Miracle-dz/UniFAR-FTUs huggingface dataset:
Maternal 25-hydroxyvitamin D and parathyroid hormone concentrations and offspring birth size.

CONTEXT There is inconsistent evidence that maternal 25-hydroxyvitamin D [25-(OH)D] deficiency may impair fetal growth. OBJECTIVE The objective of the study was to examine the relationship between maternal 25-(OH)D and PTH concentrations at less than 16 and 28 wk gestation and offspring birth size. DESIGN This was an observational study. SETTING The study was set at a hospital antenatal clinic. PARTICIPANTS Women with singleton pregnancies, before 16 wk gestation, participated. INTERVENTIONS No interventions were used. MAIN OUTCOME MEASURE Knee-heel length at birth was the main outcome measure. RESULTS Altogether 374 of 475 (79%) women completed this study. We found no evident relationship between birth size measures and maternal 25-(OH)D or PTH at recruitment (approximately 11 wk). Gestation length was 0.7 wk (95% confidence interval -1.3, -0.1) shorter and knee-heel length was 4.3 mm smaller (-7.3, -1.3) in infants of 27 mothers with low 25-(OH)D (<28 nmol/liter) at 28-32 wk vs. babies whose mothers had higher concentrations. This latter difference was reduced to -2.7 mm (-5.4, -0.1) after adjustment for gestation length, suggesting some of the apparent growth deficit is explained by shorter gestation. There was no evidence that other birth measures were affected. Maternal PTH concentration at 28-32 wk was positively related to knee-heel length, birth weight, and mid-upper arm and calf circumferences. These associations were independent of 25-(OH)D concentration. CONCLUSIONS Low maternal 25-(OH)D in late pregnancy is associated with reduced intrauterine long bone growth and slightly shorter gestation. The long-term consequences for linear growth and health require follow-up. The positive relationship between maternal PTH and measures of infant size may relate to increased mineral demands by larger babies, but warrants further investigation.
Identifying Persistent and Recurrent QoE Anomalies for DASH Streaming in the Cloud

Quality of Experience (QoE) anomalies widely exist in all types of video services. As video services migrate to the Cloud, unique challenges occur to deploy video services in the Cloud environment. We study the QoE anomalies for users in a video service deployed in a production Cloud CDN. We use a QoE anomaly identification system, QRank, to identify anomalous systems. We consider Cloud CDN servers, Cloud CDN networks, transit networks, user access networks and different types of user devices. Our extensive experiments in production Cloud find several interesting insights about QoE anomalies of video streaming in the Cloud. 91.4% of QoE anomalies are detected on 15.32% of users. These users experience QoE anomalies persistently and recurrently. The Cloud servers and networks seldom cause QoE anomalies. More than 99.98% of QoE anomalies are identified in anomalous systems including the transit networks, the access networks and user devices. We infer that transit networks are the actual bottleneck systems for QoE anomalies in production Cloud. More than 95% of persistent and recurrent QoE anomalies are identified in less than 10 transit networks. We collect latency measurements to anomalous networks and the analysis indicates that the limited capacity in transit networks are the major cause of QoE anomalies. Resulting anomalies impair user QoEs persistently or recurrently. In order to provide good user QoE, the Cloud provider should identify transit networks that may become bottlenecks for high quality video streaming and appropriate peering with Internet Service Providers (ISPs) to bypass these bottlenecks.
Minimizing Energy Consumption with Probabilistic Distance Models in Wireless Sensor Networks

Minimizing energy consumption in wireless sensor networks has been a challenging issue, and grid-based clustering and routing schemes have attracted a lot of attention due to their simplicity and feasibility. Thus how to determine the \textit{optimal grid size} in order to minimize energy consumption and prolong network lifetime becomes an important problem during the network planning and dimensioning phase. So far most existing work uses the average distances within a grid and between neighbor grids to calculate the average energy consumption, which we found largely underestimates the real value. In this paper, we propose, analyze and evaluate the energy consumption models in wireless sensor networks with probabilistic distance distributions. These models have been validated by numerical and simulation results, which shows that they can be used to optimize grid size and minimize energy consumption accurately. We also use these models to study variable-size grids, which can further improve the energy efficiency by balancing the relayed traffic in wireless sensor networks.
Clinically unrecognized myocardial infarction detected at MR imaging may not be associated with atherosclerosis.

PURPOSE To prospectively investigate whether there is support for the hypothesis that clinically unrecognized myocardial infarctions (UMIs) detected at magnetic resonance (MR) imaging have an atherosclerotic pathogenesis similar to that of recognized myocardial infarctions (RMIs). MATERIALS AND METHODS After ethics committee approval and informed consent were obtained, gadolinium-enhanced whole-body MR angiography and late-enhancement MR imaging were performed in 248 randomly chosen 70-year-old subjects (123 women, 125 men). Imaging included the aorta and the carotid, renal, and lower limb arteries to the ankle, but not the coronary arteries. Subjects with myocardial infarction (MI) scars at late-enhancement MR imaging were classified as having RMI (n=11) (those with a diagnosis of MI at the hospital) or UMI (n=49) (those without a diagnosis of MI at the hospital). The presence of 50% or higher luminal narrowing in any vessel at whole-body MR angiography was considered to represent significant atherosclerosis. Intima-media thickness of the common carotid artery was measured with ultrasonography. C-reactive protein level was measured, and coronary heart disease risk was estimated. Observers were blinded to any previous results. The chi2 test, analysis of variance, and Bonferroni correction were used for statistical analyses. RESULTS None of the measured parameters differed significantly between the group without MI scars and the UMI group, but parameters were significantly increased in the RMI group (P<.05) compared with those in the group without MI scars. Forty-two of 49 UMIs and nine of 11 RMIs were located within inferolateral segments of the left ventricle. CONCLUSION MR imaging-detected UMIs might have a different pathogenesis from that of RMIs or may have the same pathogenesis but may manifest at an earlier stage.
Improved C-V Level Set Algorithm and its Application in Video Segmentation

Image segmentation method based on level set model has wide potential application for its excellent seg-mentation result. However its complex computing restricts its application in video segmentation. In order to improve the speed of image segmentation, this paper presents a new level set initialization method based on Chan-Vese level set model. After a simple iterative, we can separate out the outline of objects. Experiments show that the method is simple and efficient, with good separation effects. The improved Chan-Vese method can be applied in video segmentation.
Wiping the smile off your base ( correlation curve )

We discuss problems with interpolating and extrapolating base correlation curves and examine the pricing of CDO tranches with non-standard subordination levels. We introduce an alternative risk measure, the expected loss of equity tranches. We calculate upper and lower boundaries on “base EL”, and set out the behaviours that base EL must obey. We investigate interpolation schemes that best avoid model arbitrage. We also look at the calculated prices and sensitivities for tranches using these different methods. This paper is intended to be a practical explanation of methodologies used by Derivative Fitch in its RAP CD synthetic CDO pricing tool. For our introduction to the underlying concept of looking at the expected loss of equity tranches, we are grateful for discussions with a number of market participants, notably Jon Gregory.
The U.S. Supreme Court and the Model of Contingent Discretion

Congress passes statutes defining particular areas of the law, but the Supreme Court can interpret those statutes. This tension over the meaning of the rule of law has profound implications for democratic theory and the separation of powers. Though scholars have examined whether the Supreme Court issues decisions against the preferences of Congress, there has been little focus on whether legislators can constrain the Court. Our study examines how much discretion Congress provides in statutes it enacts into law. Our basic argument is that ideological decision making by Supreme Court justices depends upon the level of discretion Congress incorporates into the law. The greater the discretion, the less constraint federal judges and justices will encounter, making them more likely to vote according to their individual ideologies. Conversely, more detailed statutes will reduce the judges' discretion. Using data on 1953–96 Supreme Court decisions, our analysis supports this model of contingent discretion.
Biology of aggression

SECTION 1: GENES Chapter 1 Genetic Aspects of Aggression in Nonhuman Animals Chapter 2 Human Quantitative Genetics of Aggression Chapter 3 Crustacean Models of Aggression SECTION 2: NEUROTRANSMITTERS Chapter 4 Brain Serotonin and Aggressive Disposition in Humans and Nonhuman Primates Chapter 5 Monoamines, GABA, Glutamate, and Aggression Chapter 6 Nitric Oxide and Aggression Chapter 7 Neuroplasticity and Agression: An Interaction Between Vasopressin and Serotonin SECTION 3: HORMONES Chapter 8 Contexts and Ethology of Vertebrate Aggression: Implications for the Evolution of Hormone Behavior Interactions Chapter 9 Androgens and Aggression Chapter 10 The Role of Estrogen Receptors in the Regulation of Aggressive Behaviors Chapter 11 Maternal Aggression Chapter 12 Stress and Aggressive Behaviors STRESS 4: DEVELOPMENT Chapter 13 Conditioned Defeat Chapter 14 Development of Aggression Chapter 15 Neurobiology of Aggression in Children SECTION 5: PHARMACOLOGY AND PSYCHOPHYSIOLOGY Chapter 16 Drugs of Abuse and Aggression Chapter 17 Psychopharmacology of Human Aggression: Laboratory and Clinical Studies Chapter 18 Psychophysiology of Human Antisocial Behavior
Meaning and compositionality as statistical induction of categories and constraints

What do words and phrases mean? How do we infer their meaning in a given context? How do we know which sets of words have sensible meanings when combined, as opposed to being nonsense? As language learners and speakers, we can solve these problems starting at a young age, but as scientists, our understanding of these processes is limited. This thesis seeks to address these questions using a computational approach. Bayesian modeling provides a method of combining categories and logical constraints with probabilistic inference, yielding word and phrase meanings that involve graded category memberships and are governed by probabilistically inferred structures. The Bayesian approach also allows an investigation to separately identify the prior beliefs a language user brings to a particular situation involving meaning-based inference (e.g., learning a word meaning or identifying which objects an adjective applies to within a given context), and to identify what the language user can infer from the context. This approach therefore provides the foundation also for investigations of how different prior beliefs affect what a language user infers in a given situation, and how prior beliefs can develop over time. Using a computational approach, I address the following questions: (1) How do people generalize about a word’s meaning from limited evidence? (2) How do people understand and use phrases, particularly when some of the words in those phrases depend on context for interpretation? (3) How do people know and learn which combinations of predicates and noun phrases can sensibly be combined and which are nonsensical? I show how each of these topics involves the probabilistic induction of categories, and I examine the constraints on inference in each domain. I also explore which of these constraints may themselves be learned. Thesis Supervisor: Joshua Tenenbaum Title: Associate Professor of Cognitive Science
The draft genome sequence of multidrug-resistant Pseudomonas aeruginosa strain CCBH4851, a nosocomial isolate belonging to clone SP (ST277) that is prevalent in Brazil

The high occurrence of nosocomial multidrug-resistant (MDR) microorganisms is considered a global health problem. Here, we report the draft genome sequence of a MDR Pseudomonas aeruginosa strain isolated in Brazil that belongs to the endemic clone ST277. The genome encodes important resistance determinant genes and consists of 6.7 Mb with a G+C content of 66.86% and 6,347 predicted coding regions including 60 RNAs.
Internal Representation of Embedded Hardware-/ Software - Systems the Extended Syntaxgraph Esg

The Extended Syntax Graph (ESG) is an approach to combine some advantages of data ow graphs (DFGs) with those of syntax graphs. An embedded system described by C x , a superset of ANSI-C can be entirely represented by the ESG. In the same way, an eecient dataaow analysis becomes possible. The ESG constitutes the central data structure of COSYMA (COSYnthesis for eMbedded Architectures), our experimental tool for automated hardware-software co-design. COSYMA COSYMA ErHe92] is a software oriented approach for automated hardware-software co-design. The designer describes the embedded system with C x , a superset of ANSI-C deened by us, which includes timing constraints and parallel processes as signiicant extensions. The design starts with a software solution except for our deened components and primitive peripherals. Only when timing constraints are violated, code segments are moved to a hardware implementation by an iterative procedure. The result of the partitioning process consists of software for a processor core, one or more coprocessors and peripherial components. These hardware components are synthesized with the synthesis-tool OLYMPUS ((MiMa90]) based on a description in HardwareC which is generated by COSYMA. For the software parts, COSYMA generates ANSI-C code which is then compiled. Data ow graphs often used for the high-level synthesis are inappropriate for the internal representation of dynamic data structures and parallel processes. In contrast, syntax graphs, as e.g. used by Mar90], ooer such a possibility. Furthermore, syntax graphs can easily be transformed into HardwareC and ANSI-C. For the partitioning process and estimation, COSYMA requires information about the data dependencies. Using regular syntax graphs this would be a time consuming task. Therefore, we extended the usual syntax graph description by an implicit symbol table and local data ow graphs. The ESG is a directed acyclic graph describing a sequence of declarations, deenitions and statements. Each identiier occurring in the graph is accompanied by a pointer to its deenition. Conversely, each deenition is extended by pointers to all instances. Then, the costs of communication between the processor core and its coprocessors can quickly and easily be determined with the assistance of this implicit symbol table. Only in cases where a variable is used by software as well as by hardware the variable itself is transferred to a coprocessor. More precisely, the implicit symbol table provides an upper bound on the communication costs, because variables might be reassigned. As an illustration g. 1 shows a code segment …
Algebras for hazard detection

Hazards pulses are undesirable short pulses caused by stray delays in digital circuits. Such pulses not only may cause errors in the circuit operation, but also consume energy, and add to the computation time. It is therefore very important to detect hazards in circuit designs. Two-valued Boolean algebra, which is commonly used for the analysis and synthesis of digital circuits, cannot detect hazard conditions directly. To overcome this limitation several multi-valued algebras have been proposed for hazard detection. This paper surveys these algebras, and studies their mathematical properties. Also, some recent results unifying most of the multi-valued algebras presented in the literature are described. Our attention in this paper is restricted to the study of static and dynamic hazards in gate circuits.
Vers une nouvelle socio-géographie de la mobilité quotidienne. Étude des mobilités quotidiennes des habitants de la région urbaine de Grenoble

Au prisme de la diversite des pratiques spatio-temporelles, la mobilite constitue sans contestation l'element majeur des relations sociales contemporaines. Si les pratiques spatio-temporelles et les formes des mobilites quotidiennes sont loin d'etre homogenes, comment peut-on pour autant les decrire, les qualifier et les rendre plus comprehensibles ? L'echelle la plus adequate pour analyser ces comportements peut etre celle de l'aire metropolitaine car c'est en effet un espace qui resulte de ces mobilites et dans lequel s'inscrit la majorite des mobilites urbaines d'aujourd'hui. Cette these tend a etablir une lecture de l'heterogeneite de l'espace metropolitain grenoblois et de ses organisations, a travers l'analyse des pratiques des mobilites quotidiennes. Une meilleure connaissance et representation des comportements de la mobilite quotidienne dans l'espace-temps constitue le coeur de sa problematique. La motivation essentielle de ce cadrage est la prise en compte de l'individu dans le contexte de mobilite qui lui est propre, avec toutes ses dimensions particulieres. Une demarche originale vise a rendre possible une lecture et une analyse des mobilites et des activites ainsi que des disparites en cours, a travers une grande base de donnees quantitatives, l'enquete menages deplacements (EMD 2002 sur la region grenobloise). Il s'agit d'une analyse secondaire des donnees d'un outil majeur des politiques publiques locales et qui n'a pas ete utilise jusqu'a present pour analyser les formes des mobilites quotidiennes.
Serum Brain-derived neurotrophic factor (BDNF): the severity and symptomatic dimensions of depression.

INTRODUCTION The aim of this study was to compare the concentration of serum Brain-derived neurotrophic factor (BDNF) in patients suffering from major depressive disorder (MDD) considering the severity of MDD episode defined by the Hamilton rating scale for depression (HAMD-17). The other aim was to research the connection between serum BDNF and the symptomatic dimensions of MDD. SUBJECTS AND METHODS The study includes 139 participants with major depressive disorder (MDD). Diagnosis of MDD was set by DSM-IV-TR criteria. The severity of MDD was estimated with HAM-D-17 in the manner that mild episode was diagnosed if the score on HAMD-17 was up to 18, moderately severe 18-25 and severe over 25. Concentration of BDNF was determined by the ELISA method. RESULTS This research could not find a difference in BDNF concentration considering the severity of the depressive disorder in groups suffering from mild, moderately severe and severe episodes of MDD (F=1.816; p=0.169). Factor analysis of HAMD-17 extracted four dimensions of depressive symptoms. None of the symptomatic dimensions was significantly related to BDNF concentration. CONCLUSION Results of this study indicate that serum BDNF levels are not related to the severity of depression and its specific symptomatic dimensions. These findings support the idea of a complex relationship between BDNF concentration at the periphery and in the CNS.
Description and Phylogeny of Tetrakeronopsis silvanetoi gen. nov., sp. nov. (Hypotricha, Pseudokeronopsidae), a New Benthic Marine Ciliate from Brazil

Pseudokeronopsidae Borror & Wicklow, 1983 are biotechnologically important ciliate protists which produce toxic defense substances; however, their diversity is still little known in Brazil. In the present study, Tetrakeronopsis silvanetoi, a new genus and species of marine pseudokeronopsid hypotrichs is described from samples of water with bottom sediment collected from the coast of São Paulo state. Its phylogenetic affinities to the “core urostyloids” are hypothesized based on analyses of the 18S-rDNA marker, and a new subfamily, the Nothoholostichinae subfam. nov., is erected to name the monophylum composed of pseudokeronopsids in which the anterior corona is usually formed by four frontal cirri. In addition, the new combination Monocoronella longissima comb. nov. is proposed for Nothoholosticha longissima (Dragesco & Dragesco-Kernéis, 1986) Li et al., 2009.
The Clubroot Pathogen (Plasmodiophora brassicae) Influences Auxin Signaling to Regulate Auxin Homeostasis in Arabidopsis

The clubroot disease, caused by the obligate biotrophic protist Plasmodiophora brassicae, affects cruciferous crops worldwide. It is characterized by root swellings as symptoms, which are dependent on the alteration of auxin and cytokinin metabolism. Here, we describe that two different classes of auxin receptors, the TIR family and the auxin binding protein 1 (ABP1) in Arabidopsis thaliana are transcriptionally upregulated upon gall formation. Mutations in the TIR family resulted in more susceptible reactions to the root pathogen. As target genes for the different pathways we have investigated the transcriptional regulation of selected transcriptional repressors (Aux/IAA) and transcription factors (ARF). As the TIR pathway controls auxin homeostasis via the upregulation of some auxin conjugate synthetases (GH3), the expression of selected GH3 genes was also investigated, showing in most cases upregulation. A double gh3 mutant showed also slightly higher susceptibility to P. brassicae infection, while all tested single mutants did not show any alteration in the clubroot phenotype. As targets for the ABP1-induced cell elongation the effect of potassium channel blockers on clubroot formation was investigated. Treatment with tetraethylammonium (TEA) resulted in less severe clubroot symptoms. This research provides evidence for the involvement of two auxin signaling pathways in Arabidopsis needed for the establishment of the root galls by P. brassicae.
Novel Perspectives on p53 Function in Neural Stem Cells and Brain Tumors

Malignant glioma is the most common brain tumor in adults and is associated with a very poor prognosis. Mutations in the p53 tumor suppressor gene are frequently detected in gliomas. p53 is well-known for its ability to induce cell cycle arrest, apoptosis, senescence, or differentiation following cellular stress. That the guardian of the genome also controls stem cell self-renewal and suppresses pluripotency adds a novel level of complexity to p53. Exactly how p53 works in order to prevent malignant transformation of cells in the central nervous system remains unclear, and despite being one of the most studied proteins, there is a need to acquire further knowledge about p53 in neural stem cells. Importantly, the characterization of glioma cells with stem-like properties, also known as brain tumor stem cells, has opened up for the development of novel targeted therapies. Here, we give an overview of what is currently known about p53 in brain tumors and neural stem cells. Specifically, we review the literature regarding transformation of adult neural stem cells and, we discuss how the loss of p53 and deregulation of growth factor signaling pathways, such as increased PDGF signaling, lead to brain tumor development. Reactivation of p53 in brain tumor stem cell populations in combination with current treatments for glioma should be further explored and may become a viable future therapeutic approach.