Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Hybrid Image Cryptosystem using ECC and Chaotic Map

is used to securely transmit data in open networks. Each type of data has its own features; therefore different techniques should be used to protect confidential image data from unauthorized access. The asymmetric cryptography doesn't fit for transmission of Images, since it takes more time for encryption at the source and likewise for decryption at the destination. We are therefore using hybrid cryptosystem, In this paper, we designed an algorithm to generate diffusion template using 3D standard map and rotated image by using vertically and horizontally red and green plane of the input color image. We then shuffled the red, green, and blue plane by using 3D Cat map and Standard map. Finally the Image is encrypted by performing XOR operation on the shuffled image and diffusion template. The objectives of this new design includes: (1) to efficiently extract good pseudorandom sequences from a cascading of 3D cat and Standard map for color image and (2) to simultaneously perform permutation and diffusion operations for fast encryption. The symmetric key cryptography totally depends on the session key, we are using ECC algorithm for session key exchange in secure manner.
Nonproliferating Bystander CD4+ T Cells Lacking Activation Markers Support HIV Replication During Immune Activation1

HIV replicates primarily in lymphoid tissue and immune activation is a major stimulus in vivo. To determine the cells responsible for HIV replication during Ag-driven T cell activation, we used a novel in vitro model employing dendritic cell presentation of superantigen to CD4+ T cells. Dendritic cells and CD4+ T cells are the major constituents of the paracortical region of lymphoid organs, the main site of Ag-specific activation and HIV replication. Unexpectedly, replication occurred in nonproliferating bystander CD4+ T cells that lacked activation markers. In contrast, activated Ag-specific cells were relatively protected from infection, which was associated with CCR5 and CXC chemokine receptor 4 down-regulation. The finding that HIV replication is not restricted to highly activated Ag-specific CD4+ T cells has implications for therapy, efforts to eradicate viral reservoirs, immune control of HIV, and Ag-specific immune defects.
Modelling the Cooperative Information Filtering Problem

In this paper, we present an original approach for modelling the cooperative information filtering problem using Logic of Information Flow and Situation Theory. We describe the fundamental concepts of these theories and discuss crucial issues that arise during the exposition, such as defining Situation Theory as a Heyting algebra and showing that in our application this theory is well-founded.
Music Genre Classification

Introduction Music genres allow the categorization of music into broad groups of related songs for use in applications such as song recommender systems based on genre. Many existing songs are unlabeled, and new songs are constantly being released. While hand-labeling them all would be too tedious, classifying them by genre can fit them into categories for use in recommendation. Also, even if the artist or producer labels a song as a specific genre, finding the songs that are most similar in terms of frequency structure rather than subjective labeling might provide recommendation information that the user would enjoy more.
The Ragnarok Software Development Environment

Ragnarok is an experimental software development environment that focuses on enhanced support for managerial activities in large scale software development taking the daily work of the software developer as its point of departure. The main emphasis is support in three areas: management, navigation, and collaboration . The leitmotif is the software architecture, which is extended to handle managerial data in addition to source code; this extended software architecture is put under tight version- and configuration management control and furthermore used as basis for visualisation. Preliminary results of using the Ragnarok prototype in a number of projects are outlined.
Effects of rotor bar and end-ring faults over the signals of a position estimation strategy for induction motors

The effect of rotor faults, such as broken bars and end-rings, over the signals of a position estimation strategy for induction motor drives is analyzed using a multiple coupled circuit model. The objective of this analysis is to establish the possibility of using the estimation strategy signals for fault diagnosis in variable-speed electric drives. This strategy is based on the effect produced by inductance variation on the zero-sequence voltage, when exciting the motor with a predefined inverter switching pattern. Experimental results illustrate the feasibility of the proposal.
Maximum likelihood estimation for SAR interferometry

Synthetic aperture radar (SAR) interferometry (InSAR) uses phase differences between overlapping SAR images to estimate terrain height and terrain height changes. In addition, the coherence magnitude between the images is often used as a measure of the quality of the data and the processing. By modeling the SAR image data as independent circular Gaussian random variates, the authors develop the maximum likelihood (ML) estimates for interferogram phase, coherence magnitude, and the variance of the underlying circular Gaussian distribution. They show that the ML estimate of interferogram phase is equivalent to the standard technique of computing the phase of averaged complex returns. The ML estimate of the coherence magnitude depends on the estimated interferogram phase. In comparison, the sample coherence magnitude estimate based on amplitudes alone is badly biased. They also derive the Cramer-Rao bound for each ML estimate. The ML estimate of interferogram phase is close to this bound for moderate to high coherence values. Similarly, the coherence magnitude is close to the bound for values of coherence greater than approximately 1/2. For coherence magnitudes less than 1/2, the ML estimate of coherence magnitude is biased for data samples sizes up to 16 samples. <<ETX>>
The Sampling Properties of Volatility Cones

In this research, we extend the original work on volatility cones by Burghardt and Lane (1990) to consider of the sampling properties of the variance of variance (and the standard deviation of volatility) under a rich class of models that includes stochastic volatility and conditionally fat-tailed distributions. Because the volatility cone examines volatility at quite long horizons, the estimation requires the use of overlapping data. This theory confirms the casual observation that the estimation of the variance of variance is downward biased when estimation is done on an overlapping basis. Our principal contribution is to identify what this bias is and derive an adjustment factor that approximates an unbiased estimate of the true variance of variance when overlapping data is used. Another contribution is the derivation of a formula that describes the variance of the quadratic variation over different time horizons. Using the theory presented, we tested the bias adjustments to the standard deviation of volatility using simulations. Two cases were examined: a GBM i.i. d. process and a non-i.i. d. process associated with the stochastic volatility model suggested by Heston (1993). In both cases, the bias introduced by estimation of volatility with overlapping data becomes insignificant after making the theoretical adjustments. These results are relevant to those who must sell options and must understand the nature of quadratic variation in asset prices. This will provide clearer insights into the nature of hedging errors when dynamically hedging options. This research also suggests a new method for the estimation of stochastic volatility models, where estimation over a long horizon is likely to provide robustness not associated with current methods. JEL classifications: C13, G13
Throughput bound of XOR coded wireless multicasting to three clients

It is a well-known result that constructing code-words over GF(2) to minimize the number of transmissions for a single-hop wireless multicasting is an NP-complete problem. Linearly independent codewords can be constructed in polynomial time for all the n clients, known as maximum distance separable (MDS) code, when the finite field size q is larger than or equal to the number of clients, q ≥ n. In this paper we quantify the exact minimum number of transmissions for a multicast network using erasure code when q = 2 and n = 3, such that q <; n. We first show that the use of Markov chain model to derive the minimum number of transmissions for such a network is limited for very small number of input packets. We then use combinatorial approach to derive an upper bound on the exact minimum number of transmissions. Our results show that the difference between the expected number of transmissions using XOR coding and MDS coding is negligible for n = 3.
Wavelet-Based Sparse Reduced-Rank Regression for Hyperspectral Image Restoration

In this paper, a method called wavelet-based sparse reduced-rank regression (WSRRR) is proposed for hyperspectral image restoration. The method is based on minimizing a sparse regularization problem subject to an orthogonality constraint. A cyclic descent-type algorithm is derived for solving the minimization problem. For selecting the tuning parameters, we propose a method based on Stein's unbiased risk estimation. It is shown that the hyperspectral image can be restored using a few sparse components. The method is evaluated using signal-to-noise ratio and spectral angle distance for a simulated noisy data set and by classification accuracies for a real data set. Two different classifiers, namely, support vector machines and random forest, are used in this paper. The method is compared to other restoration methods, and it is shown that WSRRR outperforms them for the simulated noisy data set. It is also shown in the experiments on a real data set that WSRRR not only effectively removes noise but also maintains more fine features compared to other methods used. WSRRR also gives higher classification accuracies.
Ultrastructure of Cytoplasmic and Nuclear Inosine-5’-Monophosphate Dehydrogenase 2 “Rods and Rings” Inclusions

Inosine-5′-monophosphate dehydrogenase catalyzes the critical step in the de novo synthesis of guanosine nucleotides: the oxidation of inosine monophosphate to xanthosine monophosphate. This reaction can be inhibited by specific inhibitors, such as ribavirin or mycophenolic acid, which are widely used in clinical treatment when required to inhibit the proliferation of viruses or cells. However, it was recently found that such an inhibition affects the cells, leading to a redistribution of IMPDH2 and the appearance of IMPDH2 inclusions in the cytoplasm. According to their shape, these inclusions have been termed “Rods and Rings” (R&R). In this work, we focused on the subcellular localization of IMPDH2 protein and the ultrastructure of R&R inclusions. Using microscopy and western blot analysis, we show the presence of nuclear IMPDH2 in human cells. We also show that the nuclear pool has an ability to form Rod structures after inhibition by ribavirin. Concerning the ultrastructure, we observed that R&R inclusions in cellulo correspond to the accumulation of fibrous material that is not surrounded by a biological membrane. The individual fibers are composed of regularly repeating subunits with a length of approximately 11 nm. Together, our findings describe the localization of IMPDH2 inside the nucleus of human cells as well as the ultrastructure of R&R inclusions.
Optimal motion strategies for range-only distributed target tracking

In this paper we study the problem of optimal trajectory generation for a team of mobile robots that tracks a moving target using range-only measurements. We propose an adaptive-relaxation algorithm for determining the set of feasible locations that each robot must move to in order to collect the most informative measurements; i.e., distance measurements that minimize the uncertainty about the position of the target. We prove that the motion strategy that minimizes the trace of the position error covariance matrix is equivalent to the one that minimizes its maximum eigenvalue. The proposed method is applicable regardless of the process model employed for describing the motion of the target while its computational complexity is linear in the number of robots. Extensive simulation results are presented, demonstrating that the performance attained with the proposed method is comparable to that obtained with exhaustive search whose computational cost is exponential in the number of robots
An anisotropic micromechanical-based model for characterizing the magneto-mechanical behavior of NiMnGa alloys

As a typical ferromagnetic shape memory alloy (FSMA), NiMnGa alloy at room temperature is a heterogeneous material with martensitic variants and a high magnetic anisotropy property to produce a giant magnetic-induced strain and high frequency response. A theoretical model based on micromechanical and thermodynamic theory is proposed to describe the magneto-mechanical behavior of single-crystal FSMAs during the reorientation process of martensitic variants. It follows the well-established Eshelby equivalent inclusion method and the Mori–Tanaka scheme, and incorporates the influence of the material anisotropy and the variant inclusion morphology on the reorientation of the martensite variants. The modified micromechanical model is further applied to characterize the stress–strain behavior and magnetic-field-induced strain during the martensite variant rearrangement process in a single-crystal NiMnGa rod under applied magnetic field and/or mechanical loading. The simulation results show good agreement with the experimental data. The effects of the material anisotropy and inclusion morphology on the magnetoelastic constitutive behavior of FSMAs are discussed.
Characterization of the Fecal Microbiome from Non-Human Wild Primates Reveals Species Specific Microbial Communities

Background Host-associated microbes comprise an integral part of animal digestive systems and these interactions have a long evolutionary history. It has been hypothesized that the gastrointestinal microbiome of humans and other non-human primates may have played significant roles in host evolution by facilitating a range of dietary adaptations. We have undertaken a comparative sequencing survey of the gastrointestinal microbiomes of several non-human primate species, with the goal of better understanding how these microbiomes relate to the evolution of non-human primate diversity. Here we present a comparative analysis of gastrointestinal microbial communities from three different species of Old World wild monkeys. Methodology/Principal Findings We analyzed fecal samples from three different wild non-human primate species (black-and-white colobus [Colubus guereza], red colobus [Piliocolobus tephrosceles], and red-tailed guenon [Cercopithecus ascanius]). Three samples from each species were subjected to small subunit rRNA tag pyrosequencing. Firmicutes comprised the vast majority of the phyla in each sample. Other phyla represented were Bacterioidetes, Proteobacteria, Spirochaetes, Actinobacteria, Verrucomicrobia, Lentisphaerae, Tenericutes, Planctomycetes, Fibrobacateres, and TM7. Bray-Curtis similarity analysis of these microbiomes indicated that microbial community composition within the same primate species are more similar to each other than to those of different primate species. Comparison of fecal microbiota from non-human primates with microbiota of human stool samples obtained in previous studies revealed that the gut microbiota of these primates are distinct and reflect host phylogeny. Conclusion/Significance Our analysis provides evidence that the fecal microbiomes of wild primates co-vary with their hosts, and that this is manifested in higher intraspecies similarity among wild primate species, perhaps reflecting species specificity of the microbiome in addition to dietary influences. These results contribute to the limited body of primate microbiome studies and provide a framework for comparative microbiome analysis between human and non-human primates as well as a comparative evolutionary understanding of the human microbiome.
Metabolic syndrome as a predictor of ischemic stroke in elderly persons.

OBJECTIVE To estimate the prevalence and risk of ischemic stroke associated with metabolic syndrome. METHODS AND PATIENTS In 197 stroke patients (80 cases of atherothrombotic infarction, 97 lacunar infarction, 16 cardioembolic infarction, 4 others) and 356 age- and sex-matched control subjects aged 65 years and older in Seiyo Municipal Nomura Hospital, we investigated the association between metabolic syndrome and risk factor-dependent augmentation of ischemic stroke in subjects with several risk factors for atherosclerosis. The diagnosis of cerebral infarction in each patient was confirmed by CT findings of the brain and metabolic syndrome was defined as at least 3 of the 5 following conditions: visceral obesity, hypertension (HT), hypertriglyceridemia, low HDL-cholesterol and diabetes mellitus (DM). RESULTS After adjustment for sex, age, and smoking, metabolic syndrome was significantly related to atherothrombotic infarction (odds ratio, 3.08; 95% confidence interval, 1.69-5.61). Of the individual components, visceral obesity, HT and DM were independent risk factors for atherothrombotic infarction. Increased risk for atherothrombotic infarction was also associated with increases in the 5 component conditions of the metabolic syndrome. CONCLUSION The clustering of cardiovascular risk factors called metabolic syndrome increases the risk of cardiovascular morbidity, and its identification may thus be important in risk assessment and treatment of patients.
Journal of Software Maintenance and Evolution: Research and Practice Software Cartography: Thematic Software Visualization with Consistent Layout ‡

SUMMARY Software visualizations can provide a concise overview of a complex software system. Unfortunately, as software has no physical shape, there is no 'natural' mapping of software to a two-dimensional space. As a consequence most visualizations tend to use a layout in which position and distance have no meaning, and consequently layout typically diverges from one visualization to another. We propose an approach to consistent layout for software visualization, called Software Cartography, in which the position of a software artifact reflects its vocabulary, and distance corresponds to similarity of vocabulary. We use Latent Semantic Indexing (LSI) to map software artifacts to a vector space, and then use Multidimensional Scaling (MDS) to map this vector space down to two dimensions. The resulting consistent layout allows us to develop a variety of thematic software maps that express very different aspects of software while making it easy to compare them. The approach is especially suitable for comparing views of evolving software, as the vocabulary of software artifacts tends to be stable over time. We present a prototype implementation of Software Cartography, and illustrate its use with practical examples from numerous open-source case studies.
Evaluation of cold plasma treatment and safety in disinfecting 21-day root canal enterococcus faecalis biofilm in vitro

Many studies have demonstrated that Enterococcus faecalis (E. faecalis) is the most important species responsible for persistent endodontic infection. E. faecalis biofilm often exhibits increased resistance to antimicrobial agents compared with planktonic bacteria. The aim of this study is to evaluate the effectiveness and safety of cold plasma therapy in disinfecting 21-day E. faecalis biofilms. Teeth with 21-day E. faecalis biofilm were treated with an argon/oxygen cold plasma for various treatment times and compared to those treated with Ca(OH)2, 2% CHX gel and Ca(OH)2/CHX gel for 7 days (positive controls). Negative control groups included normal saline treatment and Ar/O2 gas treatment. Antimicrobial efficacy was determined by colony forming unit (CFU) method. Scanning Electron Microscopy (SEM) was employed to assess the morphological changes of E. faecalis biofilm by plasma. Confocal Laser Scanning Microscopy (CLSM) was used to confirm the viability of the biofilm after the plasma treatment. Microhardness and microroughness changes caused by plasma were tested with Vickers Hardness Tester and 3D Laser Scanning Microscope respectively. Energy Dispersive X-ray Spectroscopy (EDS) was used for elemental analysis of root canal dentin. The results indicated that a 12 min cold plasma treatment could inactivate E. faecalis 21-day biofilm completely. Atmospheric pressure cold plasma is an effective tool in endodontics for its strong biofilm sterilization effect and has an accepted safety for its low temperature without significantly affecting the microhardness and microroughness of tooth enamel if placed at proper working distance.
Subject and Object Dependency Extraction Using Finite-State Transducers

We describe and evaluate an approach for fast automatic recognition and extraction of subject and object dependency relations from large French corpora, using a sequence of finite-state transducers. The extraction is performed in two major steps: incremental finite-state parsing and extraction of subject/verb and object/verb relations. Our incremental and cautious approach during the first phase allows the system to deal successfully with complex phenomena such as embeddings, coordination of VPs and NPs or non-standard word order. The extraction requires no subcategorisation information. It relies on POS information only. After describing the two steps, we give the results of an evaluation on various types of unrestricted corpora. Precision is around 90-97% for subjects (84-88% for objects) and recall around 86-92% for subjects (80-90% for objects). We also provide some error analysis; in particular, we evaluate the impact of POS tagging errors on subject/object dependency extraction.
Grid-Based Approach for Energy-Balanced Node Deployment Control in Wireless Sensor Networks

In wireless sensor networks, much research has focused on improving energy consumption and network lifetime due to limited power available on sensor nodes. The imbalance of node energy consumption results in the network partition blocking data transmission from sources to sinks. This paper proposes an efficient node deployment control protocol to achieve balanced energy consumption among sensor nodes. Firstly, a binary virtual tree topology is constructed based on grids. Secondly, considering the traffic load of each sensor node, a more efficient virtual tree topology is reconstructed by optimizing link directions. Because the reconstructed tree uses diagonal grids, performance is dramatically improved in terms of energy efficiency and the duration of data transmission. Simulation results confirm that the proposed scheme reduces the total energy consumption up to 16% and improves the network lifetime up to 33% compared to an existing binary virtual tree, by balancing power consumption of sensor nodes efficiently.