bluuebunny/crossref_metadata_2025 huggingface dataset:
FLIM for Evaluation of Difference in Metabolic Status between Native and Differentiated from iPSCs Dermal Papilla Cells
Authors: Kashirina Alena , Gavrina Alena , Mozherov Artem , Kozlov Dmitriy , Kuznetsova Daria , Vorotelyak Ekaterina , Zagaynova Elena , Kalabusheva Ekaterina , Kashina Aleksandra
Published: September 2022

iPSCs and their derivatives are the most promising cell sources for creating skin equivalents. However, their properties are not fully understood. In addition, new approaches and parameters are needed for studying cells in 3D models without destroying their organization. Thus, the aim of our work was to study and compare the metabolic status and pH of dermal spheroids created from dermal papilla cells differentiated from pluripotent stem cells (iDP) and native dermal papilla cells (hDP) using fluorescence microscopy and fluorescence lifetime imaging microscopy (FLIM). For this purpose, fluorescence intensities of NAD(P)H and FAD, fluorescence lifetimes, and the contributions of NAD(P)H, as well as the fluorescence intensities of SypHer-2 and BCECF were measured. iDP in spheroids were characterized by a more glycolytic phenotype and alkaline intra-cellular pH in comparison with hDP cells. Moreover, the metabolic activity of iDP in spheroids depends on the source of stem cells from which they were obtained. So, less differentiated and condensed spheroids from iDP-iPSDP and iDP-iPSKYOU are characterized by a more glycolytic phenotype compared to dense spheroids from iDP-DYP0730 and iDP-hES. FLIM and fluorescent microscopy in combination with the metabolism and pH are promising tools for minimally invasive and long-term analyses of 3D models based on stem cells.
Spotlight: An Interview with NCCIH Director, Dr. Helene M. Langevin, on Whole Person Health
Authors: Logan Alan C. , Langevin Helene M.
Published: September 2022

In an ongoing series of spotlight interviews, Challenges Advisory Board Member and Nova Institute for Health Fellow, Alan C. Logan, meets with thought leaders, scientists, scholars, healthcare professionals, artisans and visionaries concerned about health at scales of persons, places and the planet. Here in the inaugural interview, the Director of the National Institutes of Health, National Center for Complementary and Integrative Health, Dr. Helene Langevin, responds to a set of questions posed by Challenges. Dr. Langevin discusses the emerging concept of whole person health, and in particular, how the concept intersects with the grand and interconnected challenges of our time.
Ultra-Low Reflectivity in Visible Band of Vanadium Alumina Nanocomposites
Authors: Wang Qiujin , Zhao Guozhong , Wang Hai
Published: September 2022

The high-temperature annealing effect of a V2O5/Al2O3 bilayer on the reflectivity of visible band was studied in the present work. It was found that the V2O5 (200 nm)/Al2O3 (30 nm) sample (A-0) has a nano-granular surface morphology without a definite crystalline phase. The reflectance of A-0 overreaches 60% as the wavelength is larger than 650 nm, and its minimum reflectance (20%) occurs at the wavelength of ~500 nm. After in situ annealing treatment at 750 °C for 30 min, a triclinic AlVO4 phase appears while the nano-granular surface morphology remains (sample A-30). The reflectivity of A-30 is well suppressed in comparison with that of A-0 especially in the long wavelength range. Its minimum reflectivity approaches 5% at ~500 nm wavelength. It is speculated that the appearance of a new AlVO4 nanophase is the main reason for the decline of reflectivity. Extending the annealing time to 60 min, the reflectivity spectrum, as well as the surface morphology, are almost the same. These results can be helpful for applications of vanadium alumina nanocomposites in high-temperature environments.
A Review on Modelling and Simulation of Laser Additive Manufacturing: Heat Transfer, Microstructure Evolutions and Mechanical Properties
Authors: Zhang Zhao , Wang Yifei , Ge Peng , Wu Tao
Published: September 2022

Modelling and simulation are very important for revealing the relationship between process parameters and internal variables like grain morphology in solidification, precipitate evolution, and solid-state phase transformation in laser additive manufacturing. The impact of the microstructural changes on mechanical behaviors is also a hot topic in laser additive manufacturing. Here we reviewed key developments in thermal modelling, microstructural simulations, and the predictions of mechanical properties in laser additive manufacturing. A volumetric heat source model, including the Gaussian and double ellipsoid heat sources, is introduced. The main methods used in the simulation of microstructures, including Monte Carlo method, cellular automaton, and phase field method, are mainly described. The impacts of the microstructures on mechanical properties are revealed by the physics-based models including a precipitate evolution based model and dislocation evolution based model and by the crystal plasticity model. The key issues in the modelling and simulation of laser additive manufacturing are addressed.
Research on Mesoscale Nucleation and Growth Processes in Solution Crystallization: A Review
Authors: Wang Xiaowei , Li Kangli , Qin Xueyou , Li Mingxuan , Liu Yanbo , An Yanlong , Yang Wulong , Chen Mingyang , Ouyang Jinbo , Gong Junbo
Published: September 2022

In recent studies, the existence of mesoscale precursors has been confirmed in crystallization. Different from the classical crystallization theory, which only considers the sequential attachment of basic monomers (atoms, ions, or molecules), the nonclassical crystallization process involving precursors such as prenucleation clusters, nanoparticles, and mesocrystals is more complicated. The mesoscale structure is important for the quantitative description and directional regulation of the solution crystallization process. It is necessary to explore the mechanism by the mesoscale scientific research methods on the base of traditional chemical engineering and process system engineering research methods. Therefore, the paper reviews several representative nonclassical nucleation and growth theories, mainly including two-step nucleation theory, prenucleation clusters theory, particle agglomeration theory, amorphous precursor growth theory, particle attachment growth theory and mesocrystal growth theory. Then, the mesoscale structure and its spatiotemporal dynamic behavior are discussed, and the application of the EMMS model in the nucleation and growth process is analyzed. Finally, we put forward our views on the prospect of the paradigms and theoretical innovations of using mesoscale methods in crystal nucleation and growth.
The Effect of Cooling Rate from Solution Treatment on γ′ Reprecipitates and Creep Behaviors of a Ni-Based Superalloy Single-Crystal Casting
Authors: Huang Jiapeng , Ai Cheng , Ru Yi , Shang Yong , Pei Yanling , Li Shusuo , Gong Shengkai , Zhang Heng
Published: September 2022

Slowing down the coarsening of the γ′ phase and suppressing the precipitation of the topologically close-packed (TCP) phase is crucial for optimizing the creep properties of Ni-based single crystal superalloys, which are affected by the solution treatment history. In the present study, the effect of cooling rate on the morphology, size and lattice misfit of γ′ reprecipitates after solution treatment, as well as the microstructural evolution (e.g., the coarsening of γ′ reprecipitate and precipitation of the TCP phase) and creep properties of samples under different cooling rates at 1100 °C were investigated. The findings suggested that as the cooling rate increasing, the size of γ′ reprecipitates decreased, while the morphology transformed from polygonal to cubic. Additionally, faster cooling rate, on the one hand, the lower the degree of lattice misfit of γ/γ′ phases, which is beneficial to slow down the coarsening of the γ′ phase; on the other hand, the supersaturation of the γ-phase was reduced, i.e., the Mo and Re contents in the γ matrix were lower compared to the slow-cooling sample, which led to a lower TCP phase area fraction during thermal exposure at 1100 °C. It is crucial that the creep life of the alloy significantly improved by increasing the cooling rate after solution treatment; this is facilitated by the formation of rafts from finer cubic γ′ phase and reduction in the TCP phase as a source of microcracks. In conclusion, the findings of this study provide new insights into suppressing the precipitation of the TCP phase and optimizing alloy heat treatment processes to improve creep properties.
Modeling of Microstructure and Mechanical Properties of Heat Treated ZE41-Ca-Sr Alloys for Integrated Computing Platform
Authors: Fu Yu , Liu Chen , Song Yunkun , Hao Hai , Xu Yongdong , Shao Zhiwen , Wang Jun , Zhu Xiurong
Published: September 2022

The main objective of this study is to present a methodology to model the microstructure and mechanical properties of ZE41-xCa-ySr alloys for integrated optimization calculation of the heat treatment process of gearbox casting. Firstly, the models of microstructure and mechanical properties of ZE41-xCa-ySr alloys (0 ≤ x ≤ 2, 0 ≤ y ≤ 0.2) are developed using an artificial neural network (ANN) and multivariate regression. The dataset for ANN and regression models is generated by investigating the microstructures and mechanical properties of the ZE41-xCa-ySr alloys. The inputs for ANN and regression models are Ca and Sr contents, aging temperature and aging time. The outputs are grain size, ultimate tensile strength, elongation and microhardness. The optimal ANN model is obtained by testing the performance of different network architectures. In addition, multivariate regression models have been built based on the Least Squares method. Secondly, based on SiPESC software, an Integrated Computing Platform is constructed by combining the scripting language with the command line operation of simulation software, realizing the “process—microstructure—property” optimization calculation. Finally, based on the developed regression model, an Integrated Computing Platform batch called MATLAB achieves the heat treatment process optimization based on mechanical property prediction. The optimum aging temperature of the ZE41-0.17Ca-0.2Sr alloy is 322 °C, and the corresponding aging time is 11 h. Furthermore, the optimized results are validated by the ANN model, suggesting that ANN predicted results are in good agreement with optimized results. As a consequence, this work provides a new strategy for the research and development of Mg alloys, contributing to acceleration in the development of magnesium alloys.
Synthesis, Crystal Structure, DFT Studies and Optical/Electrochemical Properties of Two Novel Heteroleptic Copper(I) Complexes and Application in DSSC
Authors: Soto-Acosta Samuel , Campos-Gaxiola José J. , Reynoso-Soto Edgar A. , Cruz-Enríquez Adriana , Baldenebro-López Jesús , Höpfl Herbert , García Juventino J. , Flores-Álamo Marcos , Miranda-Soto Valentín , Glossman-Mitnik Daniel
Published: September 2022

New copper(I) compounds of compositions [Cu(HL)(PPh3)2]·H2O (1) and [Cu(HL)POP]·CH2Cl2 (2), where HL = monoanion of pyridine-2,5-dicarboxylic acid, PPh3 = triphenylphosphine and POP = bis [2-(diphenylphosphine)phenyl]ether), are documented. The complexes were characterized by elemental analysis, spectroscopic techniques (IR, 1H/31P RMN and UV–VIS), cyclic voltammetry, and thermogravimetric analysis. Single-crystals for 1 and 2 enabled X-ray diffraction analysis, revealing distorted tetrahedral geometries for Cu(I) centers embedded in NOP2 environments. The crystal structures are stabilized by O−H∙∙∙O, C−H∙∙∙O, C−H∙∙∙π and π∙∙∙π interactions that were analyzed by inspection of the Hirshfeld surfaces and fingerprint plots. Compounds 1 and 2 show interesting optical/electrochemical properties, which were studied experimentally in solution by UV–Vis spectroscopy and cyclic voltammetry, as well as theoretically using Time-Dependent Density Functional Theory (TD-DFT). Additionally, in combination with the ruthenium complex N719, their efficiency as co-sensitizers in dye-sensitized solar cells (DSSCs) was assessed, showing good activity.
Research Progress of Anode-Free Lithium Metal Batteries
Authors: Zhang Jian , Khan Abrar , Liu Xiaoyuan , Lei Yuban , Du Shurong , Lv Le , Zhao Hailei , Luo Dawei
Published: September 2022

Lithium-metal batteries (LMBs) are regarded as the most promising candidate for practical applications in portable electronic devices and electric vehicles because of their high capacity and energy density. However, the uncontrollable growth of lithium dendrite reduces its cycling ability and even causes a severe safety concern, which impedes the development of the technology. Although great efforts have been devoted to solving the lithium dendrite issue in recent years, the contradiction between the high cost of thin Li foil and the severe safety hazard of excess Li still exists. This is precisely the factor that inspired the development of anode-free lithium-metal batteries (AFLMBs). Compared to lithium-metal batteries, AFLMBs with a zero-excess Li anode possess an incredible, conceivable, and specific energy. Additionally, because the use of metal lithium is limited, the battery manufacturing will be safer and simpler, leading to a significant decrease in cost. However, comprehensive reviews on anode-free batteries are rare. Therefore, in this review, we aim to explain the essential development factors influencing the cycle life, energy density, cost, and working mechanism of anode-free batteries. We summarize different strategies to improve the cycling stability of AFLMBs, and we discuss the application of anode-free electrodes in other electrochemical energy storage systems. Moreover, it is believed that the combination of modification techniques, including electrolytes and current collectors, and the application protocols will be the most important solution for future anode-free batteries.
Composition Diversity and Expression Specificity of the TPS Gene Family among 24 Ficus Species
Authors: Sun Peng , Chen Xiaoyong , Chantarasuwan Bhanumas , Zhu Xueying , Deng Xiaoxia , Bao Ying , Yu Hui
Published: September 2022

Volatile organic compounds (VOCs) released by the receptive syconia of Ficus species play a vital role in attracting highly species-specific pollinating fig wasps. The components of VOCs vary considerably among Ficus species, but are generally dominated by a few common terpenoid compounds or specific proportions of several compounds. Terpene synthase (TPS) is the main source of specific and diverse terpenoids, but the evolution of the TPS gene family in Ficus and the potential functions of the TPS genes in species-specific pollination remain largely unelucidated. In this study, using transcriptomes of ostiole bracts of receptive male figs from 24 Ficus species collected from South China and Southeast Asia, we comprehensively scanned and investigated the composition and evolutionary characteristics of all TPS genes in all 24 species. We identified 248 TPS genes, including 33 orthologous genes and six singletons. Sequence and phylogenetic analysis showed that a majority of the 248 TPSs contained the DDXXD and DTE motifs, rather than the DXDD motif, and involved all subfamilies (TPS-a,b,c,e/f and g) known in other angiosperm genomes, suggesting a very diverse and complex composition of class I TPSs during the receptive phase. In addition, compared to TPS-a, which is generally the largest subfamily in some plants, the TPS-b subfamily contained the highest number of genes in Ficus species. Expression profile comparison showed that the distribution and expression levels of different TPSs among different Ficus species differed considerably, but a few TPS genes were common across most species. Positive selection analysis showed that the Ficus TPS genes were mainly under purifying selection, with only four genes having positive selection signals and two genes having positive selection sites, and two genes having relatively fast-evolving rates. The present study demonstrates the basic evolutionary characteristics of TPS genes in Ficus and reveals the roles of TPSs in shaping the diversity and specificity of the fig–fig wasp symbiotic relationship.
Liverworts of the South Kamchatka Nature Park: Survival in Active Volcanism Land
Authors: Bakalin Vadim A. , Klimova Ksenia G. , Karpov Eugeniy A. , Bakalin Daniil A. , Choi Seung Se
Published: September 2022

Kamchatka, due to its position in hemiarctic northeast Asia on the migration pathways of taxa from Asia to America and vice versa, which has an insular geographical position and provides numerous pieces of evidence regarding current active volcanism, has a peculiar flora. The study of the liverwort flora of the southeastern part of the Kamchatka Peninsula (South Kamchatka Nature Park), which, until now, has been very poorly explored, showed high taxonomic richness and some specificity due to volcanic evidence. In total, 132 species have been recorded in this sector of the “Pacific Ring of Fire”. This number is quite high compared to other floras of hemiarctic Asia. The influence of volcanism on flora formation is prominent due to the regular renewal of substrates, the appearance of specific habitats (for example, thermal water outlets), the displacement of vegetation belts, and ashfalls leading to the presence of extended spaces free of vegetation cover and is an area that is open for invaders. The altitudinal zonality, despite the difference of 2000 m in elevation, is not clearly expressed in the flora of the liverworts: arctomontane species descend far down the altitudinal profile, reaching the Betula ermanii forests. The “plantless” uppermost belt in the mountains, commonly described in floristic studies of vascular plants, is not actually free of plants if liverwort occurrences are considered. A number of species normally occupy unusual habitats in the studied flora due to contemporary volcanism evidence, e.g., sulfur-rich substrates.
Catalyzing Red List Assessments of Underrepresented Taxa through Partner Networks and Student Engagement
Authors: Böhm Monika , Waldien David L. , Setliff Gregory P. , Abenis Kristine O. , Aguirre Luis F. , Akite Perpetra , Alviola Marnelli S. , Alviola Phillip A. , Aramayo Bejarano José Luis , Badon Jade Aster T. , Barrion-Dupo Aimee Lynn A. , Brodie Gilianne , Cabras Analyn , Canteiro Cátia , Danoff-Burg James A. , De Chavez Emmanuel Ryan C. , Duya Mariano Roy M. , Eusebio Orlando L. , Fauzi Norashikin , Glass Zachary J. , Grabowski Noelle E. , Guerra Serrudo Juán Fernando , Henriques Sérgio S. , Horton Brent M. , Jayaraj Vijaya Kumaran , Kaplin Beth A. , Keller Shannon M. , Ledezma Arias Maria Julieta , Lit, Jr. Ireneo L. , Lucañas Cristian C. , Medina Milton Norman D. , Meyer Michael D. , Miladin Jenna , Mourad Ahmim , Mueller Gregory M. , Narayan Shiloh S. , Naredo Jeremy C. B. , Osborne-Naikatini Tamara , Rasalan Joseph B. , Rashni Bindiya , Musila Simon , Suganthi Appalasamy , Thomas-Moko Nunia , Torrejos Chrestine B. , Wallace John R. , Waqa-Sakiti Hilda , Yap Sheryl
Published: September 2022

Global biodiversity decline is continuing largely unabated. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species (hereafter, Red List) provides us with the gold standard for assessments, but taxonomic coverage, especially for invertebrates and fungi, remains very low. Many players contribute to the Red List knowledge base, especially IUCN Red List partners, IUCN-led assessment projects, and the Specialist Groups and Red List Authorities (RLA) of the IUCN Species Survival Commission. However, it is vital that we develop the next generation of contributors and bring in new, diverse voices to build capacity and to sustain the huge assessment effort required to fill data gaps. Here, we discuss a recently established partner network to build additional capacity for species assessments, by linking academia directly into the assessment processes run by Specialist Groups and RLAs. We aim to increase Red List “literacy” amongst potential future conservationists and help students to increase publication output, form professional networks, and develop writing and research skills. Professors can build Red List learning into their teaching and offer Red Listing opportunities to students as assignments or research projects that directly contribute to the Red List. We discuss the opportunities presented by the approach, especially for underrepresented species groups, and the challenges that remain.
A New Locality for the Blind Loach, Eidinemacheilus smithi (Teleostei: Nemacheilidae) in Iranian Zagros: A Morpho-Molecular Approach
Authors: Malek-Hosseini Mohammad Javad , Fatemi Yaser , Esmaeili Hamid Reza , Lokovšek Tjaša , Kuntner Matjaž
Published: September 2022

Four obligate cave fish species have been recorded from Zagros in Iran: Garra typhlops (Bruun and Kaiser, 1944), G. lorestanensis (Mousavi-Sabet and Eagderi, 2016), G. tashanensis (Mousavi-Sabet, Vatandoust, Fatemi and Eagderi, 2016) and Eidinemacheilus smithi (Greenwood, 1976). So far, the only known locality of the latter has been the Loven cave. Here, we extend the known range of the Zagros blind loach (E. smithi) by reporting a new locality, the Tuveh spring, located 31 km south of Loven. We combine morphological evidence with the calculated K2P genetic divergences of 1.39% between Tuveh and Loven to confirm that these populations are conspecific. Our discovery of the second E. smithi population has implications for the conservation of this rare and vulnerable species.
The Diagnostic Relevance of β-D-Glucan for Candidemia within Internal Medicine Wards
Authors: Corcione Silvia , Chasseur Luisa , Lupia Tommaso , Shbaklo Nour , Scabini Silvia , Filippini Claudia , Mornese Pinna Simone , Morra di Celle Stefania , Cavallo Rossana , De Rosa Francesco Giuseppe
Published: September 2022

Candidemia diagnosis is based on the combination of clinical, microbiological and laboratory data. We aimed to evaluate performances and accuracy of (1,3)-β-D-glucan (BDG) at various cut-offs in internal medicine patients. An observational retrospective–prospective study was performed. Patients with at least two determinations of BDG and paired, associated blood cultures within ±48 h were considered. A total of 140 patients were included: 26 with Candida spp. blood-stream infections (BSI) and 114 without candidemia. Patients with candidemia were older and had higher BDG values, need of parenteral nutrition, higher colonization by Candida in more than one site, presence of percutaneous gastrostomy and higher Candida or Charlson scores. BDG maintained the best compromise between sensitivity, specificity and optimal negative predictive value was 150 pg/mL. BDG values at cut-off of 150 pg/mL increase the strength of association between BDG and development of candidemia (Odds Ratio—OR 5.58; CI 2.48–12.53 vs. OR 1.06; CI 1.003–1.008). Analyzing BDG > 150 pg/mL along with Candida score > 2 and Charlson score > 4, the strength of the association amongst BDG, clinical scores and development of candidemia is increased. The overall clinical evaluation with the help of scores that consider BDG values > 150 pg/mL, Candida score > 2 and Charlson score > 4 in combination seems to predict better the need of antifungal empiric treatment.
Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI
Authors: di Noia Christian , Grist James T. , Riemer Frank , Lyasheva Maria , Fabozzi Miriana , Castelli Mauro , Lodi Raffaele , Tonon Caterina , Rundo Leonardo , Zaccagna Fulvio
Published: September 2022

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.
Epithelial–Mesenchymal Transition by Synergy between Transforming Growth Factor-β and Growth Factors in Cancer Progression
Authors: Saitoh Masao
Published: September 2022

Epithelial–mesenchymal transition (EMT) plays a crucial role in appropriate embryonic development, as well as wound healing, organ fibrosis, and cancer progression. During cancer progression, EMT is associated with the invasion, metastasis, and generation of circulating tumor cells and cancer stem cells, as well as resistance to chemo- and radiation therapy. EMT is induced by several transcription factors, known as EMT transcription factors (EMT-TFs). In nearly all cases, EMT-TFs appear to be regulated by growth factors or cytokines and extracellular matrix components. Among these factors, transforming growth factor (TGF)-β acts as the key mediator for EMT during physiological and pathological processes. TGF-β can initiate and maintain EMT by activating intracellular/intercellular signaling pathways and transcriptional factors. Recent studies have provided new insights into the molecular mechanisms underlying sustained EMT in aggressive cancer cells, EMT induced by TGF-β, and crosstalk between TGF-β and growth factors.
Dental Caries Risk Assessment in Children 5 Years Old and under via Machine Learning
Authors: Sadegh-Zadeh Seyed-Ali , Rahmani Qeranqayeh Ali , Benkhalifa Elhadj , Dyke David , Taylor Lynda , Bagheri Mahshid
Published: September 2022

Background: Dental caries is a prevalent, complex, chronic illness that is avoidable. Better dental health outcomes are achieved as a result of accurate and early caries risk prediction in children, which also helps to avoid additional expenses and repercussions. In recent years, artificial intelligence (AI) has been employed in the medical field to aid in the diagnosis and treatment of medical diseases. This technology is a critical tool for the early prediction of the risk of developing caries. Aim: Through the development of computational models and the use of machine learning classification techniques, we investigated the potential for dental caries factors and lifestyle among children under the age of five. Design: A total of 780 parents and their children under the age of five made up the sample. To build a classification model with high accuracy to predict caries risk in 0–5-year-old children, ten different machine learning modelling techniques (DT, XGBoost, KNN, LR, MLP, RF, SVM (linear, rbf, poly, sigmoid)) and two assessment methods (Leave-One-Out and K-fold) were utilised. The best classification model for caries risk prediction was chosen by analysing each classification model’s accuracy, specificity, and sensitivity. Results: Machine learning helped with the creation of computer algorithms that could take a variety of parameters into account, as well as the identification of risk factors for childhood caries. The performance of the classifier is almost unbiased, making it generalizable. Among all applied machine learning algorithms, Multilayer Perceptron and Random Forest had the best accuracy, with 97.4%. Support Vector Machine with RBF Kernel (with an accuracy of 97.4%) was better than Extreme Gradient Boosting (with 94.9% accuracy). Conclusion: The outcomes of this study show the potential of regular screening of children for caries risk by experts and finding the risk scores of dental caries for any individual. Therefore, in order to avoid dental caries, it is possible to concentrate on each individual by utilizing machine learning modelling.
A Realization Approach to Lossy Network Compression of a Tuple of Correlated Multivariate Gaussian RVs
Authors: Charalambous Charalambos D. , van Schuppen Jan H.
Published: September 2022

Examined in this paper is the Gray and Wyner source coding for a simple network of correlated multivariate Gaussian random variables, Y1:Ω→Rp1 and Y2:Ω→Rp2. The network consists of an encoder that produces two private rates R1 and R2, and a common rate R0, and two decoders, where decoder 1 receives rates (R1,R0) and reproduces Y1 by Y^1, and decoder 2 receives rates (R2,R0) and reproduces Y2 by Y^2, with mean-square error distortions E||Yi−Y^i||Rpi2≤Δi∈[0,∞],i=1,2. Use is made of the weak stochastic realization and the geometric approach of such random variables to derive test channel distributions, which characterize the rates that lie on the Gray and Wyner rate region. Specific new results include: (1) A proof that, among all continuous or finite-valued random variables, W:Ω→W, Wyner’s common information, C(Y1,Y2)=infPY1,Y2,W:PY1,Y2|W=PY1|WPY2|WI(Y1,Y2;W), is achieved by a Gaussian random variable, W:Ω→Rn of minimum dimension n, which makes the two components of the tuple (Y1,Y2) conditionally independent according to the weak stochastic realization of (Y1,Y2), and a the formula C(Y1,Y2)=12∑j=1nln1+dj1−dj, where di∈(0,1),i=1,…,n are the canonical correlation coefficients of the correlated parts of Y1 and Y2, and a realization of (Y1,Y2,W) which achieves this. (2) The parameterization of rates that lie on the Gray and Wyner rate region, and several of its subsets. The discussion is largely self-contained and proceeds from first principles, while connections to prior literature is discussed.
Generic Structure Extraction with Bi-Level Optimization for Graph Structure Learning
Authors: Yin Nan , Luo Zhigang
Published: September 2022

Currently, most Graph Structure Learning (GSL) methods, as a means of learning graph structure, improve the robustness of GNN merely from a local view by considering the local information related to each edge and indiscriminately applying the mechanism across edges, which may suffer from the local structure heterogeneity of the graph (i.e., the uneven distribution of inter-class connections over nodes). To overcome the drawbacks, we extract the graph structure as a learnable parameter and jointly learn the structure and common parameters of GNN from the global view. Excitingly, the common parameters contain the global information for nodes features mapping, which is also crucial for structure optimization (i.e., optimizing the structure relies on global mapping information). Mathematically, we apply a generic structure extractor to abstract the graph structure and transform GNNs in the form of learning structure and common parameters. Then, we model the learning process as a novel bi-level optimization, i.e., Generic Structure Extraction with Bi-level Optimization for Graph Structure Learning (GSEBO), which optimizes GNN parameters in the upper level to obtain the global mapping information and graph structure is optimized in the lower level with the global information learned from the upper level. We instantiate the proposed GSEBO on classical GNNs and compare it with the state-of-the-art GSL methods. Extensive experiments validate the effectiveness of the proposed GSEBO on four real-world datasets.
Implementation and Review of the Axisymmetric Equilibrium System of RFX-Mod2 within the MARTe2 Framework
Authors: Ferron Nicolò , Finotti Claudio , Manduchi Gabriele , Marchiori Giuseppe , Bettini Paolo , Abate Domenico , Cavazzana Roberto
Published: September 2022

A major refurbishment of the toroidal complex of the RFX-mod device is in progress and it will include the removal of the Inconel vacuum vessel and a modification of the stainless steel supporting structure to be made vacuum-tight. The axisymmetric equilibrium control in RFX-mod was responsible for the control of the plasma current, horizontal and vertical position along with its stability and the plasma shape. The new implementation framework, both hardware and software, is described. The system has been fully reviewed and modified, if needed, for its prospective use in RFX-mod2. In order to run tests in an operation-like context, the updated system has also been implemented in the MARTe2 framework, to be deployed for the real-time applications of RFX-mod2. The results of the previous versions were reproduced and the cycle-time requirements were met.
A Fuzzy-Logic-Based Load Balancing Scheme for a Satellite–Terrestrial Integrated Network
Authors: Gao Yuehong , Yang Haotian , Wang Xiaoqi , Chen Yihao , Li Chenyang , Zhang Xin
Published: September 2022

With the development of communication systems, users are becoming more widely distributed and require higher speed networks. A satellite–terrestrial integrated network could provide seamless coverage for these users. In previous studies of load balancing, initial access and load balancing are decided on based on signal reception and are performed reactively after the overloading occurs, which may not work well in satellite–terrestrial integrated networks. Therefore, this paper proposes a fuzzy-logic-based load balancing scheme. In this scheme, a fuzzy evaluation metric to pre-evaluate the user’s impact on overload is presented. The fuzzy logic system is constructed based on adaptive neuro fuzzy system, which takes the user’s signal reception, speed and data requirement as inputs. Then, the fuzzy-logic- and reinforcement-learning-based access is proposed to give an access decision for all users in the network to prevent overloading. Due to the large dimensions of action space, the reinforcement learning model is trained by the proposed fuzzy, deep, deterministic policy gradient. Next, the fuzzy-logic-based offloading algorithm is proposed to balance load after overloading. A simulation platform is established to evaluate the performance. Simulation results indicate that the proposed scheme can ensure load balance for a longer time than base line schemes while ensuring data rate of users.
Practical Use of Secret Sharing for Enhancing Privacy in Clouds
Authors: Čuřík Peter , Ploszek Roderik , Zajac Pavol
Published: September 2022

The topic of this contribution is the practical use of secret sharing schemes in securing private data. In the first part, we focus on the security model and the overview of the available solutions. In the second part, we describe our solution for storing sensitive data in commercial cloud storage systems, an application called Datachest. The application uploads the data in encrypted form. Cryptographic keys are divided into shares. Each cloud receives one share. This solution improves the security of users’ sensitive data in the cloud. In the final part, we explore the ramifications of secret sharing on the security and management of IoT devices, especially home appliances.
Static and Dynamic Magnetic Properties of Polycrystalline Hexaferrites of the Ba2Ni2-xCuxFe12O22 System
Authors: Zhuravlev Victor A. , Wagner Dmitry V. , Dotsenko Olga A. , Kareva Katerina V. , Zhuravlyova Elena V. , Chervinskaya Anna S. , Kuleshov Grigoriy E. , Suraev Alexander S.
Published: September 2022

The paper presents the results of a study of the phase composition and the main static magnetic characteristics: saturation magnetization, residual magnetization and coercive force of polycrystalline ferroxplana type hexaferrites of the Ba2Ni2-xCuxFe12O22 (0 ≤ x ≤ 2.0) system. These materials have high magnetic permeability and are promising for use as substrates for magnetic antennas and radar absorbing materials. It is shown that thermograms of the initial permeability can be used to quickly assess the presence of impurity magnetic phases in complex oxide ferrimagnets. The permeability and permittivity spectra of textured and non-textured composite samples with the powder of the Ba2NiCuFe12O22 hexaferrite are measured in the microwave frequency range. The radar absorbing properties of the obtained composites are analyzed. It is shown that magnetic texturing leads to an increase in the operating frequency band of an absorber with RL < −10 dB from 6.1 GHz to 8.2 GHz and a deepening of the loss minimum from −21 dB to −27 dB.
An Improved Method for the Inversion of Backscatter Ionograms by Using Neighborhood-Aided and Multistep Fitting
Authors: Lei Zhenshuo , Chen Hui , Zhang Zhaojian , Dou Gaoqi , Wang Yongliang
Published: September 2022

To solve the problem that a parameter search easily falls into a local optimum and the two-dimensional electron density profile construction error is large in the process of backscatter ionogram inversion, an improved method using neighborhood-aided and multistep fitting is proposed. The ionospheric parameter inversion results in the adjacent space are combined and reconstructed by using the neighborhood-aided correction method. The introduction of auxiliary information sources addresses the defects of the conventional genetic algorithm. The local region multistep fitting method is used to describe the local uniformity and global inhomogeneity of the two-dimensional electron density profile by dividing the fitting region. The experimental results show that the proposed method can improve the accuracy of backscatter ionogram inversion and provide reliable support for tracking radio ray trajectories.
Automatic Determination of Rock-Breaking Target Poses for Impact Hammers
Authors: Cárdenas Daniel , Parra-Tsunekawa Isao , Leiva Francisco , Ruiz-del-Solar Javier
Published: September 2022

This paper describes a system for the automatic determination of rock-breaking target poses for impact hammers used in underground mines. The rock-breaking target pose is defined as the position and angle at which the impact hammer must strike a rock in order to break it. The automatic determination of this pose is essential for the autonomous operation of an impact hammer. The proposed system takes as input sensor data composed of point clouds and images, and automatically determines a rock-breaking target pose. The system consists of a rock segmentation subsystem that receives the sensor data and identifies and individualizes the rocks/boulders present above the grizzly, and a rock-breaking target pose generation and evaluation subsystem that receives the rock information produced by the rock segmentation subsystem, and generates a list of rock-breaking target pose candidates, it evaluates them, and it selects the best candidate as the rock-breaking target pose. The system is evaluated using real data. The reported experiments show the system’s capability to generate appropriate target poses.
A Novel Hardware-in-the-Loop Approach to Investigate the Impact of Low System Inertia on RoCoF Relay Settings
Authors: Imris Peter , Taylor Gareth A. , Bradley Martin E. , Li Yun
Published: September 2022

This paper presents a novel hardware-in-the-loop (HIL) approach as used to investigate the impact of the reduction in inertia on the Great Britain (GB) electrical power system with regard to rate of change of frequency (RoCoF) settings for Loss-of-Mains (LoM) protection. Furthermore, the research as presented in this paper updates, enhances, and validates a reduced model of the Great Britain transmission system, as originally developed in DIgSILENT PowerFactory by the National Grid Electricity System Operator. The enhanced model has been developed for integrated use with the OPAL-RT real-time HIL simulation toolkit and is validated against phasor measurement unit (PMU) data from actual disturbance events using novel automated interfacing between both integrated simulation platforms, PowerFactory from DIgSILENT and ePHASORSIM from OPAL-RT. The corresponding simulations show that the updated reduced model is capable of capturing the dynamic behaviour of the GB transmission system, including both local and inter-area oscillations, with satisfactory accuracy. Finally, the paper presents HIL study results with the reduced model to investigate the influence of decreasing system inertia on the response of LoM protection relays. The studies show that decreasing system inertia may have a significant impact on LoM relays using RoCoF detection, particularly relays using the legacy G59 setting of 0.125 Hz/s. Initial studies have also demonstrated the potential for a previously unrecognised interaction between system oscillations and the 500 ms operating delay, as specified in G59 and G99 Engineering Recommendations. Consequently, faster local oscillations (>1 Hz) reset the relay and decrease the sensitivity, whereas slower inter-area oscillations (<1 Hz) appear to cause the relay to overestimate the average RoCoF.
Recent Developments in Electrical Machine Design for the Electrification of Industrial and Transportation Systems
Authors: Fernandes João F. P. , Bhagubai Pedro P. C. , Branco Paulo J. C.
Published: September 2022

The electrification of the industrial and transportation systems has been an important path toward mitigating climate change [...]
A Discrete Current Controller for High Power-Density Synchronous Machines
Authors: Ma Hongtai , Li Li , Fan Yingpeng , Guo Youguang , Jin Zhihui , Luo Jian
Published: September 2022

This paper proposes a complex vector discrete current controller based on the flux-linkage data to solve the current loop oscillation problem of high power-density synchronous machines. An offline flux-linkage table measurement method considering cross saturation is introduced, and the data are used to deduce the symmetrical complex vector model. The influence of latch and delay of inverters on the line voltage of machines at high speed is analyzed and compensated during the controller design process. The proposed controller, which only needs to tune one parameter, can deal with the inductance mismatch issues caused by iron core saturation. The controller can be adopted in the current loop of saturated salient or nonsalient synchronous machines. Simulations and experiments have verified the effectiveness of the proposed method.
The Standard Geothermal Plant as an Innovative Combined Renewable Energy Resources System: The Case from South Poland
Authors: Operacz Agnieszka , Zachora-Buławska Agnieszka , Strzelecka Izabela , Buda Mariusz , Bielec Bogusław , Migdał Karolina , Operacz Tomasz
Published: September 2022

Geothermal energy, as one of the more well-known renewable energy sources (RES), is used in many operating installations around the world. Depending on the temperature of the geothermal waters in question, the choices range from installations for generating electricity (high-temperature geothermal energy), to the production of thermal energy for use in recreational complexes, to fish farming (low-temperature geothermal energy). Lindal’s diagram determines the possibilities of using warm groundwater for many investment projects. In light of the drive to avoid climate change, it seems that the conventional “one-way” use of geothermal water resources is insufficient. Therefore, this article presents an optimal innovative solution wherein geothermal water is fully utilized in a geothermal cogeneration installation to produce heat and electricity and to provide cooling. In addition, it was proposed to expand the investment with photovoltaic and hydropower plants to ensure greater energy independence by diversifying energy sources and increasing the share of energy supplies based on renewable energy sources. Such a broad approach allows for the implementation of a sustainable development strategy in the field of environmental protection. The proposed solution involves the modernization and expansion of the existing energy generation sources by a heating plant and a geothermal power plant in Chochołowskie Termy (South Poland), as well as the construction of a power plant based on a photovoltaic installation, hydropower setup, and energy storage. The presented innovative solution may be an excellent example of implementation for similar geothermal facilities in the world. The novelty of the system is the approach of assessing and combining the different RES in one project, based on a geothermal plant. Popularizing this solution in the wider scientific environment may have a real impact in terms of the reduction of pollutant emissions.
Perovskite Solar Cells
Authors: Roose Bart
Published: September 2022

Solar energy is set to play a big role in future energy generation and achieving climate change goals [...]
Climbing the Effluent Filtration Tree: Modelling, Mechanisms & Applications—A Monograph
Authors: Adin Avner
Published: September 2022

Particle filtration is a major building block in effluent treatment facilities for water reuse in agriculture, industry, and the community. Yet, its incorporation in modern hybrid treatment systems still lacks basic know-how for process optimization. This paper aims to provide a profound understanding of particle filtration vis-à-vis its various reuse applications. The methodology used follows a road map depicted as a growing tree, representing the author’s research from roots to top: roots—basic modeling, mechanisms; tree trunk—filter design approach for reuse; branches—enhanced particle removal; and tree crown—pretreatment, bioparticle, and nanoparticle removal. Contact deep-bed filtration process optimization, algorithms for economically optimal filter design, tertiary filtration and membrane pretreatment, and related energy issues are being discussed. Some of the conclusions are that pilot plant planning should be primarily derived from particle surface interactions with filter media, based on measurements of mineral particle or bioparticle size, shape, and physicochemical characteristics, and applying attachment-detachment models. Filter design optimization would comprise of selecting efficient water quality processes first, followed by economic optimization for final design parameters. A holistic approach in the design of filtration facilities, standing alone or incorporated in hybrid systems, is also considered.