Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiovascular Physiology Concepts

Introduction to the Cardiovascular System: Learning Objectives / The Need for a Circulatory System / The Arrangement of the Cardiovascular System / The Functions of the Heart and Blood Vessels / The Regulation of Cardiac and Vascular Function / The Content of the Following Chapters / Summary of Important Concepts / Review Questions / Answers to Review Questions Electrical Activity of the Heart: CD-ROM Materials / Learning Objectives / Introduction / Cell Membrane Potentials / Conduction of Action Potentials within the Heart / The Electrocardiogram (ECG) / Electrophysiological Changes during Cardiac Ischemia / Problems and Clinical Cases / Summary of Important Concepts / Review Questions / Answers to Review Questions / Suggested Readings Cellular Structure and Function: CD-ROM Materials / Learning Objectives / Introduction / Cardiac Cell Structure and Function / Vascular Structure and Function / Problems and Clinical Cases / Summary of Important Concepts / Review Questions / Answers to Review Questions / Suggested Readings Cardiac Function: CD-ROM Materials / Learning Objectives / Introduction / Cardiac Anatomy / Cardiac Cycle / Regulation of Cardiac Output / Myocardial Oxygen Consumption / Problems and Clinical Cases / Summary of Important Concepts / Review Questions / Answers to Review Questions / Suggested Readings Vascular Function: CD-ROM Materials / Learning Objectives / Introduction / Anatomy and Function / Arterial Blood Pressure / Regulation of Systemic Vascular Resistance / Venous Blood Pressure / Venous Return and Cardiac Output / Answers to Problems and Clinical Cases / Summary of Important Concepts / Review Questions / Answers to Review Questions / Suggested Readings Neurohumoral Control of the Heart and Circulation: Learning Objectives / Introduction / Autonomic Neural Control / Humoral Control / Summary of Neurohumoral Mechanisms / Answers to Problems and Clinical Cases / Summary of Important Concepts / Review Questions / Answers to Review Questions / Suggested Readings Microcirculation Organ Blood Flow Cardiovascular Integration and Adaptation
Detecting non-Abelian statistics of topological states on a chain of superconducting circuits

In view of the fundamental importance and many promising potential applications, non-Abelian statistics of topologically protected states has attracted much attention recently. However, due to the operational difficulties in solid state materials, non-Abelian statistics has not been experimentally realized yet. The superconducting quantum circuits system is scalable and controllable, thus is a promising platform for quantum simulation. Here, we propose a scheme to demonstrate non-Abelian statistics of topologically protected zero energy edge modes on a chain of the superconducting circuits. Specifically, we can realize topological phase transition by varying the hopping strength and magnetic filed in the chain, and the realized non-Abelian operation can be used in topological quantum computation. Considering the advantages of the superconducting quantum circuits, our protocol may shed light on quantum computation via topologically-protected states.
Model-Agnostic Approaches To Handling Noisy Labels When Training Sound Event Classifiers

Label noise is emerging as a pressing issue in sound event classification. This arises as we move towards larger datasets that are difficult to annotate manually, but it is even more severe if datasets are collected automatically from online repositories, where labels are inferred through automated heuristics applied to the audio content or metadata. While learning from noisy labels has been an active area of research in computer vision, it has received little attention in sound event classification. Most recent computer vision approaches against label noise are relatively complex, requiring complex networks or extra data resources. In this work, we evaluate simple and efficient model-agnostic approaches to handling noisy labels when training sound event classifiers, namely label smoothing regularization, mixup and noise-robust loss functions. The main advantage of these methods is that they can be easily incorporated to existing deep learning pipelines without need for network modifications or extra resources. We report results from experiments conducted with the FSDnoisy18k dataset. We show that these simple methods can be effective in mitigating the effect of label noise, providing up to 2.5% of accuracy boost when incorporated to two different CNNs, while requiring minimal intervention and computational overhead.
Searching for resistance to Fusarium root rot in safflower genotypes using pathogenicity test and AFLP molecular markers

Safflower (Carthamus tinctorius L.) is an annual oilseed crop adapted chiefly to the warm climate areas of Iran, which recently commercial production became concentrated to produce oil. Fusarium root rot is one of the important diseases of safflower in Iran. Whereas the use of resistant cultivars is one of the main strategies for reducing the loss and damage caused by pathogens in plants, this research was conducted to study the genetic diversity of safflower genotypes using AFLP markers and to compare relative resistance to Fusarium root rot. Sixty selected cultivars and lines derived from various regions were evaluated in randomized complete block design in three replications under in vitro and green house condition. Forty nine genotypes of safflower from Iran and 11 from other countries were inoculated with a selected identified pathogenic isolate of Fusarium solani derived from safflower. Genotypes were classified into five groups based upon the type of reaction to the disease; i.e. resistant, semi-resistant, tolerant, susceptible and semi-susceptible. Genetic diversity of the genotypes was assessed using AFLP markers. The results indicated differences among genotypes for resistance to Fusarium and clustering based on this trait. A bootstrap procedure was used to compare mean distances within and between genotypes and resistance to Fusarium root rot. Clustering based on AFLP markers and phenotypic resistance traits did not indicate complete concordance, but resistance and susceptible genotypes were separated from one another and have significant differences with other genotypes.
Minimax Testing of a Composite null Hypothesis Defined via a Quadratic Functional in the Model of regression

We consider the problem of testing a particular type of composite null hypothesis under a nonparametric multivariate regression model. For a given quadratic functional Q, the null hypothesis states that the regression function f satisfies the constraint Q[f] = 0, while the alternative corresponds to the functions for which Q[f] is bounded away from zero. On the one hand, we provide minimax rates of testing and the exact separation constants, along with a sharp-optimal testing procedure, for diagonal and nonnegative quadratic functionals. We consider smoothness classes of ellipsoidal form and check that our conditions are fulfilled in the particular case of ellipsoids corresponding to anisotropic Sobolev classes. In this case, we present a closed form of the minimax rate and the separation constant. On the other hand, minimax rates for quadratic functionals which are neither positive nor negative makes appear two different regimes: "regular" and "irregular". In the "regular" case, the minimax rate is equal to n-1/4 while in the "irregular" case, the rate depends on the smoothness class and is slower than in the "regular" case. We apply this to the issue of testing the equality of norms of two functions observed in noisy environments
Cerebral migrational defects and periventricular calcifications in a case of congenital CMV infection

A 10-day-old full-term male newborn, product of a non-consanguineous marriage, presented with history of intractable seizures since birth, which did not respond to conventional anticonvulsants. The baby was delivered normally at home and cried immediately after birth. The mother was a 25-year-old primigravida. The antenatal period was uneventful except for an episode of fever and nonspecific rash during first trimester of pregnancy. The mother did not have any antenatal check-up by a qualified medical practitioner. On examination, the baby had intrauterine growth retardation (weight 1850 g, length 44.3 cm) microcephaly (head circumference 32.2 cm) with wide-open anterior fontanel, purpuric spots, hepatosplenomegaly and generalized hypertonia. Ophthalmological examination showed bilateral chorioretinitis. Metabolic and sepsis screening re-
Fabrika işçilerinin sigara kullanma alışkanlıkları ve sigara bırakma konusundaki düşünceleri

Amac: Bu calisma cimento ve seker fabrikasinda calisan iscilerin sigara kullanma aliskanliklarinin ve sigara bagimlilik duzeylerinin belirlenmesi ile sigara icme ve birakma konusundaki dusuncelerinin ortaya cikarilmasi amaci ile yapilmistir. Yontemler: Tanimlayici ve kesitsel tipteki bu arastirma 2014 yilinda Corum ilinde cimento ve seker fabrikasinda calisan gonullu 200 erkek isci ile yapilmistir. Arastirmanin verileri iscilerin sigara kullanma aliskanliklari, sigara bagimlilik duzeyleri, sigara icme ve birakma konusundaki dusuncelerini sorgulayan ve 40 sorudan olusan bir anket formu araciligi ile toplanmistir. Iscilerin nikotin bagimlilik duzeylerinin belirlenmesinde Fagerstrom Nikotin Bagimlilik Testi kullanilmistir. Bulgular: Iscilerde sigara icme prevalansi %38,0, sigaraya baslama yas ortalamasi 18,82 ± 4,01 yildir. 11 yil ve daha uzun suredir sigara icen iscilerin orani %88,2, gunde ortalama 11 adet ve daha fazla sigara icenlerin orani %60,5\'dir. Sigara ictigi icin pismanlik duydugunu belirtenlerin orani %93,4 iken, sigarayi birakmayi istedigini belirtenlerin orani %63,2, sigarayi birakmayi denedigini belirtenlerin orani %68,4\'dur. Sigara icen iscilerin onemli bir bolumu sagliklarinin bozulmasi konusunda endise yasamaktadir. Sigara icen isciler arasinda sigaranin zararlari hakkindaki farkindalik yuksek olmasina ragmen sigarayi birakmayi engelleyen dusuncelerin yaygin oldugu belirlenmistir. Iscilerin %29,0\'u dusuk, %3,9\'u orta ve %67,1\'i yuksek duzeyde nikotin bagimlisidir. Iscilerin sigara bagimlilik duzeylerinin gunde tuketilen sigara sayisina gore anlamli farklilik gosterdigi belirlenmistir (p=0,004). Sigara birakma konusunda saglik personelinden oneri alan iscilerin orani dusuktur. Iscilerin tamamina yakini sigara birakma konusunda hic egitim almamistir. Sonuc: Bu calismada fabrika iscilerinde sigara icme oranlarinin ve nikotin bagimliligi duzeyinin yuksek oldugu belirlenmistir.
Fast, Guaranteed Spectral Model Selection for Topic Models

The question of how to determine the number of independent latent factors, or topics, in Latent Dirichlet Allocation (LDA) is of great practical importance. In most applications, the exact number of topics is unknown, and depends on the application and the size of the data set. We introduce a spectral model selection procedure for topic number estimation that does not require learning the model’s latent parameters beforehand and comes with probabilistic guarantees. The procedure is motivated by the spectral learning approach and relies on adaptations of results from random matrix theory. In a simulation experiment taken from the nonparametric Bayesian literature, this procedure outperforms the nonparametric Bayesian approach in both accuracy and speed. We also discuss some implications of our results for the sample complexity and accuracy of popular spectral learning algorithms for LDA. The principles underlying the procedure can be extended to spectral learning algorithms for other exchangeable mixture models with similar conditional independence properties.
2 J un 2 01 5 GRADOOP : Scalable Graph Data Management and Analytics with Hadoop-Technical Report -

Many Big Data applications in business and science require the management and analysis of huge amounts of graph data. Previous approaches for graph analytics such as graph databases and parallel graph processing systems (e.g., Pregel) either lack sufficient scalability or flexibility and expressiveness. We are therefore developing a new endto-end approach for graph data management and analysis based on the Hadoop ecosystem, called Gradoop (Graph analytics on Hadoop). Gradoop is designed around the so-called Extended Property Graph Data Model (EPGM) supporting semantically rich, schema-free graph data within many distinct graphs. A set of high-level operators is provided for analyzing both single graphs and collections of graphs. Based on these operators, we propose a domain-specific language to define analytical workflows. The Gradoop graph store is currently utilizing HBase for distributed storage of graph data in Hadoop clusters. An initial version of Gradoop has been used to analyze graph data for business intelligence and social network analysis.
Clinical tetanus in pigs in a pig farming complex, Lagos, Nigeria.

Tetanus is a state of muscular contractions caused by infection of wounds with the bacterium, Clostridium tetani. This bacterium produces toxins that affect the nervous system of both humans and animals. Although tetanus is rare in swine, in this report, we examine two clinical cases of tetanus in a pig farming complex in Lagos, Nigeria. The diagnosis of tetanus in pigs was based on the combination of observed clinical signs, history of castration under non-sterile conditions and presence of animal dung in the environment. To prevent future occurrences of tetanus in pigs, we recommend that there should be improved biosecurity measures on pig farms and farmers should employ the services of veterinarians for health-related issues affecting their pigs, especially in handling cases that require surgical intervention. Keywords : Tetanus, pigs, castration, Nigeria
Correlation of FcγRIIIa Polymorphisms and the Response to Rituximab in Thai Population

It has been reported that polymorphism in Fc gamma IIIa receptor (FcγRIIIa) associates with antibody-dependent cellular cytotoxicity (ADCC) activity of rituximab, the chimeric IgG1 monoclonal antibody against CD20. This antibody has been used for treatment of several non-Hodgkin’s lymphomas originate from B cells and has ADCC as an important mechanism of action. It is also known that genotype frequencies of FcγR polymorphisms depend on race and ethnicity. In this study, we investigated Fc gamma IIIa receptor (FcγRIIIa) genetic polymorphism at amino acid position 158 in Thai population. The nested polymerase chain reaction-restriction fragment length polymorphism (nested PCR-RFLP) was used to identify the FcγRIIIa genotypes of 60 healthy Thai male volunteers with informed consent. The distributions of FcγRIIIa-158 polymorphisms in these subjects were as follows: high binding genotypes (VV and VF), 55%; and low binding genotypes (FF), 45%. The different response of these genotypes to ADCC activity of rituximab was also evaluated. Rituximab-induced ADCC was performed by using PBMCs from 60 volunteers mentioned before as effect cells and ramos cells which express CD20 as target cells in the present of rituximab. High rituximab-induced Ramos cell cytotoxicity (mean rank 37.8%) was observed in the present of PBMCs from subjects with VV and VF genotypes while lower cytotoxicity (mean rank 21.6%) was determined in the present of PBMCs from subjects with FF genotypes. Our results provide the distribution of FcγRIIIa polymorphisms in Thai population which seems to differ from other Asian countries. This information should be useful for considering to use many IgG therapeutic antibodies in Thai population.
On the asymptotics of AKT statistics

In our days there is a widespread analysis of Wasserstein distances between theoretical and empirical measures. One of the first investigation of the topic is given in the paper written by Ajtai, Komlós and Tusnády in 1984. Interestingly all the neighboring questions posed by that paper were settled already without the original one. In this paper we are going to delineate the limit behavior of the original statistics with the help of computer simulations. At the same time we kept an eye on theoretical grasping of the problem. Based on our computer simulations our opinion is that the limit distribution is Gaussian.
Ju n 20 14 ON PREDICTION WITH THE LASSO WHEN THE DESIGN IS NOT

The LASSO estimator is an l1-norm penalized least-squares estimator, which was introduced for variable selection in the linear model. When the design matrix satisfies, e.g. the Restricted Isometry Property, or has a small coherence index, the LASSO estimator has been proved to recover, with high probability, the support and sign pattern of sufficiently sparse regression vectors. Under similar assumptions, the LASSO satisfies adaptive prediction bounds in various norms. The present note provides a prediction bound based on a new index for measuring how favorable is a design matrix for the LASSO estimator. We study the behavior of our new index for matrices with independent random columns uniformly drawn on the unit sphere. Using the simple trick of appending such a random matrix (with the right number of columns) to a given design matrix, we show that a prediction bound similar to [6, Theorem 2.1] holds without any constraint on the design matrix, other than restricted non-singularity.
HIGH TOTAL LEUKOCYTE COUNT AND HEART FAILURE AFTER MYOCARDIAL INFARCTION

Background: Acute myocardial infarction ST-elevation (STEMI) is frequently associated with leukocytosis and relative increased in neutrophil count. It is believed that the peripheral leukocyte count have important prognostic implication in AMI. In this study we hypothesized that there is an association between absolute leukocytosis and neutrophilia to the short term development of congestive heart failure (CHF) after AMI. Methods: A cross sectional study carried out from June -August 2010. 200 patients with diagnosis of STEMI were included. Patients with a history of chest pain of more than 12 hours, recent trauma, infection, malignancy were excluded. Baseline demographic data was obtained. Blood sample was drawn for leukocyte count within 12 hours of admission.Echocardiogram (Echo) and X-ray chest was obtained during first four days. Chi square test was applied to seek association between high total leukocyte (TLC) and heart failure. Results: Out of 200 patients, 98 (49%) remained uncomplicated and they were discharged without clinical evidence of CHF; whereas 91(45.5%) patients who developed clinical CHF underwent Echo and discharged later. Total 11(5.5%) patients expired in hospital. Out of 91 patients who developed CHF 61(67%) had high TLC (>11000 mm3), while 30 (33%) had normal ( 65 mm3), while 10 (11%) had normal (≤65 mm3) Significant association (p < 0.016) of neutrophilia with development of CHF was observed. Conclusion: This study shows that high TLC count appears to be associated with development of CHF and mortality after acute STEMI.
Rejoinder of Feature Matching in Time Series Modeling by Y. Xia and H. Tong

We would like to thank all the discussants for their wide-ranging comments. Before we respond to them individually in alphabetical order, we would like to address some general issues first. As we have said, we have chosen to describe our aim of matching the joint distribution of the observable data as feature matching, for want of a better name. We should have perhaps emphasized that we regard cycles, spectral singularities, and so on only as partial aspects of the joint distribution. They are useful, in practical applications, only in so far as they can provide partial measures of feature matching. We think Professor Hansen has understood our aim well in his introduction. We have sometimes, for brevity, called our general approach to achieving this aim the catch-all approach. We should stress the following point once more. The catch-all approach is not restricted to catch all first-order (conditional) moments or catch all second-order moments. We have used them in the paper primarily as illustrations of what the approach can deliver in modeling, beyond conventional methods based on the one-step-ahead prediction errors. Clearly, once the catch-all idea is accepted, we can equally well catch all kth-order (conditional or unconditional) moments, catch all marginal (conditional or unconditional) distributions, and so on. Moreover, the objective function Q can also take on a form other than that of a mean squared type; for example, it can be of a likelihood type as stated in Section 2.1.
My title

In this paper, we are concerned with obtaining distribution-free concentration inequalities for mixture of independent Bernoulli variables that incorporate a notion of variance. Missing mass is the total probability mass associated to the outcomes that have not been seen in a given sample which is an important quantity that connects density estimates obtained from a sample to the population for discrete distributions. Therefore, we are specifically motivated to apply our method to study the concentration of missing mass which can be expressed as a mixture of Bernoulli in a novel way. We not only derive for the first time Bernstein-like large deviation bounds for the missing mass whose exponents behave almost linearly with respect to deviation size, but also sharpen McAllester and Ortiz [2003] and Berend and Kontorovich [2013] for large sample sizes in the case of small deviations (of the mean error) which is the most interesting case in learning theory. In the meantime, our approach shows that the heterogeneity issue introduced in McAllester and Ortiz [2003] is resolvable in the case of missing mass in the sense that one can use standard inequalities but it may not lead to strong results. Finally, we postulate that our results are general and can be applied to provide potentially sharp Bernstein-like bounds under some constraints.
Phrase Candidates ( frequent n-gram ) speaks at a town Barack Obama Anderson Cooper

As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus and has various downstream applications including information extraction/retrieval, taxonomy construction, and topic modeling. Most existing methods rely on complex, trained linguistic analyzers, and thus likely have unsatisfactory performance on text corpora of new domains and genres without extra but expensive adaption. None of the state-of-the-art models, even data-driven models, is fully automated because they require human experts for designing rules or labeling phrases. In this paper, we propose a novel framework for automated phrase mining, AutoPhrase, which supports any language as long as a general knowledge base (e.g., Wikipedia) in that language is available, while benefiting from, but not requiring, a POS tagger. Compared to the state-of-the-art methods, AutoPhrase has shown significant improvements in both effectiveness and efficiency on five real-world datasets across different domains and languages. Besides, AutoPhrase can be extend to model single-word quality phrases.
C A ] 6 O ct 2 00 9 SHARP A 2 INEQUALITY FOR HAAR SHIFT OPERATORS

Abstract. As a Corollary to the main result of the paper we give a new proof of the inequality ‖T f‖L2(w) . ‖w‖A2‖f‖L2(w) , where T is either the Hilbert transform [13], a Riesz transform [14], or the Beurling operator [16]. The weight w is non-negative, and the linear growth in the A2 characteristic on the right is sharp. Prior proofs relied strongly on Haar shift operators [12] and Bellman function techniques. The new proof uses Haar shifts, and then uses an elegant ‘two weight T 1 theorem’ of NazarovTreil-Volberg [11] to immediately identify relevant Carleson measure estimates, which are in turn verified using an appropriate corona decomposition of the weight w.