Miracle-dz/UniFAR-FTUs huggingface dataset:
The complete mitochondrial genome of the cat flea, Ctenocephalides felis

Abstract The cat flea, Ctenocephalides fells, is widely recognized as a global veterinary pest and a vector of pathogenic bacteria. We recently reported on the C. felis nuclear genome, which is characterized by over 38% protein coding gene duplication, extensive tRNA gene family expansion, and remarkable gene copy number variation (CNV) between individual fleas. Herein, we describe the assembly of the C. felis mitochondrial genome, a novel resource for comparative genomics of fleas and other insects. The order and content of mitochondrial genes is highly consistent with four previously sequenced flea mitochondrial genomes, limiting CNV to siphonapteran nuclear genomes.
Assessing the South Korean Model of Emergency Management during the COVID-19 Pandemic

ABSTRACT The COVID-19 pandemic has led to an unprecedented global public health crisis, and governments have implemented various responses with varying degrees of effectiveness. South Korea’s approach, which has involved minimal lockdown in order to “flatten the curve”, and which offers an alternative for many democracies, has attracted much attention. Based on in-depth interviews with public health professionals and policy advisors in government agencies, this article analyses how well South Korea’s response to COVID-19 complies with the expectations of good governance, and assesses the strengths and challenges of the Korean model. Our analysis shows that South Korea has been reactive rather than preventive/passive amid waves of clusters such as outbreaks in nightclubs, e-commerce warehouses, schools, hospitals and religious gatherings. The government has used a range of countermeasures, including contact tracing, diagnostic testing, media briefings and text alerts. At the same time, the challenges for the Korean approach have been concerns about privacy, fatigue over emergency alerts and politicisation.
Air Transportation Income and Price Elasticities in Remote Areas: The Case of the Brazilian Amazon Region

The literature, aimed at understanding the income–price elasticity of air passenger demand, bases its analysis on airport movement. The diversity of studies regarding the casualty between air transportation and economic growth are examples. Some studies covering this link, estimate the income–price relationship with the demand considering international traffic. Considering a domestic setting, where this traffic is significant in Brazil, studies related to remote regions are scarce, and the existing ones focus on governmental policies and subsidies. In addition, empirical studies on the theme consenter themselves in developed regions, such as Europe, North America, and Australia. For Brazil, where we find the Amazon region, there is no empirical research. This paper analyses the price–income elasticity of the demand regarding domestic passengers in air links from remote cities of the Brazilian Amazon. This study uses panel data regression analysis method on a database of domestic scheduled flights of Brazil´s National Civil Aviation Agency. The results show that air passengers involving remote region flights present a lower sensitivity regarding local income and an airline´s price variations than those in flights among capitals. The higher difference is in the income elasticity of the remote city of origin, which is lower than that of the air traffic among capitals.
Questions Can Answer Questions About Mechanisms of Preschoolers' Selective Word Learning.

This study examined how inferences about epistemic competence and generalized labeling errors influence children's selective word learning. Three- to 4-year-olds (N = 128) learned words from informants who asked questions about objects, mentioning either correct or incorrect labels. Such questions do not convey stark differences in informants' epistemic competence. Inaccurate labels, however, generate error signals that can lead to weaker encoding of novel information. Preschoolers retained novel labels from both informants but were slower to respond in the Inaccurate Labeler condition. When the test procedure was not sensitive to the strength of information encoding, children performed above chance in both conditions and their response times did not differ. These results suggest that epistemic-level inferences and error generalizations influence preschoolers' selective word learning concurrently.
Advective Lateral Transport of Streamwise Momentum Governs Mixing at Small River Confluences

Confluences are important sites for mixing within river networks. Past work has shown that mixing within confluences is highly variable; in some cases flows mix rapidly and in other cases flows remain unmixed far downstream of the confluence. The fluvial processes that govern mixing within confluences remain poorly understood. This study relates patterns and amounts of mixing to three‐dimensional flow structure at three small confluences. It focuses on lateral fluxes of streamwise momentum, which theoretical considerations suggest should influence lateral mixing. Patterns and amounts of mixing differ at the three sites. Considerable mixing occurs at an asymmetrical confluence with strong helical motion within flow from the lateral tributary, which produces substantial differences in advective lateral transport of streamwise momentum over depth. Minor mixing occurs at a comparatively symmetrical confluence where incoming flows have relatively equal momentum fluxes; however, helical motion within one of the flows locally increases mixing. At a symmetrical confluence where one incoming flow has much greater momentum flux than the other, mixing occurs largely through progressive lateral shifting of the mixing interface toward the minor tributary because of the strong lateral flux of streamwise momentum by the dominant tributary. At all three confluences, lateral turbulent transport of streamwise momentum is an order of magnitude less than advective lateral transport of streamwise momentum. The study indicates that generalization of mixing at confluences remains challenging but that advective lateral fluxes of streamwise momentum related to secondary currents (helical motion) or primary flow (cross currents) greatly enhance mixing at confluences.
The linkage between CSR and cost of equity: an Indian perspective

Purpose This study aims to explore the relationship between corporate social responsibility (CSR) and the cost of equity (CoE) capital of Indian manufacturing firms. Design/methodology/approach The study is conducted on a sample of 68 manufacturing firms listed on National Stock Exchange of India Limited (NSE) 200, investigated for the period 2013 to 2018. To deal with the issue of endogeneity, the techniques of system generalized method of moments and two-stage least square have been applied. Findings The results suggest that CSR disclosure is positively linked with the CoE in the case of manufacturing firms, signalling that socially responsible firms in India bear a higher CoE. The findings indicate that investors do not treat CSR as a value-augmenting factor. Practical implications Firms should effectuate effective managerial and organizational changes to fulfil their social responsibility instead of window dressing their activities. Regulators in India must work towards more stringent enforcement of the act and make efforts to promote public awareness of CSR. Social implications The integration of CSR activities with the economic operations of the business is imperative. Originality/value To the best of researchers’ knowledge, there is a lack of studies focussing on India, which serves as an ideal setting for the study owing to the latest legislation mandating CSR expenditure. The study focusses on manufacturing firms as these firms are more susceptible to contribute to environmental pollution, exploitation of natural resources and labour concerns.
Nonstationary modeling of NO2, NO and NOx in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach

Abstract. Regional-scale chemistry-transport models have coarse spatial resolution (coarser than 1 km ×1 km) and can thus only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, where a large part of the urban population lives. Local-scale models may be used to simulate concentrations in streets. They often assume that background concentrations are constant and/or use simplified chemistry. Recently developed, the multi-scale model Street-in-Grid (SinG) estimates gaseous pollutant concentrations simultaneously at local and regional scales by coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and a street-network model, the Model of Urban Network of Intersecting Canyons and Highway (MUNICH), with a two-way feedback. MUNICH explicitly models street canyons and intersections, and it is coupled to the first vertical level of the chemical-transport model, enabling the transfer of pollutant mass between the street-canyon roof and the atmosphere. The original versions of SinG and MUNICH adopt a stationary hypothesis to estimate pollutant concentrations in streets. Although the computation of the NOx concentration is numerically stable with the stationary approach, the partitioning between NO and NO2 is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new nonstationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO2 . Simulations of NO, NO2 and NOx concentrations over Paris with SinG, MUNICH and Polair3D are compared to observations at traffic and urban stations to estimate the added value of multi-scale modeling with a two-way dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO2 concentrations in the streets. However, there is good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The two-way dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.
Effect of three different amines on the surface properties of electrospun polycaprolactone mats

Abstract The adequacy of biomaterials is essential to generate scaffolds suitable for tissue engineering studies. The electrospinning technique is a resourceful, quick and cheap way to obtain polycaprolactone (PCL) scaffolds with an architecture with porosity and adequate properties to ensure the survival of cells. However, some obstacles need to be overcome, such as the hydrophilicity of this polymer. In this study, we produced electrospun PCL nanofibrous mats and submitted them to aminolysis with three different diamines in order to generate hydrophilic cell-friendly scaffolds. The nanofibrous mats were characterized by their morphology, thermal and mechanical properties and, lastly, seeded with Human Adipose-Derived Stem Cells (hADSC) to observe the influence of the introduced amino groups in the polymeric matrix. The obtained results suggest a successful insertion of amino groups in the polymeric matrix, without being too detrimental to its morphology and intrinsic properties. Furthermore, the aminolyzed mats displayed a qualitative increase of cells attached to the nanofibrous mats.
Screening for enteric coronaviruses in fecal samples of feral pigs of California, USA

ii Acknowledgments. iv Vita . v List of Tables . ix List of Figures . x Chapter 1: Literature Review . 1 Coronaviruses . 1 Human coronaviruses (HCoVs) . 2 Bat coronaviruses . 3 Porcine Epidemic Diarrhea Virus (PEDV) . 4 History and epidemiology . 4 PEDV in USA . 6 Structure of PEDV . 7 Transmission . 8 Pathogenesis . 8
When Populist Leaders Govern: Conceptualising Populism in Policy Making

The rise of populist governance throughout the world offers a novel opportunity to study the way in which populist leaders and parties rule. This article conceptualises populist policy making by theoretically addressing the substantive and discursive components of populist policies and the decision-making processes of populist governments. It first reconstructs the implicit ideal type of policy making in liberal democracies based on the mainstream governance and policy making scholarship. Then, taking stock of the recent populism literature, the article elaborates an ideal type of populist policy making along the dimensions of content, procedures and discourses. As an empirical illustration we apply a qualitative congruence analysis to assess the conformity of a genuine case of populist governance, social policy in post-2010 Hungary with the populist policy making ideal type. Concerning the policy content, the article argues that policy heterodoxy, strong willingness to adopt paradigmatic reforms and an excessive responsiveness to majoritarian preferences are distinguishing features of any type of populist policies. Regarding the procedural features populist leaders tend to downplay the role of technocratic expertise, sideline veto-players and implement fast and unpredictable policy changes. Discursively, populist leaders tend to extensively use crisis frames and discursive governance instruments in a Manichean language and a saliently emotional manner that reinforces polarisation in policy positions. Finally, the article suggests that policy making patterns in Hungarian social policy between 2010 and 2018 have been largely congruent with the ideal type of populist policy making.
Increasing non‐linearity of the storage‐discharge relationship in sub‐Arctic catchments

The Arctic is warming at an unprecedented rate. We hypothesis that as seasonally frozen soils thaw and recede in extent as a response to this warming, flow path diversity and thus hydrologic connectivity increases. This enhanced hydrologic connectivity then increases the non‐linearity of the storage‐discharge relationship in a catchment. The objective of this study is to test this hypothesis by quantifying trends and spatio‐temporal differences in the degree of linearity in the storage‐discharge relationships for 16 catchments within Northern Sweden from 1950 to 2018. We demonstrate a clear increase in non‐linearity of the storage‐discharge relationship over time for all catchments with 75% showing a statistically significant increase in non‐linearity. Spring has significantly more linear storage‐discharge relationships than summer for most catchments (75%) supporting the idea that seasonally frozen soils with a low degree of hydrological connectivity have a linear storage‐discharge relationship. For the period considered, spring also showed greater change in storage‐discharge relationship trends than summer signifying that changes in recessions are primarily occurring during the thawing period. Separate storage‐discharge analyses combined with preceding winter conditions demonstrated that especially cold winters with little snow yielded springs and summers with more linear storage‐discharge relationships. We show that streamflow recession analysis reflects ongoing hydrological change of an arctic landscape as well as offering new metrics for tracking change across arctic and sub‐arctic landscapes.
Coalho cheese as source of probiotic lactic acid bacteria

The aim of this study was to characterize the probiotic potential of 24 lactic acid bacteria (LAB) strains isolated from artisanal Coalho cheese from Pernambuco, Brazil by in vitro tests. The gastrointestinal tract (GIT) resistance, antimicrobial activity against intestinal pathogens, autoaggregation and coaggregation capacity, cell hydrophobicity, s-galactosidase activity, deconjugate bile salt activity for the production of bile salt hydrolase (BSH), and the sensitivity to antibiotics were evaluated. Of the 24 strains, 22 remained viable to a simulated GIT. Two LAB inhibited the growth of Listeria monocytogenes and two inhibited Escherichia coli. The autoaggregation rate ranged from 27% to 96%, and the strains were able to coaggregate with Staphylococcus aureus and E. coli reaching levels between 58% and 47%, respectively. The hydrophobicity percentage ranged from 5% to 57%. Four strains were able to produce BSH. One LAB was able to produce up to 604 Miller units of s-galactosidase. All strains were sensitive to five antibiotics and only two were resistant to vancomycin (30μg) and norfloxacin (10g). LAB strains which were able to overcome all barriers with a reduction of only one log cycle and LAB strains which were able to produce s-galactosidase were identified by 16S rRNA sequence analysis as Lactococcus lactis subsp. Lactis, Enterococcus durans, and Enterococcus faecium. The evaluated LAB showed promising probiotic characteristics. Strains identified as L. lactis subsp. Lactis were selected for studies involving their technological potential to investigate the possible use of these microorganisms into a functional product.
Time and class: How socioeconomic status shapes conceptions of the future self

ABSTRACT People generally care about their future. However, how vividly they imagine it, and how much they like and value it, may vary across socioeconomic status (SES). If lower-SES individuals believe their future to resemble their present, including the greater uncertainties and stressors of a lower-SES environment, then they may focus less on their future self, coming to view it less vividly, as less likable, and less valuable, amongst other qualities. We found support for these hypotheses across pilot data, two observational studies (one pre-registered), and a pre-registered experimental manipulation of SES. These results add to the growing literature on SES’s psychological consequences by suggesting that SES affects people’s conceptions of not only their present self, but also their future self.
A data mining approach for lubricant-based fault diagnosis

PurposeThe purpose of this paper is to develop a maintenance decision support system (DSS) framework using in-service lubricant data for fault diagnosis. The DSS reveals embedded patterns in the data (knowledge discovery) and automatically quantifies the influence of lubricant parameters on the unhealthy state of the machine using alternative classifiers. The classifiers are compared for robustness from which decision-makers select an appropriate classifier given a specific lubricant data set.Design/methodology/approachThe DSS embeds a framework integrating cluster and principal component analysis, for feature extraction, and eight classifiers among them extreme gradient boosting (XGB), random forest (RF), decision trees (DT) and logistic regression (LR). A qualitative and quantitative criterion is developed in conjunction with practitioners for comparing the classifier models.FindingsThe results show the importance of embedded knowledge, explored via a knowledge discovery approach. Moreover, the efficacy of the embedded knowledge on maintenance DSS is emphasized. Importantly, the proposed framework is demonstrated as plausible for decision support due to its high accuracy and consideration of practitioners needs.Practical implicationsThe proposed framework will potentially assist maintenance managers in accurately exploiting lubricant data for maintenance DSS, while offering insights with reduced time and errors.Originality/valueAdvances in lubricant-based intelligent approach for fault diagnosis is seldom utilized in practice, however, may be incorporated in the information management systems offering high predictive accuracy. The classification models' comparison approach, will inevitably assist the industry in selecting amongst divergent models' for DSS.
Nano-silicon for light-controlled energy transfer to molecular oxygen

This thesis presents the results of several physical and magneto-optical experiments using nanostructured silicon fabricated by an electrochemical etching method. Quantum confinement causes the efficient visible light emission of nanocrystalline silicon. Long lived excitons confined in silicon nanocrystals are applied as an energy storage medium for energy transfer to oxygen. Nanocrystalline silicon-silica aerogel composites are synthesised and examined the sensitivity with adsorbed oxygen molecules. Efficient energy transfer from photo-excited excitons to molecular oxygen to create singlet oxygen is presented in the experimental results. Spin exchange interactions are a key aspect controlling the energy transfer between silicon nanoparticles and molecular oxygens. Hence, modifications of the spins alter the dynamics of the energy transfer process. Spin distributions of the participating states are changed by applying magnetic fields or by changing excitation powers. Therefore, the dependences of the transfer process on magnetic field, excitation power and oxygen concentration were studied. The energy transfer model is constructed based on a rate equation approach. The model produces simulations that are in good agreement with the overall data. The dynamic parameters are provided and indicate the characteristics of the silicon nanostructures. Possibilities for future work in this research area are included.
The Segmentation of Neutron Digital Radiography Image through the Edge Detection Method

The digital image processing is one way to manipulate one or more digital images. Image segmentation has an essential role in the field of image analysis. The aim of this study was to develop an application to perform digital image processing of neutron digital radiographic images, hoping to improve the image quality of the digital images produced. The quality of edge detection could be used for the introduction of neutron digital radiographic image patterns through artificial intelligence. Interaction of neutrons with the matter mainly by nuclear reaction, elastic, and inelastic scattering. A neutron can quickly enter into a nucleus of an atom and cause a reaction. It is because a neutron has no charge. Neutrons can be used for digital imaging due to high-resolution information from deep layers of the material. The attenuated neutron beam in neutron radiography are passing through the investigated object. The object in a uniform neutron beam is irradiated to obtain an image neutron. The technique used in segmenting the neutron radiography in this study was a digital technique using a camera with a charge-coupled device (CCD), which was deemed more efficient technique compared to the conventional one. Through this technique, images could be displayed directly on the monitor without going through the film washing process. Edge detection methods were implemented in the algorithm program. It was the first step to complement the image information where edges characterize object boundaries. It is useful for the process of segmenting and identifying objects in neutron digital radiography images. The edge detection methods used in this study were Sobel, Prewitt, Canny, and Laplacian of Gaussian. According to the results of the image that have been tested for edge detection, the best image was carried out by the Canny operator because the method is more explicit. The obtained edges were more connected than the other methods which are still broken. The Canny technique provided edge gradient orientation which resulted in a proper localization.