Miracle-dz/UniFAR-FTUs huggingface dataset:
A Virtual Instrument for Time-Frequency Analysis of Park Power Components

Load signature analysis has been widely studied in the last ten years. It is possible to recognize a progressive growth of complexity in the approach adopted. One of the most significant changes has been the shift from quasi-steady-state analysis approaches to fully transient analysis. A case for this shift is well made in [1]. While the steadystate analysis of power components can be successfully completed in a residential environment, the same approach is very likely to fail in an industrial environment. The main reason for this failure is the fact that the signature-space becomes quickly crowded with undistinguishable loads. The use of transient data widely enriches the amount of information available allowing for the identification of a wider set of loads. In a previous paper the authors presented an approach to signature analysis based on the combination of the Park transform and a wavelet transformation [2]. The main concepts behind this approach are the following. In order to get meaningful signatures the use of current or voltage is not enough. An interesting approach is proposed in [3], where the signature is reconstructed by using instantaneous power and current. As already demonstrated in [2] through some examples a significant amount of information can be reconstructed by the instantaneous components of the power in Park domain. A comprehensive analysis of the physical interpretation of these power components can be found in [4] and [5]. In [2], in order to cope with transient data, the Park power components have been analyzed through wavelet transformation. The idea of using wavelets to analyze transient power has also been proposed in [6]and [7]. In this case though, the work focuses on single phase systems and the use of 90 degree shift filter is proposed to obtain information about reactive power. Wavelets are widely applied in power quality analysis [8] for the same reasons why the authors believe they can have a significant impact on load signature analysis: possibility to analyze non-stationary components, multiresolution capability. In particular, by using dyadic-orthonormal bases we can extract significant information for the frequency domain analysis of power. In the following, we briefly report some basic remarks about Park Transformation and Wavelet and then we focus on the implementation of the algorithms in a distributed monitoring environment. The details of the LabVIEW implementations as well as data about the hardware adopted are reported. Finally a hardware-in-the-loop (HIL) testing procedure is presented to validate the developed software. The HIL experiment is based on the Virtual Test Bed Real Time Extension (VTB-RT) developed at the University of South Carolina. Thanks to this platform, as shown in the following, we have been able to replicate the scenarios presented in [2] without the need of actually create a real flow of power but nevertheless using the real data acquisition system and the embedded hardware for measurement.
A Postmodern Argument Against Censorship: Negotiating Gender and Sexual Identity through Canadian Young Adult Novels

Resume: D'apres les theories postmodernes, les gens creent leur propre identite en reagissant aux discours culturels qu'ils doivent subir. Les adolescents canadiens etant ainsi sournis a des discours contradictoires sur la sexualite, il devient done imperieux d'etudier en classe des oeuvres qui contrebalancent ces influences parfois discutables. La lecture de romans de bon aloi, sous la gouverne de professeurs attentifs, pennettra done aux jeunes de definir et d'assumer leur identite sexuelle de facon sereine. Summary: Postmodern theories suggest that meaning is never fixed and constant, and that people are continually creating their own "identities"(their beliefs about themselves, their values, their ways of relating to the world) in interaction with the public and private forms of language which surround them. Canadian teenagers are bombarded by cultural discourses concerning gender, sexuality and violence which may be contradictory, confusing and destructive. Canadian young adult novels studied in school offer alternative discourses which enrich and balance ideas and messages received outside of school. Young people need the freedom to read and study Canadian novels in school in the company of a caring teacher, and in ways which allow them considerable latitude in negotiating and constructing meanings for gender and sexual identity.
Design & Implementation of Low Power 3-bit Flash ADC in 0.18μm CMOS

—This paper describes the design and implementation of a Low Power 3-bit flash Analog to Digital converter (ADC). It includes 7 comparators and one thermometer to binary encoder. It is implemented in 0.18um CMOS Technology. The pre-simulation of ADC is done in T-Spice and post layout simulation is done in Microwind3.1. The response time of the comparator equal to 6.82ns and for Flash ADC as 18.77ns. The Simulated result shows the power consumption in Flash ADC as is 36.273mw . The chip area is for Flash ADC is 1044um 2 .
Wilson fermions at finite temperature

The author conjectures on the phase structure expected for lattice gauge theory with two flavors of Wilson fermions, concentrating on large values of the hopping parameter. Numerous phases are expected, including the conventional confinement and deconfinement phases, as well as an Aoki phase with spontaneous breaking of flavor and parity and a large hopping phase corresponding to negative quark masses.
ICA based feature learning and feature selection

Feature extraction is playing a major role in bio signal processing. Feature identification and selection has two approaches. The common approach is engineering handcraft which is based on user experience and application area. While the other approach is feature learning that based on making the system identify and select the best features suit the application. The idea behind feature learning is to avoid dealing with any feature extraction or reduction algorithms and to train the suggested model on learning with avoiding the exposure to feature extraction which is mainly based on researcher experience. In this paper, Independent component analysis (ICA) will be implemented as a feature learning technique to learn the model extract the features from the input data. Deep learning approach will be proposed by implementing ICA to learn features. In the proposed model, the raw data will be read then represented by using different signal representation as Spectrogram, Wavelet and Wavelet Packet. Then, the new represented data will be fed to Independent component analysis layer to generate features and finally, the performance of the suggested scheme will be evaluated by applying different classifiers such as Support Vector Machine, Extreme Learning Machine and Discriminate Analysis. And As an improving step for the results, classifier fusion layer will be implemented to select the most accurate result for both training and testing set. Classifier fusion layer resulted in a promising training and testing accuracies. On the other side, Feature Selection is the process of selecting subset of features from a pool of features.
Interconnection of long-reach PON and backbone networks

This paper proposes an evolution of the STARGATE long-reach PON architecture to allow the optical interconnection of multiple STARGATEs by means of a GMPLS-based backbone network. The architecture of the optical bypass gateway is proposed and the distributed signalling for establishing inter-STARGATE connection requests is detailed. The optical bypassing capacity of the proposed architecture is evaluated through simulations.
On the Distance of Magellanic Clouds: First Overtone Cepheids

We present a detailed comparison between predicted and empirical PLI, K relations and the Wesenheit function for Galactic and Magellanic Cloud (MC) first overtone (FO) Cepheids. We find that zero points predicted by Galactic Cepheid models based on a noncanonical (mild overshooting) mass-luminosity (ML) relation are in very good agreement with empirical zero points based on Hipparcos parallaxes, while those based on the canonical (no overshooting) ML relation are ≈0.2-0.3 mag brighter. We also find that the predicted and empirical PLK relations and Wesenheit function give, according to optical (V, I; Optical Gravitational Lensing Experiment) and near-infrared (K; Two Micron All Sky Survey) data, mean distances to the MCs that agree at the 2% level. Individual distances to the Large and the Small MCs are 18.53 ± 0.08 and 19.04 ± 0.11 (theory) as well as 18.48 ± 0.13 and 19.01 ± 0.13 (empirical). Moreover, predicted and empirical FO relations do not present, within the errors, a metallicity dependence. Finally, we find that the upper limit in the FO period distribution is a robust observable to constrain the accuracy of pulsation models. Current models agree within 0.1 in log P with the observed FO upper limits.
On audience activities during presentations

Audiences have most likely always been subject to distraction and drift during all varieties of presentation. While these activities were often confined to solitary activities since inter-person distractions were limited by their visibility to the speaker (ever been caught passing notes in class? ), in the current networked-enabled presentation room, multi-person off-task "distractions" are now possible (ever read your e-mail during a conference talk? ). This paper explores the potential for positive effects of this ability; back-channel discussions that are on-topic and can even lead to a more involved audience and better interaction with the presenter.
Comparison of Different Classifiers for Biometric System Based on EEG Signals

Characteristics in EEG signals related to the motor imagery can be used to build up a biometric system. However, for the practical implementation of a biometric system, the classifier plays a crucial role. In this paper, I compared the performance of three different classifiers for the detection of the imagined movements in a group of subjects on the basis of EEG signals. The classifiers compared here were those based on Linear Discrimination Analysis (LDA), Artificial Neural Network (ANN) and Support Virtual Machine (SVM). Results show a better performance of the LDA classifier with the respect to the other classifiers.
Multilayer Optical Learning Networks

In this paper we present a new approach to learning in a multilayer optical neural network which is based on holographically interconnected nonlinear Fabry-Perot etalons. The network can learn the interconnections that form a distributed representation of a desired pattern transformation operation. The interconnections are formed in an adaptive and self aligning fashion, as volume holographic gratings in photorefractive crystals. Parallel arrays of globally space integrated inner products diffracted by the interconnecting hologram illuminate arrays of nonlinear Fabry-Perot etalons for fast thresholding of the transformed patterns. A phase conjugated reference wave interferes with a backwards propagating error signal to form holographic interference patterns which are time integrated in the volume of the photorefractive crystal in order to slowly modify and learn the appropriate self aligning interconnections. A holographic implementation of a single layer perceptron learning procedure is presented that can be extendept ,to a multilayer learning network through an optical implementation of the backward error propagation (BEP) algorithm.
CHD1L: a new candidate gene for congenital anomalies of the kidneys and urinary tract (CAKUT).

BACKGROUND Recently, we identified a microduplication in chromosomal band 1q21.1 encompassing the CHD1L/ALC1 gene encoding a chromatin-remodelling enzyme in congenital anomalies of the kidneys and urinary tract (CAKUT) patient. METHODS To explore the role of CHD1L in CAKUT, we screened 85 CAKUT patients for mutations in the CHD1L gene and performed functional analyses of the three heterozygous missense variants detected. In addition, we quantitatively determined CHD1L expression in multiple human fetal and adult tissues and analysed expression of CHD1L protein in human embryonal, adult and hydronephrotic kidney sections. RESULTS Two of three novel heterozygous missense variants identified in three patients were not found in >400 control chromosomes. All variants lead to amino acid substitutions in or near the CHD1L macro domain, a poly-ADP-ribose (PAR)-binding module interacting with PAR polymerase 1 (PARP1), and showed decreased interaction with PARP1 by pull-down assay of transfected cell lysates. Quantitative messenger RNA analysis demonstrated high CHD1L expression in human fetal kidneys, and levels were four times higher than in adult kidneys. In the human embryo at 7-11 weeks gestation, CHD1L immunolocalized in the early ureteric bud and the S- and comma-shaped bodies, critical stages of kidney development. In normal postnatal sections, CHD1L was expressed in the cytoplasm of tubular cells in all tubule segments. CHD1L expression appeared higher in the hydronephrotic kidney of one patient with a hypofunctional CHD1L variant than in normal kidneys, recapitulating high fetal levels. CONCLUSION Our data suggest that CHD1L plays a role in kidney development and may be a new candidate gene for CAKUT.
Risks of general artificial intelligence

The papers in this special volume of the Journal of Experimental and Theoretical Artificial Intelligence are the outcome of a conference on the ‘Impacts and Risks of Artificial General Intelligence’ (AGI-Impacts) that took place at the University of Oxford, St Anne’s College, on 10 and 11 December 2012 – jointly with the fifth annual conference on ‘Artificial General Intelligence’ (AGI-12). The conference was organised by the Future of Humanity Institute at Oxford: academically by Nick Bostrom and myself, with support from research fellows Stuart Armstrong, Toby Ord, Anders Sandberg and more members of the program committee; organisationally by Seán Ó hÉigeartaigh, with support from Alexandre Erler, Daniel Dewey, Stuart Armstrong and others. We are grateful to the Artificial General Intelligence (AGI) community for the openness to these issues of security, as shown by the fact that they initiated this connection and that the vast majority of the ca. 150 participants of the main AGI meeting also attended our AGI-Impacts event. Last but not least, we want to thank the ‘European Network for Cognitive Systems, Interaction and Robotics’ and the organisation ‘Saving Homo Sapiens’ for sponsoring the event.
Grouping . ,-, → ,-, into regions , curves , and junctions

We address the problem of extracting segmented, structured information from noisy data obtained through local processing of images. A unified computational framework is developed for the inference of multiple salient structures such as junctions, curves, regions, and surfaces from any combinations of points, curve elements and surface patch elements inputs in 2-D and 3-D. The methodology is grounded in two elements: tensor calculus for representation, and non-linear voting for data communication. Each input site communicates its information (a tensor) to its neighborhood through a predefined (tensor) field, and therefore cast a (tensor) vote. Each site collects all the votes casted at its location and encodes them into a new tensor. A local, parallel routine such as a modified marching cube/square process then simultaneously detects junctions, curves, regions, and surfaces. The proposed method is non-iterative, requires no initial guess or thresholding, can handle the presence of multiple curves, regions and surfaces in a large amount of noise while still preserves discontinuities, and the only free parameter is scale.
Optimizing HTTP-based Adaptive Video Streaming for wireless access networks

In this paper, we propose an optimization algorithm called Intelligent Bitrate Switching-based Adaptive Video Streaming (ISAVS) to address the key issue of bitrate switching in HTTP-based adaptive video streaming. Our proposed solution can provide the best possible video quality to users with minimum replay interruption, which is reported as one of the key video quality issues of on-line video streaming over wireless access networks. While the optimization algorithm is based on IIS Smooth Streaming architecture [1], it can be easily applied by other proposed approaches, such as Adobe Flash Dynamic Streaming, and Apple HTTP Adaptive Bitrate Streaming. Simulations show that our optimization algorithm selects the best video bitrate according to channel condition and the amount of video stream buffered in the client to provide viewers the best possible quality while reducing the number of interruptions.
Cardiovascular risk factors in pre-pubertal schoolchildren in Angola

Summary Methods The incidence of obesity is increasing worldwide, especially in countries with accelerated economic growth. We determined the prevalence of and associations between overweight/ obesity and cardiovascular risk factors in pre-pubertal (seven- to 11-year-old) schoolchildren (both genders, n = 198) in Luanda, Angola. Biochemical (fasting blood) and clinical examinations were obtained in a single visit. Data are reported as prevalence (95% confidence intervals) and association (r, Pearson). Results Prevalence of overweight/obesity was 17.7% (12.4–23.0%), high blood pressure (BP < 90% percentile) was 14.6% (9.7–19.5%), elevated glucose level was 16.7% (11.5–21.9%) and total cholesterol level < 170 mg/dl (4.4 mmol/l) was 69.2% (62.8–75.6%). Significant associations between body mass index (BMI) and systolic and diastolic BP (r = 0.46 and 0.40, respectively; p < 0.05) were found. No association between BMI and elevated glucose or cholesterol levels was found. Conclusion The prevalence of cardiovascular risk factors was high in pre-pubertal schoolchildren in Angola and fat accumulation was directly associated with blood pressure increase but not with other cardiovascular risk factors.
Early Respiratory Therapy Reduces Postoperative Atelectasis in Children Undergoing Lung Resection

BACKGROUND: Early physiotherapy reduces pulmonary complications after lung resection in adult patients. However, the effectiveness and the techniques used in postoperative physiotherapy in children undergoing lung resection have not been well described. Therefore, the standardization of a physiotherapeutic attendance after lung resection in children is necessary. METHODS: This was a retrospective and prospective, interventional, descriptive, and quantitative study. We evaluated 123 pediatric subjects undergoing lung resection. Fifty-two children were prospectively submitted to a standardized physiotherapy protocol that included a mask with a positive expiratory pressure of 10 cm H2O, expiratory rib cage compression, coughing, lifting the upper limbs, and ambulation, starting within the first 4 hours after surgery and continuing 3 times each day. A historical control group of 71 subjects received physiotherapeutic techniques without specific standardization and with variability in the start date and number of days attended. We recorded the presence of postoperative complications, prolonged air leak, postoperative bronchoscopy, the time of chest tube removal, and hospital stay following surgery. RESULTS: The group that received a standardized protocol of physiotherapy had fewer instances of atelectasis than the control group (15.4% vs 7.6%, P = .01). Subjects in the control group were more likely than those in the intervention group to require fiberoptic bronchoscopy for bronchial toilet (n = 14 [19.7%] vs n = 5 [9.6%], P ≤ .001). There was no difference in the time of drainage or hospital stay between the groups. CONCLUSIONS: Implementation of a standardized physiotherapeutic protocol after lung resection in children decreases atelectasis but does not reduce the time of chest tube removal or the duration of hospital stay.
A performance comparison of PSO and GA in scheduling hybrid flow-shops with multiprocessor tasks

Applications in industry and computing require a proper scheduling of tasks to achieve good performance. The algorithms presented in this paper tackles task scheduling problem in a multi layer multiprocessor environment. Using the scheduling terminology, problem is defined as multiprocessor task scheduling in hybrid flow-shops. This paper presents a particle swarm optimization (PSO) algorithm for the solution. In order to improve the performance of PSO, hybrid techniques were also employed. The performance results, compared with other well known meta-heuristics from the literature, are reported. Results show that PSO and hybrid methods have merits in solving multiprocessor task scheduling in hybrid flow-shop environment.
Heart rate correlates of adversive and rewarding electrical stimulation of septal, hypothalamic and mesencephalic areas in rats.

Thirty-nine albino rats were implanted with subcutaneous 10KG recording electrodes and with brain electrodes in rewarding and aversive areas. Of these 13 subjects provided useable data for 31 electrode sites in septal, hypothalamic, and dorsomedial tegmental locations. Stimulation was presented at 1, 3, and 5 sec. duration and over a range of intensities from a low current intensity just above "threshold" to a high value which was limited by motor effects, convulsions, and violent escape reactions. Rats were initiallytrained to press a lever to acquire and/or escape stimulation. Heart rate measurements during rewarding and aversive stimulation were obtained while subjects were untreated, under pentobarbital anesthesia, or curarized. Curare elevated heart rate about 100 bpm< above the other two conditions. In general, rewarding stimulation tended to be correlated with bradycardia during stimulation, while aversive stimulation was correlated with stimulation-tachycardia followed by post-stimulation breidycardia.
Mutations in Desmoglein-2 Gene Are Associated With Arrhythmogenic Right Ventricular Cardiomyopathy

Background— Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by progressive myocardial atrophy with fibrofatty replacement. The recent identification of causative mutations in plakoglobin, desmoplakin (DSP), and plakophilin-2 (PKP2) genes led to the hypothesis that ARVC is due to desmosomal defects. Therefore, desmoglein-2 (DSG2), the only desmoglein isoform expressed in cardiac myocytes, was screened in subjects with ARVC. Methods and Results— In a series of 80 unrelated ARVC probands, 26 carried a mutation in DSP (16%), PKP2 (14%), and transforming growth factor-&bgr;3 (2.5%) genes; the remaining 54 were screened for DSG2 mutations by denaturing high-performance liquid chromatography and direct sequencing. Nine heterozygous DSG2 mutations (5 missense, 2 insertion-deletions, 1 nonsense, and 1 splice site mutation) were detected in 8 probands (10%). All probands fulfilled task force criteria for ARVC. An endomyocardial biopsy was obtained in 5, showing extensive loss of myocytes with fibrofatty tissue replacement. In 3 patients, electron microscopy investigation was performed, showing intercalated disc paleness, decreased desmosome number, and intercellular gap widening. Conclusions— This is the first investigation demonstrating DSG2 gene mutations in a significant number of ARVC-unrelated probands. Cardiac phenotype is characterized clinically by typical ARVC features with frequent left ventricular involvement and morphologically by fibrofatty myocardial replacement and desmosomal remodeling. The presence of mutations in desmosomal encoding genes in 40% of cases confirms that many forms of ARVC are due to alterations in the desmosome complex.