Miracle-dz/UniFAR-FTUs huggingface dataset:
Retinoic Acid Receptors Control Spermatogonia Cell-Fate and Induce Expression of the SALL4A Transcription Factor

All-trans retinoic acid (ATRA) is instrumental to male germ cell differentiation, but its mechanism of action remains elusive. To address this question, we have analyzed the phenotypes of mice lacking, in spermatogonia, all rexinoid receptors (RXRA, RXRB and RXRG) or all ATRA receptors (RARA, RARB and RARG). We demonstrate that the combined ablation of RXRA and RXRB in spermatogonia recapitulates the set of defects observed both upon ablation of RAR in spermatogonia. We also show that ATRA activates RAR and RXR bound to a conserved regulatory region to increase expression of the SALL4A transcription factor in spermatogonia. Our results reveal that this major pluripotency gene is a target of ATRA signaling and that RAR/RXR heterodimers are the functional units driving its expression in spermatogonia. They add to the mechanisms through which ATRA promote expression of the KIT tyrosine kinase receptor to trigger a critical step in spermatogonia differentiation. Importantly, they indicate also that meiosis eventually occurs in the absence of a RAR/RXR pathway within germ cells and suggest that instructing this process is either ATRA-independent or requires an ATRA signal originating from Sertoli cells.
IPC-Based Cache Partitioning: An IPC-Oriented Dynamic Shared Cache Partitioning Mechanism

In a chip-multiprocessor with a shared cache structure, the last level cache is shared by multiple applications executing simultaneously. The competing accesses from different applications degrade the system performance, resulting in non-predicting executing time. Cache partitioning techniques partition the shared cache for multiple applications. The aim of traditional cache partitioning mechanism, Utility-based Cache Partition (UCP) for example, is to lower the overall miss rate of shared cache. But the lowest miss rate doesn't mean the highest performance (IPC). This paper investigates IPC-based Cache Partitioning (IPC-CP), an IPC performance oriented dynamic cache partitioning method. We design a Miss Rate Monitor to collect miss rate information of competing applications at run-time. Then the information collected is inputted to a Miss-Rate to IPC model to get the corresponding IPC performance. Lastly, we get the optimal cache partitioning based on IPC optimum objective function. Our evaluation, on top of a four cores CMP processor with 20 multi-programmed workloads shows that IPC-CP improves throughput by up to 53% and on average 9% over UCP.
Text-independent speaker identification

We describe current approaches to text-independent speaker identification based on probabilistic modeling techniques. The probabilistic approaches have largely supplanted methods based on comparisons of long-term feature averages. The probabilistic approaches have an important and basic dichotomy into nonparametric and parametric probability models. Nonparametric models have the advantage of being potentially more accurate models (though possibly more fragile) while parametric models that offer computational efficiencies and the ability to characterize the effects of the environment by the effects on the parameters. A robust speaker-identification system is presented that was able to deal with various forms of anomalies that are localized in time, such as spurious noise events and crosstalk. It is based on a segmental approach in which normalized segment scores formed the basic input for a variety of robust 43% procedures. Experimental results are presented, illustrating 59% the advantages and disadvantages of the different procedures. 64%. We show the role that cross-validation can play in determining how to weight the different sources of information when combining them into a single score. Finally we explore a Bayesian approach to measuring confidence in the decisions made, which enabled us to reject the consideration of certain tests in order to achieve an improved, predicted performance level on the tests that were retained. <<ETX>>
USMI: An Ultra-Node Selection Mechanism with Incentive in P2P Network

The performance of P2P networks have decreased severely because of the large number of free-riders. How to incentive nodes to provide service is an important factor to improve the performance of P2P networks. A novel ultra-node selection mechanism with incentive called USMI is presented in this paper. The main contributions of USMI are following: 1) any node in USMI has a value called utility. The utility integrates the parameters including physical capability, voluntary and anticipation to future, differing from the general ultra-node selection which is only based on physical capability and unconsidered free-riding. The ultra-nodes is selected based on the utility value; 2) the ultra-nodes are endow with supervising privilege and they can identify and prevent the free-riders through the parameter of voluntary; 3) the probability of supervising is calculated based on game theory. It’s been shown that USMI increases the total number of file shared, improves the file querying success rate, decreases the average querying hops, and ensures the cost is small at the same time in the Simulation experiments. The ultra-node overlay of USMI is steady and robust.
OncoSearch: cancer gene search engine with literature evidence

In order to identify genes that are involved in oncogenesis and to understand how such genes affect cancers, abnormal gene expressions in cancers are actively studied. For an efficient access to the results of such studies that are reported in biomedical literature, the relevant information is accumulated via text-mining tools and made available through the Web. However, current Web tools are not yet tailored enough to allow queries that specify how a cancer changes along with the change in gene expression level, which is an important piece of information to understand an involved gene's role in cancer progression or regression. OncoSearch is a Web-based engine that searches Medline abstracts for sentences that mention gene expression changes in cancers, with queries that specify (i) whether a gene expression level is up-regulated or down-regulated, (ii) whether a certain type of cancer progresses or regresses along with such gene expression change and (iii) the expected role of the gene in the cancer. OncoSearch is available through http://oncosearch.biopathway. org.
mammalian brain UTRs in the ′ Widespread and extensive lengthening of 3 Material

Material Supplemental http://genome.cshlp. org/content/suppl/2013/03/12/gr.146886. 112.DC1. html P<P Published online March 21, 2013 in advance of the print journal. License Commons Creative . http://creativecommons.org/licenses/by-nc/3.0/ described at as a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), ). After six months, it is available under http://genome.cshlp. org/site/misc/terms.xhtml for the first six months after the full-issue publication date (see This article is distributed exclusively by Cold Spring Harbor Laboratory Press
Functional Integration between Salience and Central Executive Networks: A Role for Action Video Game Experience

Action video games (AVGs) have attracted increasing research attention as they offer a unique perspective into the relation between active learning and neural plasticity. However, little research has examined the relation between AVG experience and the plasticity of neural network mechanisms. It has been proposed that AVG experience is related to the integration between Salience Network (SN) and Central Executive Network (CEN), which are responsible for attention and working memory, respectively, two cognitive functions essential for AVG playing. This study initiated a systematic investigation of this proposition by analyzing AVG experts' and amateurs' resting-state brain functions through graph theoretical analyses and functional connectivity. Results reveal enhanced intra- and internetwork functional integrations in AVG experts compared to amateurs. The findings support the possible relation between AVG experience and the neural network plasticity.
Notch-1 Signaling Promotes the Malignant Features of Human Breast Cancer through NF-κB Activation

The aberrant activation of Notch-1 signaling pathway has been proven to be associated with the development and progression of cancers. However, the specific roles and the underlying mechanisms of Notch-1 signaling pathway on the malignant behaviors of breast cancer are poorly understood. In this study, using multiple cellular and molecular approaches, we demonstrated that activation of Notch-1 signaling pathway promoted the malignant behaviors of MDA-MB-231 cells such as increased cell proliferation, colony formation, adhesion, migration, and invasion, and inhibited apoptosis; whereas deactivation of this signaling pathway led to the reversal of the aforementioned malignant cellular behaviors. Furthermore, we found that activation of Notch-1 signaling pathway triggered the activation of NF-κB signaling pathway and up-regulated the expression of NF-κB target genes including MMP-2/-9, VEGF, Survivin, Bcl-xL, and Cyclin D1. These results suggest that Notch-1 signaling pathway play important roles in promoting the malignant phenotype of breast cancer, which may be mediated partly through the activation of NF-κB signaling pathway. Our results further suggest that targeting Notch-1 signaling pathway may become a newer approach to halt the progression of breast cancer.
Evaluation of trade-offs in the design of embedded systems via co-simulation

Current design methodologies for embedded systems often force the designer to evaluate early in the design process architectural choices that will heavily impact the cost and performance of the final product. Examples of these choices are hardware/software partitioning, choice of the micro-controller, and choice of a run-time scheduling method. This paper describes how to help the designer in this task, by providing a flexible co-simulation environment in which these alternatives can be interactively evaluated. Our approach is based on the Ptolemy co-simulation framework, but it uses a different modeling paradigm, well suited for control-dominated reactive systems (asynchronous extended Finite State Machines called CFSMs). We build on previous research on software synthesis and cost estimation to provide the designer with fast but reasonably accurate performance data. We demonstrate the effectiveness of the approach by showing the result of the trade-off analysis on a dashboard control system.
The RNA Polymerase PB2 Subunit of Influenza A/HongKong/156/1997 (H5N1) Restrict the Replication of Reassortant Ribonucleoprotein Complexes

Background Genetic reassortment plays a critical role in the generation of pandemic strains of influenza virus. The influenza virus RNA polymerase, composed of PB1, PB2 and PA subunits, has been suggested to influence the efficiency of genetic reassortment. However, the role of the RNA polymerase in the genetic reassortment is not well understood. Methodology/Principal Findings Here, we reconstituted reassortant ribonucleoprotein (RNP) complexes, and demonstrated that the PB2 subunit of A/HongKong/156/1997 (H5N1) [HK PB2] dramatically reduced the synthesis of mRNA, cRNA and vRNA when introduced into the polymerase of other influenza strains of H1N1 or H3N2. The HK PB2 had no significant effect on the assembly of the polymerase trimeric complex, or on promoter binding activity or replication initiation activity in vitro. However, the HK PB2 was found to remarkably impair the accumulation of RNP. This impaired accumulation and activity of RNP was fully restored when four amino acids at position 108, 508, 524 and 627 of the HK PB2 were mutated. Conclusions/Significance Overall, we suggest that the PB2 subunit of influenza polymerase might play an important role for the replication of reassortant ribonucleoprotein complexes.
An active power synchronizing controller for grid-connected power converters with configurable natural droop characteristics

Improving the dynamics of the widely applied grid-connected power converters has been drawing a lot of interests in recent years. Since the currently installed grid-connected converters doesn't shown inertia effect in power processing, the lack of inertia in the electrical networks will become increasingly significant and less admissible when more and more renewable energy sources penetrate into the grid through grid-connected converters. An active power synchronizing controller for grid-connected power converters with configurable natural droop characteristics is proposed in this paper. The proposed controller is able to incorporate inertia, damping and configurable natural droop effect in the dynamics of the controlled converter. And in addition to the inertia characteristics, the droop and damping behaviors are discussed in detail. By a modified form of the swing equation of the synchronous generators, the droop behavior can be properly configured without undermining the damping characteristics. Experimental results are shown to validate the proposed controller.
Breakdown of adiabatic invariance in spherical tokamaks

Due to the weak but strongly varying magnetic field, fast ions in spherical tokamaks are susceptible to the breakdown of adiabatic invariance. Beam ions in present-day spherical tokamaks are typically marginally adiabatic or super-adiabatic. Super-adiabatic ions have energies in the intermediate range where the longitudinal invariant is still adiabatically invariant, but the magnetic moment is not, and their motion is integrable. Fusion alphas in proposed burning-plasma experiments would, however, to a large extent be nonadiabatic, and follow chaotic orbits.
A methodology for evaluating the impact of data compression on climate simulation data

High-resolution climate simulations require tremendous computing resources and can generate massive datasets. At present, preserving the data from these simulations consumes vast storage resources at institutions such as the National Center for Atmospheric Research (NCAR). The historical data generation trends are economically unsustainable, and storage resources are already beginning to limit science objectives. To mitigate this problem, we investigate the use of data compression techniques on climate simulation data from the Community Earth System Model. Ultimately, to convince climate scientists to compress their simulation data, we must be able to demonstrate that the reconstructed data reveals the same mean climate as the original data, and this paper is a first step toward that goal. To that end, we develop an approach for verifying the climate data and use it to evaluate several compression algorithms. We find that the diversity of the climate data requires the individual treatment of variables, and, in doing so, the reconstructed data can fall within the natural variability of the system, while achieving compression rates of up to 5:1.
Two results on interactive lossless source encoding and decoding with side information at the decoder

Slepian and Wolf proposed and analyzed a ground-breaking paradigm of source coding for a source network in which a finite alphabet source X is to be encoded and transmitted to the decoder, and another finite alphabet source Y correlated with X is available only to the decoder as a helper, or in other words, the side information. In Slepian and Wolf's paradigm, which is now commonly referred to as Slepian-Wolf (SW) coding, information flow is one-way from the encoder to the decoder, and no interaction is allowed between them.In this paper, we consider a paradigm of source coding called interactive encoding and decoding (IED). The paper answers the question: what can be gained by IED over SW coding?
On sorting strings in external memory (extended abstract)

In this paper we address for the first time the I/O complexity of the problem of sorting strings in external memory, which is a fundamental component of many large-scale text applications. In the standard unit-cost RAM comparison model, the complexity of sorting K strings of total length N is (K log2K+N). By analogy, in the external memory (or I/O) model, where the internal memory has size M and the block transfer size is B, it would be natural to guess that the I/O complexity of sorting strings is (KB logM=B KB + NB ), but the known algorithms do not come even close to achieving this bound. Our results show, somewhat counterintuitively, that the I/O complexity of string sorting depends upon the length of the strings relative to the block size. We first consider a simple comparison I/O model, where one is not allowed to break the strings into their characters, and we show that the I/O complexity of string sorting in this model is (N1 B logM=B N1 B +K2 logM=BK2+NB ), whereN1 is the total length of all strings shorter than B andK2 is the number of strings longer than B. We then consider two more general I/O comparison models in which string breaking is allowed. We obtain improved algorithms and in several cases lower bounds that match their I/O bounds. Finally, we develop more practical algorithms without assuming the comparison model. Department of Computer Science, Duke University, Durham, NC 27708–0129, USA. Email: large@cs.duke. edu. Supported in part by the U.S. Army Research Office under grant DAAH04–96–1–0013 and by the ESPRIT Long Term Research Programme under project 20244 (ALCOM–IT). Part of this work was done while at BRICS, Dept. of Computer Science, University of Aarhus, Denmark, and while visiting Universita di Firenze. y Dipartimento di Informatica, Universita di Pisa, Pisa, Italy. Email: ferragin@di.unipi. it. Supported in part by MURST of Italy. z Dipartimento di Sistemi e Informatica, Universita di Firenze, Firenze, Italy. Email: grossi@dsi2.dsi. unifi.it. Part of this work was done while visiting BRICS, University of Aarhus, Denmark. x Department of Computer Science, Duke University, Durham, NC 27708–0129, USA. Email: jsv@cs.duke. edu. Supported in part by the U.S. Army Research Office under grants DAAH04–93–G–0076 and DAAH04–96–1–0013 and by the National Science Foundation under grant CCR–9522047.
Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations

Many machine vision applications, such as compression, pictorial database querying, and image understanding, often need to analyze in detail only a representative subset of the image, which may be arranged into sequences of loci called regions-of-interest (ROIs). We have investigated and developed a methodology that serves to automatically identify such a subset of aROIs (algorithmically detected ROIs) using different image processing algorithms (IPAs), and appropriate clustering procedures. In human perception, an internal representation directs top-down, context-dependent sequences of eye movements to fixate on similar sequences of hROIs (human identified ROIs). In the paper, we introduce our methodology and we compare aROIs with hROIs as a criterion for evaluating and selecting bottom-up, context-free algorithms. An application is finally discussed.
HPV Genotyping and Site of Viral Integration in Cervical Cancers in Indian Women

Persistent HPV infection plays a major role in cervical cancer. This study was undertaken to identify HPV types in a cohort of Indian women with locally advanced cervical cancer as well as to determine the physical state and/or site of viral integration in the host genome. Pretreatment biopsies (n = 270) from patients were screened for HPV infection by a high throughput HPV genotyping assay based on luminex xMAP technology as well as MY09/11 PCR and SPF1/2 PCR. Overall HPV positivity was observed to be 95%, with HPV16 being most common (63%) followed by infection with HPV18. Integration status of the virus was identified using Amplification of Papillomavirus Oncogene Transcripts (APOT) assay in a subset of samples positive for HPV16 and/or HPV18 (n = 86) and with an adequate follow-up. The data was correlated with clinical outcome of the patients. Integration of the viral genome was observed in 79% of the cases and a preference for integration into the chromosomal loci 1p, 3q, 6q, 11q, 13q and 20q was seen. Clinical data revealed that the physical state of the virus (integrated or episomal) could be an important prognostic marker for cervical cancer.
Efficient RAID Disk Scheduling on Smart Disks

With the emerging high-performance storage systems as well as the availability of faster processors and high-speed networks, many applications that were only dreams a few years ago, have become reality. For example, Digital Libraries and Digital Medical Imaging Archive Systems have become available today. Many of these new applications are making great impacts on the way we work and the way we live. Among the supporting technologies, a high-performance storage system is one of the most critical factors in these systems.
Adaptive Performance Monitoring for Embedded Multicore Systems

With the advent of multicore processors, the performance of software has been elevated to new unforeseen heights via parallelization. However, this has not been achieved without new problems cropping up due to parallelization. One serious issue is the performance bottleneck due to cache misses or resource starvation, which is hard to detect in application software especially when the software has dynamically changing behavior. Performance monitors are usually employed for such purposes. Nevertheless, monitors have introduced their own computation and communication overheads, especially in embedded multicore systems. In this work, we try to estimate the effects of monitor overheads on different types of applications, such as CPU-bound and IO-bound tasks. Further, we give suggestions on the number and type of monitors to use for such embedded multicore applications. Besides trying to reduce monitor overheads, we also aim for the accuracy and the immediacy of the monitored information. Through a real-world example, namely digital video recording system, we demonstrate how different monitoring periods affect the tradeoff between accuracy and immediacy of the monitored information.
Financial Classification Using an Artificial Immune System

Recent years have seen a dramatic increase in the application of biologically-inspired algorithms to business problems. Applications of neural networks and evolutionary algorithms have become common. However, as yet there have been few applications of artificial immune systems (AIS), algorithms that are inspired by the workings of the natural immune system. The natural immune system can be considered as a distributed, self-organizing, classification system that operates in a dynamic environment. The mechanisms of natural immune systems, including their ability to distinguish between self and non-self, provides a rich metaphorical inspiration for the design of patternrecognition algorithms. This chapter introduces AIS and provides an example of how an immune algorithm can be used to develop a classification system for predicting IDEA GROUP PUBLISHING This paper appears in the book, Business Applications and Computational Intelligence edited by Kevin E. Voges and Nigel K. L. Pope © 2006, Idea Group Inc. 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com ITB12012 Artificial Immune System 389 Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. corporate failure. The developed system displays good classification accuracy out-ofsample, up to two years prior to failure.