Miracle-dz/UniFAR-FTUs huggingface dataset:
LICHENOID DERMATITIS DUE TO CHLOROQUINE.

MOST dermatologists in this country now use chloroquine in preference to mepacrine in the treatment of lupus erythematosus and light sensitivity. Chloroquine does not stain the skin, the results are just as good, if not better, than mepacrine and the toxic symptoms are of less severity, especially the absence of severe lichenoid eruptions. I have been unable to find in this Journal any mention of lichenoid eruptions due to chloroquine, although three short references were found in the American literature. In the Year Book of Dermatology 1954r-55 the editors comment that " one of our patients also developed a patchy lichenoid eruption on the extremities due to chloroquine ". Goldman et al., (1953) listing the various toxic manifestations of chloroquine, state that " rarely lichenoid dermatitis may occur " ; and Ahdng et al., (1948) in their studies on the toxic manifestations of chloroquine, had two patients who developed lichen planus eruptions after taking 0-5g. chloroquine daily for one year. It is interesting that Samuel Ayres III and Samuel Ayres (Jnr.) treated various dermatoses with chloroquine, including seven patients with lichen planus with " satisfactory results in five ".
Modeling and Implementing Ontology for Managing Learners’ Profiles

This paper presents an issue that is important to consider when developing a learning environment whose field is constantly evolving mainly in terms of the use of training platforms. Research in this field has enabled the successful use of information technologies for the benefit of human learning, while placing the learner at the heart of pedagogic situations. It is also an environment that integrates human agents (tutors, learners) and artificial (computers) and allows them to interact locally or through computer networks, as well as conditions for accessing local or distributed training resources. Moreover, several computing environments for human learning (CEHL) platforms are available on the web for free access. These platforms are environments that offer a learner a multitude of courses in various formats in order to satisfy the learner’s desire to learn. Several CEHL platforms are available on the web for free access. But learning itself is not enough and that is why a new generation of advanced learning systems that integrate new pedagogical approaches giving the learner an active role to learn and acquire knowledge has emerged by offering more Interactivity and incorporating a more learner-centered vision. These new generations of advanced learning systems adapt to learners and their profiles by taking into account their cognitive, intellectual and motivational characteristics. An adaptation that cannot be achieved without the complicity of ontological engineering, which plays a very important role in the sharing of knowledge between humans and computers, and between computers and sharing, and reuse of concepts through computational semantics. By the same way, this paper aims at creating a process of modeling and managing profiles of learners based on ontology whatever the learning situation may be. This management process is implemented in computer’s environment based on the learner’s ontology that supports the learner by detecting the gaps in several factors in order to improve them and adapt the pedagogical content to the learner’s profile.
Time varying channel estimation for DSTC-based relay networks

In this paper, we examine the channel estimation in an amplify-and-forward (AF) one-way relay network (OWRN) under time selective flat fading scenario, where the distributed space-time coding (DSTC) is adopted at relay nodes. Our target is to estimate and track the individual channels of each relay hop instead of the composite channels. To reduce the number of the channel parameters to be estimated, we apply the polynomial basis-expansion-model (P-BEM) and convert the problem to estimating the channel coefficient-vectors (called in-BEM-CVs) of each relay hop. With the aid of the autoregressive (AR) model, we formulate the dynamic state space for the in-BEM-CV estimation. Specifically, we adopt the unscented Kalman filter (UKF) to track the in-BEM-CV dynamic variations in an forward manner, and utilize the unscented Rauch-Tung-Striebel smoother (URTSS) to smooth the UKF's estimations in an backward manner. Finally, numerical results are provided to corroborate the proposed studies.
Chromatin programming by developmentally regulated transcription factors: lessons from the study of haematopoietic stem cell specification and differentiation

Although the body plan of individuals is encoded in their genomes, each cell type expresses a different gene expression programme and therefore has access to only a subset of this information. Alterations to gene expression programmes are the underlying basis for the differentiation of multiple cell types and are driven by tissue‐specific transcription factors (TFs) that interact with the epigenetic regulatory machinery to programme the chromatin landscape into transcriptionally active and inactive states. The haematopoietic system has long served as a paradigm for studying the molecular principles that regulate gene expression in development. In this review article, we summarize the current knowledge on the mechanism of action of TFs regulating haematopoietic stem cell specification and differentiation, and place this information into the context of general principles governing development.
Tight Integration of Spatial and Spectral Features for BSS with Deep Clustering Embeddings

Recent advances in discriminatively trained mask estimation networks to extract a single source utilizing beamforming techniques demonstrate, that the integration of statistical models and deep neural networks (DNNs) are a promising approach for robust automatic speech recognition (ASR) applications. In this contribution we demonstrate how discriminatively trained embeddings on spectral features can be tightly integrated into statistical model-based source separation to separate and transcribe overlapping speech. Good generalization to unseen spatial configurations is achieved by estimating a statistical model at test time, while still leveraging discriminative training of deep clustering embeddings on a separate training set. We formulate an expectation maximization (EM) algorithm which jointly estimates a model for deep clustering embeddings and complex-valued spatial observations in the short time Fourier transform (STFT) domain at test time. Extensive simulations confirm, that the integrated model outperforms (a) a deep clustering model with a subsequent beamforming step and (b) an EM-based model with a beamforming step alone in terms of signal to distortion ratio (SDR) and perceptually motivated metric (PESQ) gains. ASR results on a reverberated dataset further show, that the aforementioned gains translate to reduced word error rates (WERs) even in reverberant environments.
Breast Metastasis from Renal Cell Carcinoma: Rare Initial Presentation of Disease Recurrence after 5 Years

Metastasis to the breast from extra-mammary tumors is rare with only a few sporadic cases reported. We present a 58-year-old female patient diagnosed with renal cell carcinoma. Five years ago she had a radical nephrectomy and was free of disease, then discovered solitary breast mass following self-examination. The patient presented to the breast clinic for evaluation whereupon the breast mass was identified on physical and radiological examinations. Fine needle aspiration was diagnostic of metastatic renal cell carcinoma and subsequent imaging studies demonstrated multiple pulmonary deposits and recurrent renal mass in the tumor bed of the diseased site. In a multidisciplinary clinic, the patient was elected for excision biopsy followed by systemic tyrosine kinase inhibitor therapy. Six months later she had brain metastasis and received whole brain irradiation followed by palliative therapy. We are presenting this rare case with the aim of increasing awareness of breast secondaries.
In vitro activity of moxalactam and mecillinam, singly and in combination, against multi-drug-resistant Enterobacteriaceae and Pseudomonas species

The in vitro interaction of moxalactam and mecillinam against multi-drug-resistant gram-negative enteric bacilli was studied by checkerboard microdilution susceptibility tests and by killing curve kinetics. Against Enterobacteriaceae, the combination was unpredictable; the frequencies of synergy, indifference, and antagonism were 11, 76, and 13%, respectively. Against Pseudomonas sp. , the two drugs were consistently indifferent. Overall, the combination of moxalactam and mecillinam was no more active than moxalactam alone.
On the Bayesian Analysis of Ring‐Recovery Data

Summary. Vounatsou and Smith (1995, Biometrics51, 687–708) describe the modern Bayesian analysis of ring‐recovery data. Here we discuss and extend their work. We draw different conclusions from two major data analyses. We emphasize the extreme sensitivity of certain parameter estimates to the choice of prior distribution and conclude that naive use of Bayesian methods in this area can be misleading. Additionally, we explain the discrepancy between the Bayesian and classical analyses when the likelihood surface has a flat ridge. In this case, when there is no unique maximum likelihood estimate, the Bayesian estimators are remarkably precise.
Deep Analysis of a Basic Traffic Model

In this article we analyze the basic elements to be considered in vehicular traﬃc by using modeling based on agents. One of the most important activities of a traﬃc engineer is to measure the capacity of a road in order to optimize the road infrastructure of a city. The incorporation of the microscopic and macroscopic characteristics of vehicular traﬃc ﬂows are the key elements for developing a realistic model for measuring the capacity of a particular road. By using a basic traﬃc model, we present, on the one hand, the empirical relationships of a vehicular traﬃc system in terms of density, ﬂow and speed; on the other hand, we show how the use of agent-based modeling to simulate vehicular traﬃc system proves to be a plausible alternative. Also, this work makes clear the shortcomings of a basic traﬃc model that must be considered for developing a more realistic traﬃc simulation system.
Black '47 and Beyond: The Great Irish Famine in History, Economy, and Memory

Here Ireland's premier economic historian and one of the leading authorities on the Great Irish Famine examines the most lethal natural disaster to strike Europe in the nineteenth century. Between the mid-eighteenth and early-nineteenth centuries, the food source that we still call the Irish potato had allowed the fastest population growth in the whole of Western Europe. As vividly described in O Grada's new work, the advent of the blight phytophthora infestans transformed the potato from an emblem of utility to a symbol of death by starvation. The Irish famine peaked in Black '47, but it brought misery and increased mortality to Ireland for several years. Central to Irish and British history, European demography, the world history of famines, and the story of American immigration, the Great Irish Famine is presented here from a variety of new perspectives. Moving away from the traditional narrative historical approach to the catastrophe, O Grada concentrates instead on fresh insights available through interdisciplinary and comparative methods. He highlights several economic and sociological features of the famine previously neglected in the literature, such as the part played by traders and markets, by medical science, and by migration. Other topics include how the Irish climate, usually hospitable to the potato, exacerbated the failure of the crops in 1845-1847, and the controversial issue of Britain's failure to provide adequate relief to the dying Irish. O Grada also examines the impact on urban Dublin of what was mainly a rural disaster and offers a critical analysis of the famine as represented in folk memory and tradition. The broad scope of this book is matched by its remarkable range of sources, published and archival. The book will be the starting point for all future research into the Irish famine.
Damping of electromechanical oscillations by VSC-HVDC active power modulation with supplementary wams based modal LQG controller

This paper presents a Multi Input Single Output (MISO) Modal Linear Quadratic Gaussian (MLQG) Power Oscillation Damping (POD) controller for Voltage Source Converter based HVDC systems. Applying this technique to a small (four machine) test network incorporating parallel HVDC/AC transmission has lead to improved damping of electromechanical modes compared with a traditional Power System Stabilizer (PSS) based controller structure. Furthermore, the MLQG controller has demonstrated greater robustness to varying operating conditions. The performance of the proposed control structure is assessed through small and large disturbance analysis.
Maximum Likelihood Identification of a Posture Control System

To identify characteristics of a sensory feedback path of a posture control system without external disturbances, the maximum likelihood identification method was applied to data of an antero-posterior sway during quiet stance. A subject stood on a force plate and the sway angle of a body (input) was measured by a position sensor camera and the ankle joint moment (output) was measured by the force plate. Using data of 500 input-output pairs sampled every 0.1 s, parameters of the sensory feedback path were estimated and frequency response functions were calculated. These showed derivative characteristics that are necessary for stabilization of the posture control system. Gain characteristics under the closed eyes condition tended to be greater than those under the open eyes condition.
USES OF THE INPUT-OUTPUT MODEL IN DEVELOPMENT PLANNING IN UNDERDEVELOPED COUNTRIES

THE usefulness of constructing an input-output table for a developed economy has more or less ceased to be a point of argument. However, the practicability of constructing such tables for an underdeveloped economy is s t 2 a highly debatable subject and has been under critical examination by many writers. Some of them even went so far as to reject the whole idea of constructing such tables in underdeveloped countries without any reservations. The major objection which most of those writers advanced is that in these countries there is an almost complete lack of statistics of any type and even if there are some basic statistics they are not of the type which would enable the construction of an input-output table. This is no doubt a very serious reason against the construction of an input-output table in such countries, but we should never forget that an input-output table after all is nothing but a body of comprehensive estimates even in the most developed economies, and that, therefore, it is sufficient to concentrate on certain important entries in the table. These are the strategic inputs to every industry. Strategic inputs would include those which have high coefficients, e.g. the input from the agricultural sector into the sugar cane industry, the input from the mining sector into the petroleum refining, etc., they would also include fertilizers into the agricultural sector, and the input from the energy sector to every industry. Other important figures would be those of production, value added and foreign trade. These figures, as well as the figures of the strategic inputs, may not be easy to get in most underdeveloped countries, but here we should mention the fact that the construction of such a table may
Exploring Feature Descritors for Face Recognition

How to encode a face is a widely studied problem in both pattern recognition and psychology literatures. Many feature descriptors, Gabor feature, local binary pattern (LBP), and edge orientation histogram, have been proposed. In this paper, we give a comprehensive study of these descriptors under the framework of principal component analysis (PCA) followed by linear discriminant analysis (LDA), compared on three different popular similarity measures and two different feature correspondence strategies: holistic and local. Moreover, we present a new feature descriptor named multi-radius LBP, and also propose a combination scheme for the LBP and Gabor descriptor. The experiments on the Purdue and CMU PIE databases demonstrate that 1) an obvious recognition boost of LBP is achieved under PCA+LDA framework compared to the direct NN classification; 2) the LBP and Gabor features are comparable as well as mutually complementary, and the combination of these two descriptors brings a significant improvement in classification capability over single ones; and 3) the multi-radius LBP shows to outperform all the state-of-the-art feature descriptors.
A requirements engineering approach for object-oriented conceptual modeling

Many different attempts have been made out over the last three decades to tackle the problems in software engineering that directly or indirectly lead to the symptoms of software crisis. These attempts have mostly focused on different specific fields, such as improved programming languages, improved modeling techniques, introduction of analysis and design methods, formal specifications, CASE tools, etc. In spite of the various attempts to develop high quality software systems, a difficult task still remains to be able to provide a solution to this classical problem: how to go from the problem space (user requirements) to the solution space (design and implementation) with sound methodological guidance. This PhD thesis is developed in the context of OO-Method (an object-oriented method for conceptual modeling and code generation) providing an approach to undertake this problem by extending the OO-Method Conceptual Model with a Requirements Model. The two cornerstones of this approach are the Requirements Model, which provides mechanisms to identify and specify functional user requirements at different abstraction levels, and the Requirements Analysis Process, which establishes conceptual links between the requirements and the structure and behavior of an OO-Method Conceptual Schema. These provide a smooth transition from a requirements specification to a conceptual schema in a traceable way. An industrial Requirements Specification Environment is being developed as a supporting tool. The integration of this tool with the automatic Conceptual Model Execution Environment provided by the OO-Method Case Tool (OlivaNova Model Execution Software®) will bring an achievable dream closer to reality, that is, to be able to go from requirements to code.
An Adaptive Framework for Acoustic Monitoring of Potential Hazards

Robust recognition of general audio events constitutes a topic of intensive research in the signal processing community. This work presents an efficient methodology for acoustic surveillance of atypical situations which can find use under different acoustic backgrounds. The primary goal is the continuous acoustic monitoring of a scene for potentially hazardous events in order to help an authorized officer to take the appropriate actions towards preventing human loss and/or property damage. A probabilistic hierarchical scheme is designed based on Gaussian mixture models and state-of-the-art sound parameters selected through extensive experimentation. A feature of the proposed system is its model adaptation loop that provides adaptability to different sound environments. We report extensive experimental results including installation in a real environment and operational detection rates for three days of function on a 24 hour basis. Moreover, we adopt a reliable testing procedure that demonstrates high detection rates as regards average recognition, miss probability, and false alarm rates.
Maternal, Perinatal, and Postneonatal Outcomes in Women With Chronic Heart Disease in Washington State

OBJECTIVE: To explore the association between the presence of maternal heart disease and maternal, perinatal, and infant outcomes. METHODS: We conducted a population-based retrospective cohort study using Washington State birth certificates linked with hospital discharge records of mothers noted to have maternal congenital heart disease, ischemic heart disease, heart failure, or pulmonary hypertension. Women who gave birth between 1987 and 2009 (n=2,171) were compared with a sample of mothers without these conditions (n=21,710). We described characteristics of pregnant women with heart disease over time. Logistic regression estimated the association between chronic maternal heart disease and small-for-gestational-age (SGA) neonates as well as perinatal, postneonatal, and maternal death. RESULTS: The proportion of births to women with reported heart disease increased 224% between the 1987 and 1994 and 2002 and 2009 calendar periods. Chronic maternal heart disease was associated with increased risk of SGA (62 additional SGA newborns per 1,000 births, 95% confidence interval [CI] 46–78; P<.001), perinatal death (14 additional deaths per 1,000 births, 95% CI 8–20; P<.001), postneonatal death (5 additional deaths per 1,000 births, 95% CI 2–9; P<.001), and maternal death (5 additional deaths per 1,000 births, 95% CI 2–9; P<.001). CONCLUSION: The presence of chronic maternal heart disease is associated with elevated risk for poor maternal, perinatal, and postneonatal outcomes. LEVEL OF EVIDENCE: II
Isolation and molecular characterization of KlCOX14, a gene of Kluyveromyces lactis encoding a protein necessary for the assembly of the cytochrome oxidase complex

The yeast Kluyveromyces lactis was mutagenized with ethyl methane sulphonate and mutants unable to grow on respiratory carbon sources were isolated. Functional complementation of one of these mutants led to the isolation of KlCOX14, a gene encoding a 64 amino acid protein which is the functional homologue of Saccharomyces cerevisiae Cox14p, a protein necessary for the assembly of the cytochrome oxidase holoenzyme (Glerum et al., 1995 ). The disruption of KlCOX14 resulted in the absence of the absorption bands relative to cytochromes a and a3 and in the complete loss of respiratory activity. Klcox14 mutants display the typical phenotype of pet mutants and have a reduced growth rate. In addition, unlike the wild‐type, Klcox14 mutants are able to grow by fermentation also in the presence of low glucose. The nucleotide sequence of KlCOX14 has been deposited in the EMBL databank with Accession No. AJ238801. Copyright © 2000 John Wiley & Sons, Ltd.