Miracle-dz/UniFAR-FTUs huggingface dataset:
IVRT′/IVRT Index Is a Useful Tool for Detection of Elevated Left Ventricular Filling Pressure in Patients with Preserved Ejection Fraction

Objective: Deterioration of active relaxation results in prolongation of isovolumteric relaxation time (IVRT), however, when left ventricular filling pressure elevates, mitral valve opens earlier and IVRT shortens. This shortening is not seen when IVRT is measured with tissue Doppler imaging (IVRT′). Then, IVRT′ prolongs with the deceleration of active relaxation independent of left ventricular filling pressure. We hypothesized that IVRT′ reflects the relaxation rate, thus, the ratio of IVRT′ to IVRT may possibly detect left ventricular filling pressure elevation. Methods: The group of 39 subjects (aged 64 ± 5 years) with preserved ejection fraction (EF > 50%) underwent combined echocardiographic and hemodynamic examinations. Echocardiographic parameters of mitral inflow and mitral annular motion were correlated with invasive indices of left ventricular relaxation and filling pressure. Results: Time constant of isovolumetric pressure decline (tau) correlated closely with IVRT′ (r = 0.73, P < 0.001) but not with early diastolic velocity of mitral annulus (E′) (r =−0.207, P = 0.206). The best parameter correlating with M‐LVDP was IVRT′/IVRT (r = 0.694, P < 0.001, M‐LVDP = 7.7 × IVRT′/IVRT + 5.1). A weaker relation was also noted between the ratio of early mitral peak inflow velocity to early diastolic velocity of mitral annulus (E/E′) and M‐LVDP (r = 0.469, P < 0.001). The relationships between standard Doppler parameters and left ventricular diastolic pressures were uniformly poor. Conclusions: The study demonstrated that IVRT′ may serve as a surrogate of left ventricular active relaxation. IVRT′/IVRT index may be applied to estimate left ventricular filling pressure.
Continuous motion, outdoor, 2 1/2D grid map generation using an inexpensive nodding 2-D laser rangefinder

This paper introduces a technique for creating 2 1/2D grid maps of unstructured, outdoor environments, while traveling at high speeds, using an inexpensive nodding 2-D laser rangefinder. The nodding mechanism allows the acquisition of multiple range data sets for terrain in front of the robot. While these multiple data sets alleviate some of the problems traditionally associated with laser rangefinders, they also introduce a new set of problems. The paper investigates and quantifies factors that determine the accuracy of a map generated using a nodding laser rangefinder and derives an optimal basis for minimizing these errors. This research has determined that the most significant source of errors, for a nodding laser rangefinder configuration, are the roll, pitch and yaw accuracy for the laser beam. A variance weighted statistical approach was implemented to optimally fuse the range data into the 2 1/2D grid map. Simulations and experiments were conducted, demonstrating the performance of the variance weighted technique as superior to classical statistical methods
A transformation for integrating VHDL behavioral specification with synthesis and software generation

VHDL signals and wait statements provide great ezpressiue power for behavioral specification. However, due to their climulation semantics, most high-level synthesis tools severely restrict their use, eliminating much of their power. Thus, there exists a need for a tool to bridge the gap between an arbitrary VHDL behavioral specification and existing synthesis tools. In this paper, we introduce a set of transformations to convert a VHDL description with signals and wait statements to equivalent constructs that are easily handled by high-level synthesis. The proposed transformations greatly enlarge the synthesizable VHDL subset, thus increasing the usefulness and practicality of the language as an input to high-level synthesis tools. These same transformations can also serve as a basis for converting a VHDL process to a form suitable for generation of software.
An Efficient Index Building Algorithm for Selection of Aggregator Nodes in Wireless Sensor Networks

In wireless sensor networks (WSNs), aggregator nodes perform the data aggregation process. Thus, careful selection of the aggregator nodes is needed to reduce network traffic in data aggregation process and prolong overall lifetime of the network. In this paper, we formulate selection process of the aggregator nodes as a top-k query problem. To answer the top-k queries efficiently in the large-scale WSNs, building and using the indexes are important. Thus, we propose an efficient index building algorithm for selection of aggregator nodes, called the Approximate Convex Hull Index (simply, aCH-Index). The main idea of our approach is to construct a convex hull over the sensor nodes in the WSNs, which enables speeding up the extraction of a set of sensor nodes that are potential candidates to become an aggregator node. In order to do so, the aCH-Index computes the skyline over the entire set of the sensor nodes, partitions the region into multiple subregions to reduce the computing time of convex hull in all origins, and then computes the convex hull in each subregion. Through the experiments with synthetic data, we show that aCH-Index outperforms the existing methods.
Automated Cognitive Modeling

In this paper we describe an approach to automating the construction of cognitive process models. We make two psychological assumptions: that cognition can be modeled as a production system, and that cognitive behavior involves search through some problem space. Within this framework, we employ a problem reduction approach to constructing cognitive models, in which one begins with a set of independent, overly general condition-action rules, adds appropriate conditions to each of these rules, and then recombines the more specific rules into a final model. Conditions arc determined using a discrimination learning method, which requires a set of positive and negative instances for each rule. These instances are based on inferred solution paths that lead to the same answers as those observed in a human subject. We have implemented ACM, a cognitive modeling system that incorporates these methods and applied the system to error data from the domain of multi-column subtraction problems.
Comparative Distribution and In Vitro Activities of the Urotensin II-Related Peptides URP1 and URP2 in Zebrafish: Evidence for Their Colocalization in Spinal Cerebrospinal Fluid-Contacting Neurons

Urotensin II (UII) is an evolutionarily conserved neuropeptide initially isolated from teleost fish on the basis of its smooth muscle-contracting activity. Subsequent studies have demonstrated the occurrence of several UII-related peptides (URPs), such that the UII family is now known to include four paralogue genes called UII, URP, URP1 and URP2. These genes probably arose through the two rounds of whole genome duplication that occurred during early vertebrate evolution. URP has been identified both in tetrapods and teleosts. In contrast, URP1 and URP2 have only been observed in ray-finned and cartilaginous fishes, suggesting that both genes were lost in the tetrapod lineage. In the present study, the distribution of urp1 mRNA compared to urp2 mRNA is reported in the central nervous system of zebrafish. In the spinal cord, urp1 and urp2 mRNAs were mainly colocalized in the same cells. These cells were also shown to be GABAergic and express the gene encoding the polycystic kidney disease 2-like 1 (pkd2l1) channel, indicating that they likely correspond to cerebrospinal fluid-contacting neurons. In the hindbrain, urp1-expressing cells were found in the intermediate reticular formation and the glossopharyngeal-vagal motor nerve nuclei. We also showed that synthetic URP1 and URP2 were able to induce intracellular calcium mobilization in human UII receptor (hUT)-transfected CHO cells with similar potencies (pEC50=7.99 and 7.52, respectively) albeit at slightly lower potencies than human UII and mammalian URP (pEC50=9.44 and 8.61, respectively). The functional redundancy of URP1 and URP2 as well as the colocalization of their mRNAs in the spinal cord suggest the robustness of this peptidic system and its physiological importance in zebrafish.
Architectural support for scalable speculative parallelization in shared-memory multiprocessors

Speculative parallelization aggressively executes in parallel codes that cannot be fully parallelized by the compiler. Past proposals of hardware schemes have mostly focused on single-chip multiprocessors (CMPs), whose effectiveness is necessarily limited by their small size. Very few schemes have attempted this technique in the context of scalable shared-memory systems. In this paper, we present and evaluate a new hardware scheme for scalable speculative parallelization. This design needs relatively simple hardware and is efficiently integrated into a cache-coherent NUMA system. We have designed the scheme in a hierarchical manner that largely abstracts away the internals of the node. We effectively utilize a speculative CMP as the building block for our scheme. Simulations show that the architecture proposed delivers good speedups at a modest hardware cost. For a set of important non-analyzable scientific loops, we report average speedups of 4.2 for 16 processors. We show that support for per-word speculative state is required by our applications, or else the performance suffers greatly.
Crystal structures of a ddATP‐, ddTTP‐, ddCTP, and ddGTP‐ trapped ternary complex of Klentaq1: Insights into nucleotide incorporation and selectivity

The mechanism by which DNA polymerase I enzymes function has been the subject of extensive biochemical and structural studies. We previously determined the structure of a ternary complex of the large fragment of DNA polymerase I from Thermus aquaticus (Klentaq1) bound to a primer/template DNA and a dideoxycytidine 5′‐triphosphate (ddCTP). In this report, we present the details of the 2.3‐Å resolution crystal structures of three additional ternary complexes of Klentaq1 bound to a primer/template DNA and a dideoxyguanosine 5′‐triphosphate (ddGTP), a dideoxythymidine 5′‐triphosphate (ddTTP), or a dideoxyadenosine 5′‐triphosphate (ddATP). Comparison of the active site of the four ternary complexes reveals that the protein residues around the nascent base pair (that formed between the incoming dideoxynucleoside triphosphate [ddNTP] and the template base) form a snug binding pocket into which only a correct Watson‐Crick base pair can fit. Except in the ternary complex bound to dideoxyguanosine 5′‐triphosphate, there are no sequence specific contacts between the protein side chains and the nascent base pair, suggesting that steric constraints imposed by the protein onto the nascent base pair is the major contributor to nucleotide selectivity at the polymerase active site. The protein around the polymerase active site also shows plasticity, which may be responsible for the substrate diversity of the enzyme. Two conserved side chains, Q754 and R573, form hydrogen bonds with the N3 atom in the purine base and O2 atom in the pyrimidine base at the minor groove side of the base pair formed by the incorporated ddNMP and the corresponding template base in all the four ternary complexes. These hydrogen‐bonding interactions may provide a means of detecting misincorporation at this position.
HIV therapy, metabolic and cardiovascular health are associated with glomerular hyperfiltration among men with and without HIV infection

Objective:Diabetes and hypertension, common conditions in antiretroviral-treated HIV-infected individuals, are associated with glomerular hyperfiltration, which precedes the onset of proteinuria and accelerated kidney function decline. In the Multicenter AIDS Cohort Study, we examined the extent to which hyperfiltration is present and associated with metabolic, cardiovascular, HIV and treatment risk factors among HIV-infected men. Design:Cross-sectional cohort using direct measurement of glomerular filtration rate by iohexol plasma clearance for 367 HIV-infected men and 241 HIV-uninfected men who were free of chronic kidney disease. Methods:Hyperfiltration was defined as glomerular filtration rate above 140−1 ml/min per 1.73 m2 per year over age 40. Multivariate logistic regression was used to estimate the odds ratios (ORs) of prevalent hyperfiltration for metabolic, cardiovascular, HIV and cumulative antiretroviral exposure factors. Results:Among individuals without chronic kidney disease, the prevalence of hyperfiltration was higher for HIV-infected participants (25%) compared to uninfected participants (17%; P = 0.01). After adjustment, HIV infection remained associated with hyperfiltration [OR 1.70, 95% confidence interval (CI) 1.11–2.61] and modified the association between diabetes and hyperfiltration, such that the association among HIV-uninfected men (OR 2.56, 95% CI 1.33–5.54) was not observed among HIV-infected men (OR 1.19, 95% CI 0.69–2.05). These associations were independent of known risk factors for hyperfiltration. Indicators of hyperglycemia and hypertension were also associated with hyperfiltration as was cumulative zidovudine exposure. Conclusion:Hyperfiltration, a potential modifiable predictor of kidney disease progression, is significantly higher among antiretroviral-treated HIV-infected men. Furthermore, HIV-infection nullifies the association of diabetes and hyperfiltration present in HIV-uninfected men.
miR-1/133a Clusters Cooperatively Specify the Cardiomyogenic Lineage by Adjustment of Myocardin Levels during Embryonic Heart Development

miRNAs are small RNAs directing many developmental processes by posttranscriptional regulation of protein-coding genes. We uncovered a new role for miR-1-1/133a-2 and miR-1-2/133a-1 clusters in the specification of embryonic cardiomyocytes allowing transition from an immature state characterized by expression of smooth muscle (SM) genes to a more mature fetal phenotype. Concomitant knockout of miR-1-1/133a-2 and miR-1-2/133a-1 released suppression of the transcriptional co-activator myocardin, a major regulator of SM gene expression, but not of its binding partner SRF. Overexpression of myocardin in the embryonic heart essentially recapitulated the miR-1/133a mutant phenotype at the molecular level, arresting embryonic cardiomyocytes in an immature state. Interestingly, the majority of postulated miR-1/133a targets was not altered in double mutant mice, indicating that the ability of miR-1/133a to suppress target molecules strongly depends on the cellular context. Finally, we show that myocardin positively regulates expression of miR-1/133a, thus constituting a negative feedback loop that is essential for early cardiac development.
The Introduction of Fuzzy Model to Compute the Edge Betweenness Centrality in Social Networks

Nowadays, we live in web area. The area through which the formation of various social network, new communicative and informing methods are introduced to the widespread social communications. A social network is a social structure which is made out of individuals and meanwhile, by the pass of time, the analyzing these social network will gain increasing primacy. In this research, one of the parameters of social network analysis called edge betweenness centrality is introduced. Edge betweenness is an edge to compute the shortest paths between pair of nodes in the network that passes through it most frequently. In this research, to detect the communities through edge betweenness centrality algorithm, a method is introduced in such a way that each edge by receiving one fuzzy membership degree in the interval [1,0] the measure of its effect on the network will be different. One of the features of this algorithm that makes it distinguished from others is the application of fuzzy logic to detect the communities of social network. Then by introducing the density of each cluster the density measure of the communities graph is computed through considering the fuzzy detected structures. The finding of the implementation of algorithm indicated that introduced algorithm to compute the density of samples and to detect the number of mono-nodes while clustering has revealed more accuracy rather than the related works.
Object-centered hybrid reasoning for whole-body mobile manipulation

Many houseworks such as cleaning the floor or wiping the windows require to manipulate tools over wide areas. It is necessary to move along a path while manipulating a tool with the whole body and applying exactly the right amount of force to successfully accomplish the task. So mastering such a challenge demands detailed knowledge about the involved objects and the underlying process models. Reasoning about an appropriate parameterization of the task is thereby essential. In this paper we propose a combination of object-centered hybrid reasoning and compliant force control to solve complex whole-body mobile manipulation issues. Depending on the objects involved in the task, an appropriate controller is selected and automatically parameterized. The methods are validated in an elaborate experiment on the humanoid robot Rollin' Justin.
Rotational thromboelastometry can detect factor XIII deficiency and bleeding diathesis in patients with cirrhosis

Patients with progressive liver disease exhibit complex coagulation disorders. Factor XIII plays a crucial role in the last steps of haemostasis, and its deficiency is associated with an increased incidence of bleeding diathesis. However, current conventional coagulation tests cannot detect factor XIII deficiency. In this study, we examined factor XIII activity and the ability of rotational thromboelastometry to detect factor XIII deficiency and bleeding diathesis in patients with cirrhosis.
Generating eating plans for athletes using the particle swarm optimization

This paper presents the automatic generation of optimal eating plans for athletes. The automatic generation of the eating plans is introduced as an optimization problem, where particle swarm optimization is taken as the problem solver. Inputs for the proposed particle swarm optimization algorithm are generated training plan and list of the potential meals, while the output of the algorithm represents a list of meals that should be consumed by the athletes. The first practical experiments showed that this solution is very promising.
Data for Development: the D4D Challenge on Mobile Phone Data

The Orange \Data for Development" (D4D) challenge is an open data challenge on anonymous call patterns of Orange's mobile phone users in Ivory Coast. The goal of the challenge is to help address society development questions in novel ways by contributing to the socio-economic development and well-being of the Ivory Coast population. Participants to the challenge are given access to four mobile phone datasets and the purpose of this paper is to describe the four datasets. The website http://www.d4d. orange.com contains more information about the participation rules. The datasets are based on anonymized Call Detail Records (CDR) of phone calls and SMS exchanges between
Current Integral Method for Fine Commutation Tuning of Sensorless Brushless DC Motor

This paper presents a method for fine commutation tuning of brushless direct current (BLDC) motor. First, we analyze the phase current waveform under commutation error and nonideal back-EMF. From the relationship derived, we propose a feedback compensation method in combination with a sensored BLDC motor or any sensorless drive technique to adjust commutation instant by forcing the current integrals of the two half periods in one 60° conducting period to be equal. The method is robust to variations in resistance and inductance, as well as to nonideal back-EMF, pushing the peak values of the current waveform at the front and back of each conducting period to be more identical. Simulations are presented and a digital signal processor (DSP)-based sensorless scheme contingent on a disturbance observer for back electromotive force (back-EMF) estimation in combination with the proposed control method is implemented to verify its effectiveness experimentally. The results show that proposed method is capable of running the motor at different speeds, load torque, and under the speed-varying operating condition with low levels of motor vibration and power consumption.
Diagnosis of repeated failures in discrete event systems

We introduce the notion of repeated failure diagnosability for diagnosing the occurrence of a repeated number of failures in discrete event systems. This generalizes the earlier notion of diagnosability that was used to diagnose the occurrence of a failure, but from which the information regarding the multiplicity of the occurrence of the failure could not be obtained. It is possible that in some systems the same type of failure repeats a multiple number of times. It is desirable to have a diagnoser which not only diagnoses that such a failure has occurred but also determines the number of times the failure has occurred. To aide such analysis we introduce the notions of K-diagnosability (K failures diagnosability), [1,K]-diagnosability (1 through K failures diagnosability), and [1,/spl infin/]-diagnosability (1 through /spl infin/ failures diagnosability). Here the first notion is the weakest of all three, and the earlier notion of diagnosability is the same as that of K-diagnosability or that of [1,K]-diagnosability with K=1. We give polynomial algorithms for checking these various notions of repeated failure diagnosability, and also present a procedure of polynomial complexity for the online diagnosis of repeated failures.
Adaptive multi-domain thermal modeling and analysis for integrated circuit synthesis and design

Chip-package thermal analysis is necessary for the design and synthesis of reliable, high-performance, low-power, compact integrated circuits (ICs). Many methods of IC thermal analysis suffer performance or accuracy problems that prevent use in IC synthesis and hinder use in architectural design. This article describes ISAC, a novel, fast, accurate thermal analysis system for use in IC synthesis and design. We present new, cooperative, temporal and spatial adaptation methods to dramatically accelerate accurate analysis. The proposed system unifies steady-state, time-domain, and frequency-domain analysis techniques. It is composed of our spatially-adaptive multigrid iterative solver, a new temporally and spatially adaptive asynchronous time marching solver, and a new spatially-adaptive frequency-domain moment matching solver. Together, these cooperative adaptation and multi-domain analysis techniques allow the proposed system to efficiently solve the static, short time scale, and long time scale variants of the IC thermal analysis problem. Experimental results demonstrate significant performance improvement over existing thermal analysis solutions. Our spatial adaptation techniques bring a 21.6times -690.0times speedup over recently-published steady-state thermal analysis techniques. Our unified spatial and temporal adaptation techniques, within our asynchronous time marching method, bring a 1,071times -1,890times speedup over other widely-used, time-domain thermal analysis techniques with less than 0.5% error. Our spatial adaptation techniques enable the efficient use of our frequency-domain thermal analysis technique, which brings a 10times - 100times speedup over the fastest-known time-domain technique, when used for long time scale thermal analysis. The thermal analysis system described in this article has been implemented as a C/C++ library that has been publicly released for free academic and personal use