Miracle-dz/UniFAR-FTUs huggingface dataset:
The derivation of a brief Student Nurse Stress Index

The lack of an adequate measure of perceived sources of stress for student nurses led to the construction of the Student Nurse Stress Index (SNSI). Responses from 235 first-year student nurses to 35 items from the Beck and Srivastava Stress Inventory (Beck, and Srivastava, 1991), and 15 new items, were subjected to exploratory factor analysis using principal components analysis and oblimin rotation. A reliable 22-variable solution with a simple oblique structure including Academic load, Clinical sources, Interface worries, and Personal problems factors was obtained in this initial sample, and confirmed at an exploratory level in a further independent validation sample of 188 first-year students. Confirmatory factor analysis established the four-factor model in the first sample, but required that three variables load onto more than one factor. This more complex four-factor model was confirmed using independent data from the validation sample, and the total invariance of factor loadings and factor covarianc.
The socially anxious perspective in face‐to‐face interaction: an experimental comparison

We argue that social psychological and evolution theories can be combined to produce an adequate theory of social anxiety. From this combination we predict that the socially anxious utilize competitive schemata in social interaction whereas non-anxious people utilize cooperative schemata, with consequent differential effects on cognitions and emotions. These predictions were evaluated in an experiment in which two groups of studentsÐ12 high and 12 low scorers on the Fear of Negative Evaluation ScaleÐengaged in a semi-naturalistic, mildly stressful interaction, after which they were asked to reconstruct their thoughts and feelings at points of `discomfort' using video-aided recall. Anxious students evaluated themselves as subordinate, the confederate as dominant, thought he should take the lead, and blamed themselves for disruption in the conversation and experienced embarrassment. Non-anxious students in contrast evaluated themselves as more dominant than the confederate, thought the conversation should have been more reciprocal, and tended to blame the confederate for disruptions. The results were interpreted as providing qualified and preliminary support for the theory. # 1998 John Wiley & Sons, Ltd.
Building distributed scalable dependable real-time systems

This paper describes an on-going effort in constructing a platform for developing distributed, embedded, real-time control systems which have high dependability and scalability requirements. Complex, embedded real-time control systems typically have a very large grain task model upon which hard and soft timing constraints are simultaneously imposed. Often, such systems are required to function in extremely hostile and unpredictable environments. This demands large dependability and availability in a continuous manner We describe a new paradigm to build such systems which is based on the notion of paths-the granularity at which the notion of time is expressed in software. Further the paper describes distributed middleware services that are being developed to provide dependable, adaptive dynamic resource management. To illustrate the approach, an automobile air bag control system is used as an application example. Path descriptions can be applied in system design or system maintenance and during run time optimization. Within this framework, model based evaluation is often required. Therefore, in the second part of the paper a modeling approach for paths based on Stochastic Petri Nets is described, and results of a performance evaluation are presented.
Improving Analysis and Visualizing of JVM Profiling Logs Using Process Mining

Growing size and complexity of modern software applications increase the demand to make the information systems self-configuring, self-optimizing and with flexible architecture. Although managed languages have eliminated or minimized many low-level software errors there are many other sources of errors that persist. Java Virtual Machine (JVM), as managed language has many adaptive optimization techniques, which needs tools to analysis program behavior determines where the application spends most of its time. In this paper, new approached has been introduced to use process-mining techniques to represent the analysis and visualize phases of JVM profilers. They are flexible enough to cover so many perspectives in several ways. That can form a unified layer for analysis and visualize across profiling.
Applying big-data technologies to network architecture

The pace of change will continue to speed up Facilitating the Networked Society presents the telecom industry, as well as many others, with the opportunity to surpass their current levels of innovation, to develop new technologies, and to test new and sustainable business solutions. Today, there are slightly more than 6.2 billion mobile subscriptions worldwide – a figure that is set to rise to 9 billion in 2017. With so many people using mobile networks, and owing to the increase in smartphone penetration and constant connectivity, the volume of data traffic in these networks is expected to rise 15 times in the same time frame. The nature of this data is also set to change – the size of single data sets, the variety of data types and the demand for real-time access to data are all on the rise. These factors lead to varying types of data being collected by the network and transmitted through it. Data sets are irregular and may be unstructured, they can contain ambiguities, they are timeand location-dependent, and are constantly being updated by capture equipment such as mobile devices, sensors and RFID readers. In its simplest form, big-data technology encompasses the tools, processes and procedures to consolidate, verify, analyze, manage and visualize a month – which amounts to an annual increase of 30 percent. When a new phenomenon comes about, it often takes the related industries a while to agree on a common definition, and big data is no exception. However, the consensus seems to be that data gets big when it starts to stretch the limits of traditional technology. Network congestion, reduced application performance and a negative impact on user experience are the consequences of increased data volumes. To mitigate these effects, scalable and costefficient data-management technologies are needed. Technologies such as not only SQL (NoSQL), characterized by its nonadherence to the RDBMS model, and MapReduce, a programming model tailored for processing large-scale distributed data sets, are both used in a wide variety of industry applications including telecom. These technologies have the flexibility to handle big data and support central management of MONA M AT T I A N D TOR KV E R N V I K
Frame-based dynamic voltage and frequency scaling for a MPEG decoder

This paper describes a dynamic voltage and frequency scaling (DVFS) technique for MPEG decoding to reduce the energy consumption while maintaining a quality of service (QoS) constraint. The computational workload for an incoming frame is predicted using a frame-based history so that the processor voltage and frequency can be scaled to provide: the exact amount of computing power needed to decode the frame. More precisely, the required decoding time for each frame is separated into two parts: a frame-dependent (FD) part and a frame-independent (FI) part. The FD part varies greatly according to the type the incoming frame whereas the FI part remains constant regardless of the frame type. In the DVFS scheme presented in this paper the FI part is used to compensate for the prediction error that may occur during the FD part such that a significant amount of energy can be saved while meeting the frame rate requirement. The proposed DVFS algorithm has been implemented on a StrongArm-1110 based evaluation board. Measurement results demonstrate a higher than 50% CPU energy saving as a result of DVFS.
"I had no desire to be having this battle with this faceless man on the soccer field anymore": exploring the ethics of sporting retirement.

In this article, I examine the relatively youthful sporting retirement of four athletes from popular Western team sports, namely soccer, ice hockey and rugby union. Drawing on studies of sporting transitions and retirement (e.g., Denison, 1997; Douglas & Carless, 2009; Sparkes, 1998; Sparkes & Smith, 2002; Stambulova, Alfermann, Statler, & Cote, 2009; Wylleman, Alfermann, & Lavallee, 2004) and Foucault’s notions of games of truth and ethical self-creation, I argue that these athletes’ decisions to retire from sport were based on a refusal to accept the subject position proposed to them within their sports and, subsequently, these sporting transitions formed acts of ethical self-creation. My conclusions reveal an as yet under-explored interpretation of sporting retirement in which the process of retirement forms part of an attempt to recreate an ethical self.
FPGA implementation of hardware countermeasures

A FPGA implementation of a frequency sensor has been presented. Its main mission consists to determine when the frequency of test signal is into an allowed range. This implementation has the following configurable parameters: timing resolution and allowed range of frequency. This component operates in real-time with a delay of only one operation cycle. Countermeasures against clock glitch attacks is one of its possible applications. Experimental results in a Spartan-3AN700 device show a minimum allowed period of about 16 ns and a minimum resolution of about 4 ns. The implementation of the sensor has been verified in an electronic lock, used as a case of study. This system has been attacked with clock glitches, showing its behavior without and with sensor.
Online pedestrian tracking via saliency-based H-S histogram

Object tracking is one of the most important topics in computer vision. While the state-of-the-art tracking algorithms achieved great success, there are still some challenging problems to be solved. Firstly, it remains a tough task to develop a tracking algorithm with both accuracy and efficiency. Secondly, the ground truth is often given by a rectangular bounding box, which contains not only the target, but also the background pixels. The background pixels in the initial bounding box will mislead the appearance model of the target. Thirdly, most features for representing the target only use the gray scale information, and are not robust to pedestrians. The third problem is especially serious when the targets are pedestrians, which have colorful cloths on them, and change their pose and shape while walking. In this paper, we propose a novel saliency-based H-S histogram algorithm. Saliency detection can efficiently delete most of the background pixels, which makes the appearance model more accurate. H-S histogram is a statistic-based feature, which is more robust to shape deformation, and the color information is considered in the H-S channels. Experiments on Caltech pedestrian database show the proposed method can handle some hard cases, and achieves a higher success rate.
Image interpolation using shearlet based sparsity priors

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering, (b) promoting sparsity in a selected dictionary through thresholding and (c) extracting high frequency information from the approximation and adding it to the initial estimate. For the sparse modeling, a shearlet dictionary is chosen to yield a multi-scale directional representation. The proposed algorithm is compared to several state-of-the-art methods to assess its objective as well as subjective performance. Compared to the cubic spline interpolation method, an average PSNR gain of around 0.7 dB is observed over a dataset of 200 images.
After the Wall: Parental attitudes to child rearing in East and West Germany

In the years following German reunification, East and West German parents (282 mothers and 207 fathers) were interviewed about attitudes to the rearing of their 7- to 13-year-old children and about their social networks. Path analyses show that East German parents engage in more protective and less permissive parenting, and that East German fathers raise their children in a more traditional and authoritarian manner than their West German counterparts. In part, these differences can be attributed to the strong family orientation of East German parents (many and intensive kinship relations, few friends). Further analyses show that corollaries of the social upheavals in East Germany, namely closer cohesion of the immediate family and a decrease in the social support provided by the extrafamilial environment, are associated with protective attitudes to parenting and hence with the tendency to limit children’s freedom of decision-making.
A One-Degree-of-Freedom Test for Supra-Multiplicativity of SNP Effects

Deviation from multiplicativity of genetic risk factors is biologically plausible and might explain why Genome-wide association studies (GWAS) so far could unravel only a portion of disease heritability. Still, evidence for SNP-SNP epistasis has rarely been reported, suggesting that 2-SNP models are overly simplistic. In this context, it was recently proposed that the genetic architecture of complex diseases could follow limiting pathway models. These models are defined by a critical risk allele load and imply multiple high-dimensional interactions. Here, we present a computationally efficient one-degree-of-freedom “supra-multiplicativity-test” (SMT) for SNP sets of size 2 to 500 that is designed to detect risk alleles whose joint effect is fortified when they occur together in the same individual. Via a simulation study we show that the SMT is powerful in the presence of threshold models, even when only about 30–45% of the model SNPs are available. In addition, we demonstrate that the SMT outperforms standard interaction analysis under recessive models involving just a few SNPs. We apply our test to 10 consensus Alzheimer’s disease (AD) susceptibility SNPs that were previously identified by GWAS and obtain evidence for supra-multiplicativity () that is not attributable to either two-way or three-way interaction.
Enhancement of neovascularization with mobilized blood cells transplantaion: Supply of angioblasts and angiogenic cytokines

We have recently provided evidence that transplantation of G‐CSF mobilized peripheral blood mononuclear cells (M‐PBMNCs) improves limb ischemia in diabetic patients. This method represents a simple, safe, effective, and novel therapeutic approach for diabetic ischemia. Here we investigated the mechanisms by which mobilized blood cells transplantation improves limb ischemia. Unilateral hindlimb ischemia was surgically induced in streptozotocin‐induced diabetic nude mice, and they were intramuscularly injected 106 M‐PBMNCs, or human umbilical vein endothelial cells (HUVECs), PBS controls. We compared their blood‐flow restoration via laser Doppler perfusion image (LDPI), angiogenesis via histological determination of capillary density. Physiological and histological assessment revealed an acceleration of ischemia recovery and increase in capillary density with less apoptosis in M‐PBMNCs group, compared with those in HUVECs and PBS groups. In vivo noninvasive imaging and immunofluorescence revealed the survival, migration, proliferation, differentiation, and incorporation of M‐PBMNCs into foci of vessel networks. More angioblasts were from blood cells after mobilization, and they also produced a number of antiapoptotic and proagniogenic factors that promoted angiogenesis in vivo. M‐PBMNCs and its conditioned medium augmented the vessel formation in matrigel plugs in vivo. Thus, transplantation of M‐PBMNCs achieved therapeutic neovascularization via supply of abundant angioblasts and angiogenic factors. J. Cell. Biochem. 102: 183–195, 2007. © 2007 Wiley‐Liss, Inc.
A cellular genome-wide association study reveals human variation in microtubule stability and a role in inflammatory cell death

Interindividual variation was screened for inflammatory cell death—pyroptosis. Natural variation in expression of the tubulin isoform TUBB6 or experimental manipulation of expression altered microtubule stability and susceptibility of cells to pyroptosis. Diversity in microtubule stability regulates pyroptosis and likely other human traits.
Path Planning with Markovian Processes

This paper describes the path planning for the mobile robots, based on the Markov Decision Problems. The presented algorithms are developed for resolving problems with partially observable states. The algorithm is applied in an office environment and tested with a skid-steered robot. The created map combines two mapping theory, the topological respectively the metric method. The main goal of the robot is to reach from the home point to the door of the indoor environment using algorithms which are based on Markovian decisions.
Adaptive Bayesian Estimation with Cluster Structured Sparsity

Armed with structures, group sparsity can be exploited to extraordinarily improve the performance of adaptive estimation. In this letter, the adaptive estimation algorithm for cluster structured sparse signals, called A-CluSS, is proposed. In particular, a hierarchical Bayesian model is built, where both sparse prior and cluster structured prior are exploited simultaneously. The adaptive updating formulas for statistical variables are obtained via the variational Bayesian inference and the resulted algorithms can adaptively estimate the cluster structured sparse signals without knowledge of block size, block numbers and block locations. Superiority of proposed A-CluSS is demonstrated via various simulations.
Use of modern technologies and software to deliver efficient design and optimization of 1380 km long bipole III ±500 kV HVDC transmission line, Manitoba, Canada

The new ±500 kV HVDC Bipole III line is one of the longest transmission lines to be built in North America. It will connect the generation source on the Nelson River in Northern Manitoba with the load centre located near Winnipeg in the South. Modern technologies have been used for designing and optimization this line such as: the use of LiDAR survey which provided accurate time/cost efficient non invasive survey of the line corridor, use of Reliability Based Design (RBD) method that provides more cost efficiency and higher reliability than common deterministic methods, use of modern software that allows a extremely efficient import of LiDAR survey data and creation of line profiles for tower spotting. The same software was also used to select the family of towers to be designed and for tower spotting that results in the minimum line cost.
The Application of Temperature Data Loggers for Remotely Monitoring the Nests of Emei Shan Liocichla (Liocichla omeiensis)

Temperature data loggers (TDL) are mostly used to monitor avian incubation behavior in bird studies. In this paper we demonstrate how TDL can also be used to determine different breeding stages and nest success of the vulnerable Emei Shan Liocichla (Liocichla omeiensis). All nests that contained at least one egg were divided into two groups. Group I included six nests monitored traditionally by the observers' visits, while Group II included eight nests monitored by TDL. Group I and Group II were visited every 1–4 days and 7 days, respectively, to check nest contents and status (e.g., active vs. inactive, and the breeding process) until fledging or nest failure. The time of each observation was recorded to verify the interpretation of TDL. The data recorded by TDL were converted into line graphs of temperature against time and assessed visually. The results indicated that TDL can reliably identify different breeding stages and estimate daily nest survival rates (DSR) and total nest success. The nest success of Group II (0.3015) was higher than that of Group I (0.2387), suggesting that deployment of TDL did not negatively influence nest survival rate of Emei Shan Liocichla. In contrast to traditional nest visits, TDL minimized disturbance by observers and provided a more precise estimate of nest survival. We suggest that TDL should be used more widely in studies of the breeding ecology of rare and endangered birds.
Risk of primary biliary liver cirrhosis in patients with coeliac disease: Danish and Swedish cohort data

BACKGROUND Several case reports, but only a few studies, have examined the coexistence of coeliac disease and primary biliary cirrhosis. AIM To estimate the risk of primary biliary cirrhosis in two national cohorts of patients with coeliac disease in Denmark and Sweden. METHODS Through record linkage all Danish patients hospitalised with coeliac disease were followed for possible occurrence of primary biliary cirrhosis from 1 January 1977 until 31 December 1992. All patients hospitalised with coeliac disease in Sweden from 1987 to 1996 were also followed in a separate analysis. RESULTS A total of 896 patients with coeliac disease were identified in Denmark with a median follow up period of 9.1 years for a total of 8040 person-years at risk. Two cases of primary biliary cirrhosis were observed where 0.07 were expected, giving a standardised incidence ratio of 27.6 (95% confidence interval 2.9 to 133.5). A total of 7735 patients with coeliac disease were identified in Sweden with a median follow up period of 5.1 years for a total of 39 284 person-years at risk. Twenty two people with primary biliary cirrhosis were identified compared with 0.88 expected, giving a standardised incidence ratio of 25.1 (95% confidence interval 15.7 to 37.9). CONCLUSION Patients with coeliac disease are at increased risk of having primary biliary cirrhosis.
Novel image registration method using multiple Gaussian mixture models

Traditional feature based image registration methods work like point set registration with treating feature points from a whole image as one feature point set. However, unlike point set registration problem where only one meaningful structure is present, remote sensing images are usually present with lots of details. This paper uses the spatial information of feature points to divide them into several meaningful interest areas. In this way it is more appropriate to use point set registration methods. The image registration method presented in this paper takes advantage of the robustness and efficiency of Gaussian Mixture Models (GMM) based point set registration methods and makes several improvements considering the particularities of image registration. Experiments performed on real remote sensing images proved our method's superiority over traditional direct implementation.
SIR-based interference-maps for TDMA-based outdoor mesh networks

A TDMA-based MAC protocol is essential to achieve high throughput and low delay/jitter values, in WiFi mesh networks. An important component of such a network is the interference map, which quantifies the level of interference between pairs of links in the network. Past work in this domain has been relatively sparse, although many protocols and algorithms have been proposed which assume an interference map. In a TDMA network where carrier-sense is disabled, all interference shows up as hidden-terminal cases. Prior work on building interference maps has not focused on the hidden terminal case. Further, most prior evaluation has been in indoor settings. In this work, we present an SIR based interference measurement technique. We start by measuring the average RSS for each link in the network. This is subsequently used to get an estimated average SIR. The average SIR is then used in conjunction with an SIR-versus-PER plot, to estimate the link error rate under interference. We show through measurements on an outdoor 802.11b/g testbed, that the above estimate is accurate for (1) non-interfering links, as well as (2) fully interfering links, but is less accurate for (3) intermediate link pairs. The resultant 3-way classification of inter-link interference will be useful input for subsequent TDMA scheduling algorithms.