bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Fidelity Aerodynamic Data Fusion with a Deep Neural Network Modeling Method
Authors: He Lei , Qian Weiqi , Zhao Tun , Wang Qing
Published: September 2020

To generate more high-quality aerodynamic data using the information provided by different fidelity data, where low-fidelity aerodynamic data provides the trend information and high-fidelity aerodynamic data provides value information, we applied a deep neural network (DNN) algorithm to fuse the information of multi-fidelity aerodynamic data. We discuss the relationships between the low-fidelity and high-fidelity data, and then we describe the proposed architecture for an aerodynamic data fusion model. The architecture consists of three fully-connected neural networks that are employed to approximate low-fidelity data, and the linear part and nonlinear part of correlation for the low- and high-fidelity data, respectively. To test the proposed multi-fidelity aerodynamic data fusion method, we calculated Euler and Navier–Stokes simulations for a typical airfoil at various Mach numbers and angles of attack to obtain the aerodynamic coefficients as low- and high-fidelity data. A fusion model of the longitudinal coefficients of lift CL and drag CD was constructed with the proposed method. For comparisons, variable complexity modeling and cokriging models were also built. The accuracy spread between the predicted value and true value was discussed for both the training and test data of the three different methods. We calculated the root mean square error and average relative deviation to demonstrate the performance of the three different methods. The fusion result of the proposed method was satisfactory on the test case, and showed a better performance compared with the other two traditional methods presented. The results provide evidence that the method proposed in this paper can be useful in dealing with the multi-fidelity aerodynamic data fusion problem.
Revisiting the Environmental Kuznets Curve: The Spatial Interaction between Economy and Territory
Authors: Mosconi Enrico Maria , Colantoni Andrea , Gambella Filippo , Cudlinová Eva , Salvati Luca , Rodrigo-Comino Jesús
Published: September 2020

A complex interplay of socio-ecological drivers of change exists at the different spatiotemporal scales affecting environmental degradation. This is a key issue worldwide and needs to be understood to develop efficient management solutions. One of the most applied theories in the regional analysis is the U-shaped relationship between environmental degradation and the level of income in a given economic system or Environmental Kuznets Curve (EKC). Specifically, the EKC hypothesis underlines the (potentially positive) role of formal responses to environmental degradation grounded on government policies that are usually more ambitious in wealthier economic systems. However, there is a lack of knowledge on the role of space in EKC, arguing that spatial variability in the environment–income relationship may indicate additional targets for integrated socio–environmental policies. We hypothesize that a spatially differentiated response to environmental degradation could better adapt to differentiated local contexts. Therefore, to achieve this goal, we present a multi-scale investigation of degradation processes at the local level, providing a refined knowledge of the environment–economy linkages considering more traditional, cross-country and cross-region exercises. Our results demonstrated that—together with temporal, sectoral, and institutional aspects—space and, consequently, the related analysis’ spatial scales, are significant dimensions in ecological economics, whose investigation requires improvements in data collection and dedicated statistical approaches.
Does Trade Openness Affect Bank Risk-Taking Behavior? Evidence from BRICS Countries
Authors: Rahman Mohammed Mizanur , Begum Munni , Ashraf Badar Nadeem , Masud Md. Abdul Kaium
Published: September 2020

In this paper, we examine the impact of trade openness on bank risk-taking behavior employing a panel dataset of 899 banks from the BRICS (i.e., Brazil, Russia, India, China, and South Africa) countries over the period 2000–2017. We find that higher trade openness lowers bank risk-taking. Our results are robust when we use alternative proxies of trade openness and bank risk-taking, estimate country-wise regressions, or use alternative estimation methods such as system Generalized Methods of Moments (GMM), fixed effects, pooled Ordinary Least Square (OLS), and Vector Error Correction Model (VECM) models. We also observe higher trade openness decreases bank risk-taking in both the short and long run. Moreover, banks in more open countries perform relatively better during the crisis period further signifying the diversification benefits of openness. Together, our findings imply the beneficial impact of trade openness for financial sector stability.
Indicators of Regional Innovation Clusters’ Effectiveness in the Higher Education System
Authors: Lysenko Iryna , Stepenko Serhii , Dyvnych Hanna
Published: September 2020

Under globalization conditions, the main priority of the state education policy in many countries of the world is to ensure higher education quality. This is possible through close and efficient cooperation between the state, higher education institutions, future specialists, employers and innovative structures (clusters). This study focuses on the development of indicators that can comprehensively assess the effectiveness of regional innovation clusters in the higher education system. The main attention is given to the analysis of innovations, business, education development and competitiveness, as indicators of the effectiveness of regional innovation clusters in the higher education system. The following methods have been used within the research: content analysis, statistical, correlation and regression analysis, econometric modeling and the graphical method. As a result of the research, indicators of the effectiveness of regional innovation clusters have been identified and the impact of these indicators on the higher education system has been evaluated. The authors have shown that there is a close relationship between the level of development of regional innovation clusters, indicators of business and innovations development, and the level of competitiveness. The direct impact of those on the higher education system has been established and confirmed by the provided calculations.
A Hybrid Recommendation Method Integrating the Social Trust Network and Local Social Influence of Users
Authors: Lu Lilei , Yuan Yuyu , Chen Xu , Li Zhaohui
Published: September 2020

Recommendation system plays an indispensable role in helping users make decisions in different application scenarios. The issue about how to improve the accuracy of a recommendation system has gained widespread concern in both academic and industry fields. To solve this problem, many models have been proposed, but most of them usually focus on a single perspective. Different from the existing work, we propose a hybrid recommendation method based on the users’ social trust network in this study. The proposed method has several advantages over conventional recommendation solutions. First, it offers a reliable two-step way of determining reference users by employing direct trust between users in the social trust network and setting a similarity threshold. Second, it improves the traditional collaborative filtering (CF) method based on a Pearson Correlation Coefficient (PCC) to reduce extreme values in prediction. Third, it introduces a personalized local social influence (LSI) factor into the improved CF method to further enhance the prediction accuracy. Seventy-one groups of random experiments based on the real dataset Epinions in social networks verify the proposed method. The experimental results demonstrate its feasibility, effectiveness, and accuracy in improving recommendation performance.
A Review on Biomedical MIMO Radars for Vital Sign Detection and Human Localization
Authors: Cardillo Emanuele , Caddemi Alina
Published: September 2020

This paper reports a thorough overview on the last developments concerning the vital sign detection and the human localization employing the multiple-input-multiple-output (MIMO) technology. The wireless motion and vital sign detection represents an outstanding research area aimed at monitoring the health conditions of human subjects and at detecting their presence in different environments with minimal concern. MIMO radars exhibit several interesting advantages over conventional single-input-single-output architectures mainly related to their angle detection capabilities and enhanced signal-to-noise ratio. This paper describes the main features and details the operating principles of MIMO technology. Thereafter, it summarizes the state-of-the-art of the available solutions with the purpose of fueling the research activities on this hot topic.
A Novel SRAM PUF Stability Improvement Method Using Ionization Irradiation
Authors: Zhang Xu , Jiang Chunsheng , Gu Ke , Zhong Le , Fang Wen , Dai Gang
Published: September 2020

As one of the fundamental elements of the fingerprints of integrated circuit chips, static random-access memory based physical unclonable function (SRAM PUF) has been regarded as an attractive option for hardware security circuits. Commercial SRAM chips could be used as PUF chips for low cost systems. However, the mismatches existing in most commercial SRAM chips are quite small, which could result in poor stability of SRAM PUF. To address this issue, this paper proposes a novel SRAM PUF stability improvement method using total ionization dose (TID) effect for commercial SRAM chips. The principles of this new method are presented in detail and verified by simulations. Thereafter, the TID experiments are carried out on one kind of commercial SRAM chips and validate that this novel method could reduce the intra-chip hamming distance (??_?????) by two orders of magnitude within the ionizing dose range of 40–100 Krad (SiO2), which is a significant stability improvement. Furthermore, considering the trade-offs of other performance factors, 40 Krad (SiO2) has been regarded as the recommended ionizing dose, which not only makes the stability and uniformity of SRAM PUF attain almost ideal values but also keeps the radiation-induced damage within a limited level.
Parallel Classification Pipelines for Skin Cancer Detection Exploiting Hyperspectral Imaging on Hybrid Systems
Authors: Torti Emanuele , Leon Raquel , La Salvia Marco , Florimbi Giordana , Martinez-Vega Beatriz , Fabelo Himar , Ortega Samuel , Callicó Gustavo M. , Leporati Francesco
Published: September 2020

The early detection of skin cancer is of crucial importance to plan an effective therapy to treat the lesion. In routine medical practice, the diagnosis is based on the visual inspection of the lesion and it relies on the dermatologists’ expertise. After a first examination, the dermatologist may require a biopsy to confirm if the lesion is malignant or not. This methodology suffers from false positives and negatives issues, leading to unnecessary surgical procedures. Hyperspectral imaging is gaining relevance in this medical field since it is a non-invasive and non-ionizing technique, capable of providing higher accuracy than traditional imaging methods. Therefore, the development of an automatic classification system based on hyperspectral images could improve the medical practice to distinguish pigmented skin lesions from malignant, benign, and atypical lesions. Additionally, the system can assist general practitioners in first aid care to prevent noncritical lesions from reaching dermatologists, thereby alleviating the workload of medical specialists. In this paper is presented a parallel pipeline for skin cancer detection that exploits hyperspectral imaging. The computational times of the serial processing have been reduced by adopting multicore and many-core technologies, such as OpenMP and CUDA paradigms. Different parallel approaches have been combined, leading to the development of fifteen classification pipeline versions. Experimental results using in-vivo hyperspectral images show that a hybrid parallel approach is capable of classifying an image of 50 × 50 pixels with 125 bands in less than 1 s.
Compact Hardware Architectures of Enocoro-128v2 Stream Cipher for Constrained Embedded Devices
Authors: Pyrgas Lampros , Kitsos Paris
Published: September 2020

Lightweight cryptography is a vital and fast growing field in today’s world where billions of constrained devices interact with each other. In this paper, two novel compact architectures of the Enocoro-128v2 stream cipher are presented. The Enocoro-128v2 is part of the ISO/IEC 29192-3 standard. The first architecture has an 8-bit datapath while the second one has a 4-bit datapath. The proposed architectures were implemented on the BASYS3 board (Artix 7 XC7A35T) using the VERILOG hardware description language. The hardware implementation of the proposed 8-bit architecture runs at a 189 MHz clock and reaches a throughput equal to 302 Mbps, while at the same time, it utilizes only 254 Look-up Tables (LUTs) and 330 Flip-flops (FFs). Each round of computations requires 5 clock cycles. The 4-bit implementation has an operating frequency of 204 MHz and reaches a throughput equal to 181 Mbps, with each round requiring 9 clock cycles. The 4-bit implementation utilizes 249 LUTs and 343 FFs. To our knowledge, this is the first time that such implementations of the Enocoro-128v2 are presented. Both implementations utilize a very low number of resources (only 78 FPGA slices are required for the 8-bit architecture and only 83 for the 4-bit one) and the results demonstrate that they are sustainable for area constrained embedded devices.
Simulation of a Smart Sensor Detection Scheme for Wireless Communication Based on Modeling
Authors: Koyuncu Hakan , Bagwari Ashish , Tomar Geetam Singh
Published: September 2020

The principle of sensing and sending information applies to all kinds of communications in different media like air, water, etc. During data transmission through sensors, the most important issue is sensing failure problems. In communication systems, sensing failure problems generally occur and affect sensor system performance. In this study, sensing failure issues are discussed, and a smart sensor is introduced that detects the communication signals. The characteristics of these sensors are identified with signal-to-noise ratio (SNR) readings. The proposed sensor system has high performance and it is better than many systems in the literature. Graphical findings show that the suggested scheme increases device efficiency and has more performance than the energy detector (ED) and ED-ADT-2013 by 33.5%, adaptive spectrum sensing (ASS)-2012 by 41.5%, energy detecting technique for adaptive spectrum sensing (EDT-ASS)-2015 by 28.2%, energy detector, and cyclo-2010 by 57.0%, and energy-SNR adaptive threshold (ADT) detector-2016 by 52.8% at −12 dB SNR, respectively. The proposed sensor detection scheme performs well compared to other existing sensors regarding sensing time. It was found that cooperative spectrum sensing (CSS) with the proposed method outperforms HwQ-2012 and CSS-EDT-ASS-2015 by 22.70% and 16.10% in terms of probability at −12 dB SNR, respectively, and detects the signal at −19.70 dB SNR.
Guided Networks for Few-Shot Image Segmentation and Fully Connected CRFs
Authors: Zhang Kun , Zheng Yuanjie , Deng Xiaobo , Jia Weikuan , Lian Jian , Chen Xin
Published: September 2020

The goal of the few-shot learning method is to learn quickly from a low-data regime. Structured output tasks like segmentation are challenging for few-shot learning, due to their being high-dimensional and statistically dependent. For this problem, we propose improved guided networks and combine them with a fully connected conditional random field (CRF). The guided network extracts task representations from annotated support images through feature fusion to do fast, accurate inference on new unannotated query images. By bringing together few-shot learning methods and fully connected CRFs, our method can do accurate object segmentation by overcoming poor localization properties of deep convolutional neural networks and can quickly updating tasks, without further optimization, when faced with new data. Our guided network is at the forefront of accuracy for the terms of annotation volume and time.
NAT++: An Efficient Micro-NAT Architecture for Solving IP-Spoofing Attacks in a Corporate Network
Authors: Veeraraghavan Prakash , Hanna Dalal , Pardede Eric
Published: September 2020

The Internet Protocol (IP) version 4 (IPv4) has several known vulnerabilities. One of the important vulnerabilities is that the protocol does not validate the correctness of the source address carried in an IP packet. Users with malicious intentions may take advantage of this vulnerability and launch various attacks against a target host or a network. These attacks are popularly known as IP Address Spoofing attacks. One of the classical IP-spoofing attacks that cost several million dollars worldwide is the DNS-amplification attack. Currently, the availability of solutions is limited, proprietary, expensive, and requires expertise. The Internet is subjected to several other forms of amplification attacks happening every day. Even though IP-Spoofing is one of the well-researched areas since 2005, there is no holistic solution available to solve this problem from the gross-root. Also, every solution assumes that the attackers are always from outside networks. In this paper, we provide an efficient and scalable solution to solve the IP-Spoofing problem that arises from malicious or compromised inside hosts. We use a modified form of Network Address Translation (NAT) to build our solution framework. We call our framework as NAT++. The proposed infrastructure is robust, crypto-free, and easy to implement. Our simulation results have shown that the proposed NAT++ infrastructure does not consume more than the resources required by a simple NAT.
Tree Line Shift in the Olympus Mountain (Greece) and Climate Change
Authors: Zindros Athanasios , Radoglou Kalliopi , Milios Elias , Kitikidou Kyriaki
Published: September 2020

One of the effects of climate change is, among others, changes to forest ecosystems. Research Highlights: Temperature increases and upward tree line shifts are linked in many studies. However, the impact of climate change on tree lines has not been studied in Greece. Background and Objectives: The aim of this study is to assess the relation of tree line shifts and climate change in Olympus mountain, and especially in a protected area. Materials and Methods: In the Olympus mountain, which includes a protected area (the Olympus National Park core) since 1938, GIS data regarding forest cover were analyzed, while climate change from a previous study is presented. Results: Forest expansion and an upward tree line shift are proven in the Olympus mountain area. In the National Park core, the tree line shift is the result of climate change and attributed to the significant temperature increase in the growing season. Conclusions: There are strong indications that a temperature increase leads to an upward shift of the tree lines in the National Park core.
Bioavailability and Bioactivities of Polyphenols Eco Extracts from Coffee Grounds after In Vitro Digestion
Authors: Vamanu Emanuel , Gatea Florentina , Pelinescu Diana Roxana
Published: September 2020

Coffee grounds are a valuable source of bioactive compounds. In Romania, most of the amount obtained is lost through non-recovery; the rest is occasionally used as organic fertilizer. The coffee grounds were selected according to the roasting degree: blonde roasted (BR), medium roasted (MR), and dark roasted (DR). The study aimed to evaluate three extracts, obtained with a mixture of ethanol/water/acetic acid (50/49.5/0.5), depending on the roasting degree. The majority phenolic component, the antioxidant, and anti-inflammatory effect, as well as the role that gastrointestinal transit had on the bioavailability of bioactive compounds were determined. Chlorogenic acid was inversely proportional to the roasting degree. BR showed the best correlation between antioxidant and anti-inflammatory activities in vitro/in vivo. The antiproliferative capacity of the extracts determined an inhibitory effect on the tumor cells. Antimicrobial activities, relevant in the control of type 2 diabetes, were exerted through the inhibition of microbial strains (Escherichia coli). Following gastric digestion, BR demonstrated a maximum loss of 20% in the stomach. The recovery of coffee grounds depended on the pattern of functional compounds and the bioavailability of the main component, chlorogenic acid.
Occurrence, Antimicrobial Resistance and Molecular Diversity of Enterococcus faecium in Processed Pork Meat Products in Korea
Authors: Kim Hyun Jung , Koo Minseon
Published: September 2020

Because Enterococcus faecium is an important nosocomial pathogen and sentinel organism for tracking antimicrobial resistance, information on the contamination and antimicrobial resistance patterns of E. faecium in food are essential to public health and food safety. We analyzed the occurrence of E. faecium in retail pork meat products (n = 124), and antimicrobial resistance of 30 E. faecium isolates were examined against 14 antimicrobials using the broth dilution test and disc diffusion test. Rep-PCR-based molecular diversity was also analyzed using Deviersilab. The highest contamination of enterococci was observed for minced pork meat but most of the E. faecium was isolated from meatball-type frozen pork meat products (FP). Incidences of antimicrobial-resistant E. faecium against erythromycin, clindamycin and nitrofurantoin were 80%, 50% and 20%, respectively. No vancomycin-resistant enterococci were analyzed. Rep-PCR showed distinctive clusters with a similarity ≥ 98%, consisting of 18 E. faecium isolates from FP manufactured in seven companies. The analyzed data on the contamination and antimicrobial resistance patterns combined with molecular typing can be useful to derive risk management of antimicrobial-resistant enterococci in food.
Casing Contribution to Proteolytic Changes and Biogenic Amines Content in the Production of an Artisanal Naturally Fermented Dry Sausage
Authors: Serio Annalisa , Laika Jessica , Maggio Francesca , Sacchetti Giampiero , D’Alessandro Flavio , Rossi Chiara , Martuscelli Maria , Chaves-López Clemencia , Paparella Antonello
Published: September 2020

The effect of two kinds of casings on the production and characteristics of a dry fermented sausage was investigated. In detail, an Italian product, naturally fermented at low temperatures and normally wrapped in beef casing instead of the most diffused hog one, was selected. Two different productions (one traditionally in beef casing (MCB) and another in hog casing (MCH)) were investigated over time to determine the differences particularly regarding proteolytic changes during fermentation and ripening. First of all, the product in hog casing required a longer ripening time, up to 120 days, instead of 45–50 days, because of the lower drying rate, while the microbial dynamics were not significantly modified. Conversely, the proteolysis showed a different evolution, being more pronounced, together with the biogenic amines content up to 341 mg/Kg instead of 265 mg/Kg for the traditional products. The latter products were instead characterized by higher quantities of total free amino acids, 3-methyl butanoic acid, 3-Methyl-1-butanal, and 2-Methylpropanal, enriching the final taste and aroma. The traditional product MCB also showed lower hardness and chewiness than MCH. The results highlight how the choice of casing has a relevant impact on the development of the final characteristics of fermented sausages.
Effect of Microwave Pretreatment of Seeds on the Quality and Antioxidant Capacity of Pomegranate Seed Oil
Authors: Kaseke Tafadzwa , Opara Umezuruike Linus , Fawole Olaniyi Amos
Published: September 2020

Microwave pretreatment of oilseeds is a novel technique used to enhance oil nutraceutical properties. In this study, the effect of microwave pretreatment of seeds was investigated on pomegranate seed oil quality attributes including oil yield, yellowness index, refractive index, peroxide value, ρ-anisidine value, total oxidation value, conjugated dienes, total phenolic content, total carotenoids content, phytosterol composition, fatty acid composition, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity, and ferric reducing antioxidant power (FRAP). The seeds of three different pomegranate cultivars (‘Acco’, ‘Herskawitz’, and ‘Wonderful’) were microwave heated at 261 W for 102 s. Pomegranate seeds microwave pretreatment enhanced oil yield, yellowness index, total carotenoids content, total phenolic content, FRAP and DPPH radical scavenging capacity, despite an increase in conjugated dienes, and peroxide value. Palmitic acid, oleic acid, linoleic acid, saturated, and monosaturated fatty acids were increased after pomegranate seeds microwave pretreatment, whilst the levels of punicic acid and β-sitosterol were reduced. Nevertheless, the refractive index, the ratio of unsaturated to saturated fatty acid of the extracted oil were not significantly (p > 0.05) affected by pomegranate seeds microwave pretreatment. Principal component analysis and agglomerative hierarchical clustering established that ‘Acco’ and ‘Wonderful’ oil extracts from microwave pretreated PS exhibited better oil yield, whilst ‘Herskawitz’ oil extracts showed higher total carotenoids content, total phenolic content, and antioxidant capacity.
Headspace Gas Chromatography Coupled to Mass Spectrometry and Ion Mobility Spectrometry: Classification of Virgin Olive Oils as a Study Case
Authors: García-Nicolás María , Arroyo-Manzanares Natalia , Arce Lourdes , Hernández-Córdoba Manuel , Viñas Pilar
Published: September 2020

Due to its multiple advantages, ion mobility spectrometry (IMS) is being considered as a complementary technique to mass spectrometry (MS). The goal of this work is to investigate and compare the capacity of IMS and MS in the classification of olive oil according to its quality. For this purpose, two analytical methods based on headspace gas chromatography (HS-GC) coupled with MS or with IMS have been optimized and characterized for the determination of volatile organic compounds from olive oil samples. Both detectors were compared in terms of sensitivity and selectivity, demonstrating that complementary data were obtained and both detectors have proven to be complementary. MS and IMS showed similar selectivity (10 out of 38 compounds were detected by HS-GC-IMS, whereas twelve compounds were detected by HS-GC-MS). However, IMS presented slightly better sensitivity (Limits of quantification (LOQ) ranged between 0.08 and 0.8 µg g−1 for HS-GC-IMS, and between 0.2 and 2.1 µg g−1 for HS-GC-MS). Finally, the potential of both detectors coupled with HS-GC for classification of olive oil samples depending on its quality was investigated. In this case, similar results were obtained when using both HS-GC-MS and HS-GC-IMS equipment (85.71 % of samples of the external validation set were classified correctly (validation rate)) and, although both techniques were shown to be complementary, data fusion did not improve validation results (80.95% validation rate).
Phytotoxicity of Essential Oils: Opportunities and Constraints for the Development of Biopesticides. A Review
Authors: Werrie Pierre-Yves , Durenne Bastien , Delaplace Pierre , Fauconnier Marie-Laure
Published: September 2020

The extensive use of chemical pesticides leads to risks for both the environment and human health due to the toxicity and poor biodegradability that they may present. Farmers therefore need alternative agricultural practices including the use of natural molecules to achieve more sustainable production methods to meet consumer and societal expectations. Numerous studies have reported the potential of essential oils as biopesticides for integrated weed or pest management. However, their phytotoxic properties have long been a major drawback for their potential applicability (apart from herbicidal application). Therefore, deciphering the mode of action of essential oils exogenously applied in regards to their potential phytotoxicity will help in the development of biopesticides for sustainable agriculture. Nowadays, plant physiologists are attempting to understand the mechanisms underlying their phytotoxicity at both cellular and molecular levels using transcriptomic and metabolomic tools. This review systematically discusses the functional and cellular impacts of essential oils applied in the agronomic context. Putative molecular targets and resulting physiological disturbances are described. New opportunities regarding the development of biopesticides are discussed including biostimulation and defense elicitation or priming properties of essential oils.
A Relativistic Orbit Model for Temporal Properties of AGN
Authors: Rana Prerna , Mangalam A.
Published: September 2020

We present a unified model for X-ray quasi-periodic oscillations (QPOs) seen in Narrow-line Seyfert 1 (NLSy1) galaxies, γ-ray and optical band QPOs that are seen in Blazars. The origin of these QPOs is attributed to the plasma motion in corona or jets of these AGN. In the case of X-ray QPOs, we applied the general relativistic precession model for the two simultaneous QPOs seen in NLSy1 1H 0707-945 and deduce orbital parameters, such the radius of the emission region, and spin parameter a for a circular orbit; we obtained the Carter’s constant Q, a, and the radius in the case of a spherical orbit solution. In other cases where only one X-ray QPO is seen, we localized the orbital parameters for NLSy1 galaxies REJ 1034+396, 2XMM J123103.2+110648, MS 2254.9-3712, Mrk 766, and MCG-06-30-15. By applying the lighthouse model, we found that a kinematic origin of the jet based γ-ray and optical QPOs, in a relativistic MHD framework, is possible. Based on the inbuilt Hamiltonian formulation with a power-law distribution in the orbital energy of the plasma consisting of only circular or spherical trajectories, we show that the resulting Fourier power spectral density (PSD) has a break corresponding to the energy at ISCO. Further, we derive connection formulae between the slopes in the PSD and that of the energy distribution. Overall, given the preliminary but promising results of these relativistic orbit models to match the observed QPO frequencies and PSD at diverse scales in the inner corona and the jet, it motivates us to build detailed models, including a transfer function for the energy spectrum in the corona and relativistic MHD jet models for plasma flow and its polarization properties.
Gel Volume Near the Critical Point of Binary Mixture Isobutyric Acid–Water
Authors: Yamamoto Takao , Noguchi Motoki , Maki Yasuyuki , Dobashi Toshiaki
Published: September 2020

The volume of a cylindrical polyacrylamide gel was measured when immersed in a binary mixture of isobutyric acid–water at different temperatures and weight fractions of isobutyric acid. Near the upper critical solution temperature of the binary mixture, the curve for gel volume vs. isobutyric acid weight fraction has a shoulder or a peak near the critical weight fraction. On the other hand, in a region away from the critical temperature, the gel volume decreased monotonically with increasing isobutyric acid weight fraction. The cloud point temperature of the binary mixture inside the gel was lower than that outside the gel. Thermodynamic description for the gel in the critical mixture is derived on the basis of the Ising model. By the description, the experimental results are explained consistently. The theoretical analysis shows that the shoulder and the peak appearing in the swelling behavior of the gel are respectively induced by the criticalities of the binary mixture outside and inside the gel. It also shows that the cloud point temperature lowering of the binary mixture inside the gel is attributed to the effective enhancement of the temperature of the binary mixture inside the gel induced by the presence of the gel polymer.
Bullying Victimization in Young Females with Fragile-X-Syndrome
Authors: Joga-Elvira Lorena , Jacas Carlos , Joga María-Luisa , Roche-Martínez Ana , Brun-Gasca Carme
Published: September 2020

The aim of this study is to investigate the risk associated with girls with fragile X syndrome (FXS) suffering bullying in the role of a victim and its effects on their adaptive behavior, socialization style, and emotional state. A neuropsychological assessment was carried out on a sample of 40 participants (26 FXS positive and 14 control group) using the following instruments: WISC-V, SENA, BAS-2, ABAS-II. The results show that the group of girls with FXS presented higher ratios of lack of social support and isolation from classmates. This finding suggests that problems with social interaction and communication in the group of girls with FXS could lead to difficulties in interpreting social signals and identifying situations of bullying correctly, placing them in a very vulnerable situation.
Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
Authors: Zhu Yitan , Brettin Thomas , Evrard Yvonne A. , Xia Fangfang , Partin Alexander , Shukla Maulik , Yoo Hyunseung , Doroshow James H. , Stevens Rick L.
Published: September 2020

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.
Foreign Body Ingestion: A Curious Case of the Missing Denture
Authors: Marquardt Patrick , Derousseau Taylor , Patel Neha
Published: September 2020

Foreign body ingestion is an under-recognized hazard in adults, especially in the elderly where it may lead to significant morbidity and even mortality. We present the case of an elderly patient who ingested her denture without any reported symptoms. After early recognition, endoscopic retrieval of the item was performed. We provide support for endoscopy as a safe and effective intervention for removing ingested foreign bodies in the geriatric population.
COVID-19 and Mental Well-Being: Guidance on the Application of Behavioral and Positive Well-Being Strategies
Authors: Kanekar Amar , Sharma Manoj
Published: September 2020

The raging COVID-19 pandemic has been a great source of anxiety, distress, and stress among the population. Along with mandates for social distancing and infection control measures, the growing importance of managing and cultivating good mental well-being practices cannot be disregarded. The purpose of this commentary is to outline and discuss some research-proven positive well-being and stress reduction strategies to instill healthy coping mechanisms among individuals and community members. The authors anticipate that usage of these strategies at the individual and the community level should greatly benefit the mental well-being not only in the current COVID-19 pandemic but also in any future epidemics at the national level.
Association between Periodontal Disease and Levels of Triglyceride and Total Cholesterol among Korean Adults
Authors: Kim Seon-Rye , Nam Seoul-Hee
Published: September 2020

Although the correlation between periodontal condition and hyperlipidemia was shown by previous researches, it remains disputed. This study was based on data from the seventh Korea National Health and Nutrition Examination Survey 2016–2018. Data included 14,068 subjects’ demographic characteristics, total cholesterol levels, triglyceride levels, and periodontal conditions. We analyzed the correlation between periodontal disease and blood lipid levels using complex-sample chi square tests and complex-sample logistic regression. The results of chi square tests showed a significant difference in demographic characteristics according to total cholesterol level and triglyceride level. The results of logistic regression, adjusted for the subjects’ demographic characteristics such as age, gender, house income, marital status, home ownership, number of persons living together, health insurance coverage, and economic activity, showed that prevalence of periodontal disease was 1.048-fold (confidence interval (CI) 0.827–1.133) higher in the high-total-cholesterol group and 1.499-fold (CI 1.576–1.983) higher in high-triglyceride group. We found that not high total cholesterol but high triglyceride level was connected with periodontal disease. Therefore, management of triglyceride level could be a possible precaution of periodontal disease.
Are Health Literacy and Lifestyle of Undergraduates Related to the Educational Field? An Italian Survey
Authors: Gallè Francesca , Calella Patrizia , Napoli Christian , Liguori Fabrizio , Parisi Eduardo Alfonso , Orsi Giovanni Battista , Liguori Giorgio , Valerio Giuliana
Published: September 2020

Background: Health literacy (HL) is a fundamental ability to successfully deal with health and illness issues. This study aimed to assess HL among undergraduates from healthcare and non-healthcare degree courses of two Italian universities and the association between their HL, lifestyles, and BMI assumed as health outcome. Methods: The Health Literacy Assessment Tool (HLAT-8) and the Newest Vital Sign (NVS) were used to assess health literacy dimensions. Demographic and anthropometric data, adherence to Mediterranean diet (MD), physical activity levels, and smoking habits were assessed in the enrolled sample to highlight possible associations. Results: A total sample of 806 undergraduates (46% males, mean age 21.01 ± 1.78 years) was recruited. Higher HL scores were found among healthcare rather than non-healthcare students (28.7 ± 4.5 vs. 26.7 ± 4.2 for HLAT-8 and 4.9 ± 1.5 vs. 3.9 ± 1.8 for NVS, p < 0.01). However, healthcare undergraduates were more likely to report unhealthy behaviors. Body Mass Index (BMI) was associated with literacy and numeracy skills only in non-healthcare undergraduates. Significant associations were found between HL scores and adherence to MD in both groups. In the regression analysis, educational field and MD were shown to be predictors of HL scores. Conclusions: Attending a healthcare related degree course was associated with higher HL scores but not with healthy behaviors. This issue should be addressed considering the role that healthcare professionals may have in educating patients towards a healthy lifestyle. Adherence to MD seems to be related to higher HL scores.
Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective
Authors: Cao Yuanyuan , Li Junjun , Qin Xinghong , Hu Baoliang
Published: September 2020

Aging has increased the burden of social medical care. Mobile health (mHealth) services provide an effective way to alleviate this pressure. However, the actual usage of mHealth services for elderly users is still very low. The extant studies mainly focused on elderly users’ mHealth adoption behavior, but resistance behavior has not been sufficiently explored by previous research. A present study tried to remedy this research gap by examining the effect of overload factors on the mHealth application resistance behavior based on the stimulus-organism-response (SOR) framework. The results indicated that information overload and system feature overload of an mHealth application increased the fatigue and technostress of the elderly user, which further increased their resistance behavior. Meanwhile, we integrated the intergeneration support with the SOR model to identify the buffer factor of the elderly user’s resistance behavior. The results showed that intergenerational support not only directly decrease the elderly user’s mHealth application resistance behavior, but also moderates (weaken) the effects of fatigue and technostress on resistance behavior. The present study also provided several valuable theoretical and practical implications.
Pharmacists’ Preparedness to Patients Education at the Time of Pandemic—A Cross-Sectional Study with an Example of SARS-CoV-2 Outbreak in Poland
Authors: Cerbin-Koczorowska Magdalena , Waszyk-Nowaczyk Magdalena , Przymuszała Piotr
Published: September 2020

Although pharmacy employees’ involvement in patient education has great potential, the extent to which they actually provide cognitive services seems inadequate. Given the overburdening of the healthcare system and limited access to medical services due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic outbreak, this study aimed to evaluate the preparedness of Polish pharmacy employees for patient education on the new threat. The study was conducted using the mystery shopper method. Two interviewers phoned 90 randomly chosen community pharmacies throughout Poland and presented some inquiries on the SARS-CoV-2. Pharmacists devoted more time to patients than pharmacy technicians (2:22 vs. 1:54), and the information they provided was significantly more comprehensive (p = 0.006). The majority of respondents provided an evidence-based recommendation on prevention, symptoms, and management of SARS-CoV-2; however, the scope of advice significantly varied. Community pharmacy staff often expressed their concern about the lack of time to address patients’ questions adequately. No statistically significant differences were found in recommendations provided by chain and non-chain pharmacy staff. Obtained results seem to confirm the possibility of involving pharmacists in public health activities during a pandemic. Nevertheless, providing proper working conditions and adequate just-in-time learning solutions is crucial.
Promoting Green Product Development Performance via Leader Green Transformationality and Employee Green Self-Efficacy: The Moderating Role of Environmental Regulation
Authors: Zhang Wengang , Sun Baiqing , Xu Feng
Published: September 2020

By integrating internal green self-efficacy and external environmental regulation, this research investigates the relationship between green transformational leadership and green product development performance. Taking 23 new energy vehicle enterprises in China as samples, we collected 298 valid questionnaires and verified the hypotheses through structural equation modeling. The results show that both green transformational leadership and green self-efficacy can promote green product development performance; green self-efficacy mediates the positive relationship between green transformational leadership and green product development performance, while environmental regulation positively moderates the mediating effect of green self-efficacy. Furthermore, environmental regulation and green self-efficacy interact to promote green product development performance. Our research provides a new perspective to understand how green transformational leadership is related to green product development performance and how this relationship is molded by contextual antecedents. Enterprises need to comprehensively consider the green influence of transformational leadership, green driving of employees themselves, and green linkage among organizations (macro policy guidance, passive market incentives, and self-issued actions) to improve green product development performance. Limitations and future scope are discussed.
Modeling Network Public Opinion Propagation with the Consideration of Individual Emotions
Authors: Fu Peihua , Jing Bailu , Chen Tinggui , Yang Jianjun , Cong Guodong
Published: September 2020

The occurrence of popular social events causes fluctuations and changes of public emotions, while the rapid development of online social platforms and networks has made individual interactions more intense and further escalated public emotions into public opinion. However, there is a lack of consideration of individual emotions in the current research on online public opinion. Based on this, this paper firstly expounds the quantitative representation of attitude and emotion, analyzes the formation and propagation process of online public opinion by combining individual’s expression willingness, individual’s expression ability, attitude perception value, attitude change probability and other factors, and constructs a network public opinion propagation model that takes individual emotion into consideration. Finally, the main factors affecting the formation and propagation of network public opinion are discussed through simulation experiments. The results demonstrate that: (1) fear is conducive to the formation of online public opinion, but the speed is relatively slow; sadness is not conducive to the formation, but once enough people participate in the exchange of views, the formation of online public opinion will be faster; (2) the influence of online public opinion on individual emotions expands with the increase of the number of individual interactions; (3) different network structures impact differently on the propagation of public opinion. Among them, BA (BA network is a scale-free network model proposed by Barabasi and Albert in order to explain the generation mechanism of power law, BA model has two characteristics: growth and priority connection mechanism) and ER (ER network is a network with random connectivity proposed by Erdös-Renyi) random networks can promote the propagation of online public opinion, which is prone to “one-sided” online public opinion. WS small-world networks (proposed by Watts and Strogatz. It is a kind of network with short average path length and high clustering coefficient) and fully-connected networks have an inhibitory effect on the spread of online public opinion, easily maintaining the multi-dimensional nature of online public opinion.