bluuebunny/crossref_metadata_2025 huggingface dataset:
AI-Based Quantification of Fitness Activities Using Smartphones
Authors: Huang Junhui , Kaewunruen Sakdirat , Ning Jingzhiyuan
Published: January 2022

To encourage more active activities that have the potential to significantly reduce the risk of people’s health, we aim to develop an AI-based mobile app to identify four gym activities accurately: ascending, cycling, elliptical, and running. To save computational cost, the present study deals with the dilemma of the performance provided by only a phone-based accelerometer since a wide range of activity recognition projects used more than one sensor. To attain this goal, we derived 1200 min of on-body data from 10 subjects using their phone-based accelerometers. Subsequently, three subtasks have been performed to optimize the performances of the K-nearest neighbors (KNN), Support Vector Machine (SVM), Shallow Neural Network (SNN), and Deep Neural Network (DNN): (1) During the process of the raw data converted to a 38-handcrafted feature dataset, different window sizes are used, and a comparative analysis is conducted to identify the optimal one; (2) principal component analysis (PCA) is adopted to extract the most dominant information from the 38-feature dataset described to a simpler and smaller size representation providing the benefit of ease of interpreting leading to high accuracy for the models; (3) with the optimal window size and the transformed dataset, the hyper-parameters of each model are tuned to optimal inferring that DNN outperforms the rest three with a testing accuracy of 0.974. This development can be further implemented in Apps Store to enhance public usage so that active physical human activities can be promoted to enhance good health and wellbeing in accordance with United Nation’s sustainable development goals.
Estimating the Spatial Heterogeneity and Seasonal Differences of the Contribution of Tourism Industry Activities to Night Light Index by POI
Authors: Wei Juan , Zhong Yongde , Fan Jingling
Published: January 2022

The spatial distribution of tourism has a profound impact on its operational efficiency and geographical relevance. Point of interest (POI), as a kind of spatial data shared by subject and object, can reflect the spatial distribution form and function of tourism geographical objects under the all-for-one tourism policy. Continuous satellite observation and in-depth study of night lights pave the way to clarify human activities and socio-economic dynamics. The purpose of this paper is to investigate the seasonal changes of night light images and their correlation with tourism in 122 counties (cities, districts) of Hunan Province. We obtained night earth observation data (seasonality) and POI in 2019 and processed them by Geographic Information System and statistical analysis (ordinary least squares (OLS) and geographically weighted regression (GWR)). The results show that the luminous radiation intensity is highly correlated with the POI of tourism activities. The POI of different tourism activities in different regions shows obvious spatial heterogeneity and seasonal differences, which is the result of the comprehensive effect of tourism resource distribution and social environment in Hunan Province. GWR has proved to be a more effective tool. It provides a new method and perspective for tourism research and especially reveals the geographical spatial differences of tourism activities, which is helpful to study the spatial distribution and seasonality of tourism at the county level. In addition, the spatial evaluation of the contribution of tourism and luminous radiation can provide reference and suggestions for relevant departments to formulate tourism night protection measures.
The Analysis of Spatial Patterns and Significant Factors Associated with Young-Driver-Involved Crashes in Florida
Authors: Koloushani Mohammadreza , Ghorbanzadeh Mahyar , Ulak Mehmet Baran , Ozguven Eren Erman , Horner Mark W. , Vanli Omer Arda
Published: January 2022

Over the last three decades, traffic crashes have been one of the leading causes of fatalities and economic losses in the U.S.; compared with other age groups, this is especially concerning for the youth population (those aged between 16 and 24), mostly due to their inexperience, greater inattentiveness, and riskier behavior while driving. This research intends to investigate this issue around selected Florida university campuses. We employed three methods: (1) a comparative assessment for three selected counties using both planar Euclidean Distance and Roadway Network Distance-based Kernel Density Estimation methods to determine high-risk crash locations, (2) a crash density ratio difference approach to compare the maxima-normalized crash densities for the youth population and those victims that are 25 and up, and (3) a logistic regression approach to identify the statistically significant factors contributing to young-driver-involved crashes. The developed GIS maps illustrate the difference in spatial patterns of young-driver crash densities compared to those for other age groups. The statistical findings also reveal that intersections around university areas appear to be significantly problematic for youth populations, regardless of the differences in the general perspective of the characteristics of the selected counties. Moreover, the speed limit countermeasures around universities could not effectively prevent young-driver crash occurrences. Hence, the results of this study can provide valuable insights to transportation agencies in terms of pinpointing the high-risk locations around universities, assessing the effectiveness of existing safety countermeasures, and developing more reliable plans with a focus on the youth population.
Ecological Security Pattern Construction in Beijing-Tianjin-Hebei Region Based on Hotspots of Multiple Ecosystem Services
Authors: Wang Sheng , Li Wenjing , Li Qing , Wang Jinfeng
Published: January 2022

The contradiction between urban expansion and ecological protection in the Beijing-Tianjin-Hebei region (BTH) is increasingly acute, which has become one of the main problems restricting regional development, and sustainable development of ecosystem services is the key to increasing human well-being. Based on GIS platform and multiple models, this paper analyzes the temporal and spatial variation characteristics of four key ecosystem services (water conservation, soil conservation, habitat quality, and plant net primary productivity) in different ecological regions of BTH in recent 20 years, quantifies the impact of different climate factors and land use change on ecosystem services (ESs), and discusses the primary ecosystem hotspots and ecological security pattern. The results showed that the interannual variation of water conservation (WC) and plant net primary productivity (NPP) increased from 2000 to 2020, while the change of soil conservation (SC) was not obvious, which was mainly controlled by climate factors, WC and SC were more affected by precipitation, and temperature was the key factor affecting NPP. Habitat quality (HQ) presented a significant downward trend; it was mainly attributed to the deterioration of ecological environment caused by accelerated urbanization expansion. According to hotspot analysis, it could be found that WC was the fastest-growing ecosystem service function in BTH, and NPP would become the factor with the greatest contribution to ecological importance in the future. The important protected areas and main ecological sources of ecological security pattern were mainly distributed in Yanshan-Taihang mountain area, which was consistent with the key areas of ecosystem services. In this study, the temporal and spatial differences of ecosystem service in BTH were demonstrated in a more intuitive way and provided scientific guidance for decision makers to formulate effective ecological protection policies in different regions.
Challenging Novelties within the Circular Economy Concept under the Digital Transformation of Society
Authors: Ilić Milena P. , Ranković Marko , Dobrilović Milutin , Bucea-Manea-Țoniş Rocsana , Mihoreanu Larisa , Gheța Mădălina Ionela , Simion Violeta-Elena
Published: January 2022

The study makes, under a new configuration of the circular economy, a cross-country analysis based on the Competitiveness and Innovation Indicators in the E.U., i.e., two sub-criteria: private investments, jobs, and gross value added; and patents related to recycling and secondary raw materials as a proxy for innovation. The analysis proved that investments influence the number of patents, and participate in societal transformation. A further cluster analysis classified countries on the level of innovation. The cluster analysis in SPSS centres on significant potential, weaknesses, impact, and waste management control through blockchain technology. It is found that the factors that influence innovation, according to the Global Competitiveness Report, link the business dynamism and innovation capability with the capacity to sustain resilient ideas, such as competitive intelligence and social entrepreneurship. The discussions aim to prove that the efforts to rethink the circular economy principles contribute to its conceptual and societal transformation role through the implementation of innovative processes, inventive solutions, and blockchain technologies, and their social consequences to solve environmental problems. Once understood and accepted, CE will drive sustainable behaviour.
Margin Trading Program, External Profit Pressure and Enterprise Financialization—A Quasi-Natural Experiment Based on Double Difference Model
Authors: Gao Shuiwen , Gu Haifeng , Halepoto Habiba
Published: January 2022

Based on the urgent need of the real economy to “get away from fictitious to substantial”, this paper constructs a quasi-natural experiment based on the margin trading program gradually implemented in China in 2010 and studies the influence of the margin trading program on the financialization level of the target company by using the difference-in-difference method. The results show that, because of the dominant role of financing transactions in margin trading programs in China’s capital market, financing transactions drive up the share prices of listed companies, which leads to an excessive easing of the financing constraints of listed companies and short-sighted behavior of executives, which has a significant role in promoting enterprise financialization. Moreover, the driving effect is more significant in state-owned enterprises, enterprises with a high degree of financing constraint, and enterprises with a low degree of marketization. Economic policy uncertainty will restrain the positive effect of margin trading programs on enterprise financialization through information and governance mechanisms. In contrast, the “branding” effect caused by the financial connection of senior executives will intensify the positive relationship between margin trading programs on enterprise financialization levels. When considering the intermediary effect, we find that the margin trading program will result in the optimistic deviation of analysts’ earnings forecasts and cause the external profit pressure of enterprises, thus increasing the financialization trend. This study is of great theoretical significance and practical value for evaluating the policy effect of the margin trading program, improving this policy, investigating the influencing factors of enterprise financialization, and promoting the real economy to move from fictitious to substantial.
Seismic Performance of Hybrid Corrosion-Free Self-Centering Concrete Shear Walls
Authors: Abraik Emad , Youssef Maged A. , El-Fitiany Salah F.
Published: January 2022

Reinforced concrete (RC) walls are extensively used in high-rise buildings to resist lateral loads, while ensuring an adequate level of ductility. Durability problems, including corrosion of conventional steel reinforcements, necessitate exploring alternative types of reinforcement. The use of glass fiber reinforced polymer (FRP) bars is a potential solution. However, these bars cannot be used in seismic applications because of their brittleness and inability to dissipate seismic energy. Superelastic shape memory alloy (SMA) is a corrosion-free material with high ductility and unique self-centering ability. Its high cost is a major barrier to use in construction projects. The clear advantage of utilizing both SMA and FRP to achieve durable self-centering structures has motivated the development of a composite SMA-FRP bar. This paper investigates the hybrid use of FRP bars and either SMA bars or composite SMA-FRP in concrete shear walls. An extensive parametric study was conducted to study the effect of different design parameters on the lateral performance of hybrid RC walls. The seismic behavior of the hybrid walls was then examined. The hybrid walls not only solved the durability problem but also significantly improved the seismic performance.
On Modified Second Paine–de Hoog–Anderssen Boundary Value Problem
Authors: Karjanto Natanael
Published: January 2022

This article deals with a special case of the Sturm–Liouville boundary value problem (BVP), an eigenvalue problem characterized by the Sturm–Liouville differential operator with unknown spectra and the associated eigenfunctions. By examining the BVP in the Schrödinger form, we are interested in the problem where the corresponding invariant function takes the form of a reciprocal quadratic form. We call this BVP the modified second Paine–de Hoog–Anderssen (PdHA) problem. We estimate the lowest-order eigenvalue without solving the eigenvalue problem but by utilizing the localized landscape and effective potential functions instead. While for particular combinations of parameter values that the spectrum estimates exhibit a poor quality, the outcomes are generally acceptable although they overestimate the numerical computations. Qualitatively, the eigenvalue estimate is strikingly excellent, and the proposal can be adopted to other BVPs.
Clustering with Missing Features: A Density-Based Approach
Authors: Gao Kun , Khan Hassan Ali , Qu Wenwen
Published: January 2022

Density clustering has been widely used in many research disciplines to determine the structure of real-world datasets. Existing density clustering algorithms only work well on complete datasets. In real-world datasets, however, there may be missing feature values due to technical limitations. Many imputation methods used for density clustering cause the aggregation phenomenon. To solve this problem, a two-stage novel density peak clustering approach with missing features is proposed: First, the density peak clustering algorithm is used for the data with complete features, while the labeled core points that can represent the whole data distribution are used to train the classifier. Second, we calculate a symmetrical FWPD distance matrix for incomplete data points, then the incomplete data are imputed by the symmetrical FWPD distance matrix and classified by the classifier. The experimental results show that the proposed approach performs well on both synthetic datasets and real datasets.
Memristive Structure-Based Chaotic System for PRNG
Authors: Haliuk Serhii , Krulikovskyi Oleh , Vovchuk Dmytro , Corinto Fernando
Published: January 2022

This paper suggests an approach to generate pseudo-random sequences based on the discrete-time model of the simple memristive chaotic system. We show that implementing Euler’s and Runge–Kutta’s methods for the simulation solutions gives the possibility of obtaining chaotic sequences that maintain general properties of the original chaotic system. A preliminary criterion based on the binary sequence balance estimation is proposed and applied to separate any binary representation of the chaotic time sequences into random and non-random parts. This gives us the possibility to delete obviously non-random sequences prior to the post-processing. The investigations were performed for arithmetic with both fixed and floating points. In both cases, the obtained sequences successfully passed the NIST SP 800-22 statistical tests. The utilization of the unidirectional asymmetric coupling of chaotic systems without full synchronization between them was suggested to increase the performance of the chaotic pseudo-random number generator (CPRNG) and avoid identical sequences on different outputs of the coupled systems. The proposed CPRNG was also implemented and tested on FPGA using Euler’s method and fixed-point arithmetic for possible usage in different applications. The FPGA implementation of CPRNG supports a generation speed up to 1.2 Gbits/s for a clock frequency of 50 MHz. In addition, we presented an example of the application of CPRNG to symmetric image encryption, but nevertheless, one is suitable for the encryption of any binary source.
The Precision of the Human Hand: Variability in Pinch Strength and Manual Dexterity
Authors: Bardo Ameline , Town Katie , Kivell Tracy L. , Donati Georgina , Ballieux Haiko , Stamate Cosmin , Edginton Trudi , Forrester Gillian S.
Published: January 2022

Changes in hand morphology throughout human evolution have facilitated the use of forceful pad-to-pad precision grips, contributing to the development of fine motor movement and dexterous manipulation typical of modern humans. Today, variation in human hand function may be affected by demographic and/or lifestyle factors, but these remain largely unexplored. We measured pinch grip strength and dexterity in a heterogeneous cross-sectional sample of human participants (n = 556) to test for the potential effects of sex, age, hand asymmetries, hand morphology, and frequently practiced manual activities across the lifespan. We found a significant effect of sex on pinch strength, dexterity, and different directional asymmetries, with the practice of manual musical instruments, significantly increasing female dexterity for both hands. Males and females with wider hands were also stronger, but not more precise, than those with longer hands, while the thumb-index ratio had no effect. Hand dominance asymmetry further had a significant effect on dexterity but not on pinch strength. These results indicate that different patterns of hand asymmetries and hand function are influenced in part by life experiences, improving our understanding of the link between hand form and function and offering a referential context for interpreting the evolution of human dexterity.
Counting Non-Convex 5-Holes in a Planar Point Set
Authors: Sung Young-Hun , Bae Sang Won
Published: January 2022

Let S be a set of n points in the general position, that is, no three points in S are collinear. A simple k-gon with all corners in S such that its interior avoids any point of S is called a k-hole. In this paper, we present the first algorithm that counts the number of non-convex 5-holes in S. To our best knowledge, prior to this work there was no known algorithm in the literature except a trivial brute force algorithm. Our algorithm runs in time O(T+Q), where T denotes the number of 3-holes, or empty triangles, in S and Q that denotes the number of non-convex 4-holes in S. Note that T+Q ranges from Ω(n2) to O(n3), while its expected number is Θ(n2logn) when the points in S are chosen uniformly and independently at random from a convex and bounded body in the plane.
Homochiral or Heterochiral: A Systematic Study of Threonine Clusters Using a FT ICR Mass Spectrometer
Authors: Jiao Luyang , Du Mengying , Hou Yameng , Ma Yuan , Kong Xianglei
Published: January 2022

The strong chiral preferences of some magic clusters of amino acids have attracted continually increasing interests due to their unique structures, properties and possible roles in homochirogenesis. However, how chirality can influence the generation and stability of cluster ions in a wild range of cluster sizes is still unknown for most amino acids. In this study, the preference for threonine clusters to form homochiral and heterochiral complex ions has been investigated by electrospray ionization (ESI) mass spectrometry. Abundant cluster [Thrn+mH]m+ ions (7 ≤ n ≤ 78, 1 ≤ m ≤ 5) have been observed for both samples of enantiopure (100% L) and racemic (50:50 L:D) threonine solutions. Further analyses of the spectra show that the [Thr14+2H]2+ ion is characterized by its most outstanding homochiral preference, and [Thr7+H]+ and [Thr8+H]+ ions also clearly exhibit their homochiral preferences. Although most of the triply charged clusters (20 ≤ n ≤ 36) are characterized by heterochiral preferences, the quadruply charged [Thrn+4H]4+ ions (40 ≤ n ≤ 59) have no obvious chiral preference in general. On the other hand, a weak homochiral preference exists for most of the quintuply charged ions observed in the experiment.
Prediction of Protein Secondary Structure Based on WS-BiLSTM Model
Authors: Gao Yang , Zhao Yawu , Ma Yuming , Liu Yihui
Published: January 2022

Protein secondary structure prediction is an important topic in bioinformatics. This paper proposed a novel model named WS-BiLSTM, which combined the wavelet scattering convolutional network and the long-short-term memory network for the first time to predict protein secondary structure. This model captures nonlocal interactions between amino acid sequences and remembers long-range interactions between amino acids. In our WS-BiLSTM model, the wavelet scattering convolutional network is used to extract protein features from the PSSM sliding window; the extracted features are combined with the original PSSM data as the input features of the long-short-term memory network to predict protein secondary structure. It is worth noting that the wavelet scattering convolutional network is asymmetric as a member of the continuous wavelet family. The Q3 accuracy on the test set CASP9, CASP10, CASP11, CASP12, CB513, and PDB25 reached 85.26%, 85.84%, 84.91%, 85.13%, 86.10%, and 85.52%, which were higher 2.15%, 2.16%, 3.5%, 3.19%, 4.22%, and 2.75%, respectively, than using the long-short-term memory network alone. Comparing our results with the state-of-art methods shows that our proposed model achieved better results on the CB513 and CASP12 data sets. The experimental results show that the features extracted from the wavelet scattering convolutional network can effectively improve the accuracy of protein secondary structure prediction.
A 3D Agent-Based Model of Lung Fibrosis
Authors: Cogno Nicolò , Bauer Roman , Durante Marco
Published: January 2022

Understanding the pathophysiology of lung fibrosis is of paramount importance to elaborate targeted and effective therapies. As it onsets, the randomly accumulating extracellular matrix (ECM) breaks the symmetry of the branching lung structure. Interestingly, similar pathways have been reported for both idiopathic pulmonary fibrosis and radiation-induced lung fibrosis (RILF). Individuals suffering from the disease, the worldwide incidence of which is growing, have poor prognosis and a short mean survival time. In this context, mathematical and computational models have the potential to shed light on key underlying pathological mechanisms, shorten the time needed for clinical trials, parallelize hypotheses testing, and improve personalized drug development. Agent-based modeling (ABM) has proven to be a reliable and versatile simulation tool, whose features make it a good candidate for recapitulating emergent behaviors in heterogeneous systems, such as those found at multiple scales in the human body. In this paper, we detail the implementation of a 3D agent-based model of lung fibrosis using a novel simulation platform, namely, BioDynaMo, and prove that it can qualitatively and quantitatively reproduce published results. Furthermore, we provide additional insights on late-fibrosis patterns through ECM density distribution histograms. The model recapitulates key intercellular mechanisms, while cell numbers and types are embodied by alveolar segments that act as agents and are spatially arranged by a custom algorithm. Finally, our model may hold potential for future applications in the context of lung disorders, ranging from RILF (by implementing radiation-induced cell damage mechanisms) to COVID-19 and inflammatory diseases (such as asthma or chronic obstructive pulmonary disease).
A Quadruple Integral Involving Chebyshev Polynomials Tn(x): Derivation and Evaluation
Authors: Reynolds Robert , Stauffer Allan
Published: January 2022

The aim of the current document is to evaluate a quadruple integral involving the Chebyshev polynomial of the first kind Tn(x) and derive in terms of the Hurwitz-Lerch zeta function. Special cases are evaluated in terms of fundamental constants. The zero distribution of almost all Hurwitz-Lerch zeta functions is asymmetrical. All the results in this work are new.
Exploiting User Friendship Networks for User Identification across Social Networks
Authors: Qu Yating , Xing Ling , Ma Huahong , Wu Honghai , Zhang Kun , Deng Kaikai
Published: January 2022

Identifying offline entities corresponding to multiple virtual accounts of users across social networks is crucial for the development of related fields, such as user recommendation system, network security, and user behavior pattern analysis. The data generated by users on multiple social networks has similarities. Thus, the concept of symmetry can be used to analyze user-generated information for user identification. In this paper, we propose a friendship networks-based user identification across social networks algorithm (FNUI), which performs the similarity of multi-hop neighbor nodes of a user to characterize the information redundancy in the friend networks fully. Subsequently, a gradient descent algorithm is used to optimize the contribution of the user’s multi-hop nodes in the user identification process. Ultimately, user identification is achieved in conjunction with the Gale–Shapley matching algorithm. Experimental results show that compared with baselines, such as friend relationship-based user identification (FRUI) and friendship learning-based user identification (FBI): (1) The contribution of single-hop neighbor nodes in the user identification process is higher than other multi-hop neighbor nodes; (2) The redundancy of information contained in multi-hop neighbor nodes has a more significant impact on user identification; (3) The precision rate, recall rate, comprehensive evaluation index (F1), and area under curve (AUC) of user identification have been improved.
Cosmoparticle Physics of Dark Universe
Authors: Khlopov Maxim
Published: January 2022

The physics of the dark Universe goes beyond the standard model (BSM) of fundamental interactions. The now-standard cosmology involves inflation, baryosynthesis and dark matter/energy corresponding to BSM physics. Cosmoparticle physics offers cross disciplinary study of the fundamental relationship of cosmology and particle physics in the combination of its physical, astrophysical and cosmological signatures. Methods of cosmoparticle physics in studies of BSM physics in its relationship with inevitably nonstandard features of dark universe cosmology are discussed. In the context of these methods, such exotic phenomena as primordial black holes, antimatter stars in baryon asymmetrical Universe or multi-charged constituents of nuclear interacting atoms of composite dark matter play the role of sensitive probes for BSM models and their parameters.
Incremental Nonnegative Tucker Decomposition with Block-Coordinate Descent and Recursive Approaches
Authors: Zdunek Rafał , Fonał Krzysztof
Published: January 2022

Nonnegative Tucker decomposition (NTD) is a robust method used for nonnegative multilinear feature extraction from nonnegative multi-way arrays. The standard version of NTD assumes that all of the observed data are accessible for batch processing. However, the data in many real-world applications are not static or are represented by a large number of multi-way samples that cannot be processing in one batch. To tackle this problem, a dynamic approach to NTD can be explored. In this study, we extend the standard model of NTD to an incremental or online version, assuming volatility of observed multi-way data along one mode. We propose two computational approaches for updating the factors in the incremental model: one is based on the recursive update model, and the other uses the concept of the block Kaczmarz method that belongs to coordinate descent methods. The experimental results performed on various datasets and streaming data demonstrate high efficiently of both algorithmic approaches, with respect to the baseline NTD methods.
An Ensemble Framework of Evolutionary Algorithm for Constrained Multi-Objective Optimization
Authors: Ku Junhua , Ming Fei , Gong Wenyin
Published: January 2022

In the real-world, symmetry or asymmetry widely exists in various problems. Some of them can be formulated as constrained multi-objective optimization problems (CMOPs). During the past few years, handling CMOPs by evolutionary algorithms has become more popular. Lots of constrained multi-objective optimization evolutionary algorithms (CMOEAs) have been proposed. Whereas different CMOEAs may be more suitable for different CMOPs, it is difficult to choose the best one for a CMOP at hand. In this paper, we propose an ensemble framework of CMOEAs that aims to achieve better versatility on handling diverse CMOPs. In the proposed framework, the hypervolume indicator is used to evaluate the performance of CMOEAs, and a decreasing mechanism is devised to delete the poorly performed CMOEAs and to gradually determine the most suitable CMOEA. A new CMOEA, namely ECMOEA, is developed based on the framework and three state-of-the-art CMOEAs. Experimental results on five benchmarks with totally 52 instances demonstrate the effectiveness of our approach. In addition, the superiority of ECMOEA is verified through comparisons to seven state-of-the-art CMOEAs. Moreover, the effectiveness of ECMOEA on the real-world problems is also evaluated for eight instances.
A Novel Dual-Band Implantable Antenna for Pancreas Telemetry Sensor Applications
Authors: Matthaiou Maria , Koulouridis Stavros , Kotsopoulos Stavros
Published: January 2022

In this study, a novel implantable dual-band planar inverted F-antenna (PIFA) is proposed and designed for wireless biotelemetry. The developed antenna is intended to operate on the surface of the pancreas within the Medical Device Radiocommunications Service (MedRadio 401–406 MHz) and the industrial scientific and medical band (ISM, 2.4–2.5 GHz). The design analysis was carried out in two steps, initially inside a canonical model representing the pancreas, based on a finite element method (FEM) numerical solver. The proposed antenna was further simulated inside the human body taking into account the corresponding dimensions of the tissues and the electrical properties at the frequencies of interest using a finite-difference time-domain (FDTD) numerical solver. Resonance, radiation performance, electrical field attenuation, total radiated power, and specific absorption rate (SAR), which determines the safety of the patient and the maximum permissible input power and other electromagnetic parameters, are presented and evaluated.
A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks
Authors: Temene Natalie , Sergiou Charalampos , Ioannou Christiana , Georgiou Chryssis , Vassiliou Vasos
Published: January 2022

The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those issues is the use of mobile nodes or nodes deployed by mobile robots. The use of mobile elements essentially increases the resources and the capacity of the network. In this work, we present a Node Placement Algorithm with two variations, which utilizes mobile nodes for the creation of alternative paths from source to sink. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. We then extend the local variation of the algorithm by also accounting for the energy levels of the nodes as a contributing factor regarding the creation of alternative paths. We offer both a high-level description of the concept and also detailed algorithmic solutions. The evaluation of the solutions was performed in a case study of resolving congestion in the network. Results have shown that the proposed algorithms can significantly contribute to the alleviation of the problem of congestion in IoT and WSNs and can easily be used for other types of network problems.
Characterizing Steam Penetration through Thermal Protective Fabric Materials
Authors: Mandal Sumit , Song Guowen
Published: January 2022

This study performs an analysis of steam penetration through thermal protective fabric materials. Different, multilayered thermal protective fabrics were selected and tested in a laboratory-simulated steam exposure, and their steam protective performance (SPP) was measured in terms of the time required to generate second-degree burns on the bodies of wearers. Additionally, the total transmitted thermal energy (TTTE) through the fabrics during testing was measured. Through statistical analysis, it was established that fabric properties, namely air permeability and thickness, are the key factors that affect the SPP and TTTE; the relationship among the fabric properties, SPP, and TTTE is also summarized. Theoretically, it has been found that heat and mass (steam) transfer occur through fabrics in the course of steam exposure, which mainly affect the SPP and TTTE. This study could help textile/materials engineers to develop high performance thermal protective fabrics for the increased occupational health and safety of firefighters and industrial workers.
Occurrence and Seasonal Monitoring of Domoic Acid in Three Shellfish Species from the Northern Adriatic Sea
Authors: Kvrgić Kristina , Lešić Tina , Džafić Natalija , Pleadin Jelka
Published: January 2022

As filter feeders, bivalves and ascidians can accumulate contaminants present in the environment and pass them on to higher food chain levels as vectors. The consumption of bivalves contaminated with the potent neurotoxin domoic acid (DA) can cause amnesic shellfish poisoning in humans. The aim of this study was to determine seasonal differences in occurrence and accumulation of this phycotoxin in European oysters (Ostrea edulis Linnaeus, 1758) (n = 46), Queen scallops (Aequipecten opercularis Linnaeus, 1758) (n = 53), and edible ascidians of the Microcosmus spp. (n = 107), originating from the same harvesting area in the Northern Adriatic Sea. The quantification was performed using ultra-performance liquid chromatography–tandem mass spectrometry (LC-MS/MS) preceded by derivatization with dansyl chloride. DA was found in very low concentrations throughout the year, with a maximum value of 810 μg/kg in Queen scallops. This study reveals differences in the occurrence and accumulation of DA between Queen scallops and the other two investigated species (oysters and ascidians) and the highest concentrations during the colder part of the year. Even though DA was detected in all of them, Queen scallops showed higher DA accumulation compared to the other two (p < 0.001), hence representing a sentinel species suitable for the monitoring of DA level in seafood.
Pydiflumetofen Co-Formulated with Prothioconazole: A Novel Fungicide for Fusarium Head Blight and Deoxynivalenol Control
Authors: Edwards Simon G.
Published: January 2022

Fusarium head blight (FHB) is an important disease of small grain cereals worldwide, resulting in reduced yield and quality as well as the contamination of harvested grains with mycotoxins. The key mycotoxin of concern is deoxynivalenol (DON), which has legislative and advisory limits in numerous countries. Cereal growers have a number of control options for FHB including rotation, cultivation, and varietal resistance; however, growers are still reliant on fungicides applied at flowering as part of an IPM program. Fungicides currently available to control FHB are largely restricted to triazole chemistry. This study conducted three field experiments to compare a new co-formulation of pydiflumetofen (a succinate dehydrogenase inhibitor (SDHI) with the tradename ADEPIDYN™) and prothioconazole (a triazole) against current standard fungicides at various timings (flag leaf fully emerged, mid-head emergence, early flowering, and late flowering) for the control of FHB and DON. Overall, the co-formulation showed greater efficacy compared to either pydiflumetofen alone or current fungicide chemistry. This greater activity was demonstrated over a wide range of spray timings (flag leaf fully emerged to late flowering). The availability of an SDHI with good activity against FHB and the resulting DON contamination of harvested grain will give growers an additional tool within an IPM program that will provide a greater flexibility of spray application windows and reduce fungicide resistance selection pressure.
Ciguatoxin Detection in Flesh and Liver of Relevant Fish Species from the Canary Islands
Authors: Ramos-Sosa María José , García-Álvarez Natalia , Sanchez-Henao Andres , Silva Sergent Freddy , Padilla Daniel , Estévez Pablo , Caballero María José , Martín-Barrasa José Luís , Gago-Martínez Ana , Diogène Jorge , Real Fernando
Published: January 2022

The Canary Islands are a ciguatoxin (CTX) hotspot with an established official monitoring for the detection of CTX in fish flesh from the authorised points of first sale. Fish caught by recreational fishermen are not officially tested and the consumption of toxic viscera or flesh could lead to ciguatera poisoning (CP). The objectives of this study were to determine the presence of CTX-like toxicity in relevant species from this archipelago, compare CTX levels in liver and flesh and examine possible factors involved in their toxicity. Sixty amberjack (Seriola spp.), 27 dusky grouper (Epinephelus marginatus), 11 black moray eels (Muraena helena) and 11 common two-banded seabream (Diplodus vulgaris) were analysed by cell-based assay (CBA) and Caribbean ciguatoxin-1 (C-CTX1) was detected by liquid chromatography mass spectrometry (LC-MS/MS) in all these species. Most of the liver displayed higher CTX levels than flesh and even individuals without detectable CTX in flesh exhibited hepatic toxicity. Black moray eels stand out for the large difference between CTX concentration in both tissues. None of the specimens with non-toxic liver showed toxicity in flesh. This is the first evidence of the presence of C-CTX1 in the common two-banded seabream and the first report of toxicity comparison between liver and muscle from relevant fish species captured in the Canary Islands.
Hilltop Inflation and Generation of Helical Magnetic Field
Authors: Chakraborty Sumanta , Pal Supratik , SenGupta Soumitra
Published: January 2022

Primordial magnetic field generated in the inflationary era can act as a viable source for the present day intergalactic magnetic field of sufficient strength. We present a fundamental origin for such a primordial generation of the magnetic field, namely through anomaly cancellation of U(1) gauge field in quantum electrodynamics in the context of hilltop inflation. We have analysed at length the power spectrum of the magnetic field, thus generated, which turns out to be helical in nature. We have also found that magnetic power spectrum has significant scale-dependence giving rise to a non-trivial magnetic spectral index, a key feature of this model. Interestingly, there exists a large parameter space, where magnetic field of significant strength can be produced.
E6 GUT and Baryon Asymmetry Generation in the E6CHM
Authors: Nevzorov Roman
Published: January 2022

Grand unified theories (GUTs) may result in the E6-inspired composite Higgs model (E6CHM) at low energies, almost stabilizing the electroweak scale. We consider an orbifold GUT in 6 dimensions in which the E6-gauge group is broken to the gauge symmetry of the standard model (SM) while different multiplets of the SM fermions come from different 27-plets. The strongly coupled sector of the E6CHM is confined on the brane where E6 is broken down to its SU(6) subgroup. Near the scale of f≳5TeV, this approximate SU(6) symmetry is expected to be further broken down to its SU(5) subgroup, which contains the SM-gauge group. Such a breakdown leads to a set of pseudo-Nambu–Goldstone bosons (pNGBs) that includes an SM-like Higgs doublet. The approximate gauge coupling unification in the E6CHM takes place at high energies when the right-handed top quark is a composite fermion. To ensure anomaly cancellation, the weakly coupled sector of this model contains extra exotic matter beyond the SM. We discuss the mechanism of the generation of matter–antimatter asymmetry within the variant of the E6CHM in which the baryon number and CP invariance are violated.
Time in Quantum Cosmology
Authors: Kiefer Claus , Peter Patrick
Published: January 2022

Time in quantum gravity is not a well-defined notion despite its central role in the very definition of dynamics. Using the formalism of quantum geometrodynamics, we briefly review the problem and illustrate it with two proposed solutions. Our main application is quantum cosmology—the application of quantum gravity to the Universe as a whole.
Digging into Axion Physics with (Baby)IAXO
Authors: Dafni Theopisti , Galán Javier
Published: January 2022

Dark matter searches have been ongoing for three decades; the lack of a positive discovery of the main candidate, the WIMP, after dedicated efforts, has put axions and axion-like particles in the spotlight. The three main techniques employed to search for them complement each other well in covering a wide range in the parameter space defined by the axion decay constant and the axion mass. The International AXion Observatory (IAXO) is an international collaboration planning to build the fourth generation axion helioscope, with an unparalleled expected sensitivity and discovery potential. The distinguishing characteristic of IAXO is that it will feature a magnet that is designed to maximise the relevant parameters in sensitivity and which will be equipped with X-ray focusing devices and detectors that have been developed for axion physics. In this paper, we review aspects that motivate IAXO and its prototype, BabyIAXO, in the axion, and ALPs landscape. As part of this Special Issue, some emphasis is given on Spanish participation in the project, of which CAPA (Centro de Astropartículas y Física de Altas Energías of the Universidad de Zaragoza) is a strong promoter.
Special Issue: Virus Receptors and Viral Tropism
Authors: Susi Petri
Published: January 2022

Cell surface receptors play a key role in a virus’ ability to recognize and invade cells and tissues, which basically defines viral pathogenicity [...]
Epidemiology and Transmitted HIV-1 Drug Resistance among Treatment-Naïve Individuals in Israel, 2010–2018
Authors: Wagner Tali , Zuckerman Neta S. , Halperin Tami , Chemtob Daniel , Levy Itzchak , Elbirt Daniel , Shachar Eduardo , Olshtain-Pops Karen , Elinav Hila , Chowers Michal , Itsomin Valery , Riesenberg Klaris , Wax Marina , Shirazi Rachel , Gozlan Yael , Matus Natasha , Girshengorn Shirley , Marom Rotem , Mendelson Ella , Turner Dan , Mor Orna
Published: January 2022

Despite the low prevalence of HIV-1 in Israel, continuous waves of immigration may have impacted the local epidemic. We characterized all people diagnosed with HIV-1 in Israel in 2010–2018. The demographics and clinical data of all individuals (n = 3639) newly diagnosed with HIV-1 were retrieved. Subtypes, transmitted drug-resistance mutations (TDRM), and phylogenetic relations, were determined in >50% of them. In 39.1%, HIV-1 transmission was through heterosexual contact; 34.3% were men who have sex with men (MSM); and 10.4% were people who inject drugs. Many (>65%) were immigrants. Israeli-born individuals were mostly (78.3%) MSM, whereas only 9% of those born in Sub-Saharan Africa (SSA), Eastern Europe and Central Asia (EEU/CA), were MSM. The proportion of individuals from SSA decreased through the years 2010–2018 (21.1% in 2010–2012; 16.8% in 2016–2018) whereas those from EEU/CA increased significantly (21% in 2010–2012; 27.8% in 2016–2018, p < 0.001). TDRM were identified in 12.1%; 3.7, 3.3 and 6.6% had protease inhibitors (PI), nucleotide reverse transcriptase inhibitors (NRTI), and non-nucleoside reverse transcriptase inhibitors (NNRTI) TDRM, respectively, with the overall proportion remaining stable in the studied years. None had integrase TDRM. Subtype B was present in 43.9%, subtype A in 25.2% (A6 in 22.8 and A1 in 2.4%) and subtype C in 17.1% of individuals. Most MSM had subtype B. Subtype C carriers formed small clusters (with one unexpected MSM cluster), A1 formed a cluster mainly of locally-born patients with NNRTI mutations, and A6 formed a looser cluster of individuals mainly from EEU. Israelis, <50 years old, carrying A1, had the highest risk for having TDRM. In conclusion, an increase in immigrants from EEU/CA and a decrease in those from SSA characterized the HIV-1 epidemic in 2010–2018. Baseline resistance testing should still be recommended to identify TDRM, and improve surveillance and care.
A Cross Sectional Sampling Reveals Novel Coronaviruses in Bat Populations of Georgia
Authors: Urushadze Lela , Babuadze George , Shi Mang , Escobar Luis E. , Mauldin Matthew R. , Natradeze Ioseb , Machablishvili Ann , Kutateladze Tamar , Imnadze Paata , Nakazawa Yoshinori , Velasco-Villa Andres
Published: January 2022

Mammal-associated coronaviruses have a long evolutionary history across global bat populations, which makes them prone to be the most likely ancestral origins of coronavirus-associated epidemics and pandemics globally. Limited coronavirus research has occurred at the junction of Europe and Asia, thereby investigations in Georgia are critical to complete the coronavirus diversity map in the region. We conducted a cross-sectional coronavirus survey in bat populations at eight locations of Georgia, from July to October of 2014. We tested 188 anal swab samples, remains of previous pathogen discovery studies, for the presence of coronaviruses using end-point pan-coronavirus RT-PCR assays. Samples positive for a 440 bp amplicon were Sanger sequenced to infer coronavirus subgenus or species through phylogenetic reconstructions. Overall, we found a 24.5% positive rate, with 10.1% for Alphacoronavirus and 14.4% for Betacoronavirus. Albeit R. euryale, R. ferrumequinum, M. blythii and M. emarginatus were found infected with both CoV genera, we could not rule out CoV co-infection due to limitation of the sequencing method used and sample availability. Based on phylogenetic inferences and genetic distances at nucleotide and amino acid levels, we found one putative new subgenus and three new species of Alphacoronavirus, and two new species of Betacoronavirus.