Miracle-dz/UniFAR-FTUs huggingface dataset:
TNIP1, a Retinoic Acid Receptor Corepressor and A20-binding Inhibitor of NF-κB, Distributes to Both Nuclear and Cytoplasmic Locations

An increasingly wide range of functions, from repression of NF-κB signaling to protection from apoptosis, is being recognized for tumor necrosis factor α–induced protein 3-interacting protein 1 (TNIP1). The authors recently demonstrated TNIP1 interaction with and repression of liganded retinoic acid receptors, distinguishing it from the more typical NCoR and SMRT corepressors, which function only in the absence of ligand. To improve their understanding of TNIP1’s roles in physiologic and pathologic events, the authors examined its distribution in normal and malignant human tissues and cultured cells. They found cytoplasmic and nuclear TNIP1 in normal skin keratinocytes as it colocalized with retinoic acid receptor α, one of the nuclear receptors it corepresses. Nuclear and cytoplasmic TNIP1 was also found in the malignant keratinocytes of squamous cell carcinomas. Compared to adjacent normal tissues of other organs, TNIP1 staining and distribution varied with increased levels in esophageal cancer and marked decreases in prostate cancer. The varying levels and distribution of TNIP1 in normal and disease state tissues could be expected to affect processes in which TNIP1 is involved, such as NF-κB and nuclear receptor signaling, possibly contributing to the disease course or response to therapies targeting these key players of cell growth and differentiation.
On the capacity-achieving distribution of the discrete-time noncoherent and partially coherent AWGN channels

We investigate the communication limits over rapid phase-varying channels and consider the capacity of a discrete- time noncoherent additive white Gaussian noise (NCAWGN) channel under the average power constraint. We obtain necessary and sufficient conditions for the capacity-achieving input distribution and show that this distribution is discrete and possesses an infinite number of mass points. Using this characterization of the capacity-achieving distribution we compute a tight lower bound on the capacity of the channel based on examining suboptimal input distributions. In addition, we provide some easily computable lower and upper bounds on the channel capacity. Finally, we extend some of these results to the partially coherent channel, where it is assumed that a phase-locked loop (PLL) is used to track the carrier phase at the receiver, and that an ideal interleaver and de-interleaver are employed-rendering the Tikhonov distributed residual phase errors statistically independent from one symbol interval to another.
Extending the reach and power of deductive program verification

Software is vital for modern society. The efficient development of correct and reliable software is of ever-growing importance. An important technique to achieve this goal is deductive program verification: the construction of logical proofs that programs are correct. In this thesis, we address three important challenges for deductive verification on its way to a wider deployment in the industry: 1. verification of thread-based concurrent programs 2. correctness management of verification systems 3. change management in the verification process. These are consistently brought up by practitioners when applying otherwise mature verification systems. The three challenges correspond to the three parts of this thesis (not counting the introductory first part, providing technical background on the KeY verification approach). In the first part, we define a novel program logic for specifying correctness properties of object-oriented programs with unbounded thread-based concurrency. We also present a calculus for the above logic, which allows verifying actual Java programs. The calculus is based on symbolic execution resulting in its good understandability for the user. We describe the implementation of the calculus in the KeY verification system and present a case study. In the second part, we provide a first systematic survey and appraisal of factors involved in reliability of formal reasoning. We elucidate the potential and limitations of self-application of formal methods in this area and give recommendations based on our experience in design and operation of verification systems. In the third part, we show how the technique of similarity-based proof reuse can be applied to the problems of industrial verification life cycle. We address issues (e.g., coping with changes in the proof system) that are important in verification practice, but have been neglected by research so far.
Resolution-Based Execution of Description Logics Programs for Instance-Retrieval

This paper compares two resolution-based ABox reasoning te chniques over the description logic languageALC. Queries are executed in a Prolog-framework using the PTTP ( Prolog Technology Theorem Proving) approach. The aim of these reasonin g algorithms is to efficiently answer instance-check and instance-retrieval queries when large mounts of data are stored in the ABox. We describe two approaches of transforming a DL knowledge-b ase to Prolog clauses. A case study highlights the usage of these techniques in practice.
Privacy Enhancing Technologies for RFID – A Critical State-ofthe-Art Report

Radio Frequency Identification (RFID) is a technology that allows for automatic and remote identification of objects and is currently discussed as one of the most important technical enablers of Pervasive Computing, boosting economic processes and home computing applications. However, as far as privacy is concerned RFID is still in its ‘kindershoes’. A public outcry as to the privacy and security limitations of RFID has fostered the development of myriad privacy enhancing proposals. In this article we review and categorize the state-of–the-art of research work in this domain. We compare proposed solutions from a technological and economic point of view and we critically review their ability to give users real control over their privacy vis-à-vis RFID readers. Considering over 200 scientific publications in the field we come to the conclusion that the most promising and low cost approach does hardly get any attention from academia.
Comparison of plasma virus loads among individuals infected with hepatitis C virus (HCV) genotypes 1, 2, and 3 by quantiplex HCV RNA assay versions 1 and 2, Roche Monitor assay, and an in-house limiting dilution method

The accuracy of different methods for the quantitation of hepatitis C virus in plasma was measured with samples from individuals infected with different genotypes and by using RNA transcripts of predetermined concentrations. Highly reproducible results were observed upon repeat testing of samples by both the original version of the Chiron branched-DNA (bDNA) assay (Quantiplex RNA assay; bDNA-1) and the currently available version (Quantiplex HCV RNA 2.0 assay; bDNA-2). A greater variability was observed in the Roche Monitor assay (correlation coefficient of 0.537, compared with 0.942 and 0.964 for the bDNA-1 and bDNA-2 assays, respectively). Significant differences in the efficiency of detection of genotypes 1, 2, and 3 were observed for the bDNA-1 and Roche Monitor assays, whereas the bDNA-2 assay and nested PCR at limiting dilution were able to quantify genotypes with equal sensitivity. By quantifying RNA transcripts of different genotypes, the sensitivities of the Roche Monitor assay for sequences of the type 2 and type 3 transcripts were estimated to be 11 and 8% of those achieved for genotype 1. When correction factors based upon these results and those from quantitation of circulating viral RNA sequences in samples from blood donors were used, the genotype-specific differences in virus load in samples from blood donors were no longer observed, consistent with previous studies with corrected values from the bDNA-1 assay. These results suggest that many of the previous studies evaluating the effect of genotype and virus load on the response to interferon using methods such as the Roche Monitor assay and other competitive PCR methods require reinterpretation. Differences in efficiency of quantitation should be taken into account in future investigations of the relationship between genotype and virus load.
The spoken corpus of Cameroon Pidgin English

This article reports on the construction of a 240,000-word pilot corpus of spoken Cameroon Pidgin English (CPE), a widely-used yet stigmatised and largely uncodified written pidgin/creole variety. The corpus consists of private and public dialogues and monologues, with mark-up and POS-tagging. Text categories and the proportions of monologue and dialogue are guided by those of the International Corpus of English project, which makes the corpus immediately comparable with existing corpora of post-colonial varieties of English. We discuss the extent to which this corpus can be regarded as an ICE component, and illustrate the relation between CPE and standardised Nigerian and Cameroonian varieties of English in Africa by means of case studies employing ICE-NIGERIA and the Corpus of Cameroon English.
A novel computationally efficient SMC-PHD Filter using particle-measurement partition

The probability hypothesis density (PHD) filter is widely used to solve multi-target tracking (MTT) problems. Although the Sequential Monte Carlo (SMC) implementation provides a tractable solution for PHD filter to handle the highly nonlinear and non-Gaussian MTT scenario, the high computational cost caused by a large number of particles limits the applications that need to be performed in real-time. This paper proposes a computationally efficient SMC-PHD filter using particle-measurement partition and intermediate region strategy. Firstly, the partition strategy provides a way to solve the related PHD calculation in each partition independently. Secondly, based on the rectangular gating technique, the particle intermediate region strategy ensures the estimation accuracy of the proposed method. The simulation results indicate that the partition strategy significantly reduces the computational complexity of the SMC-PHD filter. In addition, the proposed method can maintain comparable accuracy as the standard SMC-PHD filter via the intermediate region strategy.
Attractive faces temporally modulate visual attention

Facial attractiveness is an important biological and social signal on social interaction. Recent research has demonstrated that an attractive face captures greater spatial attention than an unattractive face does. Little is known, however, about the temporal characteristics of visual attention for facial attractiveness. In this study, we investigated the temporal modulation of visual attention induced by facial attractiveness by using a rapid serial visual presentation. Fourteen male faces and two female faces were successively presented for 160 ms, respectively, and participants were asked to identify two female faces embedded among a series of multiple male distractor faces. Identification of a second female target (T2) was impaired when a first target (T1) was attractive compared to neutral or unattractive faces, at 320 ms stimulus onset asynchrony (SOA); identification was improved when T1 was attractive compared to unattractive faces at 640 ms SOA. These findings suggest that the spontaneous appraisal of facial attractiveness modulates temporal attention.
ROSA: A step torwards a global virtual network

ROSA is an overlay network which, deployed on a network, ensures a endogenous routing more resilient than IP. The ROSA routing detects and bypasses failures of routers, gateways and other underlay physical devices. Once installed on an information system, ROSA is completely autonomous, does not need any additional human intervention for its maintenance. ROSA has been proved scalable since it was shown in previous works that the cost in term of network overhead of the self-healing and self-maintenance of ROSA does not depend of the number of nodes of the overlay network. All these properties make ROSA a candidate for building a sole global virtual network that is astride over many physical networks. ROSA deployed over a large number of different network could unify them and could be the solution for the networks of the years to come and for the next generation Internet.
A speaker driver for single phase supply Class G & I

The paper describes the design and implementation of a speaker driver applied to Class G/Class I with single phase power supply. Gain expanding and compressing technology are employed in signal processing circuit to optimize power dissipation. Experimental results using 0. 18µm N-well CMOS show that it can obtain less than 0.006% THD at low power range and less than 0.4% at medium power range with a 1 KHz sine wave signal. It can get maximum output power of 360mW at a load of 8Ω. The power efficiency is about twice as that of traditional class AB driver at the power range of 80mW and more than 18% improvement at higher power range.
PolyVaccine: Protecting Web Servers against Zero-Day, Polymorphic and Metamorphic Exploits

Today web servers are ubiquitous having become critical infrastructures of many organizations. However, they are still one of the most vulnerable parts of organizations infrastructure. Exploits are many times used by worms to fast propagate across the full Internet being web servers one of their main targets. New exploit techniques have arouse in the last few years that have rendered useless traditional IDS techniques based on signature identification. Exploits use polymorphism (code encryption) and metamorphism (code obfuscation) to evade detection from signature-based IDSs. In this paper, we address precisely the topic of how to protect web servers against zero-day (new), polymorphic, and metamorphic malware embedded in data streams (requests) that target web servers. We rely on a novel technique to detect harmful binary code injection (i.e., exploits) in HTTP requests that is more efficient than current techniques based on binary code emulation or instrumentation of virtual engines. The detection of exploits is done through sandbox processes. The technique is complemented by another set of techniques such as caching, and pooling, to reduce its cost to neglectable levels.Our technique has little assumptions regarding the exploit unlike previous approaches that assume the existence of sled or getPC code, loops, read of the payload, writes to different addresses, etc. The evaluation shows that caching is highly effective and that the average latency introduced by our system is neglectable.
Exploiting Data Semantics to Discover, Extract, and Model Web Sources

We describe Deimos, a system that automatically discovers and models new sources of information.The system exploits four core technologies developed by our group that makes an end-to-end solution to this problem possible. First, given an example source, Deimos finds other similar sources online. Second, it invokes and extracts data from these sources. Third, given the syntactic structure of a source, Deimos maps its inputs and outputs to semantic types. Finally, it infers the source's semantic definition, i.e., the function that maps the inputs to the outputs. Deimos is able to successfully automate these steps by exploiting a combination of background knowledge and data semantics. We describe the challenges in integrating separate components into a unified approach to discovering, extracting and modeling new online sources. We provide an end-to-end validation of the system in two information domains to show that it can successfully discover and model new data sources in those domains.
Picture navigation using an ambient display and implicit interactions

There is increasing demand for ubiquitous displays that react to a user's actions. We propose a method of navigating pictures on an ambient display using implicit interactions. The ambient display can identify the user and measure how far away they are using an RFID reader and ultrasonic sensors. When the user is a long way from the display, it acts as a digital picture and does not attract attention. When the user comes within an appropriate range for interaction, the display shows pictures that are related to the user and provides quasi-3D navigation using the TIP (tour into the picture) method. In addition, menus can be manipulated directly on a touch-screen or remotely using an air mouse. In an emergency, LEDs around the display flash to alert the user.
Physicochemical characteristics of pristine and functionalized graphene

Graphene‐based nanomaterials have received significant attention in the last decade due to their interesting properties. Its electrical and thermal conductivity and strength make graphene well suited for a variety of applications, particularly for use as a composite material in plastics. Furthermore, much work is taking place to utilize graphene as a biomaterial for uses such as drug delivery and tissue regeneration scaffolds. Owing to the rapid progress of graphene and its potential in many marketplaces, the potential toxicity of these materials has garnered attention. Graphene, while simple in its purest form, can have many different chemical and physical properties. In this paper, we describe our toxicity evaluation of pristine graphene and a functionalized graphene sample that has been oxidized for enhanced hydrophilicity, which was synthesized from the pristine sample. The samples were characterized by X‐ray photoelectron spectroscopy, Raman spectroscopy, infrared spectroscopy, thermogravimetric analysis, zeta‐potential, atomic force microscopy and electron microscopy. We discuss the disagreement between the size of imaged samples analyzed by atomic force microscopy and by transmission electron microscopy. Furthermore, the samples each exhibit quite different surface chemistry and structure, which directly affects their interaction with aqueous environments and is important to consider when evaluating the toxicity of materials both in vitro and in vivo. Copyright © 2017 John Wiley & Sons, Ltd.
Spintronics for low-power computing

Microelectronics has been following Moore's law for almost 40 years. However this trend tends to run out of steam in recent technology nodes. The continuous improvements in the size of the transistors and in the operating frequencies result in serious power consumption, heat dissipation and reliability issues. Spintronics (Nobel Prize of Physics, 2007 awarded to Prof. Fert from Univ. Paris-Sud and Peter Grünberg from Forschungszentrum Jülich) nanodevices can reduce significantly the power, improve the reliability or allow new functionalities. The 2010 ITRS report on emerging research devices identified Magnetic Tunnel Junction (MTJ) nanopillar (the preeminent spintronics nanodevice) as one of the most promising technologies to be part of the future microelectronics circuits. It provides data non-volatility, hardness to radiations, fast data access and low-power operations. Magnetic memories become the most promising candidate for both low power logic computing and the data storage. This tutorial paper presents multi-discipline questions (Device, Circuit, Architecture, System and CAD) related to this topic to share the most recent results and discuss the future challenges.
Radon and Lung Cancer in the American Cancer Society Cohort

Background: Case–control studies conducted in North America, Europe, and Asia provided evidence of increased lung cancer risk due to radon in homes. Here, the association between residential radon and lung cancer mortality was examined in a large-scale cohort study. Methods: Nearly 1.2 million Cancer Prevention Study-II participants were recruited in 1982. Mean county-level residential radon concentrations were linked to study participants according to ZIP code information at enrollment [mean (SD) = 53.5 Bq/m3 (38.0)]. Cox proportional hazards regression models were used to obtain adjusted HR and 95% CI for lung cancer mortality associated with radon. Potential effect modification by cigarette smoking, ambient sulfate concentrations, and other risk factors was assessed on both the additive and multiplicative scales. Results: Through 1988, 3,493 lung cancer deaths were observed among 811,961 participants included in the analysis. A significant positive linear trend was observed between categories of radon concentrations and lung cancer mortality (P = 0.02). A 15% (95% CI, 1–31) increase in the risk of lung cancer mortality was observed per 100 Bq/m3 increase in radon. Participants with mean radon concentrations above the EPA guideline value (148 Bq/m3) experienced a 34% (95% CI, 7–68) increase in risk for lung cancer mortality relative to those below the guideline value. Conclusions: This large prospective study showed positive associations between ecological indicators of residential radon and lung cancer. Impact: These results further support efforts to reduce radon concentrations in homes to the lowest possible level. Cancer Epidemiol Biomarkers Prev; 20(3); 438–48. ©2011 AACR.
Auto-Tuning Strategies for Parallelizing Sparse Matrix-Vector (SpMV) Multiplication on Multi- and Many-Core Processors

Because sparse matrix-vector multiplication (SpMV) is an important and widely used computational kernel in many real-world applications, it behooves us to accelerate SpMV on modern multi- and many-core architectures. While many storage formats have been developed to facilitate SpMV operations, the compressed sparse row (CSR) format is still the most popular and general storage format. However, parallelizing CSR-based SpMV on multi- and many-core processors (e.g., CPUs, APUs, GPUs) remains a challenging problem, including dealing with uncoalesced memory access, balancing workload, and identifying the most appropriate parallelizing strategy. In the paper, we propose a novel auto-tuning framework that automatically finds the most efficient parallelizing strategy to achieve high-performance SpMV. Our framework can deter- mine the right binning schemes to group similar workloads into bins (e.g., buckets) with negligible overhead. Then, for each bin, the most suitable kernel is selected to process the rows within. Our framework is input-aware and based on a machine-learning method. The results show that our auto-tuned SpMV performs significantly better than the default SpMV. The speedups on 16 representative matrices range from 1.2x to 52.0x. Compared to the state-of-the-art SpMV kernel, our work yields better performance in most cases, achieving up to a 1.9x speedup.
Efficient Online Sequence Prediction with Side Information

Sequence prediction is a key task in machine learning and data mining. It involves predicting the next symbol in a sequence given its previous symbols. Our motivating application is predicting the execution path of a process on an operating system in real-time. In this case, each symbol in the sequence represents a system call accompanied with arguments and a return value. We propose a novel online algorithm for predicting the next system call by leveraging both context and side information. The online update of our algorithm is efficient in terms of time cost and memory consumption. Experiments on real-world data sets showed that our method outperforms state-of-the-art online sequence prediction methods in both accuracy and efficiency, and incorporation of side information does significantly improve the predictive accuracy.