Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Musical Time Information from Performed MIDI Files

Even though originally developed for exchanging control commands between electronic instruments, MIDI has been used as quasi standard for encoding and storing scorerelated parameters. MIDI allows for representing musical time information as specified by sheet music as well as physical time information that reflects performance aspects. However, in many of the available MIDI files the musical beat and tempo information is set to a preset value with no relation to the actual music content. In this paper, we introduce a procedure to determine the musical beat grid from a given performed MIDI file. As one main contribution, we show how the global estimate of the time signature can be used to correct local errors in the pulse grid estimation. Different to MIDI quantization, where one tries to map MIDI note onsets onto a given musical pulse grid, our goal is to actually estimate such a grid. In this sense, our procedure can be used in combination with existing MIDI quantization procedures to convert performed MIDI files into semantically enriched score-like MIDI files.
REGRESSION TRAINING Energy Variation Audio Short-Term Event Repetition Harmonic Variation Spectral Balance Variation Annotated Perceptual Tempo GMM feature + tempo + class Estimated Perceptual Tempo xcorr xcorr xcorr

This extended abstract details a submission to the Music Information Retrieval Evaluation eXchange (MIREX) 2012 for the Audio Tempo Estimation task. We submitted a prototype software 1 corresponding to the GMMRegression method we recently proposed in [2] for the estimation of perceptual tempo. We briefly summarize this new method here. 1. GMM-REGRESSION FOR PERCEPTUAL TEMPO For the estimation of the perceptual tempo, we start from a set of assumptions. For each of these assumptions we create a related audio feature. We assume that the perception of tempo is related to the rate of variation of four musical attributes: −1− the rate of variation of energy (as did the previous works) but also −2− the rate of variation of harmonic content, −3− the rate of variation of spectral balance (the distribution in high or low frequency of the energy) and −4− the rate of short-term-event-repetitions. We assume that a track with a rapid chord changes, rapid spectral-balance changes or rapid short-term repetitions will be perceived as fast even if the tempo of the sequencer was set to slow. We then create a model to find the relationship between the perceptual tempo, the perceptual tempo class and the four feature-sets. This model is then used to predict the perceptual tempo given the audio features. The model and the prediction is done using a technique borrowed from speech processing: GMM-Regression [1]. In [1], a GMM model is trained to learn the relationship between pitch and spectral envelope. The model is then used to predict the most-likely pitch given an observed spectral envelope. This is done using a regression over the values of the most-likely components of the GMM. The same method is applied here to predict the most-likely perceptual tempo given the audio features. The feature extraction, training and regression processes of our method are illustrated in Figure 1. Details of the method can be found in [2]. 1 For the MATLAB c ©envirronment This document is licensed under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 License. http://creativecommons.org/licenses/by-nc-sa/3.0/ c © 2010 The Authors. REGRESSION TRAINING
Covariance Plasticity and Regulated Criticality

We propose that a regulation mechanism based on Hebbian covariance plasticity may cause the brain to operate near criticality. We analyze the effect of such a regulation on the dynamics of a network with excitatory and inhibitory neurons and uniform connectivity within and across the two populations. We show that, under broad conditions, the system converges to a critical state lying at the common boundary of three regions in parameter space; these correspond to three modes of behavior: high activity, low activity, oscillation.
Function-Based Engineering Product Retrieval : Progress Report

This paper describes work in progress to develop an information broker of engineering parts that enables the user to describe his/her goal in terms of the function to be achieved. The desired function is described in the form of "to do X" with any number of qualifying terms. The system assists the user in incremental refinement of search goals. It uses explicit ontologies of functional terms and a knowledge of typical functions in order to map from the given functional specification to actual products.
An OpenGL Application for Industrial Robots Simulation

This paper presents a Visual C++ and OpenGL application for 3D simulation of the serial industrial robots. To develop this application we started from the forward kinematics of the robot taken into consideration. The functions implemented in the source code are able to calculate the position and orientation of each robot joint, including the position and orientation of the robot gripper. With the help of the OpenGL functions, the application is able to draw and simulate the 3D kinematic scheme of the robot. In addition, the application has a calculus module where the gripper position can be determined using particular values for the robot joints positions or orientations
Balkanization and pauperization: Analysis of media capture of public service broadcasters in the Western Balkans

This article provides an in-depth analysis of public service broadcasters in seven countries of the Western Balkans from the perspective of capture by political and market forces. A lack of editorial independence, reflected in politically biased, pro-government news content, is the main problem of public service broadcasting in the region. Another factor is the commercialization of programs, reflected in the neglect of public interest content in favor of entertainment formats, and the introduction of sponsored content and product placement. Financial difficulties, small fragmented markets, minor languages, weak economies, market pressures from commercial broadcasters, inefficient license fee collection, pressure and interference from political elites, as well as characteristics of local political and journalistic culture are among the reasons that public service broadcasters in these post-communist countries currently display similar characteristics.
For Better or Worse? Coregulation of Couples' Cortisol Levels and Mood States Defining Coregulation Cohabiting Partners May Influence Each Other's Moods and Physiology; for Example, Mcclintock (1971) Has Reported That Roommates' Men- Strual Cycles Become Synchronized over Time. Other Researchers

Although a majority of adults live with a close relationship partner, little is known about whether and how partners' momentary affect and physiology covary, or " coregulate. " This study used a dyadic multilevel modeling approach to explore the coregulation of spouses' mood states and cortisol levels in 30 married couples who sampled saliva and reported on mood states 4 times per day for 3 days. For both husbands and wives, own cortisol level was positively associated with partner's cortisol level, even after sampling time was controlled. For wives, marital satisfaction weakened the strength of this effect. Partner's negative mood was positively associated with own negative mood for both husbands and wives. Marital satisfaction fully moderated this effect, reducing the strength of the association between one's own and one's partner's negative mood states. Spouses' positive moods were not correlated. As expected, within-couple coregulation coefficients were stronger when mood and cortisol were sampled in the early morning and evening, when spouses were together at home, than during the workday. The results suggest that spouses' fluctuations in negative mood and cortisol levels are linked over several days and that marital satisfaction may buffer spouses from their partners' negative mood or stress state. Psychology has traditionally focused on the individual as the unit of analysis— but humans exist within relationships and are therefore reactive and responsive to inputs from friends, partners, and children. Social connectedness can affect both mental and physical health; for example, social network size and the perceived availability of social support have been associated with longevity, physical symptoms, and vulnerability to ailments ranging from the common cold to cancer (Uchino, Cacioppo, & Kiecolt-Glaser, 1996). For many adults, marriage constitutes their most central and enduring social relationship and has been linked with greater life satisfaction, lower rates of depression, and a reduced risk of all-cause mortality. At the same time, poor marital quality may compromise health, particularly for women (cf. Despite the established importance of the marital context for individual health, little is known about the interplay of mood and physiology between spouses. Do partners " coregulate, " or show synchrony, in their everyday physiological and affective states? When couples vow to stay together " for better or worse, " do they also expect to share in each other's momentary ups and downs? Additionally, how is coregulation linked with relationship func-tioning? Considering that most adults, in the United States and worldwide, …
GENERALIZATIONS OF THE DENNIS-MORÉ THEOREM II 1

This paper is a continuation of our previous paper [3] were we presented generalizations of the Dennis-Moré theorem to characterize q-superliner convergences of quasi-Newton methods for solving equations and variational inequalities in Banach spaces. Here we prove Dennis-Moré type theorems for inexact quasi-Newton methods applied to variational inequalities in finite dimensions. We first consider variational inequalities for functions that are merely Lipschitz continuous. Then we present a parallel result for semismooth functions. An erratum to a theorem in our previous paper is also given.
Candida albicans Induces Metabolic Reprogramming in Human NK Cells and Responds to Perforin with a Zinc Depletion Response

As part of the innate immune system, natural killer (NK) cells are directly involved in the response to fungal infections. Perforin has been identified as the major effector molecule acting against many fungal pathogens. While several studies have shown that perforin mediated fungicidal effects can contribute to fungal clearance, neither the activation of NK cells by fungal pathogens nor the effects of perforin on fungal cells are well-understood. In a dual approach, we have studied the global gene expression pattern of primary and cytokine activated NK cells after co-incubation with Candida albicans and the transcriptomic adaptation of C. albicans to perforin exposure. NK cells responded to the fungal pathogen with an up-regulation of genes involved in immune signaling and release of cytokines. Furthermore, we observed a pronounced increase of genes involved in glycolysis and glycolysis inhibitor 2-deoxy-D-glucose impaired C. albicans induced NK cell activation. This strongly indicates that metabolic adaptation is a major part of the NK cell response to C. albicans infections. In the fungal pathogen, perforin induced a strong up-regulation of several fungal genes involved in the zinc depletion response, such as PRA1 and ZRT1. These data suggest that fungal zinc homeostasis is linked to the reaction to perforin secreted by NK cells. However, deletion mutants in PRA1 and ZRT1 did not show altered susceptibility to perforin.
Classification of Heart Disease Using Support Vector Machine

Diabetes mellitus is one of the most serious health challenges in both developing and developed countries. According to the International Diabetes Federation, there are 285 million diabetic people worldwide. This total is expected to rise to 380 million within 20 years. Due to its importance, a design of classifier for the detection of Diabetes disease with optimal cost and better performance is the need of the age. The Pima Indian diabetic database at the UCI machine learning laboratory has become a standard for testing data mining algorithms to see their prediction accuracy in diabetes data classification. The proposed method uses Support Vector Machine (SVM), a machine learning method as the classifier for diagnosis of diabetes. The machine learning method focus on classifying diabetes disease from high dimensional medical dataset. The experimental results obtained show that support vector machine can be successfully used for diagnosing diabetes disease.
Development of a Diagnostic Expert System for Autism Disorder-PCADEX

Autism is a neurodevelopment, psychological and behavioral disorder. It is a childhood disorder and diagnosing autism is a major issue as its symptoms can easily be confused with those of mental retardness. Successful intervention requires correct diagnosis. As the major issue faced in Pakistan is of proper diagnosis of the autistic children who are mostly misdiagnosed as mentally retarded and thus are unable to get the required treatment which can enable those children to live like a normal child. Despite autism being a major area of concern worldwide, no remarkable work is done in Pakistan as yet. The diagnoses of autism currently being done in Pakistan is based on manual procedures. It is the need of time to have automated systems for diagnosing these disorders instead of doing them manually. Therefore, we developed an expert system, on the requirement of the clinical psychologist, which can act intelligently and correctly diagnoses the subject on the basis of the characteristics/symptoms. It is an interview based system which works on the basis of the behavioral characteristics of autism that are incorporated into the system in the form of rules and facts. Rules and facts make the knowledge base of the system from which the decision is extracted by the inference engine depending on the user’s data input. The result is generated on its basis that categorizes the subject as having autism or not and classifies the level of autism present. This expert system will facilitate the clinicians and the related professionals in diagnosing this disorder. And will also open new horizons for the further developments for autism in Pakistan.
Prevalence of Sleep Disorders and their Effects on Sleep Quality in Epileptic Patients

Introduction Epilepsy is a complex pervasive neurobehavioral and social condition accompanied by a wide range of comorbid conditions that can adversely affect the quality of life of patients. Sleep complaints are common among patients with epilepsy. The aim of this study was to assess the prevalence of subjective sleep disturbances and its effects on sleep quality in epileptic patients. Methods In this cross-sectional study, 152 consecutive epileptic patients and 152 controls were interviewed. We used Epworth Sleepiness Scale, Insomnia Severity Index, Berlin Questionnaire and Pittsburg Sleep Quality Index to measure excessive daytime sleepiness, insomnia, obstructive sleep apnea and sleep quality. R estless leg syndrome was diagnosed using three questions. Results The age, gender and average total sleep time was similar in patients and control group. The frequency of excessive sleepiness scale and subjective complaint of sleep maintenance was higher in epileptic patients than control group (P<0.05). The symptoms of restless leg syndrome were reported by 32.3% of patients and 11.8% of controls (P<0.05). Discussion Daytime sleepiness, difficulty in sleep maintenance, poor sleep quality and RLS appear to be common in patients with epilepsy. Further confirmatory studies are needed using objective sleep studies to detect underlying mechanisms of sleep disorders in these patients.
The impact of text valence, star rating and rated usefulness in online reviews

ABSTRACT The influence of text valence, star rating and rated usefulness of online reviews on review readers’ impression of the review and their positive word-of-mouth intention is tested in an experimental study (n = 431). In addition, we investigate the moderating role of review readers’ product category involvement and susceptibility to interpersonal influence on the effect of the three review components. The influence of review text valence on evaluative responses is stronger for more highly involved people and for people who are more susceptible to interpersonal influence. The influence of rated review usefulness on review impression is marginally stronger for people who are more susceptible to interpersonal influence. Star ratings do not influence evaluative responses, and their effect is not moderated by either involvement or susceptibility.
Overexpression of the KdpF Membrane Peptide in Mycobacterium bovis BCG Results in Reduced Intramacrophage Growth and Altered Cording Morphology

Membrane peptides appear as an emerging class of regulatory molecules in bacteria, which can interact with membrane proteins, such as sensor kinases. To date, regulatory membrane peptides have been completely overlooked in mycobacteria. The 30 amino-acid-long KdpF peptide, which is co-transcribed with kdpABC genes and regulated by the KdpDE two-component system, is supposed to stabilize the KdpABC potassium transporter complex but may also exhibit unsuspected regulatory function(s) towards the KdpD sensor kinase. Herein, we showed by quantitative RT-PCR that the Mycobacterium bovis BCG kdpAB and kdpDE genes clusters are differentially induced in potassium-deprived broth medium or within infected macrophages. We have overexpressed the kdpF gene in M. bovis BCG to investigate its possible regulatory role and effect on mycobacterial virulence. Our results indicate that KdpF does not play a critical regulatory role on kdp genes expression despite the fact that KdpF interacts with the KdpD sensor kinase in a bacterial two-hybrid assay. However, overexpression of kdpF results in a significant reduction of M. bovis BCG growth in both murine and human primary macrophages, and is associated with a strong alteration of colonial morphology and impaired cording formation. To identify novel KdpF interactants, a mycobacterial library was screened using KdpF as bait in the bacterial two-hybrid system. This allowed us to identify members of the MmpL family of membrane proteins, known to participate in the biosynthesis/transport of various cell wall lipids, thus highlighting a possible link between KdpF and cell wall lipid metabolism. Taken together, these data suggest that KdpF overexpression reduces intramacrophage growth which may result from alteration of the mycobacterial cell wall.
A Convergent Review of Interventions for School-Age Children With Autism Spectrum Disorder

A review and comparative analysis of single-subject research to identify applied behavior analysis–based therapy components targeting language, communication, and social skills for school-age children (ages 6–17) diagnosed with Autism Spectrum Disorder (ASD) was conducted. The National Standards Project and the National Professional Development Center on ASD have conducted similar reviews with diverse methods to identify effective interventions. Both organizations, as well as Horner et al. (2005), have established rigorous standards to determine empirically supported interventions. In the current review, 48 data-based articles were identified and scored for quality by independent reviewers according to 21 indicators (Horner et al., 2005) and organized into categories according to established treatment classifications, and convergent results across all reviews are reported. Discussion and recommendations for improving the identification of empirically supported practices for school-age children with ASD are proposed for services and policy.
Adaptive Run-time Overhead Adjustments for Optimizing Multiple Continuous Query Processing *

The time-varying characteristics of infinite data streams require continuous queries to be adaptively processed. The order in which multiple join operations are evaluated has serious consequences for the algorithm performance because the selectivity of each join operation can differ significantly from the selectivity of the other operations. The evaluation order may be effectively determined using the k-EGA and A-SEGO schemes, as proposed in previous studies. These methods optimize target continuous queries by monitoring a set of their promising subplans simultaneously. Each scheme also employs a user-defined cost-bound parameter for controlling the number of monitored subplans. A more optimized global plan may be generated by using a more highly configured cost-bound parameter. However, this approach can increase the overhead associated with monitoring the subplans. This paper proposes a new scheme, Adaptive Run-time Overhead Adjustment (AROA), which provides a novel method for adaptively determining the value of a cost-bound parameter based on the system environment. Unlike the previously described A-SEGO scheme, the scheme proposed here automatically selects the cost-bound parameter to reflect the system workloads (e.g., the input tuple rate, and other parameters). This method not only augments the probability of generating an optimized execution plan, it reduces the run-time delay caused by the optimization process. Experimental verification of the proposed scheme AROA demonstrated that AROA outperforms the previous schemes.
Large Scale Near-Duplicate Celebrity Web Images Retrieval Using Visual and Textual Features

Near-duplicate image retrieval is a classical research problem in computer vision toward many applications such as image annotation and content-based image retrieval. On the web, near-duplication is more prevalent in queries for celebrities and historical figures which are of particular interest to the end users. Existing methods such as bag-of-visual-words (BoVW) solve this problem mainly by exploiting purely visual features. To overcome this limitation, this paper proposes a novel text-based data-driven reranking framework, which utilizes textual features and is combined with state-of-art BoVW schemes. Under this framework, the input of the retrieval procedure is still only a query image. To verify the proposed approach, a dataset of 2 million images of 1089 different celebrities together with their accompanying texts is constructed. In addition, we comprehensively analyze the different categories of near duplication observed in our constructed dataset. Experimental results on this dataset show that the proposed framework can achieve higher mean average precision (mAP) with an improvement of 21% on average in comparison with the approaches based only on visual features, while does not notably prolong the retrieval time.
Acupuncture as anticancer treatment?

The mystery of Traditional Chinese Medicine has been attracting people for years. Acupuncture, ranked among the most common services of Complementary and Alternative Medicine, has recently gained a lot of interest in the scientific world. Contemporary researchers have been continuously trying to shed light on its possible mechanism of action in human organism. Numerous studies pertaining to acupuncture’s application in cancer symptoms or treatment-related side effects management have already been published. Moreover, since the modern idea of acupuncture’s immunomodulating effect seems to be promising, scientists have propounded a concept of its potential application as part of direct anti-tumor therapy. In our previous study we summarized possible use of acupuncture in management of cancer symptoms and treatment-related ailments, such as chemotherapy-induced nausea and vomiting, pain, xerostomia, vasomotor symptoms, neutropenia, fatigue, anxiety, insomnia, lymphoedema after mastectomy and peripheral neuropathy. This article reviews the studies concerning acupuncture as a possible tool in modern anticancer treatment.