Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Using Telegram and Interpersonal communication of Islamic Azad University Students of Karaj

The present study aims at investigating the relationship between using Telegram and interpersonal communications of university students of Karaj, Iran in 2015. The study, considering its purpose, adopted an applied method, and used descriptive methods and correlation for data collection. The statistical population of this study included 3865 students of Islamic Azad University of Karaj, Iran. Using stratified random sampling and based on Morgan table, 345 students were selected as the research sample. Data were collected using Hirshfiled’s (1997) standardized interpersonal dependence questionnaire. The collected data obtained from questionnaires were then analyzed using SPSS 19 in two parts of descriptive and inferential statistics (logistic regression). According to the obtained results, all three components of interpersonal dependence, the average of the students who are members of Telegram is higher than that of the students who do not use Telegram. Furthermore, there is a significant relationship between Telegram and emotional dependence on others while the relationship between Telegram and the lack of self-confidence and the lack of independence was not significant. Hence,it is suggested that universities inform of using Telegram and its various effects on students.
Sliding Conformal Contact Tribocharging of Polystyrene and Polyvinyl Chloride

The electric double layer is known to affect thin-film lubrication. Other researchers have shown that tribocharging affects the breaking torque in a metal shaft-oil-lip seal system and that an external electric field may be employed to control this phenomenon. One main issue in all these studies is the characterization of the charging state of the bodies in contact. This is quite a difficult challenge when the contact occurs between two insulating materials. The ultimate aim of this paper is to validate an experimental procedure appropriate for ensuring the reproducibility of the tribocharging conditions in sliding contacts between polymeric materials. The experiments were performed with samples of polystyrene and polyvinyl chloride. Surface potential measurements were done to evaluate the tribocharging effects. The experiments pointed out that the amount of charge accumulated on the sliding bodies depends on the external force applied to the contact and the number of tribocharging cycles (i.e., back-and-forth relative motions). However, this charge is nonuniformly distributed on the surface of the samples. This means that it will be difficult to use the tribocharging effect for controlling the charging state and, hence, the lubrication of the contact between two insulating bodies.
A Polynomial time Algorithm for the Maximum Weight Independent Set Problem on Outerstring Graphs ∗

Outerstring graphs are the intersection graphs of curves that lie inside a disk such that each curve intersects the boundary of the disk in one of its endpoints. Outerstring graphs were introduced in 1991 and are amongst the most general classes of intersection graphs studied, including among others, chordal graphs and interval filament graphs. To date no polynomial time algorithm is known for any of the classical graph optimization problems on outerstring graphs, in fact most are NP-hard. It is known that there is an intersection model for any outerstring graph that consists of polygonal arcs attached to a circle. However, this representation may require an exponential number of segments relative to the size of the graph. We develop a general simple dynamic programming algorithm for the Maximum Weight Independent Set problem. Given an outerstring graph and an intersection model consisting of polygonal arcs with a total of N segments, we show that our algorithm solves the Maximum Weight Independent Set problem in O ( N ) time. If the polygonal arcs are restricted to single segments, then outersegment graphs result. In this special case we show that our algorithm solves the Maximum Weight Independent Set problem in O ( n ) time where n is the number of vertices in the graph. ∗Supported by NSERC †Corresponding Author
Ambient Videogames for Health Monitoring in Older Adults

Ambient videogames can be used for frequent continuous monitoring of older adults in order to detect early signs of frailty. In this paper we propose a general architecture for health monitoring through ambient videogames and illustrate its instantiation with the development of two ambient casual games that have been designed to measure arm muscle strength utilizing a custom-designed interaction device that provides a natural user interface for the games. The games are designed to be used frequently and for short periods of time. We conducted a formative evaluation of the games with 5 older adults to assess ease of use and their interest in playing them. We compare the results of traditional measures of muscle strength using a clinical dynamometer with those obtained using the videogame.
Error Recovery in Cyberphysical Digital Microfluidic Biochips

Droplet-based digital microfluidics technology has now come of age, and software-controlled biochips for healthcare applications are starting to emerge. However, today's digital microfluidic biochips suffer from the drawback that there is no feedback to the control software from the underlying hardware platform. Due to the lack of precision inherent in biochemical experiments, errors are likely during droplet manipulation; error recovery based on the repetition of experiments leads to wastage of expensive reagents and hard-to-prepare samples. By exploiting recent advances in the integration of optical detectors (sensors) into a digital microfluidics biochip, we present a physical-aware system reconfiguration technique that uses sensor data at intermediate checkpoints to dynamically reconfigure the biochip. A cyberphysical resynthesis technique is used to recompute electrode-actuation sequences, thereby deriving new schedules, module placement, and droplet routing pathways, with minimum impact on the time-to-response.
A Timer Based Acknowledgement Scheme for Node Misbehavior Detection and Isolation in MANET

The nodes in the network that causes dysfunction in network and damage to the other node are misbehaving nodes. They support the flow of route discovery traffic but interrupt the data flow causing the routing protocol to restart the route discovery process. In this paper, an efficient timer based acknowledgement technique is proposed to detect and isolate the misbehaving nodes and can even find a possible alternate route in case when the number of misbehaving nodes is greater than minimum count. This involves a detection timer and forward counter that help to reduce the number of acknowledgements thus reducing the delay and overhead. This approach is keenly focusing on acknowledgement of nodes regarding the misbehaviors so that the source takes the corresponding action. Simulation results show that the timer based acknowledgement scheme attains good packet delivery ratio with reduced packet drop, delay and overhead, when compared with secured on-demand routing protocol.
Fibred semantics and the weaving of logics. Part 1: Modal and intuitionistic logics

Abstract This is Part 1 of a paper on fibred semantics and combination of logics. It aims to present a methodology for combining arbitrary logical systems Li, i ∈ I, to form a new system LI. The methodology ‘fibres’ the semantics i of Li into a semantics for LI, and ‘weaves’ the proof theory (axiomatics) of Li into a proof system of LI. There are various ways of doing this, we distinguish by different names such as ‘fibring’, ‘dovetailing’ etc, yielding different systems, denoted by etc. Once the logics are ‘weaved’, further ‘interaction’ axioms can be geometrically motivated and added, and then systematically studied. The methodology is general and is applied to modal and intuitionistic logics as well as to general algebraic logics. We obtain general results on bulk, in the sense that we develop standard combining techniques and refinements which can be applied to any family of initial logics to obtain further combined logics. The main results of this paper is a construction for combining arbitrary, (possibly not normal) modal or intermediate logics, each complete for a class of (not necessarily frame) Kripke models. We show transfer of recursive axiomatisability, decidability and finite model property. Some results on combining logics (normal modal extensions of K) have recently been introduced by Kracht and Wolter, Goranko and Passy and by Fine and Schurz as well as a multitude of special combined systems existing in the literature of the past 20–30 years. We hope our methodology will help organise the field systematically.
Principal and Independent Component Analysis for Crypto-systems with Hardware Unmasked Units

Principal component analysis (PCA) is a well-known statis- tical method for reducing the dimension of a data set. This method flnds a new representation of the data set conserving only the most impor- tant information. It is based on spectral decomposition of the covariance matrix of the data set. In this article, we apply principal component analysis to facilitate simple power analysis. Principal component anal- ysis, however, makes no assumption on the independence of the data vectors. In 1986, Herault and Jutten introduced a learning algorithm based on a version of the Hebb learning rule (1). This algorithm was able to blindly separate mixtures of independent signals. Independent Com- ponent Analysis (ICA) is a powerful tool for signal processing. PCA and ICA permit to improve the signal to noise ratio of signals used for dif- ferential side channel analysis, which makes the application of classical methods to recover cryptographic keys more easy. To be a serious threat against present cryptographic implementations, PCA and ICA should be accompanied with other signal processing tools.
An Architecture for SDN Based Sensor Networks

Software Defined Networks (SDN) are considered an efficient and flexible network architecture for managing large scale networks, in particular as it decouple between hardware and software and facilitates global network optimizations. Incorporating SDN concepts into Wireless Sensor Networks (WSN) opens interesting research challenges. This paper proposes an architecture for applying SDN to WSN. The architecture relies on recent extendibility features of OpenFlow to enable reconfiguring sensor behavior and network forwarding tables according to changes such as arrival of new sensors or change in user requests, as well as to apply dynamic in-network aggregation and filtering options. An evaluation of our approach for the specific case of in-network aggregation and its beneficial impact on the number of sent messages is also presented.
Three-dimensional modeling and simulation of the sliding motion of a soft fingertip with friction, focusing on stick-slip transition

We have proposed a dynamic model to investigate the sliding motion of a 3-dimensional soft fingertip on a plane with friction. The fingertip is comprised virtually of a finite number of elastic compressible and bendable cantilevers whose free ends act as infinitesimal contact points. The contact surface is afterward meshed using finite element method based on coordinates of contact points. By introducing Coulomb's law and contact compliance into each contact point, we are able to assess the frictional characteristic during sliding motions of the fingertip. We also successfully described dynamically localized displacements on the contact surface during stick-slip transition, which occurs substantially on hemispherical soft fingertip. Moreover, each simulation trial was implemented in a very small amount of time comparing to commercial softwares, promising use of this model in realtime application In addition, we conducted experiments to valid proposed simulation, including force/moment and vision setups.
Probabilistic neural networks combined with GMMs for speaker recognition over telephone channels

We study the applicability of probabilistic neural networks (PNNs) as core classifiers to medium scale speaker recognition over fixed telephone networks. In particular, banking applications with up to 400 enrolled speakers and short training times are targeted. Two PNN-based open-set text-independent systems, for speaker identification and speaker verification, respectively, are presented. The performance of these systems is studied with and without the use of a supporting Gaussian mixture models classifier. Results from experiments carried out on the Polycost and SpeechDat(II)-Greek corpus, with training times as short as 43 seconds, are reported.
The Rise of Mission-Oriented State Investment Banks: The Cases of Germany's KfW and Brazil's BNDES

This paper focuses on the rise of state investment banks (SIBs) as lead funders of mission-oriented innovation in various countries’ agendas regarding smart (innovation-led) growth, and not just fixers of ‘market failures’. The market failure justification for public finance fails to capture the active mission-oriented role that such banks are playing in shaping and creating markets, rather than just fixing them. In tackling innovation priorities and shaping new markets, these banks are developing new financial tools that also help to reform the financial system from within, addressing issues of short-termism and financialisation. This paper documents and analyses the roles of such banks, building on the Neo-Schumpeterian work on mission-oriented policies (that is, policies that aim to address societal issues or challenges). The paper presents a rich analytical description of mission-oriented investments in two of the leading SIBs: Brazil’s BNDES and Germany’s KfW. We discuss the directionality of the investments, the various tools used, and the lessons to be learned for evaluating these tools outside of a market failure framework.
Development of a Model to Examine the Wind Induced Forces on Oats Plant

Approximately 735,000 tonnes of oats are produced in the UK, and demand is increasing. One of the biggest yield loss factors in oat production is lodging, the permanent displacement of a plant from its vertical (Pinthus, 1973,Ingver, 2010)). It has been reported that lodging can reduce yields up to 40% (Fischer & Quail, 1990). Unfortunately, although it is well accepted that wind induced forces on oats plant is a factor lead to lodging, what and how affect lodging in oats are still unclear. Previous research has successfully studied crops, such as wheat, barley, etc. (Baker 1995, Farquhar 2003, Sterling et al. 2003, Berry et al.2003) and developed appropriated conceptual models to assess lodging. However, using such models to assess oat lodging may not always be appropriate due to the different structural form of oats. The aim of the current project is to develop a model which accounts for the interaction of wind with an oat plant in order to provide an insight into the factors which affect lodging.
A completely analytical family of dynamical models for spherical galaxies and bulges with a central black hole

We present a family of spherical models for elliptical galaxies and bulges consisting of a stellar component and a central black hole. All models in this family share the same stellar density profile, which has a steep central cusp. The gravitational potential of each model is a linear combination of the potential generated self-consistently by the stars and the potential of a central black hole. The relative importance of these two contributions is a free parameter in the models. Assuming an isotropic dynamical structure, almost all kinematical properties of these models can be calculated analytically. In particular, they form the first simple dynamical models for galaxies with a central black hole where the distribution function and differential energy distribution can be written completely in terms of elementary functions only. We also present various extensions of this family to models with anisotropic orbital structures. Also for these dynamical models, the distribution function and its moments can be expressed completely in terms of elementary functions. This family is useful for a large range of applications, in particular to generate initial conditions for N-body and hydrodynamical simulations to model galactic nuclei with a central black hole.
GREEN INFORMATION TECHNOLOGY: A STRATEGY TO BECOME SOCIALLY RESPONSIBLE SOFTWARE ORGANIZATION

Current trends show that for retaining competitive advantage, organizations are actively getting involved in corporate social responsibility (CSR). One of the major attentions of corporate social responsibility (CSR) is on developing an information technology (IT) framework which would enhance environmental friendly practices like recycling of paper, proper disposal of information technology instruments and products. The forces behind green IT framework are the push for reducing carbon footprints by international organizations and the realization by major software organizations on the detrimental effect of their operations on the environment. The green IT framework supports the concepts of the use of renewable energy, proper disposal of IT equipments, adopting of green technologies and greening of data centres. The proposed research is focused on the various green initiatives that have been adopted by various software organizations in an effort to reduce carbon footprint and, whether they are actually implementing these initiatives in their organizations. The research will content-analyze the different software organizations and will present a comparative analysis of the state of green information technology framework. Data collected was analyzed using SPSS. The analysis showed that many software organizations have been involved in one of the green information technology initiatives. It is also observed that the organizations involved in more initiatives are considered to be socially responsible which is being reflected in their core strategy and mission statement.
Hereditary angioedema: what the gastroenterologist needs to know

Up to 93% of patients with hereditary angioedema (HAE) experience recurrent abdominal pain. Many of these patients, who often present to emergency departments, primary care physicians, general surgeons, or gastroenterologists, are misdiagnosed for years and undergo unnecessary testing and surgical procedures. Making the diagnosis of HAE can be challenging because symptoms and attack locations are often inconsistent from one episode to the next. Abdominal attacks are common and can occur without other attack locations. An early, accurate diagnosis is central to managing HAE. Unexplained abdominal pain, particularly when accompanied by swelling of the face and extremities, suggests the diagnosis of HAE. A family history and radiologic imaging demonstrating edematous bowel also support an HAE diagnosis. Once HAE is suspected, C4 and C1 esterase inhibitor (C1-INH) laboratory studies are usually diagnostic. Patients with HAE may benefit from recently approved specific treatments, including plasma-derived C1-INH or recombinant C1-INH, a bradykinin B2-receptor antagonist, or a kallikrein inhibitor as first-line therapy and solvent/detergent-treated or fresh frozen plasma as second-line therapy for acute episodes. Short-term or long-term prophylaxis with nanofiltered C1-INH or attenuated androgens will prevent or reduce the frequency and severity of episodes. Gastroenterologists can play a critical role in identifying and treating patients with HAE, and should have a high index of suspicion when encountering patients with recurrent, unexplained bouts of abdominal pain. Given the high rate of abdominal attacks in HAE, it is important for gastroenterologists to appropriately diagnose and promptly recognize and treat HAE, or refer patients with HAE to an allergist.
Estimating the number of founder lineages from haplotypes of closely linked SNPs

We consider an isolated population founded by a small number of individuals randomly chosen from a source population of known genetic composition at a known time in the past. We develop a Monte‐Carlo maximum‐likelihood method for estimating the number of founding individuals from the haplotype frequencies at several SNP (single nucleotide polymorphism) loci in a sample. We assume the isolated population was founded recently enough that that mutation can be ignored and that haplotype frequencies in the source population have not changed. We apply the method to simulated data and show that it is unbiased. With a reasonable number of individuals sampled, it is possible to estimate the number of founders within a factor of 2. We show that the performance of the method is not degraded substantially if the frequencies of the rare haplotypes in the source are not known precisely and if there is some recombination. We illustrate the use of our method by applying it to a previously published data set from a recently founded population of wolves (Canis lupus) in Scandinavia.
On the Origin of Shame: Feelings of Disgust toward the Self

On the Origin of Shame: Feelings of Disgust toward the Self John A. Terrizzi Jr. Shame and disgust are believed to be evolved psychological solutions to different adaptive challenges and, thus, independent emotions. Shame is thought to promote the maintenance of social hierarchies (Gilbert, 1997; Fessler, 2004), whereas disgust is believed to encourage disease avoidance (Curtis et al., 2004; Oaten et al., 2009). Although shame and disgust are often treated as orthogonal emotions, they share some important commonalities. Both shame and disgust involve bodily concerns, have been described as moral emotions, and encourage avoidance of social interaction. The purpose of the current studies was to investigate the relation between shame and disgust. More specifically, the current research examined whether shame is experienced, at least in part, as disgust toward the self. As shame is often confounded with guilt (Tangney et al., 2007), it was important to demonstrate the uniqueness of the relation between shame and disgust. Thus, guilt was included as a comparison variable. In Study 1, disgust sensitivity and fear of contamination were positively correlated with shame, but not guilt, even after controlling for guilt and negative affect. In Study 2, a disgust induction increased shame, but not guilt, for individuals who were sensitive to disgust. In Study 3, a disgust induction led to an unanticipated significant reduction in shame, whereas a purity induction did not affect shame. In Study 4, inducing disgust increased shame for those who were less sensitive to disgust, but not for those who were more sensitive to disgust. The current research provides initial evidence that there is a unique relation between shame and disgust. Across all 4 Studies, disgust sensitivity and shame propensity were positively correlated even after controlling for negative affect and guilt propensity. However, the results of the three experimental studies provide conflicting evidence as to the causal nature of this relation.