Miracle-dz/UniFAR-FTUs huggingface dataset:
A verifiable secret shuffle and its application to e-voting

We present a mathematical construct which provides a cryptographic protocol to verifiably shuffle a sequence of k modular integers, and discuss its application to secure, universally verifiable, multi-authority election schemes. The output of the shuffle operation is another sequence of k modular integers, each of which is the same secret power of a corresponding input element, but the order of elements in the output is kept secret. Though it is a trivial matter for the "shuffler" (who chooses the permutation of the elements to be applied) to compute the output from the input, the construction is important because it provides a linear size proof of correctness for the output sequence (i.e. a proof that it is of the form claimed) that can be checked by an arbitrary verifiers. The complexity of the protocol improves on that of Furukawa-Sako[16] both measured by number of exponentiations and by overall size.The protocol is shown to be honest-verifier zeroknowledge in a special case, and is computational zeroknowledge in general. On the way to the final result, we also construct a generalization of the well known Chaum-Pedersen protocol for knowledge of discrete logarithm equality [10], [7]. In fact, the generalization specializes exactly to the Chaum-Pedersen protocol in the case k = 2. This result may be of interest on its own.An application to electronic voting is given that matches the features of the best current protocols with significant efficiency improvements. An alternative application to electronic voting is also given that introduces an entirely new paradigm for achieving Universally Verifiable elections.
The physiological importance of photosynthetic ferredoxin NADP+ oxidoreductase (FNR) isoforms in wheat

Ferredoxin NADP+ oxidoreductase (FNR) enzymes catalyse electron transfer between ferredoxin and NADPH. In plants, a photosynthetic FNR (pFNR) transfers electrons from reduced ferredoxin to NADPH for the final step of linear electron flow, providing reductant for carbon fixation. pFNR is also thought to play important roles in two different mechanisms of cyclic electron flow around photosystem I; and photosynthetic reductant is itself partitioned between competing linear, cyclic, and alternative electron flow pathways. Four pFNR protein isoforms in wheat that display distinct reaction kinetics with leaf-type ferredoxin have previously been identified. It has been suggested that these isoforms may be crucial to the regulation of reductant partition between carbon fixation and other metabolic pathways. Here the 12 cm primary wheat leaf has been used to show that the alternative N-terminal pFNRI and pFNRII protein isoforms have statistically significant differences in response to the physiological parameters of chloroplast maturity, nitrogen regime, and oxidative stress. More specifically, the results obtained suggest that the alternative N-terminal forms of pFNRI have distinct roles in the partitioning of photosynthetic reductant. The role of alternative N-terminal processing of pFNRI is also discussed in terms of its importance for thylakoid targeting. The results suggest that the four pFNR protein isoforms are each present in the chloroplast in phosphorylated and non-phosphorylated states. pFNR isoforms vary in putative phosphorylation responses to physiological parameters, but the physiological significance requires further investigation.
LIPABASE: a database for 'true' lipase family enzymes

Lipase enzymes play an important role in lipid metabolism and are produced by a variety of species. Compared with animal, bacterial and fungal, little is known about plant lipases. Although lipases belong to many different protein families, they have the same architecture, the ? /? -hydrolase fold and a conserved active site signature, the Gly-Xaa-Ser-Xaa-Gly motif. Several studies on enzymatic activity and interfacial activation phenomenon of lipases confirm the presence of consensus sequence and a conserved domain. Lipases can be divided into two main groups: carboxylesterases (EC 3.1.1.1); 'true' lipases (EC 3.1.1.3), which differ in several biochemical features, which allow us to develop a database that regroups all 'true' lipase proprieties to establish relationship between structure and function. LIPABASE is a centralised resource database, which provides information about 'true' lipase from different species. It includes general, taxonomic, physicochemical and molecular data. Access to LIPABASE is free and available at http://www.lipabase-pfba-tun.org.
A sequential repetition model for improved disfluency detection

This paper proposes a new method for automatically detecting disﬂuencies in spontaneous speech – speciﬁcally, self-corrections – that explicitly models repetitions vs. other disﬂu-encies. We show that, in a corpus of Supreme Court oral arguments, repetition disﬂuencies can be longer and more stutter-like than the short repetitions observed in the Switchboard corpus and suggest that they can be better represented with a ﬂat structure that covers the full sequence. Since these disﬂuencies are relatively easy to detect, weakly supervised training is an effective way to minimize labeling costs. By explicitly modeling these, we improve general disﬂuency detection within and across domains, and we provide a richer transcript
Cholecystokinin (CCK) - induced anxiety in rats: influence of environmental stimuli and involvement of endopioid mechanisms and serotonin

Forty-five male Wistar rats were selected according to their behavior in the elevated plus-maze. They were separated as follows: animals with low exploratory activity ( ‘anxious’), an ‘intermediate’ group and animals having high exploratory activity ( ‘non-anxious’). Various receptor binding studies and hormonal assays were also performed in these selected rats. The affinity of 5-hydroxytryptamine 5-HT2a receptors in the frontal cortex was lower in the ‘anxious’ rats compared to home-cage controls and ‘non-anxious’ animals. Moreover, the number of cholecystokinin (CCK) receptors in the hippocampus was significantly elevated in the ‘anxious’ group compared to home-cage control animals. The blood levels of growth hormone (GH) were significantly lower in the ‘non-anxious’ rats compared to ‘anxious’ counterparts. In conclusion, it seems likely that the decreased exploratory activity of rats is related to the increased 5-hydroxytryptamine (5-HT) and CCK mediated neurotransmission in the brain. The different serum levels of GH in the selected rats probably reflect alterations in the activity of 5-HT and CCK. © 1997 Elsevier Science B.V.
Automatic plagiarism detection using similarity analysis

Plagiarism involves reproducing the existing information in modified format or sometimes the original document as it is. This is quiet common among students, researchers and academicians. This has made some strong influence on research community and awareness among academic peoples to prevent such a kind of malpractice. Though there exits some commercial tools to detect plagiarism, still plagiarism is tricky and quiet challenging task due to abundant information available online. Commercially existing software adopt methods like paraphrasing, sentence matching or keyword matching. Such techniques are not too good in identifying the plagiarized contents effectively. However this paper focuses its attention on identifying some key parameters that would help to identify plagiarism in a better manner. The results seem to be promising and have further scope in detecting the plagiarism.
Clinical Reviews

Assessment of disease activity in inflammatory bowel disease (IBD), i.e., ulcerative colitis (UC) and Crohn's disease (CD), is done using clinical parameters and various biological disease markers. Ideally, a disease marker must: be able to identify individuals at risk of a given disorder, be disease specific, mirror the disease activity and, finally, be easily applicable for routine clinical purposes. However, no such disease markers have yet been identified for IBD. In this article, classical disease markers including erythrocyte sedimentation rate, acute phase proteins (especially orosomucoid and CRP), leukocyte and platelet counts, albumin, neopterin, and β2-microglobulin will be reviewed together with emerging disease markers such as antibodies of the ANCA/ASCA type, cytokines (e.g., IL-1, IL-2Rα, IL-6, IL-8, TNF-α, and TNF-α receptors) and with various adhesion molecules. It is concluded that none of the pertinent laboratory surrogate markers of disease activity in IBD are specific or sensitive enough to replace basic clinical observation such as the number of daily bowel movements, general well-being, and other parameters in parallel. Further studies are highly warranted to identify and assess the clinical importance and applicability of new laboratory markers for the diagnosis or the disease activity of IBD.
Term Graphs and Principal Types for X

In this paper we study the calculus of circuits X , as first presented in [13] and studied in detail in [5]. We will present a number of n ew implementations ofX using term graph rewriting techniques, which are improveme nts of the technique used in [6]. We will show that alpha conversion can be dealt with ‘on the fly’, and that explicit copying can be avoided, by present ing, discussing and comparing a number of solutions to these problems. We will define a notion of type assignment on circuits by label ling input and output connectors with types. This notion is then used to defi ne a non-standard notion of type assignment on term graph rewriting. We will sh ow that this system has a principal type property.
Prospective memory, executive functions, and metacognition are already differentiated in young elementary school children: Evidence from latent factor modeling.

Abstract. This study investigated the empirical differentiation of prospective memory, executive functions, and metacognition and their structural relationships in 119 elementary school children (M = 95 months, SD = 4.8 months). These cognitive abilities share many characteristics on the theoretical level and are all highly relevant in many everyday contexts when intentions must be executed. Nevertheless, their empirical relationships have not been examined on the latent level, although an empirical approach would contribute to our knowledge concerning the differentiation of cognitive abilities during childhood. We administered a computerized event-based prospective memory task, three executive function tasks (updating, inhibition, shifting), and a metacognitive control task in the context of spelling. Confirmatory factor analysis revealed that the three cognitive abilities are already empirically differentiable in young elementary school children. At the same time, prospective memory and executive functi.
Near-Optimal Detection in MIMO Systems Using Gibbs Sampling

In this paper we study a Markov Chain Monte Carlo (MCMC) Gibbs sampler for solving the integer leastsquares problem. In digital communication the problem is equivalent to performing Maximum Likelihood (ML) detection in Multiple-Input Multiple-Output (MIMO) systems. While the use of MCMC methods for such problems has already been proposed, our method is novel in that we optimize the "temperature" parameter so that in steady state, i.e. after the Markov chain has mixed, there is only polynomially (rather than exponentially) small probability of encountering the optimal solution. More precisely, we obtain the largest value of the temperature parameter for this to occur, since the higher the temperature, the faster the mixing. This is in contrast to simulated annealing techniques where, rather than being held fixed, the temperature parameter is tended to zero. Simulations suggest that the resulting Gibbs sampler provides a computationally efficient way of achieving approximative ML detection in MIMO systems having a huge number of transmit and receive dimensions. In fact, they further suggest that the Markov chain is rapidly mixing. Thus, it has been observed that even in cases were ML detection using, e.g. sphere decoding becomes infeasible, the Gibbs sampler can still offer a near-optimal solution using much less computations.
An Empirical Model for Probability of Packet Reception in Vehicular Ad Hoc Networks

Today's advanced simulators facilitate thorough studies on VANETs but are hampered by the computational effort required to consider all of the important influencing factors. In particular, large-scale simulations involving thousands of communicating vehicles cannot be served in reasonable simulation times with typical network simulation frameworks. A solution to this challenge might be found in hybrid simulations that encapsulate parts of a discrete-event simulation in an analytical model while maintaining the simulation's credibility. In this paper, we introduce a hybrid simulation model that analytically represents the probability of packet reception in an IEEE 802.11p network based on four inputs: the distance between sender and receiver, transmission power, transmission rate, and vehicular traffic density. We also describe the process of building our model which utilizes a large set of simulation traces and is based on general linear least squares approximation techniques. The model is then validated via the comparison of simulation results with the model output. In addition, we present a transmission power control problem in order to show the model's suitability for solving parameter optimization problems, which are of fundamental importance to VANETs.
Neuro-visually inspired figure-ground segregation

An extra-classical receptive field (ECRF) based mid-level model of visual processing which we refer to as the neuro-visually inspired model of figure-ground segregation (NFGS) is proposed in this work. It is inspired by the non-linear interaction of the classical receptive field (CRF) and its non-classical extended surround, comprising of the non-linear mean increasing and decreasing sub-units. A simple digital kernel has been derived that performs efficient mid-level block representation.
Model Selection and Parameter Estimation for Censored Data from Highly Fractionated Experiments

Complicated structure of BCrooning experiments coupled with censored data resulting from life-testing of durable products makes the characterization and optimization of process variables very difficult. Existing methods are inadequate for analyzing such data from highly fractionated experiments because important effects are identified wrongly. By studying contrasts from censored data, we can. identify an appropriate initial model for the "imputation-modeling-maximization" algorithm to compare many models simultaneously and select the best model for process· optimization. We demonstrate the procedure by reanalyzing data sets from Specht's heat exchanger experiments and show its superiority over some existing methods by comparing their predicted lifetimes.
Generalized Space-and-Frequency Index Modulation

Unlike in conventional modulation where information bits are conveyed only through symbols from modulation alphabets defined in the complex plane [e.g., quadrature amplitude modulation (QAM) and phase shift keying (PSK)], in index modulation (IM), additional information bits are conveyed through indexes of certain transmit entities that get involved in the transmission. Transmit antennas in multiantenna systems and subcarriers in multicarrier systems are examples of such transmit entities that can be used to convey additional information bits through indexing. In this paper, we introduce generalized space and frequency IM, where the indexes of active transmit antennas and subcarriers convey information bits. We first introduce IM in the spatial domain, which is referred to as generalized spatial IM (GSIM). For GSIM, where bits are indexed only in the spatial domain, we derive the expression for achievable rate and easy-to-compute upper and lower bounds on this rate. We show that the achievable rate in GSIM can be more than that in spatial multiplexing and analytically establish the condition under which this can happen. It is noted that GSIM achieves this higher rate using fewer transmit radio-frequency (RF) chains compared with spatial multiplexing. We also propose a Gibbs-sampling-based detection algorithm for GSIM and show that GSIM can achieve better bit error rate (BER) performance than spatial multiplexing. For generalized space-frequency IM (GSFIM), where bits are encoded through indexing in both active antennas and subcarriers, we derive the achievable rate expression. Numerical results show that GSFIM can achieve higher rates compared with conventional multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM). Moreover, BER results show the potential for GSFIM performing better than MIMO-OFDM.
An Overview of Major Satellite Systems

A satellite communication system is distinguished by its global coverage, inherent broadcast capability, ability to support mobility and bandwidth-on-demand flexibility. Taking into account this emerging communication role of the satellite systems, the paper provides an overview of major narrowband GEO, MEO and LEO satellite systems. It presents some typical commercial examples of such satellite systems and discusses their basic features consisting of used frequency bands, supported applications and terminals and critical performance issues. Key-Words: GEO, LEO, MEO, Narrowband Satellite Systems, Onboard Processing.
A Feed-Forward Mechanism Involving the NOX Complex and RyR-Mediated Ca2+ Release During Axonal Specification

Physiological levels of ROS support neurite outgrowth and axonal specification, but the mechanisms by which ROS are able to shape neurons remain unknown. Ca2+, a broad intracellular second messenger, promotes both Rac1 activation and neurite extension. Ca2+ release from the endoplasmic reticulum, mediated by both the IP3R1 and ryanodine receptor (RyR) channels, requires physiological ROS levels that are mainly sustained by the NADPH oxidase (NOX) complex. In this work, we explore the contribution of the link between NOX and RyR-mediated Ca2+ release toward axonal specification of rat hippocampal neurons. Using genetic approaches, we find that NOX activation promotes both axonal development and Rac1 activation through a RyR-mediated mechanism, which in turn activates NOX through Rac1, one of the NOX subunits. Collectively, these data suggest a feedforward mechanism that integrates both NOX activity and RyR-mediated Ca2+ release to support cellular mechanisms involved in axon development. SIGNIFICANCE STATEMENT High levels of ROS are frequently associated with oxidative stress and disease. In contrast, physiological levels of ROS, mainly sustained by the NADPH oxidase (NOX) complex, promote neuronal development and axonal growth. However, the mechanisms by which ROS shape neurons have not been described. Our work suggests that NOX-derived ROS promote axonal growth by regulating Rac1 activity, a molecular determinant of axonal growth, through a ryanodine receptor (RyR)-mediated Ca2+ release mechanism. In addition, Rac1, one of the NOX subunits, was activated after RyR-mediated Ca2+ release, suggesting a feedforward mechanism between NOX and RyR. Collectively, our data suggest a novel mechanism that is instrumental in sustaining physiological levels of ROS required for axonal growth of hippocampal neurons.
The Effect of Superparamagnetic Iron Oxide with iRGD Peptide on the Labeling of Pancreatic Cancer Cells In Vitro: A Preliminary Study

The iRGD peptide loaded with iron oxide nanoparticles for tumor targeting and tissue penetration was developed for targeted tumor therapy and ultrasensitive MR imaging. Binding of iRGD, a tumor homing peptide, is mediated by integrins, which are widely expressed on the surface of cells. Several types of small molecular drugs and nanoparticles can be transfected into cells with the help of iRGD peptide. Thus, we postulate that SPIO nanoparticles, which have good biocompatibility, can also be transfected into cells using iRGD. Despite the many kinds of cell labeling studies that have been performed with SPIO nanoparticles and RGD peptide or its analogues, only a few have applied SPIO nanoparticles with iRGD peptide in pancreatic cancer cells. This paper reports our preliminary findings regarding the effect of iRGD peptide (CRGDK/RGPD/EC) combined with SPIO on the labeling of pancreatic cancer cells. The results suggest that SPIO with iRGD peptide can enhance the positive labeling rate of cells and the uptake of SPIO. Optimal functionalization was achieved with the appropriate concentration or concentration range of SPIO and iRGD peptide. This study describes a simple and economical protocol to label panc-1 cells using SPIO in combination with iRGD peptide and may provide a useful method to improve the sensitivity of pancreatic cancer imaging.
Louise Newman self-protective strategies , and dispositional representations Comparing models of borderline personality disorder : Mothers ' experience

This study compared aspects of the functioning of mothers with borderline personality disorder (BPD) to those of mothers without psychiatric disorder using two different conceptualizations of attachment theory. The Adult Attachment Interviews (AAIs) of 32 mothers were classified using both the Main and Goldwyn method (M&G) and the Dynamic-Maturational Model method (DMM). We found that mothers with BPD recalled more danger, reported more negative effects of danger, and gave evidence of more unresolved psychological trauma tied to danger than other mothers. We also found that the DMM classifications discriminated between the two groups of mothers better than the M&G classifications. Using the DMM method, the AAIs of BPD mothers were more complex, extreme, and had more indicators of rapid shifts in arousal than those of other mothers. Representations drawn from the AAI, using either classificatory method, did not match the representations of the mother’s child drawn from the Working Model of the Child Interview; mothers with very anxious DMM classifications were paired with secure-balanced child representations. We propose that the DMM offers greater clinical utility, conceptual coherence, empirical validity, and coder reliability than the M&G.
Extraction of impervious surface based on the standardized ratio model

With rapid urban growth in recent years, it becomes an important research topic for us to understand urban biophysical composition and dynamics. Remote sensing technologies introduce a potentially scientific basis for examining urban composition and monitoring its changes over time. The vegetation-impervious surface-soil-water (V-I-S-W) model, in particular, provides a foundation for describing urban/suburban environments and a basis for further urban analyses including urban growth modeling, environmental impact analysis, and socioeconomic factor estimation. This paper develops a standardized ratio model (SRM) method to examine urban composition especially urban impervious surface in Haizhu District using Landsat ETM+ data. In particular, a brightness SRM method is applied to reduce brightness variation. Through this standardization, brightness variability within each V-I-S-W component is reduced or eliminated, thus allowing a single end-member representing each component. Further, with the standardized image, four endmembers, vegetation, impervious surface, soil, and water, are chosen to model heterogeneous urban composition using a constrained spectral mixture analysis (SMA) models. The accuracy of impervious surface estimation is assessed and compared with other existing model. Results indicate that the proposed model is a better alternative to existing models, with a root mean square error (RMSE) of 12.6% for impervious surface estimation in the study area.