Miracle-dz/UniFAR-FTUs huggingface dataset:
IL-9 Production by Regulatory T Cells Recruits Mast Cells That Are Essential for Regulatory T Cell-Induced Immune Suppression

Both mast cells (MCs) and regulatory T cells (Tregs) have gained attention as immunosuppressive cell populations. To investigate a possible interaction, we used the Th1- and Th17-dependent model of nephrotoxic serum nephritis (NTS), in which both MCs and Tregs have been shown to play a protective role. Transfer of wild-type (wt) Tregs into wt recipients almost completely prevents development of NTS and leads to a profound increase of MCs in the renal draining lymph nodes (LNs). By contrast, transfer of wt Tregs into animals deficient in MCs, which are characterized by an exaggerated susceptibility to NTS, no longer exhibited protective effects. Blocking the pleiotropic cytokine IL-9, known to be involved in MC recruitment and proliferation, by means of a mAb in mice receiving Tregs abrogated protection from NTS. Moreover, transfer of IL-9–deficient Tregs also failed to protect from NTS. In the absence of Treg-derived IL-9, MCs fail to accumulate in the LNs, despite the fact that IL-9 deficiency does not alter the general suppressive activity of Tregs. In summary, to our knowledge, we provide the first direct in vivo evidence that the nephroprotective, anti-inflammatory effects of Tregs critically depend on IL-9–mediated attraction of MCs into kidney-draining LNs.
An optimization-based method for bounding state functionals of nonlinear stochastic systems

We propose a method for bounding state functionals of a class of nonlinear stochastic differential equations. Given a class of state functionals of a stochastic system, the Feynman-Kac Lemma is a backward in time partial differential equation that describes the evolution of the state functional. We bound these state functionals based on a method which uses barrier functionals. We show that, under the assumption of polynomial data, the bounds can be obtained by using semi-definite programming. The proposed method is then applied to the case study of noise in genetic negative autoregulation to bound a functional of the second moment, which is of specific interest to experimental assays. The bound obtained is found to be in good agreement with experimental results in the literature.
Floors Concept For Studying e-commerce Development: Pertinence With Reference To Tunisian Context

E-commerce development is described in literature with reference to divergent points of views having many insufficiencies. In order to palliate these limits, this paper proposes a new construct, namely floors, corresponding to growing development levels. This construct permits e-commerce development influencing factors analysis. This paper proposes a model specifying factors influencing e-commerce development in Tunisian hospitality sector. A technology-organization-environment model was adopted to model the variables shaping development. Variables maintained in the model are affected to development floors.
MicroSAGE: a modified procedure for serial analysis of gene expression in limited amounts of tissue.

Serial Analysis of Gene Expression (SAGE) is a powerful expression profiling method, allowing the analysis of the expression of thousands of transcripts simultaneously. A disadvantage of the method, however, is the relatively high amount of input RNA required. Consequently, SAGE cannot be used for the generation of expression profiles when RNA is limited, i.e. in small biological samples such as tissue biopsies or microdissected material. Here we describe a modification of SAGE, named microSAGE, which requires 500- to 5000-fold less starting material. Compared with SAGE, microSAGE is simplified due to incorporation of a 'single-tube' procedure for all steps from RNA isolation to tag release. Furthermore, a limited number of additional PCR cycles are performed. Using microSAGE gene expression profiles can be obtained from minute quantities of tissue such as a single hippocampal punch from a rat brain slice of 325 micrometers thickness, estimated to contain, at most, 10(5) cells. This method opens up a multitude of new possibilities for the application of SAGE, for example the characterization of expression profiles in tissue biopsies, tumor metastases or in other cases where tissue is scarce and the generation of region-specific expression profiles of complex heterogeneous tissues.
Understanding the Travel Needs, Behaviour and Aspirations of People in Later Life

This study explores the travel needs, behaviour and aspirations of people as they make the transition into retirement and later life. The objectives of this study were to: Describe older people's current transport needs and behaviours;  Discuss older people's experiences of using transport; Explore the transition into retirement and the attitudes that inform older people's transport behaviours now, and in the past; and Examine the transport aspirations of older people.
Becoming a Professor: an Analysis of Gender on the Promotion of Faculty from Associate to Full Professor

72 1024x768 Normal 0 false false false st1\:*{behavior:url(#ieooui) } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} 72 1024x768 Normal 0 false false false st1\:*{behavior:url(#ieooui) } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} Factors associated with the promotion of associate professors to full professor were evaluated at a land-grant university in the United States of America. In univariable analyses, gender (female), field of study (non-STEM) and highest degree held (non-doctoral) were all associated with decreased odds of being promoted from associate professor to full professor. However in an adjusted analysis, only the highest degree held by the individual seeking promotion and field of study remained associated with promotion from associate professor to full professor. Male and female faculty with non-doctoral degrees in non-STEM fields had similar but decreased odds of promotion to full professor from associate professor. These data indicate that after adjusting for the highest degree held by the individual seeking promotion and the field of study, there was no evidence that gender was associated with decreased odds of promotion from associate to full professor.
Dual REPS: A Generalization of Relative Entropy Policy Search Exploiting Bad Experiences

Policy search (PS) algorithms are widely used for their simplicity and effectiveness in finding solutions for robotic problems. However, most current PS algorithms derive policies by statistically fitting the data from the best experiments only. This means that experiments yielding a poor performance are usually discarded or given too little influence on the policy update. In this paper, we propose a generalization of the relative entropy policy search (REPS) algorithm that takes bad experiences into consideration when computing a policy. The proposed approach, named dual REPS (DREPS) following the philosophical interpretation of the duality between good and bad, finds clusters of experimental data yielding a poor behavior and adds them to the optimization problem as a repulsive constraint. Thus, considering that there is a duality between good and bad data samples, both are taken into account in the stochastic search for a policy. Additionally, a cluster with the best samples may be included as an attractor to enforce faster convergence to a single optimal solution in multimodal problems. We first tested our proposed approach in a simulated reinforcement learning setting and found that DREPS considerably speeds up the learning process, especially during the early optimization steps and in cases where other approaches get trapped in between several alternative maxima. Further experiments in which a real robot had to learn a task with a multimodal reward function confirm the advantages of our proposed approach with respect to REPS.
CpG Hypermethylation of MDR 1 Gene Contributes to the Pathogenesis and Progression of Human Prostate Cancer

Multidrug resistance 1 (MDR1) gene encodes for P-glycoprotein (P-gp), a Mr 170,000 transmembrane calcium-dependent efflux pump that is inactivated in prostate cancer. We hypothesize that inactivation of the MDR1 gene through CpG methylation contributes to the pathogenesis and progression of prostate cancer. To test this hypothesis, CpG methylation status of the MDR1 promoter and its correlation with clinicopathological findings were evaluated in 177 prostate cancer samples and 69 benign prostate hypertrophy (BPH) samples. Cellular proliferation index and apoptotic index were determined by proliferating cell nuclear antigen (PCNA) and single-strand DNA immunostaining, respectively. After 5-aza-2 -deoxycytidine treatment, increased expression of MDR1 mRNA transcript was found in prostate cancer cell lines (DU145, DuPro, and ND1). MDR1 methylation frequency was significantly higher in prostate cancer samples compared with BPH samples (54.8 versus 11.6%, respectively, P < 0.001). Logistic regression analysis revealed that PC patients are 11.5 times more likely to have MDR1 methylation than BPH patients (95% confidence interval 4.87–27.0) and that MDR1 methylation is independent of the age. Significant correlation of MDR1 methylation was observed with high pT category (P < 0.001), high Gleason sum (P 0.008), high preoperative prostate-specific antigen (P 0.01), and advancing pathological features. In addition, PCNA-labeling index were significantly higher in methylation-specific PCR (MSP)-positive than in MSP-negative prostate cancer samples (P 0.048). In contrast, no significant difference in apoptotic index was found between MSP-positive and -negative prostate cancer samples. These findings suggest that CpG hypermethylation of MDR1 promoter is a frequent event in prostate cancer and is related to disease progression via increased cell proliferation in prostate cancer cells.
Friendship relations of Southeast Asian immigrant children in Norway

The main focus and aim of this master thesis is to write about the nature of friendship and experiences of the Southeast Asian immigrant children in Norway. The overall methodological perspective of this study is based on the philosophy of the new social studies of childhood where children are constructed as social actors, listening to their voices, seeing them as active agents in their daily lives who are able to choose their friends and form friendship in their new country. I conducted semi-structured interview and observation with my participants and informal discussion with the parents. I interviewed eight children from ages 8 to 14 years old.In the analysis chapter I discussed about my participant’s idea of friendship or the meaning of the concept for them, I also talked about the activities they do together to nurture the friendship. I wrote down some quotations from my participants to illustrate their own words on the matter. I also discuss ways my participants formed friendship with the other children, and in doing so, it became evident to me that my younger participants form friendship with other children differently than my older participants. I further discuss the differences of friendship relations of my participants across different age groups, factors how they view friendships. I also discussed my participant’s friendship at home, in school and their neighborhood and their parent’s earlier influence on friendship formation. I also talked about my participant’s groups, their experiences of conflicts and disputes with friends. I also talked about gendered friendship because it is an important area to help us understand the nature of children’s friendship.I conclude my research with the results that among the challenges my participants experienced as an immigrant, learning the language spoken in the country where they live is the most important aspect to enable the children to form friendship with other children. My research also documented that my participants are competent children capable of adapting to a new society by learning the language, making new friends and nurture friendship. This thesis therefore confirm the new social studies of childhood where children are social actors who are active agents in their daily lives able to choose their friends and form friendship in their new country.
A DLL-Supported, Low Phase Noise Fractional-N PLL With a Wideband VCO and a Highly Linear Frequency Ramp Generator for FMCW Radars

This paper describes a frequency synthesizer for frequency-modulated continuous wave (FMCW) radars, operating in combination with a frequency multiplier, at 77 GHz. The fractional-N phase-locked loop (PLL)-based synthesizer is equipped with a wideband voltage-controlled oscillator, which is realized with CMOS transistors in a current-reuse technique, and a delay-locked loop (DLL). Utilized as a frequency multiplier for the reference signal, the DLL improves both the phase noise performance of the PLL and the linearity of the frequency sweep generated by the PLL. Two types of voltage-controlled delay lines used in the DLL are also introduced and compared in this paper. Both show a good performance in terms of phase noise and can be easily realized in a standard CMOS technology. The false-lock issue of the DLL is also discussed and a solution is proposed. Furthermore, a frequency multiplier is used to multiply the output frequency of the PLL by a multiplication factor of 18. This architecture enables an increase in the target resolution and an improvement in the accuracy of the measurements of FMCW radars.
Generating parallel programs from the wavefront design pattern

Object-oriented programming, design patterns, and frameworks are common techniques that have been used to reduce the complexity of sequential programming. We have applied these techniques to the more difficult domain of parallel programming. This paper describes CO2P3S, a pattern-based parallel programming system that generates parallel programs from parallel design patterns. We demonstrate CO2P3S by applying a new design pattern called the Wavefront pattern to three problems. We show that it is quick and easy to use CO2P3S to generate structurally correct parallel programs with good speed-ups on shared-memory computers.
Extraction of UMLS® Concepts Using Apache cTAKES™ for German Language

Automatic information extraction of medical concepts and classification with semantic standards from medical reports is useful for standardization and for clinical research. This paper presents an approach for an UMLS concept extraction with a customized natural language processing pipeline for German clinical notes using Apache cTAKES. The objectives are, to test the natural language processing tool for German language if it is suitable to identify UMLS concepts and map these with SNOMED-CT. The German UMLS database and German OpenNLP models extended the natural language processing pipeline, so the pipeline can normalize to domain ontologies such as SNOMED-CT using the German concepts. For testing, the ShARe/CLEF eHealth 2013 training dataset translated into German was used. The implemented algorithms are tested with a set of 199 German reports, obtaining a result of average 0.36 F1 measure without German stemming, pre- and post-processing of the reports.
Bootstrapping the spectrum in ultra wide-band cognitive radio networks

The ultra wide-band cognitive radio networks, in recent years, have attracted the attention of the research due to their challenges concerning the signals detection over multiband. The aim of this paper is to address the ultra wide-band spectrum sensing, i.e. to detect the existence of spectral holes in ultra-wide frequency bands in order to improve the spectrum utilization and minimize the interference to the primary communications. Because of channel fading, the detection by one cognitive radio (CR) receiver is subject to missed detection, therefore it is instrumental for a network of spatially diverse CRs to collaborate during the spectrum sensing. In this paper, the collaborative detection is performed and the decentralized decision is discussed. A new paradigm for the decentralized decision based on bootstrap sampling in the spatio-frequency domain is presented. The performance of the proposed spectrum sensing approach for ultra wideband cognitive radio networks is also investigated.
Evaluation of human liver condition Self-organizing map and feed forward backpropagation technique

Serum Glutamic Pyruvate Transferase (SGPT) is an enzyme that used as a medical standard to evaluate health of human liver. The only method for measuring the amount of SGPT is through blood sampling. This paper introduces a new approach to measure the level on SGPT using body composition and home-used measuring tool. The self-organizing map was use as clustering tool and feature extraction tool. The prediction model was synthesized by using multi-layered feedforward neural network. The accuracy of the presented approach is reaching an impressive rate of 91%–97%, depending on the network structure and training features.
DOA estimation exploiting unified coprime array with multi-period subarrays

In this paper, we propose a unified coprime array by extending two subarrays in it from one-period to multi-period. One subarray can have arbitrary number of periods and the other has more periods than it. Therefore, more than one element of the unified structure coincide. The resulting configuration treats the nested array as well as the existing coprime structure, such as the extended one and CACIS as its special case. The comparisons of different coprime arrays are provided. The direction-of-arrival estimation performance and the coarray structures of these coprime arrays are examined through numerical simulations.
Fingerprinting intellectual property using constraint-addition

Recently, intellectual property protection (IPP) techniques attracted a great deal of attention from semiconductor, system integration and software companies. A number of watermarking-based techniques have been proposed for IPP. One of the key limitations of watermarking is that it does not facilitate tracing of illegally resold intellectual property (IP). Fingerprinting resolves this problem by providing each customer with a unique instance of functionally identical IP. We propose a general technique which enables fingerprinting at all level of design process and is applicable to an arbitrary optimization step. In particular, we address the following fingerprinting problem: How to generate a large number of high quality solution for a given optimization problem by solving the initial problem only once. In addition we also discuss how to select a subset of k solutions from the pool of n solutions so that the solutions are maximally different. In order to make our discussion concrete we focus on a single NP-complete problem -- graph coloring. We test the new fingerprinting on a number of standard benchmarks. Interestingly, while on random graphs it is relatively difficult to produce a large number of solutions without nontrivial quality degradation, on all real-life compilation graphs we are able to generate millions of solution which are all optimal.
To separate speech: a system for recognizing simultaneous speech

The PASCAL Speech Separation Challenge (SSC) is based on a corpus of sentences from the Wall Street Journal task read by two speakers simultaneously and captured with two circular eight-channel microphone arrays. This work describes our system for the recognition of such simultaneous speech. Our system has four principal components: A person tracker returns the locations of both active speakers, as well as segmentation information for each utterance, which are often of unequal length; two beamformers in generalized sidelobe canceller (GSC) configuration separate the simultaneous speech by setting their active weight vectors according to a minimum mutual information (MMI) criterion; a postfilter and binary mask operating on the outputs of the beamformers further enhance the separated speech; and finally an automatic speech recognition (ASR) engine based on a weighted finite-state transducer (WFST) returns the most likely word hypotheses for the separated streams. In addition to optimizing each of these components, we investigated the effect of the filter bank design used to perform subband analysis and synthesis during beamforming. On the SSC development data, our system achieved a word error rate of 39.6%.
Veri cation Through the Principle of Least Astonishment

Assessing the correctness of a digital design is a challenging task hampered by extremely large circuit netlists, counterintuitive property descriptions and ill-defined specifications. In this paper we propose a new verification methodology, inspired by the principle of least astonishment. The underlying idea is to provide an automatic assessment of what constitutes "common behavior" for a system, and use this to detect any anomaly in the design. Deviant behavior is presented to the verification engineer through intuitive, compact diagrams which lend themselves to quick inspection for correctness. To enable this methodology we introduce Inferno, a new tool which can analyze the results of a logic simulation trace and automatically extract high-level diagrams representing the design's transaction activity across any user-defined interface. In addition, Inferno can automatically generate a checker module corresponding to a given transaction, suitable for use in a wide range of verification methodologies. We envision the deployment of Inferno in a closed-loop constraint-random simulation methodology where any new transaction detected on the interface is presented to the user for analysis and, once deemed legal, it is merged into an "approved transactions" checker, which flags the detection of any new type of transactions. We provide a series of examples and experimental results to show the effectiveness of Inferno and some of its possible uses
The discovery of Antarctic RNA viruses: a new game changer

Antarctic ecosystems are dominated by micro‐organisms, and viruses play particularly important roles in the food webs. Since the first report in 2009 (López‐Bueno et al. ), ‘omic’‐based studies have greatly enlightened our understanding of Antarctic aquatic microbial diversity and ecosystem function (Wilkins et al. ; Cavicchioli ). This has included the discovery of many new eukaryotic viruses (López‐Bueno et al. ), virophage predators of algal viruses (Yau et al. ), bacteria with resistance to phage (Lauro et al. ) and mechanisms of haloarchaeal evasion, defence and adaptation to viruses (Tschitschko et al. ). In this issue of Molecular Ecology, López‐Bueno et al. ( ) report the first discovery of RNA viruses from an Antarctic aquatic environment. High sequence coverage enabled genome variation to be assessed for four positive‐sense single‐stranded RNA viruses from the order Picornavirales. By examining the populations present in the water column and in the lake's catchment area, populations of ‘quasispecies’ were able to be linked to local environmental factors. In view of the importance of viruses in Antarctic ecosystems but lack of data describing them, this study represents a significant advance in the field.