Miracle-dz/UniFAR-FTUs huggingface dataset:
Leakage-Free Integrity Assurance for Tree Data Structures

Data sharing with multiple parties over a third-party distribution framework requires that both data integrity and conﬁdentiality be assured. One of the most widely used data organization structures is the tree structure. When such structures encode sensitive information (such as in the XML documents), it is crucial that integrity and conﬁdentiality be assured not only for the content, but also for the structure. Digital signature schemes are commonly used to authenticate the integrity of the data. The most widely used such technique for tree structures is the Merkle hash technique, which however is known to be “not hiding”, thus leading to leakage of information. Most existing techniques for the integrity of hierarchical data structures are based on the Merkle hash technique and thus suﬀer from the problem of information leakages. We describe the types of leakages and inference attacks that can be carried out on the Merkle hash technique, in the context of integrity assurance. Assurance of integrity and conﬁdentiality (no leakages) of tree-structured data is an important problem in the context of secure data publishing and content distribution systems. In this paper, we propose an integrity assurance scheme for tree data structures, which assures both conﬁ-dentiality and integrity and is also eﬃcient, especially in third-party distribution environments. Our integrity assurance technique, which we refer to as the “structural integrity assurance scheme”, is based on the structure of the tree as deﬁned by tree traversals (pre-order, post-order, in-order) and is deﬁned using a randomized notion of such traversal numbers. Techniques for computing randomized traversal numbers are also described in the paper. In addition to formally deﬁning the technique, we prove that it protects against violations of content and structural integrity and information leakages. We also show through complexity and performance analysis that the structural integrity assurance scheme is eﬃcient; with respect to the Merkle hash technique, it incurs comparable cost for signing trees and incurs lower cost for user-side integrity veriﬁcation. Further, we extend the proposed technique in order to assure integrity of weighted trees and dynamic updates. We also show how the proposed structural integrity assurance technique can be applied in order to precisely detect integrity violations as well as to eﬃciently recover data. Such techniques have applications in digital forensics and eﬃcient data transmission.
α-Galactosylceramide, a Ligand of Natural Killer T Cells, Inhibits Allergic Airway Inflammation

α-Galactosylceramide (α-GalCer) is a specific ligand of natural killer T cells (NKT cells) that regulates the immune responses such as tumor rejection and autoimmunity by producing interferon (IFN)-γ and interleukin (IL)-4. However, it has not been determined whether α-GalCer–activated NKT cells modulate allergic inflammation. Because α-GalCer induces a large amount of IFN-γ production by NKT cells, we hypothesized that an in vivo administration of α-GalCer could inhibit allergic airway inflammation in mice. Strikingly, a single intraperitoneal injection of α-GalCer almost completely abrogated an infiltrate with eosinophils in the lung tissue as well as in the bronchoalveolar lavage. This inhibition of allergic inflammation was associated with a significant decrease in the levels of IL-4, IL-5, and IL-13 in bronchoalveolar lavage fluid and in the number of goblet cells. In addition, this ligand significantly inhibited airway hyperresponsiveness to inhaled methacholine and raised the serum levels of ovalbu.
Comparative Transcriptome Analysis Revealed Genes Commonly Responsive to Varied Nitrate Stress in Leaves of Tibetan Hulless Barley

Nitrogen (N) deprivation or excess can lead to dramatic phenotype change, disrupt important biological processes, and ultimately limit plant productivity. To explore genes in Tibetan hulless barley responsive to varied N stress, we utilized a comparative transcriptomics method to investigate gene expression patterns under three nitrate treatments. The transcriptome of the control (optimal-nitrate, ON) sample was compared with that of free-nitrate (FN), low-nitrate (LN), and high-nitrate (HN) treatment samples, identifying 2428, 1274, and 1861 genes, respectively, that exhibited significant differences in transcript abundance. Among these, 9 genes encoding ribulose bisphosphate carboxylases exhibited up-regulated expression under varied N stress. We further compared FN vs. ON and LN vs. ON to investigate the impact of stress degree on gene expression. With the aggravation of stress, more genes were differentially expressed and thus possibly involved in the response to nitrogen deficiency. Cluster and functional enrichment analysis indicated that the differentially expressed genes (DEGs) in FN were highly enriched in response to stress, defense response, and gene expression regulation. Comprehensive comparison analysis further suggested that Tibetan hulless barley could respond to varied N stress by regulating multiple common biological processes and pathways such as nitrogen metabolism, carbon metabolism, and photosynthesis. A large number of specific DEGs involved in diverse biological processes were also detected, implying differences in the potential regulatory patterns of low- and high-N stress response. Notably, we also identified some NIN-like proteins and other transcription factors significantly modulated by these stresses, suggesting the involvement of these transcription factors in N stress response. To our knowledge, this study is the first investigation of the Tibetan hulless barley transcriptome under N stress. The identified N-stress-related genes may provide resources for genetic improvement and promote N use efficiency.
Nearest-neighbor classification using unlabeled data for real world image application

Currently, Nearest-Neighbor approaches (NN) have been widely applied to real world image data mining. These approaches have the following three disadvantages: (i) the performance is inferior on small datasets; (ii) the performance of approximated nearest neighbor search will degrade for data with high dimensions; (iii) they are heavily dependent on the chosen feature and distance measure. To overcome these intrinsic weaknesses, we propose a novel Nearest-Neighbor method, which improves the original NN approaches from three aspects. Firstly, we propose a novel neighborhood similarity measure, where the similarity between test images and labeled images in the database is calculated jointly by the original image-to-image similarity and the average similarity of their neighboring unlabeled data. Secondly, we adopt the kernelized locality sensitive hashing to effectively conduct the nearest neighbor search for high dimensional data. Finally, to enhance the robustness of the method on different genres of images, we propose to fuse the discrimination power of different features by considering all the retrieved nearest neighbors via hashing systems using different features/kernels. Experimental result shows the advantage over traditional Nearest-Neighbor methods using the labeled data only. Even when the ratio of labeled data is very small, our method could also achieve remarkable results, thanks to the help of unlabeled data and multiple features.
Rate-cost tradeoffs in control

Consider a distributed control problem with a communication channel connecting the observer of a linear stochastic system to the controller. The goal of the controller is minimize a quadratic cost function. The most basic special case of that cost function is the mean-square deviation of the system state from the desired state. We study the fundamental tradeoff between the communication rate r bits/sec and the limsup of the expected cost b, and show a lower bound on the rate necessary to attain b. The bound applies as long as the system noise has a probability density function. If target cost b is not too large, that bound can be closely approached by a simple lattice quantization scheme that only quantizes the innovation, that is, the difference between the controller's belief about the current state and the true state.
Local popularity based collaborative filters

Motivated by applications such as recommendation systems, we consider the estimation of a binary random field X obtained by unknown row and column permutations of a block constant random matrix. The estimation of X is based on observations Y, which are obtained by passing entries of X through a binary symmetric channel (BSC) (representing noisy user behavior) and an erasure channel (representing missing data). We analyze an estimation algorithm based on local popularity. We study the bit error rate (BER) in the limit as the matrix size approaches infinity and the erasure rate approaches unity at a specified rate. Our main result identifies three regimes characterized by the cluster size and erasure rate. In one regime, the algorithm has asymptotically zero BER, in another regime the BER is bounded away from 0 and 1/2, while in the remaining regime, the algorithm fails and BER approaches 1/2. Numerical results for the Movielens dataset and comparison with earlier work is also given.
Congestion-Aware Video Streaming for Peer-to-Peer Live Multicast

Peer-to-peer video multicast is promising for largescale streaming video distribution over the Internet. Viewers contribute their resources to a peer-to-peer overlay network to act as relays for the media streams and no dedicated infrastructure is required. As packets are transmitted over long unreliable multipeer transmission paths, it is particularly challenging to achieve constant and high video quality and low end-to-end delay. In this article we analyze optimized scheduling for peer-to-peer live streaming, where multiple peers collaborate to simultaneously forward a video stream to a large set of receivers. We present a low-complexity scheduling method to transmit in priority the most important packets in terms of video quality to the receivers which will serve, in turn, the largest set of peers. This prioritization algorithm is combined with a distortionoptimized retransmission scheduler which operates at the receiver and adapts to the video content to request the most important missing packets first. Experiments carried out over simulated networks with hundreds of peers show the advantage of adaptive scheduling for low-latency streaming.
On the identification of the Fermi/LAT source 0FGL J2001.0+4352 with a BL Lac

We report on the identification of the gamma-ray source 0FGL J20001.0+4352 listed in the Fermi bright source catalogue. This object, which has an observed 1–100 GeV flux of (7.8 ± 1.2) × 10−9 ph cm−2 s−1 and is located close to the Galactic plane, is not associated with any previously known high-energy source. We use archival XMM–Newton and Swift/X-ray Telescope (XRT) data to localize with arcsec accuracy the X-ray counterpart of this GeV emitter and to characterize its X-ray properties: the source is bright (the 0.2–12 keV flux is 1.9 × 10−12 erg cm−2 s−1), variable (by a factor of ∼2) and with a steep power-law spectrum (Γ= 2.7). It coincides with a radio bright (∼200 mJy at 8.4 GHz) and flat spectrum object [MG4 J200112+4352 in NASA/IPAC Extragalactic Database (NED)]. Broad-band optical photometry of this source suggests variability also in this waveband, while a spectroscopic follow-up observation provides the first source classification as a BL Lac object. The source SED, as well as the overall characteristics and optical classification, point to a high frequency peaked blazar identification for 0FGL J2001.0+4352.
Evidence for a language quantitative trait locus on chromosome 7q in multiplex autism families.

Autism is a syndrome characterized by deficits in language and social skills and by repetitive behaviors. We hypothesized that potential quantitative trait loci (QTLs) related to component autism endophenotypes might underlie putative or significant regions of autism linkage. We performed nonparametric multipoint linkage analyses, in 152 families from the Autism Genetic Resource Exchange, focusing on three traits derived from the Autism Diagnostic Interview: "age at first word," "age at first phrase," and a composite measure of "repetitive and stereotyped behavior. " Families were genotyped for 335 markers, and multipoint sib pair linkage analyses were conducted. Using nonparametric multipoint linkage analysis, we found the strongest QTL evidence for age at first word on chromosome 7q (nonparametric test statistic [Z] 2.98; P=.001), and subsequent linkage analyses of additional markers and association analyses in the same region supported the initial result (Z=2.85, P=.002; chi(2)=18.84, df 8, P=. 016). Moreover, the peak fine-mapping result for repetitive behavior (Z=2.48; P=.007) localized to a region overlapping this language QTL. The putative autism-susceptibility locus on chromosome 7 may be the result of separate QTLs for the language and repetitive or stereotyped behavior deficits that are associated with the disorder.
Part-of-Speech Induction in Dependency Trees for Statistical Machine Translation

This paper proposes a nonparametric Bayesian method for inducing Part-ofSpeech (POS) tags in dependency trees to improve the performance of statistical machine translation (SMT). In particular, we extend the monolingual infinite tree model (Finkel et al., 2007) to a bilingual scenario: each hidden state (POS tag) of a source-side dependency tree emits a source word together with its aligned target word, either jointly (joint model), or independently (independent model). Evaluations of Japanese-to-English translation on the NTCIR-9 data show that our induced Japanese POS tags for dependency trees improve the performance of a forestto-string SMT system. Our independent model gains over 1 point in BLEU by resolving the sparseness problem introduced in the joint model.
NJL model with infrared confinement

We consider an extended Nambu--Jona-Lasinio (NJL) model for the light meson sector of QCD where unphysical quark production thresholds are excluded by an infrared cut-off on the momentum integration within quark loop diagrams. This chiral quark model conserves the low energy theorems. The infrared cut-off is fixed selfconsistently by the dynamically generated quark mass (quark condensate). The masses and decay widths of the \sigma- and \rho-mesons are described in the model.
A Communication Perspective on Automatic Text Categorization

The basic concern of a Communication System is to transfer information from its source to a destination some distance away. Textual documents also deal with the transmission of information. Particularly, from a text categorization system point of view, the information encoded by a document is the topic or category it belongs to. Following this initial intuition, a theoretical framework is developed where Automatic Text Categorization(ATC) is studied under a Communication System perspective. Under this approach, the problematic indexing feature space dimensionality reduction has been tackled by a two-level supervised scheme, implemented by a noisy terms filtering and a subsequent redundant terms compression. Gaussian probabilistic categorizers have been revisited and adapted to the concomitance of sparsity in ATC. Experimental results pertaining to 20 Newsgroups and Reuters-21578 collections validate the theoretical approaches. The noise filter and redundancy compressor allows an aggressive term vocabulary reduction (reduction factor greater than 0.99) with a minimum loss (lower than 3 percent) and, in some cases, gain (greater than 4 percent) of final classification accuracy. The adapted Gaussian Naive Bayes classifier reaches classification results similar to those obtained by state-of-the-art Multinomial Naive Bayes (MNB) and Support Vector Machines (SVMs).
Cytoskeleton and Consciousness: An Evolutionary Based Review

The fields of quantum biology and physics are now starting to unite to solve the mysteries associated with the field of evolutionary biology. One such question is the origination and propagation of consciousness which has always been ambiguous and in order to understand this concept, many theories have been proposed by several philosophers and scientists. This review paper agrees with the idea, that evolution is not a random process but hypothesizes, that its succession was managed by the expanding level of consciousness due to cell division and cell differentiation. Several theories propose that the cytoskeleton and its proteins are promoters for consciousness in the brain, which propagates by means of super-conductance. A better correlation of cytoskeletal evolution and consciousness could help solve the enigma of the origination, propagation and existence of consciousness. This review is a compilation of theories, evidences and scientific studies which intends to bring an association between propagation of consciousness and the evolution of the cytoskeleton and its proteins.
A probabilistic assessment of historic land use CO 2 emissions based on atmospheric , oceanic , and ice-core observations

Carbon dioxide emissions from anthropogenic land use changes are an important climate forcing. Current estimates of land use change CO 2 emissions (LUCCE) are deeply uncertain. This uncertainty limits the mechanistic understanding of the global carbon cycle and the skill of carbon cycle and climate projections. Here we assimilate oceanic, atmospheric, and ice core observations into a simple carbon cycle model to assess the relative likelihood of published LUCCE estimates. We identify as the highest likelihood LUCCE estimate a recent LUCCE estimate derived in a study using a cropland inventory land use dataset combined with the geographically explicit terrestrial carbon cycle component of the Integrated Science Assessment Model. We show that using Bayesian data assimilation to account for uncertainty in LUCCE estimates can reduce overconfidence and bias in model parameters and projections. We use this framework to derive a likelihood based average of LUCCE estimates. This approach leads to a sharpening of parameter estimates and a tightening of projections of future carbon sinks.
Model-based feature extraction of electrocardiogram using mean shift

Feature extraction of electrocardiogram (ECG) is the fundamental work of further automatic diagnosis. However, suffered from various kinds of noises with white, pink, and other colors, feature extraction is not a straightforward work but requires necessary signal processing techniques. In this paper, we propose an accurate and robust ECG feature extraction method based on mean shift algorithm which has the ability to remove noise involved in input signal by taking advantage of its embedded Gaussian filter and locate extremes of input signal using gradient optimization based on self-adaptive search steps. To demonstrate the availability and efficacy of the proposed method, we conduct experiments on signals contaminated by noises of white, pink and brown colors from 5dB to 15dB signal-noise ratios. Clean signals are produced by ECG synthesizer (ECGSyn) so that we can obtain the real features and quantitatively calculate feature extraction errors of the proposed method. Experiment results verify that our method can handle various kinds of noises and achieve satisfactory feature extraction performance.
ISUAL AND C HEMICAL S IGNALS OF S OCIAL C OMMUNICATION : P ROVIDING THE L INK TO H ABITAT AND E NVIRONMENT

Social communication in most reptiles involves primarily visual and chemical signals. Components of visual signals include movement (frequency, motor pattern), colors and color patterns, which can convey different information. Chemical signals also can be complex, containing a variety of components conveying information on species identity, sex, reproductive condition, body size, social status, feeding status, and immune status. Fence lizards (Sceloporus) show fascinating variation in color patterning and in motion display patterning, and behavioral responses to conspecific chemicals. Sceloporus are found in an array of habitats in North and Central America, as diverse as shrub-steppe habitat of the Great Basin desert, arid deserts of the American southwest and Mexico, pine-oak woodlands, and semi-deciduous tropical forests. Working at the species level and in a phylogenetic context, we study the evolution of multimodal and multicomponent communicative signals. Centered on behavior, our work examines physiological mechanisms involved in signal production and in signal reception, and the potential costs and benefits of signals and signal components. We are especially interested in endocrine mechanisms and evolutionary variation in these mechanisms. Endocrine mechanisms have the potential to constrain or to facilitate evolution, depending on the degree to which suites of traits are closely coupled to a given endocrine mechanism.
SULT 1 A 1 Arg 213 His Polymorphism and Lung Cancer Risk : a Meta-analysis

Sulfotransferases (SULTs) are involved in the phase II metabolism of endogenous and exogenous compounds including drugs, thyroid and steroid hormones, catecholamines and procarcinogenic agents (Falany, 1997; Richard et al., 2001). Sulfotransferase 1A1 (SULT1A1), an important member of this enzyme superfamily, has high activity towards a wide range of substrates including environmental and tobacco carcinogens. SULT1A1 catalyze the sulfonation of N-hydroxy derivatives of arylamines and heterocyclic amines, which are presented in tobacco smoke, to form more reactive DNA-damaging electrophiles (Ozawa et al., 1994; Chou et al., 1995). Sulfonation can also activate another major class of tobacco carcinogens, polycyclic aromatic hydrocarbons (PAHs) and nitro PAHs (Watabe et al., 1982; Surh et al., 1995; Arlt et al., 2002). Therefore, reduced activity of SULT enzymes may result in accumulation of potential carcinogens. Several single nucleotide polymorphisms have been identified in the SULT1A1 gene (Raftogianis et al.,
Campylobacteriosis in Urban versus Rural Areas: A Case-Case Study Integrated with Molecular Typing to Validate Risk Factors and to Attribute Sources of Infection

Campylobacter infection is a leading cause of bacterial gastroenteritis worldwide, and most clinical cases appear as isolated, sporadic infections for which the source is rarely apparent. From July 2005 to December 2007 we conducted a prospective case-case study of sporadic, domestically-acquired Campylobacter enteritis in rural versus urban areas and a prevalence study of Campylobacter in animal and environmental sources in the Eastern Townships, Quebec. Isolates were typed using Multilocus Sequence Typing (MLST) to reinforce the case-case findings and to assign a source probability estimate for each human isolate. The risk of human campylobacteriosis was 1.89-fold higher in rural than urban areas. Unconditional multivariate logistic regression analysis identified two independent risk factors associated with human Campylobacter infections acquired in rural area: occupational exposure to animals (OR = 10.6, 95% CI: 1.2–91, p = 0.032), and household water coming from a private well (OR = 8.3, 95% CI: 3.4–20.4, p<0.0001). A total of 851 C. jejuni isolates (178 human, 257 chicken, 87 bovine, 266 water, 63 wild bird) were typed using MLST. Among human isolates, the incidence rates of clonal complexes (CC) CC-21, CC-45, and CC-61 were higher in rural than urban areas. MLST-based source attribution analysis indicated that 64.5% of human C. jejuni isolates were attributable to chicken, followed by cattle (25.8%), water (7.4%), and wild birds (2.3%). Chicken was the attributable source for the majority of cases, independent of residential area, sex and age. The increased incidence in rural compared to urban areas was associated with occupational exposure to animals, particularly cattle among those aged 15–34 years, and with consumption of private well water. Both bovine and water exposure appeared to contribute to the seasonal variation in campylobacteriosis. These results provide a basis for developing public education and preventive programs targeting the risk factors identified.