bluuebunny/crossref_metadata_2025_split huggingface dataset:
Government Responses Matter: Predicting Covid-19 cases in US using an empirical Bayesian time series framework
Authors: Liu Ziyue , Guo Wensheng 
Published: March 2020

AbstractSince the Covid-19 outbreak, researchers have been predicting how the epidemic will evolve, especially the number in each country, through using parametric extrapolations based on the history. In reality, the epidemic progressing in a particular country depends largely on its policy responses and interventions. Since the outbreaks in some countries are earlier than United States, the prediction of US cases can benefit from incorporating the similarity in their trajectories. We propose an empirical Bayesian time series framework to predict US cases using different countries as prior reference. The resultant forecast is based on observed US data and prior information from the reference country while accounting for different population sizes. When Italy is used as prior in the prediction, which the US data resemble the most, the cases in the US will exceed 300,000 by the beginning of April unless strong measures are adopted.
Medical treatment of 55 patients with COVID-19 from seven cities in northeast China who fully recovered: a single-center, retrospective, observational study
Authors: Fan Lichao , Liu Huan , Li Na , Liu Chang , Gu Ye , Liu Yongyu , Chen Yu 
Published: March 2020

SummaryBackgroundCOVID-19 is an emerging disease caused by the SARS-CoV-2 virus; no specific medication has been identified to date. We aimed to investigate the administered medications and intervention times for patients who completely recovered from COVID-19.MethodsThis single-center, retrospective, and observational study included 55 patients with COVID-19 who were transferred to Shenyang Sixth People’s Hospital between January 20 and March 15, 2020. Demographic information, symptoms, laboratory indicators, treatment processes, and clinical outcomes were collected. Administered drugs and intervention times were compared in 47 and eight patients with mild and severe symptoms, respectively.FindingsAll 55 patients recovered. Fifty-three patients (96·36%) received antiviral therapy, including 45 in the mild group (median treatment: 14 days; 17 received umifenovir) and all eight severe-group patients (median treatment: 17·5 days; four received lopinavir/ritonavir). Twenty-nine patients (52·72%) were administered antibiotics, including 21 in the mild group (median treatment: 13·5 days; 15 received moxifloxacin) and all eight in the severe group (median treatment: 9 days; two received linezolid). Moreover, seven patients (12·72%) were treated with glucocorticoids and nine (16·36%) with immunomodulators.InterpretationGiven the 100% recovery rate, early administration of antiviral drugs can be considered. Umifenovir may benefit patients with mild symptoms, while lopinavir/ritonavir may benefit those with severe symptoms. Prophylactic administration of common antibiotics may reduce the risk of co-infection. The use of glucocorticoids is usually not necessary.FundingThis work was supported by the Shenyang Major Science and Technology Innovation R&D Program (JY2020-9-018 to Y. Chen).
Deep Learning-Based Recognizing COVID-19 and other Common Infectious Diseases of the Lung by Chest CT Scan Images
Authors: Fu Min , Yi Shuang-Lian , Zeng Yuanfeng , Ye Feng , Li Yuxuan , Dong Xuan , Ren Yan-Dan , Luo Linkai , Pan Jin-Shui , Zhang Qi 
Published: March 2020

AbstractPurposeCOVID-19 has become global threaten. CT acts as an important method of diagnosis. However, human–based interpretation of CT imaging is time consuming. More than that, substantial inter-observer-variation cannot be ignored. We aim at developing a diagnostic tool for artificial intelligence (AI)–based classification of CT images for recognizing COVID-19 and other common infectious diseases of the lung.Experimental DesignIn this study, images were retrospectively collected and prospectively analyzed using machine learning. CT scan images of the lung that show or do not show COVID-19 were used to train and validate a classification framework based on convolutional neural network. Five conditions including COVID-19 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, pulmonary tuberculosis, and normal lung were evaluated. Training and validation set of images were collected from Wuhan Jin Yin-Tan Hospital whereas test set of images were collected from Zhongshan Hospital Xiamen University and the fifth Hospital of Wuhan.ResultsAccuracy, sensitivity, and specificity of the AI framework were reported. For test dataset, accuracies for recognizing normal lung, COVID-19 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, and pulmonary tuberculosis were 99.4%, 98.8%, 98.5%, 98.3%, and 98.6%, respectively. For the test dataset, accuracy, sensitivity, specificity, PPV, and NPV of recognizing COVID-19 were 98.8%, 98.2%, 98.9%, 94.5%, and 99.7%, respectively.ConclusionsThe performance of the proposed AI framework has excellent performance of recognizing COVID-19 and other common infectious diseases of the lung, which also has balanced sensitivity and specificity.
Which Measures are Effective in Containing COVID-19? — Empirical Research Based on Prevention and Control Cases in China
Authors: Lin Shanlang , Huang Junpei , He Ziwen , Zhan Dandan 
Published: March 2020

AbstractVarious epidemic prevention and control measures aimed at reducing person-to-person contact has paid a certain cost while controlling the epidemic. So accurate evaluation of these measures helps to maximize the effectiveness of prevention and control while minimizing social costs. In this paper, we develop the model in Dirk Brockmann and Dirk Helbing (2013) to theoretically explain the impact mechanism of traffic control and social distancing measures on the spread of the epidemic, and empirically tests the effect of the two measures in China at the present stage using econometric approach. We found that both traffic control and social distancing measures have played a very good role in controlling the development of the epidemic. Nationally, social distancing measures are better than traffic control measures; the two measures are complementary and their combined action will play a better epidemic prevention effect; Traffic control and social distancing do not work everywhere. Traffic control only works in cities with higher GDP per capita and population size, while fails in cities with lower GDP per capita and population size. In cities with lower population size, social distancing becomes inoperative; the rapid and accurate transmission of information, a higher protection awareness of the public, and a stronger confidence of residents in epidemic prevention can promote the realization of the measure effects. The findings above verify the effectiveness and correctness of the measures implemented in China at present, at the same time, we propose that it is necessary to fully consider the respective characteristics of the two measures, cooperating and complementing each other; what’s more, measures should be formulated according to the city’s own situation, achieving precise epidemic prevention; Finally, we should increase the transparency of information, improve protection awareness of the public, guide emotions of the public in a proper way, enhancing public confidence.
Herd immunity vs suppressed equilibrium in COVID-19 pandemic: different goals require different models for tracking
Authors: Huang Norden E. , Qiao Fangli , Qian Wang , Tung Ka-Kit 
Published: March 2020

ABSTRACTNew COVID-19 epicenters have sprung up in Europe and US as the epidemic in China wanes. Many mechanistic models’ past predictions for China were widely off the mark (1, 2), and still vary widely for the new epicenters, due to uncertain disease characteristics. The epidemic ended in Wuhan, and later in South Korea, with less than 1% of their population infected, much less than that required to achieve “herd immunity”. Now as most countries pursue the goal of “suppressed equilibrium”, the traditional concept of “herd immunity” in epidemiology needs to be re-examined. Traditional model predictions of large potential impacts serve their purpose in prompting policy decisions on contact suppression and lockdown to combat the spread, and are useful for evaluating various scenarios. After imposition of these measures it is important to turn to statistical models that incorporate real-time information that reflects ongoing policy implementation and degrees of compliance to more realistically track and project the epidemic’s course. Here we apply such a tool, supported by theory and validated by past data as accurate, to US and Europe. Most countries started with a Reproduction Number of 4 and declined to around 1 at a rate highly dependent on contact-reduction measures.
A novel antiviral formulation inhibits a range of enveloped viruses
Authors: Fletcher Nicola F. , Meredith Luke W. , Tidswell Emma , Bryden Steven R , Gonçalves-Carneiro Daniel , Chaudhry Yasmin , Lowe Claire Shannon , Folan Michael A. , Lefteri Daniella A , Pingen Marieke , Bailey Dalan , McKimmie Clive S. , Baird Alan W. 
Published: March 2020

AbstractSome free fatty acids derived from milk and vegetable oils are known to have potent antiviral and antibacterial properties. However, therapeutic applications of short to medium chain fatty acids are limited by physical characteristics such as immiscibility in aqueous solutions. We evaluated a novel proprietary formulation based on an emulsion of short chain caprylic acid, ViroSAL, for its ability to inhibit a range of viral infectionsin vitroandin vivo. In vitro, ViroSAL inhibited the enveloped viruses Epstein-Barr, measles, herpes simplex, Zika and orf parapoxvirus, together with Ebola, Lassa, vesicular stomatitis and SARS-CoV-1 pseudoviruses, in a concentration- and time-dependent manner. Evaluation of the components of ViroSAL revealed that caprylic acid was the main antiviral component; however, the ViroSAL formulation significantly inhibited viral entry compared with caprylic acid alone.In vivo, ViroSAL significantly inhibited Zika and Semliki Forest Virus replication in mice following the inoculation of these viruses into mosquito bite sites. In agreement with studies investigating other free fatty acids, ViroSAL had no effect on norovirus, a non-enveloped virus, indicating that its mechanism of action may be via surfactant disruption of the viral envelope. We have identified a novel antiviral formulation that is of great interest for prevention and/or treatment of a broad range of enveloped viruses.
Assessing the sex-related genomic composition difference using a K-mer-based approach: a case of study in Arapaima gigas (Pirarucu)
Authors: Cavalcante R.L.D , Ortega J.M. , Souza J.E.S , Sakamoto T. 
Published: March 2020

ABSTRACTArapaima gigas is one of the largest freshwater bony fish in the world, in which adults could weigh 200 kilograms and measure 3 meters in length. Due to its large size and its low-fat meat, Arapaima gigas has quickly become a species of special interest in fish-farming. One challenge faced during their production is the lack of an efficient sexing methodology, since their sexual maturation occurs late (around the third to the fifth year) and the genetic mechanisms linked to their sex determination system are not known yet. For a more sustainable management, it is of paramount importance to seek an effective and non-invasive method to differentiate sexually juvenile individuals of Arapaima gigas. For this, the establishment of genetic markers associated with sexual differentiation would be an advantageous tool. In this study, we proposed a k-mer based approach to identify genome features with sex-determining properties. For this purpose, we used genomic data from four adult representatives of Arapaima gigas, two males and two females, and counted the k-mers comprising them. As result, we found k-mers from repetitive regions with high difference and disproportion in the count among individuals of the opposite sex. These differences in the k-mer-based genomic composition indicate the existence of genetic factors involved in the sexing of individuals in Arapaima gigas.
A kernel-based method to calculate local field potentials from networks of spiking neurons
Authors: Telenczuk Bartosz , Telenczuk Maria , Destexhe Alain 
Published: March 2020

AbstractBackgroundThe local field potential (LFP) is usually calculated from current sources arising from transmembrane currents, in particular in asymmetric cellular morphologies such as pyramidal neurons.New methodHere, we adopt a different point of view and relate the spiking of neurons to the LFP through efferent synaptic connections and provide a method to calculate LFPs.ResultsWe show that the so-called unitary LFPs (uLFP) provide the key to such a calculation. We show experimental measurements and simulations of uLFPs in neocortex and hippocampus, for both excitatory and inhibitory neurons. We fit a “kernel” function to measurements of uLFPs, and we estimate its spatial and temporal spread by using simulations of morphologically detailed reconstructions of hippocampal pyramidal neurons. Assuming that LFPs are the sum of uLFPs generated by every neuron in the network, the LFP generated by excitatory and inhibitory neurons can be calculated by convolving the trains of action potentials with the kernels estimated from uLFPs. This provides a method to calculate the LFP from networks of spiking neurons, even for point neurons for which the LFP is not easily defined. We show examples of LFPs calculated from networks of point neurons and compare to the LFP calculated from synaptic currents.ConclusionsThe kernel-based method provides a practical way to calculate LFPs from networks of point neurons.HighlightsWe provide a method to estimate the LFP from spiking neuronsThis method is based on kernels, estimated from experimental dataWe show applications of this method to calculate the LFP from networks of spiking neuronsWe show that the kernel-based method is a low-pass filtered version of the LFP calculated from synaptic currents
LPV robust servo control of aircraft active side-sticks
Authors: Zhou Guang Rui , Liu Shi Qian , Sang Yuan Jun , Wang Xu Dong , Jia Xiao Peng , Niu Er Zhuo 
Published: March 2020

Purpose
This paper aims to focus on the variable stick force-displacement (SFD) gradience in the active side stick (ASS) servo system for the civil aircraft.

Design/methodology/approach
The problem of variable SFD gradience was introduced first, followed by the analysis of its impact on the ASS servo system. To solve this problem, a linear-parameter-varying (LPV) control approach was suggested to process the variable gradience of the SFD. A H∞ robust control method was proposed to deal with the external disturbance.

Findings
To validate the algorithm performance, a linear time-variant system was calculated to be used to worst cases and the SFD gradience was set to linear and non-linear variation to test the algorithm, and some typical examples of pitch angle and side-slip angle tracking control for a large civil aircraft were also used to verify the algorithm. The results showed that the LPV control method had less settling time and less steady tracking errors than H∞ control, even in the variable SFD case.

Practical implications
This paper presented an ASS servo system using the LPV control method to solve the problem caused by the variable SFD gradience. The motor torque command was calculated by pressure and position feedback without additional hardware support. It was more useful for the electronic hydraulic servo actuator.

Originality/value
This was the research paper that analyzed the impact of the variable SFD gradience in the ASS servo system and presented an LPV control method to solve it. It was applicable for the SFD gradience changing in the linear and non-linear cases.
The effect of digital transformation strategy on performance
Authors: Wang Hecheng , Feng Junzheng , Zhang Hui , Li Xin 
Published: March 2020

PurposeThe purpose of this study is to verify whether digital transformation strategy (DTS) could improve the organizational performance and provide a comprehensive analysis for enterprises on the necessity of implementing digital transformation in the context of China and draw on the perspectives of “Skewed conflict,” “minority dissent theory” and “too-much-of-a-good-thing.” This study investigates the curvilinear moderating role of cognitive conflict between DTS and performance.Design/methodology/approachAn empirical investigation was used to collect a large sample data of Chinese enterprises’ digital transformation. A multiple linear regression analysis with SPSS was used to test the proposed hypotheses such as the inverted U-shaped moderating effect of the cognitive conflict.FindingsIn the Chinese context, DTS has a positive relationship on the short- and long-term financial performance. Moreover, this relationship was moderated by cognitive conflict such that the relationship between DTS and short-term financial performance could be further enhanced under the moderate cognitive conflict; however, the relationship between DTS and long-term financial performance was considerably influenced for higher cognitive conflict.Originality/valueBased on the co-evolution of the information technology/information system (IT/IS) and business strategy, this study clarified the relationships among DTS, digital strategy and business and information technology strategies. By focusing on corporate strategy, this study further examined the effect of digital transformation on both short- and long-term financial performance. To further reveal the micro-psychological mechanisms underlying the effect of DTS on organizational performance, this study confirmed the inverted U-shaped moderating effect of the top management team’s cognitive conflict. Therefore, this research provides a new theoretical perspective for future research in the field of IT/IS, DTS and digital strategy.
Does bank competition matter for performance and risk-taking? empirical evidence from BRICS countries
Authors: Moudud-Ul-Huq Syed 
Published: March 2020

PurposeThis study examines the relationship between banks' competition performance and risk-taking behavior concerning the impacts of bank size and the recent global financial crisis. The analysis empirically uses dynamic panel data from 1137 banks of the BRICS countries (i.e. Brazil Russia India China and South Africa) for the period 2000–2015.Design/methodology/approachDynamic panel generalized method of moments (GMM) has been used primarily to examine the effect of bank competition on performance and risk-taking. Later the paper validates the core results by using three-stage least squares (3SLS) and incorporating alternative measure of competition in baseline equations.FindingsThis study confirms the significant impact of competition that complies with the structure-conduct-performance hypothesis quiet life hypothesis and “competition fragility” view. However, the key robust results are as follows: (1) in competitive markets large banks are more efficient than small banks; (2) there is a nonlinear relationship between competition performance and risk; (3) across bank size competition heterogeneously affects profitability efficiency risk and stability; (4) notably small banks are as efficient as large banks during crisis but shared with risk; and (5) small banks also stable during crisis in highly concentrated markets but less stable in competitive environments.Practical implicationsThis study promotes higher market power for the bank's profitability and financial stability. More intently policymakers should nurture both cost and revenue efficiency for large banks as these are less efficient than small banks in concentrated markets though these banks produce risk. Hence those banks should be cautious to minimize non-performing loans and maximize stability regarding financial and efficiency. Based on the nonlinear pattern of competition the regulators should adopt different policies for short and long run. It also recommends encouraging commercial and cooperative banks in the BRICS region as these are more efficient risk-averse and better stabilized than other types of banks.Originality/valueA good number of studies are available in the current literature which examines the impact of bank competition on either bank performance or risk-taking in a single country or cross country analysis. However, very few studies examine the relationship between bank performance and risk-taking behavior concerning the impacts of competition (non-linear and quadratic) size financial crisis and ownership structure together. Moreover, there is a dearth of literature on this topic that built on BRICS economies.
Zakahcompliance behavior among entrepreneurs: economic factors approach
Authors: Bin-Nashwan Saeed Awadh , Abdul-Jabbar Hijattulah , Aziz Saliza Abdul , Haladu Alhassan 
Published: March 2020

PurposeAs one of the constituted main pillars of Islam,Zakahcompliance (ZC) is mandated upon Muslims from all studies of life. Taking the disappointingly low compliance level in developing countries, including Yemen, as its backdrop, the purpose of this study is to investigate ZC behavior among entrepreneurs, drawing on the economic approach perspective.Design/methodology/approachThe study adopted a cross-sectional design based on a survey of entrepreneurs in Yemen. It used primary data collected via self-administered questionnaires, involving a sample of 500 participants. A variance-based structural modeling equation-partial least squares were used to measure the instruments and assess the hypothesized relationships.FindingsThe findings affirmed the suitability of the economic factors approaches in the context of ZC in a developing country. Specifically, the study demonstrated thatZakahlaw complexity has a significant negative influence on ZC of entrepreneurs. It also found a significant positive relationship between religiosity and ZC among the study sample, whereas the study revealed that law enforcement has no influence on compliance behavior.Practical implicationsPolicies and programs focused onZakahlaws and regulations could be formulated to make them less complex and simpler for acceptable levels of ZC. The result is further relevant to policymakers in Muslim communities to strengthen the religious faith of Zakah payers toward compliance with one of the fundamental religious obligations such asZakah.Originality/valueThis study enriches the limited previous studies on actual ZC from the perspective of developing communities, especially Yemen. Most importantly, the value was added to the limited literature internationally from an economic aspect.