bluuebunny/crossref_metadata_2025_split huggingface dataset:
Super-Nernstian ion sensitive field-effect transistor exploiting charge screening in WSe2/MoS2 heterostructure
Authors: Sanjay Sooraj , Hossain Mainul , Rao Ankit , Bhat Navakanta 
Published: December 2021

AbstractIon-sensitive field-effect transistors (ISFETs) have gained a lot of attention in recent times as compact, low-cost biosensors with fast response time and label-free detection. Dual gate ISFETs have been shown to enhance detection sensitivity beyond the Nernst limit of 59 mV pH−1when the back gate dielectric is much thicker than the top dielectric. However, the thicker back-dielectric limits its application for ultrascaled point-of-care devices. In this work, we introduce and demonstrate a pH sensor, with WSe2(top)/MoS2(bottom) heterostructure based double gated ISFET. The proposed device is capable of surpassing the Nernst detection limit and uses thin high-k hafnium oxide as the gate oxide. The 2D atomic layered structure, combined with nanometer-thick top and bottom oxides, offers excellent scalability and linear response with a maximum sensitivity of 362 mV pH−1. We have also used technology computer-aided (TCAD) simulations to elucidate the underlying physics, namely back gate electric field screening through channel and interface charges due to the heterointerface. The proposed mechanism is independent of the dielectric thickness that makes miniaturization of these devices easier. We also demonstrate super-Nernstian behavior with the flipped MoS2(top)/WSe2(bottom) heterostructure ISFET. The results open up a new pathway of 2D heterostructure engineering as an excellent option for enhancing ISFET sensitivity beyond the Nernst limit, for the next-generation of label-free biosensors for single-molecular detection and point-of-care diagnostics.
In vitro functional analysis of gRNA sites regulating assembly of hepatitis B virus
Authors: Patel Nikesh , Clark Sam , Weiß Eva U. , Mata Carlos P. , Bohon Jen , Farquhar Erik R. , Maskell Daniel P. , Ranson Neil A. , Twarock Reidun , Stockley Peter G. 
Published: December 2021

AbstractThe roles of RNA sequence/structure motifs, Packaging Signals (PSs), for regulating assembly of an HBV genome transcript have been investigated in an efficient in vitro assay containing only core protein (Cp) and RNA. Variants of three conserved PSs, within the genome of a strain not used previously, preventing correct presentation of a Cp-recognition loop motif are differentially deleterious for assembly of nucleocapsid-like particles (NCPs). Cryo-electron microscopy reconstruction of the T = 4 NCPs formed with the wild-type gRNA transcript, reveal that the interior of the Cp shell is in contact with lower resolution density, potentially encompassing the arginine-rich protein domains and gRNA. Symmetry relaxation followed by asymmetric reconstruction reveal that such contacts are made at every symmetry axis. We infer from their regulation of assembly that some of these contacts would involve gRNA PSs, and confirmed this by X-ray RNA footprinting. Mutation of the ε stem-loop in the gRNA, where polymerase binds in vivo, produces a poor RNA assembly substrate with Cp alone, largely due to alterations in its conformation. The results show that RNA PSs regulate assembly of HBV genomic transcripts in vitro, and therefore may play similar roles in vivo, in concert with other molecular factors.
IQ-Switch is a QF-based innocuous, silencing-free, and inducible gene switch system in zebrafish
Authors: Hong Jeongkwan , Lee Jae-Geun , Sohn Kyung-Cheol , Lee Kayoung , Lee Seoee , Lee Jinyoung , Hong Jihye , Choi Dongju , Hong Yeseul , Jin Hyo Sun , Choi Dae-Kyoung , Lee Su Ui , Kee Yun , Jung Jangham , Bae Young-Ki , Hwang Ran Hee , Hur Gang Min , Lee Jeong-Soo , Ro Hyunju 
Published: December 2021

AbstractThough various transgene expression switches have been adopted in a wide variety of organisms for basic and biomedical research, intrinsic obstacles of those existing systems, including toxicity and silencing, have been limiting their use in vertebrate transgenesis. Here we demonstrate a novel QF-based binary transgene switch (IQ-Switch) that is relatively free of driver toxicity and transgene silencing, and exhibits potent and highly tunable transgene activation by the chemical inducer tebufenozide, a non-toxic lipophilic molecule to developing zebrafish with negligible background. The interchangeable IQ-Switch makes it possible to elicit ubiquitous and tissue specific transgene expression in a spatiotemporal manner. We generated a RASopathy disease model using IQ-Switch and demonstrated that the RASopathy symptoms were ameliorated by the specific BRAF(V600E) inhibitor vemurafenib, validating the therapeutic use of the gene switch. The orthogonal IQ-Switch provides a state-of-the-art platform for flexible regulation of transgene expression in zebrafish, potentially applicable in cell-based systems and other model organisms.
A shortcut to the thermodynamic limit for quantum many-body calculations of metals
Authors: Mihm Tina N. , Schäfer Tobias , Ramadugu Sai Kumar , Weiler Laura , Grüneis Andreas , Shepherd James J. 
Published: December 2021

AbstractComputationally efficient and accurate quantum mechanical approximations to solve the many-electron Schrödinger equation are crucial for computational materials science. Methods such as coupled cluster theory show potential for widespread adoption if computational cost bottlenecks can be removed. For example, extremely dense k-point grids are required to model long-range electronic correlation effects, particularly for metals. Although these grids can be made more effective by averaging calculations over an offset (or twist angle), the resultant cost in time for coupled cluster theory is prohibitive. We show here that a single special twist angle can be found using the transition structure factor, which provides the same benefit as twist averaging with one or two orders of magnitude reduction in computational time. We demonstrate that this not only works for metal systems but also is applicable to a broader range of materials, including insulators and semiconductors.
On the effect of metal loading on the reducibility and redox chemistry of ceria supported Pd catalysts
Authors: Clark Adam H. , Marchbank Huw R. , Thompsett David , Fisher Janet M. , Longo Alessandro , Beyer Kevin A. , Hyde Timothy I. , Sankar Gopinathan 
Published: December 2021

The effect of Pd loading on the redox characteristics of a ceria support was examined using in situ Pd K-edge, Ce L3-edge XAS and in situ X-ray diffraction techniques.
A feature‐based on potential and differential entropy information for electroencephalogram emotion recognition
Authors: Li Dongdong , Xie Li , Chai Bing , Wang Zhe 
Published: December 2021

AbstractElectroencephalogram (EEG) signals by virtue of its good time resolution can provide a more comprehensive way for emotion recognition. To further mine the emotion‐relevant information of EEG signals, a kind of innovative and effective feature named mean differential entropy (MDE) is proposed for EEG emotion recognition (EER). The MDE feature extracted from EEG signals supplements the additional potential information of each EEG frame on the basis of time‐frequency information. To verify its effectiveness, extensive experiments are conducted on DEAP (database for emotion analysis using physiological signals) dataset. The experiment results of the proposed methods on public EEG emotion dataset DEAP reached accuracies of 94.56% and 91.84% in valence dimension and four emotion labels with gradient boosting decision tree (GBDT), and 95.15% in arousal dimension with Random Forest (RF), which proved that the MDE feature is helpful to improve the performance of EER.
Transient stability emergency control for AC/DC grids considering successive commutation failures
Authors: Ma Yunfei , Geng Guangchao , Jiang Quanyuan , Yan Rong 
Published: December 2021

AbstractThe prevalence of Line‐Commutated Converter (LCC) HVDC makes the coupling and interaction phenomenon between AC system and DC system of particular complicated. There are significant challenges to determine control strategy using state‐of‐the‐art approaches especially when discrete events (e.g. switching and state resetting) happen frequently due to successive commutation failures (CFs). An enhanced transient stability emergency control (TSEC) for AC/DC grids based on the optimal control is presented to maintain the transient stability and mitigate the successive CFs caused by AC faults. In the proposed TSEC method, an extinction advance angle constraint is added to the TSEC model to mitigate the successive CFs. The emergency power control of LCC‐HVDC is employed as an additional control measure to reduce generator‐tripping and load‐shedding amount. The direct sequential approach is adopted to obtain the optimal solution of TSEC to improve the calculation efficiency. In the direct sequential approach, the modified adjoint sensitivity analysis (MASA) with the consideration of adjoint jump conditions is utilized to increase the gradient calculation accuracy. The effectiveness of the control strategies and the accuracy of the sensitivity calculation are verified on two test systems.
Stacking‐based ensemble learning method for the recognition of the preceding vehicle lane‐changing manoeuvre: A naturalistic driving study on the highway
Authors: Zhang Hongjia , Guo Yingshi , Wang Chang , Fu Rui 
Published: December 2021

AbstractThe recognition of the preceding vehicle lane‐changing manoeuvre (LCM) is essential for improving the rationality and safety of the decision‐making of driverless vehicles. However, traditional recognition researches for preceding vehicle LCM are generally characterized by problems such as low recognition accuracy and poor research foundation. In response to these problems, this paper carried out naturalistic driving study (NDS) on the highway, from which a large amount of on‐road data consisting of lane‐keeping (LK) and lane‐changing left and right (LCL, LCR) manoeuvres were collected. A stacking‐based ensemble learning method for the recognition of the LCM of the preceding vehicle, which integrates the random forest, support vector machine, long and short‐term memory network (LSTM), and bi‐directional LSTM based on attention mechanism (AT‐Bi‐LSTM) algorithms, is proposed. Compared with traditional machine learning methods, the proposed method exhibits greater advantages in terms of its recognition accuracy. It is particularly of note that the recognition accuracy of the model at 0.4 s and 0.8 s after the LCM reached 90.77% and 95.54%, respectively. The study reported is of great significance for the construction of more intelligent vehicle‐vehicle collaboration and the promotion of the industrial applications of intelligent vehicle technology.
An enhanced single gate driven voltage‐balanced SiC MOSFET stack topology suitable for high‐voltage low‐power applications
Authors: Wang Rui , Jørgensen Asger Bjørn , Munk‐Nielsen Stig 
Published: December 2021

AbstractIn the fabrication of some high‐voltage low‐power applications, low cost is much concerned, and thus using silicon carbide (SiC) MOSFET stack consisting of series connected low‐voltage devices is preferred rather than using an expensive single high‐voltage device. Therefore, a cost‐efficient single gate driven voltage‐balanced SiC MOSFET stack topology is proposed in this paper, where only some passive components are equipped with the stack. With a concept of single gate driver, the gate driver design of an SiC MOSFET stack is simplified. With an automatic balancing circuit which operates well with the sequential lagging single gate driver, good voltage balancing of SiC MOSFETs in the stack is realized without causing much extra loss and no additional active control is required. The working principle is illustrated in detail and the parameter selection together with design consideration is presented. Next, this topology is compared with RCD snubber method and active delay adjusting method to better illustrate its advantages. Finally, in a typical high‐voltage low‐power application, auxiliary power supply, the simulation and experimental results further verify the effectiveness of the proposed topology.
Impact of the global pandemic situation of COVID-19 on the growth of the economic level of private security services in the selected region
Authors: Boros Martin , Velas Andrej , Zvakova Zuzana , Mendel Robert 
Published: December 2021

Research background: The research presented in the article is focused on assessing the impact of measures implemented against the spread of COVID-19 in the conditions of the Slovak Republic. We will focus primarily on curfews, work at home and the like, which are directly related to private security services and have affected the company’s economic situation. An important factor influencing the economic level of society is also the ban on organizing sports events, at which private security services ensure the safety and protection of visitors, athletes and organizers.
Purpose of the article: The aim of the article is to determine the degree of impact of the pandemic situation caused by COVID-19 on the economic level and profitability of the mentioned companies in the selected Slovak region by means of a multi-year financial analysis of private security services.
Methods: The article will use several methods such as financial analysis, profitability analysis, comparison and other scientific methods such as forecasting the future situation in case they would take long-term anti-pandemic measures.
Findings & Value added: The result of the research presented in the article will be an evaluation of the degree of impact on companies operating on the Slovak market in the field of security from the point of view of profitability due to the impossibility of performing employment. Among other things, the expected estimate of the time period that private security services can manage if they would last long-term compared to pandemic measures will be presented.
COVID-19 pandemic is a stimulus for sustainable development of rural areas and labor markets
Authors: Chekmarev Oleg , Manilov Alexander , Ulimbashev Akhmedkhan , Timoshenko Svetlana 
Published: December 2021

Research background: The COVID-19 pandemic has exacerbated the challenges of maintaining the sustainability of urban agglomerations and provides a fresh look at the feasibility of developing rural areas and their labor markets. This situation stimulates the authorities, the population and business to pay attention to the benefits of the development of rural areas
Purpose of the article: The main goal of the presented article is assessment of the COVID-19 pandemic impact on the stimulus and opportunities for the sustainable development formulation of rural areas and its labor markets.
Methods: For research statistical materials and the results of scientific research by Russian and foreign scientists on the problems of the development of rural areas and their labor markets in the pre-covid period are used. The dynamics and dependence of the incidence of COVID-19 on the population's residence in rural and urban areas in certain regions of Russia, the growth in demand for suburban real estate, the problems of limiting migration during the development of the coronavirus pandemic and changes in labor markets that stimulate the relocation of the population to rural areas are investigated.
Findings & Value added: The results indicate that the COVID-19 pandemic has created stimulus for the intensive development of rural areas, both on population of the countries and authorities. To maintain the positive trends, the state authorities is needed to invest in sustainable development infrastructure of rural areas, as well as the legislative consolidation of the rights and obligations of freelancers.
The Impact of the Financial Stability on the Earnings Management Practices
Authors: Siekelova Anna 
Published: December 2021

Research background: In recent years, the world economy has changed. Earnings management, as a modern phenomenon, plays an important role within the financial world under the condition of globalization. The academic community deals with the issue of the informative value of the reported financial results. The informative value of these results becomes questionable when we realize that managers have not only the motivation but also the ability to use the earnings management techniques to influence these results.
Purpose of the article: The aim of the contribution is earnings management detection by using a model with the highest explanatory power, as well as verifying hypotheses about the existence of a statistically significant relationship between earnings management practices and financial stability within a sample of companies.
Methods: Based on the results of the explanatory power examination, the modified Jones model is recommended for earnings management detection within the sample of V4 companies. Data were obtained from the Amadeus database. The sample contains 1,480 financial reports of companies from 2019 to 2017. Research is focused on V4 companies that have the sum of total assets higher than 2,000,000 EUR, as well as the sum of operating revenue is higher than 100,000 EUR. Also, the Pearson correlation coefficient was used to test the hypotheses about the existing statistically significant relationship between financial stability and earnings management practices.
Findings & Value added: The article provides an overview of the earnings management issue within V4 countries. It examines the earnings management practices and the impact of financial stability on the level and direction of earnings management practices.
Sustainable Industry 4.0 Wireless Networks, Machine Learning Algorithms, and Internet of Things-based Real-Time Production Logistics in Digital Twin-driven Smart Manufacturing
Authors: Nica Elvira , Popescu Gheorghe H. , Lăzăroiu George 
Published: December 2021

Research background: The aim of this paper is to synthesize and analyze existing evidence on artificial intelligence-based decision-making algorithms, industrial big data, and Internet of Things sensing networks in digital twin-driven smart manufacturing.
Purpose of the article: Using and replicating data from Altair, Catapult, Deloitte, DHL, GAVS, PwC, and ZDNet we performed analyses and made estimates regarding cyber-physical system-based real-time monitoring, product decision-making information systems, and artificial intelligence data-driven Internet of Things systems in digital twin-based cyber-physical production systems.
Methods: From the completed surveys, we calculated descriptive statistics of compiled data when appropriate. The data was weighted in a multistep process that accounts for multiple stages of sampling and nonresponse that occur at different points in the survey process. The precision of the online polls was measured using a Bayesian credibility interval. To ensure high-quality data, data quality checks were performed to identify any respondents showing clear patterns of satisficing. Test data was populated and analyzed in SPSS to ensure the logic and randomizations were working as intended before launching the survey. An Internet-based survey software program was utilized for the delivery and collection of responses. The sample weighting was accomplished using an iterative proportional fitting process that simultaneously balanced the distributions of all variables. The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau’s American Community Survey to reflect reliably and accurately the demographic composition of the United States. Confirmatory factor analysis was employed to test for the reliability and validity of measurement instruments.
Findings & Value added: The way Internet of Things-based decision support systems, artificial intelligence-driven big data analytics, and robotic wireless sensor networks configure digital twin-driven smart manufacturing and cyber-physical production systems in sustainable Industry 4.0.
Eco-innovations in V4 countries: Comparison from a Global Perspective
Authors: Parobek Ján , Rokonalová Alena , Slašťanová Katarína , Loučanová Erika 
Published: December 2021

Research background: Globalization and the associated growing global competition provide incentives for the adoption of new technologies and innovations. In general, innovations could be considered as a dominant driver of the economic growth. However, current environmental challenges and sustainable development support the diffusion of eco-innovations to foster green growth. In terms of its global position, a country is often compared to its neighbouring countries, which are often the most important trading partners in the international market.
Purpose of the article: This paper is focused on the evaluation of eco-innovation performance of the V4 countries with emphasis on the Slovak Republic.
Methods: The article applies selected indicators of the Global Innovation Index to provide insightful data on countries' eco-innovation performance from the different V4 countries by applying the correlation analysis.
Findings & Value added: The results compare the state of selected indicators of innovation within the V4 countries and describe the current position of the Slovak Republic. The results demonstrate the relative strengths within all selected countries in the sub-pillar Ecological Sustainability and significant eco-innovation potential.
The impact of customer behaviour on the corporate competitiveness in the European environment
Authors: Kožená Marcela , Mlázovský Martin 
Published: December 2021

Research background: Corporate competitiveness is closely connected with the competitive advantage. Contemporary developed European countries are characterised by being highly competitive. Thus, the competitive advantage is particularly bound by fulfilling the customer preferences and needs. However, there is a necessity to preserve and strengthen customer satisfaction and loyalty, in the long-run.
Purpose of the article: In the current globalised world, there is apparent high pressure on the sustainable development of the whole society. This trend was shifted from the mere legislation scope to the society-wide discussion. However, the previous researches prove that this trend is not reflected in the real purchasing behaviour in Czechia. Thus, the main aim of this article is to explore the role of customer behaviour in the corporate competitiveness paradigm concerning the current trend of corporate social responsibility.
Methods: Primary quantitative research is based on a questionnaire survey with Czech managers at the top and middle level. The data collection was conducted from April to June 2021 via personal interviewing. The questionnaire contained mainly close-ended questions. However, if it was relevant there were also used additional open-ended questions for a closer explanation of the question point.
Findings & Value added: The results indicate that the Czech business mostly perceives as a key factor of corporate competitiveness innovation potential, not direct relationships with customers. However, this factor has a significant indirect connection with customer satisfaction. CSR has the lowest impact on corporate competitiveness according to the respondents. However, they predicate the upward trend of this factor, similar to the global environment.