bluuebunny/crossref_metadata_2025 huggingface dataset:
Biosignal Compression Toolbox for Digital Biomarker Discovery
Authors: Bent Brinnae , Lu Baiying , Kim Juseong , Dunn Jessilyn P.
Published: January 2021

A critical challenge to using longitudinal wearable sensor biosignal data for healthcare applications and digital biomarker development is the exacerbation of the healthcare “data deluge,” leading to new data storage and organization challenges and costs. Data aggregation, sampling rate minimization, and effective data compression are all methods for consolidating wearable sensor data to reduce data volumes. There has been limited research on appropriate, effective, and efficient data compression methods for biosignal data. Here, we examine the application of different data compression pipelines built using combinations of algorithmic- and encoding-based methods to biosignal data from wearable sensors and explore how these implementations affect data recoverability and storage footprint. Algorithmic methods tested include singular value decomposition, the discrete cosine transform, and the biorthogonal discrete wavelet transform. Encoding methods tested include run-length encoding and Huffman encoding. We apply these methods to common wearable sensor data, including electrocardiogram (ECG), photoplethysmography (PPG), accelerometry, electrodermal activity (EDA), and skin temperature measurements. Of the methods examined in this study and in line with the characteristics of the different data types, we recommend direct data compression with Huffman encoding for ECG, and PPG, singular value decomposition with Huffman encoding for EDA and accelerometry, and the biorthogonal discrete wavelet transform with Huffman encoding for skin temperature to maximize data recoverability after compression. We also report the best methods for maximizing the compression ratio. Finally, we develop and document open-source code and data for each compression method tested here, which can be accessed through the Digital Biomarker Discovery Pipeline as the “Biosignal Data Compression Toolbox,” an open-source, accessible software platform for compressing biosignal data.
A Maximum-Information-Minimum-Redundancy-Based Feature Fusion Framework for Ship Classification in Moderate-Resolution SAR Image
Authors: Zhou Gaoyu , Zhang Gong , Xue Biao
Published: January 2021

High-resolution synthetic aperture radar (SAR) images are mostly used in the current field of ship classification, but in practical applications, moderate-resolution SAR images that can offer wider swath are more suitable for maritime surveillance. The ship targets in moderate-resolution SAR images occupy only a few pixels, and some of them show the shape of bright spots, which brings great difficulty for ship classification. To fully explore the deep-level feature representations of moderate-resolution SAR images and avoid the “dimension disaster”, we innovatively proposed a feature fusion framework based on the classification ability of individual features and the efficiency of overall information representation, called maximum-information-minimum-redundancy (MIMR). First, we applied the Filter method and Kernel Principal Component Analysis (KPCA) method to form two feature subsets representing the best classification ability and the highest information representation efficiency in linear space and nonlinear space. Second, the MIMR feature fusion method is adopted to assign different weights to feature vectors with different physical properties and discriminability. Comprehensive experiments on the open dataset OpenSARShip show that compared with traditional and emerging deep learning methods, the proposed method can effectively fuse non-redundant complementary feature subsets to improve the performance of ship classification in moderate-resolution SAR images.
An Optimal Parameter Selection Method for MOMEDA Based on EHNR and Its Spectral Entropy
Authors: Li Zhuorui , Ma Jun , Wang Xiaodong , Li Xiang
Published: January 2021

As a vital component widely used in the industrial production field, rolling bearings work under complicated working conditions and are prone to failure, which will affect the normal operation of the whole mechanical system. Therefore, it is essential to conduct a health assessment of the rolling bearing. In recent years, Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) is applied to the fault feature extraction for rolling bearings. However, the algorithm still has the following problems: (1) The selection of fault period T depends on prior knowledge. (2) The accuracy of signal denoising is affected by filter length L. To solve the limitations, an improved MOMEDA (IMOMEDA) method is proposed in this paper. Firstly, the envelope harmonic-to-noise ratio (EHNR) spectrum is adopted to estimate the fault period of MOMEDA. Then, the improved grid search method with EHNR spectral entropy as the objective function is constructed to calculate the optimal filter length used in the MOMEDA. Finally, a feature extraction method based on the improved MOMEDA (IMOMEDA) and Teager-Kaiser energy operator (TKEO) is applied in the field of rolling bearing fault diagnosis. The effectiveness and generalization performance of the proposed method is verified through comparison experiment with three data sets.
Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication
Authors: Xu Zhengjia , Petrunin Ivan , Tsourdos Antonios
Published: January 2021

In anticipation of wide implementation of 5G technologies, the scarcity of spectrum resources for the unmanned aerial vehicles (UAVs) communication remains one of the major challenges in arranging safe drone operations. Dynamic spectrum management among multiple UAVs as a tool that is able to address this issue, requires integrated solutions with considerations of heterogeneous link types and support of the multi-UAV operations. This paper proposes a synthesized resource allocation and opportunistic link selection (RA-OLS) scheme for the air-to-ground (A2G) UAV communication with dynamic link selections. The link opportunities using link hopping sequences (LHSs) are allocated in the GCSs for alleviating the internal collisions within the UAV network, offloading the on-board computations in the spectrum processing function, and avoiding the contention in the air. In this context, exclusive technical solutions are proposed to form the prototype system. A sub-optimal allocation method based on the greedy algorithm is presented for addressing the resource allocation problem. A mathematical model of the RA-OLS throughput with above propositions is formulated for the spectrum dense and scarce environments. An interference factor is introduced to measure the protection effects on the primary users. The proposed throughput model approximates the simulated communication under requirements of small errors in the spectrum dense environment and the spectrum scarce environment, where the sensitivity analysis is implemented. The proposed RA-OLS outperforms the static communication scheme in terms of the utilization rate by over 50% in case when multiple links are available. It also enables the collaborative communication when the spectral resources are in scarcity. The impacts from diverse parameters on the RA-OLS communication performance are analyzed.
Energy-Efficient Hybrid Routing Protocol for IoT Communication Systems in 5G and Beyond
Authors: Baniata Mohammad , Reda Haftu Tasew , Chilamkurti Naveen , Abuadbba Alsharif
Published: January 2021

One of the major concerns in wireless sensor networks (WSNs) is most of the sensor nodes are powered through limited lifetime of energy-constrained batteries, which majorly affects the performance, quality, and lifetime of the network. Therefore, diverse clustering methods are proposed to improve energy efficiency of the WSNs. In the meantime, fifth-generation (5G) communications require that several Internet of Things (IoT) applications need to adopt the use of multiple-input multiple-output (MIMO) antenna systems to provide an improved capacity over multi-path channel environment. In this paper, we study a clustering technique for MIMO-based IoT communication systems to achieve energy efficiency. In particular, a novel MIMO-based energy-efficient unequal hybrid clustering (MIMO-HC) protocol is proposed for applications on the IoT in the 5G environment and beyond. Experimental analysis is conducted to assess the effectiveness of the suggested MIMO-HC protocol and compared with existing state-of-the-art research. The proposed MIMO-HC scheme achieves less energy consumption and better network lifetime compared to existing techniques. Specifically, the proposed MIMO-HC improves the network lifetime by approximately 3× as long as the first node and the final node dies as compared with the existing protocol. Moreover, the energy that cluster heads consume on the proposed MIMO-HC is 40% less than that expended in the existing protocol.
Towards Providing Effective Data-Driven Responses to Predict the Covid-19 in São Paulo and Brazil
Authors: Amaral Fabio , Casaca Wallace , Oishi Cassio M. , Cuminato José A.
Published: January 2021

São Paulo is the most populous state in Brazil, home to around 22% of the country’s population. The total number of Covid-19-infected people in São Paulo has reached more than 1 million, while its total death toll stands at 25% of all the country’s fatalities. Joining the Brazilian academia efforts in the fight against Covid-19, in this paper we describe a unified framework for monitoring and forecasting the Covid-19 progress in the state of São Paulo. More specifically, a freely available, online platform to collect and exploit Covid-19 time-series data is presented, supporting decision-makers while still allowing the general public to interact with data from different regions of the state. Moreover, a novel forecasting data-driven method has also been proposed, by combining the so-called Susceptible-Infectious-Recovered-Deceased model with machine learning strategies to better fit the mathematical model’s coefficients for predicting Infections, Recoveries, Deaths, and Viral Reproduction Numbers. We show that the obtained predictor is capable of dealing with badly conditioned data samples while still delivering accurate 10-day predictions. Our integrated computational system can be used for guiding government actions mainly in two basic aspects: real-time data assessment and dynamic predictions of Covid-19 curves for different regions of the state. We extend our analysis and investigation to inspect the virus spreading in Brazil in its regions. Finally, experiments involving the Covid-19 advance in other countries are also given.
Computerized Assessment of Occlusion and Muscle Activity during Use of a Multilayer Clear Retainer: A Preliminary Study
Authors: Kim Kyoung Yeon , Choi Jin-Young , Oh Song Hee , Moon Hyung-Wook , Kim Seong-Hun , Ahn Hyo-Won , Kim Kyung A , Nelson Gerald
Published: January 2021

The aim of this preliminary study was to evaluate the short-term changes of occlusal contacts and muscle activity after orthodontic treatment during the use of a multi-layer clear retainer. Evaluation was done with the T-scan and BioEMG systems. A total of 18 subjects were included, who were evaluated at three time intervals—T0 at debonding, T1 at one month after retainer delivery, and T2 at four months after retainer delivery. The T-scan and electromyography (EMG) data were recorded simultaneously. The T-scan system recorded the occlusion time, disclusion time and force distribution. The EMG waves were quantified by calculating the asymmetry index and activity index. The time variables changed but not significantly. Occlusal force decreased in the anterior dentition and increased in the posterior dentition during T0–T2. There was no clear evidence of a relationship between unbalanced occlusal forces and muscle activity. In most subjects, the temporalis anterior muscle was more dominant than the masseter muscle. From this preliminary computerized study, there were no significant changes in the state of the occlusion or muscle activity during the short-term retention period.
High-Availability Computing Platform with Sensor Fault Resilience
Authors: Lee Yen-Lin , Arizky Shinta Nuraisya , Chen Yu-Ren , Liang Deron , Wang Wei-Jen
Published: January 2021

Modern computing platforms usually use multiple sensors to report system information. In order to achieve high availability (HA) for the platform, the sensors can be used to efficiently detect system faults that make a cloud service not live. However, a sensor may fail and disable HA protection. In this case, human intervention is needed, either to change the original fault model or to fix the sensor fault. Therefore, this study proposes an HA mechanism that can continuously provide HA to a cloud system based on dynamic fault model reconstruction. We have implemented the proposed HA mechanism on a four-layer OpenStack cloud system and tested the performance of the proposed mechanism for all possible sets of sensor faults. For each fault model, we inject possible system faults and measure the average fault detection time. The experimental result shows that the proposed mechanism can accurately detect and recover an injected system fault with disabled sensors. In addition, the system fault detection time increases as the number of sensor faults increases, until the HA mechanism is degraded to a one-system-fault model, which is the worst case as the system layer heartbeating.
Effects of Carbon Emissions, Environmental Disclosures and CSR Assurance on Cost of Equity in Emerging Markets
Authors: Garzón-Jiménez Renato , Zorio-Grima Ana
Published: January 2021

The objective of the paper is to empirically test the relation between carbon emissions, environmental disclosures, assurance of sustainability reports and firms’ Cost of Equity (COE) measured by an Ex-Ante proxy model. The methodological approach uses the Generalized Method of Moments (GMM) required to control endogeneity problems using a sample of 929 firms that are included in the Morgan Stanley Emerging Market Index. The data panel includes 5328 observations from 30 emerging countries covering the period 2014 to 2019. Our results indicate that firms with higher carbon emissions have higher COE, which implies that capital providers penalize highly polluting firms. Contrarily, evidence shows that firms with greater environmental disclosures, and the those who externally assure their corporate social responsibility reports decrease their COE. Our study expands the literature regarding carbon emissions and its relation with firms’ COE from an emerging market perspective covering a multi-country sample, with findings that confirm that higher emitters are penalized in terms of COE. Moreover, our research confirms in this setting the negative relation between environmental, social and governance disclosure scores and COE. Moreover, we evidence as well that the assurance of sustainability reports also promotes legitimacy and decreases information asymmetries, in the sense of reducing COE. The value of our findings is especially relevant as it may encourage listed companies in emerging countries to engage in more sustainable practices—e.g., reduce carbon emissions.
Signaling Value through Gender Diversity: Evidence from Initial Coin Offerings
Authors: Guzmán Alexander , Pinto-Gutiérrez Cristian , Trujillo María-Andrea
Published: January 2021

We analyze women’s participation and the effects of team gender diversity on initial coin offering (ICO) success measured by the total funding amount raised in the actual ICO and the project’s long-term survival. Using a database featuring 875 initial coin offerings between 2017 and 2019, we find that women are significantly under-represented in ICO projects (on average, only 13% of team members are women). However, for projects that do have participation of women, we find that team gender diversity increases the total funding raised in the ICO. Moreover, when we separate team members into areas of expertise or roles in the project, we find that the presence of women in critical positions, such as being a founder or having financial or legal responsibilities, significantly reduces the likelihood of long-term coin failure. Our results are consistent with the notion that investors perceive women’s participation in leadership positions as a positive signal of desirable organizational practices that will translate into better performance. Our results are also consistent with the idea that having women, who abide by ethical values and are less prone to fraud, reduces the likelihood that informationally opaque ICOs turn out to be scams.
Technology-Enhanced Airport Services—Attractiveness from the Travelers’ Perspective
Authors: Miskolczi Márk , Jászberényi Melinda , Tóth Dávid
Published: January 2021

The rapid emergence of automation brings new opportunities for airport development. Airports strive to maximize passenger satisfaction as well as optimize their operation. However, the lack of knowledge of consumer preferences might be an important barrier to achieve these objectives. Therefore, our study aims to unveil the potential of service development alternatives based on artificial intelligence (AI). For this, a systematic literature review (SLR) and a quantitative analysis of a survey have been conducted. The results of the empirical research are based on 593 responses; most of the subjects belong to generation Z (digital natives) and Y (millennials). The analysis revealed attitudes towards different AI-based transport solutions and AI robots that provide information at the airports. Based on the perceived attractiveness of such services, the environmentally conscious behaviour of consumers, and sociodemographic data, subjects were classified into three different clusters (Negligents, AV Enthusiasts, and Robot Fanatics). Results proved the attractiveness of AI-based transport services that can be used in the air-side zone. Among the millennials, the idea of self-driving buses running between airport terminals is the most appealing. Greater interest in AI-based communication solutions can be perceived among generation Z. For both generations, environmentally conscious consumption is also of paramount importance. The attractiveness of AI-based solutions has been analyzed in a tourist environment, which might be a good starting point for further research into the technology acceptance of AI-based services.
Why I Would Want to Live in the Village If I Was Not Interested in Cultivating the Plot? A Study of Home Gardening in Rural Czechia
Authors: Vávra Jan , Smutná Zdeňka , Hruška Vladan
Published: January 2021

Unsustainable food practices in the global North have brought a lot of attention to the concept of alternative food networks. However, prevailing research perspectives have focused on urban areas or market-related activities and tended to overlook the widespread yet neglected food growing in home gardens, especially in rural areas. This paper uses a mixed method approach to study home gardening in two villages in Czechia, focusing on the state of the art of gardening, its sustainability context, and the perception of gardening by the local citizens. We have found that the vast majority of households grow fruit and vegetables, while livestock is also present. Home grown food, which has a supplemental character, is mostly shared within networks of relatives. An understanding of food production as a part of rural identity and tradition is an important element of the perception of gardening. Our findings contribute to the rich debates about the sustainability of food systems. The paper is innovative because it steps outside of the typical poverty or food security discourse of rural informal food production, as well it reveals information on livestock breeding, discusses home gardening in the context of rural development and food policies, and emancipates the semi-peripheral locality as a regular source of new knowledge.
Income Redistribution Effect of Raising the Overall Planning Level of Basic Endowment Insurance for Urban Employees in China
Authors: Yu Wenguang , Li Bing , Zhu Xianghan
Published: January 2021

It is the focus of social security system reform at this stage in China to promote the transition of basic endowment insurance for urban employees from provincial overall planning level to national overall planning level, which is of great significance to the realization of fair and efficient of economic development. Based on the micro data of China Household Finance Survey 2017 (CHFS2017), this paper first establishes a personal wage prediction model to estimate the distribution of personal lifetime wage income, then designs two pension collection and payment plans of “direct national overall planning” and “indirect national overall planning”, and establishes an actuarial model of pension to calculate the present value of personal lifetime contribution, lifetime claim and lifetime real wage income after pension adjustment under different overall planning levels. Finally, the income gap index and net benefit rate index are used to measure the change of the whole income gap and the transfer of pension benefits. The results show that on the whole, the basic endowment insurance for urban employees does have a significant income redistribution effect, and its income adjustment effect is positively related to the overall planning level and intensity of the system. Under the current provincial overall planning level, the income redistribution effects of the system are as follows: the high-income group transfers to the low-income group, the young generation to the elderly generation, the female insured person to the male insured person, and the non-state-owned economic unit to the state-owned economic unit. With the improvement of the overall planning level and strengthening of intensity, there are differences in the changes of benefits among different groups.
A Literature Evaluation of Systemic Challenges Affecting the European Maritime Energy Transition
Authors: Bergsma Jurrit M. , Pruyn Jeroen , van de Kaa Geerten
Published: January 2021

Energy transition is affecting the European maritime sector at an increasing rate. New technologies and regulations are being introduced with increasing speed. The ability to adapt to these changes is crucial for the economic success of the maritime sector. However, the sector is challenged by inertia due to its global nature and long-life assets (e.g., vessels). These developments result in a globally projected greenhouse gas emission growth rather than a reduction towards 2050. The sector can be considered essential to economic prosperity, but its innovation system should align with global sustainability trends. This article aims to structure and evaluate the maritime sector’s systemic challenges by conducting an extensive systematic review of (sustainable) maritime innovation literature. These findings are structured and discussed via four key activities that support the transition process: developing strategy and policy, creating legitimacy, mobilizing resources, and developing and disseminating knowledge.
Early-Stage Neural Network Hardware Performance Analysis
Authors: Karbachevsky Alex , Baskin Chaim , Zheltonozhskii Evgenii , Yermolin Yevgeny , Gabbay Freddy , Bronstein Alex M. , Mendelson Avi
Published: January 2021

The demand for running NNs in embedded environments has increased significantly in recent years due to the significant success of convolutional neural network (CNN) approaches in various tasks, including image recognition and generation. The task of achieving high accuracy on resource-restricted devices, however, is still considered to be challenging, which is mainly due to the vast number of design parameters that need to be balanced. While the quantization of CNN parameters leads to a reduction of power and area, it can also generate unexpected changes in the balance between communication and computation. This change is hard to evaluate, and the lack of balance may lead to lower utilization of either memory bandwidth or computational resources, thereby reducing performance. This paper introduces a hardware performance analysis framework for identifying bottlenecks in the early stages of CNN hardware design. We demonstrate how the proposed method can help in evaluating different architecture alternatives of resource-restricted CNN accelerators (e.g., part of real-time embedded systems) early in design stages and, thus, prevent making design mistakes.
Better Managers for More Sustainability Sports Organizations: Validation of Sports Managers Competency Scale (COSM) in Chile
Authors: Duclos-Bastías Daniel , Giakoni-Ramírez Frano , Parra-Camacho David , Rendic-Vera Wladimir , Rementería-Vera Norman , Gajardo-Araya Guillermo
Published: January 2021

The aim of this study is to analyze the validity and reliability of the scale of competences of sports managers (COSM) in the Chilean context. The adaptation of the COSM to Spanish was carried out in accordance with the international methodological standards. A Spanish pilot version of the instrument was then administered to 33 municipal sports managers, whose comments on the instructions and the way the articles were written resulted in minor changes. Finally, this last version was empirically applied to 212 municipal sports managers (82.5% men and 17.5% women) from 129 city councils in 16 regions of Chile who participated. The original instrument consisted of 31 items grouped in six dimensions. The analyses carried out to check the psychometric properties of the scale determined the grouping of the indicators in three dimensions, retaining 22 items from the original proposal. The new factors were: Sports and Facilities Use Regulation (12 items), Budget Management (five items), and Communication Skills (five items). The scale presented adequate goodness-of-fit indices according to the parameters recommended by the literature, as well as optimal values of the different reliability measures. The use of this instrument will contribute to the process of diagnosis of competences in sport managers, with the purpose of planning relevant and contextualized training strategies that aim at improving skills and knowledge related to professional work. Likewise, the instrument can be used by the Chilean academic community in research processes involving sport managers’ competences.
Investigating the Anisotropy of Mechanical Parameters of Schist Rock with Practical Numerical Methods
Authors: Cui Zhen , Sheng Qian , Luo Qingzi , Zhang Guimin
Published: January 2021

The anisotropy of deformation and strength behavior in quartz mica schist is fundamental to rock mechanics. Here, we concentrated on the practical application of the numerical simulation of the anisotropy of schist rock. First, the existence of the anisotropy of the schist rock in engineering application was reported, tested in situ, and analyzed. Then, a set of specially designed multi-angle uniaxial compression tests was conducted. Based on these, two numerical simulation methods (explicit and implicit) for anisotropy were demonstrated and discussed. Between the two methods, the implicit method was more practical. Ultimately, the implicit method was adopted to perform an excavation simulation of the exploratory tunnel CPD-1. Our findings demonstrated the feasibility of the implicit method as a practical numerical method to determine the anisotropy of schist rock.
A Review of Synchronous Reluctance Motor-Drive Advancements
Authors: Heidari Hamidreza , Rassõlkin Anton , Kallaste Ants , Vaimann Toomas , Andriushchenko Ekaterina , Belahcen Anouar , Lukichev Dmitry V.
Published: January 2021

Recent studies show that synchronous reluctance motors (SynRMs) present promising technologies. As a result, research on trending SynRMs drive systems has expanded. This work disseminates the recent developments of design, modeling, and more specifically, control of these motors. Firstly, a brief study of the dominant motor technologies compared to SynRMs is carried out. Secondly, the most prominent motor control methods are studied and classified, which can come in handy for researchers and industries to opt for a proper control method for motor drive systems. Finally, the control strategies for different speed regions of SynRM are studied and the transitions between trajectories are analyzed.
Leadership Style in Amateur Club Sports: A Key Element in Strategic Management
Authors: Martínez-Moreno Alfonso , Cavas-García Francisco , Díaz-Suárez Arturo
Published: January 2021

Leadership is key in sports management, as it allows organizations to endure over time. Leadership style determines how an organization or sports club works. The purpose of this study is to investigate employees’ perceptions of the leadership style of presidents (managers) in amateur clubs and how it influences the effort, efficiency and satisfaction of those employees. The sample consists of club managers (N = 334), of whom 286 are men and 48 are women, with an average age of 42.05 (±9.64). The subordinate version of the Multifactorial Leadership Questionnaire is used, and it is found that club presidents mostly use the transformational style, regardless of sports discipline. A descriptive analysis of the qualitative variables consists of absolute and relative frequencies. ANOVA is used for comparisons between groups, and forward multiple regression is used to determine the effects of different variables. There are significant differences between the managers of collective and individual sports clubs in terms of efficiency (p = 0.014) and satisfaction (p = 0.04). Leadership style had significant effects on effort, effectiveness and satisfaction, while the genre and type of sport did not, corroborating the positive predictive power of the transformational and transactional styles. Transformational and transactional leadership styles positively and statistically significantly predict the extra effort of subordinates, the perceived effectiveness of leadership and satisfaction with the leader. Leadership training brings advantages in the stability and sustainability of sports clubs.
Sustainability and Branding: An Integrated Perspective of Eco-innovation and Brand
Authors: Loučanová Erika , Šupín Mikuláš , Čorejová Tatiana , Repková-Štofková Katarína , Šupínová Mária , Štofková Zuzana , Olšiaková Miriam
Published: January 2021

Eco-innovation presents a tool that helps companies to transform environmental constraints into opportunities and advantages such as cost reduction, better reputation, and benefit for new markets. The purpose of the paper is to evaluate the perception of eco-innovation and green brands in the context of sustainability in Slovakia and their mutual relation. The applied research focused on the perception of eco-innovation and green brands. The survey was realized by the Kano model that provides customers’ opinions regarding the requirements of the monitored object. In our case, the research object is ecological innovation evaluated in terms of selected parameters. To generalize the relationships among examined parameters, cluster analysis was applied to identify clusters of examined parameters of ecological innovations. The aim of the contribution is to present the output of the cluster analysis in a form of a dendrogram showing a graphical grouping of related objects in three clusters that include examined parameters according to their perception by customers.
Analysis of Fractal Structures in Dehydrated Films of Protein Solutions
Authors: Baranov Maksim , Velichko Elena , Greshnevikov Konstantin
Published: January 2021

The article deals with dendritic structures resulting from self-organization processes in aqueous solutions of albumin proteins. The methods for obtaining the structures and experimental results are presented. It is shown that dendrites are fractal structures that are symmetric under certain conditions of their formation and can have different characteristics depending on the isothermal dehydration of liquid samples. The fractal dimension of the structures in films of the albumin protein solution has been calculated. Dependences of the fractal dimension on the concentrations of salts and protein in the initial solutions and also on the dehydration temperature have been revealed. It has been shown that as the protein concentration in the solution grows, the salt concentration for the initiation of the dendritic structure formation increases. It has been found that the temperature dependences of the fractal dimension of the structures become smoother with increasing protein concentration in solutions. The relationship between geometric characteristics of dendrites and self-organization parameters during drying is discussed.
An Efficient Login Authentication System against Multiple Attacks in Mobile Devices
Authors: Li Yang , Yun Xinyu , Fang Liming , Ge Chunpeng
Published: January 2021

Access management of IoT devices is extremely important, and a secure login authentication scheme can effectively protect users’ privacy. However, traditional authentication schemes are threatened by shoulder-surfing attacks, and biometric-based schemes, such as fingerprint recognition and face recognition, that are commonly used today can also be cracked. Researchers have proposed some schemes for current attacks, but they are limited by usability. For example, the login authentication process requires additional device support. This method solves the problem of attacks, but it is unusable, which limits its application. At present, most authentication schemes for the Internet of Things and mobile platforms either focus on security, thus ignoring availability, or have excellent convenience but insufficient security. This is a symmetry problem worth exploring. Therefore, users need a new type of login authentication scheme that can balance security and usability to protect users’ private data or maintain device security. In this paper, we propose a login authentication scheme named PinWheel, which combines a textual password, a graphical password, and biometrics to prevent both shoulder-surfing attacks and smudge attacks and solves the current schemes’ lack of usability. We implemented PinWheel and evaluated it from the perspective of security and usability. The experiments required 262 days, and 573 subjects participated in our investigation. The evaluation results show that PinWheel can at least effectively resist both mainstream attacks and is superior to most existing schemes in terms of usability.
Investigating Multi-Mycotoxin Exposure in Occupational Settings: A Biomonitoring and Airborne Measurement Approach
Authors: Ndaw Sophie , Jargot Daniele , Antoine Guillaume , Denis Flavien , Melin Sandrine , Robert Alain
Published: January 2021

Investigating workplace exposure to mycotoxins is of the utmost importance in supporting the implementation of preventive measures for workers. The aim of this study was to provide tools for measuring mycotoxins in urine and airborne samples. A multi-class mycotoxin method was developed in urine for the determination of aflatoxin B1, aflatoxin M1, ochratoxin A, ochratoxin α, deoxynivalenol, zearalenone, α-zearalenol, β-zearalenol, fumonisin B1, HT2-toxin and T2-toxin. Analysis was based on liquid chromatography–high resolution mass spectrometry. Sample pre-treatments included enzymatic digestion and an online or offline sample clean-up step. The method was validated according to the European Medicines Agency guidance procedures. In order to estimate external exposure, air samples collected with a CIP 10 (Capteur Individuel de Particules 10) personal dust sampler were analyzed for the quantification of up to ten mycotoxins, including aflatoxins, ochratoxin A, deoxynivalenol, zearalenone, fumonisin B1 and HT-2 toxin and T-2 toxin. The method was validated according to standards for workplace exposure to chemical and biological agents EN 482. Both methods, biomonitoring and airborne mycotoxin measurement, showed good analytical performances. They were successfully applied in a small pilot study to assess mycotoxin contamination in workers during cleaning of a grain elevator. We demonstrated that this approach was suitable for investigating occupational exposure to mycotoxins.
Mapping the DNA-Binding Motif of Scabin Toxin, a Guanine Modifying Enzyme from Streptomyces scabies
Authors: Vatta Maritza , Lyons Bronwyn , Heney Kayla A. , Lidster Taylor , Merrill A. Rod
Published: January 2021

Scabin is a mono-ADP-ribosyltransferase toxin/enzyme and possible virulence factor produced by the agriculture pathogen, Streptomyces scabies. Recently, molecular dynamic approaches and MD simulations revealed its interaction with both NAD+ and DNA substrates. An Essential Dynamics Analysis identified a crab-claw-like mechanism, including coupled changes in the exposed motifs, and the Rβ1-RLa-NLc-STTβ2-WPN-WARTT-(QxE)ARTT sequence motif was proposed as a catalytic signature of the Pierisin family of DNA-acting toxins. A new fluorescence assay was devised to measure the kinetics for both RNA and DNA substrates. Several protein variants were prepared to probe the Scabin-NAD-DNA molecular model and to reveal the reaction mechanism for the transfer of ADP-ribose to the guanine base in the DNA substrate. The results revealed that there are several lysine and arginine residues in Scabin that are important for binding the DNA substrate; also, key residues such as Asn110 in the mechanism of ADP-ribose transfer to the guanine base were identified. The DNA-binding residues are shared with ScARP from Streptomyces coelicolor but are not conserved with Pierisin-1, suggesting that the modification of guanine bases by ADP-ribosyltransferases is divergent even in the Pierisin family.
Botulinum Toxin: An Update on Pharmacology and Newer Products in Development
Authors: Choudhury Supriyo , Baker Mark R. , Chatterjee Suparna , Kumar Hrishikesh
Published: January 2021

Since its introduction as a treatment for strabismus, botulinum toxin (BoNT) has had a phenomenal journey and is now recommended as first-line treatment for focal dystonia, despite short-term clinical benefits and the risks of adverse effects. To cater for the high demand across various medical specialties, at least six US Food and Drug Administration (FDA)-approved formulations of BoNT are currently available for diverse labelled indications. The toxo-pharmacological properties of these formulations are not uniform and thus should not be used interchangeably. Synthetic BoNTs and BoNTs from non-clostridial sources are not far from clinical use. Moreover, the study of mutations in naturally occurring toxins has led to modulation in the toxo-pharmacokinetic properties of BoNTs, including the duration and potency. We present an overview of the toxo-pharmacology of conventional and novel BoNT preparations, including those awaiting imminent translation from the laboratory to the clinic.
Canine Distemper Outbreaks in Wild Carnivores in Northern Italy
Authors: Trogu Tiziana , Canziani Sabrina , Salvato Sara , Bianchi Alessandro , Bertoletti Irene , Gibelli Lucia Rita , Alborali Giovanni Loris , Barbieri Ilaria , Gaffuri Alessandra , Sala Giovanni , Sozzi Enrica , Lelli Davide , Lavazza Antonio , Moreno Ana
Published: January 2021

Canine distemper (CD) is a fatal, highly contagious disease of wild and domestic carnivores. In the Alpine territory, several outbreaks have occurred in the past few decades within wild populations. This study investigated the presence of canine distemper virus (CDV) infections in wild carnivores in Lombardy, relating to the different circulating genotypes. From 2018 to 2020, foxes, badgers, and martens collected during passive surveillance were subjected to necropsy and histological examination, showing classical signs and microscopic lesions related to CDV. Pools of viscera from each animal were analysed by molecular methods and immunoelectron microscopy. Total prevalences of 39.7%, 52.6%, and 14.3% were recorded in foxes, badgers, and stone martens, respectively. A phylogenetic analysis showed that the sequences obtained belonged to the European 1 lineage and were divided into two different clades (a and b) according to the geographical conformation of alpine valleys included in the study. Clade a was related to the European outbreaks originating from Germany in 2006–2010, while clade b was closely related to the CDV sequences originating from northeastern Italy during the 2011–2018 epidemic wave. Our results suggest that CDV is currently well adapted to wild carnivores, mostly circulating with subclinical manifestations and without severe impact on the dynamics of these populations.
An Advanced Protocol for the Quantification of Marine Sediment Viruses via Flow Cytometry
Authors: Heinrichs Mara Elena , De Corte Daniele , Engelen Bert , Pan Donald
Published: January 2021

Viruses are highly abundant, diverse, and active components of marine environments. Flow cytometry has helped to increase the understanding of their impact on shaping microbial communities and biogeochemical cycles in the pelagic zone. However, to date, flow cytometric quantification of sediment viruses is still hindered by interference from the sediment matrix. Here, we developed a protocol for the enumeration of marine sediment viruses by flow cytometry based on separation of viruses from sediment particles using a Nycodenz density gradient. Results indicated that there was sufficient removal of background interference to allow for flow cytometric quantification. Applying this new protocol to deep-sea and tidal-flat samples, viral abundances enumerated by flow cytometry correlated well (R2 = 0.899) with counts assessed by epifluorescence microscopy over several orders of magnitude from marine sediments of various compositions. Further optimization may be needed for sediments with low biomass or high organic content. Overall, the new protocol enables fast and accurate quantification of marine sediment viruses, and opens up the options for virus sorting, targeted viromics, and single-virus sequencing.
Surveillance and Genetic Characterization of Virulent Newcastle Disease Virus Subgenotype V.3 in Indigenous Chickens from Backyard Poultry Farms and Live Bird Markets in Kenya
Authors: Kariithi Henry M. , Ferreira Helena L. , Welch Catharine N. , Ateya Leonard O. , Apopo Auleria A. , Zoller Richard , Volkening Jeremy D. , Williams-Coplin Dawn , Parris Darren J. , Olivier Tim L. , Goldenberg Dana , Binepal Yatinder S. , Hernandez Sonia M. , Afonso Claudio L. , Suarez David L.
Published: January 2021

Kenyan poultry consists of ~80% free-range indigenous chickens kept in small flocks (~30 birds) on backyard poultry farms (BPFs) and they are traded via live bird markets (LBMs). Newcastle disease virus (NDV) was detected in samples collected from chickens, wild farm birds, and other domestic poultry species during a 2017–2018 survey conducted at 66 BPFs and 21 LBMs in nine Kenyan counties. NDV nucleic acids were detected by rRT-PCR L-test in 39.5% (641/1621) of 1621 analyzed samples, of which 9.67% (62/641) were NDV-positive by both the L-test and a fusion-test designed to identify the virulent virus, with a majority being at LBMs (64.5%; 40/62) compared to BPFs (25.5%; 22/62). Virus isolation and next-generation sequencing (NGS) on a subset of samples resulted in 32 complete NDV genome sequences with 95.8–100% nucleotide identities amongst themselves and 95.7-98.2% identity with other east African isolates from 2010-2016. These isolates were classified as a new sub-genotype, V.3, and shared 86.5–88.9% and 88.5–91.8% nucleotide identities with subgenotypes V.1 and V.2 viruses, respectively. The putative fusion protein cleavage site (113R-Q-K-R↓F 117) in all 32 isolates, and a 1.86 ICPI score of an isolate from a BPF chicken that had clinical signs consistent with Newcastle disease, confirmed the high virulence of the NDVs. Compared to genotypes V and VI viruses, the attachment (HN) protein of 18 of the 32 vNDVs had amino acid substitutions in the antigenic sites. A time-scaled phylogeographic analysis suggests a west-to-east dispersal of the NDVs via the live chicken trade, but the virus origins remain unconfirmed due to scarcity of continuous and systematic surveillance data. This study reveals the widespread prevalence of vNDVs in Kenyan backyard poultry, the central role of LBMs in the dispersal and possibly generation of new virus variants, and the need for robust molecular epidemiological surveillance in poultry and non-poultry avian species.
Systematic Search for SARS-CoV-2 Main Protease Inhibitors for Drug Repurposing: Ethacrynic Acid as a Potential Drug
Authors: Isgrò Camilla , Sardanelli Anna Maria , Palese Luigi Leonardo
Published: January 2021

In 2019 an outbreak occurred which resulted in a global pandemic. The causative agent has been identified in a virus belonging to the Coronaviridae family, similar to the agent of SARS, referred to as SARS-CoV-2. This epidemic spread rapidly globally with high morbidity and mortality. Although vaccine development is at a very advanced stage, there are currently no truly effective antiviral drugs to treat SARS-CoV-2 infection. In this study we present systematic and integrative antiviral drug repurposing effort aimed at identifying, among the drugs already authorized for clinical use, some active inhibitors of the SARS-CoV-2 main protease. The most important result of this analysis is the demonstration that ethacrynic acid, a powerful diuretic, is revealed to be an effective inhibitor of SARS-CoV-2 main protease. Even with all the necessary cautions, given the particular nature of this drug, these data can be the starting point for the development of an effective therapeutic strategy against SARS-CoV-2.
Spatial and Temporal Evolution of Leaching Zones within Potash Seams Reproduced by Reactive Transport Simulations
Authors: Steding Svenja , Kempka Thomas , Zirkler Axel , Kühn Michael
Published: January 2021

Leaching zones within potash seams generally represent a significant risk to subsurface mining operations and the construction of technical caverns in salt rocks, but their temporal and spatial formation has been investigated only rudimentarily to date. To the knowledge of the authors, current reactive transport simulation implementations are not capable to address hydraulic-chemical interactions within potash salt. For this reason, a reactive transport model has been developed and complemented by an innovative approach to calculate the interchange of minerals and solution at the water-rock interface. Using this model, a scenario analysis was carried out based on a carnallite-bearing potash seam. The results show that the evolution of leaching zones depends on the mineral composition and dissolution rate of the original salt rock, and that the formation can be classified by the dimensionless parameters of Péclet (Pe) and Damköhler (Da). For Pe > 2 and Da > 1, a funnel-shaped leaching zone is formed, otherwise the dissolution front is planar. Additionally, Da > 1 results in the formation of a sylvinitic zone and a flow barrier. Most scenarios represent hybrid forms of these cases. The simulated shapes and mineralogies are confirmed by literature data and can be used to assess the hazard potential.