Miracle-dz/UniFAR-FTUs huggingface dataset:
Time-Efficient Black Blood RCA Wall Imaging at 3T Using Improved Motion Sensitized Driven Equilibrium (iMSDE): Feasibility and Reproducibility

Background The aim of this study was to explore the feasibility and reproducibility of a time-efficient coronary vessel wall measurement approach using an improved motion-sensitized driven equilibrium (iMSDE) pulse sequence. Methodology In this study, the iMSDE pulse sequence was first optimized and then applied on a group of healthy volunteers (N = 10) to evaluate its feasibility of vessel wall visualization. The same technique was also applied on a separate group of volunteers (N = 19) for a reproducibility study by scanning the same subject in two separate sessions. The iMSDE sequence was found to provide good coronary vessel wall delineation. It was also found to provide reproducible coronary vessel wall diameter and thickness measurements in both proximal and middle segments of the right coronary artery. Conclusion The feasibility and reproducibility of iMSDE based coronary vessel wall imaging were demonstrated for the first time, paving the way for further testing in a clinical environment for fast and accurate coronary artery disease detection.
Inhibition of iron absorption by calcium is modest in an iron-fortified, casein- and whey-based drink in Indian children and is easily compensated for by addition of ascorbic acid.

BACKGROUND Calcium inhibits and ascorbic acid (AA) enhances iron absorption from iron-fortified foods. Absorption efficiency depends on iron status, although the interaction is unclear. OBJECTIVE We investigated the ability of AA to overcome calcium-induced inhibition of iron absorption in children differing in iron status. METHODS The effect of calcium (0, 100, and 200 mg/test meal) on iron absorption in the absence and presence of AA (0, 42.5, and 85 mg/test meal) from a casein/whey-based drink fortified with ferrous sulfate was assessed in a series of randomized crossover studies both in iron-replete (IR) Indian schoolchildren and in children with iron deficiency anemia (IDA) (6-11 y; n = 14-16/group) by using stable isotopes. RESULTS In the absence of calcium and AA, iron absorption from the casein/whey-based drink was 20% lower in IR children than in children with IDA. The addition of calcium reduced mean iron absorption by 18-27%, with the effect being stronger for high added calcium (P < 0.01). AA at a 2:1 or 4:1 molar ratio enhanced iron absorption by a factor of 2-4 and greatly overcompensated for the inhibitory effect of calcium on iron absorption in a dose-dependent manner (P < 0.001). The dose-response effect tended to be stronger (P < 0.1) in the IDA group, and iron status was of far less influence on iron absorption than the enhancing effect of AA. CONCLUSION When adding AA to iron-fortified milk products, care should be taken not to provide absorbable iron in excess of needs.
Estimating high-dimensional intervention effects from observational data

We assume that we have observational data generated from an unknown underlying directed acyclic graph (DAG) model. A DAG is typically not identifiable from observational data, but it is possible to consistently estimate the equivalence class of a DAG. Moreover, for any given DAG, causal effects can be estimated using intervention calculus. In this paper, we combine these two parts. For each DAG in the estimated equivalence class, we use intervention calculus to estimate the causal effects of the covariates on the response. This yields a collection of estimated causal effects for each covariate. We show that the distinct values in this set can be consistently estimated by an algorithm that uses only local information of the graph. This local approach is computationally fast and feasible in high-dimensional problems. We propose to use summary measures of the set of possible causal effects to determine variable importance. In particular, we use the minimum absolute value of this set, since that is a lower bound on the size of the causal effect. We demonstrate the merits of our methods in a simulation study and on a data set about riboflavin production.
Domain Wall Memory based Convolutional Neural Networks for Bit-width Extendability and Energy-Efficiency

In the hardware implementation of deep learning algorithms such as Convolutional Neural Networks (CNNs), vector-vector multiplications and memories for storing parameters take a significant portion of area and power consumption. In this paper, we propose a Domain Wall Memory (DWM) based design of CNN convolutional layer. In the proposed design, the resistive cell sensing mechanism is efficiently exploited to design a low-cost DWM-based cell arrays for storing parameters. The unique serial access mechanism and small footprint of DWM are also used to reduce the area and power cost of the input registers for aligning inputs. Contrary to the conventional implementation using Memristor-Based Crossbar (MBC), the bit-width of the proposed CNN convolutional layer is extendable for high resolution classifications and training. Simulation results using 65 nm CMOS process show that the proposed design archives 34% of energy savings compared to the conventional MBC based design approach.
ESTIMATION OF STREAMFLOW, BASE FLOW, AND NITRATE‐NITROGEN LOADS IN IOWA USING MULTIPLE LINEAR REGRESSION MODELS 1

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest.
The Similarity Between Stochastic Kronecker and Chung-Lu Graph Models

The analysis of massive graphs is now becoming a very important part of science and industrial research. This has led to the construction of a large variety of graph models, each with their own advantages. The Stochastic Kronecker Graph (SKG) model has been chosen by the Graph500 steering committee to create supercomputer benchmarks for graph algorithms. The major reasons for this are its easy parallelization and ability to mirror real data. Although SKG is easy to implement, there is little understanding of the properties and behavior of this model. We show that the parallel variant of the edgeconfiguration model given by Chung and Lu (referred to as CL) is notably similar to the SKG model. The graph properties of an SKG are extremely close to those of a CL graph generated with the appropriate parameters. Indeed, the final probability matrix used by SKG is almost identical to that of a CL model. This implies that the graph distribution represented by SKG is almost the same as that given by a CL model. We also show that when it comes to fitting real data, CL performs as well as SKG based on empirical studies of graph properties. CL has the added benefit of a trivially simple fitting procedure and exactly matching the degree distribution. Our results suggest that users of the SKG model should consider the CL model because of its similar properties, simpler structure, and ability to fit a wider range of degree distributions. At the very least, CL is a good control model to compare against. ∗This work was funded by the applied mathematics program at the United States Department of Energy and performed at Sandia National Laboratories, a multiprogram laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000. †Sandia National Laboratories, CA, apinar@sandia.gov ‡Sandia National Laboratories, CA, scomand@sandia.gov §Sandia National Laboratories, CA, tgkolda@sandia.gov
Physical Computing and its Scope - Towards a Constructionist Computer Science Curriculum with Physical Computing

Physical computing covers the design and realization of interactive objects and instal- lations and allows students to develop concrete, tangible products of the real world, which arise from the learners' imagination. This can be used in computer science education to provide students with interesting and motivating access to the different topic areas of the subject in construction- ist and creative learning environments. To make many existing activities and examples of such project ideas available for classroom use and to expand the topic areas suitable for learning in such environments beyond introductory to programming, a physical computing syllabus for computer science courses in general education schools has been developed. In this paper the methods and different perspectives that were taken into account are presented. The resulting syllabus can be used to develop a constructionist computer science curriculum with physical computing.
A Movie Rating Prediction Algorithm with Collaborative Filtering

Recommendation systems are one of the research areas studied intensively in the last decades and several solutions have been elicited for problems in different domains for recommending. Recommendation may differ as content, collaborative filtering or both. Other than known challenges in collaborative filtering techniques, accuracy and computational cost at a large scale data are still at saliency. In this paper we proposed an approach by utilizing matrix value factorization for predicting rating i by user j with the sub matrix as k-most similar items specific to user i for all users who rated them all. In an attempt, previously predicted values are used for subsequent predictions. In order to investigate the accuracy of neighborhood methods we applied our method on Netflix Prize [1]. We have considered both items and users relationships on Netflix dataset for predicting movie ratings. We have conducted several experiments.
Effects of Eicosapentaenoic Acid on the Cytoprotection Through Nrf2-Mediated Heme Oxygenase-1 in Human Endothelial Cells

Abstract: Consumption of omega-3 polyunsaturated fatty acid, particularly eicosapentaenoic acid (EPA), is associated with a significant reduction in the risk of developing cardiovascular disease. The aim of this study was to investigate whether heme oxygenase-1 (HO-1) induction contributes to the cytoprotective effects of EPA in endothelial cells threatened with oxidative damage. In this study, we investigated the effect of EPA on the induction of HO-1 by NF-E2-related factor 2 (Nrf2) in human umbilical vein endothelial cells. In cells treated with low concentrations of EPA (10–25 &mgr;M), HO-1 expression increased in a time- and concentration-dependent manner. Additionally, EPA treatment increased Nrf2 nuclear translocation and antioxidant response element activity, leading to the upregulation of HO-1 expression. Furthermore, treatment with EPA reduced hydrogen peroxide (H2O2)-induced cell death. The reduction in cell death was reversed by treatment with zinc protoporphyrin, an inhibitor of HO-1, indicating that HO-1 contributed to the protective effect of EPA. These data suggest that EPA protects against H2O2-induced oxidative stress in endothelial cells by activating Nrf2 and inducting HO-1 expression.
Genetic Tracing of Ca v 3 . 2 T-Type Calcium Channel Expression in the Peripheral Nervous System

Characterizing the distinct functions of the T-type ion channel subunits Cav3.1, 3.2 or 3.3 has proven difficult due to their highly conserved amino-acid sequences and the lack of pharmacological blockers specific for each subunit. To precisely determine the expression pattern of the Cav3.2 channel in the nervous system we generated two knock-in mouse strains that express EGFP or Cre recombinase under the control of the Cav3.2 gene promoter. We show that in the brains of these animals, the Cav3.2 channel is predominantly expressed in the dentate gyrus of the hippocampus. In the peripheral nervous system, the activation of the promoter starts at E9.5 in neural crest cells that will give rise to dorsal root ganglia (DRG) neurons, but not sympathetic neurons. As development progresses the number of DRG cells expressing the Cav3.2 channel reaches around 7% of the DRG at E16.5, and remains constant until E18.5. Characterization of sensory neuron subpopulations at E18.5 showed that EGFP cells are a heterogeneous population consisting mainly of TrkB and TrkC cells, while only a small percentage of DRG cells were TrkA. Genetic tracing of the sensory nerve end-organ innervation of the skin showed that the activity of the Cav3.2 channel promoter in sensory progenitors marks many mechanoreceptor and nociceptor endings, but spares slowly adapting mechanoreceptors with endings associated with Merkel cells. Our genetic analysis reveals for the first time that progenitors that express the Cav3.2 T-type calcium channel, defines a sensory specific lineage that populates a large proportion of the DRG. Using our Cav3.2-Cre mice together with AAV viruses containing a conditional fluorescent reporter (tdTomato) we could also show that Cre expression is largely restricted to two functionally distinct sensory neuron types in the adult ganglia. Cav3.2 positive neurons innervating the skin were found to only form lanceolate endings on hair follicles and are probably identical to D-hair receptors. A second population of nociceptive sensory neurons expressing the Cav3.2 gene was found to be positive for the calcitonin-gene related peptide but these neurons are deep tissue nociceptors that do not innervate the skin.
trans-Bis(μ-2-hydroxyethanethiolato-κ2 S:S)bis[dinitrosyliron(II)](Fe—Fe)

The title complex, [Fe2(C2H5OS)2(NO)4], lies on a crystallographic inversion center. The Fe—Fe distance is characteristic of a metal–metal bond. In the crystal structure, intermolecular O—H⋯O hydrogen bonds link complex molecules into a two-dimensional network.
Decoding the Text Encoding

Word clouds and text visualization is one of the recent most popular and widely used types of visualizations. Despite the attractiveness and simplicity of producing word clouds, they do not provide a thorough visualization for the distribution of the underlying data. Therefore, it is important to redesign word clouds for improving their design choices and to be able to do further statistical analysis on data. In this paper we have proposed a fully automatic redesigning algorithm for word cloud visualization. Our proposed method is able to decode an input word cloud visualization and provides the raw data in the form of a list of (word, value) pairs. To the best of our knowledge our work is the first attempt to extract raw data from word cloud visualization. We have tested our proposed method both qualitatively and quantitatively. The results of our experiments show that our algorithm is able to extract the words and their weights effectively with considerable low error rate.
Reinventing the Wheel?! Why Harmonization and Reuse Fail in Complex Data Warehouse Environments and a Proposed Solution to the Problem

Enterprise or group data warehouses are often introduced in complex multi-national organizations in order to foster harmonization, integrate heterogeneous source systems and hide the heterogeneity from analytical systems. Industry reference data warehouse logical data models such as Teradata’s FS-LDM or IBM’s BDW are promoted as accelerators for the development of such large data warehouses. However, this paper shows that logical data models alone are not sufficient to ensure reusability in those environments. In order to provide a solid basis for standardization, the logical data model needs to be accompanied by a semantic business information model used as an anchor point for the mappings and for communication with business users. Such a model allows a model-driven approach for specification of the data transformations, which usually accounts for at least half the total effort of large data warehouse projects. The paper presents an approach building upon the Teradata Business Data Element (BDE) concept giving practical examples from project experience in the financial services industry. A research prototype is presented, utilizing Semantic Web technologies such as the Web Ontology Language (OWL) to facilitate the traceability of data requirements, business terms and physical data elements in the different layers of a complex data warehouse architecture.
A re-assessment of the brachiopod genus spanodonta prendergast from the lower Ordovician of Western Australia

The poorly known plectambonitacean genus Spanodonta Prendergast is re-assessed and its type species, S. hoskingiae Prendergast 1935 from the Lower Ordovician of Western Australia, redescribed. The only other species assigned to the genus, S. tingriensis Liu, is rejected from it. The genus is considered to be most closely related to Aporthophyla Ulrich & Cooper and is therefore assigned to the Taffidae.
The Transimpedance Limit

The transimpedance limit describes the maximum transimpedance that a transimpedance amplifier (TIA) can attain for a given bandwidth and technology. We analyze and compare this limit for a wide variety of TIA topologies thus exposing their relative merits. The topologies considered are the shunt-feedback TIA with single and multistage amplifier, the shunt-feedback TIA with feedback capacitor, the shunt-feedback TIA followed by a post amplifier, the shunt-feedback TIA with a current amplifier, the common-base/gate feedforward TIA, the shunt-feedback TIA with a common-base/gate input stage, and the shunt-feedback TIA with a regulated-cascode input stage. The analysis includes a discussion of the conditions under which the limit is realizable.
Rotor Loss Analysis of Interior Permanent Magnet Motors Using Combination of 2-D and 3-D Finite Element Method

A novel method using combination of 2-D and 3-D finite element analyses is proposed for the rotor loss calculation of interior permanent magnet motors. First, the differential permeability at the average flux density of the rotor core is estimated by the 2-D nonlinear time-domain analysis. Then, the 3-D frequency-domain finite element analyses at each remarkable harmonic field are carried out with this permeability, in order to consider the magnetic saturation. Using this method, the calculation time is reduced to less than 1/100 compared with the full 3-D analysis, whereas the accuracy is nearly same.
Magnetopause characteristics at 0840-1040 hours local time

We have analyzed three-dimensional energetic (> or approx. =24 keV) particle distributions for 14 consecutive inbound ISEE orbits during times of magnetopause crossings and close approaches. The data are from the November 10 through December 11, 1977, time period and cover local times of approx.0840--1040 hours. We find that in this period the magnetopause as defined by energetic particles can be represented as sharp (very much less than the ion gyroradius) and very well defined boundary for magnetospheric activity and magnetosheath field conditions. Using the technique described by Williams (1979) we have determined the magnetopause position, orientation, and velocity for all identified magnetopause crossings and close approaches. We find that the magnetopause is nearly always in motion with velocities ranging from near zero to > or approx. = +- 25 km/s. Large-amplitude (>1000 km) radial motions often are present and at times are quasi-periodic. Superimposed on these large-scale motions is the nearly continuous presence of orientation angle variations consistent with boundary waves having periods of approx.100--450 s and amplitudes of a few hundred kilometers. During a rare interval when the boundary orientation was steady, large magnetopause radial motion was observed. Conversely, during an interval of near-zero magnetopause velocity, orientation anglemore » variations were observed. Correlations with published plasma, magnetic field, and plasma wave magnetopause identifications show the energetic (> or approx. =24 keV) particle results to be accurate and an important factor in determining magnetopause characteristics and behavior. Comparison of our results with published plasma data for the November 10, 1977, inbound magnetopause encounters yields a scale length (e-folding distance) for magnetosheath plasma penetration into the magnetosphere of approx.60--90 km for electrons and approx.90--110 km for protons. « less
Functional trade-offs in the limb bones of dogs selected for running versus fighting

SUMMARY The physical demands of rapid and economical running differ from the demands of fighting in ways that may prevent the simultaneous evolution of optimal performance in these two behaviors. Here, we test an hypothesis of functional trade-off in limb bones by measuring mechanical properties of limb bones in two breeds of domestic dog (Canis lupus familiaris L.) that have undergone intense artificial selection for running (greyhound) and fighting (pit bull) performance. The bones were loaded to fracture in three-point static bending. To correct for the effect of shear, we estimated the shear stress in the cross section and added energy due to shear stress to the tensile energy. The proximal limb bones of the pit bulls differed from those of the greyhounds in having relatively larger second moments of area of mid-diaphyseal cross sections and in having more circular cross-sectional shape. The pit bulls exhibited lower stresses at yield, had lower elastic moduli and failed at much higher levels of work. The stiffness of the tissue of the humerus, radius, femur and tibia was 1.5-2.4-fold greater in the greyhounds than in the pit bulls. These bones from the pit bulls absorbed 1.9-2.6-fold more energy before failure than did those of the greyhounds. These differences between breeds were not observed in the long bones of the feet, metacarpals and metatarsals. Nevertheless, the results of this analysis suggest that selection for high-speed running is associated with the evolution of relatively stiff, brittle limb bones, whereas selection for fighting performance leads to the evolution of limb bones with relatively high resistance to failure.