Miracle-dz/UniFAR-FTUs huggingface dataset:
Electronic [ re ] constitution of groups : Group dynamics 5 from face-to-face to an online setting 6

12 Abstract The authors work as online tutors for a BSc (Hons) physiotherapy programme at 13 Coventry University in the United Kingdom. This paper represents a stage in our 14 developing understanding, over a 3 year period, of the impact of group dynamics on online 15 interaction among physiotherapy students engaged in sharing with their peers their first 16 experiences of clinical practice. The literature exploring online interaction tends to situate 17 meaning either in theories borrowed from conventional face-to-face interaction or on virtual 18 interaction. Research focusing on ‘blended learning’ that combines face-to-face and online 19 interaction is limited in terms of considering how group dynamics impact groups that are 20 constituted and reconstituted in the two very different learning contexts. Using a case study 21 approach, the authors consider how group dynamics change as groups move from face22 to-face to online collaboration in pursuit of learning objectives. We character typical features 23 of the cases and draw conclusions based on similarities and differences. Findings suggest that 24 group learning is linked to group cohesion, which appears to be mediated by social and 25 cognitive factors students bring with them. Social presence appears vital to positive group 26 dynamics and is a precursor to cognitive presence, which develops when groups rise above 27 their desire to be sociable and supportive. Group dynamics, whether positive or negative, and 28 their consequent impact on interaction appear to be relatively stable across contexts once the 29 group scene is set through face-to-face interaction. Engagement and interaction of individual 30 students, however, can alter when face-to-face interaction moves online.
Excessive Cytokine Response to Rapid Proliferation of Highly Pathogenic Avian Influenza Viruses Leads to Fatal Systemic Capillary Leakage in Chickens

Highly pathogenic avian influenza viruses (HPAIVs) cause lethal infection in chickens. Severe cases of HPAIV infections have been also reported in mammals, including humans. In both mammals and birds, the relationship between host cytokine response to the infection with HPAIVs and lethal outcome has not been well understood. In the present study, the highly pathogenic avian influenza viruses A/turkey/Italy/4580/1999 (H7N1) (Ty/Italy) and A/chicken/Netherlands/2586/2003 (H7N7) (Ck/NL) and the low pathogenic avian influenza virus (LPAIV) A/chicken/Ibaraki/1/2005 (H5N2) (Ck/Ibaraki) were intranasally inoculated into chickens. Ty/Italy replicated more extensively than Ck/NL in systemic tissues of the chickens, especially in the brain, and induced excessive mRNA expression of inflammatory and antiviral cytokines (IFN-γ, IL-1β, IL-6, and IFN-α) in proportion to its proliferation. Using in situ hybridization, IL-6 mRNA was detected mainly in microglial nodules in the brain of the chickens infected with Ty/Italy. Capillary leakage assessed by Evans blue staining was observed in multiple organs, especially in the brains of the chickens infected with Ty/Italy, and was not observed in those infected with Ck/NL. In contrast, LPAIV caused only local infection in the chickens, with neither apparent cytokine expression nor capillary leakage in any tissue of the chickens. The present results indicate that an excessive cytokine response is induced by rapid and extensive proliferation of HPAIV and causes fatal multiple organ failure in chickens.
Semi-automatic remote medicine monitoring system of miners

The advances in biological sensors have resulted in rapid development of various remote medical care systems, which enable extended independent living at home and improvement of life quality for individuals. Now, it's possible for us to monitor not only people's physical health but also mental health. Considering incomplete utilization of mental sensors and electronic health record in most Remote medical care systems of miners, we propose a remote medical care system to monitor miners' physical and mental health, with the ontology model of Electronic health record knowledge. In this study, health solutions about the EHR and emotion (ontology model of EHR and emotion detection method) are shown. Finally, some preliminary tests are given out to show this system's practicability and novelty.
Evaluating fit of the Prospective and Retrospective Memory Questionnaire (PRMQ) in a Nigerian adult population

This study aimed to evaluate the latent structure of the Prospective and Retrospective Memory Questionnaire (PRMQ) and to estimate the reliability and validity of scores from the measure in a Nigerian adult population (N = 758; age range = 18 - 63 years; females = 52.24%). Respondents also completed the Cognitive Failures Questionnaire (CFQ). The data were analysed utilising confirmatory factor analysis (CFA). The results suggest the PRMQ to have a tripartite structure characterised by the following features: general memory, plus eight prospective and eight retrospective memory items. Scores from the PRMQ had evidence of convergent validity with the CFQ. The reliability of scores from the PRMQ was of acceptable magnitude for the research purposes investigated in the study.
Understanding context-awareness in business process design

In recent years, flexibility has emerged as an important guiding principle in the design of business processes. However, research on process flexibility has traditionally been solely focused on ways of how the demand for process flexibility can be satisfied by advanced process modelling techniques, i.e., issues intrinsic to the process. This paper proposes to extent existing research by studying the extrinsic drivers for process flexibility, i.e. an analysis of the root causes that drive the demand for flexible processes. These drivers can be found in the context of the process, which may include among others time, location, weather, legislation, culture or performance requirements. We argue for a stronger and more explicit consideration of these contextual factors in the design and modelling of business processes. Based on a real case study, we discuss how context can be conceptualized and integrated with existing approaches to business process design. These extensions are an essential foundation for the definition and implementation of agile processes and as such of high practical and theoretical value.
An Efficient Algorithm to Reduce the Semantic Gap between Image Contents and Tags

With the rapid growth in the new era of Internet Technology, image retrieval is an active and traditional method for searching the images by keywords or by images from the large amount of image database. As tags gives the descriptive information of an image on the web. Due to noisy nature in tags, it becomes necessary to correlate both image content and tag information for retrieval purposes. However, semantic gap is a major problem in the image processing concept. Therefore, our presented research is going to reduce the problem of semantic gap by applying techniques to extract low level features of an image such as color, texture and edge. Then, construction of a mixed graph between image and tag to perform random walk on graph for getting accurate results in an efficient way. Experimental results show the effectiveness of our approach.
Automated Termination in Model-Checking Modulo Theories

We identify sufficient conditions to automatically establish the termination of a backward reachability procedure for infinite state systems by using well-quasi-orderings. Besides showing that backward reachability succeeds on many instances of problems covered by general termination results, we argue that it could predict termination also on interesting instances of the reachability problem that are outside the scope of applicability of such general results. We work in the declarative framework of Model Checking Modulo Theories that permits us to exploit recent advances in Satisfiability Modulo Theories solving and model-theoretic notions of first-order logic.
Automatic Staging of Audio with Emotions

Current day text-to-speech technologies are mature enough to be acceptable in quality for the users. There is still a large gap between a synthesised speech and a real human speech due to lack of expressions and emotions. Geneemo is a technology for automatic addition of emotions and expressions to any audio. The process of staging the text is to dramatize it. The text is enriched and transformed into a performance. Similarly, "staging the audio" refers to extending text dramatisation to audio by enriching emotionally neutral audio content into a natural human speech with real expressions. The audio can be generated by any text-to-speech technology. The aim of the project is to make human computer interactions as natural as possible with expressive speech. This also opens up a portfolio of applications replacing real human voices.
Security in Delay Tolerant Networks for the Android Platform

Security Block (ASB) The structure of an ASB is presented in g. 3.2, and contains the following elds. • Block type code: Speci es the type of the block and is included in all DTN blocks. As of security, it speci es whether the block is BAB (0x02), PIB (0x03), PCB (0x04) or ESB (0x09). • Block processing control ags: It is de ned in the Bundle Protocol and is common to all DTN blocks. • EID references: Is an optional eld that contains the security-source and security-destination of the present bundle. • Block data length: Contains the length (bytes) of the remainder of the block. • Ciphersuite ID: Speci es the ciphersuite that is being used among the registered ones. • Ciphersuite ags: Control ags that mandate the security functionality. • Correlator: This optional eld is used to associate several related instances of a security block when this functionality is needed • Ciphersuite parameters and Security result: These two elds are composed of tuples represented as type-length-value, and are used by the CHAPTER 3. DTNRG PROTOCOLS 22 di erent ciphersuites to store security results. Some of the types that can be included are: Initialization Vector, encoded key information, salt, PCB Integrity Check value (ICV). Figure 3.2: Abstract Security Block (ASB) Payload Con dentiality Block (PCB) PCB is used to indicate that the bundle payload has been encrypted at the PCB security-source, and it will be decrypted at the security-destination. A ciphersuite that operates with a PCB should rstly generate a secure random key, called bundle encryption key (BEK) and use this key to encrypt the payload of the bundle. After that, it should encrypt the BEK with a long term encryption key (e.g., a public key) and send this encrypted key inside the PCB. In addition, a data integrity mechanism should be implemented to detect tampering into the bundle payload content. Bundle Authentication Block (BAB) BAB provides integrity and authenticity of the whole bundle on a hop-byhop basis, i.e., from a security-capable node to the next security-capable node (which might be actually more than one node distance). Payload Integrity Block (PIB) The PIB provides integrity and authenticity for the payload in an end-toend basis, starting from a security-source, which generates a signature of the block, and ending in the security-destination, which veri es the integrity of the received payload. Intermediate nodes could eventually check the integrity in case that they are in possession of the needed credentials. CHAPTER 3. DTNRG PROTOCOLS 23 Extension Security Block (ESB) The ESB is a later addition to the Bundle Security Protocol, which allows the protection of blocks not considered by the previous services. The Bundle Protocol allow the creation of speci c-purpose blocks to provide a particular functionality. The previously de ned security blocks aim only at encrypting the bundle payload and integrity protecting the whole bundle. In case that a speci c-purpose extension block needs security, the ESB is the right security block to provide it.
A Formal Knowledge Representation System (FKRS) for the Intelligent Knowledge Base of a Cognitive Learning Engine

It is recognized that the generic form of machine learning is a knowledge acquisition and manipulation process mimicking the brain. Therefore, knowledge representation as a dynamic concept network is centric in the design and implementation of the intelligent knowledge base of a Cognitive Learning Engine CLE. This paper presents a Formal Knowledge Representation System FKRS for autonomous concept formation and manipulation based on concept algebra. The Object-Attribute-Relation OAR model for knowledge representation is adopted in the design of FKRS. The conceptual model, architectural model, and behavioral models of the FKRS system is formally designed and specified in Real-Time Process Algebra RTPA. The FKRS system is implemented in Java as a core component towards the development of the CLE and other knowledge-based systems in cognitive computing and computational intelligence.
Providing victims of crime with information on police response activity: The challenges faced by the police non-emergency call-handler

Police policy in England and Wales is to always explain to a member of the public who contacts the police what will happen as a result of them doing so. During initial contact between a victim of crime and the police, this task often falls to police call-handlers. This article examines information on police response activity provided to victims by police non-emergency call-handlers during such instances of contact. Empirical analysis highlights the importance that call-handlers place on providing accurate information on response activity to those who call the police, and the various challenges that they can encounter when attempting this.
Image Retrieval using Fractional Coefficients of Transformed Image using DCT and Walsh Transform

The paper presents innovative content based image retrieval (CBIR) techniques based on feature vectors as fractional coefficients of transformed images using DCT and Walsh transforms. Here the feature vector size per image is greatly reduced by taking fractional coefficients of transformed image. The feature vectors are extracted in fourteen different ways from the transformed image. Along with the first being all the coefficients of transformed image, seven reduced coefficients sets (as 50%, 25%, 12.5%, 6.25%, 3.125%, 1.5625% ,0.7813%, 0.39%, 0.195%, 0.097%, 0.048%, 0.024%, 0.012% and 0.06% of complete transformed image) are considered as feature vectors. The two transforms are applied on gray image equivalents and the colour components of images to extract Gray and RGB feature sets respectively. Instead of using all coefficients of transformed images as feature vector for image retrieval, these fourteen reduced coefficients sets for gray as well as RGB feature vectors are used, resulting into better performance and lower computations. The proposed CBIR techniques are implemented on a database having 1000 images spread across 11 categories. For each proposed CBIR technique 55 queries (5 per category) are fired on the database and net average precision and recall are computed for all feature sets per transform. The results have shown the performance improvement (higher precision and recall values) with fractional coefficients compared to complete transform of image at reduced computations resulting in faster retrieval. Finally Walsh transform surpasses DCT transforms in performance with highest precision and recall values for fractional coefficients and minimum number of computations up to 0.097% and then DCT takes over
Event sharing in vehicular networks using geographic vectors and maps

By exchanging events in a vehicular ad hoc network (VANET), drivers can receive information that allows them to find relevant places (e.g., parking spaces) or avoid dangerous/undesirable situations (e.g., an accident or a traffic jam). However, developing this kind of information services for drivers calls for new data management approaches, such as an appropriate dissemination protocol and some mechanism to decide when a driver should be alerted. In this paper, we present a data management solution for event exchange in vehicular networks and compare two different approaches for relevance assessment. The first approach relies on the computation of geographic vectors to estimate the relevance of events, whereas the second approach exploits digital road maps. We also describe a prototype that has allowed us to test our proposals in a real environment. Moreover, we present an exhaustive simulation-based experimental evaluation that proves the usefulness of exploiting the information stored in digital road maps for data management and sharing in vehicular networks, which is an important novelty regarding existing works. The experiments also show that the first approach can also be used with a good accuracy, although smaller in some situations, in cars where maps are not available.
A real time hand gesture recognition system using motion history image

Hand gesture recognition based man-machine interface is being developed vigorously in recent years. Due to the effect of lighting and complex background, most visual hand gesture recognition systems work only under restricted environment. An adaptive skin color model based on face detection is utilized to detect skin color regions like hands. To classify the dynamic hand gestures, we developed a simple and fast motion history image based method. Four groups of haar-like directional patterns were trained for the up, down, left, and right hand gestures classifiers. Together with fist hand and waving hand gestures, there were totally six hand gestures defined. In general, it is suitable to control most home appliances. Five persons doing 250 hand gestures at near, medium, and far distances in front of the web camera were tested. Experimental results show that the accuracy is 94.1% in average and the processing time is 3.81 ms per frame. These demonstrated the feasibility of the proposed system.
The Impact of Sleep Disorders on Driving Safety - Findings from the SHRP2 Naturalistic Driving Study

This study is the first examination on the association between seven types of sleep disorder and driving risk using large-scale naturalistic driving study data involving more than 3,400 participants. Regression analyses revealed that females with restless leg syndrome or sleep apnea and drivers with insomnia, shift work sleep disorder, or periodic limb movement disorder are associated with significantly higher driving risk than other drivers without those conditons. Furthermore, despite a small number of observations, there is a strong indication of increased risk for narcoleptic drivers. The findings confirmed results from simulator and epidemiological studies that the driving risk increases amongst people with certain types of sleep disorders. However, this study did not yield evidence in naturalistic driving settings to confirm significantly increased driving risk associated with migraine in prior research. The inconsistency may be an indication that the significant decline in cognitive performance among drivers with sleep disorders observed in laboratory settings may not nessarily translate to an increase in actual driving risk. Further research is necessary to define how to incentivize drivers with specific sleep disorders to balance road safety and personal mobility. The Impact of Sleep Disorders on Driving Safety – Findings from the SHRP2 Naturalistic Driving Study
Dynamic Virtual Machine Scheduling in Clouds for Architectural Shared Resources

Although virtual machine (VM) migration has been used to avoid conflicts on traditional system resources like CPU and memory, micro-architectural resources such as shared caches, memory controllers, and non-uniform memory access (NUMA) affinity, have only relied on intra-system scheduling to reduce contentions on them. This study shows that live VM migration can be used to mitigate the contentions on micro-architectural resources. Such cloud-level VM scheduling can widen the scope of VM selections for architectural shared resources beyond a single system, and thus improve the opportunity to further reduce possible conflicts. This paper proposes and evaluates two cluster-level virtual machine scheduling techniques for cache sharing and NUMA affinity, which do not require any prior knowledge on the behaviors of VMs.
Software Components for Reliable Automotive Systems

System-level integration requires an overall understanding of the interplay of the sub-systems to enable component- based development with portability, reconfigurability and extensibility, together with guaranteed reliability and performance levels. Integration by simple interfaces and plug- and-play of sub-systems, which is the main objective of AUTOSAR, requires solving essential technical problems. We discuss to what degree the existing AUTOSAR standard can support the development of safety- and time-critical software and what is required to move toward the desirable goal of timing isolation when integrating multiple applications into the same execution platform.
Supramolecular Ring Structures of 7-Methylguanine: A Computational Study of Its Self-assembly and Anion Binding

The density functional theory calculations of 7-methylguanine clusters revealed that stable ring assemblies can be formed with or without anions in the center position and hexameric clusters are the most stable and most planar ones. The coordination of anions (Cl−, Br−, NO3−) stabilizes and thus favors the formation of planar aggregates. We believe that the predicted planar structures stabilized by anions are good models for self-assembly structures formed at solid-liquid or solid-gas interfaces. Comparing the bonding and average H-bond energy to reference ribbon calculations we pointed out the presence of the previously introduced cooperativity effect in circular supramolecular structures of 7-methylguanine.
An Empirical Analysis of Price, Quality, and Incumbency in Procurement Auctions

The use of multiattribute auctions for procurement of products and services when both price and quality matter is becoming more frequent. Such auctions often employ scoring rules and are open ended in winner determination. Yet there is a significant gap in the literature on the efficiency of these procurement mechanisms. In this paper, providing a theoretical model and utilizing data from legal service procurement auctions, we study how open-ended scoring auctions can be used effectively in procurement and demonstrate the roles supplier quality and incumbency play in this process. We demonstrate that open-ended auctions can generate substantial savings to a buyer without compromising quality. We study the underlying mechanism and show how the auction format can work to achieve such performance. We find that the buyer's revealed preferences significantly differ from her stated preferences. Finally, we contribute to the understanding of the role of incumbency in procurement auctions by providing evidence that what may be perceived as incumbency bias can in fact be a revelation of preference for quality.