Miracle-dz/UniFAR-FTUs huggingface dataset:
Adoption of Instant Messaging Technologies by University Students

The main objective of this paper is to better understand the nature and patterns of students’ socialization patterns in relation to the adoption of Instant Messaging (IM) systems. A model based on the Extended Planned Behavior Theory (EPBT) was applied to a sample of 80 students of software engineering at the University of New South Wales, Australia. Based on the EPBT model, a questionnaire was administered to these students. A number of key concepts were identified in relation to the students’ adoption of IM. It was also found that students use IM to support a number of task-related purposes such as collaborating with their classmates about group work and assignments, as well as for scheduling and coordinating meetings and significant results were obtained.
Midregional pro-atrial natriuretic peptide and procalcitonin improve survival prediction in VAP

Ventilator-associated pneumonia (VAP) affects mortality, morbidity and cost of critical care. Reliable risk estimation might improve end-of-life decisions, resource allocation and outcome. Several scoring systems for survival prediction have been established and optimised over the last decades. Recently, new biomarkers have gained interest in the prognostic field. We assessed whether midregional pro-atrial natriuretic peptide (MR-proANP) and procalcitonin (PCT) improve the predictive value of the Simplified Acute Physiologic Score (SAPS) II and Sequential Related Organ Failure Assessment (SOFA) in VAP. Specified end-points of a prospective multinational trial including 101 patients with VAP were analysed. Death <28 days after VAP onset was the primary end-point. MR-proANP and PCT were elevated at the onset of VAP in nonsurvivors compared with survivors (p = 0.003 and p = 0.017, respectively) and their slope of decline differed significantly (p = 0.018 and p = 0.039, respectively). Patients with the highest MR-proANP quartile at VAP onset were at increased risk for death (log rank p = 0.013). In a logistic regression model, MR-proANP was identified as the best predictor of survival. Adding MR-proANP and PCT to SAPS II and SOFA improved their predictive properties (area under the curve 0.895 and 0.880). We conclude that the combination of two biomarkers, MR-proANP and PCT, improve survival prediction of clinical severity scores in VAP.
Mobile-Based Intelligent Transportation for Bus Commuters Based on Twitter Analytics

In this paper, we present an intelligent, state-of-the-art, mobile-based transportation system called SAFAR (Safe and Fast around the Road), which provides dynamic information to Karachi bus commuters concerning any type of violence incident which has occurred farther ahead from their current location on the current bus route. Using named entity recognition techniques, we have trained SAFAR to recognize the location and method of violence incident along with the casualty information (if available) from live Twitter news feeds. Using the well-known A* heuristic search algorithm, SAFAR also recommends alternative routes to reach the destination in case of any violence up ahead. SAFAR has a competitive violence detection accuracy of 80% on a test corpus as well as in an online evaluation with real users. Finally, a subjective evaluation of these users reveals satisfactory performance of SAFAR across several dimensions.
Acquisition of nominal morphophonological alternations in Russian

Morphophonological alternations can make target-like production of grammatical morphemes challenging due to changes in form depending on the phonological environment. This article explores the acquisition of morphophonological alternations involving the interacting patterns of vowel deletion and stress shift in Russian-speaking children (aged 4;0–7;11) using a ‘wug’ test with real and nonce words. Depending on the phonological context, participants were expected to either delete vowels (e.g. ko’mokNom,sg – kom’kaGen,sg) or preserve them (e.g. pji’lotNom,sg – pji’lotaGen,sg). The results showed that children’s sensitivity to morphophonological patterns increases with age: 4-year-olds tended to preserve underlying vowels and stress across conditions, whereas older children demonstrated growing accuracy, at least with real words. Stressed vowels were more appropriately alternated and preserved across conditions, suggesting suprasegmental effects on the acquisition of segmental alternation patterns in Russian.
Institute of Transport and Logistics Studies Working Paper Itls‐wp‐16‐06 Experience Conditioning in Modal Choice Modelling – Does It Make a Difference? Title: Experience Conditioning in Modal Choice Modelling – Does It Make a Difference?

It is often suggested that real experience counts when making choices and that choice responses are likely to be different after an individual has experienced specific alternatives. This has links with hypothetical bias associated with stated choice (SC) experiments as well as with the concerns over the reliability of revealed preference (RP) data obtained on alternatives that individuals have had little if any exposure to through use or consumption. If we had a way of identifying experience with each alternative in a choice set, constructed from RP or SC data, might we obtain different estimates of key behavioural outputs such as willingness to pay and elasticity? What if we weighted each alternative associated with each observation by some measure of overt experience? A reason why this might be important is that it enables us to recognise that as more individuals use particular alternatives, especially new infrastructure such as toll roads and public transport, the forecasts of benefits are likely to converge closer to estimates of utility in which the parameter estimates (and hence implied willingness to pay and elasticities) are conditioned on experience, on the reasonable hypothesis that future predictions reflect growing levels of exposure and hence experience with specific alternatives. We use an RP data set collected in Sydney on commuter mode choice to investigate this phenomenon, comparing the value of travel time savings, and cost and travel time elasticities associated with car and public transport under a model in which we do not condition the time and cost parameters on experience, and a model in which we do, using frequency of use as a proxy indicator of overt experience. The differences are very marked, and suggest, albeit from a single study, that this topic appears to have great merit as a candidate source of potential errors in forecasts. We suggest a way forward in which this evidence on experience might be applied to obtain revised forecasts of modal shares.
From Isovists to Visibility Graphs: A Methodology for the Analysis of Architectural Space

An isovist, or viewshed, is the area in a spatial environment directly visible from a location within the space. Here we show how a set of isovists can be used to generate a graph of mutual visibility between locations. We demonstrate that this graph can also be constructed without reference to isovists and that we are in fact invoking the more general concept of a visibility graph. Using the visibility graph, we can extend both isovist and current graph-based analyses of architectural space to form a new methodology for the investigation of configurational relationships. The measurement of local and global characteristics of the graph, for each vertex or for the system as a whole, is of interest from an architectural perspective, allowing us to describe a configuration with reference to accessibility and visibility, to compare from location to location within a system, and to compare systems with different geometries. Finally we show that visibility graph properties may be closely related to manifestations of spatial perception, such as way-finding, movement, and space use.
Face familiarity promotes stable identity recognition: exploring face perception using serial dependence

Studies suggest that familiar faces are processed in a manner distinct from unfamiliar faces and that familiarity with a face confers an advantage in identity recognition. Our visual system seems to capitalize on experience to build stable face representations that are impervious to variation in retinal input that may occur due to changes in lighting, viewpoint, viewing distance, eye movements, etc. Emerging evidence also suggests that our visual system maintains a continuous perception of a face's identity from one moment to the next despite the retinal input variations through serial dependence. This study investigates whether interactions occur between face familiarity and serial dependence. In two experiments, participants used a continuous scale to rate attractiveness of unfamiliar and familiar faces (either experimentally learned or famous) presented in rapid sequences. Both experiments revealed robust inter-trial effects in which attractiveness ratings for a given face depended on the preceding face's attractiveness. This inter-trial attractiveness effect was most pronounced for unfamiliar faces. Indeed, when participants were familiar with a given face, attractiveness ratings showed significantly less serial dependence. These results represent the first evidence that familiar faces can resist the temporal integration seen in sequential dependencies and highlight the importance of familiarity to visual cognition.
An improved occlusion handling for appearance-based tracking

The object occlusion is one serious issue in object tracking, especially when objects merge or split. The tracker may fail if it has no adaptability to such variations. In this paper, we present an improved solution of the appearance-based tracking for occlusion handling. The proposed method first recognizes the motion situations (merging and splitting of the moving objects), and then applies different template finding approach on each motion to get an association between detected blobs and targets. By this way, the accuracy of the data association can be improved when object occlusion occurs. Experiments were conducted to compare our results with those by other popular tracking algorithms. The proposed method is found robust for short-time complete occlusion and partial occlusion.
On Hopf Algebras with Positive Bases

We show that if a finite dimensional Hopf algebra H over C has a basis with respect to which all the structure constants are nonnegative, then H is isomorphic to the bi-cross-product Hopf algebra constructed by Takeuchi and Majid from a finite group G and a unique factorization G = G+ G− of G into two subgroups. We also show that Hopf algebras in the category of finite sets with correspondences as morphisms are classified in a similar way. Our results can be used to explain some results on Hopf algebras from the set-theoretical point of view.
Video segmentation using vector-valued diffusion and clustering

In this paper, we propose a user-assisted video segmentation algorithm based on color information to alleviate oversegmentation problems. We perform intra-frame segmentation by image simplification, region labeling, and color clustering. In this paper, we also present a discrete three dimensional diffusion model for easy implementation. The statistical property of each labeled region is used to estimate the number of total clusters, and agglomerative hierarchical clustering is performed with the estimated number of clusters. Since the proposed clustering algorithm counts each region as a unit, it does not generate oversegmentation problems along region boundaries. For inter-frame segmentation, we employ a look-up table for foreground color clusters, track the foreground regions, and utilize those information to extract moving objects.
Endothelial sulfated sialyl Lewis x glycans, putative L-selectin ligands, are preferentially expressed in bronchial asthma but not in other chronic inflammatory lung diseases.

Lymphocyte infiltrate is a hallmark of inflammatory responses. We have previously shown that de novo-induced endothelial sialyl Lewis x (sLex) expression guides lymphocytes in an L-selectin-dependent manner to sites of acute organ transplant rejections. In this research, we have analyzed five groups of chronic lung inflammations to determine the presence of properly glycosylated, i.e., sulfated, sLex-decorated, L-selectin ligands. Two anti-sLex (2F3 and HECA-452) and one anti-6- and/or 6'-sulfated and/or 6,6'-bisulfated (MECA-79) monoclonal antibodies (mAbs) were used. The control lung specimens did not express L-selectin ligands on endothelium. In contrast, the endothelial staining intensity and the number of positive peribronchial venules and capillaries with mAbs 2F3, HECA-452, and MECA-79 were significantly greater in bronchial biopsies from patients with asthma compared with normal specimens (P<0.003). However, no significant increase of peribronchial endothelial reactivity with these antibodies was observed in adult respiratory distress syndrome, chronic bronchitis, fibrosing alveolitis, and granulomatous inflammation compared with controls. These data suggest that sulfated sLex glycans, acting putatively as ligands for L-selectin, could be instrumental in lymphocyte extravasation into human peribronchial lung tissue during asthma, but not so important in several other inflammatory lung diseases.
RSS Based Localization Using a New WKNN Approach

Location aware applications are constantly under development. By using an Indoor Location System (ILS), a user can localize himself, plan an indoor route and destination, or receive useful information and services in malls, airports, shopping centers, etc. To this purpose, various signal strength or timing based localization methods exist, each one having their own advantages and disadvantages. Localization based on the Received Signal Strength (RSS) methods, typically require only off-the-shelf equipment to operate. Moreover, they can utilize the existing infrastructure. This paper presents a new method on how to use the captured RSS values for localization purposes. The proposed method analyses a captured signal over a short distance and stores it into the fingerprint database for later comparison, rather than using an average value obtained from static measurements. Real-world measurements are used in order to validate our approach.
When IT Meets Telco: RAN as a Service

Network virtualization functions (NFV) and software-defined networking (SDN) are changing the landscape of the telecommunications industry, particularly infrastructure and network systems of Telco operators with the introduction of cloud computing, paradigms of virtualization and software approaches. In this paper, we describe a demonstrator which shows how IT technologies reduce the time of deployment of a wireless infrastructure. In less than 60s, a wireless LTE network is available for connecting Smartphone's. In this demo, the eNodeB, virtualized using docker containers, is orchestrated by OpenStack heat.
Research on the key techniques of wireless communication for emergency information system

As China's continuous improvement in the degree of information, the wireless communication network has covered all regions of the country, and information has also brought a great deal of information network security issues. In this paper, firstly, the information security emergency response procedures and disposal system are proposed according to the comprehensive analysis of weak links in information security defense system. Secondly, the OFDM - MIMO and the support vector machine technologies are applied to deal with unexpected information security incidents. Experiment results show that these technologies are reasonable in practical application. Finally, an example for specific application is given to clarify the processes of information security emergency response. The risks and potential losses met by important social information systems can be reduced through the timely detection, tracking, analysis and recognition of a major hazard information security incident and proper response. it is very important to strengthen information security emergency response capabilities in the future.
Fermionic vacuum polarization by a cylindrical boundary in the cosmic string spacetime

The vacuum expectation values of the energy-momentum tensor and the fermionic condensate are analyzed for a massive spinor field obeying the MIT bag boundary condition on a cylindrical shell in the cosmic string spacetime. Both regions inside and outside the shell are considered. By applying to the corresponding mode sums a variant of the generalized Abel-Plana formula, we explicitly extract the parts in the expectation values corresponding to the cosmic string geometry without boundaries. In this way the renormalization procedure is reduced to that for the boundary-free cosmic string spacetime. The parts induced by the cylindrical shell are presented in terms of integrals rapidly convergent for points away from the boundary. The behavior of the vacuum densities is investigated in various asymptotic regions of the parameters. In the limit of large values of the planar angle deficit, the boundary-induced expectation values are exponentially suppressed. As a special case, we discuss the fermionic vacuum densities for the cylindrical shell on the background of the Minkowski spacetime.
A system to analyze Twitter data for social science study

Twitter data has been becoming more interesting in social science study since it can effectively reflect a nature of human behavior. Unfortunately, it is complicated to analyze Twitter data, and the existing tools are not suitable for this domain. In this paper, we present a system that is tailored to analyze Twitter data for the social science research. The system comprises four main functions including: (i) case study management, (ii) user/keyword search, (iii) interest group customization, and (iv) user-friendly analysis and visualization. Furthermore, three kinds of measures: connectivity, reciprocity, and mentioning, are presented to support the analysis process. Some of them are selectively employed from other domains, while others are invented in this work. The experiments were conducted on more than two millions Twitter activities related to the political situation in Thailand during May-June 2014. The results showed that our proposed measures can reveal useful knowledge in Twitter social group with the aid of the system that can provide scenario-based analysis and capture interactions among user groups.
Immunogenicity of Anaplasma marginale Type IV Secretion System Proteins in a Protective Outer Membrane Vaccine

ABSTRACT Rickettsial pathogens in the genera Anaplasma and Ehrlichia cause acute infection in immunologically naive hosts and are major causes of tick-borne disease in animals and humans. Immunization with purified outer membranes induces protection against acute Anaplasma marginale infection and disease, and a proteomic and genomic approach recently identified 21 proteins within the outer membrane immunogen in addition to the well-characterized major surface proteins MSP1 to MSP5. Among the newly described proteins were the type IV secretion system (TFSS) proteins VirB9, VirB10, and conjugal transfer protein (CTP). In other gram-negative bacteria, TFSS proteins form channels, facilitate secretion of molecules, and are required for intracellular survival. However, TFSS proteins have not been explored as vaccine antigens. In this study we demonstrate that in Anaplasma marginale outer membrane-vaccinated cattle, VirB9, VirB10, and CTP are recognized by serum immunoglobulin G2 (IgG2) and stimulate memory T-lymphocyte proliferation and gamma interferon secretion. VirB9 induced the greatest proliferation in CD4+ T-cell lines, and VirB9-specific CD4+ T-cell clones responded to three A. marginale strains, confirming the VirB9-specific T-cell responses are directed against epitopes in the native protein. The three TFSS proteins are highly conserved with orthologous proteins in Anaplasma phagocytophilum, Ehrlichia chaffeensis, and Ehrlichia canis. Recognition of TFSS antigens by CD4+ T cells and by IgG2 from cattle immunized with the protective outer membrane fraction provides a rationale for including these proteins in development of vaccines against A. marginale and related pathogens.
Applying Gaussian mixture model on Discrete Cosine features for image segmentation and classification

Content-based image retrieval (CBIR) is the process of searching digital images in a large database based on features, such as colour, texture and shape (so-called visual content) of a given query image. Consequently, retrieved images are the most similar in content to the query image. One effective approach is to segment an image into regions (i.e. clusters) of similar colour and texture to capture its visual content. This paper presents a study that applies an adaptive Expectation-Maximization algorithm on Gaussian Mixture Model (EM/GMM) to segment an image according to local colour and texture features extracted from Discrete Cosine Transform coefficients (DCT). The EM algorithm determines rather than imposes the effective number of clusters from the image's content. This paper evaluates the effectiveness of our method by conducting a number of image classification experiments using the k-nearest neighbor (k-NN) classifier. The experiments have shown a clearly marked improvement in image retrieval accuracy of using EM/GMM over the k-means algorithm. The paper is intended to demonstrate the effectiveness of adaptive GMM in segmenting an image and capturing regions of similar colour and texture within an image.
Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review

Objective Research studies show that social media may be valuable tools in the disease surveillance toolkit used for improving public health professionals’ ability to detect disease outbreaks faster than traditional methods and to enhance outbreak response. A social media work group, consisting of surveillance practitioners, academic researchers, and other subject matter experts convened by the International Society for Disease Surveillance, conducted a systematic primary literature review using the PRISMA framework to identify research, published through February 2013, answering either of the following questions: Can social media be integrated into disease surveillance practice and outbreak management to support and improve public health? Can social media be used to effectively target populations, specifically vulnerable populations, to test an intervention and interact with a community to improve health outcomes? Examples of social media included are Facebook, MySpace, microblogs (e.g., Twitter), blogs, and discussion forums. For Question 1, 33 manuscripts were identified, starting in 2009 with topics on Influenza-like Illnesses (n = 15), Infectious Diseases (n = 6), Non-infectious Diseases (n = 4), Medication and Vaccines (n = 3), and Other (n = 5). For Question 2, 32 manuscripts were identified, the first in 2000 with topics on Health Risk Behaviors (n = 10), Infectious Diseases (n = 3), Non-infectious Diseases (n = 9), and Other (n = 10). Conclusions The literature on the use of social media to support public health practice has identified many gaps and biases in current knowledge. Despite the potential for success identified in exploratory studies, there are limited studies on interventions and little use of social media in practice. However, information gleaned from the articles demonstrates the effectiveness of social media in supporting and improving public health and in identifying target populations for intervention. A primary recommendation resulting from the review is to identify opportunities that enable public health professionals to integrate social media analytics into disease surveillance and outbreak management practice.