3 gene with a pathogenic expanded 84 cytosine–adenine–guanine (CAG) repeat motif at 9 months of age. Compared with the control mice harboring a 15 CAG repeat motif, the SCA3 84Q mice treated with IGF-1 for 9 months exhibited the improvement only in locomotor function and minimized degeneration of the cerebellar cortex as indicated by the survival of more Purkinje cells with a more favorable mitochondrial function along with a decrease in oxidative stress caused by DNA damage. These findings could be attributable to the inhibition of mitochondrial fission, resulting in mitochondrial fusion, and decreased immunofluorescence staining in aggresome formation and ataxin-3 mutant protein levels, possibly through the enhancement of autophagy. The findings of this study show the therapeutic potential effect of IGF-1 injection for SCA3 to prevent the exacerbation of disease progress.
Is Tissue Still the Issue? The Promise of Liquid Biopsy in Uveal Melanoma
Authors: de Bruyn Daniël P. , Beasley Aaron B. , Verdijk Robert M. , van Poppelen Natasha M. , Paridaens Dion , de Keizer Ronald O. B. , Naus Nicole C. , Gray Elin S. , de Klein Annelies , Brosens Erwin , Kiliç Emine
Published: February 2022

Uveal melanoma (UM) is the second most frequent type of melanoma. Therapeutic options for UM favor minimally invasive techniques such as irradiation for vision preservation. As a consequence, no tumor material is obtained. Without available tissue, molecular analyses for gene expression, mutation or copy number analysis cannot be performed. Thus, proper patient stratification is impossible and patients’ uncertainty about their prognosis rises. Minimally invasive techniques have been studied for prognostication in UM. Blood-based biomarker analysis has become more common in recent years; however, no clinically standardized protocol exists. This review summarizes insights in biomarker analysis, addressing new insights in circulating tumor cells, circulating tumor DNA, extracellular vesicles, proteomics, and metabolomics. Additionally, medical imaging can play a significant role in staging, surveillance, and prognostication of UM and is addressed in this review. We propose that combining multiple minimally invasive modalities using tumor biomarkers should be the way forward and warrant more attention in the coming years.
Parthenolide and Its Soluble Analogues: Multitasking Compounds with Antitumor Properties
Authors: Carlisi Daniela , Lauricella Marianna , D’Anneo Antonella , De Blasio Anna , Celesia Adriana , Pratelli Giovanni , Notaro Antonietta , Calvaruso Giuseppe , Giuliano Michela , Emanuele Sonia
Published: February 2022

Due to its chemical properties and multiple molecular effects on different tumor cell types, the sesquiterpene lactone parthenolide (PN) can be considered an effective drug with significant potential in cancer therapy. PN has been shown to induce either classic apoptosis or alternative caspase-independent forms of cell death in many tumor models. The therapeutical potential of PN has been increased by chemical design and synthesis of more soluble analogues including dimethylaminoparthenolide (DMAPT). This review focuses on the molecular mechanisms of both PN and analogues action in tumor models, highlighting their effects on gene expression, signal transduction and execution of different types of cell death. Recent findings indicate that these compounds not only inhibit prosurvival transcriptional factors such as NF-κB and STATs but can also determine the activation of specific death pathways, increasing intracellular reactive oxygen species (ROS) production and modifications of Bcl-2 family members. An intriguing property of these compounds is its specific targeting of cancer stem cells. The unusual actions of PN and its analogues make these agents good candidates for molecular targeted cancer therapy.
Foam-Replicated Diopside/Fluorapatite/Wollastonite-Based Glass–Ceramic Scaffolds
Authors: Baino Francesco , Tulyaganov Dilshat U. , Kahharov Ziyodilla , Rahdar Abbas , Verné Enrica
Published: February 2022

Implantation of three-dimensional (3D) bioactive glass-derived porous scaffolds is an effective strategy for promoting bone repair and regeneration in large osseous defect sites. The present study intends to expand the potential of a SiO2–P2O5–CaO–MgO–Na2O–CaF2 glass composition, which has already proven to be successful in regenerating bone in both animals and human patients. Specifically, this research work reports the fabrication of macroporous glass–ceramic scaffolds by the foam replica method, using the abovementioned bioactive glass powders as a parent material. The sinter-crystallization of the glass powder was investigated by hot-stage microscopy, differential thermal analysis, and X-ray diffraction. Scanning electron microscopy was used to investigate the pore–strut architecture of the resultant glass–ceramic scaffolds in which diopside, fluorapatite, and wollastonite crystallized during thermal treatment. Immersion studies in simulated body fluids revealed that the scaffolds have bioactive behavior in vitro; the mechanical properties were also potentially suitable to suggest use in load-bearing bone applications.
A Unique Case of Primary Cutaneous Adenoid Cystic Carcinoma Associated with Aplasia Cutis Congenita in a Four-Year-Old Female: A Case Report
Authors: Zulli Andrea , Martin Alessandra , Facchini Flavio , Coletta Riccardo , Tamburini Angela , Oranges Teresa , Filippeschi Cesare , Bassi Andrea , Buccoliero Anna Maria , Morabito Antonino
Published: February 2022

Introduction: Primary cutaneous adenoid-cystic carcinoma (PCACC) is a rare malignant tumour reported in only about 450 cases in the literature, with only two adolescent cases reported. PCACC seems to occur between the fifth and seventh decade of life, and the most frequent regions involved are head and neck (46%). Aplasia cutis congenita (ACC) has an incidence of 1:10,000, and it seems to be rarely associated with neoplastic lesions. Interestingly, the association between PCACC and ACC has, so far, never been described. Methods: We report a case of PCACC in the scalp associated with ACC in a four-year-old patient. Discussion: The patient was under follow-up at the dermatology unit, but suddenly a red lesion appeared within the ACC. This red, ulcerated area increased rapidly over six months, so it was surgically removed, and the pathological examination results were suggestive for cribriform PCACC. According to the guidelines for skin tumours, the patient underwent widening resection, and an advancement-sliding skin flap was performed to recreate the scalp. After one year of follow-up, the patient has no local or widespread recurrence of the PCACC, and the surgical scar appears to have healed well. Conclusions: This clinical case is the first known patient with PCACC associated with ACC. A skin excision biopsy should be performed with wide margins to avoid a second widening resection of skin in a similar scenario. Genetic studies may help to identify the origin of this rare association.
Maternal Milk Provision in the Neonatal Intensive Care Unit and Mother–Infant Emotional Connection for Preterm Infants
Authors: Viglione Clare , Cherkerzian Sara , Timpson Wendy , Liu Cindy H. , Woodward Lianne J. , Belfort Mandy B.
Published: February 2022

Maternal milk (MM) intake during neonatal intensive care unit (NICU) hospitalization is associated with improved neurodevelopment in preterm infants. Underlying mechanisms may include stronger mother–infant emotional connection. This paper examines associations between MM provision in the NICU with maternal connection to her infant using three factors validated in our sample: maternal sensitivity, emotional concern, and positive interaction/engagement. We studied 70 mothers of infants born <1500 g and/or <32 weeks’ gestation. Associations between MM provision and mother–infant connection were modeled using median regression adjusted for clustering. Mothers who provided exclusive MM (i.e., 100% MM, no other milk) reported higher levels of maternal sensitivity by a median score of 2 units (β = 2.00, 95% CI: 0.76, 3.24, p = 0.002) than the mixed group (i.e., MM < 100% days, other milk ≥1 days), as well as greater emotional concern (β = 3.00, 95% CI: −0.002, 6.00, p = 0.05). Among mothers of very preterm infants, greater milk provision was associated with greater maternal sensitivity, but also with greater emotional concern about meeting the infant’s needs. These findings highlight the importance of supporting MM provision and early infant care as an integrated part of lactation support. The findings may also provide insight into links between MM provision in the NICU and infant neurodevelopment.
Rex Shunt for Extra-Hepatic Portal Venous Obstruction in Children
Authors: Zhang Jinshan , Li Long
Published: February 2022

Rex shunt, which was first put in use in 1992, has been considered as an ideal surgical method for the treatment of extra-hepatic portal venous obstruction (EHPVO) due to its reconstruction of the hepatopetal portal blood flow. However, despite its long tradition, there are only a few reports about the application and advances in Rex shunt for the treatment of EHPVO in children. In this paper, we summarized the literature related to Rex shunt and discussed the new advances of Rex shunt in the following aspects: surgical method of Rex shunt, the indications of Rex shunt, the strengths of Rex shunt, the effectiveness of Rex shunt, factors affecting the efficacy of Rex shunt, methods that improve the prognosis of Rex shunt, and treatment strategy for recurrence after Rex shunt.
Molecular Structure-Based Screening of the Constituents of Calotropis procera Identifies Potential Inhibitors of Diabetes Mellitus Target Alpha Glucosidase
Authors: Adinortey Cynthia A. , Kwarko Gabriel B. , Koranteng Russell , Boison Daniel , Obuaba Issaka , Wilson Michael D. , Kwofie Samuel K.
Published: February 2022

Diabetes mellitus is a disorder characterized by higher levels of blood glucose due to impaired insulin mechanisms. Alpha glucosidase is a critical drug target implicated in the mechanisms of diabetes mellitus and its inhibition controls hyperglycemia. Since the existing standard synthetic drugs have therapeutic limitations, it is imperative to identify new potent inhibitors of natural product origin which may slow carbohydrate digestion and absorption via alpha glucosidase. Since plant extracts from Calotropis procera have been extensively used in the treatment of diabetes mellitus, the present study used molecular docking and dynamics simulation techniques to screen its constituents against the receptor alpha glucosidase. Taraxasterol, syriogenin, isorhamnetin-3-O-robinobioside and calotoxin were identified as potential novel lead compounds with plausible binding energies of −40.2, −35.1, −34.3 and −34.3 kJ/mol against alpha glucosidase, respectively. The residues Trp481, Asp518, Leu677, Leu678 and Leu680 were identified as critical for binding and the compounds were predicted as alpha glucosidase inhibitors. Structurally similar compounds with Tanimoto coefficients greater than 0.7 were reported experimentally to be inhibitors of alpha glucosidase or antidiabetic. The structures of the molecules may serve as templates for the design of novel inhibitors and warrant in vitro assaying to corroborate their antidiabetic potential.
Nematode-Applied Technology for Human Tumor Microenvironment Research and Development
Authors: di Luccio Eric , Kaifuchi Satoru , Kondo Nobuaki , Chijimatsu Ryota , Vecchione Andrea , Hirotsu Takaaki , Ishii Hideshi
Published: February 2022

Nematodes, such as Caenorhabditis elegans, have been instrumental to the study of cancer. Recently, their significance as powerful cancer biodiagnostic tools has emerged, but also for mechanism analysis and drug discovery. It is expected that nematode-applied technology will facilitate research and development on the human tumor microenvironment. In the history of cancer research, which has been spurred by numerous discoveries since the last century, nematodes have been important model organisms for the discovery of cancer microenvironment. First, microRNAs (miRNAs), which are noncoding small RNAs that exert various functions to control cell differentiation, were first discovered in C. elegans and have been actively incorporated into cancer research, especially in the study of cancer genome defects. Second, the excellent sense of smell of nematodes has been applied to the diagnosis of diseases, especially refractory tumors, such as human pancreatic cancer, by sensing complex volatile compounds derived from heterogeneous cancer microenvironment, which are difficult to analyze using ordinary analytical methods. Third, a nematode model system can help evaluate invadosomes, the phenomenon of cell invasion by direct observation, which has provided a new direction for cancer research by contributing to the elucidation of complex cell–cell communications. In this cutting-edge review, we highlight milestones in cancer research history and, from a unique viewpoint, focus on recent information on the contributions of nematodes in cancer research towards precision medicine in humans.
The LiTFSI/COFs Fiber as Separator Coating with Bifunction of Inhibition of Lithium Dendrite and Shuttle Effect for Li-SeS2 Battery
Authors: Wang Jun , Chen Jia-He , Chen Zhen-Chong , Wu Zhen-Yi , Zhong Xiao-Na , Ke Jing-Ping
Published: February 2022

The safety problem caused by lithium dendrite of lithium metal anode and the rapid capacity decay problem caused by the shuttle effect of polysulfide and polyselenide during the charge and discharge of selenium disulfide cathode limit the application of lithium selenium disulfide batteries significantly. Here, a fibrous ATFG-COF, containing rich carbonyl and amino functional groups, was applied as the separator coating layer. Density Functional Theory (DFT) theoretical calculations and experimental results showed that the abundant carbonyl group in ATFG-COF had a positive effect on lithium ions, and the amino group formed hydrogen bonds with bis ((trifluoromethyl) sulfonyl) azanide anionics (TFSI−), which fixed TFSI− in the channel, so as to improve the transfer number of lithium ions and narrow the channels. Therefore, ATFG-COF fiber coating can not only form a rapid and uniform lithium-ion flow on the lithium anode to inhibit the growth of lithium dendrites, but also effectively screen polysulfide and polyselenide ions to suppress the shuttle effect. The Li-SeS2 cell with ATFG-COF/polypropylene (ATFG-COF/PP) separator exhibited good cycle stability at 0.5 C and maintained a specific capacity of 509 mAh/g after 200 cycles. Our work provides insights into the design of dual-function separators with high-performance batteries.
Lysozyme Influence on Monolayers of Individual and Mixed Lipids
Authors: Torrent-Burgués Juan
Published: February 2022

Fatty acids, cholesterol, and phospholipids are amphiphilic compounds of biological interest, which form ordered monolayers mimicking biomembranes, and can be studied with the Langmuir technique using surface pressure-area isotherms and compressibility plots. Proteins are also components of biomembranes or are present in body fluids. In this study, the influence of lysozyme on different films of a fatty acid (stearic acid or oleic acid), cholesterol, a phospholipid (dipalmitoylphosphatidylcholine, DPPC, or palmitoyloleoylphosphatidylcholine, POPC), and mixtures of them is presented using a 0.9% saline solution as subphase. Results show that the presence of lysozyme alters the lipid monolayer formation in an important way at the beginning (low surface pressures) and the middle (intermediate surface pressures) parts of the isotherm. At high surface pressures, the phospholipids DPPC and POPC and the saturated fatty acid, stearic acid, expel lysozyme from the surface, while oleic acid and cholesterol permit the presence of lysozyme on it. The mixtures of oleic acid-DPPC also expel lysozyme from the surface at high surface pressures, while mixtures of oleic acid-POPC and cholesterol-POPC permit the presence of lysozyme on it. The compressibility of the monolayer is affected in all cases, with an important reduction in the elastic modulus values and an increase in the fluidity, especially at low and intermediate surface pressures.
Assessment of SQL and NoSQL Systems to Store and Mine COVID-19 Data
Authors: Antas João , Rocha Silva Rodrigo , Bernardino Jorge
Published: February 2022

COVID-19 has provoked enormous negative impacts on human lives and the world economy. In order to help in the fight against this pandemic, this study evaluates different databases’ systems and selects the most suitable for storing, handling, and mining COVID-19 data. We evaluate different SQL and NoSQL database systems using the following metrics: query runtime, memory used, CPU used, and storage size. The databases systems assessed were Microsoft SQL Server, MongoDB, and Cassandra. We also evaluate Data Mining algorithms, including Decision Trees, Random Forest, Naive Bayes, and Logistic Regression using Orange Data Mining software data classification tests. Classification tests were performed using cross-validation in a table with about 3 M records, including COVID-19 exams with patients’ symptoms. The Random Forest algorithm has obtained the best average accuracy, recall, precision, and F1 Score in the COVID-19 predictive model performed in the mining stage. In performance evaluation, MongoDB has presented the best results for almost all tests with a large data volume.
British Columbia’s Index of Multiple Deprivation for Community Health Service Areas
Authors: Relova Sharon , Joffres Yayuk , Rasali Drona , Zhang Li Rita , McKee Geoffrey , Janjua Naveed
Published: February 2022

Area-based socio-economic indicators, such as the Canadian Index of Multiple Deprivation (CIMD), have been used in equity analyses to inform strategies to improve needs-based, timely, and effective patient care and public health services to communities. The CIMD comprises four dimensions of deprivation: residential instability, economic dependency, ethno-cultural composition, and situational vulnerability. Using the CIMD methodology, the British Columbia Index of Multiple Deprivation (BCIMD) was developed to create indexes at the Community Health Services Area (CHSA) level in British Columbia (BC). BCIMD indexes are reported by quintiles, where quintile 1 represents the least deprived (or ethno-culturally diverse), and quintile 5 is the most deprived (or diverse). Distinctive characteristics of a community can be captured using the BCIMD, where a given CHSA may have a high level of deprivation in one dimension and a low level of deprivation in another. The utility of this data as a surveillance tool to monitor population demography has been used to inform decision making in healthcare by stakeholders in the regional health authorities and governmental agencies. The data have also been linked to health care data, such as COVID-19 case incidence and vaccination coverage, to understand the epidemiology of disease burden through an equity lens.
Changing Children’s Attitudes to Disability through Music: A Learning Intervention by Young Disabled Mentors
Authors: McCarron Eamonn , Curran Erica , McConkey Roy
Published: February 2022

Children with disabilities are at greater risk of social exclusion. In part, this results from the negative perceptions of disability held by their peers. An innovative, school-based project used creative music-making sessions facilitated by young disabled musicians to nurture more positive attitudes among children aged 9 years in four schools, with two classes from each. In all, around 200 pupils were involved in weekly sessions totalling 16 h. Their attitudes to disability were assessed before and after participating in the project, along with the reactions of parents and teachers. Pupils were significantly more disposed to interacting with children with disabilities and to persons with disabilities more generally as well as to having a teacher with a disability. Parents and teachers confirmed the pupils’ enthusiasm for the project and the impact it had on them. A core driver for change appeared to be sharing enjoyable musical activities with competent musicians who had disabilities. Further research should explore the potential of mentoring by disabled persons in other arts activities and sports to provide further validation of this approach.
A Novel Epidemic Model Base on Pulse Charging in Wireless Rechargeable Sensor Networks
Authors: Liu Guiyun , Su Xiaokai , Hong Fenghuo , Zhong Xiaojing , Liang Zhongwei , Wu Xilai , Huang Ziyi
Published: February 2022

As wireless rechargeable sensor networks (WRSNs) are gradually being widely accepted and recognized, the security issues of WRSNs have also become the focus of research discussion. In the existing WRSNs research, few people introduced the idea of pulse charging. Taking into account the utilization rate of nodes’ energy, this paper proposes a novel pulse infectious disease model (SIALS-P), which is composed of susceptible, infected, anti-malware and low-energy susceptible states under pulse charging, to deal with the security issues of WRSNs. In each periodic pulse point, some parts of low energy states (LS nodes, LI nodes) will be converted into the normal energy states (S nodes, I nodes) to control the number of susceptible nodes and infected nodes. This paper first analyzes the local stability of the SIALS-P model by Floquet theory. Then, a suitable comparison system is given by comparing theorem to analyze the stability of malware-free T-period solution and the persistence of malware transmission. Additionally, the optimal control of the proposed model is analyzed. Finally, the comparative simulation analysis regarding the proposed model, the non-charging model and the continuous charging model is given, and the effects of parameters on the basic reproduction number of the three models are shown. Meanwhile, the sensitivity of each parameter and the optimal control theory is further verified.
Enhanced Credit Card Fraud Detection Model Using Machine Learning
Authors: Alfaiz Noor Saleh , Fati Suliman Mohamed
Published: February 2022

The COVID-19 pandemic has limited people’s mobility to a certain extent, making it difficult to purchase goods and services offline, which has led the creation of a culture of increased dependence on online services. One of the crucial issues with using credit cards is fraud, which is a serious challenge in the realm of online transactions. Consequently, there is a huge need to develop the best approach possible to using machine learning in order to prevent almost all fraudulent credit card transactions. This paper studies a total of 66 machine learning models based on two stages of evaluation. A real-world credit card fraud detection dataset of European cardholders is used in each model along with stratified K-fold cross-validation. In the first stage, nine machine learning algorithms are tested to detect fraudulent transactions. The best three algorithms are nominated to be used again in the second stage, with 19 resampling techniques used with each one of the best three algorithms. Out of 330 evaluation metric values that took nearly one month to obtain, the All K-Nearest Neighbors (AllKNN) undersampling technique along with CatBoost (AllKNN-CatBoost) is considered to be the best proposed model. Accordingly, the AllKNN-CatBoost model is compared with related works. The results indicate that the proposed model outperforms previous models with an AUC value of 97.94%, a Recall value of 95.91%, and an F1-Score value of 87.40%.
RETRACTED: Implementation of Binarized Neural Networks in All-Programmable System-on-Chip Platforms
Authors: Xiang Maoyang , Teo Tee
Published: February 2022

The Binarized Neural Network (BNN) is a Convolutional Neural Network (CNN) consisting of binary weights and activation rather than real-value weights. Smaller models are used, allowing for inference effectively on mobile or embedded devices with limited power and computing capabilities. Nevertheless, binarization results in lower-entropy feature maps and gradient vanishing, which leads to a loss in accuracy compared to real-value networks. Previous research has addressed these issues with various approaches. However, those approaches significantly increase the algorithm’s time and space complexity, which puts a heavy burden on those embedded devices. Therefore, a novel approach for BNN implementation on embedded systems with multi-scale BNN topology is proposed in this paper, from two optimization perspectives: hardware structure and BNN topology, that retains more low-level features throughout the feed-forward process with few operations. Experiments on the CIFAR-10 dataset indicate that the proposed method outperforms a number of current BNN designs in terms of efficiency and accuracy. Additionally, the proposed BNN was implemented on the All Programmable System on Chip (APSoC) with 4.4 W power consumption using the hardware accelerator.
Textural Feature Analysis of Optical Coherence Tomography Phantoms
Authors: Kulmaganbetov Mukhit , Bevan Ryan J. , Anantrasirichai Nantheera , Achim Alin , Erchova Irina , White Nick , Albon Julie , Morgan James E.
Published: February 2022

Optical coherence tomography (OCT) is an imaging technique based on interferometry of backscattered lights from materials and biological samples. For the quantitative evaluation of an OCT system, artificial optical samples or phantoms are commonly used. They mimic the structure of biological tissues and can provide a quality standard for comparison within and across devices. Phantoms contain medium matrix and scattering particles within the dimension range of target biological structures such as the retina. The aim was to determine if changes in speckle derived optical texture could be employed to classify the OCT phantoms based on their structural composition. Four groups of phantom types were prepared and imaged. These comprise different concentrations of a medium matrix (gelatin solution), different sized polystyrene beads (PBs), the volume of PBs and different refractive indices of scatterers (PBs and SiO2). Texture analysis was applied to detect subtle optical differences in OCT image intensity, surface coarseness and brightness of regions of interest. A semi-automated classifier based on principal component analysis (PCA) and support vector machine (SVM) was applied to discriminate the various texture models. The classifier detected correctly different phantom textures from 82% to 100%, demonstrating that analysis of the texture of OCT images can be potentially used to discriminate biological structure based on subtle changes in light scattering.
Applications of Federated Learning; Taxonomy, Challenges, and Research Trends
Authors: Shaheen Momina , Farooq Muhammad Shoaib , Umer Tariq , Kim Byung-Seo
Published: February 2022

The federated learning technique (FL) supports the collaborative training of machine learning and deep learning models for edge network optimization. Although a complex edge network with heterogeneous devices having different constraints can affect its performance, this leads to a problem in this area. Therefore, some research can be seen to design new frameworks and approaches to improve federated learning processes. The purpose of this study is to provide an overview of the FL technique and its applicability in different domains. The key focus of the paper is to produce a systematic literature review of recent research studies that clearly describes the adoption of FL in edge networks. The search procedure was performed from April 2020 to May 2021 with a total initial number of papers being 7546 published in the duration of 2016 to 2020. The systematic literature synthesizes and compares the algorithms, models, and frameworks of federated learning. Additionally, we have presented the scope of FL applications in different industries and domains. It has been revealed after careful investigation of studies that 25% of the studies used FL in IoT and edge-based applications and 30% of studies implement the FL concept in the health industry, 10% for NLP, 10% for autonomous vehicles, 10% for mobile services, 10% for recommender systems, and 5% for FinTech. A taxonomy is also proposed on implementing FL for edge networks in different domains. Moreover, another novelty of this paper is that datasets used for the implementation of FL are discussed in detail to provide the researchers an overview of the distributed datasets, which can be used for employing FL techniques. Lastly, this study discusses the current challenges of implementing the FL technique. We have found that the areas of medical AI, IoT, edge systems, and the autonomous industry can adapt the FL in many of its sub-domains; however, the challenges these domains can encounter are statistical heterogeneity, system heterogeneity, data imbalance, resource allocation, and privacy.
Composite Non-Linear Control of Hybrid Energy-Storage System in Electric Vehicle
Authors: Lu Zhangyu , Zhang Xizheng
Published: February 2022

The underlying circuit control is a key problem of the hybrid energy-storage system (HESS) in electric vehicles (EV). In this paper, a composite non-linear control strategy (CNC) is proposed for the accurate tracking current/voltage of the fully-active HESS by combining the exact feedback linearization method and the sliding mode variable structure control technology. Firstly, by analyzing the circuit characteristics of HESS, the affine non-linear model of fully-active HESS is derived. Then, a rule-based energy management strategy (EMS) is designed to generate the reference current value. Finally, the HESS is linearized by the exact feedback linearization method, and the proposed CNC strategy is developed combined with sliding mode variable structure control technology to ensure fast response, high performance, and robustness. At the same time, the stability proof based on the Lyapunov method is given. Moreover, the performance of the CNC strategy is thoroughly investigated and compared with simulation studies with the traditional PI control and a modified sliding mode control, and its effectiveness under different driving conditions is fully verified.
Contribution of Thermal Inertia to the Interior Climate of Girona Cathedral: Feasibility Analysis for the Preservation of Pieces of Art through the Monitoring of Thermal Conditions for 6 Years
Authors: Corominas i Tabares Jordi , Fonseca i Casas Antoni , Fonseca i Casas Pau
Published: February 2022

The purpose of this study is to determine Girona Cathedral’s thermal performance and to verify that it is suitable for containing historical pieces of art. We present the results of our analysis of the indoor thermal conditions during the period from January 2011 to December 2016. Real data were collected from strategically located probes inside the cathedral and from an outside weather station. The results were compared with an EnergyPlus computer model to verify the calculations and improve decision making. The model considers the envelope’s thermal inertia, the characteristics of the enclosure, and the passive systems for performing thermal analysis. The cathedral’s indoor environment is very stable. Because of a high capability of thermal-energy accumulation, a one-month thermal lag between indoor and outdoor temperatures exists. Furthermore, the maximum and minimum temperatures are dampened, with a two-degree variation above or below the outdoor average, depending on the season. The outdoor humidity can vary from 40% to 100% daily, whereas the indoor humidity variation is around 5%. This indoor stable condition protects the artistic objects in the building. This six-year monitoring and analysis allows for the determination that high-inertia buildings are suitable for displaying and preserving pieces of art and antique furniture, protecting them from deterioration.
The Role of Pre-Commitments and Engle Curves in Thailand’s Aggregate Energy Demand System
Authors: Duangnate Kannika , Mjelde James W.
Published: February 2022

In the present paper, an investigation into Thailand’s energy demand is performed to determine if: (1) a linear or nonlinear Engel curve better explains the relationship between income and energy consumption, and (2) systems with pre-commitments better model energy consumptions. Four demand systems are estimated: an almost ideal demand system (AIDS), the quadratic almost ideal demand system (QAIDS), generalized almost ideal demand system (GAIDS), and the generalized quadratic almost ideal demand system (GQAIDS). Elasticities are calculated for policy implications. The empirical results suggest that models considering pre-commitments and nonlinear Engel curves may be slightly more appropriate for Thailand’s energy system, from both statistic and economic standpoints. Statistical inferences appear to favor the GQAIDS model based on the encompassing results. Economic reasonability also appears to favor the GQAIDS model, in particular, petroleum products, as it provides results consistent with the notions of precommitments and fuel substitutability found in previous studies. Most of the previous studies in various forms have shown that the demand for petroleum products is relatively inelastic to price in Thailand. The current study, however, finds that own-price elasticities of uncompensated demand for petroleum products are almost unitary, which is relatively more elastic than most of the previous studies. As such, further studies are required and the price-based policy on petroleum products targeting the reduction in petroleum product dependence must be implemented with caution.
Investigation of Nexus between Knowledge Learning and Enterprise Green Innovation Based on Meta-Analysis with a Focus on China
Authors: Zhang Mengjuan , Li Mingxing , Sun Hongzheng , Oteng Agyeman Fredrick , ud din Khan Hira Salah , Zhang Zedong
Published: February 2022

Knowledge learning is a vital pre-factor and the driving force of green enterprise innovation; hence, meriting the numerous academic research and accumulated relevant literature. In this paper, the meta-analysis methodology was used to explore the direction and intensity of the influence of knowledge learning on green enterprise innovation, taking 32 independent documents as research samples. Meta-analysis results showed that the search breadth and the search depth of green resources and the green resources absorption and integration have significant positive effects on the green innovation of enterprises, among which green resources absorption and integration were the most important. Further, the research on the moderating effect found that the measurement method of green innovation affected the relationship between knowledge learning and green enterprise innovation; however, the moderating effect of the research object was not pronounced.
Optimal Operation for Regional IES Considering the Demand- and Supply-Side Characteristics
Authors: Li Wenying , Tang Ming , Zhang Xinzhen , Gao Danhui , Wang Jian
Published: February 2022

A regional integrated energy system (RIES) is an electricity-centric multi-energy system that can realize the mutual conversion of electricity, heat, cold, and other energy. Through multi-flexible resource interaction and the transaction of multi-investment entities, the efficiency of energy utilization can be improved. To systematize energy-consuming entities and scale photovoltaic-based renewable energy in a distribution network, the energy-consuming behavior, energy-producing schedule, and trading strategy can be coupled. Considering the interaction between the energy-consuming behavior and the uncertainty of distributed photovoltaic output, an optimal operation method for RIES is proposed on the basis of social network theory and an uncertain evolutionary game method in this paper. From the perspective of the operator, the overall profits of RIES are maximized considering the entity characteristics of both the demand and the supply side. A case study shows that the proposed method can ensure the reasonable distribution of profit among the investment entities. A closer social relationship between energy-consuming entities or a lower transaction risk cost of energy-producing entities can increase the overall energy transaction profit.
An Analytical Method to Estimate Supersaturation in Gas–Liquid Systems as a Function of Pressure-Reduction Step and Waiting Time
Authors: Pradhan Sushobhan , Bikkina Prem Kumar
Published: February 2022

When the concentration of a gas exceeds the equilibrium concentration in a liquid, the gas–liquid system is referred as a supersaturated system. The supersaturation can be achieved by either changing the pressure and/or temperature of the system. The gas from a supersaturated liquid escapes either through bubble nucleation that usually occurs on solid surface and/or gas diffusion through the gas–liquid interface. The bubble nucleation requires a minimum threshold supersaturation. A waiting time is required to observe whether the applied supersaturation is sufficient to initiate bubble nucleation. When the supersaturation is not sufficient to cause bubble nucleation, some or all of the supersaturated gas may diffuse out from the liquid through the gas–liquid interface before further reducing the pressure in order to increase the supersaturation. In this article, using Fick’s second law of diffusion and Henry’s law, an analytical method is proposed to estimate the level of supersaturations generated in three gas–liquid systems at different step-down pressures. Characteristic times of the gas–liquid systems were estimated to validate whether the waiting times used in this study are in accordance with the semi-infinite diffusion model used to estimate the supersaturations generated.
Characterization and Role of Sterols in Saccharomyces cerevisiae during White Wine Alcoholic Fermentation
Authors: Girardi Piva Giovana , Casalta Erick , Legras Jean-Luc , Tesnière Catherine , Sablayrolles Jean-Marie , Ferreira David , Ortiz-Julien Anne , Galeote Virginie , Mouret Jean-Roch
Published: February 2022

Responsible for plasma membrane structure maintenance in eukaryotic organisms, sterols are essential for yeast development. The role of two sterol sources in Saccharomyces cerevisiae during wine fermentation is highlighted in this review: ergosterol (yeast sterol produced by yeast cells under aerobic conditions) and phytosterols (plant sterols imported by yeast cells from grape musts in the absence of oxygen). These compounds are responsible for the maintenance of yeast cell viability during white wine fermentation under stress conditions, such as ethanol stress and sterol starvation, to avoid sluggish and stuck fermentations.