Miracle-dz/UniFAR-FTUs huggingface dataset:
UVC-Induced Stress Granules in Mammalian Cells

Stress granules (SGs) are well characterized cytoplasmic RNA bodies that form under various stress conditions. We have observed that exposure of mammalian cells in culture to low doses of UVC induces the formation of discrete cytoplasmic RNA granules that were detected by immunofluorescence staining using antibodies to RNA-binding proteins. UVC-induced cytoplasmic granules are not Processing Bodies (P-bodies) and are bone fide SGs as they contain TIA-1, TIA-1/R, Caprin1, FMRP, G3BP1, PABP1, well known markers, and mRNA. Concomitant with the accumulation of the granules in the cytoplasm, cells enter a quiescent state, as they are arrested in G1 phase of the cell cycle in order to repair DNA damages induced by UVC irradiation. This blockage persists as long as the granules are present. A tight correlation between their decay and re-entry into S-phase was observed. However the kinetics of their formation, their low number per cell, their absence of fusion into larger granules, their persistence over 48 hours and their slow decay, all differ from classical SGs induced by arsenite or heat treatment. The induction of these SGs does not correlate with major translation inhibition nor with phosphorylation of the α subunit of eukaryotic translation initiation factor 2 (eIF2α). We propose that a restricted subset of mRNAs coding for proteins implicated in cell cycling are removed from the translational apparatus and are sequestered in a repressed form in SGs.
Design and Evaluation of a Parallel Execution Framework for the CLEVER Clustering Algorithm

Data mining is used to extract valuable knowledge from vast pools of data. Due to the computational complexity of the algorithms applied and the problems of handling large data sets themselves, data mining applications often require days to perform their analysis when dealing with large data sets. This paper presents the design and evaluation of a parallel computation framework for CLEVER, a prototype-based clustering algorithm which has been successfully used for a wide range of application scenarios. The algorithm supports plug-in fitness functions and employs randomized hill climbing to maximize a given fitness function. We explore various parallelization strategies using OpenMP and CUDA, and evaluate the performance of the parallel algorithms for three different data sets. Our results indicate a nearly linear scalability of the parallel algorithm using multi-core processors, reducing the execution time and allowing to solve problems which were considered not feasible with the sequential version of CLEVER.
The validity of androgen assays

Problems in the measurement of androgens and in interpreting results have been reviewed and classified as follows: Preanalytical factors. The exact sampling conditions in relation to circadian and seasonal variations, diet, alcohol, physical activity and posture. Physiological and medical factors. Androgen levels vary according to the patient's general health, stress, sexual activity and smoking habits. Analytical variables. Sample preservation and storage variables are often unknown. The different androgen assays used have widely differing accuracy and precision and are subject to large inter-laboratory variation, which especially in women and children can render the results of routinely available direct immunoassays meaningless. Interpretation of results. Laboratory reference ranges vary widely, largely independent of methodology, and fail to take into account the log-normal distribution of androgen values, causing errors in clinical diagnosis and treatment. Other unknowns are antagonists such as SHBG, estrogens, catecholamines, cortisol, and anti-androgens. As well as age, androgen receptor polymorphisms play a major role in regulating androgen levels and resistance to their action. Conclusions. Though laboratory assays can support a diagnosis of androgen deficiency in men, they should not be used to exclude it. It is suggested that there needs to be greater reliance on the history and clinical features, together with careful evaluation of the symptomatology, and where necessary a therapeutic trial of androgen treatment given.
Exponential localization in one-dimensional quasi-periodic optical lattices

We investigate the localization properties of a one-dimensional bichromatic optical lattice in the tight-binding regime, by discussing how exponentially localized states emerge upon changing the degree of commensurability. We also review the mapping onto the discrete Aubry–André model, and provide evidence on how the momentum distribution gets modified in the crossover from extended to exponentially localized states. This analysis is relevant to the recent experiment on the Anderson localization of a noninteracting Bose–Einstein condensate in a quasi-periodic optical lattice (Roati et al 2008 Nature 453 895).
Mechanical strain‐induced NO production by bone cells: a possible role in adaptive bone (re)modeling?

The structural competence of the skeleton is maintained by an adaptive mechanism in which resident bone cells respond to load‐induced strains. To investigate the possible role of the messenger molecule nitric oxide (NO) in this response, we studied NO production in well‐characterized organ culture systems, rat long bone‐derived osteoblast‐like (LOBs) cells, and embryonic chick osteocytes (LOCYs) in monolayer culture. In superfused cancellous bone cores, loading (for 15 min) produces increases in NO2‐ (stable NO metabolite) release during the loading period, which paralleled those in PGI2 and PGE2‐ Loading of rat vertebrae and ulnae produces increases in NO2‐ release, and in ulnae NO synthase inhibitors diminish these responses. Transient rapid increases in NO release are stimidated by strain in both LOBs and LOCYs. Polymerase chain reaction amplification of extracted mRNA shows that rat ulnae, LOBs, and LOCYs express both the inducible and neuronal (constitutive) isoforms of NO synthase. Adaptability to mechanical strain relies on assessment of the strain environment followed by modification of bone architecture. Immediate increases in NO production induced by loading suggest the involvement of NO in strain measurement and cellular communication to establish strain distribution, as well as potentially in adaptive changes in bone cell behavior. —Pitsillides, A. A. , Rawlinson, S. C. F. , Suswillo, R. F. L. , Bourrin, S. , Zaman, G. , Lanyon, L. E. Mechanical strain‐induced NO production by bone cells: a possible role in adaptive bone (re)modeling? FASEB J. 9, 1614‐1622(1995)
Introducing a Collaborative Congestion Control Based on TFRC

Wireless ad-hoc networks, composed by PDA-like mobile equipments, are the technologies used in pervasive ambient networks. These environ- ments opens applicative perspectives allowing the co- operation of hierarchical user groups which are mobile in the context of emergency operations (EO). In this paper, we introduce a novel "collaborative" conges- tion control mechanism at the transport level allow- ing for improving the QoS. When available resources are not enough to offer an acceptable level of QoS for all connections, the approach consists in improving the highest priorities connections while maintaining the fairness and friendliness properties regarding the other connections. We present the results obtained by ns-2 simulation that allow to determinate as well as validate the work hypothesis for such a "collabora- tive" congestion control.
Curvaton dynamics in brane-worlds

We study the curvaton dynamics in brane-world cosmologies. Assuming that the inflaton field survives without decay after the end of inflation, we apply the curvaton reheating mechanism to the Randall–Sundrum model and to its curvature corrections: Gauss–Bonnet, induced gravity and combined Gauss–Bonnet and induced gravity cosmological models. In the case of chaotic inflation and requiring suppression of possible short-wavelength generated gravitational waves, we constrain the parameters of a successful curvaton brane-world cosmological model. If density perturbations are also generated by the curvaton field, then the fundamental five-dimensional mass could be much lower than the Planck mass.
Mapping geographic coverage of the web

In this paper, we describe a methodology to estimate the geographic coverage of the web without the need for secondary knowledge or complex geo-tagging. This is achieved by randomly selecting toponyms from the Ordnance Survey 50K gazetteer to create search queries and thus gather document counts from various web sources for Great Britain. The same gazetteer is then used to geo-code the results and enable mapping. To validate our approach, and demonstrate the effects of geo/non-geo and geo/geo ambiguity, we mapped the selected toponyms to Geograph, a community project that contains user generated geo-tagged photographs of the UK. Although success varies with resolution, the proposed approach is likely sufficient to be reliably used by applications exploring the geographic coverage of the web for cases where references to settlements are likely to be common. In our case, we applied the method to produce maps of web coverage for a range of sources at a resolution of 30km.
Automatic Vehicle Detection Using Pixelwise Classification Approach

We present a system to detect and track moving vehicles based on the pixelwise classification approach. In this approach escapes some of the existing frameworks for detection vehicles in traffic monitoring systems. So many researchers and intelligent minds are introduces so many technique but not provided the accurate results. Proposed technique uses designed pixel wise classification method, canny edge detection techniques and back ground color subtraction method that leads to accurate results in vehicle detection rate. Pixel wise classification provides not only region wise but also sliding window also detected the vehicles. The feature extraction performed in both training and detection stages. The classification purpose we use dynamic Bayesian networks and in this network vehicle and non vehicle are identify purpose used a support vector machine. The classification of vehicles and non vehicles are identification purpose used a color histogram algorithm. When we performed all the methods easily identify the vehicles and provides accuracy results to compare the previous approaches. In experimental results are shown in different videos are taken at different cameras and different heights in surveillance systems.
A Personality-based Framework for Utterance Generation in Dialogue Applications

Conversation is an essential component of social behaviour, one of the primary means by which humans express emotions, moods, attitudes and personality. Thus a key technical capability for dialogue applications, such as interactive narrative systems (INS), human robot interaction (HRI) and spoken dialogue systems (SDS), is the ability to support natural conversational interaction. However, system utterances in existing systems are typically handcrafted, leading to problems of portability and scalability. We propose a framework for automatically generating language projecting different personality traits based on the ‘Big Five’ model of personality. We show that our PERSONAGE generator can produce utterances with recognisable personality for all Big Five traits, according to human judges. We also test the ability of PERSONAGE to vary the characters’ personality in an existing interactive narrative system, showing that some forms of variation can be automatically obtained in a new domain, depending on the level of utterance representation.
Dynamic duplicate deferral techniques for redundant Wi-Fi networks

Wireless communications suffer from disturbance and interference, which prevent reliable data exchanges and preclude their adoption in the real-time applications found at the lower levels of factory automation systems. This is particularly true for Wi-Fi, for which mechanisms like channel hopping and blacklisting are not available. Several solutions were defined in the past few years, which range from the adoption of general-purpose redundancy protocols over conventional communication equipment to proposals like Wi-Red, which offers link-level redundancy. In this paper, an enhancement is presented for the latter solution, which achieves better performance by deferring transmission of duplicate frames. The net effect is a sort of load balancing between wireless channels, which reduces network traffic and increases reliability further.
Proof General / Eclipse: A Generic Interface for Interactive Proof

This paper introduces PG/Eclipse; a sophisticated new interface for interactive theorem provers, offering users a rich set of proof development tools. It is based upon two complementary frameworks. The first is PG/Kit, a generic communication framework for connecting theorem provers and interfaces. PG/Kit should allow straightforward adaptation to most interactive theorem provers. Moreover, by separating interface development from proof engine development, this framework should facilitate the development of both. The second is Eclipse, a sophisticated open source framework for building IDEs. Eclipse is highly modular and extensible, making it a good platform for interface research. Using it has allowed us to provide a rich range of interface features. These frameworks correspond to the twin goals of this project: to define a clear separation between provers and interfaces, and to translate programming development tools to a theorem proving environment.
Detection and Interpretation of Text Information in Noisy Video Sequences

Text superimposed on the video frames provides supplemental but important information for video indexing and retrieval. The detection and recognition of text from video is thus an important issue in automated content-based indexing of visual information in video archives. Text of interest is not limited to static text. They could be scrolling in a linear motion where only part of the text information is available during different frames of the video. The problem is further complicated if the video is corrupted with noise. An algorithm is proposed to detect, classify and segment both static and simple linear moving text in complex noisy background. The extracted texts are further processed using averaging to attain a quality suitable for text recognition by commercial optical character recognition (OCR) software
TRAITS AND STATES 639 TRAITS : PERSONALITY AND CRIME

We propose and test a model of criminal decision making that integrates the individual differences perspective with research and theorizing on proximal factors. The individual differences perspective is operationalized using the recent HEXACO personality structure. This structure incorporates the main personality traits, but it carries the advantage of also incorporating Self-Control within its personality sphere, and an additional trait termed Honesty-Humility. Furthermore, the model offers a new perspective on proximal predictors, “states,” of criminal decisions by adding affect (i.e., feelings) to the rational choice–crime equation. The proposed model is tested using scenario data from a representative sample of the Dutch population in terms of gender, age, education level, and province (N = 495). As predicted by the model, personality was both directly and indirectly related to criminal decision making. Specifically, the traits Emotionality, Self-Control, and HonestyHumility were mediated by both affect and rational choice variables. Conscientiousness operated only indirectly on criminal decision making via rational choice. Together, the findings support a trait-state model of criminal decision making.
Optimizing software data prefetches with rotating registers

Software data prefetching is a well-known technique to improve the performance of programs that suffer many cache misses at several levels of memory hierarchy. However, it has significant overhead in terms of increased code size, additional instructions, and possibly increased memory bus traffic due to redundant prefetches. This paper presents two novel methods to reduce the overhead of software data prefetching and improve the program performance by optimized prefetch scheduling. These methods exploit the availability of rotating registers and predication in architectures such as the Itanium/sup TM/ architecture. The methods (I) minimize redundant prefetches, (2) reduce the number of issue slots needed for prefetch instructions, and (3) avoid branch mispredict penalties - all with minimal code size increase. Compared to traditional data prefetching techniques, these methods (i) do not require loop unrolling, (ii) do not require predicate computations and (iii) require fewer machine resources. One of these methods has been implemented in the Intel Production Compiler for the ItaniumTM processor. This technique is compared with traditional approaches for software prefetching and experimental results are presented based on the floating-point benchmark suite of CPU2000.
Separating concurrent languages with categories of language embeddings

Concurrent programming enjoys a proliferation of languages but suffers from the lack of a general method of language comparison. In particular, concurrent (as well as sequential) programming languages cannot be usefully distinguished based on complexitytheoretic considerations, since most of them are Turingcomplete. Nevertheless, differences between programming languages matter, else we would not have invented so many of them. We develop a general method for comparing concurrent programming languages based on their algebraic (structural) complexity, and, using this method, achieve separation results among many well-known concurrent languages. The method is not restricted to concurrent languages. It can be used to compare the algebraic complexity of abstract machine models, other families of programming languages, logics, and, more generaly, any family of languages with some syntactic operations and a notion of semantic equivalence. The method can also be used to compare the algebraic complexity of families of operations wit hin a language or across languages. We note that using the method we were able to compare languages and computational models that do not have a common semantic basis. Permission to copy without fee afl or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. @ 1991 ACM 089791-397-3/91/0004/0198 $1.50
From Training to Match Performance: A Predictive and Explanatory Study on Novel Tracking Data

The recent FIFA approval of the use of Electronic Performance and Tracking Systems (EPTS) during competition, has provided the availability of novel data regarding physical player performance. The analysis of this kind of information will provide teams with competitive advantages, by gaining a deeper understanding of the relation between training and match load, and individual player's fitness characteristics. In order to make sense of this physical data, which is inherently complex, machine learning algorithms that exploit both non-linear and linear relations among variables could be of great aid on building predictive and explanatory models. Also, the increasing availability of information brings the necessity and the challenge for successful interpretation of these models in order to be able to translate the findings into information that can be quickly applied by fast-paced practitioners, such as physical coaches. For season 2015-2016 F. C. Barcelona has collected both physical information from both training sessions and matches using EPTS devices. This study focuses primarily on evaluating up to what extent is possible to predict match performance from training and match physical information. Different machine learning algorithms are applied for building predictive regression models, in combination with feature selection techniques and Principal Component Analysis (PCA) for dimensionality reduction. Physical Variables are segmented into three groups: Locomotor, Metabolic and Mechanical variables, reaching successful prediction rates in 11 out of 17 total variables, based on a threshold determined by expert physical coaches. A normalized root mean square error metric is proposed that allows better understanding of results for practitioners. The second part of this study is focused on understanding the predictor variables that better explain each of the 17 analyzed match variables. It was found that specific variables can act as representatives of the set of highly correlated ones, so reducing greatly the amount of variables needed in the periodical physical analysis carried out by coaches, passing from 17 to 4 variables in average.
Submodularity and curvature : the optimal algorithm

Let (X, I) be a matroid and let f : 2 → R+ be a monotone submodular function. The curvature of f is a parameter c ∈ [0, 1] such that for any S ⊂ X and j ∈ X \ S, f(S ∪ {j})− f(S) ≥ (1− c)f({j}). We consider the optimization problem max{f(S) : S ∈ I}. It is known that the greedy algorithm yields a 1/2-approximation for this problem [11], and 1 1+c -approximation when f has curvature c [4]. For the uniform matroid, it was known that the greedy algorithm yields an improved 1 c (1− e−c)-approximation [4]. In this paper, we analyze the continuous greedy algorithm [23] and prove that it gives a 1 c (1 − e−c)-approximation for any matroid. Moreover, we show that this holds for a relaxed notion of curvature, curvature with respect to the optimum, and we prove that any better approximation under these conditions would require an exponential number of value queries.
Tuning retractable , microscale , membrane-breaking protein needles 1 2

10 The refractile (R) bodies found in Caedibacter taeniospiralis, a bacterial endosymbiont of Paramecium 11 tetraurelia, are large, polymeric protein structures that can switch between two conformations. At 12 cytoplasmic pH, they resemble coiled ribbons of protein 500nm in diameter. At low pH, they extend to 13 form hollow needles up to 20 microns long. They can be expressed heterologously from an operon 14 containing four short open reading frames and can function in vitro in diverse buffer conditions. 15 In this study, R bodies purified from Escherichia coli were found to be capable of undergoing many 16 consecutive extension-contraction cycles. Furthermore, the solubility of R bodies, which can easily be 17 interpreted by eye, was found to correlate with their extension state. This macroscopic phenotype was 18 used to develop a quantitative, high-throughput assay for R body state, enabling a visual screen of R 19 body mutants defective in extension. The role of specific amino acids in extension was determined, and 20 this information was used to construct rationally-designed mutants tailored to extend at higher pH. 21 Furthermore, R bodies were able to rupture E. coli spheroplasts to release soluble proteins across lipid 22 bilayers. Taken together, these results show that R bodies act as tunable, pH-actuated pistons suitable 23 for a variety of membrane-breaking applications. 24
Multi-resolution on compressed sets of clauses

The paper presents a system based on new operators for handling sets of propositional clauses represented by means of ZBDDs (zero-suppressed binary decision diagrams). The high compression power of such data structures allows efficient encodings of structured instances. A specialized operator for the distribution of sets of clauses is introduced and used for performing multi-resolution on clause sets. Cut eliminations between sets of clauses of exponential size may then be performed using polynomial size data structures. The ZREs system, a new implementation of the Davis-Putnam procedure (M. Davis and H. Putnam, 1960), solves two hard problems for resolution, that are currently out of the scope of the best SAT provers.