Miracle-dz/UniFAR-FTUs huggingface dataset:
SenSquare: A mobile crowdsensing architecture for smart cities

In the recent years the Smart City paradigm has gained interest worldwide. Services are built on top of data sensed in the city and then analyzed in order to enhance people's quality of life. Nowadays users are also able to participate in such a data gathering, mostly thanks to a reduction in the cost of the sensing devices. Moreover, smartphones encompass many useful sensors and can be leveraged to obtain data by end users on the move, within the scope of mobile crowdsensing. In this paper, we propose SenSquare, a mobile crowdsensing architecture for Smart Cities, built to embrace both data availability and devices heterogeneity. SenSquare also offers the possibility for stakeholders to reward users sharing their data. Finally, we compare our proposal against a non-smart ideal architecture, showing the benefits and the advantages of a smart architecture such as SenSquare.
Effective emotional expressions with expression humanoid robot WE-4RII: integration of humanoid robot hand RCH-1

The authors have been developing humanoid robots in order to develop new mechanisms and functions for a humanoid robot that has the ability to communicate naturally with a human by expressing human-like emotion. We considered that human hands play an important role in communication because human hands have grasping, sensing and emotional expression abilities. Then, we developed the emotion expression humanoid robot WE-4RII (Waseda Eye No.4 Refined II) by integrating the new humanoid robot hands RCH-1 (RoboCasa Hand No.1) into the emotion expression humanoid robot WE-4R. Furthermore, we confirmed that RCH-1 and WE-4RII had effective emotional expression ability because the correct recognition rate of WE-4RII's emotional expressions was higher than the WE-4R's one. In this paper, we describe the mechanical features of WE-4RII.
Text Mining Post Project Reviews to Improve the Construction Project Supply Chain Design

Post Project Reviews (PPR) capture good and bad practices, identify problems, waste, risks, missed opportunities, communication lag, financial issues, partner relationships etc., of a construction project supply chain (CPSC). They are huge sources of information, knowledge and experience from project managers, clients, suppliers and contractors, related to issues from every stage of the construction project. If these reports were analysed collectively, they may expose important detail, perhaps repeated across a number of projects. However, because most companies do not have the resources to thoroughly examine these PPRs, either individually or collectively, important insights are missed thereby leading to missed opportunities to learn from previous projects. This research shows that the hidden knowledge and experiences could be captured using knowledge discovery and text mining approaches to uncover patterns, associations, and trends in PPRs. The results might then be used to address specific problem areas, enhance processes and improve the design and planning for new construction projects.
Predictors of Acquisition of Competitive Employment for People Enrolled in Supported Employment Programs

Abstract This study aims at assessing the relative contribution of employment specialist competencies working in supported employment (SE) programs and client variables in determining the likelihood of obtaining competitive employment. A total of 489 persons with a severe mental illness and 97 employment specialists working in 24 SE programs across three Canadian provinces were included in the study. Overall, 43% of the sample obtained competitive work. Both client variables and employment specialist competencies, while controlling for the quality of SE programs implementation, predicted job acquisition. Multilevel analyses further indicated that younger client age, shorter duration of unemployment, and client use of job search strategies, as well as the working alliance perceived by the employment specialist, were the strongest predictors of competitive employment for people with severe mental illness, with 51% of variance explained. For people with severe mental illness seeking employment, active job search behaviors, relational abilities, and employment specialist competencies are central contributors to acquisition of competitive employment.
Three days of intermittent stretching after muscle disuse alters the proteins involved in force transmission in muscle fibers in weanling rats

The aim of this study was to determine the effects of intermittent passive manual stretching on various proteins involved in force transmission in skeletal muscle. Female Wistar weanling rats were randomly assigned to 5 groups: 2 control groups containing 21- and 30-day-old rats that received neither immobilization nor stretching, and 3 test groups that received 1) passive stretching over 3 days, 2) immobilization for 7 days and then passive stretching over 3 days, or 3) immobilization for 7 days. Maximal plantar flexion in the right hind limb was imposed, and the stretching protocol of 10 repetitions of 30 s stretches was applied. The soleus muscles were harvested and processed for HE and picrosirius staining; immunohistochemical analysis of collagen types I, III, IV, desmin, and vimentin; and immunofluorescence labeling of dystrophin and CD68. The numbers of desmin- and vimentin-positive cells were significantly decreased compared with those in the control following immobilization, regardless of whether stretching was applied (P<0.05). In addition, the semi-quantitative analysis showed that collagen type I was increased and type IV was decreased in the immobilized animals, regardless of whether the stretching protocol was applied. In conclusion, the largest changes in response to stretching were observed in muscles that had been previously immobilized, and the stretching protocol applied here did not mitigate the immobilization-induced muscle changes. Muscle disuse adversely affected several proteins involved in the transmission of forces between the intracellular and extracellular compartments. Thus, the 3-day rehabilitation period tested here did not provide sufficient time for the muscles to recover from the disuse maladaptations in animals undergoing postnatal development.
Left ventricular remodeling after myocardial infarction: pathophysiology and therapy.

Left ventricular remodeling is the process by which ventricular size, shape, and function are regulated by mechanical, neurohormonal, and genetic factors.1 2 Remodeling may be physiological and adaptive during normal growth or pathological due to myocardial infarction, cardiomyopathy, hypertension, or valvular heart disease (Figure 1⇓). This article will review postinfarction remodeling, pathophysiological mechanisms, and therapeutic intervention. Figure 1. Diagrammatic representation of the many factors involved in the pathophysiology of ventricular remodeling. ECM indicates extracellular matrix; RAAS, renin-angiotensin-aldosterone system; CO, cardiac output; SVR, systemic vascular resistance; LV, left ventricular; and AII, angiotensin II. ### Postinfarction Left Ventricular Remodeling The acute loss of myocardium results in an abrupt increase in loading conditions that induces a unique pattern of remodeling involving the infarcted border zone and remote noninfarcted myocardium. Myocyte necrosis and the resultant increase in load trigger a cascade of biochemical intracellular signaling processes that initiates and subsequently modulates reparative changes, which include dilatation, hypertrophy, and the formation of a discrete collagen scar. Ventricular remodeling may continue for weeks or months until the distending forces are counterbalanced by the tensile strength of the collagen scar. This balance is determined by the size, location, and transmurality of the infarct, the extent of myocardial stunning, the patency of the infarct-related artery, and local tropic factors.1 3 The myocardium consists of 3 integrated components: myocytes, extracellular matrix, and the capillary microcirculation that services the contractile unit assembly. Consideration of all 3 components provides important insights into the remodeling process and a rationale for future therapeutic strategies. The cardiomyocyte is terminally differentiated and develops tension by shortening. The extracellular matrix provides a stress-tolerant, viscoelastic scaffold consisting of type I and type III collagen that couples myocytes and maintains the spatial relations between the myofilaments and their capillary microcirculation.4 5 The collagen framework couples adjacent myocytes by intercellular struts that …
Flexible expressed region analysis for RNA-seq with derfinder

Background Differential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. We previously introduced an intermediate statistical approach called differentially expressed region (DER) finder that seeks to identify contiguous regions of the genome showing differential expression signal at single base resolution without relying on existing annotation or potentially inaccurate transcript assembly. Results We present the derfinder software that improves our annotation-agnostic approach to RNA-seq analysis by: (1) implementing a computationally efficient bump-hunting approach to identify DERs which permits genome-scale analyses in a large number of samples, (2) introducing a flexible statistical modeling framework, including multi-group and time-course analyses and (3) introducing a new set of data visualizations for expressed region analysis. We apply this approach to public RNA-seq data from the Genotype-Tissue Expression (GTEx) project and BrainSpan project to show that derfinder permits the analysis of hundreds of samples at base resolution in R, identifies expression outside of known gene boundaries and can be used to visualize expressed regions at base-resolution. In simulations our base resolution approaches enable discovery in the presence of incomplete annotation and is nearly as powerful as feature-level methods when the annotation is complete. Conclusions derfinder analysis using expressed region-level and single base-level approaches provides a compromise between full transcript reconstruction and feature-level analysis. The package is available from Bioconductor at www.bioconductor. org/packages/derfinder.
On the pulse-width statistics in radio pulsars – I. Importance of the interpulse emission

We performed Monte Carlo simulations of different properties of pulsar radio emission, such as: pulsar periods, pulse–widths, inclination angles and rates of occurrence of interpulse emission (IP). We used recently available large data sets of the pulsar periods P, the pulse profile widths W and the magnetic inclination angle �. We also compiled the largest ever database of pulsars with interpulse emission, divided into the double–pole (DP–IP) and the single–pole (SP–IP) cases. We identified 31 (about 2%) and 13 (about 1%) of the former and the latter, respectively, in the population of 1520 normal pulsars. Their distribution on the P u P diagram strongly suggests a secular alignment of the magnetic axis from the originally random orientation. We derived possible parent distribution functions of important pulsar parameters by means of the Kolmogorov–Smirnov significance test using the available data sets (P, W, � and IP), different models of pulsar radio beam � = �(P) as well as different trial distribution functions of pulsar period P and the inclination angles �. The best suited parent period distribution function is the log–normal distribution, although the gamma function distribution cannot be excluded. The strongest constraint on derived model distribution functions was the requirement that the numbers of interpulses generated by means of Monte Carlo simulations (both DP–IP and SP–IP cases) were exactly (within 1� errors) at the observed level of occurrences. We found that a suitable model distribution function for the inclination angle is the complicated trigonometric function which has two local maxima, one near 0 � and the other near 90 � . The former and the latter implies the right rates of IP, occurrence, single–pole (almost aligned rotator) and double–pole (almost orthogonal rotator), respectively. It is very unlikely that the pulsar beam deviates significantly from the circular cross-section. We found that the upper limit for the average beaming factor fb describing a fraction of the full sphere (called also beaming fraction) covered by a pulsar beam is about 10%. This implies that the number of the neutron stars in the Galaxy might be underestimated.
Chapter 7 Bio-Inspired Algorithms for Fuzzy Rule-Based Systems

In this chapter we focus on three bio-inspired algorithms and their combinations with fuzzy rule based systems. Rule Based systems are widely being used in decision making, control systems and forecasting. In the real world, much of the knowledge is imprecise and ambiguous but fuzzy logic provides for systems better presentations of the knowledge, which is often expressed in terms of the natural language. Fuzzy rule based systems constitute an extension of classical Rule-Based Systems, because they deal with fuzzy rules instead of classical logic rules. Since bio-inspired optimization algorithms have been shown effective in improving the tuning the parameters and learning the Fuzzy Rule Base, our major objective is to represent the application of these algorithms in improving the Knowledge Based Systems with focus on Rule-Base Learning. We first introduce the Evolutionary Computation and Swarm Intelligence topics as a subfield of Computational Intelligence dealing with Combinatorial Optimization problems. Then, three following bio-inspired algorithms, i.e. Genetic Algorithms, Ant Colony Optimization, and Particle Swarm Optimization are explained and their application in improving the knowledge Based Systems are presented.
Chronic noise exposure and testosterone deficiency -- meta-analysis and meta-regression of experimental studies in rodents.

INTRODUCTION Chronic psychological distress can cause suppression of the hypothalamic-pituitary-testicular axis and thus lead to male hypogonadism, which is associated with psycho-social dysfunction, chronic diseases, and as a result, considerable economic costs. Conversely, noise is a prototypal environmental stressor of growing importance, already linked to birth outcomes and diabetes. However, its effects on male testosterone levels have been paid little attention. MATERIAL AND METHODS This paper reports a systematic review and meta-analysis of experimental studies in rodents, which have examined the effect of chronic noise stress on serum testosterone levels. A systematic search in MEDLINE, EMBASE and the Internet yielded seven studies. A quality effects meta-analytical model was applied to compute pooled Hedges's g. Quality effects meta-regression was carried out as well. RESULTS We found pooled Hedges's g of -2.41 (95% CI: -3.28, -1.54), indicating a very large effect of noise exposure on testosterone. Metaregression confirmed that the overall duration of exposure explained a significant proportion of the variance across individual effect sizes (Q (1) = 3.95, p = 0.047). However, there was considerable inter-study heterogeneity (I2 = 82%) and publication bias (p = 0.016). After inputting two studies previously thought to be missing, the pooled effect dropped to g = -1.53 (95% CI: -3.01, -0.05). CONCLUSIONS Chronic noise exposure of ≈ 100 dB leads to a significant reduction of serum testosterone in male rodents. Research on humans is highly warranted, especially given the steady trend in Western societies for increasing the burden of both male hypogonadism and noise pollution.
A Regionalizable Statistical Model of Intersecting Regions in protein-ligand binding Cavities

Finding elements of proteins that influence ligand binding specificity is an essential aspect of research in many fields. To assist in this effort, this paper presents two statistical models, based on the same theoretical foundation, for evaluating structural similarity among binding cavities. The first model specializes in the "unified" comparison of whole cavities, enabling the selection of cavities that are too dissimilar to have similar binding specificity. The second model enables a "regionalized" comparison of cavities within a user-defined region, enabling the selection of cavities that are too dissimilar to bind the same molecular fragments in the given region. We applied these models to analyze the ligand binding cavities of the serine protease and enolase superfamilies. Next, we observed that our unified model correctly separated sets of cavities with identical binding preferences from other sets with varying binding preferences, and that our regionalized model correctly distinguished cavity regions that are too dissimilar to bind similar molecular fragments in the user-defined region. These observations point to applications of statistical modeling that can be used to examine and, more importantly, identify influential structural similarities within binding site structure in order to better detect influences on protein-ligand binding specificity.
APEx: Automated inference of error specifications for C APIs

Although correct error handling is crucial to software robustness and security, developers often inadvertently introduce bugs in error handling code. Moreover, such bugs are hard to detect using existing bug-finding tools without correct error specifications. Creating error specifications manually is tedious and error-prone. In this paper, we present a new technique that automatically infers error specifications of API functions based on their usage patterns in C programs. Our key insight is that error-handling code tend to have fewer branching points and program statements than the code implementing regular functionality. Our scheme leverages this property to automatically identify error handling code at API call sites and infer the corresponding error constraints. We then use the error constraints from multiple call sites for robust inference of API error specifications. We evaluated our technique on 217 API functions from 6 different libraries across 28 projects written in C and found that it can identify error-handling paths with an average precision of 94% and recall of 66%. We also found that our technique can infer correct API error specifications with an average precision of 77% and recall of 47%. To further demonstrate the usefulness of the inferred error specifications, we used them to find 118 previously unknown potential bugs (including several security flaws that are currently being fixed by the corresponding developers) in the 28 tested projects.
Unsupervised Classification Using Immune Algorithm

Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed UCSC algorithm is more reliable and has high classification precision comparing to traditional classification methods such as K-means.
Period Focusing Induced by Network Feedback in Populations of Noisy Integrate-and-Fire Neurons

The population dynamics of an ensemble of nonleaky integrate-and-fire stochastic neurons is studied. The model selected allows for a detailed analysis of situations where noise plays a dominant role. Simulations in a regime with weak to moderate interactions show that a mechanism of excitatory message interchange among the neurons leads to a decrease in the firing period dispersion of the individual units. The dispersion reduction observed is larger than what would be expected from the decrease in the period. This period focusing is explained using a mean-field model. It is a dynamical effect that arises from the progressive decrease of the effective firing threshold as a result of the messages received by each unit from the rest of the population. A back-of-the-envelope formula to calculate this nontrivial dispersion reduction and a simple geometrical description of the effect are also provided.
Efficient Image Classification via Multiple Rank Regression

The problem of image classification has aroused considerable research interest in the field of image processing. Traditional methods often convert an image to a vector and then use a vector-based classifier. In this paper, a novel multiple rank regression model (MRR) for matrix data classification is proposed. Unlike traditional vector-based methods, we employ multiple-rank left projecting vectors and right projecting vectors to regress each matrix data set to its label for each category. The convergence behavior, initialization, computational complexity, and parameter determination are also analyzed. Compared with vector-based regression methods, MRR achieves higher accuracy and has lower computational complexity. Compared with traditional supervised tensor-based methods, MRR performs better for matrix data classification. Promising experimental results on face, object, and hand-written digit image classification tasks are provided to show the effectiveness of our method.
Genomic Repeat Abundances Contain Phylogenetic Signal

A large proportion of genomic information, particularly repetitive elements, is usually ignored when researchers are using next-generation sequencing. Here we demonstrate the usefulness of this repetitive fraction in phylogenetic analyses, utilizing comparative graph-based clustering of next-generation sequence reads, which results in abundance estimates of different classes of genomic repeats. Phylogenetic trees are then inferred based on the genome-wide abundance of different repeat types treated as continuously varying characters; such repeats are scattered across chromosomes and in angiosperms can constitute a majority of nuclear genomic DNA. In six diverse examples, five angiosperms and one insect, this method provides generally well-supported relationships at interspecific and intergeneric levels that agree with results from more standard phylogenetic analyses of commonly used markers. We propose that this methodology may prove especially useful in groups where there is little genetic differentiation in standard phylogenetic markers. At the same time as providing data for phylogenetic inference, this method additionally yields a wealth of data for comparative studies of genome evolution.
Relationship Between Job Stress, Workload, Environment and Employees Turnover Intentions: What We Know, What Should We Know

In this competitive era, organizations are continuously looking new ways to develop their human capital. This leads to a new challenge i.e., how organizations can retain their skilled human resource. Present study is focused to find out the relationship among job stressor, workload, work place environment and employee turnover intentions. A random sample of 250 employees from textile industry of Pakistan is selected. Total 109 employees responded and filled the questionnaire, with a response rate of 44%. Structural modelling is used for empirical analysis of data using AMOS 18 software. Results reveal that employee turnover intentions are positively related with job stressor and work load. While negative relationship with work place environment is reported.