Miracle-dz/UniFAR-FTUs huggingface dataset:
CD 28-inducible transcription factor DEC 1 is required for efficient autoreactive CD 4 + T cell response

The Rockefeller University Press $30.00 J. Exp. Med. 2013 Vol. 210 No. 8 1603-1619 www.jem. org/cgi/doi/10.1084/jem.20122387 1603 For productive activation, naive T cells require two signals: an antigen-specific signal through the TCR and a second signal via the CD28 co-stimulatory receptor (Lenschow et al., 1996; Bour-Jordan et al., 2011). The delivery of the combined signals rapidly promotes a complex pattern of transcriptional changes that leads to efficient T cell proliferation and differentiation (Diehn et al., 2002; Riley et al., 2002). Many studies have focused on the membrane-proximal events involved in CD28 signals and their immediate effects on nuclear translocation of transcription factors, including AP-1, NFAT, and NF-B family members (Jain et al., 1993; Köntgen et al., 1995; Kempiak et al., 1999; Rao et al., 2003; Marinari et al., 2004; SánchezValdepeñas et al., 2006). Based on the central role of the CD28/B7 signaling pathway in immune responses, autoimmune diseases, and allograft rejection, two drugs that block this pathway, abatacept and belatacept, have been developed and FDA approved (Linsley and Nadler, 2009). However, in spite of the functional and clinical progress in developing costimulation antagonists for clinical purposes, there are few studies on the transcriptional program initiated after CD28/B7 engagement, and CORRESPONDENCE Jeffrey A. Bluestone: Jeff.Bluestone@ucsf.edu
Cognitive and Opportunistic Relay for QoS Guarantees in Machine-to-Machine Communications

Deploying spectrum sharing machine-to-machine (M2M) communications with the existing wireless networks achieves ubiquitous data transportation among objects and the surrounding environment to benefit our daily life. However, the lack of schemes to completely characterize M2M network topology, to efficiently share radio resource, and to provide quality-of-service (QoS) guarantee regarding end-to-end delay creates challenges to practically facilitate M2M communications. Via mathematical derivations, the network connectivity, degree distribution, and average distance are provided for large M2M networks. To achieve reliable communications upon such M2M networks, inspired by cognitive radio technology and cooperative communications, a cognitive and opportunistic relay (COR) scheme is proposed. Specifically, machines with the proposed COR autonomously sense the primary systems' spectrum usage so as to mitigate detractive interference and adopt opportunistic forwarder selection for lower link delay of packet transmissions. Furthermore, by analytical deriving the effective capacity of the COR over connected M2M networks, the throughput under statistical QoS guarantee and the corresponding delay violation probability are proposed to specify the QoS guarantee capability of the networks and thus suggest the conditions of dependable end-to-end transmissions. Simulation results confirm that the proposed COR effectively achieves the delay guarantee performance, to yield a novel framework for facilitating reliable M2M communications in large machine networks.
Unified Boundary Trapezoidal Modulation Control Utilizing Fixed Duty Cycle Compensation and Magnetizing Current Design for Dual Active Bridge DC–DC Converter

The unified boundary trapezoidal modulation (TZM) control utilizing fixed duty cycle compensation and magnetizing current design for dual active bridge dc-dc converter is proposed in this paper. The fixed duty cycle compensation and magnetizing current design are first introduced to achieve the zero voltage switching (ZVS) of the power switches, which cannot be ensured with the conventional TZM control. As a result, all the power switches of dual active dc-dc converter can achieve ZVS and four switches can be turned off with very low current. Besides, based on the revealed power transfer characteristic, the power control variables including the duty cycles and phase-shift ratio can be unified without lookup tables or operation region division. With the proposed boundary TZM control, circulating current losses can be reduced and nonactive power is significantly suppressed according to the mathematic analysis, resulting in decrease of the conduction loss. A 1.6-kW laboratory prototype is built to verify the theoretical analysis and effectiveness of the proposed control.
Angiotensin-Converting Enzyme 2 Suppresses Pathological Hypertrophy, Myocardial Fibrosis, and Cardiac Dysfunction

Background— Angiotensin-converting enzyme 2 (ACE2) is a pleiotropic monocarboxypeptidase capable of metabolizing several peptide substrates. We hypothesized that ACE2 is a negative regulator of angiotensin II (Ang II)–mediated signaling and its adverse effects on the cardiovascular system. Methods and Results— Ang II infusion (1.5 mg · kg−1 · d−1) for 14 days resulted in worsening cardiac fibrosis and pathological hypertrophy in ACE2 knockout (Ace2−/y) mice compared with wild-type (WT) mice. Daily treatment of Ang II–infused wild-type mice with recombinant human ACE2 (rhACE2; 2 mg · kg−1 · d−1 IP) blunted the hypertrophic response and expression of hypertrophy markers and reduced Ang II–induced superoxide production. Ang II–mediated myocardial fibrosis and expression of procollagen type I&agr;1, procollagen type III&agr;1, transforming growth factor-&bgr;1, and fibronectin were also suppressed by rhACE2. Ang II–induced diastolic dysfunction was inhibited by rhACE2 in association with reduced plasma and myocardial Ang II and increased plasma Ang 1-7 levels. rhACE2 treatment inhibited Ang II–mediated activation of protein kinase C-&agr; and protein kinase C-&bgr;1 protein levels and phosphorylation of the extracellular signal-regulated 1/2, Janus kinase 2, and signal transducer and activator of transcription 3 signaling pathways in wild-type mice. A subpressor dose of Ang II (0.15 mg · kg−1 · d−1) resulted in a milder phenotype that was strikingly attenuated by rhACE2 (2 mg · kg−1 · d−1 IP). In adult ventricular cardiomyocytes and cardiofibroblasts, Ang II–mediated superoxide generation, collagen production, and extracellular signal-regulated 1/2 signaling were inhibited by rhACE2 in an Ang 1-7–dependent manner. Importantly, rhACE2 partially prevented the development of dilated cardiomyopathy in pressure-overloaded wild-type mice. Conclusions— Elevated Ang II induced hypertension, myocardial hypertrophy, fibrosis, and diastolic dysfunction, which were exacerbated by ACE2 deficiency, whereas rhACE2 attenuated Ang II– and pressure-overload–induced adverse myocardial remodeling. Hence, ACE2 is an important negative regulator of Ang II–induced heart disease and suppresses adverse myocardial remodeling.
2D and 3D Multiscale/Multicomponent Modeling of Impact Response of Heterogeneous Energetic Composites

Abstract : The objective of this project as modified and approved by DTRA is to develop a new scientific framework and technical capability for the computational analyses and design of the thermal mechanical behavior of energetic composite materials under dynamic impact loading. The model material system polymer bonded explosives (PBX). The capability to be developed goes beyond what is available at the present. Due to the reduced level of funding available relative to the level in the original proposal, we have made certain changes in the scope of the work. The characteristics of the framework and capability include (1) focus on our state-of-the-art2D CFEM computational framework, (2) account of fully dynamic finite deformation kinetics and kinematics, (3) tracking of microstructural level fracture, failure, shear banding, contact and frictional heating, (4) account for the coupling between mechanical deformation and thermal generation and conduction, (5) account for the initiation of energetic reactions in dynamically deforming heterogeneous materials, (6) characterization of the stochastic variations in ignition behavior, and (7) three-dimensional (3D) modeling will primarily focus on the effect of anisotropic crystalline plastic response (slip) on the dissipation mechanisms in HMX granule aggregates.
Metal/ceramic composites from freeze-cast preforms: domain structure and mechanical properties

Domain level mechanical properties of innovative metal/ceramic composites produced by melt infiltration of freeze-cast ceramic performs have been examined. Individual domains exhibit pronounced elastic-plastic anisotropy. The highest stiffness and strength are observed in the direction parallel to the preform freezing direction. Analysis of processing induced thermal residual stress and internal load transfer were studied using energy dispersive syncjrotron X-ray diffarction.
An assessment of CFD applied to a catalytic converter system with planar diffuser

Catalytic converters are widely used in the automotive industry to comply with increasingly stringent emissions regulations. The flow distribution across the catalyst substrate significantly affects its conversion efficiency. Measuring the flow in a catalyst system is challenging; computational fluid dynamics (CFD) provides an alternative approach for the assessment of different design concepts and is therefore commonly employed to model flow behaviour. This thesis studies the application of CFD to modelling flow in a two-dimensional system consisting of a catalyst monolith downstream of a wide-angled planar diffuser, with total included angle 60°. Computational models are developed using the commercial CFD software STAR-CCM+. Flow predictions are compared to experimental data collected by Mat Yamin, (2012) and also as part of this study. Measurements were obtained on a two-dimensional isothermal flow rig using particle image velocimetry (PIV) and hot-wire anemometry (HWA). Steady flow studies compare different methods of modelling the monolith. Models include the common approach of modelling the monolith as a porous medium and the computationally expensive individual channels model. A hybrid model is developed that combines the two approaches, benefiting from the respective merits of each method. Two monolith lengths are considered, with flow at varying Reynolds numbers. The porous model predicts the downstream velocity profile well for the shorter monolith but overpredicts flow maldistribution for the longer monolith. The inclusion of an entrance effect to account for the pressure losses associated with oblique entry into the monolith channels is studied. Best agreement in downstream velocity is observed when the pressure losses are limited using a critical angle approach. The individual channels model is found to be the most consistently accurate across monolith lengths, attributable to the accurate capture of flow behaviour upon entry into the monolith channels. A novel hybrid model is proposed, which combines the computational efficiency of the porous model with the geometrical accuracy of individual channels. The model is evaluated and is found to provide results similar to the individual channels model, with
Comparative Analysis of Linear Portfolio Rebalancing Strategies: An Application to Hedge Funds

This paper applies formal risk management methodologies to optimization of a portfolio of hedge funds (fund of funds). We compare recently developed risk management methodologies: Conditional Value-at-Risk and Conditional Drawdown-at- Risk with more established Mean-Absolute Deviation, Maximum Loss, and Market Neutrality approaches. The common property of considered risk management techniques is that they admit the formulation of a portfolio optimization model as a linear programming (LP) problem. LP formulations allow for implementing efficient and robust portfo lio allocation algorithms, which can successfully handle optimization problems with thousands of instruments and scenarios. The performance of various risk constraints is investigated and discussed in detail for in-sample and out-of-sample testing of the algorithm. The numerical experiments show that imposing risk constraints may improve the "real" performance of a portfolio rebalancing strategy in out -of-sample runs. It is beneficial to combine several types of risk constraints that control different sources of risk.
A Lossless Cache Compression Algorithm for Parallel Compression of Multiple Words and to Reduce Decompression Overhead

With the increasing speeds of processor performance gap between processor and memory is increasing . Access latency of off-chip memory is more than that of on chip memory. Effective utilization of on chip memory is an important issue. We present a lossless microprocessor cache compression algorithm. The algorithm has features like parallel compression and decompression of multiple words. It uses single dictionary for the compression of multiple words. Parallel decompression of multiple words greatly reduces the decompression overhead. I. Introduction RAM speeds are much slower compared to CPU speeds. Full efficiency of the CPU can't be utilized by accessing off-chip RAM. Off-chip communication should be reduced to attain full efficiency of CPU.We need to device a method which can effectively utilize the on chip cache. Cache compression presents several challenges. First, decompression and compression must be extremely fast i.e method itself should not increase cache hit latency. Second, the hardware should occupy little area compared to the corresponding decrease in the physical size of the cache memory, and should not substantially increase the total chip power consumption. Third, the algorithm should losslessly compress data. The above requirements prevent the use of high-overhead compression algorithms such as the PPM family of algorithms[7] or Burrows-Wheeler transforms [8]. A faster and lower-overhead technique is required.
Regularized Independent Component Analysis in Face Verification

A regularized Independent Component Analysis (denoted as RICA) is proposed in the application of face verification. In RICA, information of correlation coefficients between images is employed to form a Laplacian matrix. This Laplacian matrix is used for locating localized features through regularizing the facial data before independent component analysis (ICA) feature extraction. Since there are two different architectures of ICA (ICA I and ICA II), RICA is implemented on these two architectures, namely RICA_ICA I and RICA_ICA II, respectively. Two face datasets are adopted to access the effectiveness of the proposed techniques. The databases are Facial Recognition Technology (FERET) and CMU Pose, Illumination, and Expression (CMU PIE). From the experimental results, it is demonstrated that the both proposed techniques, RICA_ICA I and RICA_ICA II, are able to show its superiority in face verification.
Understanding the needs of vulnerable prisoners: the role of social and emotional wellbeing.

PURPOSE Social and emotional wellbeing (SEWB) is a term used to refer to the state of an individual's overall wellbeing. This review aims to consider the importance of understanding and assessing SEWB in prisoner populations, and identify potentially important differences between groups of prisoners, including those who identify as from minority cultural backgrounds (Aboriginal and Torres Strait Islander in Australia), protective custody prisoners, remand prisoners, prisoners identified with an intellectual disability, and prisoners with an acquired brain injury. DESIGN/METHODOLOGY/APPROACH The paper is a general review of the published literature, with a specific focus on work conducted with Aboriginal and Torres Strait Islander communities in Australia. FINDINGS Eight domains of SEWB are identified across which Aboriginal and Torres Strait Islander prisoners, along with those in protection units, remandees, and prisoners with intellectual disabilities or acquired brain injuries are likely to experience particularly low levels of functioning. Few programs have been developed to address these needs, although attending to low levels of SEWB has the potential to make a positive contribution to prisoner health, prison management, and offender rehabilitation. ORIGINALITY/VALUE Relatively little literature has considered this topic previously and, as a result, the paper is necessarily descriptive. Nonetheless, issues of SEWB appear to warrant further consideration, particularly in relation to those prisoners who identify with minority cultural groups.
A general method for deriving output resistances of serial fixed type switched-capacitor power supplies

A simple method for deriving analytically the output resistance of switched-capacitor (SC) power supplies is presented. By using the proposed method, the output resistances of the serial fixed type SC transformers are derived as a general case. The obtained output resistances are exactly equal to those using the conventional method.
Active Estimation of F-Measures

We address the problem of estimating the Fα-measure of a given model as accurately as possible on a fixed labeling budget. This problem occurs whenever an estimate cannot be obtained from held-out training data; for instance, when data that have been used to train the model are held back for reasons of privacy or do not reflect the test distribution. In this case, new test instances have to be drawn and labeled at a cost. An active estimation procedure selects instances according to an instrumental sampling distribution. An analysis of the sources of estimation error leads to an optimal sampling distribution that minimizes estimator variance. We explore conditions under which active estimates of Fα-measures are more accurate than estimates based on instances sampled from the test distribution.
The Impact of Democratization on the Formation of Trade Blocs

Although there is evidence that domestic politics matter for the formation of preferential trade agreements, the impact of large-scale changes in political institutions, especially in the direction of democratization, on economic integration has been given surprisingly short shrift in the previous literature. This study takes a first step toward developing such an explanation. It posits that, at least under certain conditions, the process of democratization constitutes an important factor in the formation of regional arrangements. Specifically, when compared to unilateral and multilateral trade liberalization, forming a regional integration arrangement involves lower political costs for decision-makers. Thus, if moving towards democratic regimes forces political leaders to implement trade liberalization, the decision to form a regional trade agreement is usually the easiest and the most feasible to execute. Moreover, in presence of cluster of democratization in a given historical period several neighbouring countries are likely to share the same interest in liberalizing trade, thereby easing the bargaining process, which generally represents the main obstacle to the formation of a regional integration arrangement. This paper quantitatively tests the previous hypothesis using an original dataset that covers twenty Latin America countries from 1991 to 2000. Empirical results support the argument.
Word Sense Disambiguation: An Overview

Word sense disambiguation is a subfield of computational linguistics in which computer systems are designed to determine the appropriate meaning of a word as it appears in the linguistic context. This article provides a survey of what has been done in this area: the ways that word meaning can be represented in the computer, the approaches taken by systems, how performance is evaluated and an overview of the intended applications that might benefit from this technology. One of the major issues has been, and still remains, that of finding an appropriate computational representation of word meaning as this is fundamental to the performance and utility of systems.
Holistic SparseCNN: Forging the Trident of Accuracy, Speed, and Size

Phenomenally successful in practical inference problems, convolutional neural networks (CNN) are widely deployed in mobile devices, data centers, and even supercomputers. The number of parameters needed in CNNs, however, are often large and undesirable. Consequently, various methods have been developed to prune a CNN once it is trained. Nevertheless, the resulting CNNs offer limited benefits. While pruning the fully connected layers reduces a CNN's size considerably, it does not improve inference speed noticeably as the compute heavy parts lie in convolutions. Pruning CNNs in a way that increase inference speed often imposes specific sparsity structures, thus limiting the achievable sparsity levels. We present a method to realize simultaneously size economy and speed improvement while pruning CNNs. Paramount to our success is an efficient general sparse-with-dense matrix multiplication implementation that is applicable to convolution of feature maps with kernels of arbitrary sparsity patterns. Complementing this, we developed a performance model that predicts sweet spots of sparsity levels for different layers and on different computer architectures. Together, these two allow us to demonstrate 3.1--7.3$\times$ convolution speedups over dense convolution in AlexNet, on Intel Atom, Xeon, and Xeon Phi processors, spanning the spectrum from mobile devices to supercomputers. We also open source our project at this https URL.
Rate of Convergence in Approximating the Spectral Factor of Regular Stochastic Sequences

Common methods for the calculation of the spectral factorization rely on an approximation of the given spectral density by a polynomial and a subsequent factorization of this polynomial. It is known that the regularity of the stochastic sequence determines the achievable approximation rate of its spectrum. However, since the approximative polynomial should be factorized, it has to be positive. It is shown that this restriction on the approximation polynomial implies a limitation on the approximation rate for linear methods whereas for nonlinear methods the optimal approximation rate can still be achieved. This has also consequences for the rate of convergence of the spectral factor, which is investigated in the second part. There, a lower and an upper bound for the error in the spectral factor is derived, which shows the dependency on the approximation degree and on the regularity of the stochastic sequence. Finally, if the spectral density is given only on a finite set of sampling points, no linear approximation method exists such that the error in the spectral factor can be controlled by the approximation degree.