Miracle-dz/UniFAR-FTUs huggingface dataset:
Intestinal flora during the first months of life: new perspectives

Increasing awareness that the human intestinal flora is a major factor in health and disease has led to different strategies to manipulate the flora to promote health. The complex microflora of the adult is difficult to change in the long term. There is greater impact of diet on the infant microflora. Manipulation of the flora particularly with probiotics has shown promising results in the prevention and treatment of diarrhoea and allergy. Before attempting to change the flora of the infant population in general, a greater understanding of the gut bacterial colonisation process is required. The critical stages of gut colonisation are after birth and during weaning. Lactic acid bacteria dominate the flora of the breast-fed infant. The formula-fed infant has a more diverse flora. The faeces of the breast-fed infant contain mainly acetic and lactic acid whereas the formula fed-infant has mainly acetic and propionic acid. Butyric acid is not a significant component in either group. The formula-fed infant also has higher faecal ammonia and other potentially harmful bacterial products. The composition of the microflora diversifies shortly before and particularly after weaning. The flora of the formula-fed infant develops more quickly than that of the breast-fed infant. Before embarking on any strategy to change the flora, the following questions should be considered: Should we retain a breast-fed style flora with limited ability to ferment complex carbohydrates? Can pro- and prebiotics achieve a flora with adult characteristics but with more lactic acid bacteria in weaned infants? Are there any health risks associated with such manipulations of the flora?
Fuel selection in human skeletal muscle in insulin resistance: a reexamination.

For many years, the Randle glucose fatty acid cycle has been invoked to explain insulin resistance in skeletal muscle of patients with type 2 diabetes or obesity. Increased fat oxidation was hypothesized to reduce glucose metabolism. The results of a number of investigations have shown that artificially increasing fat oxidation by provision of excess lipid does decrease glucose oxidation in the whole body. However, results obtained with rodent or human systems that more directly examined muscle fuel selection have found that skeletal muscle in insulin resistance is accompanied by increased, rather than decreased, muscle glucose oxidation under basal conditions and decreased glucose oxidation under insulin-stimulated circumstances, producing a state of "metabolic inflexibility. " Such a situation could contribute to the accumulation of triglyceride within the myocyte, as has been observed in insulin resistance. Recent knowledge of insulin receptor signaling indicates that the accumulation of lipid products in muscle can interfere with insulin signaling and produce insulin resistance. Therefore, although the Randle cycle is a valid physiological principle, it may not explain insulin resistance in skeletal muscle.
Efficiency standards for low voltage substation transformers

At present, there are no specific standards to distinguish "premium efficiency" transformers from "standard efficiency" transformers. The National Electrical Manufacturers Association (NEMA) has promulgated performance and test requirements for low voltage designs that can be listed as NEMA Class I, and for such units efficiencies are somewhat higher than those which appear in the literature as standard designs. The US Department of Energy, acting as required by the Energy Policy Act of 1992, is analyzing potential mandatory efficiency standards for a range of product classes that include the 500-2500 kVA dry and liquid-type low voltage transformers that are normally used in industrial substations. This paper explores the practical economic effects of transformer selection over a range of efficiency levels at and above the NEMA Class I levels.
Economic versus Cultural Differences: Forms of Ethnic Diversity and Public Goods Provision

Arguments about how ethnic diversity affects governance typically posit that groups differ from each other in substantively important ways and that these differences make effective governance more difficult. But existing cross-national empirical tests typically use measures of ethnolinguistic fractionalization (ELF) that have no information about substantive differences between groups. This article examines two important ways that groups differ from each other—culturally and economically—and assesses how such differences affect public goods provision. Across 46 countries, the analysis compares existing measures of cultural differences with a new measure that captures economic differences between groups: between-group inequality (BGI). We show that ELF, cultural fractionalization (CF), and BGI measure different things, and that the choice between them has an important impact on our understanding of which countries are most ethnically diverse. Furthermore, empirical tests reveal that BGI has a large, robust, and negative relationship with public goods provision, whereas CF, ELF, and overall inequality do not.
Variability of renal apparent diffusion coefficients: limitations of the monoexponential model for diffusion quantification.

PURPOSE To investigate whether variability in reported renal apparent diffusion coefficient (ADC) values in literature can be explained by the use of different diffusion weightings (b values) and the use of a monoexponential model to calculate ADC. MATERIALS AND METHODS This prospective study was approved by institutional review board and was HIPAA-compliant, and all subjects gave written informed consent. Diffusion-weighted (DW) imaging of the kidneys was performed in three healthy volunteers to generate reference diffusion decay curves. In a literature meta-analysis, the authors resampled the reference curves at the various b values used in 19 published studies of normal kidneys (reported ADC = [2.0-4.1] x 10(-3) mm(2) / sec for cortex and [1.9-5.1] x 10(-3) mm(2) / sec for medulla) and then fitted the resampled signals by monoexponential model to produce "predicted" ADC. Correlation plots were used to compare the predicted ADC values with the published values obtained with the same b values. RESULTS Significant correlation was found between the reported and predicted ADC values for whole renal parenchyma (R(2) = 0.50, P = . 002), cortex (R(2) = 0.87, P = . 0002), and medulla (R(2) = 0.61, P = . 0129), indicating that most of the variability in reported ADC values arises from limitations of a monoexponential model and use of different b values. CONCLUSION The use of a monoexponential function for DW imaging analysis and variably sampled diffusion weighting plays a substantial role in causing the variability in ADC of healthy kidneys. For maximum reliability in renal apparent diffusion coefficient quantification, data for monoexponential analysis should be acquired at a fixed set of b values or a biexponential model should be used. (c) RSNA, 2010.
Cardiac Electrophysiological Activation Pattern Estimation From Images Using a Patient-Specific Database of Synthetic Image Sequences

While abnormal patterns of cardiac electrophysiological activation are at the origin of important cardiovascular diseases (e.g., arrhythmia, asynchrony), the only clinically available method to observe detailed left ventricular endocardial surface activation pattern is through invasive catheter mapping. However, this electrophysiological activation controls the onset of the mechanical contraction; therefore, important information about the electrophysiology could be deduced from the detailed observation of the resulting motion patterns. In this paper, we present the study of this inverse cardiac electrokinematic relationship. The objective is to predict the activation pattern knowing the cardiac motion from the analysis of cardiac image sequences. To achieve this, we propose to create a rich patient-specific database of synthetic time series of the cardiac images using simulations of a personalized cardiac electromechanical model, in order to study this complex relationship between electrical activity and kinematic patterns in the context of this specific patient. We use this database to train a machine-learning algorithm which estimates the depolarization times of each cardiac segment from global and regional kinematic descriptors based on displacements or strains and their derivatives. Finally, we use this learning to estimate the patient's electrical activation times using the acquired clinical images. Experiments on the inverse electrokinematic learning are demonstrated on synthetic sequences and are evaluated on clinical data with promising results. The error calculated between our prediction and the invasive intracardiac mapping ground truth is relatively small (around 10 ms for ischemic patients and 20 ms for nonischemic patient). This approach suggests the possibility of noninvasive electrophysiological pattern estimation using cardiac motion imaging.
A projection semi‐implicit scheme for the coupling of an elastic structure with an incompressible fluid

We address the numerical simulation of fluid–structure systems involving an incompressible viscous fluid. This issue is particularly difficult to face when the fluid added‐mass acting on the structure is strong, as it happens in hemodynamics for example. Indeed, several works have shown that, in such situations, implicit coupling seems to be necessary in order to avoid numerical instabilities. Although significant improvements have been achieved during the last years, solving implicit coupling often exhibits a prohibitive computational cost. In this work, we introduce a semi‐implicit coupling scheme which remains stable for a reasonable range of the discretization parameters. The first idea consists in treating implicitly the added‐mass effect, whereas the other contributions (geometrical non‐linearities, viscous and convective effects) are treated explicitly. The second idea, relies on the fact that this kind of explicit–implicit splitting can be naturally performed using a Chorin–Temam projection scheme in the fluid. We prove (conditional) stability of the scheme for a fully discrete formulation. Several numerical experiments point out the efficiency of the present scheme compared to several implicit approaches. Copyright © 2006 John Wiley & Sons, Ltd.
a Robust Matching Method for Unmmaned Aerial Vehicle Images with Different Viewpoint Angles Based on Regional Coherency

Abstract. One of the main challenges confronting high-resolution remote sensing image matching is how to address the issue of geometric deformation between images, especially when the images are obtained from different viewpoints. In this paper, a robust matching method for Unmanned Aerial Vehicle images of different viewpoint angles based on regional coherency is proposed. The literature on the geometric transform analysis reveals that if transformations between different pixel pairs are different, they can't be expressed by a uniform affine transform. While for the same real scene, if the instantaneous field of view or the target depth changes is small, transformation between pixels in the whole image can be approximated by an affine transform. On the basis of this analysis, a region coherency matching method for Unmanned Aerial Vehicle images is proposed. In the proposed method, the simplified mapping from image view change to scale change and rotation change has been derived. Through this processing, the matching between view change images can be converted into the matching between rotation and scale changed images. In the method, firstly local image regions are detected and view changes between these local regions are mapped to rotation and scale change by performing local region simulation. And then, point feature detection and matching are implemented in the simulated image regions. Finally, a group of Unmanned Aerial Vehicle images are adopted to verify the performance of proposed matching method respectively, and a comparative analysis with other methods demonstrates the effectiveness of the proposed method.
Constraints on Cardassian Expansion from Distant Type Ia Supernovae

The distant Type Ia supernovae data compiled by Perlmutter et al. are used to analyze the Cardassian expansion scenario, which was recently proposed by Freese & Lewis as an alternative to a cosmological constant (or more generally a dark energy component) in explaining the currently accelerating universe. We show that the allowed intervals for n and zeq, the two parameters of the Cardassian model, will give rise to a universe with a very low matter density, which can hardly be reconciled with the current value derived from the measurements of the cosmic microwave background anisotropy and galaxy clusters (cluster baryon fraction). As a result, this Cardassian expansion proposal does not seem to survive the magnitude-redshift test for the present Type Ia supernovae data, unless the universe contains primarily baryonic matter.
Reliability-constrained area optimization of VLSI power/ground networks via sequence of linear programmings

This paper presents a new method for determining the widths of the power and ground routes in integrated circuits so that the area required by the routes is minimized subject to the reliability constraints. The basic idea is to transform the resulting constrained nonlinear programming problem into a sequence of linear programs. Theoretically, we show that the sequence of linear programs always converges to the optimum solution of the relaxed convex problem. Experimental results demonstrate that the sequence-of-linear-programming method is orders of magnitude faster than the best-known method based on conjugate gradients, with constantly better optimization solutions.
Parallel clock tree synthesis

Clock tree synthesis (CTS) is an important phase of the physical design of integrated circuits in which the network carrying the clock signal is laid out. As the sizes of modern circuits continue to grow exponentially, the amount of computation required in designing the clock network increases proportionally. CTS is a prime candidate for parallelization but is almost entirely unexplored in the literature. This paper highlights properties of common algorithms for performing CTS that are favorable for parallelization and presents parallel versions of the algorithms. Practical considerations in implementing parallel versions of the algorithms are also discussed. Experiments show the effectiveness of the parallel implementations in achieving linear speedup with the number of processors.
Robust Predictive Dead-Beat Controller for Buck Converters

This paper presents a predictive dead-beat current controller which uses an online estimation of the system's behavior. Only the measurement of inductor current is necessary for the realization. This idea also works for variable parameters of the load and of the power supply as well. Here pulse width modulation (PWM) method with constant frequency is taken into use, to limit switching losses. After a setpoint step-change, a new switch duty cycle is computed. If possible, the new setpoint is reached after one pulse period. That means, after the setpoint step-change, it takes one pulse period for the calculation and one more period to reach the final value.
Applications of Multivariate Pattern Classification Analyses in Developmental Neuroimaging of Healthy and Clinical Populations

Analyses of functional and structural imaging data typically involve testing hypotheses at each voxel in the brain. However, it is often the case that distributed spatial patterns may be a more appropriate metric for discriminating between conditions or groups. Multivariate pattern analysis has been gaining traction in neuroimaging of adult healthy and clinical populations; studies have shown that information present in neuroimaging data can be used to decode intentions and perceptual states, as well as discriminate between healthy and diseased brains. While few studies to date have applied these methods in pediatric populations, in this review we discuss exciting potential applications for studying both healthy, and aberrant, brain development. We include an overview of methods and discussion of challenges and limitations.
Flow-based formulations for the Mixed Capacitated Arc Routing Problem - Lower bounds 1

Mixed Capacitated Arc Routing Problem (MCARP) models arise in distribution or collecting problems where activities are performed by vehicles, with limited capacity, and are continuously distributed along some predefined links (routes, streets) of an associated network. Considering directed as well as undirected required links, it is a generalization of the well known Capacitated Arc Routing problem (CARP). A compact flow based and valid model for the MCARP is presented. Due to its large number of variables and constraints we develop an aggregated version of this model. Although not valid, its linear programming bound coincides with the linear programming bound of the original model. During the presentation, computational experiments will be reported.
Inotropic effects and changes in sodium and calcium contents associated with inhibition of monovalent cation active transport by ouabain in cultured myocardial cells

Cultured monolayers of spontaneously contracting chick embryo ventricular cells were perfused with culture medium containing ouabain. Contractile state was monitored by an optical-video system recording amplitude and velocity of cell wall motion. Positive inotropic effects of 2.5 x 10(-7) to 10(-6) M ouabain were manifest within 1.5-2 min, and reached a stable plateau within 5-6 min. The inotropic effect was fully reversed within 5 min after washout of ouabain. Inhibition of uptake of 42K+ (or the K+ analog 86Rb+) and efflux of 24Na+ occurred 1.5-2 min after exposure to ouabain. The degree of inhibition of transport was closely related to the magnitude of the positive inotropic effect throughout the ouabain concentration range 10(-7) to 10(-6) M. After washout of ouabain from monolayers, the monovalent cation active transport rate returned to normal within 1 min. Thus, both the onset and offset of inotropic action of ouabain were closely related temporally to inhibition of the sodium pump. Exposure to ouabain caused significant increases in exchangeable Na and Ca contents that appeared to be developed within 5 min. These data support the hypothesis that inhibition of monovalent cation active transport by ouabain is causally related to the development of positive inotropy and are consistent with modulation of Ca content by intracellular Na+ via the Na+-Ca2+ exchange carrier mechanism.
Throughput analysis of narrowband cognitive radio networks for fading channel

At present, spectrum scarcity is a major concern in the field of mobile communication. The necessity of spectrum is increasing gradually because the usage of wireless communication is rising tremendously. Cognitive radio (CR) is capable of dealing with this problem. This is referred to as an intelligent and reconfigurable radio which enables efficient usage of unused spectrum while avoiding any kind of interference. There are two groups of users in cognitive radio network. Primary users (PU) are the authorized users of the frequency band, the secondary users (SU) make use of those bands while primary users don't use those bands. So the unlicensed users i.e secondary users must sense the spectrum holes which are vacate as quickly as possible for conserving this spectrum reuse consequence and if it is detected that the channel is occupied by primary users again, it is obvious that the secondary users should vacate the channel in between a definite amount of time. Hence spectrum sensing plays a vital role in cognitive radio technology. Again, enhancing throughput is one of the fundamental issue in this field. If the sensing time large then CR gets less time to transmit data. Thus, throughput will degrades and if sensing time is low throughput will be high. In our paper, we try to improve throughput for different fading channel in narrowband with the help of a proposed model.
Mouse Bestrophin-2 Is a Bona fide Cl− Channel

Bestrophins have recently been proposed to comprise a new family of Cl− channels. Our goal was to test whether mouse bestrophin-2 (mBest2) is a bona fide Cl− channel. We expressed mBest2 in three different mammalian cell lines. mBest2 was trafficked to the plasma membrane as shown by biotinylation and immunoprecipitation, and induced a Ca2+-activated Cl− current in all three cell lines (EC50 for Ca2+ = 230 nM). The permeability sequence was SCN−: I−: Br−: Cl−: F− (8.2: 1.9: 1.4: 1: 0.5). Although SCN− was highly permeant, its conductance was ∼10% that of Cl− and SCN− blocked Cl− conductance (IC50 = 12 mM). Therefore, SCN− entered the pore more easily than Cl−, but bound more tightly than Cl−. Mutations in S79 altered the relative permeability and conductance for SCN− as expected if S79 contributed to an anion binding site in the channel. PSCN/PCl = 8.2 ± 1.3 for wild-type and 3.9 ± 0.4 for S79C. GSCN/GCl = 0.14 ± 0.03 for wild-type and 0.94 ± 0.04 for S79C. In the S79 mutants, SCN− did not block Cl− conductance. This suggested that the S79C mutation altered the affinity of an anion binding site for SCN−. Additional evidence that S79 was located in the conduction pathway was provided by the finding that modification of the sulfhydryl group in S79C with MTSET+ or MTSES− increased conductance significantly. Because the effect of positively and negatively charged MTS reagents was similar, electrostatic interactions between the permeant anion and the channel at this residue were probably not critical in anion selectivity. These data provide strong evidence that mBest2 forms part of the novel Cl− conduction pathway in mBest2-transfected cells and that S79 plays an important role in anion binding in the pore of the channel.
A Power-Law Model of Psychological Memory Strength in Short- and Long-Term Recognition

A classic law of cognition is that forgetting curves are closely approximated by power functions. This law describes relations between different empirical dependent variables and the retention interval, and the precise form of the functional relation depends on the scale used to measure each variable. In the research reported here, we conducted a recognition task involving both short- and long-term probes. We discovered that formal memory-strength parameters from an exemplar-recognition model closely followed a power function of the lag between studied items and a test probe. The model accounted for rich sets of response time (RT) data at both individual-subject and individual-lag levels. Because memory strengths were derived from model fits to choices and RTs from individual trials, the psychological power law was independent of the scale used to summarize the forgetting functions. Alternative models that assumed different functional relations or posited a separate fixed-strength working memory store fared considerably worse than the power-law model did in predicting the data.