Miracle-dz/UniFAR-FTUs huggingface dataset:
Connected seniors: how older adults in East York exchange social support online and offline

ABSTRACT How do older adults mobilize social support, with and without digital media? To investigate this, we focus on older adults 65+ residing in the Toronto locality of East York, using 42 interviews lasting about 90 minutes done in 2013–2014. We find that digital media help in mobilizing social support as well as maintaining and strengthening existing relationships with geographically near and distant contacts. This is especially important for those individuals (and their network members) who have limited mobility. Once older adults start using digital media, they become routinely incorporated into their lives, used in conjunction with the telephone to maintain existing relationships but not to develop new ones. Contradicting fears that digital media are inadequate for meaningful relational contact, we found that these older adults considered social support exchanged via digital media to be real support that cannot be dismissed as token. Older adults especially used and valued digital media for companionship. They also used them for coordination, maintaining ties, and casual conversations. Email was used more with friends than relatives; some Skype was used with close family ties. Our research suggests that policy efforts need to emphasize the strengthening of existing networks rather than the establishment of interventions that are outside of older adults’ existing ties. Our findings also show that learning how to master technology is in itself a form of social support that provides opportunities to strengthen the networks of older adults.
Constructing Parallel Corpora for Six Indian Languages via Crowdsourcing

Recent work has established the efficacy of Amazon's Mechanical Turk for constructing parallel corpora for machine translation research. We apply this to building a collection of parallel corpora between English and six languages from the Indian subcontinent: Bengali, Hindi, Malayalam, Tamil, Telugu, and Urdu. These languages are low-resource, under-studied, and exhibit linguistic phenomena that are difficult for machine translation. We conduct a variety of baseline experiments and analysis, and release the data to the community.
Research on modeling of Virtual Operation Training Domain Application Systems

The research and development of architecture of Virtual Operation Training Domain Application Systems (VOTDAS) can not only unify the system modeling method, but also realize the reusability of software architecture and components to the maximum degree. Aim at the domain application of virtual operation training, the paper brought out reusable framework of VOTDAS and researched on the modeling method and simulation engine design method of domain application system based on the framework, which can facilitate users to quickly generate the system simulation models for specific applications of various kinds of virtual operation training based on the framework.
Relating folksonomies with Dublin Core

This article presents a research carried out to continue the project Kinds of Tags, which intends to identify elements required for metadata originating from folksonomies. It will provide information that may be used by intelligent applications to assign tags to metadata elements. Despite the unquestionably high value of DC and DC Terms, the pilot study revealed a significant number of tags for which no corresponding properties yet existed. A need for new properties was determined. This article presents the problem, motivation and methodology of the underlying research. It further presents and discusses the findings from the pilot study.
Visual Typo Correction by Collocative Optimization: A Case Study on Merchandize Images

Near-duplicate retrieval (NDR) in merchandize images is of great importance to a lot of online applications on e-Commerce websites. In those applications where the requirement of response time is critical, however, the conventional techniques developed for a general purpose NDR are limited, because expensive post-processing like spatial verification or hashing is usually employed to compromise the quantization errors among the visual words used for the images. In this paper, we argue that most of the errors are introduced because of the quantization process where the visual words are considered individually, which has ignored the contextual relations among words. We propose a “spelling or phrase correction” like process for NDR, which extends the concept of collocations to visual domain for modeling the contextual relations. Binary quadratic programming is used to enforce the contextual consistency of words selected for an image, so that the errors (typos) are eliminated and the quality of the quantization process is improved. The experimental results show that the proposed method can improve the efficiency of NDR by reducing vocabulary size by 1000% times, and under the scenario of merchandize image NDR, the expensive local interest point feature used in conventional approaches can be replaced by color-moment feature, which reduces the time cost by 9202% while maintaining comparable performance to the state-of-the-art methods.
New FDTD model for excitation of microstrip lines

A new simple technique to excite microstrip lines with the finite-difference time-domain method (FDTD) is introduced. In the model, the incident voltages are calculated in an auxiliary ID transmission line that is connected to the 3D problem space at the feeding location. The proposed model allows to extract the scattering parameters with a single 3D FDTD run with a reduced simulation time as compared with many of the well-known excitation models. The model is applied to simulate a microstrip patch antenna with an artificial magneto-dielectric material filling.
Towards a composite map of organisational person–environment fit

This paper explores the concept of person–organisation fit to extend the existing literature by revealing organisational members’ sense of fit. This was achieved by using causal mapping and storytelling. These techniques provoked individuals to describe the factors relating to their sense of fit and their causal attributions of these factors utilising specific examples and explanatory narratives. One outcome of this study is the generation of a composite map of factors influencing people’s fit which represents a substantial development of our understanding of how different forms of person–environment fit combine. The findings of the study suggest that respondents’ sense of fit is influenced by five main factors: job, people, organisation, employment and work/life balance. A further thirteen sub-dimensions relating to these factors are also outlined in the paper. The importance of fit and misfit as independent variables in the explanation of specific work-related behavioural outcomes are discussed. The determinants of people’s behaviour have been the interest of much conceptual and empirical research (Bowers, 1973; Chatman, 1989, 1991; Pervin, 1978). After years of debate there is now general agreement that individual characteristics, aspects of the situation, and, crucially, the interaction of person and situational variables combine to explain behaviour (Krahé, 1992). In the domain of work, the power of interactions to shape behaviour has been shown in many ways. Holland (1985), for example, has demonstrated that people choose vocations based on the fit of their personality to their perceptions of the profession. Chatman’s (1991) work demonstrated that new recruits become socialized to their new employer based on the congruence of individual and organisational values, and Caldwell and O’Reilly (1990) have shown that job performance and satisfaction are strongly related to the 1 This paper was presented at the 2005 British Academy of Management annual conference held at Oxford
yTraffic Information Dissemination in Vehicular Ad Hoc Networks

Today, cars are equipped with all kind of on-board sensors and microcomputers that are able to measure geolocation, speed, tire pressure, raindrops on the windshield, etc., and based on these information Intelligent Transportation Systems (ITS) are built. The ITS applications are intended to ease the everyday life of drivers by reducing the risk of accidents, improving safety, increasing road capacity and reducing traffic jams. Many research papers, for example Torok et al. (2008) and Sormani et al. (2006), pointed out that a significant reduction of traffic jams can be achieved through the use of vehicular ad-hoc networks (VANETs). Vehicles could serve as Traffic and Travel Information (TTI) collectors and transmit this information to other participants in the vehicular network Laborczi et al. (2006). The ITS applications could utilize this information to actively relieve traffic congestion. Practically, vehicles could detect traffic congestion automatically when the usual (historical) characteristics of traffic patterns drastically change, i.e. the number of neighboring vehicles is high and/or the average speed is too low. Then this information should be relayed, disseminated to the vehicles approaching the congested area; thus, they will have enough time to choose alternative routes. Due to their inherent characteristics, viable communication is harder to support in ITS scenarios than in conventional wireless networks. Vehicles are usually moving much faster than traditional mobile nodes; moreover, a vehicular network might be very heterogeneous in terms of node density, becoming fragmented in many cases. Reliability is also compromised due to the usually high interference in urban scenarios. Thus, there is a need to reconsider the wireless ad hoc communication networking protocols, and to use new concepts that fit better the specificities of ITS applications. Traffic and Travel Information (TTI) spreading in vehicular ad hoc networks is achieved by the means of a flooding mechanism. To overcome network fragmentation the vehicles usually maintain and carry a copy of the packets, which is disseminated along the road segments Zhao & Cao (2006), Burgess et al. (2006), Tian et al. (2004). The frequency of subsequent transmissions will control the quality of the TTI reports, in terms of delay and accuracy. If the frequency of TTI transmissions is high, the time necessary for the information to reach the outer bounds of the geographic area is lower. The accuracy of TTI also varies in function of the amount of communication involved in the travel information gathering and transmission. Frequent information exchange leads to a more accurate picture about the traffic situation, but also to superfluous dissemination. Superfluous forwarding can be reduced by using adaptivity in the flooding mechanisms. Adaptivity can be introduced by controlling the 6
Biochemical Markers of Physical Exercise on Mild Cognitive Impairment and Dementia: Systematic Review and Perspectives

Background The cognitive effects of physical exercise in patients with dementia disorders or mild cognitive impairment have been examined in various studies; however the biochemical effects of exercise from intervention studies are largely unknown. The objective of this systematic review is to investigate the published results on biomarkers in physical exercise intervention studies in patients with MCI or dementia. Methods The PubMed database was searched for studies from 1976 to February 2015. We included intervention studies investigating the effect of physical exercise activity on biomarkers in patients with MCI or dementia. Results A total of eight studies were identified (n = 447 patients) evaluating exercise regimes with variable duration (single session–three sessions/week for 26 weeks) and intensity (light-resistance training–high-intensity aerobic exercise). Various biomarkers were measured before and after intervention. Seven of the eight studies found a significant effect on their selected biomarkers with a positive effect of exercise on brain-derived neurotrophic factor, cholesterol, testosterone, estradiol, dehydroepiadrosterone, and insulin in the intervention groups compared with controls. Conclusion Although few studies suggest a beneficial effect on selected biomarkers, we need more knowledge of the biochemical effect of physical exercise in dementia or MCI.
The dynamics of Rho GTPase signaling and implications for targeting cancer and the tumor microenvironment

Numerous large scale genomics studies have demonstrated that cancer is a molecularly heterogeneous disease, characterized by acquired changes in the structure and DNA sequence of tumor genomes. More recently, the role of the equally complex tumor microenvironment in driving the aggressiveness of this disease is increasingly being realized. Tumor cells are surrounded by activated stroma, creating a dynamic environment that promotes cancer development, metastasis and chemoresistance. The Rho family of small GTPases plays an essential role in the regulation of cell shape, cytokinesis, cell adhesion, and cell motility. Importantly, these processes need to be considered in the context of a complex 3-dimensional (3D) environment, with reciprocal feedback and cross-talk taking place between the tumor cells and host environment. Here we discuss the role of molecular networks involving Rho GTPases in cancer, and the therapeutic implications of inhibiting Rho signaling in both cancer cells and the emerging concept of targeting the surrounding stroma.
Stock price index movement classification using a CEFLANN with extreme learning machine

Recently, an efficient learning algorithm called extreme learning machine (ELM) has been proposed for training of single hidden layer feed forward neural networks (SLFNs). ELM has shown good generalization performances for many real applications with an extremely fast learning speed. This study proposes a computational efficient functional link artificial neural network (CEFLANN) trained with ELM for addressing the problem of classifying stock price index movements as up and down movements. The proposed model is also compared with two other popular networks like Chebyshev FLANN and RBF, used mostly in classification problems. Again the performance of all the networks are compared with back propagation and ELM based learning over two benchmark financial data sets. Experimental results show that the performance of proposed model outperforms the other models.
Notational effects on use of collaboratively constructed representations during individual essay writing

Prior analyses of collaboration through different notational systems (e.g., threaded discussions and evidence maps) have documented differential influences of notations on collaborative processes as well as ways in which groups appropriate these notations for their work. These prior analyses have focused on collaborative interaction, yet for instrumental purposes in educational practice, the individual is the unit of analysis. Hence it is relevant to ask how individuals use the products of collaborative interaction as documented in a given notational system. This paper reports on an analysis of data from a prior study to uncover how participants went about writing individual essays, drawing on the products of interactionally prior joint problem solving. The analysis first documented parameters of the human-computer interactions through which individual participants accessed and appropriated the record of prior work. Parameters included focus shifts, use of copy/paste, and access to records of data and hypotheses considered. The analysis then compared three experimental conditions and two post-hoc groups on the selected parameters. Profiles plots reveal consistent differences between the use of the notational systems that are indicative of differences in engagement with the materials.
IFFT IFFT ? ? ? ? ? ? ?

MFSK (M-ary frequency shift keying) can be combined with OFDM (orthogonal frequency division multiplexing) by grouping the subcarriers into groups of M and applying MFSK modulation to each of these groups. The detection of such an OFDM-MFSK modulation scheme can be noncoherent and it is very robust against Doppler shift and Doppler spread. The noncoherent detection of OFDMMFSK allows an arbitrary phase choice for all subcarriers in the transmitter. This degree of freedom can be exploited to reduce the PAPR (peak-to-average power ratio), which is a well known problem for multicarrier transmission schemes. In this paper we compare several PAPR reduction schemes and apply them to OFDM-MFSK. A new PAPR reduction algorithm is introduced, which adjusts the subcarrier phases of an OFDM symbol to obtain a low PAPR. The effects on the spectrum of the OFDM-MFSK signal in the presence of a nonlinear transmitter are considered and the improvements achievable by the various PAPR reduction schemes are shown. Finally the complexity of the presented schemes is compared.
Flow Control, Routing, and Performance from Service Provider Viewpoint 1

We consider a game theoretic framework to analyze traffic in a congested network, where a profit-maximizing monopolist sets prices for different routes. Each link in the network is associated with a flow-dependent latency function which specifies the time needed to traverse the link given its congestion. Users have utility functions defined over the amount of data flow transmitted, the delays they incur in transmission, and the expenditure they make for using the bandwidth. Given the prices of the links, each user chooses the amount of flow to send and the routes to maximize the utility he receives. We define an equilibrium of user choices given the prices, show its existence and essential uniqueness, and characterize how this equilibrium changes in response to changes in prices. We then define a monopoly equilibrium (ME) as the equilibrium prices set by the monopolist and the corresponding user equilibrium, and characterize this equilibrium. We also study the performance of the ME relative to the user equilibrium at zero prices and the social optimum, which would result from the choice of a network planner with full information and full control over the flow and routing choices of users. Although equilibria for a given price vector or without prices are typically inefficient relative to the social optimum, we show that the ME achieves full efficiency for the routing problem (i.e., where each user has a fixed amount of data to transmit).
Deficiency of the lipid synthesis enzyme, DGAT1, extends longevity in mice

Calorie restriction results in leanness, which is linked to metabolic conditions that favor longevity. We show here that deficiency of the triglyceride synthesis enzyme acyl CoA:diacylglycerol acyltransferase 1 (DGAT1), which promotes leanness, also extends longevity without limiting food intake. Female DGAT1-deficient mice were protected from age-related increases in body fat, tissue triglycerides, and inflammation in white adipose tissue. This protection was accompanied by increased mean and maximal life spans of ~25% and ~10%, respectively. Middle-aged Dgat1−/− mice exhibited several features associated with longevity, including decreased levels of circulating insulin growth factor 1 (IGF1) and reduced fecundity. Thus, deletion of DGAT1 in mice provides a model of leanness and extended lifespan that is independent of calorie restriction.
The Web Laboratory PageRank Calculation using Map Reduce Spring 2008 Report

The main goal of this project was to implement the well-known Pagerank algorithm using Map-Reduce programming. We have come up with several formulations of Pagerank using Map-Reduce programming. While the formulations appear different, at the heart of the Pagerank computation is computing the product of a sparse matrix and a vector. The sparse matrix is stored as a list of tuples. Map-Reduce programming is very suitable for doing aggregation operations like summing the product bits and hence the applicability of Map-Reduce programming to compute Pagerank of large graphs. We implemented our different formulations on the Hadoop distributed system with six nodes. However we report the results of only one of the implementations. Hadoop is an open source system and is being increasingly used by different companies as their production system. We used a small synthetic dataset generated according to "the referential attachment" model of random graphs to match the degree distribution of many real world networks. We tested different parameter settings of the Hadoop system on the small dataset to get a better understanding of how parameters like number of Map tasks, number of Reduce tasks, choice of an intermediate Combiner, etc affects the performance of our implementation of Pagerank.
Participating in Social Network Online Purchase: How Significant Emotional Intelligence IS

The social networking has become a phenomenon not only to the social system, but also to the business activities. Engaging the social network for buying and selling products and services has become common, although these shopping sites are lacking of many trustworthy elements due to their limited virtual characteristics. Thus, it motivates us to examine the role of emotional intelligence, trust and perceived value as significant psychological elements in predicting consumers’ decisions to engage in social networking online purchase. We then proposed a model that links relationships of emotional intelligence, trust, perceived value, purchased intention and confirmation. Using a survey conducted via a cross sectional study, we collected data from 334 respondents who have taken part in social networking online purchase. Based on the regression analyses, the findings reveal that consumers’ decisions are explained by emotional intelligence and trust. Besides, trust plays the role as a predictor for perceived value and purchase intention. In addition, there are also significant relationships between perceived value and purchase intention, and between purchase intention and confirmation. The study contributes to the understanding of emotional intelligence as the basis for online and mobile retailers in taking the appropriate strategies to attract more consumers and generate higher sales. Building on this research and for knowledge enrichment, future study may incorporate social informatics in building social intelligence of the future social business community.