Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Deep Learning Methods to Automate Collaborative Learning Process Coding Based on Multi-Dimensional Coding Scheme

—In computer-supported collaborative learning research, it may be a significantly important task to figure out guidelines for carrying out an appropriate scaffolding by extracting indicators for distinguishing groups with poor progress in collaborative process upon analyzing the mechanism of interactive activation. And for this collaborative process analysis, coding and statistical analysis are often adopted as a method. But as far as our project is concerned, we are trying to automate this huge laborious coding work with deep learning technology. In our previous research, supervised data was prepared for deep learning based on a coding scheme consisting of 16 labels according to speech acts. In this paper, with a multi-dimensional coding scheme with five dimensions newly designed aiming at analyzing collaborative learning process more comprehensively and multilaterally, an automatic coding is performed by deep learning methods and its accuracy is verified.
A review of potential pharmacological treatments of COVID-19: an evidence-based perspective

Coronaviruses (CoVs) typically manifest as mild to severe respiratory tract infections. No drug is approved by US food and drug administration (FDA) for the treatment of patients with coronaviruses infection. With growing COVID19 pandemic globally, need of hour is to work on potential prophylactic and therapeutic drugs to prevent local and community transmission. A literature search for eligible studies published till March 2020 was conducted in the PubMed, Medline, EMBASE, OVID, and Google Scholar databases by two reviewers. Therapeutic efficacy and safety of different drug regimens targeting treatment pathway acting against corona virus-2019 (COVID-19) were reviewed. Possible mechanism of actions of these potential repurposed drugs against COVID-19 were reviewed to develop effective prevention and treatment strategies. Many potential pharmacological therapies are being studied in various clinical trials. No FDA-approved repurposed drugs have shown safety and efficacy in randomized controlled trials for patients with COVID-19. Vaccines are under development and only few vaccines are under clinical evaluation. This review highlights potential drug actions against COVID-19 and their safety issues. It could help researchers and physicians to use these potential agents judiciously in clinical trials as well as in treatment protocols.
A HYBRIDIZATION OF SIMULTANEOUS AND SEQUENTIAL LINEUPS REVEALS DIAGNOSTIC FEATURES OF BOTH TRADITIONAL PROCEDURES

This study investigated a hybridization of simultaneous and sequential procedures to facilitate eyewitness identifications. The slideshow procedure presented photos to participants in a cycling loop, allowing them to view photos multiple times, but always one-at-a-time. We hypothesized allowing witnesses to view all photos without directly comparing them would increase correct identifications and correct non-identifications. Simultaneous presentation led to the most correct identifications, while sequential presentation led to the most correct non-identifications. The hybridization reduced both types of correct response and failed to support our hypothesis. The hybridization appears to promote guessing rather than conservative responding. Receiver operating characteristic (ROC) analysis revealed simultaneous advantage when making identifications, but sequential advantage when making non-identifications. We conclude that performing ROC analysis of both identifications and non-identifications may reveal the same interaction noted between perpetrator presence and lineup modality when analyzing identification decisions.
Object Detection in the Autonomous Driving Scenario

Self-driving vehicle technology has become a popular topic in recent years among industry leaders and research oriented institutions with applications for micro-transit and highway driving. This technology has proved to be robust in certain realistic trafﬁc scenarios, but one important aspect that has led to debates is safety. With safety being a reason for concern in the deployment and testing of self-driving vehicles, perception and tracking stacks become a critical component of autonomous driving architectures. In this study, we investigated the performance of three popular multi-object detectors on a dataset collected by a real world driving vehicle setup, where the main emphasis is on real-time computation. Since most object datasets do not contain information related to speciﬁc car models, we also trained a deep neural network to speciﬁcally recognize classes of cars. Our results summarize which object detector to use for autonomous driving research and how to best train it for further uses.
THE LONG-RUN CAUSAL NEXUS BETWEEN EXPENDITURE IN SOCIAL SERVICES SECTOR AND ECONOMIC SERVICES SECTOR: A COMPARATIVE ANALYSIS BETWEEN NATIONAL AND SUB- NATIONAL GOVERNMENT

Every welfare state allocates resources to numerous socio-economic and general welfare services sectorsto have higher growth in Output, to generate more employment opportunities, to reduce poverty and to achieve social and economic equality. By generating resources through tax and non-tax measures, the government executes a number of activities to provide basic necessities of people like roads and bridges, irrigation for agriculture, drinking water facilities, electricity, housing, medical and public health facilities, protection to citizens etc. These services are part of general services, social services and economic services sectors.There are dearth of studies in analyzing the relationship between the expenditure in social service sector and the expenditure in the economic service sector. Hence, the study attempts toanalyze the long run association, and to examine the causal nexus between the expenditure in social services and the expenditure in economic services both in Indian context as well as for Odisha. The JohansenJuselius cointegration approach established the long-run relationship between the expenditure in social service sector and economic service sector both for India and Odisha. The VECM based causality estimates concluded that in Indian context, expenditure in social service sector causes economic service sector expenditure but not vice versa while for Odisha, economic service sector expenditure causes social service sector expenditure but not vice versa. As regards to policy
The Modeling homogeneous bubble nucleation in liquids : A probable mechanism

In this paper we studied rapid evaporation of a liquid at its superheat limit is one of the few aspects of boiling that is amenable to rigorous theoretical modeling. On the other hand the classical theory of bubble nucleation is reviewed and recent developments are presented that have been proposed for improving the treatment of the energy of forming bubble molecular dimensions. Application are discussed in which homogeneous nucleation is the most probable mechanism for initiating a phase transition, including thermal ink jet printing processes, rapid decompression of a two phase flow, and vapour explosion of liquids droplets.
Games User Research for independent studios: Tool Development

Formative user test sessions are becoming more integrated in game development cycles. However, user tests are not always feasible or affordable for smaller independent game studios, as they require specialised equipment and expertise. Given the recent growth and prevalence of independent developers, there is a need to adapt games user research methods to conduct fast, easy-to-learn, and affordable user tests. Therefore, our research focuses on developing tools for integrating games user research more effectively in the development cycles of independent studios. The paper showcases two of these tools that are currently underdevelopment in our lab.
Defending Social Networks Against Sybil Attacks

— In the online social networks, the large number of real users can be affected by the various Sybil account. Sybil accounts means the person having the fake account and giving the unwanted friend requests and messages to the real users. In the existing system, the Sybils were only isolated by using the page ranking algorithm. The fake accounts were detected but they were again activated. The best approach to permanently deactivate the Sybil accounts is by using E-VoteTrust algorithm. E-VoteTrust Algorithm is a robust against manipulations of the graph. The goal of E-VoteTrust-based votes assignment is to assign low vote capacity to Sybils and deactivate those fake accounts.
COMPARATIVE ANALYSIS OF APPLYING DEEP-LEARNING ON PID PROCESS

The deep learning approach to machine learning emphasizes high-capacity, scalable models that learn distributed representations of their input. This paper addresses the use of deep learning algorithm to design the controller; to explore the feasibility of applying deep learning into control problems. The proposed deep learning controller is designed by learning discrete and continues PID controller which is most commonly used in industry. The input/output of the PID controller are used as the learning data set for the deep learning network. SAE (Stacked Autoencoder) algorithm is used to design the deep learning controller. We develop an extension of sparse autoencoder by incorporating a stacking 2 autoencoders and softmax layer for hidden units. Unlike the standard autoencoder, our model uses the backpropagation algorithm to fine-tuning which leads to promote category-dependent sharing of learned features, which tends to improve the generalization performance. The simulation is performed using MatLab/Simulink and the detailed results of a comparison study between the proposed deep learning controller and a PID controller was conducted. We also analyzed other neural network based control system in comparison to our proposed model. It is demonstrated that neural network based controllers can perform even better than conventional controllers.
ACOUSTIC SCENE CLASSIFICATION BASED ON LIGHTWEIGHT CNN WITH EFFICIENT CONVOLUTIONS Technical Report

This technical report is for the Task 1B Acoustic scene classification of the IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE). Targeting low complexity solutions for the classification problem in term of model size, a kind of lightweight Convolutional Neural Network (CNN) with efficient convolutions is designed. The network is constructed by a kind of improved bottleneck block based on the inverted residual linear bottleneck block. In the improved bottleneck block, the operations of Detpthwise Channel Ascent (DCA) and Group Channel Descent (GCD) are used to replace pointwise convolution to realize efficient channel transformation. The designed network is denoted by CNN-BDG in this report. CNN-BDG realizes a better performance which is 4.46% higher than the baseline model in the validation set. Besides, the parameters are reduced to about 30% compared to the baseline model.
Chemical and microbiological characterization of primary
biological aerosol particles at the boreal forest

Abstract. Primary biological aerosol particles (PBAPs) play an important role in the interaction between biosphere, atmosphere and climate, affecting cloud and precipitation formation processes. The contribution of pollen, plant fragments, spores, bacteria, algae and viruses to PBAPs is well known. In order to explore the complex interrelationships between airborne and particulate chemical traces (amino acids, saccharides), gene copy numbers, gas phase chemistry and the particle size distribution, 84 size-segregated aerosol samples from four particle size fractions ( 10 µm) were collected at SMEAR II station, Finland in autumn 2017. The gene copy numbers and size distribution of bacteria, Pseudomonas and fungi in PBAPs were determined by DNA extraction and amplification. In addition, free amino acids (19) and saccharides (8) were analyzed in aerosol samples by hydrophilic interaction liquid chromatography -mass spectrometry (HILIC-MS). Different machine learning (ML) approaches, such as cluster analysis, discriminant analysis, neural network and multiple linear regression (MLR) were used for the clarification of several aspects related to the PBAPs composition. Clear variations were observed for the composition of PBAPs as a function of the particle size. In most cases, the highest concentration values, gene copy numbers in the case of microbes, were observed for 2.5–10 µm particles followed by > 10 µm, 1–2.5 µm and
Changes in particle sizes and geochemistry of Siyah Keshim lagoon sediment of Gilan province to determine origin and tectonic position of sediment

Useful information was obtained about the environmental condition of this region such as energy, sediment location, origin, sediment carrying path, pond evolutionary process, and tectonic conditions and origins of sediments by studying physical and geochemical sediment changes processes in place and time, distribution of sediments and elements in lagoon bed, and also identification the effective factors on sediment distribution model. In this regard, 59 sediment samples were taken from Siyah Keshim lagoon and were analyzed chemically and aggregation by XRF and ICP-MS technic. Adaptation of data by Folk diagrams showed that this region is placed in a range of sand, muddy sand, sand with a little gravel, muddy sand with a little gravel, and silty sand. Weak to medium sorting and negative tilting shows sediment in a coastal area. Geochemical evidence shows that SiO2/Al2O3 ratio in these sediments is 2.6-3.7. In addition, Na2O value shows relatively low sediment investigation for sediments of this lagoon. Moreover, determination of the weathering effect in origin place by the chemical index of alteration (CIA) and chemical weathering index (CWI) shows intensive chemical alternation on sediments. Index of combined variety was averagely 1.54 in the studied sediments and show that sediments resulted from the first cycle sediment. Using tectonic separating diagrams based on the primary and secondary oxidants percentage show the sediment in the active continent margin (ACM), continent-island arc (CIA), and oceanic island arc (OIA) and shows that the studied sediments are related to subduction margin.
Spread modelling: a suitable tool to explore the role of human-mediated dispersal in the range expansion of the yellow-legged hornet in Europe

Abstract Invasive species can spread locally on their own and can be introduced at long distance by humans. Here, we show how a spread model can be used to explore the role of humans in the range expansion of the invasive yellow-legged hornet, Vespa velutina nigrithorax, in Europe with a special focus on some islands. In 2017, the hornet distribution in France, southern Belgium, south-eastern Germany and northern Spain could largely be explained by the insect’s own dispersal while the occurrence in Portugal, Italy, the Netherlands and Great Britain likely results from human-mediated dispersal. However, in the following years, it could spread to Portugal, Italy and Great Britain also by its own means. The yellow-legged hornet has likely reached the Channel Islands by its own flight but it could hardly reach the Mediterranean islands. Hence, the infestation in Majorca likely results from an accidental introduction. When simulating human-mediated dispersal in the Mediterranean islands, the hornet density would remain relatively low anyhow. Assessing the means of dispersal is important in terms of pest management as the target is either to reduce the spread rate and the population density, or to reduce the risk of entry.
Customer basket heterogeneity: how to measure it and some possible business applications

Abstract Companies offering a wide range of products may have an interest in measuring the degree of diversity of their clients’ shopping baskets as an indicator of consumer behaviour. Customers buying a wide range of products are somehow more dependent on the business and their switching costs might be higher compared to others that only buy a small number of products from your catalogue. We aim to provide companies with a tool to measure how heterogeneous their clients are in terms of the composition of their shopping basket. First, the objective of this paper is to take advantage of some approaches used in other fields to create a new measurement. Second, we will show some possible applications of this indicator in a business context. We consider that a client with low heterogeneity is not highly dependent on the business and is more likely to defect. To check if this intuition is true, we will test the dependence of heterogeneity and churn with real data. By proving our hypothesis, we will be potentially enriching churn models with a new explanatory variable, and we could prevent the defection of those clients scoring low heterogeneity by making the appropriate marketing decisions.
Police-community engagement and the affordances and constraints of social media

ABSTRACT This article provides an analysis of the ‘affordances’ and ‘constraints’ of technology-mediated police-community engagement in the United Kingdom (UK). Whilst there has been optimism that social media may transform police communicative practice and help democratise policing, studies suggest that this potential has yet to be realised. Drawing on in-depth interviews with communications professionals, the article demonstrates that social media may afford constabularies visibility, editability, and association. However, organisational, individual and technological factors influence whether these affordances are achieved. This article adds to the literature by demonstrating how citizen engagement with mediated communication is not inevitable. It is instead a product of what the technology affords, the relationship between the technology and its users, and the context within which it is used.
A DISCUSSION OF THAI STUDENT TEACHERS’ EXPERIENCES OF CULTURE SHOCK DURING THEIR STUDY IN INDONESIA

Culture shock aspect is such a common issue that is experienced among students who studyabroad. The causes of culture shock aspect usually are anxiety and the lack of interculturalcommunication competence. Most of studies in the previous study tend to discuss the importanceof intercultural communication competence and only describe the kinds of culture shock. Thus,to fill this empirical void, this study aims to investigate Thai student teachers’ experiences ofintercultural communication competence and how they handle their culture shock during study inIndonesia. In order to understand more about culture shock aspects, we used culture shock andaxiety theory by Oberg (1960) and Dornyei (2005). The study is employed qualitative method.Participants in this research were two Thai student teachers who have lived for more or less 4years in one of Islamic universities in Yogyakarta. , They are from different batch and major. Thedata were obtained by in-depth interview. We analyzed the data by using thematic analysismethod by Braun a Clarke (2006). The finding showed that all participants experienced theculture shock symptoms stages, such as tension of adaptation, sense of loss and rejection fromenvironment, rejected by new culture, unpredictable anxiety, and feeling of helplessness at thefirst time they studied in Indonesia. There was also an interesting finding that both of them hadthe lack of intercultural communication competence, and also the anxiety leads them to survivein Indonesia. Keywords: Culture Shock Symptoms, Intercultural Communication Competence, Anxiety
Uncertain Adolescent Educational Expectations and College Matriculation in the Wake of the Great Recession

ABSTRACT Though contemporary adolescents in the United States have ambitious educational goals, a sizable number of youth express uncertainty about their future educational attainment. Using data from the High School Longitudinal Study of 2009 (n = 17,340), we investigate whether uncertainty in educational expectations in adolescence is associated with college matriculation and dropout. Approximately 21% of youth expressed uncertainty about their future educational attainment, and the odds of attending college were lower among uncertain teens compared to youth who expected at least 4-year degrees. Among college matriculants, however, uncertain expectations in adolescence did not increase the risk of early college dropout.
A landscape perspective on rates of multiple paternity and brood parasitism among Greater Prairie-Chickens across Kansas, USA

ABSTRACT Fragmentation and degraded habitat conditions can result in increased competition for critical resources, altered mating systems, and can eventually result in population declines or extinction. We investigated the degree to which habitat degradation and habitat loss impacted the breeding ecology of Greater Prairie-Chickens at 3 study sites across relatively intact grasslands in Kansas, USA. Across all 3 study systems, we found similar rates of multiple mating by females at 14–20% of broods. In addition, we found evidence for facultative nest parasitism of conspecific females. Prairie-chicken females inhabiting more intact and less fragmented landscapes with a higher probability of survival did not engage in parasitic egg laying, whereas ∼17% of females inhabiting a more fragmented and isolated landscape engaged in parasitic egg laying. Parasitic egg layers tended to be older females that parasitized nests of yearling females. Parasitic egg layers only laid parasitically after an initial nesting attempt failed. Parasitic laying females all renested and hatched their own clutches. When counting parasitically laid eggs, parasitic egg-laying females laid significantly more eggs than nonparasitic egg layers and, as a result, had 25% greater fecundity. This case study across the relatively intact grasslands of Kansas highlights how land use and management can influence adaptive life history traits and population stability. Consequently, understanding these relationships will be essential to developing effective future conservation and management plans for prairie-grouse.