Miracle-dz/UniFAR-FTUs huggingface dataset:
Sketch-Based Dance Choreography

Sketching and doodling are two techniques commonly used by choreographers to design a dance sequence. These sketches usually represent the trajectory of the dancer in the scene. A set of annotations can be used to differentiate the various dance movements. In order to have more control over the choreographed dance, a 3D animation is preferable. This paper presents a novel sketch-based approach to assist dance choreographers authoring dance motions in a 3D environment. The proposed approach allows a choreographer to story board a dance using stick figure sketches of a dancer. Inspired by traditional choreography, a set of simple annotations is introduced for ballet. These annotations help to retrieve and blend ballet 'mini-motions' in order to create a synthesized dance. To build the mini-motions, we have analyzed and processed several ballet movements available in a MoCap database.
An experience-based approach to software project management

The paper describes an experience-based model for software project management. In this approach, the focus is on concrete cases or episodes, rather than on basic principles. Past problem solving experience is recorded as a collection of solution instances indexed using a set of labels. When a new problem is presented, the case-based reasoner searches its case repository and retrieves an old record that closely matches the current context. In the proposed scheme, we employ fuzzy sets to represent case indices and fuzzy aggregation functions to evaluate cases. This provides a formal scheme to quantify the partial matches of a given problem with multiple cases in the database and to utilize these partial matches to compute an aggregated result. Cost estimation and risk assessment functions of software project management are covered here. The paper discusses the basic principles of case-based reasoning and provides a functional description of the proposed system with details of case representation and case evaluation strategies. <<ETX>>
Possible role of the JAK/STAT pathways in the regulation of T cell-interferon related genes in systemic lupus erythematosus

Changes in gene expression in CD3+ T cells associated with disease progression in systemic lupus erythematosus (SLE) patients were determined. The genes related to SLE disease-related activities were identified and their gene regulatory networks were investigated. Analyses of gene expression were performed by both DNA microarray and real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). The expression of certain genes including interferon (IFN) regulatory factor (IRF)-related genes, such as IFN-regulated, -related, and -signature genes was increased in the active phase of SLE. Pathway network analyses suggested that these IRF-related genes are regulated through the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway. JAK/STAT pathway-mediated regulation of IRF-related genes may have an important role in the disease activity of SLE. Inhibitors of JAK/STAT cascade may be useful as therapeutic agents.
Clinical Management Review: Orthopedic Rehabilitation for Standing and Walking in Selected Neuromuscular Diseases

Orthopedic rehabilitation can significantly extend the ability of patients with selected neuromuscular diseases to stand and walk. Surgery is designed to release contracture and correct deformity. Bracing stabilizes the lower extremities and provides torso-pelvic balance. Orthopedic and physiatric methods should be part of the aggressive rehabilitation of these patients.
Human genetics. Genetic influences on disease remain hidden.

The quest to find genes that strongly influence whether people will develop common diseases is turning out to be even more difficult than some researchers had expected. At the annual meeting of the American Society of Human Genetics, several huge DNA sequencing studies aimed at ferreting out genetic variants behind diseases such as diabetes and heart disease reported initial findings. This work shows that a popular hypothesis in the field—that the general population carries somewhat rare variants that greatly increase or decrease a person9s disease risk—is not yet panning out.
Listeria monocytogenes: bacteria antigua, desafío permanente

Este texto completo es la transcripcion editada de una conferencia dictada en reunion clinica del Departamento de Medicina, Hospital Clinico Universidad de Chile. La publicacion de estas actas ha sido posible gracias a una colaboracion editorial entre Medwave y el Departamento de Medicina del Hospital Clinico Universidad de Chile. El director del Departamento de Medicina es el Dr. Alejandro Cotera.
Cyberwar, Netwar, and the future of Cyberdefense

Over twenty years ago, Arquilla and Ronfeldt warned that both “Netwar” and “Cyberwar” were coming, and could impact the 21st Century security landscape as significantly as combined arms maneuver warfare had impacted the security landscape of the 20th. Since that time, the concept of “Cyberwar” has received great attention, while the parallel concept of “Netwar” has languished, even as its salience to global security has continued to grow. This paper suggests that just as Cyberdefense organizations have been required to confront Cyberwar, Netwar organizations, or Netwar-savvy Cyberdefense organizations, are increasingly needed to counter Netwar. Revisiting the Netwar concepts of the 1990s, it offers a 21st century Netwar definition; examines Netwar from a non-western perspective, exploring intersections between Netwar and Russian concepts of `Information-Psychological,' Chinese United Front Theory, and Chinese Legal Warfare, and concludes with thoughts on unique roles that today's Cyberdefence organizations may play in future Netwar conflict.
The Non-geek's Guide to the DAE Platform

The Document Analysis and Exploitation platform is a sophisticated technical environment that consists of a repository containing document images, implementations of document analysis algorithms, and the results of these algorithms when applied to data in the repository. The use of a web services model makes it possible to set up document analysis pipelines that form the basis for reproducible protocols. Since the platform keeps track of all intermediate results, it becomes an information resource for the analysis of experimental data. This paper provides a tutorial on how to get started using the platform. It covers the technical details needed to overcome the initial hurdles and have a productive experience with DAE.
Keyword Spotting in Handwritten Documents Using Projections of Oriented Gradients

In this paper, we present a novel approach for segmentation-based handwritten keyword spotting. The proposed approach relies upon the extraction of a simple yet efficient descriptor which is based on projections of oriented gradients. To this end, a global and a local word image descriptors, together with their combination, are proposed. Retrieval is performed using to the euclidean distance between the descriptors of a query image and the segmented word images. The proposed methods have been evaluated on the dataset of the ICFHR 2014 Competition on handwritten keyword spotting. Experimental results prove the efficiency of the proposed methods compared to several state-of-the-art techniques.
Semi-automatic Text and Graphics Extraction of Manga Using Eye Tracking Information

The popularity of storing, distributing and reading comic books electronically has made the task of comics analysis an interesting research problem. Different work have been carried out aiming at understanding their layout structure and the graphic content. However the results are still far from universally applicable, largely due to the huge variety in expression styles and page arrangement, especially in manga (Japanese comics). In this paper, we propose a comic image analysis approach using eye-tracking data recorded during manga reading sessions. As humans are extremely capable of interpreting the structured drawing content, and show different reading behaviors based on the nature of the content, their eye movements follow distinguishable patterns over text or graphic regions. Therefore, eye gaze data can add rich information to the understanding of the manga content. Experimental results show that the fixations and saccades indeed form consistent patterns among readers, and can be used for manga textual and graphical analysis.
Intelligent Component-Based Automation of Baggage Handling Systems With IEC 61499

Airport baggage handling is a field of automation systems that is currently dependent on centralized control systems and conventional automation programming techniques. In this and other areas of manufacturing and materials handling, these legacy automation technologies are increasingly limiting for the growing demand for systems that are reconfigurable, fault tolerant, and easy to maintain. IEC 61499 Function Blocks is an emerging architectural framework for the design of distributed industrial automation systems and their reusable components. A number of architectures have been suggested for multiagent and holonic control systems that incorporate function blocks. This paper presents a multiagent control approach for a baggage handling system (BHS) using IEC 61499 Function Blocks. In particular, it focuses on demonstrating a decentralized control system that is scalable, reconfigurable, and fault tolerant. The design follows the automation object approach, and produces a function block component representing a single section of conveyor. In accordance with holonic principles, this component is autonomous and collaborative, such that the structure and the behavior of a BHS can be entirely defined by the interconnection of these components within the function block design environment. Simulation is used to demonstrate the effectiveness of the agent-based control system and a utility is presented for real-time viewing of these systems. Tests on a physical conveyor test system demonstrated deployment to embedded control hardware.
Nutritional aspects of feeding in the United States navy.

In approaching the topic of this paper, may I remind the reader that there is no more important single factor in building and maintaining high morale and keenness in naval personnel than an acceptable diet of high nutritive value. In fact, the import of optimum nutrition, in relation to physical fitness, can hardly be overemphasized. Modern naval warfare presents enormously increased hazards and a continuous state of tension, increased tremendously by the advent of air power, a heavy toll being laid on the physical and nervous stamina of the operating personnel. Not only must the food supply be adequate in quantity, but the variety must satisfy the requirements of a well balanced ration. This poses a difficult problem which can be met only by careful preplanning and skilful supervision. The administrative responsibility for the subsistence activities of the Navy lies in the Supply Corps, which procures, stores, issues, prepares and
MARTE to ΠSDF transformation for data-intensive applications analysis

This paper proposes and validates a new methodology to facilitate the analysis of modern data-intensive applications. A major part of handling the processing needs of these applications consists in using the appropriate Model-of-Computation (MoC) which guarantees accurate performance estimations. Our methodology introduces one major contribution that facilitates the analysis step in the co-design flow. It is based on an intermediate level of abstraction implementing the Parameterized and Interfaced Synchronous Dataflow (ΠSDF) semantics. In the proposed methodology, a system designer models the embedded system using the standardised Modeling and Analysis of Real-Time and Embedded Systems (MARTE) profile. High-level models are then refined towards intermediate level models by following the Model-Driven Engineering (MDE) transformation paradigm. The model-to-model transformation permitting to reach the ΠSDF level starting from a MARTE-compliant model is detailed and validated in this paper. It is shown to facilitate system analysis.
Gender Differences in the Relationship Between Quadriceps Work and Fatigue During High‐Intensity Exercise

The purpose of this study was to examine gender differences in peak quadriceps torque, the rate of torque decline, and the relationship between these 2 variables during high-intensity isokinetic exercise. Subjects for this study included 16 healthy men and 16 healthy women. Following a dynamic warm-up period, subjects performed 30 reciprocal, concentric maximal knee extension and flexion contractions at a preset angular velocity of 180 deg·sec−1 on the Biodex System II Isokinetic Dynamometer. Values for quadriceps work (N·m) were calculated for each repetition between a windowed range of motion of 10° and 60° of flexion. Values for quadriceps work were then converted to a ratio of individual body mass (N·m·kg−1). The rate of quadriceps fatigue was calculated as the decline in work output by the linear slope (b) across the 30 repetitions. This value was then assessed for gender differences with an independent i-test. The relationship between peak quadriceps work and the associated slope was examined by regression analysis for men and women, separately, and differences in these relationships were calculated using Fisher's Z-transformation. The results demonstrated significantly higher peak quadriceps work and rate of fatigue (slope) in men as compared with women (p < 0.05). The relationship between peak quadriceps work and the rate of fatigue was demonstrated to be significant in both sexes (men: r = 0.86; women: r = 0.69), and was statistically higher in men than in women. The findings from this study suggest that the physiological characteristics of quadriceps in men may be more conducive for high-intensity short-term work output.
An MMSE Estimator for Speech Enhancement Under a Combined Stochastic–Deterministic Speech Model

Although many discrete Fourier transform (DFT) domain-based speech enhancement methods rely on stochastic models to derive clean speech estimators, like the Gaussian and Laplace distribution, certain speech sounds clearly show a more deterministic character. In this paper, we study the use of a deterministic model in combination with the well-known stochastic models for speech enhancement. We derive a minimum mean-square error (MMSE) estimator under a combined stochastic-deterministic speech model with speech presence uncertainty and show that for different distributions of the DFT coefficients the combined stochastic-deterministic speech model leads to improved performance of approximately 0.8 dB segmental signal-to-noise ratio (SNR) over the use of a stochastic model alone. Evaluation with perceptual evaluation of speech quality (PESQ) shows performance improvements of approximately 0.15 on an MOS scale
Time–Frequency Cepstral Features and Heteroscedastic Linear Discriminant Analysis for Language Recognition

The shifted delta cepstrum (SDC) is a widely used feature extraction for language recognition (LRE). With a high context width due to incorporation of multiple frames, SDC outperforms traditional delta and acceleration feature vectors. However, it also introduces correlation into the concatenated feature vector, which increases redundancy and may degrade the performance of backend classifiers. In this paper, we first propose a time-frequency cepstral (TFC) feature vector, which is obtained by performing a temporal discrete cosine transform (DCT) on the cepstrum matrix and selecting the transformed elements in a zigzag scan order. Beyond this, we increase discriminability through a heteroscedastic linear discriminant analysis (HLDA) on the full cepstrum matrix. By utilizing block diagonal matrix constraints, the large HLDA problem is then reduced to several smaller HLDA problems, creating a block diagonal HLDA (BDHLDA) algorithm which has much lower computational complexity. The BDHLDA method is finally extended to the GMM domain, using the simpler TFC features during re-estimation to provide significantly improved computation speed. Experiments on NIST 2003 and 2007 LRE evaluation corpora show that TFC is more effective than SDC, and that the GMM-based BDHLDA results in lower equal error rate (EER) and minimum average cost (Cavg) than either TFC or SDC approaches.
A Cluster Analysis of Pediatric Cancer Incidence Rates in Florida: 2000–2010

This study uses disease surveillance cluster analysis methods to identify clusters for the three most common pediatric cancers in Florida (brain tumors, leukemia, lymphoma). In addition to a univariate purely spatial analysis, a space–time analysis is done, followed by a nonparametric permutation test for space–time interaction. This is followed by a multivariate spatial analysis for the three pediatric cancer types together. The main findings include a significant spatial cluster for each of the three cancer types covered in this study, in addition to identifying two significant clusters for all pediatric cancer types combined.
An open interface for probabilistic models of text

Summary form only given. An application program interface (API) for meddling sequential text is described. The API is intended to shield the user from details of the modelling and probability estimation process. This should enable different implementations of models to be replaced transparently in application programs. The motivation for this API is work on the use of textual models for applications in addition to strict data compression. The API is probabilistic, that is, it supplies the probability of the next symbol in the sequence. It is general enough to deal accurately with models that include escapes for probabilities. The concepts abstracted by the API are explained together with details of the API calls. Such predictive models can be used for a number of applications other than compression. Users of the models do not want to be concerned about the details either of the implementation of the models or how they were trained and the sources of the training text. The problem considered is how to permit code for different models and actual trained models themselves to be interchanged easily between users. The fundamental idea is that it should be possible to write application programs independent of the details of particular modelling code, that it should be possible to implement different modelling code independent of the various applications, and that it should be possible to easily exchange different pre-trained models between users. It is hoped that this independence will foster the exchange and use of high-performance modelling code, the construction of sophisticated adaptive systems based on the best available models, and the proliferation and provision of high-quality models of standard text types such as English or other natural languages, and easy comparison of different modelling techniques.
Packet Loss Concealment Based on Deep Neural Networks for Digital Speech Transmission

In this paper, we propose the regression-based packet loss concealment (PLC) for digital speech transmission by using deep neural networks (DNNs) with a multiple-layer deep architecture. For the DNN training, log-power spectra and phases are employed as features in the input layer for the large training set, which ensures non-linear mapping the frames from the last correctly received frame to the missing frame. Once the training is accomplished by the restricted Boltzmann machine (RBM)-based pre-training to initialize the DNN, minimum mean square error (MMSE)-based fine tuning is then performed based on the back-propagation algorithm. In the reconstruction stage, the trained DNN model is fed with the features of the previous frames in order to estimate the log-power spectra and phases of the missing frames. Reconstruction is further improved by using the cross-fading technique to mitigate discontinuity between the reconstruction signal and good frame signal in the time-domain. To demonstrate the performance of the proposed algorithm, hidden Markov model (HMM)-based PLC algorithm and the PLC algorithm standardized in adaptive multi-rate wideband (AMR-WB) Appendix I were used for comparison. The experimental results show that the proposed approach provides better speech quality and speech recognition accuracy than the conventional approaches.
Evaluation of polyomavirus BK reactivation in lupus patients who underwent kidney transplantation

Background. A pathogenic role for polyomavirus BK in systemic lupus erythematosus (SLE) has been proposed, however no study evaluated the occurrence of BK replication in renal transplant recipients according to the underlying disease leading to transplantation and its potential impact. Methods. The occurrence of BK reactivation was serially evaluated in 468 renal transplant recipients, including 11 patients with SLE as underlying disease (overall, 2370 serum and 2370 urine specimens; 65 from SLE patients). Results. Considering the overall occurrence of viral reactivation (viremia and/or viruria), 26/65 (40%) specimens were positive in four SLE patients (36.3%) versus 331/2143 (15.4%) in 130/227 (57.3%) non-SLE patients. A patient transplanted for class III lupus nephritis evidenced sustained BK viremia and viruria (with viremia values potentially indicative of polyomavirus-associated nephropathy) in the absence of clinical features of renal dysfunction or recurrence of lupus nephritis. Conclusions. Further studies on larger populations and for a longer follow-up should be required to evaluate the impact of BKV reactivation in renal transplant patients with SLE as underlying disease, as well as the potential therapeutic implications.
Vitamin A deficiency and maternal‐infant transmission of HIV in two metropolitan areas in the United States

Objective:To determine whether vitamin A deficiency is associated with maternal-infant HIV transmission among HIV-infected pregnant women in two United States cities. Methods:Third trimester serum vitamin A levels were evaluated using high-performance liquid chromatography in 133 HIV-infected women who delivered livebirths during May 1986 to May 1994 and whose infants had known HIV infection status. Results:Sixteen per cent (seven out of 44) of the transmitting mothers and 6% (five out of 89) of the non-transmitting mothers had severe vitamin A deficiency (<0.70 μmol/l; P = 0.05). Maternal-infant transmission was also associated with prematurity <37 weeks gestation (P = 0.02), and Cesarean section delivery (P = 0.04), CD4 percentage (P = 0.03) and marginally associated with duration of membrane rupture of ≥ 4 h (P = 0.06) by univariate analysis. In a multivariate logistic regression model, severe vitamin A deficiency [adjusted odds ratio (AOR), 5.05; 95% confidence interval (CI), 1.20–21.24], Cesarean section delivery (AOR, 3.75; 95% CI, 1.10–12.87), and prematurity (AOR, 2.25; 95% CI, 1.22–4.13) were associated with transmission after adjusting for CD4+ percentage, and duration of membrane rupture. Conclusion:Increased risk of maternal-infant transmission was associated with severe vitamin A deficiency among non-breastfeeding women in these cohorts from the United States.
The forgotten malaria.

Malaria caused by the parasite Plasmodium vivax has long been an afterthought in both public health plans and in research funding. One of the five Plasmodium species that cause malaria in humans, P. vivax is often overshadowed by its more lethal cousin, P. falciparum . Now, new recognition of the severe disease that P. vivax can cause and its ability to elude many of the standard malaria control measures have prompted researchers and policymakers to give the parasite new attention. The parasite has a number of tricks, however, that make it a formidable foe.