bluuebunny/crossref_metadata_2025 huggingface dataset:
Heterogeneous Tau Oligomers as Molecular Targets for Alzheimer’s Disease and Related Tauopathies
Authors: Lo Chih Hung
Published: November 2022

Tauopathies, including Alzheimer’s disease (AD), are a group of neurodegenerative disorders characterized by pathological aggregation of microtubule binding protein tau. The presence of tau neurofibrillary tangles, which are insoluble β-sheet fibrils, in the brain has been the histopathological hallmark of these diseases as their level correlates with the degree of cognitive impairment. However, recent studies suggest that tau oligomers, which are soluble proteins that are formed prior to insoluble fibrils, are the principal toxic species impairing neurons and inducing neurodegeneration. Targeting toxic tau oligomers is challenging, as they are mostly unstructured and adopting multiple conformations. The heterogeneity of tau oligomers is further illustrated by the different oligomeric species formed by various methods. The current models and technologies to study tau oligomerization represent important resources and avenues to push the forefront of elucidating the true toxic tau species. In this review, we will summarize the distinct tau oligomers generated using different strategies and discuss their conformational characteristics, neurotoxicity, relevance to pathological phenotypes, as well as their applications in drug discovery. This information will provide insights to understanding heterogeneous tau oligomers and their role as molecular targets for AD and related tauopathies.
Bioenergy Generation and Wastewater Purification with Li0.95Ta0.76Nb0.19Mg0.15O3 as New Air-Photocathode for MFCs
Authors: Touach Noureddine , Benzaouak Abdellah , Toyir Jamil , El Hamidi Adnane , El Mahi Mohammed , Lotfi El Mostapha , Kacimi Mohamed , Liotta Leonarda Francesca
Published: November 2022

MFC is a promising technology that can be used for simultaneous electricity generation and wastewater treatment. Power energy generation of a ferroelectric cathodic ceramic, Li0.95Ta0.76Nb0.19Mg0.15O3 (LTNMg), has been measured in microbial fuel cells, integrating a single chamber fed by industrial wastewater (CODinitial = 471 mg L−1, and pHinitial = 7.24 at T = 27 °C). In this process, the mixed multicomponent oxide material has been prepared and characterized by XRD, PSD, TEM, and UV-Vis spectroscopy. The catalytic activity has been investigated by COD determination, analysis of heavy metals, and polarization measurement. The results show a high COD reduction efficiency, which reaches 95.70% after a working time of 168 h with a maximal power density of 228 mW m−2. In addition, the maximum value of generated voltage in the open-circuit potential (OCP) of this MFC configuration has been increased from 340 mV in the absence of a light source to 470 mV under irradiation, indicating the presence of a promoting photocatalytic effect of LTNMg, which improved the process of the cathodic electron transfer inside the MFC device.
Progress of Near-Infrared-Based Medical Imaging and Cancer Cell Suppressors
Authors: Mudeng Vicky , Ayana Gelan , Zhang Sung-Uk , Choe Se-woon
Published: November 2022

Diffuse optical tomography, an imaging modality that utilizes near-infrared light, is a new way to assess soft tissue. It provides a non-invasive screening of soft tissue, such as the breast in females and prostate in males, to inspect the existence of cancer. This new imaging method is considered cost-effective and preferred because the implementation is simply through the application of a laser or light-emitting diode as a light source. Near-infrared technology does not only offer cancer screening modality, but also acts as a cancer treatment method, called near-infrared photoimmunotherapy. Despite plentiful studies in the area of near-infrared technology for cancer imaging and cancer cell suppression, there is no consolidated review that provides an overview of near-infrared application in cancer cell imaging and therapy. The objective of this study is to review near-infrared-based medical imaging and novel approaches to eradicate cancer cells. Additionally, we have discussed prospective instrumentation to establish cancer therapeutics apparatuses based on near-infrared technology. This review is expected to guide researchers implementing near-infrared for a medical imaging modality and cancer suppression in vitro, in vivo, and in clinical settings.
Applying Two-Dimensional Correlation Spectroscopy and Principal Component Analysis to Understand How Temperature Affects the Neptunium(V) Absorption Spectrum
Authors: Sadergaski Luke R. , Morgan Kyle
Published: November 2022

The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO2+) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO2+) is an important factor to consider with spectrophotometric applications but has often been overlooked. Optical Vis-NIR absorption spectra (400–1700 nm) of Np(V) (0.017–0.89 M) in 1 M nitric acid were evaluated with varying temperatures (T = 10–80 °C). The intensity, position, and overall shape of the bands were sensitive to interactions with the solvent and coordination environment. Numerous temperature-induced isosbestic points were identified resulting from dynamic, overlapping peak shifts. Spectral variations were characterized using principal component analysis (PCA) and 2D correlation spectroscopy (COS). 2D-COS revealed that the absorption band near 1095 nm likely consists of two bands centered near 1087 and 1096 nm, which cannot be explained by current computational methods. 2D-COS analysis also provided an unambiguous assignment of unresolved peaks in the visible region for comparison with computational predictions. PCA was used to identify nonlinearity in the spectral response at elevated Np(V) concentrations ≥ 0.5 M. This unique experimental data and interpretation will foster a deeper understanding of the absorption spectra for complex actinyl ions.
Reactive and Proactive Aggression among Children and Adolescents: A Latent Profile Analysis and Latent Transition Analysis
Authors: Lohbeck Annette
Published: November 2022

The present study aimed to explore children’s and adolescents’ profiles of reactive and proactive aggression and the stability of those profiles over a six-month period using latent profile analysis (LPA) and latent transition analysis (LTA). Data were collected at two measurement points from a sample of N = 1468 children and adolescents aged from 9 to 18 years. Results of LPA revealed three distinct profiles, labeled as “Severe Reactively and Proactively Aggressive (S-RA-PA)”, “Highly Reactively and Proactively Aggressive” (H-RA-PA), and “Moderately Low Reactively and Proactively Aggressive” (M-RA-PA). All profiles appeared to be relatively stable over six months, supporting their within-sample consistency. The most stable and largest profile was the “M-RA-PA” profile, while the least stable and smallest profile was the “S-RA-PA” profile. However, there was also some within-person variability in children’s and adolescents’ profile membership because almost 40–50% of the participants of the “S-RA-PA” and “H-RA-PA” profiles transitioned to another profile across six months. In contrast, more than 90% of the participants of the “M-RA-PA” profile remained in their profile. These results provide a dynamic picture of children’s and adolescents’ development of reactive and proactive aggression and bear several implications from a short longitudinal person-oriented perspective.
Critical Issues in the Management of Newborn Hearing Screening in the Time of COVID-19 in Umbria, Italy
Authors: Gambacorta Valeria , Orzan Eva , Molini Egisto , Lapenna Ruggero , Paniconi Matteo , Di Giovanni Alfredo , Faralli Mario , Ricci Giampietro
Published: November 2022

Hearing impairment is the most frequent of the sensorial defects in humans, and if not treated promptly, can severely impair cognitive and spoken language skills. For this reason, a universal newborn hearing screening (UNHS) has been established. The purpose of our study is to examine, by means of a retrospective analysis, the results of the UNHS program in the Umbria region during the spread of COVID-19 (2020–2021), comparing the same data from the years 2011–2012, to understand if the program has improved. Our study has shown how the coverage rate of well born babies’ (WB) screening has significantly increased to currently meet the JCIH benchmark. The percentage of WB referrals significantly decreased in 2020–2021, another indicator of the screening program’s greater efficiency in Umbria. However, a critical issue has emerged: the percentage of those lost to follow-up is greater than 30%, well above the benchmark. As far as the COVID-19 pandemic has certainly had a significant impact, it is necessary to carefully monitor those who do not access the diagnostic level. To emphasize the importance of a proper screening program, it will be helpful to strengthen the computerized data collection system and create an information network between audiologists, pediatricians and families.
Youth Judokas Competing in Higher Age Groups Leads to a Short-Term Success
Authors: Simenko Jozef
Published: November 2022

Coaches of youth judo athletes might be under the influence of some extraordinary elite judo athletes that have won elite competitions at a relatively young age and might put youth athletes under pressure to gain as much fighting experience as fast as possible. The present study aims to present a 5-year competition structure, volume and age competition categories (ACC) range in which youth judokas competed with 10-year dropout status. Data from 46 judokas were collected (M = 24; F = 22) for four categorisation classes (National-NC; Perspective-PC; International-IC; World class-WC). Competitive structure, volume, performance and number of ACC were collected from 2009 to 2013 for all age groups from scores and standings records of the National Federation. Youth judokas competed in 8 (±2) competitions per year and also competed in 3 (±1) ACC. Abroad competitions affect the fighting experience and competitive success (CS). CS showed positive correlations with the number of ACC in the year 2009 (p = 0.01), 2010 (p = 0.01) and 2011 (p = 0.04). The final observed years’ CS 2012 (p = 0.009) and 2013 (p = 0.002) showed a negative association with the number of ACC. CS in the final observed year 2013 showed a positive association (p = 0.012) with the dropout status in 2018 and a negative one with the number of abroad competitions in 2013 (p = 0.029). In total, 52% dropout was noted in 10 years. This ‘’playing-up’’ approach was shown to be successful in creating youth medalists. However, just in the short term, if implemented for too long, it starts to affect competition success negatively and increases youth athletes’ dropout. Therefore, coaches should include more competitions abroad in competitors’ primary age group, while training sessions could be done with higher age groups which would allow for gathering additional experience in a more controlled environment in their yearly periodisation.
Elementary Students’ Perceptions of Cognitively Challenging Physical Activity Games in Physical Education
Authors: Kolovelonis Athanasios , Samara Evdoxia , Digelidis Nikolaos , Goudas Marios
Published: November 2022

This study examined 10–11-year-old students’ perceptions regarding three different types of physical activity games based on different principles of mental engagement (contextual interference, mental control, or discovery). A total of 156 students (84 girls) from five fourth-grade (75 students) and five fifth-grade (81 students) classes of five elementary schools located in a middle-sized city in central Greece participated in the study. These students participated in a larger project consisting of a series of acute experiments aiming to examine the effectiveness of cognitively challenging physical activity games in elementary physical education. Students responded to open-ended questions regarding their perceptions of the physical activity games. Their responses were analyzed through a thematic analysis. A total number of 706 quotes were identified and categorized into the lower-order themes which were organized into four higher-order themes: (a) characteristics of the games, (b) effects of the games, (c) areas for improvement, and (d) preferences for specific games. Students’ views provided supporting evidence regarding the employment of cognitively challenging physical activity games in physical education. Useful insights regarding the characteristics of the games, their effects, and their areas for improvement were also gained.
Full Body Surface Coverage with Water-Equivalent Bolus as Novel Technique for Total Body Irradiation before Hematopoietic Stem Cell Transplantation in Pediatric Acute Lymphoid Leukemia
Authors: Furka Andrea , Nagy Zsofia , Szabó Imre , Fekete Gábor , Kelemen Ágnes , Bolobás Gábor , Sebők Gábriel , Molnár Tünde , Árvai János , Tornyi Ilona , Kostyál László , Révész János , Hauser Peter
Published: November 2022

Background: Total body irradiation (TBI) 2 × 2 Gy for 3 consecutive days followed by chemotherapy for conditioning pediatric patients with acute lymphoid leukemia (ALL) before bone marrow transplantation is superior to chemo-conditioning alone. The globally used anterior-posterior/posterior-anterior (AP/PA) technique is the most referable method, but volumetric modulated arc therapy (VMAT) with modern linear accelerators is more precise in terms of ensuring better dose distribution, especially for skin, and higher protection of organs at risk, resulting in less side effects. Method: For TBI, a modern VMAT technique was used. Whole-body immobilization in the supine position was performed using a vacuum mattress with a full body coverage, with a water-equivalent bolus of 1 cm thickness. The design goal was to achieve dose inhomogeneity of less than ±10%. Results: From 2020 to 2022, we performed TBI for five pediatric patients with ALL, with full body bolus and VMAT, who later received hematopoietic stem cell transplantation. No acute complications related to TBI were observed during the treatment period with a median follow-up of 1.27 (0.43–2.11) years. Conclusion: Using full body water-equivalent bolus with VMAT for TBI provides a safe method for children with a better organ sparing in the short term follow-up.
End-of-Life Management of Electric Vehicle Lithium-Ion Batteries in the United States
Authors: Meegoda Jay N. , Malladi Sarvagna , Zayas Isabel C.
Published: November 2022

Electric vehicles, which are primarily powered by lithium-ion batteries, have gained much attention as the future of transportation for their environmental and economic benefits. However, the current economy of lithium-ion battery management is quite linear. A circular economy with reusing and end-of-life recycling of lithium-ion batteries, would reduce the social and environmental costs associated with the mining of metals, decelerate the depletion of natural resources, and prevent the improper management that often accompanies disposal. This research suggests improvements to the end-of-life management of lithium-ion batteries in the US, considering current and emerging recycling technologies, current collection and transportation infrastructure, current reuse applications, and an analysis of the current regulatory policies in place. Along with providing a comprehensive overview of these topics, this research compiles and provides a set of actionable End-of-Life (EOL) management recommendations for the US on policy, infrastructure, and technology.
The Influence of Ukraine’s Foreign Grain Trade through Romania on Prices
Authors: Sterie Maria Cristina , Petre Ionut Laurentiu , Bogos Iulia Bianca
Published: November 2022

The objective of the present research was to determine the external influence of the grain trade, i.e., the influence of Ukraine’s grain trade through Romania on price levels recorded at Romania’s borders. The research methods to achieve this objective consisted of quantitative and qualitative analyses of wheat and maize imports and export data from the beginning of 2022 to the present, as well as using the t-stat test to determine the existence of significant price differences, and the linear regression model. The research results confirm that there were differences between the two pre- and post-military conflict periods regarding the volume of imports from Ukraine and the increase in the supply of wheat and maize from Romania, through this trade activity, led to changes in prices.
Elucidation of Structures, Electronic Properties, and Chemical Bonding of Monophosphorus-Substituted Boron Clusters in Neutral, Negative, and Positively Charged PBn/PBn–/PBn+ (n = 4–8)
Authors: Li Qing-Shan , Song Bingyi , Wen Limei , Yang Li-Ming , Ganz Eric
Published: November 2022

This paper reports the computational study of phosphorus-doped boron clusters PBn/PBn–/PBn+ (n = 4–8). First, a global search and optimization of these clusters were performed to determine the stable structures. We used density functional theory (DFT) methods and ab initio calculations to study the stability of the atomic clusters and to explore the arrangement of stable structures. We found that the lowest energy structures of the smaller phosphorus-doped boron clusters tend to form planar or quasi-planar structures. As additional boron atoms are added to the smallest structures, the boron atoms expand in a zigzag arrangement or in a net-like manner, and the phosphorus atom is arranged on the periphery. For larger structures with seven or eight boron atoms, an unusual umbrella-like structure appears. We calculated the binding energy as well as other energies to study cluster stability. We calculated the ionization energy, electron affinity, and the HOMO–LUMO gaps. In addition, we used the adaptive natural density partitioning program to perform bond analysis so that we have a comprehensive understanding of the bonding. In order to have a suitable connection with the experiment, we simulated the infrared and photoelectron spectra.
The Advancement of Herbal-Based Nanomedicine for Hair
Authors: Padule Komal , Shinde Sonali , Chitlange Sohan , Giram Prabhanjan , Nagore Dheeraj
Published: November 2022

Polymer, lipid, and natural protein-based hair care nanocarriers are in preclinical testing. Nanomedicine has enhanced therapeutic efficacy and decreased side effects. This review examines herbal nanomedicine for hair care. We also reviewed the hair cycle, its morphology, and the mechanisms of herbal-based medicine that regulate the hair cycle to treat hair loss. Nano-formulations have better solubility, permeability, therapeutic efficacy, and prolonged distribution than standard herbal medicines. This review also discussed the nanotechnology barrier and nano formulations for hair loss and growth and includes a recent herbal nanomedicine study. Researchers interested in using herbs to treat hair problems and clinically translating hair care products may find the results presented significant.
Biochemical Properties and Cosmetic Uses of Commiphora myrrha and Boswellia serrata
Authors: Alraddadi Bssmah Ghazi , Shin Hyun-Jae
Published: November 2022

Organic materials have been the subject of numerous recent cosmetics studies. Plant extracts and/or plant-derived resources in the Middle East have significant potential in many cosmetic fields because they exhibit useful properties that promote the repair of cellular functions and improve skin conditions. Multiple organic substances from these resources have long-lasting environmental effects, extensive storage capacities, and affect human physiological activity. Recent studies have revealed that Commiphora myrrha (myrrh) and Boswellia serrata (frankincense) extracts can prevent aging, acne, and spots while enhancing skin moisture and suppleness. Given that myrrh and frankincense exhibit anti-inflammatory and antioxidant characteristics that significantly improve human health, their utilization in various cosmetic products has received attention from global cosmetic corporations. This review details the bioactive compounds and cosmeceutical properties of myrrh and frankincense and their use in cosmetic formulations.
Shift Register, Reconvergent-Fanout (SiRF) PUF Implementation on an FPGA
Authors: Plusquellic Jim
Published: November 2022

Physical unclonable functions (PUFs) are gaining traction as an attractive alternative to generating and storing device keying material over traditional secure non-volatile memory (NVM) technologies. In this paper, we propose an engineered delay-based PUF called the shift-register, reconvergent-fanout (SiRF) PUF, and present an analysis of the statistical quality of its bitstrings using data collected from a set of FPGAs subjected to extended industrial temperature-voltage environmental conditions. The SiRF PUF utilizes the Xilinx shift register primitive and an engineered network of logic gates that are designed to distribute signal paths over a wide region of the FPGA fabric using a MUXing scheme similar in principle to the shift-rows permutation function within the Advanced Encryption Standard algorithm. The shift register is utilized in a unique fashion to enable individual paths through a Xilinx 5-input LUT to be selected as a source of entropy by the challenge. The engineered logic gate network utilizes reconvergent-fanout as a means of adding entropy, eliminating bias and increasing uncertainty with respect to which paths are actually being timed and used in post-processing to produce the secret key or authentication bitstring. The SiRF PUF is a strong PUF build on top of a network with 10’s of millions of possible paths.
Sn-Doped Hydrated V2O5 Cathode Material with Enhanced Rate and Cycling Properties for Zinc-Ion Batteries
Authors: Guo Kai , Cheng Wenchong , Liu Haiyuan , She Wenhao , Wan Yinpeng , Wang Heng , Li Hanbin , Li Zidan , Zhong Xing , Ouyang Jinbo , Yu Neng
Published: November 2022

Water molecules and cations with mono, binary, and triple valences have been intercalated into V2O5 to significantly improve its electrochemical properties as a cathode material of zinc-ion batteries. Sn as a tetravalent element is supposed to interact aggressively with the V2O5 layer and have a significant impact on the electrochemical performance of V2O5. However, it has been rarely investigated as a pre-intercalated ion in previous works. Hence, it is intriguing and beneficial to develop water molecules and Sn co-doped V2O5 for zinc-ion batteries. Herein, Sn-doped hydrated V2O5 nanosheets were prepared by a one-step hydrothermal synthesis, and they demonstrated that they had a high specific capacity of 374 mAh/g at 100 mA/g. Meanwhile, they also showed an exceptional rate capability with 301 mAh/g even at a large current density of 10 A/g, while it was only 40 mAh/g for the pristine hydrated V2O5, and an excellent cycling life (87.2% after 2500 cycles at 5 A/g), which was far more than the 25% of the pure hydrated V2O5. The dramatic improvement of the rate and cycling performance is mainly attributed to the faster charge transfer kinetics and the enhanced crystalline framework. The remarkable electrochemical performance makes the Sn-doped hydrate V2O5 a potential cathode material for zinc-ion batteries.
Trade in Southeast Asian Box Turtles from Indonesia: Legality, Livelihoods, Sustainability and Overexploitation
Authors: Nijman Vincent , Shepherd Chris R.
Published: November 2022

Southeast Asian box turtles Cuora amboinensis are distributed in mainland Southeast Asia and throughout most of insular Southeast Asia and are often found in habitats shared with humans. In the 2000s evidence emerged of an enormous illegal export of Southeast Asian box turtles from Indonesia estimated at a hundred times larger than the legal exports. Using publicly available data we show that one or two exporters in Sampit in the province of Central Kalimantan, one of nine provinces where harvest of Southeast Asian box turtles is authorised, continue to trade above permitted levels. Harvest quotas for Central Kalimantan are set at 1000 turtles a year, and this is divided between five approved traders, two of whom are based in Sampit. A single visit to one of these two traders in April 2019 documented the presence of 549 Southeast Asian box turtles. Based on documented data from middlemen we estimate that the number of Southeast Asian box turtles that are harvested in Central Kalimantan to supply the traders in Sampit amounts to 19,000–45,000 individuals a year. If the Sampit traders stay within their quotas potential profits are less than USD 400 year−1, compared to up to USD 40,000 year−1 when trading the higher numbers. It is not known how many box turtles are traded by the other three exporters in the province. With the annual harvest quota for all of Indonesia set at less than 15,000 the massive illegal trade as documented in the 1990s and 2000s continues unabated. Assessments of the harvest and trade in Southeast Asian box turtles must consider both the sustainability and legality of this trade.
When BERT Started Traveling: TourBERT—A Natural Language Processing Model for the Travel Industry
Authors: Arefeva Veronika , Egger Roman
Published: November 2022

In recent years, Natural Language Processing (NLP) has become increasingly important for extracting new insights from unstructured text data, and pre-trained language models now have the ability to perform state-of-the-art tasks like topic modeling, text classification, or sentiment analysis. Currently, BERT is the most widespread and widely used model, but it has been shown that a potential to optimize BERT can be applied to domain-specific contexts. While a number of BERT models that improve downstream tasks’ performance for other domains already exist, an optimized BERT model for tourism has yet to be revealed. This study thus aimed to develop and evaluate TourBERT, a pre-trained BERT model for the tourism industry. It was trained from scratch and outperforms BERT-Base in all tourism-specific evaluations. Therefore, this study makes an essential contribution to the growing importance of NLP in tourism by providing an open-source BERT model adapted to tourism requirements and particularities.
An Enzyme-Linked Immunosorbent Assay for the Detection of Mitochondrial DNA–Protein Cross-Links from Mammalian Cells
Authors: Xu Wenyan , Zhao Linlin
Published: November 2022

DNA–Protein cross-links (DPCs) are cytotoxic DNA lesions with a protein covalently bound to the DNA. Although much has been learned about the formation, repair, and biological consequences of DPCs in the nucleus, little is known regarding mitochondrial DPCs. This is due in part to the lack of robust and specific methods to measure mitochondrial DPCs. Herein, we reported an enzyme-linked immunosorbent assay (ELISA)-based method for detecting mitochondrial DPCs formed between DNA and mitochondrial transcription factor A (TFAM) in cultured human cells. To optimize the purification and detection workflow, we prepared model TFAM-DPCs via Schiff base chemistry using recombinant human TFAM and a DNA substrate containing an abasic (AP) lesion. We optimized the isolation of TFAM-DPCs using commercial silica gel-based columns to achieve a high recovery yield for DPCs. We evaluated the microplate, DNA-coating solution, and HRP substrate for specific and sensitive detection of TFAM-DPCs. Additionally, we optimized the mtDNA isolation procedure to eliminate almost all nuclear DNA contaminants. For proof of concept, we detected the different levels of TFAM-DPCs in mtDNA from HEK293 cells under different biological conditions. The method is based on commercially available materials and can be amended to detect other types of DPCs in mitochondria.
Improved Black Widow Spider Optimization Algorithm Integrating Multiple Strategies
Authors: Wan Chenxin , He Bitao , Fan Yuancheng , Tan Wei , Qin Tao , Yang Jing
Published: November 2022

The black widow spider optimization algorithm (BWOA) had the problems of slow convergence speed and easily to falling into local optimum mode. To address these problems, this paper proposes a multi-strategy black widow spider optimization algorithm (IBWOA). First, Gauss chaotic mapping is introduced to initialize the population to ensure the diversity of the algorithm at the initial stage. Then, the sine cosine strategy is introduced to perturb the individuals during iteration to improve the global search ability of the algorithm. In addition, the elite opposition-based learning strategy is introduced to improve convergence speed of algorithm. Finally, the mutation method of the differential evolution algorithm is integrated to reorganize the individuals with poor fitness values. Through the analysis of the optimization results of 13 benchmark test functions and a part of CEC2017 test functions, the effectiveness and rationality of each improved strategy are verified. Moreover, it shows that the proposed algorithm has significant improvement in solution accuracy, performance and convergence speed compared with other algorithms. Furthermore, the IBWOA algorithm is used to solve six practical constrained engineering problems. The results show that the IBWOA has excellent optimization ability and scalability.
An Edge-Supported Blockchain-Based Secure Authentication Method and a Cryptocurrency-Based Billing System for P2P Charging of Electric Vehicles
Authors: Akhter A. F. M. Suaib , Arnob Tawsif Zaman , Noor Ekra Binta , Hizal Selman , Pathan Al-Sakib Khan
Published: November 2022

The popularity of electric vehicles (EVs) is constantly increasing, as they use relatively greener, sustainable energy. However, it is a fact that the charging stations for EVs are yet to meet the demand. It could be a great solution if a peer-to-peer (P2P) charging system could be initiated by anyone who wants to make their garage’s charge points publicly available for commercial purposes, named a home charging station (HCS). In this work, our idea is to bring interested charging stations under a network of nodes and a blockchain-based management system, where the blockchain is responsible for ensuring the authenticity of both the charging stations and charge receiver. A cryptocurrency-based payment system has also been proposed to ensure transactions’ security, integrity, transparency, and immutability. A reputation management system is applied to maintain the quality of service. Miners with high processing power are used to alleviate lagging during block creation, supported by edge servers. The proposed system has been implemented by using virtual machines. A theoretical analysis is presented to assess the compatibility and possible cost requirements to implement the system in a real-world scenario.
Three-Dimensional Face Recognition Using Solid Harmonic Wavelet Scattering and Homotopy Dictionary Learning
Authors: He Yi , Cheng Peng , Yang Shanmin , Zhang Jianwei
Published: November 2022

Data representation has been one of the core topics in 3D graphics and pattern recognition in high-dimensional data. Although the high-resolution geometrical information of a physical object can be well preserved in the form of metrical data, e.g., point clouds/triangular meshes, from a regular data (e.g., image/audio) processing perspective, they also bring excessive noise in the course of feature abstraction and regression. For 3D face recognition, preceding attempts focus on treating the scan samples as signals laying on an underlying discrete surface (mesh) or morphable (statistic) models and by embedding auxiliary information, e.g., texture onto the regularized local planar structure to obtain a superior expressive performance to registration-based methods, but environmental variations such as posture/illumination will dissatisfy the integrity or uniform sampling condition, which holistic models generally rely on. In this paper, a geometric deep learning framework for face recognition is proposed, which merely requires the consumption of raw spatial coordinates. The non-uniformity and non-grid geometric transformations in the course of point cloud face scanning are mitigated by modeling each identity as a stochastic process. Individual face scans are considered realizations, yielding underlying inherent distributions under the appropriate assumption of ergodicity. To accomplish 3D facial recognition, we propose a windowed solid harmonic scattering transform on point cloud face scans to extract the invariant coefficients so that unrelated variations can be encoded into certain components of the scattering domain. With these constructions, a sparse learning network as the semi-supervised classification backbone network can work on reducing intraclass variability. Our framework obtained superior performance to current competing methods; without excluding any fragmentary or severely deformed samples, the rank-1 recognition rate (RR1) achieved was 99.84% on the Face Recognition Grand Challenge (FRGC) v2.0 dataset and 99.90% on the Bosphorus dataset.
How Well Do Contemporary Theories Explain Floating Exchange Rate Changes in an Emerging Economy: The Case of EUR/PLN
Authors: Burda Adrian Marek
Published: November 2022

The purpose of this paper is to investigate how well contemporary exchange rate theories explain fluctuations in exchange rates of emerging economies, before and after the Global Financial Crisis (GFC). As an example, the EUR/PLN exchange rate in 1999–2015 was selected as the currency pair that was the most liquid in the region; it had a stable exchange rate regime in the given period. The whole analysis was performed within the selected linear vector error correction (VEC) model framework. VEC models incorporate such well-known theories as purchasing power parity (PPP), the uncovered interest rate parity (UIP), the Harrod–Balassa–Samuelson (HBS) effect, the terms of trade (TOT), the net financial asset (NFA) theory and risk premium. The results indicate the greater importance of external factors—in particular, the Euro Area (EA) short-term interest rates and EA price shocks after the GFC. The main sources of EUR/PLN variability were found to be exchange rate shocks, terms of trade shocks and foreign and domestic short-term interest rate shocks, as well as foreign price shocks. These results are of particularly high importance for our own exchange rate shocks and indicate that a large part of exchange rate fluctuations in EUR/PLN still remains unexplained.
Consideration for Positive and Negative Effect of Multi-Sensory Environment Interventions on Disabled Patients through Electrocardiography
Authors: Jeong Hieyong , Ohno Yuko
Published: November 2022

Many studies have supported the efficacy of multi-sensory environment (MSE) interventions in reducing behavioral and psychological symptoms and improving the quality of life for disabled patients. However, it is difficult to identify the groups that are helped and those who are harmed. This study verified the effect of multi-sensory environment interventions on disabled patients by using thermal images, then addressed the precaution using electrocardiography (ECG). Twenty disabled patients participated in experiments for 12 min: ten with muscular dystrophy (MD) and ten with severe motor and intellectual disabilities (SMID). The continuous measurement of nasal temperature evaluated the emotional arousal after facial detection. The QT-RR relation was used to assess the risk degree. It was found that the continuous measurement of nasal temperature enabled us to evaluate the emotional arousal of disabled patients in MSE with the comparison of ECG. Through the QT-RR relation, it was found that the risk assessment for the patient with SMID was 11 times higher than those with MD because the QT was below 300 ms. Therefore, it was concluded that the specification for the risky group was related to the kind of prescribed medication through continuous measurement.
Learning to Co-Embed Queries and Documents
Authors: Wu Yuehong , Lu Bowen , Tian Lin , Liang Shangsong
Published: November 2022

Learning to Rank (L2R) methods that utilize machine learning techniques to solve the ranking problems have been widely studied in the field of information retrieval. Existing methods usually concatenate query and document features as training input, without explicit understanding of relevance between queries and documents, especially in pairwise based ranking approach. Thus, it is an interesting question whether we can devise an algorithm that effectively describes the relation between queries and documents to learn a better ranking model without incurring huge parameter costs. In this paper, we present a Gaussian Embedding model for Ranking (GERank), an architecture for co-embedding queries and documents, such that each query or document is represented by a Gaussian distribution with mean and variance. Our GERank optimizes an energy-based loss based on the pairwise ranking framework. Additionally, the KL-divergence is utilized to measure the relevance between queries and documents. Experimental results on two LETOR datasets and one TREC dataset demonstrate that our model obtains a remarkable improvement in the ranking performance compared with the state-of-the-art retrieval models.
Research on Retinex Algorithm Combining with Attention Mechanism for Image Enhancement
Authors: Liu Mingzhu , Chen Junyu , Han Xiaofei
Published: November 2022

Considering the high noise and chromatic aberration in the Retinex-Net image enhancement results, this paper put forward a modified Retinex-Net algorithm for weak illumination image enhancement based on the Decom-Net and Enhance-Net structures of Retinex-Net. The improved structure proposed in this paper adds the attention mechanism ECA-Net into the Decom-Net and Enhance-Net convolution layer of the original Retinex-Net structure, which can effectively reduce the problem of irrelevant background and local brightness imbalance, activate sensitive features, and improve the image’s details and brightness processing ability. Additionally, deep connected attention networks are embedded between the introduced attention modules, so that all of the attention modules can be trained jointly to improve the learning ability. Furthermore, the improved method also introduces a noise reduction loss function and a color loss function to suppress noise and to reduce image color distortion. The test results of the proposed method indicate that the image’s overall brightness can be balanced, the local areas cannot be overexposed, and more image details and color information can be retained than with other enhancement algorithms.
Ultrawideband Precision RCS Regulation for Trihedral Corner Reflectors by Loading Resistive Film Absorbers
Authors: Sun Tianqi , Yin Fangfang , Xu Chengxiang , Zhao Shan , Yan Hua , Yi Hongcheng
Published: November 2022

In this paper, an absorber with a resistive film is proposed, which holds stable polarization absorption characteristics at large angles by exploring the principle of absorption structure. The absorber contains three layers: the top layer is a metal patch with a resistive film, and the middle layer is covered with a metal patch. The thickness of the absorber structure is only 0.5 mm, and the absorber can be perfectly attached to the trihedral corner reflector (TCR) without affecting the characteristics of the reflector. By laying the absorber on the TCR, the TCR is stabilized at 8–40 GHz in the range of the incident angle ±20°, and the radar cross-section (RCS) reduction value of the TCR fluctuates around 1 dBsm. Thus, the RCS values of the three frequency points of 10 GHz, 15 GHz, and 35 GHz are consistent to achieve the accurate regulation of RCS. The stability of the absorber at different frequencies can be achieved, which is essential for the precise RCS regulation of complex scatterer structures. The effectiveness of the method was verified in experiments using a TCR metamaterial absorbing unit with resistive film.
Mapping and Optimization Method of SpMV on Multi-DSP Accelerator
Authors: Liu Sheng , Cao Yasong , Sun Shuwei
Published: November 2022

Sparse matrix-vector multiplication (SpMV) solves the product of a sparse matrix and dense vector, and the sparseness of a sparse matrix is often more than 90%. Usually, the sparse matrix is compressed to save storage resources, but this causes irregular access to dense vectors in the algorithm, which takes a lot of time and degrades the SpMV performance of the system. In this study, we design a dedicated channel in the DMA to implement an indirect memory access process to speed up the SpMV operation. On this basis, we propose six SpMV algorithm schemes and map them to optimize the performance of SpMV. The results show that the M processor’s SpMV performance reached 6.88 GFLOPS. Besides, the average performance of the HPCG benchmark is 2.8 GFLOPS.
A Script-Based Cycle-True Verification Framework to Speed-Up Hardware and Software Co-Design: Performance Evaluation on ECC Accelerator Use-Case
Authors: Zulberti Luca , Di Matteo Stefano , Nannipieri Pietro , Saponara Sergio , Fanucci Luca
Published: November 2022

Digital designs complexity has exponentially increased in the last decades. Heterogeneous Systems-on-Chip integrate many different hardware components which require a reliable and scalable verification environment. The effort to set up such environments has increased as well and plays a significant role in digital design projects, taking more than 50% of the total project time. Several solutions have been developed with the goal of automating this task, integrating various steps of the Very Large Scale Integration design flow, but without addressing the exploration of the design space on both the software and hardware sides. Early in the co-design phase, designers break down the system into hardware and software parts taking into account different choices to explore the design space. This work describes the use of a framework for automating the verification of such choices, considering both hardware and software development flows. The framework automates compilation of software, cycle-true simulations and analyses on synthesised netlists. It accelerates the design space exploration exploiting the GNU Make tool, and we focus on ensuring consistency of results and providing a mechanism to obtain reproducibility of the design flow. In design teams, the last feature increases cooperation and knowledge sharing from single expert to the whole team. Using flow recipes, designers can configure various third-party tools integrated into the modular structure of the framework, and make workflow execution customisable. We demonstrate how the developed framework can be used to speed up the setup of the evaluation flow of an Elliptic-Curve-Cryptography accelerator, performing post-synthesis analyses. The framework can be easily configured taking approximately 30 min, instead of few days, to build up an environment to assess the accelerator performance and its resistance to simple power analysis side-channel attacks.
Performance Evaluation of Solar PV-Based Z-Source Cascaded Multilevel Inverter with Optimized Switching Scheme
Authors: Faiz Minai Ahmad , Khan Akhlaque Ahmad , Pachauri Rupendra Kumar , Malik Hasmat , García Márquez Fausto Pedro , Arcos Jiménez Alfredo
Published: November 2022

AC loads may demand a fixed or variable voltage at their input terminals. When using inverters to power such loads, the response of the inverter must be precisely controlled to suit the demands of the AC loads. Inverters with higher efficiency and sensitivity will play an increasingly essential role as the need for solar PV applications in prospective green technology grows. To increase power quality and provide a reliable power source, an inverter architecture with harmonic reduction approaches is proposed. The multilevel inverter (MLI), unlike conventional inverters, is developed by cascaded single inverter units and is often used to connect renewable energy sources. As a result, they can be utilized to efficiently reduce harmonics. Among the three topologies, the most widely used in industries is the neutral-point clamped MLI. When the levels are raised, however, they demand a larger number of diodes. When the level of the flying capacitor exceeds three, several capacitors are necessary. As a result, the optimum option for synthesizing the right output voltage from several DC sources is a cascaded multilevel inverter (CMLI). Each link in a CMLI is connected by a single DC source; therefore, there is no voltage imbalance. However, getting equal DC voltages at the input of each unit is once again a limitation. In this work, various existing multilevel inverter topologies including hybrid topologies with different switching strategies are investigated and reported. The performance of a solar PV-based seven-level quasi-Z-source cascaded H-Bridge MLI (qZS-CHBMLI) has been thoroughly examined with the best switching scheme and best topology of multilevel inverters using MATLAB/Simulink.
A Synthesis of Pulse Influenza Vaccination Policies Using an Efficient Controlled Elitism Non-Dominated Sorting Genetic Algorithm (CENSGA)
Authors: Alkhamis Asma Khalil , Hosny Manar
Published: November 2022

Seasonal influenza (also known as flu) is responsible for considerable morbidity and mortality across the globe. The three recognized pathogens that cause epidemics during the winter season are influenza A, B and C. The influenza virus is particularly dangerous due to its mutability. Vaccines are an effective tool in preventing seasonal influenza, and their formulas are updated yearly according to the WHO recommendations. However, in order to facilitate decision-making in the planning of the intervention, policymakers need information on the projected costs and quantities related to introducing the influenza vaccine in order to help governments obtain an optimal allocation of the vaccine each year. In this paper, an approach based on a Controlled Elitism Non-Dominated Sorting Genetic Algorithm (CENSGA) model is introduced to optimize the allocation of the influenza vaccination. A bi-objective model is formulated to control the infection volume, and reduce the unit cost of the vaccination campaign. An SIR (Susceptible–Infected–Recovered) model is employed for representing a potential epidemic. The model constraints are based on the epidemiological model, time management and vaccine quantity. A two-phase optimization process is proposed: guardian control followed by contingent controls. The proposed approach is an evolutionary metaheuristic multi-objective optimization algorithm with a local search procedure based on a hash table. Moreover, in order to optimize the scheduling of a set of policies over a predetermined time to form a complete campaign, an extended CENSGA is introduced with a variable-length chromosome (VLC) along with mutation and crossover operations. To validate the applicability of the proposed CENSGA, it is compared with the classical Non-Dominated Sorting Genetic Algorithm (NSGA-II). The results indicate that optimal vaccination campaigns with compromise tradeoffs between the two conflicting objectives can be designed effectively using CENSGA, providing policymakers with a number of alternatives to accommodate the best strategies. The results are analyzed using graphical and statistical comparisons in terms of cardinality, convergence, distribution and spread quality metrics, illustrating that the proposed CENSGA is effective and useful for determining the optimal vaccination allocation campaigns.