Miracle-dz/UniFAR-FTUs huggingface dataset:
Trust model with delayed verification for message relay in VANETs

Trust management is one of the major issues for secure communication in vehicular network. Most of the existing trust models are identity-based and use excessive periodic exchange between vehicles to build a decision about trustiness of participating vehicles. Malicious data can be minimized in such models using identities reputation. In general, the nature and the quality of the data are not taken into account, despite some models which may revoke messages based on their nature and their type. In this work, we propose a new trust model for VANETs, which based on the early detection of attacks by relying on the opinion of the last forwarder and delayed verification of the exchanged messages. In our scheme, we developed an intrusion detection module which perform such operation and evaluate the trustiness of received messages. We introduce a new concept of companion vehicles which is used to filter out and select the most trusted nodes among neighboring vehicles, to be used as relays in the forwarding procedure. The deployment of this mechanism allow us to prevent vehicles identified as probable dishonest nodes from participating in the network. In this study, we simulation results show the effectiveness of our trust model in detecting dishonest nodes as well as malicious messages that are sent by honest or dishonest nodes, after a very low number of messages exchange. We also show that in the worst case scenario, our trust model offers equally good results.
Metabolic heterogeneity during preimplantation development: the missing link?

BACKGROUND Most tissues in the body rely on the presence of gap junctions in order to couple their component cells electrically and metabolically via intercellular transport of ions, metabolites and signalling agents. As a result, cells within tissues achieve a high degree of, 'metabolic homogeneity' which enables them to develop in an integrated way and co-ordinate their response to physiological signals and environmental cues. Unusually, the developing mammalian preimplantation embryo does not form functional gap junctions until it has divided into 8 or more cells. We discuss the implications of this 'missing link' during the first few days of development for the maintenance of homogeneity between embryonic cells and for the co-ordination of the embryonic response to intrinsic genetic damage and external environmental signals. METHODS No systematic review has been carried out. The physiology of preimplantation development and the general nature of gap junctions have been reviewed briefly before examining experimental evidence which addresses the following points: (i) whether there are functional differences between early blastomeres; (ii) when during preimplantation development the embryo is most sensitive to environmental perturbation and (iii) the consequences for early embryos of ablating gap junction formation and function. RESULTS AND CONCLUSIONS General conclusions are confounded by species differences, especially in the timing of embryonic genome activation (EGA) and the extent of intrinsic genotypic and phenotypic variation (low in embryos from inbred mice; high in human embryos). Nevertheless, we propose that the absence of gap junctions requires cleavage stage mammalian embryos to behave cell autonomously in a metabolic sense, contributes to their heightened sensitivity to environmental perturbation compared with the later stages of preimplantation development and poses more problems in the early human embryo, where there is a high degree of heterogeneity between the blastomeres. We argue that the legacy of metabolic heterogeneity, in part generated by the absence of gap junctions, is 'rescued' by the onset of apoptosis following EGA. In the context of human-assisted conception, since early embryos lacking gap junctions are more sensitive to environmental stress during cleavage, this would support transfer to the natural environment as early as possible after fertilization.
Diagnostic cost group hierarchical condition category models for medicare risk adjustment

Affiliations: Health Economics Research, Inc. Waltham, MA Department of Economics, Boston University, Boston, MA Health Care Research Unit, Boston University School of Medicine, Boston, MA Associate Professor of Medicine and Health Care Policy, Harvard Medical School and Brigham and Women's Hospital Chief, Division of General Medicine, Brigham and Women's Hospital, Medical Director of Clinical and Quality Analysis, Partners Healthcare, Associate Professor of Medicine, Harvard Medical School Assistant Professor, Harvard Medical School (on leave) Professor of Medicine at Harvard Medical School and Co-Director of Research, Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center Assistant Professor of Medicine, Harvard Medical School, Director of Quality and Outcomes Research, Hebrew Rehabilitation Center for Aged
Modeling Interactions between Speech Production and Perception: Speech Error Detection at Semantic and Phonological Levels and the Inner Speech Loop

Production and comprehension of speech are closely interwoven. For example, the ability to detect an error in one's own speech, halt speech production, and finally correct the error can be explained by assuming an inner speech loop which continuously compares the word representations induced by production to those induced by perception at various cognitive levels (e.g., conceptual, word, or phonological levels). Because spontaneous speech errors are relatively rare, a picture naming and halt paradigm can be used to evoke them. In this paradigm, picture presentation (target word initiation) is followed by an auditory stop signal (distractor word) for halting speech production. The current study seeks to understand the neural mechanisms governing self-detection of speech errors by developing a biologically inspired neural model of the inner speech loop. The neural model is based on the Neural Engineering Framework (NEF) and consists of a network of about 500,000 spiking neurons. In the first experiment we induce simulated speech errors semantically and phonologically. In the second experiment, we simulate a picture naming and halt task. Target-distractor word pairs were balanced with respect to variation of phonological and semantic similarity. The results of the first experiment show that speech errors are successfully detected by a monitoring component in the inner speech loop. The results of the second experiment show that the model correctly reproduces human behavioral data on the picture naming and halt task. In particular, the halting rate in the production of target words was lower for phonologically similar words than for semantically similar or fully dissimilar distractor words. We thus conclude that the neural architecture proposed here to model the inner speech loop reflects important interactions in production and perception at phonological and semantic levels.
Large fluctuations of stochastic differential equations with regime switching: applications to simulation and finance

This thesis deals with the asymptotic behaviour of various classes of stochastic differential equations (SDEs) and their discretisations. More specifically, it concerns the largest fluctuations of such equations by considering the rate of growth of the almost sure running maxima of the solutions. The first chapter gives a brief overview of the main ideas and motivations for this thesis. Chapter 2 examines a class of nonlinear finite–dimensional SDEs which have mean– reverting drift terms and bounded noise intensity or, by extension, unbounded noise intensity. Equations subject to Markovian switching are also studied, allowing the drift and diffusion coefficients to switch randomly according to a Markov jump process. The assumptions are motivated by the large fluctuations experienced by financial markets which are subjected to random regime shifts. We determine sharp upper and lower bounds on the rate of growth of the large fluctuations of the process by means of stochastic comparison methods and time change techniques. Chapter 3 applies similar techniques to a variant of the classical Geometric Brownian Motion (GBM) market model which is subject to random regime shifts. We prove that the model exhibits the same long–run growth properties and deviations from the trend rate of growth as conventional GBM. The fourth chapter examines the consistency of the asymptotic behaviour of a discretisation of the model detailed in Chapter 3. More specifically, it is shown that the discrete approximation to the stock price grows exponentially and that the large fluctuations from this exponential growth trend are governed by a Law of the Iterated Logarithm. The results about the asymptotic behaviour of discretised SDEs found in Chapter 4, rely on the use of an exponential martingale inequality (EMI). Chapter 5 considers a discrete version of the EMI driven by independent Gaussian sequences. Some extensions, applications and ramifications of the results are detailed. The final chapter uses the EMI developed in Chapter 5 to analyse the asymptotic behaviour of discretised SDEs. Two different methods of discretisation are considered: a standard Euler–Maruyama method and an implicit split–step variant of Euler–Maruyama. v
PGC-1 Coactivators in Cardiac Development and Disease

The beating heart requires a constant flux of ATP to maintain contractile function, and there is increasing evidence that energetic defects contribute to the development of heart failure. The last 10 years have seen a resurgent interest in cardiac intermediary metabolism and a dramatic increase in our understanding of transcriptional networks that regulate cardiac energetics. The PPAR-&ggr; coactivator (PGC)-1 family of proteins plays a central role in these pathways. The mechanisms by which PGC-1 proteins regulate transcriptional networks and are regulated by physiological cues, as well as the roles they play in cardiac development and disease, are reviewed here.
Strong weak CP hierarchy from nonrenormalization theorems

We point out that the hierarchy between the measured values of the CKM phase and the strong CP phase has a natural origin in supersymmetry with spontaneous CP violation and low energy supersymmetry breaking. The underlying reason is simple and elegant: in supersymmetry the strong CP phase is protected by an exact non-renormalization theorem while the CKM phase is not. We present explicit examples of models which exploit this fact and discuss corrections to the non-renormalization theorem in the presence of supersymmetry breaking. This framework for solving the strong CP problem has generic predictions for the superpartner spectrum, for CP and flavor violation, and predicts a preferred range of values for electric dipole moments.
Maps of Information Flow Reveal Community Structure In Complex Networks

To comprehend the multipartite organization of large-scal e biological and social systems, we introduce a new information theoretic approach to reveal community struct ure in weighted and directed networks. The method decomposes a network into modules by optimally compressing a description of information flows on the network. The result is a map that both simplifies and highlights the reg ularities in the structure and their relationships. We illustrate the method by making a map of scientific communica tion as captured in the citation patterns of more than 6000 journals. We discover a multicentric organizatio n with fields that vary dramatically in size and degree of integration into the network of science. Along the backbo ne f the network — including physics, chemistry, molecular biology, and medicine — information flows bidirec tionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.
Measuring Of Semantic Similarity Between Words Using WebSearch Engine Approach

Semantic similarity is the process of identifying the synonyms for a given word. Which returns the one or more words which give the same meaning in context. In dictionary the semantic similarity between words is solved. But when it comes to web, measuring the semantic similarity between words has become the challenging task.Inorder to find the semantic similarity between the words we have proposed a lexical pattern extraction algorithm to find the numerous semantic relations between two words. And also a sequential pattern clustering algorithm was proposed to find the number of lexical patterns that shows the same semantic relations between two words. Page count concurrence measures along with lexical patterns extracted from snippets are used to define features of a word pair. Testing on three benchmark desk by training two class SVM the proposed method outperformed various baselines. And also it also improved the efficiency of community mining. 1 . Introduction Pattern matching is the concept which reveals/deals with the similarity between words. It is useful in finding the files in a folder or disk Given text in a document etc. The concept of tries helps to achieve this and the following algorithms are used For example pattern matching algorithms like Brute force Boyer moore Knuth-morris Semantic similarity is the process of identifying the synonyms for a given word. Which returns the one or more words which give the some meaning in context. In dictionary the semantic similarity between words is solved. But when it comes to web, measuring the semantic similarity between words has become the challenging task. This can be achieved by the below mentioned methods. Depending upon frequent usage of words we can make the semantic relation between words. Let us consider an example:Web search engine based approach gives the results for the words like apple and computer. The page count of the query “apple” and “computer” in Google is 2,88,000,000,whereas the same for “banana” and “computer” is only 3,590,000.
LTE Advanced — A further evolutionary step for Next Generation Mobile Networks

The World Radio Conference in 2007 identified additional spectrum for IMT-2000 and IMT-Advanced systems. That's why also 3GPP has started a feasibility study for LTE-Advanced techniques to continuously evolve LTE technology. LTE-Advanced is expected to enable download peak rates over 1Gbps at 100MHz bandwidth and in the upload peak rates over 0.5Gbps. Novel techniques on radio interface are going to be analyzed especially to improve spectral efficiency and cell edge performance. Advanced Antenna systems, Multi-User and Multi-Cell Multiple-Input Multiple-Output, Coordinated Multi-Point (CoMP) transmission schemes for interference reduction, Cooperative Relaying are some of potential features to enhance the Next Generation Mobile Network.
Higher Order Aberrations of the Corneal Surface after Laser Subepithelial Keratomileusis

Purpose To evaluate the changes of higher order aberrations (HOAs) before and after laser subepithelial keratomileusis (LASEK) and to analyze the influence of tear film instability on HOAs of the corneal surface after LASEK. Methods In this cross-sectional study, 31 patients who underwent LASEK were divided into dry eye (16 patients, 32 eyes) and non-dry eye groups (15 patients, 30 eyes). Uncorrected distance visual acuity, spherical equivalent refraction, ablation depth, tear film parameters and Ocular Surface Disease Index (OSDI) questionnaire scores were evaluated in both groups. Total HOA root mean square (RMS), third-order coma, third-order trefoil and fourth-order spherical aberration (SA) of the corneal surface immediately and at 10 seconds after blinking were measured before and after surgery. Results The total HOA RMS, coma, trefoil and SA significantly increased after LASEK compared with preoperative values in both groups. In the dry eye group, total HOA RMS, coma and trefoil significantly increased except for SA at 10 seconds after blinking compared with those measured immediately after blinking. In addition, the changes of total HOA RMS, coma and trefoil were negatively correlated with tear film break-up time (R = -0.420, -0.473 and -0.439, respectively), but positively correlated with OSDI score (R = 0.433, 0.499 and 0.532, respectively). In the non-dry eye group, there were no significant differences between HOAs measured at 10 seconds after blinking and those measured immediately after blinking. Conclusions The HOAs including coma, trefoil and SA significantly increased after LASEK. The tear film instability in the dry eye can be associated with more deterioration of the optical quality after LASEK, due to more significant increase of total HOA RMS, coma and trefoil.
Spatio-temporal indexing in non-relational distributed databases

Big Data has driven the need for datastores that can scale horizontally leading to the development of many different NoSQL database implementations, each with different persistence and query philosophies. Spatio-temporal data such as location data is one of the largest types of data being collected today. We describe a novel spatio-temporal index structure that leverages the horizontal scalability of NoSQL databases to achieve performant query and transformation semantics. We present performance characteristics gathered from testing with Accumulo.
Power-down synthesis for analog circuits including switch sizing

In order to reduce the power consumption of a system-on-chip, analog circuits can be switched off when not needed with the help of power-down switches. The power-down synthesis task comprises the structural synthesis of the power-down circuitry and switch sizing. A first approach for automatic structural synthesis was published recently. This paper completes the power-down synthesis task by an effective, efficient and very easy sizing heuristic. An optimum size for the power-down switches is identified. The sizing approach is derived from exhaustive simulation results for three different amplifier circuits and a voltage-controlled ring oscillator. The variations in the power-on performance values, the power consumption during power-down mode, the power-on to power-down settling time and the power-down to power-on settling time are determined for different sizes of the power-down switches. From the simulation results, it can be concluded that the technology's minimal switch size can be chosen for the switches. This simple sizing step completes state-of-the-art power-down synthesis with the missing sizing step.
Design and implementation of the video detecting and recording system on DSP

A compact video processing system which deals with video detecting, compressing and recording is designed on DSP. And in order to find a balance among hardware resources (prime cost), processing speed, detecting performance, system stability and system reliability, further algorithm and processing mechanism optimizations are proposed. This system does automatic surveillance of an unattended area installed fixed video camera, which automatically detects and locates moving objects, sends alarm message, compresses and records the video of the scene. The DSP core does the moving object detecting first, then starts sending alarm message and recording according to the results. As for video detecting, a fast and reliable moving object detecting algorithm is designed. This algorithm is based on principles of temporal differencing and background subtraction algorithm. Thus on one hand the system can make reliable alarm determinations. On the other hand, it is robust when there is light interference or sudden background change. As for video recording, SDHC card is chosen to be the storage device. Because it is pluggable and portable, SDHC card is very suitable for a compact system. The compressed video data will be stored in the card in FAT32 file format through SPI bus. Considering the automation and remote control of the system, GPRS wireless module is used to send multi-media alarm messages to the user. Long time experiment results demonstrate that the system can capture the moving object in an unattended area effectively, send alarm message to the remote user, and be robust when the light or the background changes.
Partisan Politics and the U . S . Income Distribution

Census Bureau data reveal large, consistent differences in patterns of real pre-tax income growth under Democratic and Republican presidents in the postwar U.S. Democratic presidents have produced slightly more income growth for poor families than for rich families, resulting in a modest decrease in overall inequality. Republican presidents have produced a great deal more income growth for rich families than for poor families, resulting in a substantial increase in inequality. On average, families at the 95th percentile of the income distribution have experienced identical income growth under Democratic and Republican presidents, while those at the 20th percentile have experienced more than four times as much income growth under Democrats as they have under Republicans. These differences are attributable to partisan differences in unemployment (which has been 30 percent lower under Democratic presidents, on average) and GDP growth (which has been 30 percent higher under Democratic presidents, on average); both unemployment and GDP growth have much stronger effects on income growth at the bottom of the income distribution than at the top. Similar partisan differences appear in the distribution of post-tax income growth of households since 1980, despite the fact that the corresponding pre-tax income growth data for that period show little evidence of partisan differences.
Auto-Tuning Distributed-Memory 3-Dimensional Fast Fourier Transforms on the Cray XT4

We present auto tuning, optimization, and performance modeling of 3 Dimensional Fast Fourier Transforms on Cray XT4 (Franklin) system. Spectral methods involving FFTs are a commonly used numerical technique with applications in engineering, chemistry, geosciences, and other areas of scientific computing. In the case of materials science the wavefunction of the electrons are expanded in spatial frequency components which is a natural basis since the wavefunction for a free electron is a plane wave. In this paper we study the performance of a 3D FFT specifically written for materials science applications. The problem with a parallel 3d FFT is that for a grid of N points the computational work involved is O(NlogN) while the amount of communication is O(N). This means that for small values of N (64 x 64 x 64 3D FFTs), the communication costs rapidly overwhelm the parallel computation savings. A distributed 3D FFT represents a considerable challenge for the communications infrastructure of a parallel machine because of the all-to-all nature of the distributed transposes required, and it stresses aspects of the machine that complement those addressed by other benchmark kernels, such as Linpack, that solves system of linear equations, Ax = b. Auto tuning can play a vital role in optimizing 3D FFT kernels for a diverse platforms as it can exploit features of the system-specific configuration characteristics to improve performance. We also depend on analytic performance models as a tool for predicting the idealized performance for the 3-dimensional Fast Fourier Transforms to set performance expectations for the target computational system. Overall, our methodology is able to achieve a substantial improvement in performance over conventional approaches to tuning 3D FFT performance.