Miracle-dz/UniFAR-FTUs huggingface dataset:
Video super-resolution based on nonlinear mapping and patch similarity

Aiming at recovering lost detailed information in low-resolution videos, a novel video super-resolution algorithm based on nonlinear mapping and patch similarity was proposed in this paper. Taking advantage of the strong fitting ability of the convolutional neural network for the nonlinear relationship, this algorithm utilizes the learned reconstruction parameters to pad missing structures and make the low-resolution video approach to the ground truth. However, it is unavoidable to introduce irrelevant information and amplify noises in this process. The patch similarity is imported to improve the spatial-temporal consistency and anti-noise ability of this algorithm. Moreover, instead of considering the nonlocal self-similarity only, this algorithm combines the nonlocal external sparsity and spatial-temporal similarity to enrich the prior information. All these patch similarities are used to optimize the intermediate video achieved from the mapping process. Experimental results demonstrated that the proposed algorithm achieves a competitive super-resolution quality on both the subjective and the objective evaluations, when compared to other state-of-the-art algorithms.
Orphan Afterglows of Collimated Gamma-Ray Bursts: Rate Predictions and Prospects for Detection

We make a quantitative prediction for the detection rate of orphan gamma-ray burst (GRB) afterglows as a function of flux sensitivity in X-ray, optical, and radio wave bands, based on a recent model of collimated GRB afterglows. We find that the orphan afterglow rate strongly depends on the opening angle of the jet (roughly ∝θ), as expected from simple geometrical consideration, if the total jet energy is kept constant as suggested by recent studies. The relative beaming factor brel, i.e., the ratio of all afterglow rates including orphans to those associated with observable prompt GRBs, could be as high as brel ≳ 100 for searches deeper than R ~ 24, depending on afterglow parameters. To make the most plausible predictions, we average the model emission for 10 sets of afterglow parameters obtained through fits to 10 well-observed, collimated GRB jets, weighted by the sky coverage of each jet. Our model expectations are consistent with the results (or constraints) obtained by all past searches. We estimate the number of orphan afterglows in the first 1500 deg2 field of the Sloan Digital Sky Survey (SDSS) to be about 0.2. The relative beaming factor brel is rapidly increasing with the search sensitivity: brel ~ 3 for the SDSS sensitivity to transient objects in the northern sky (R ~ 19), ~14 for the past high-z supernova searches (R ~ 23), and ~50 for the sensitivity of the Subaru Suprime-Cam (R ~ 26). Predictions are made for the current facilities and future projects in X-ray, optical, and radio bands. Among them, the southern sky observation of the SDSS (sensitive to transients down to R ~ 23) could detect ~40 orphan afterglows during the 5 yr operation. The Allen Telescope Array would find about 200 afterglows in a radio band at ~0.1-1 mJy with brel ~ 15.
Gender differences in pretend play in a primary school group

This study observed pretend play behaviour in 4#fr1#sh2> year old boys and girls in their first term at school. It was found that girls engaged in slightly more episodes of pretend play behaviour than boys. Girls also engaged in person fantasy play more than boys, whereas boys engaged in more object fantasy play. It was also found that both boys and girls showed more co‐operative pretend play than solitary pretend play. There were no differences in number of verbalisations in pretend play between boys and girls.
Toward Naturalistic Self-Monitoring of Medicine Intake

Since drug actions are dose- and time-dependent, adherence to prescribed medications is essential for the effectiveness of therapies. Unfortunately, several studies show that when patients are responsible for treatment administration, poor adherence is prevalent. Hence, it is necessary to devise effective methods to remotely assess medication compliance and support self-administration of drugs. Existing methods include electronic reminders such as short message service reminders and pill reminder apps. Although those tools may help increasing adherence, they interfere with the normal routine of patients by providing unnecessary reminders, or providing the reminder at an unfortunate time. More sophisticated solutions include the use of smart packaging and ingestible sensors to quantify and monitor drug intake. While those solutions do not interfere with normal routines, currently they are restricted to patients involved in a few clinical studies. In this paper, we introduce a novel system to support self-administration of drugs without interfering with the patient's routines. The system is based on a combination of cheap sensors and a smartphone. Tiny Bluetooth low energy sensors attached to medicine boxes communicate motion data to an app running on the patient's smartphone. Thanks to a machine learning algorithm, the app detects intake events, and reminds the user only when needed. Active learning is used to improve recognition rates thanks to the user's feedback. Preliminary experiments with a dataset acquired from volunteers show that the algorithm can detect most intake events with a few false positives. At the time of writing, we have developed a working prototype of the system, and we are beginning an experimental evaluation with a group of patients of an Italian hospital.
Haptic Interaction for Hands-On Learning in System Dynamics and Controls

Every student entering the control engineering classroom brings years of experience in the hands-on practice of controls, earned through the control of the motions and actions of his or her own body and the control of objects in the environment. Much of this control experience has been subjected to conscious observation and experimentation, yet this expertise is very seldom leveraged when teaching control theory in the classroom. Certainly, tying theory to existing practical knowledge is a process containing many potential pitfalls. But if concepts in control theory can be correctly and appropriately tied to personal experience and intuition in human motor control, then our effectiveness as control educators could be significantly increased. By harnessing this intuition, the mathematical symbols manipulated on paper might be integrated with intuitive, long-lasting memory and used to develop good engineering judgement.
Cooperative spectrum sensing based on the limiting eigenvalue ratio distribution in wishart matrices

Recent advances in random matrix theory have spurred the adoption of eigenvalue-based detection techniques for cooperative spectrum sensing in cognitive radio. These techniques use the ratio between the largest and the smallest eigenvalues of the received signal covariance matrix to infer the presence or absence of the primary signal. The results derived so far are based on asymptotical assumptions, due to the difficulties in characterizing the exact eigenvalues ratio distribution. By exploiting a recent result on the limiting distribution of the smallest eigenvalue in complex Wishart matrices, in this paper we derive an expression for the limiting eigenvalue ratio distribution, which turns out to be much more accurate than the previous approximations also in the non-asymptotical region. This result is then applied to calculate the decision sensing threshold as a function of a target probability of false alarm. Numerical simulations show that the proposed detection rule provides a substantial improvement compared to the other eigenvalue-based algorithms.
Dissecting Contributions: Experiences in Elementary and Middle School Physical Education

School age learners like physical education because the experiences provide much enjoyment. Most of them, however, do not think physical education experiences are valuable in terms of gaining useful knowledge and skills (Goodlad, 1984). In the standard-based curriculum reform, a number of standards have been developed to enhance positive experiences for learning, such as the standards developed by National Association of Sport and Physical Education (2004) in the United States. At local levels, the states have been creating curricula and assessment tools to help learners accomplish the goals defined in the standards (e.g., Rink & Mitchell, 2003).
A retrospective analysis of endoscopic treatment outcomes in patients with postoperative bile leakage

OBJECTIVE: Bile leakage, while rare, can be a complication seen after cholecystectomy. It may also occur after hepatic or biliary surgical procedures. Etiology may be underlying pathology or surgical complication. Endoscopic retrograde cholangiopancreatography (ERCP) can play major role in diagnosis and treatment of bile leakage. Present study was a retrospective analysis of outcomes of ERCP procedure in patients with bile leakage. METHODS: Patients who underwent ERCP for bile leakage after surgery between 2008 and 2012 were included in the study. Etiology, clinical and radiological characteristics, and endoscopic treatment outcomes were recorded and analyzed. RESULTS: Total of 31 patients (10 male, 21 female) were included in the study. ERCP was performed for bile leakage after cholecystectomy in 20 patients, after hydatid cyst operation in 10 patients, and after hepatic resection in 1 patient. Clinical signs and symptoms of bile leakage included abdominal pain, bile drainage from percutaneous drain, peritonitis, jaundice, and bilioma. Twelve (60%) patients were treated with endoscopic sphincterotomy (ES) and nasobiliary drainage (NBD) catheter, 7 patients (35%) were treated with ES and biliary stent (BS), and 1 patient (5%) was treated with ES alone. Treatment efficiency was 100% in bile leakage cases after cholecystectomy. Ten (32%) cases of hydatid cyst surgery had subsequent cystobiliary fistula. Of these patients, 7 were treated with ES and NBD, 2 were treated with ES and BS, and 1 patient (8%) with ES alone. Treatment was successful in 90% of these cases. CONCLUSION: ERCP is an effective method to diagnose and treat bile leakage. Endoscopic treatment of postoperative bile leakage should be individualized based on etiological and other factors, such as accompanying fistula.
Assessment of effective parameters on dilution using approximate reasoning methods in longwall mining method, Iran coal mines

Approximately more than 90% of all coal production in Iranian underground mines is derived directly longwall mining method. Out of seam dilution is one of the essential problems in these mines. Therefore the dilution can impose the additional cost of mining and milling. As a result, recognition of the effective parameters on the dilution has a remarkable role in industry. In this way, this paper has analyzed the influence of 13 parameters (attributed variables) versus the decision attribute (dilution value), so that using two approximate reasoning methods, namely Rough Set Theory (RST) and Self Organizing Neuro- Fuzzy Inference System (SONFIS) the best rules on our collected data sets has been extracted. The other benefit of later methods is to predict new unknown cases. So, the reduced sets (reducts) by RST have been obtained. Therefore the emerged results by utilizing mentioned methods shows that the high sensitive variables are thickness of layer, length of stope, rate of advance, number of miners, type of advancing.
Evolution of the X-ray Emission of Radio-quiet Quasars

We report new Chandra observations of seven optically faint, z ~ 4 radio-quiet quasars (RQQs). We have combined these new observations with previous Chandra observations of RQQs to create a sample of 174 sources. These sources have 0.1 < z < 4.7, and 1044 ergs s-1 < νLν (2500 Å) < 1048 ergs s-1. The X-ray detection fraction is 90%. We find that the X-ray loudness of RQQs decreases with UV luminosity and increases with redshift. The model that is best supported by the data has a linear dependence of optical to X-ray ratio αox on cosmic time and a quadratic dependence of αox on log LUV, where αox becomes X-ray quiet more rapidly at higher log LUV. We find no significant evidence for a relationship between the X-ray photon index Γx and the UV luminosity, and we find marginally significant evidence that the X-ray continuum flattens with increasing z (2 σ). The Γx-z anticorrelation may be the result of X-ray spectral curvature, redshifting of a Compton reflection component into the observed Chandra band, and/or redshifting of a soft excess out of the observed Chandra band. Using the results for Γx, we show that the αox-z relationship is unlikely to be a spurious result caused by redshifting of the observable X-ray spectral region. A correlation between αox and z implies evolution of the accretion process. We present a qualitative comparison of these new results with models for accretion disk emission.
Teaching Bodies: Affects in the Classroom

This article reintroduces notions of the experiential, lived body as crucial for teaching. It critiques some recent moves within women’s studies, and cultural studies more generally, to use ‘theory’ as a way of abstracting bodies from the classroom. Using the work of Silvan Tomkins on affects, and Deleuzian notions of the body, it argues for a more comprehensive account of the affects, politics and practices of pedagogy.
Asthma Length of Stay in Hospitals in London 2001–2006: Demographic, Diagnostic and Temporal Factors

Asthma is a condition of significant public health concern associated with morbidity, mortality and healthcare utilisation. This study identifies key determinants of length of stay (LOS) associated with asthma-related hospital admissions in London, and further explores their effects on individuals. Subjects were primarily diagnosed and admitted for asthma in London between 1st January 2001 and 31st December 2006. All repeated admissions were treated uniquely as independent cases. Negative binomial regression was used to model the effect(s) of demographic, temporal and diagnostic factors on the LOS, taking into account the cluster effect of each patient's hospital attendance in London. The median and mean asthma LOS over the period of study were 2 and 3 days respectively. Admissions increased over the years from 8,308 (2001) to 10,554 (2006), but LOS consistently declined within the same period. Younger individuals were more likely to be admitted than the elderly, but the latter significantly had higher LOS (p<0.001). Respiratory related secondary diagnoses, age, and gender of the patient as well as day of the week and year of admission were important predictors of LOS. Asthma LOS can be predicted by socio-demographic factors, temporal and clinical factors using count models on hospital admission data. The procedure can be a useful tool for planning and resource allocation in health service provision.
Predicting Inmate Penitentiary Adjustment

This study examines the relative efficacy of four classification systems in predicting inmate institutional adjustment in a penitentiary setting. The four systems are: (1) demographic variables, (2) Megargee Typologies, (3) Security Designation, and (4) Custody Classification. Data on 337 male inmates' adjustment as measured by four criterion variables of (a) number of disciplinary reports received, (b) days spent in disciplinary segregation, (c) days of statutory good time forfeited. and (d) work performance ratings were obtained and analyzed in relation to the four classification systems. Results of a canonical correlation procedure indicate that Custody Classification was the single best predictor of overall inmate adjustment with the demographic variable of age a distant second best. Using a stepwise multiple regression, each of the four measures of inmate adjustment was examined separately. Results reveal Custody Classification and inclusion in three of the ten Megargee Typologies to be the most effective single predictors. Recommendation for establishing a classificatory formula based on these variables is made with emphasis placed on the benefits of such a system.
Time-optimal path tracking for robots under dynamics constraints based on convex optimization

SUMMARY To fully utilize the dynamic performance of robotic manipulators and enforce minimum motion time in path tracking, the problem of minimum time path tracking for robotic manipulators under confined torque, change rate of the torque, and voltage of the DC motor is considered. The main contribution is the introduction of the concepts of virtual change rate of the torque and the virtual voltage, which are linear functions in the state and control variables and are shown to be very tight approximation to the real ones. As a result, the computationally challenging non-convex minimum time path tracking problem is reduced to a convex optimization problem which can be solved efficiently. It is also shown that introducing dynamics constraints can significantly improve the motion precision without costing much in motion time, especially in the case of high speed motion. Extensive simulations are presented to demonstrate the effectiveness of the proposed approach.
Academic self-efficacy in ALL: Capacity-building through self-belief

Academic Language and Learning (ALL) Advisers are very often in the position of building students’ confidence in their ability to study; indeed, this may even be a core business of what we do. This role can be clarified through a clear understanding of what academic self-efficacy is and how to develop it. This article reviews the literature on academic self-efficacy before giving clear and concrete suggestions for how these insights may be applied to the practice of ALL Advisers. This is a step towards articulating the approach of the ALL “community of practice”.
Contributions of ventilation and perfusion inhomogeneities to the VA/Q distribution.

The anatomic distributions of ventilation (VA) and perfusion (Q) in prone and supine dogs have been described in the literature. These data also provide frequency distributions, i.e., the distribution of lung units as a function of VA or Q. A comprehensive distribution that encompasses these two distributions is described, and the properties of the comprehensive distribution that determine the width of the VA/Q distribution are identified. Using data on the VA and Q distributions taken from various sources in the literature, we estimated the widths of the VA/Q distributions. The widths estimated from the independent data on the VA and Q distributions agree well with the widths obtained from gas exchange data. The analysis provides information about the relative contributions of the VA and Q distributions to the width of the VA/Q distribution. In the prone dog, the VA and Q distributions, as described by the available data, have different length scales, and we argue that these distributions are therefore not highly correlated. As a result, the variance of the VA/Q distributions is approximately the sum of the variances of the VA and Q distributions. Two-thirds of the variance in VA/Q is a result of nonuniform Q, and one-third is a result of nonuniform VA. In the supine dog, the variance of VA is larger than in the prone dog because of a vertical gradient and the variance of Q is larger, in part, because of a vertical gradient. Because the magnitudes of the vertical gradients of VA and Q are about equal, the vertical gradient of VA/Q is small, and these components of the VA and Q inhomogeneities contribute little to the width of the VA/Q distribution. The other components of Q inhomogeneity cause the additional variance of VA/Q in the supine dog.
Answer Set Programming for Qualitative Spatio-Temporal Reasoning: Methods and Experiments

We study the translation of reasoning problems involving qualitative spatio-temporal calculi into answer set programming (ASP). We present various alternative transformations and provide a qualitative comparison among them. An implementation of these transformations is provided by a tool that transforms problem instances specified in the language of the Generic Qualitative Reasoner (GQR) into ASP problems. Finally, we report on an experimental analysis of solving consistency problems for Allen's Interval Algebra and the Region Connection Calculus with eight base relations (RCC-8).
Distributed optimization in an energy-constrained network using a digital communication scheme

We consider a distributed optimization problem where n nodes, S<inf>l</inf>, l ∈ {1, …, n}, wish to minimize a common strongly convex function ƒ(x), x = [x<inf>1</inf>, … , x<inf>n</inf>]<sup>T</sup> , and suppose that node S<inf>l</inf> only has control of variable x<inf>l</inf>. The nodes locally update their respective variables and periodically exchange their values over noisy channels. Previous studies of this problem have mainly focused on the convergence issue and the analysis of convergence rate. In this work, we focus on the communication energy and study its impact on convergence. In particular, we study the minimum amount of communication energy required for nodes to obtain an ∈-minimizer of ƒ(x) in the mean square sense. In an earlier work, we considered analog communication schemes and proved that the communication energy must grow at the rate of Ω(∈<sup>−1</sup>) to obtain an ∈-minimizer of a convex quadratic function. In this paper, we consider digital communication schemes and propose a distributed algorithm which only requires communication energy of O ((log ∈<sup>−1</sup>)<sup>3</sup>) to obtain an ∈-minimizer of ƒ(x). Furthermore, the algorithm provided herein converges linearly. Thus, distributed optimization with digital communication schemes is significantly more energy efficient than with analog communication schemes.
The impact of constellation cardinality on Gaussian channel capacity

Denote by Cm(snr) the Gaussian channel capacity with signal-to-noise ratio snr and input cardinality m. We show that as m grows, Cm(snr) approaches C(snr) = 1 over 2 log(1 + snr) exponentially fast. Lower and upper bounds on the exponent are given as functions of snr. We propose a family of input constellations based on the roots of the Hermite polynomials which achieves exponential convergence.
FARE-CAFE: a database of functional and regulatory elements of cancer-associated fusion events

Chromosomal translocation (CT) is of enormous clinical interest because this disorder is associated with various major solid tumors and leukemia. A tumor-specific fusion gene event may occur when a translocation joins two separate genes. Currently, various CT databases provide information about fusion genes and their genomic elements. However, no database of the roles of fusion genes, in terms of essential functional and regulatory elements in oncogenesis, is available. FARE-CAFE is a unique combination of CTs, fusion proteins, protein domains, domain–domain interactions, protein–protein interactions, transcription factors and microRNAs, with subsequent experimental information, which cannot be found in any other CT database. Genomic DNA information including, for example, manually collected exact locations of the first and second break points, sequences and karyotypes of fusion genes are included. FARE-CAFE will substantially facilitate the cancer biologist’s mission of elucidating the pathogenesis of various types of cancer. This database will ultimately help to develop ‘novel’ therapeutic approaches. Database URL: http://ppi.bioinfo. asia.edu. tw/FARE-CAFE