Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the protective effect of Nigella sativa extract and its primary active component thymoquinone against DMBA-induced breast cancer in female rats

Introduction The historical use of black cumin seed (Nigella sativa) dates back centuries, being embedded in Arabian culture and having a long history of unsurpassed medicinal value with versatility to treat a wide range of ailments. Thymoquinone (TQ) is now known to be the primary active constituent of black cumin seed oil (BCS oil) responsible for its medicinal effects and also showing promise for treatment of cancer. Material and methods In the current study, we have studied the effects of TQ and BCS oil on tumor markers (MDA, LDH, ALP and AST), histopathological alterations and the regulation of several genes (Brca1, Brca2, Id-1 and P53 mutation) related to breast cancer in female rats induced by 7,12-dimethylbenz[a]anthracene (DMBA) treatment. Rats received a single dose (65 mg/kg b.w.) of DMBA via an intragastric tube to induce breast cancer. Animals that received DMBA were treated orally with 1, 5, 10 mg/kg of TQ or BCS oil via an intragastric tube three times per week for 4 months. Results We found that TQ and then BCS reduced the rate of tumor markers (levels of MDA and LDH as well as ALP and AST activities), inhibited the histopathological alterations and decreased the expression of the Brca1, Brca2, Id-1 and P53 mutations in mammary tissues of female rats induced by DMBA treatment. Conclusions The results suggest that TQ and BCS oil exert a protective effect against breast carcinogens. The antioxidant property of TQ and BCS oil is mediated by their actions and investigating other underlying mechanisms merits further studies.
Adversarial Leakage in Games

While the minimax (or maximin) strategy has become the standard and most agreed-upon solution for decision making in adversarial settings, as discussed in game theory, computer science, and other disciplines, its power arises from the use of mixed strategies, also known as probabilistic algorithms. Nevertheless, in adversarial settings we face the risk of information leakage about the actual strategy instantiation. Hence, real robust algorithms should take information leakage into account. In this paper we introduce the notion of adversarial leakage in games, namely, the ability of a player to learn the value of $b$ binary predicates about the strategy instantiation of her opponent. Different leakage models are suggested and tight bounds on the effect of adversarial leakage as a function of the level of leakage (captured by $b$) are established. The complexity of computing optimal strategies under these adversarial leakage models is also addressed. Together, our study introduces a new framework for robust.
On the random graph induced by a random key predistribution scheme under full visibility

We consider the random graph induced by the random key predistribution scheme of Eschenauer and Gligor under the assumption of full visibility. We show the existence of a zero-one law for the absence of isolated nodes, and complement it by a Poisson convergence for the number of isolated nodes. Leveraging earlier results and analogies with Erdos-Renyi graphs, we explore similar results for the property of graph connectivity.
Proposed scheme for palm vein recognition based on Linear Discrimination Analysis and nearest neighbour classifier

Palm vein recognition is a new promising field in biometrics. The palm vein pattern provides highly discriminating features that are difficult to forge because it resides underneath the palmar skin. However, the issues of extracting the palm vein features and the high dimension of the feature space are still open. Therefore, in this paper, we propose an improved scheme of palm vein recognition method based on the Linear Discrimination Analysis (LDA) to extract the discriminative features with low dimension. LDA is later followed by the matching procedure using cosine distance nearest neighbor classifier. The performance of the proposed scheme produced 99.50% for identification rate, 100% for verification rate and 0.0% of Equal Error Rate (EER). The experiments prove that the proposed method has a better performance compared with Principal Component Analysis and Gabor filter methods.
Design Issues for Hexapod Walking Robots

Hexapod walking robots have attracted considerable attention for several decades. Many studies have been carried out in research centers, universities and industries. However, only in the recent past have efficient walking machines been conceived, designed and built with performances that can be suitable for practical applications. This paper gives an overview of the state of the art on hexapod walking robots by referring both to the early design solutions and the most recent achievements. Careful attention is given to the main design issues and constraints that influence the technical feasibility and operation performance. A design procedure is outlined in order to systematically design a hexapod walking robot. In particular, the proposed design procedure takes into account the main features, such as mechanical structure and leg configuration, actuating and driving systems, payload, motion conditions, and walking gait. A case study is described in order to show the effectiveness and feasibility of the proposed design procedure.
Executive Control of Attention in Narcolepsy

Background Narcolepsy with cataplexy (NC) is a disabling sleep disorder characterized by early loss of hypocretin neurons that project to areas involved in the attention network. We characterized the executive control of attention in drug-free patients with NC to determine whether the executive deficits observed in patients with NC are specific to the disease itself or whether they reflect performance changes due to the severity of excessive daytime sleepiness. Methodology Twenty-two patients with NC compared to 22 patients with narcolepsy without cataplexy (NwC) matched for age, gender, intellectual level, objective daytime sleepiness and number of sleep onset REM periods (SOREMPs) were studied. Thirty-two matched healthy controls were included. All participants underwent a standardized interview, completed questionnaires, and neuropsychological tests. All patients underwent a polysomnography followed by multiple sleep latency tests (MSLT), with neuropsychological evaluation performed the same day between MSLT sessions. Principal Findings Irrespective of diagnosis, patients reported higher self-reported attentional complaints associated with the intensity of depressive symptoms. Patients with NC performed slower and more variably on simple reaction time tasks than patients with NwC, who did not differ from controls. Patients with NC and NwC generally performed slower, reacted more variably, and made more errors than controls on executive functioning tests. Individual profile analyses showed a clear heterogeneity of the severity of executive deficit. This severity was related to objective sleepiness, higher number of SOREMPs on the MSLT, and lower intelligence quotient. The nature and severity of the executive deficits were unrelated to NC and NwC diagnosis. Conclusions We demonstrated that drug-free patients with NC and NwC complained of attention deficit, with altered executive control of attention being explained by the severity of objective sleepiness and global intellectual level. Further studies are needed to explore whether medications that promote wakefulness can improve the executive functions in narcolepsy.
Role of Antigen-Presenting Cells in Mediating Tolerance and Autoimmunity

The mechanisms that determine whether receptor stimulation leads to lymphocyte tolerance versus activation remain poorly understood. We have used rat insulin promoter (RIP)-gp/P14 double-transgenic mice expressing the lymphocytic choriomeningitis virus (LCMV) glycoprotein (gp) on pancreatic β-islet cells together with T cells expressing an LCMV-gp–specific T cell receptor to assess the requirements for the induction of autoimmunity. Our studies have shown that administration of the gp peptide gp33 leads to the activation of P14-transgenic T cells, as measured by the upregulation of activation markers and the induction of effector cytotoxic activity. This treatment also leads to expansion and deletion of P14 T cells. Despite the induction of cytotoxic T lymphocyte activity, peptide administration is not sufficient to induce diabetes. However, the administration of gp peptide together with an activating anti-CD40 antibody rapidly induces diabetes. These findings suggest that the induction of tolerance versus autoimmunity is determined by resting versus activated antigen-presenting cells.
Use of query reformulation and relevance feedback by Excite users

Examines the use of query reformulation, and particularly the use of relevance feedback by users of the Excite Web search engine. A total of 985 user search sessions from a data set of 18,113 user search sessions containing 51,473 queries were examined. Includes a qualitative and quantitative analysis of 191 user sessions including more than one query, to examine patterns of user query reformulation; and second, all 804 user sessions including relevance feedback were examined. Results show limited use of query reformulation and relevance feedback by Excite users – only one in five users reformulated queries. Most relevance feedback sessions were successful. Identifies the most common pattern of searching and discusses implications for Web search system design.
An eighth-order CMOS lowpass filter with 30-120 Mhz tuning range and programmable boost

A CMOS lowpass filter with programmable cutoff frequency is presented. The architecture is gm/C type with the gm controlled through a resistor servo approach. The wide tuning range is achieved by exploiting a dual loop control over a degenerated differential pair. This filter, implemented in a 0.25 µm 2.5V CMOS technology, dissipates 120mW with fc=120MHz and has a die area of 0.23mm2.
Novel substrate integrated waveguide cavity filter with defected ground structure

An open-structure eigenvalue problem of substrate integrated waveguide (SIW) cavity structures is investigated in detail by using a finite-difference frequency-domain method, and the quality (Q) factor of such SIW cavities is given. Based on the concept of a defected ground structure, a new class of SIW cavity bandpass filters are designed, fabricated, and measured around 5.8 GHz. With their fabrication on standard printed circuit boards, such filters present the advantages of high-Q factor, high power capacity, and small size. Simulated and measured results are presented and discussed to show promising performances of the proposed filters.
Asymptotic Analysis of Amplify and Forward Relaying in a Parallel MIMO Relay Network

This paper studies the setup of a parallel MIMO relay network in which K relays, each equipped with N antennas, assist in transmitting data between a source and a destination, each equipped with M antennas (M ≤ N), in the half-duplex mode. It is assumed that there is no direct source-destination link and the communication is performed in two hops. An amplify-and-forward relaying scheme called Incremental Cooperative Beamforming Scheme (ICBS) is introduced and shown to achieve the capacity of the network in the asymptotic case of K → ∞ with a gap scaling of at most [(log(K))/({4}√{K})]. This result is shown to hold as long as the power of each relay is significantly larger than [(log3 (K) log(log(K)))/(K)]. In addition, in the case that the source power is equal to the relays' power and both tend to infinity, the proposed scheme is shown to achieve the full multiplexing gain regardless of the number of relays. Simulation results confirm the validity of analytical arguments.
Global Transcription Profiling Reveals Comprehensive Insights into Hypoxic Response in Arabidopsis1[w]

Plants have evolved adaptation mechanisms to sense oxygen deficiency in their environments and make coordinated physiological and structural adjustments to enhance their hypoxic tolerance. To gain insight into how plants respond to low-oxygen stress, gene expression profiling using whole-genome DNA amplicon microarrays was carried out at seven time points over 24 h, in wild-type and transgenic PSAG12:ipt Arabidopsis (Arabidopsis thaliana) plants under normoxic and hypoxic conditions. Transcript levels of genes involved in glycolysis and fermentation pathways, ethylene synthesis and perception, calcium signaling, nitrogen utilization, trehalose metabolism, and alkaloid synthesis were significantly altered in response to oxygen limitation. Analysis based on gene ontology assignments suggested a significant down-regulation of genes whose functions are associated with cell walls, nucleosome structures, water channels, and ion transporters and a significant up-regulation of genes involved in transcriptional regulation, protein kinase activity, and auxin responses under conditions of oxygen shortage. Promoter analysis on a cluster of up-regulated genes revealed a significant overrepresentation of the AtMYB2-binding motif (GT motif), a sugar response element-like motif, and a G-box-related sequence, and also identified several putative anaerobic response elements. Finally, quantitative real-time polymerase chain reactions using 29 selected genes independently verified the microarray results. This study represents one of the most comprehensive analyses conducted to date investigating hypoxia-responsive transcriptional networks in plants.
Model-based Security Metrics Using ADversary VIew Security Evaluation (ADVISE)

System architects need quantitative security metrics to make informed trade-off decisions involving system security. The security metrics need to provide insight on weak points in the system defense, considering characteristics of both the system and its adversaries. To provide such metrics, we formally define the ADversary View Security Evaluation (ADVISE) method. Our approach is to create an executable state-based security model of a system and an adversary that represents how the adversary is likely to attack the system and the results of such an attack. The attack decision function uses information about adversary attack preferences and possible attacks against the system to mimic how the adversary selects the most attractive next attack step. The adversary's decision involves looking ahead some number of attack steps. System architects can use ADVISE to compare the security strength of system architecture variants and analyze the threats posed by different adversaries. We demonstrate the feasibility and benefits of ADVISE using a case study. To produce quantitative model-based security metrics, we have implemented the ADVISE method in a tool that facilitates user input of system and adversary data and automatically generates executable models.
Doing research on a deployed spoken dialogue system: one year of let's go! experience

This paper describes our work with Let’s Go, a telephonebased bus schedule information system that has been in use by the Pittsburgh population since March 2005. Results from several studies show that while task success correlates strongly with speech recognition accuracy, other aspects of dialogue such as turn-taking, the set of error recovery strategies, and the initiative style also significantly impact system performance and user behavior. Index Terms: spoken dialogue systems, real-world applications, speech recognition
Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification

Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits. In stochastic spectral methods, one needs to determine a set of orthonormal polynomials and a proper numerical quadrature rule. The former are used as the basis functions in a generalized polynomial chaos expansion. The latter is used to compute the integrals involved in stochastic spectral methods. Obtaining such information requires knowing the density function of the random input a-priori. However, individual system components are often described by surrogate models rather than density functions. In order to apply stochastic spectral methods in hierarchical uncertainty quantification, we first propose to construct physically consistent closed-form density functions by two monotone interpolation schemes. Then, by exploiting the special forms of the obtained density functions, we determine the generalized polynomial-chaos basis functions and the Gauss quadrature rules that are required by a stochastic spectral simulator. The effectiveness of our proposed algorithm is verified by both synthetic and practical circuit examples.
User study of the free-eye photo browsing interface

The striking proliferation of user-generated as well as broadcasted visual content prompted a high demand for effective content management tools and interfaces for search and browsing of visual media. This paper presents a novel intuitive interactive interface for browsing of large-scale image collections. It visualises underlying structure of the dataset by its size and spatial relations. In order to achieve this, images are initially clustered using an unsupervised graph-based clustering algorithm. By selecting images that are hierarchically laid out on the screen, user can intuitively navigate through the collection or search for specific content. The conducted experimental results based on user evaluation of photo search, browsing and selection demonstrate good usability of the presented system and improvement when compared to the standard methods for interaction with large-scale image collections.
Epidemic Algorithms for Replicated Databases

We present a family of epidemic algorithms for maintaining replicated database systems. The algorithms are based on the causal delivery of log records where each record corresponds to one transaction instead of one operation. The first algorithm in this family is a pessimistic protocol that ensures serializability and guarantees strict executions. Since we expect the epidemic algorithms to be used in environments with low probability of conflicts among transactions, we develop a variant of the pessimistic algorithm which is optimistic in that transactions commit as soon as they terminate locally and inconsistencies are detected asynchronously as the effects of committed transactions propagate through the system. The last member of the family of epidemic algorithms is pessimistic and uses voting with quorums to resolve conflicts and improve transaction response time. A simulation study evaluates the performance of the protocols.
Assessment of debris flow susceptibility using bivariate and multivariate statistical analyses and verification based on catastrophic events from 2014 in the Krivánska Malá Fatra Mountains, Slovakia

The presented study shows using of bivariate and multivariate statistical analyses in mountain area of the Krivánska Fatra Mountains affected by debris flows. Three generations of data were studied in order to assess the debris flows in the area, from these two main periods of debris flows were taken into the analysis: the debris flows from 1950s to 1970s and catastrophic debris flows from July 2014. Various input data were used in the statistical analyses: elevation, slope angle, plan curvature, topographic wetness index, flow accumulation, lithology, and land cover. Two main evaluations were made: first using the older debris flow data and second using debris flow data from the both periods. Receiver operating characteristic analysis was performed in order to assess the reliability of the models with the area under curve more than 95 % for both evaluations and more than 85 % for the first evaluation checked by both periods of debris flows in case of multivariate analysis, respectively almost 83 % and 80 % in case of bivariate analysis. The comparison with existing avalanche tracks was performed as well and shows satisfactory results. The tracks of debris flows from July 2014 show the extraordinariness of the event in comparison with older debris flows. Experimental assessment of natural hazard was performed using the map of difference between the two susceptibility maps in order to find out the areas of possible high magnitude low frequency events.
Joint Multi-View Face Alignment in the Wild

The de facto algorithm for facial landmark estimation involves running a face detector with a subsequent deformable model fitting on the bounding box. This encompasses two basic problems: 1) the detection and deformable fitting steps are performed independently, while the detector might not provide the best-suited initialization for the fitting step, and 2) the face appearance varies hugely across different poses, which makes the deformable face fitting very challenging and thus distinct models have to be used (e.g., one for profile and one for frontal faces). In this paper, we propose the first, to the best of our knowledge, joint multi-view convolutional network to handle large pose variations across faces in-the-wild, and elegantly bridge face detection and facial landmark localization tasks. The existing joint face detection and landmark localization methods focus only on a very small set of landmarks. By contrast, our method can detect and align a large number of landmarks for semi-frontal (68 landmarks) and profile (39 landmarks) faces. We evaluate our model on a plethora of datasets including the standard static image datasets such as IBUG, 300W, COFW, and the latest Menpo Benchmark for both semi-frontal and profile faces. A significant improvement over the state-of-the-art methods on deformable face tracking is witnessed on the 300VW benchmark. We also demonstrate state-of-the-art results for face detection on FDDB and MALF datasets.
Asymptotic Achievability of the CramÉr–Rao Bound for Noisy Compressive Sampling

We consider a model of the form y = Ax + n, where x isin CM is sparse with at most L nonzero coefficients in unknown locations, y isin CN is the observation vector, A isin CN times M is the measurement matrix and n isin CN is the Gaussian noise. We develop a Cramer-Rao bound on the mean squared estimation error of the nonzero elements of x, corresponding to the genie-aided estimator (GAE) which is provided with the locations of the nonzero elements of x. Intuitively, the mean squared estimation error of any estimator without the knowledge of the locations of the nonzero elements of x is no less than that of the GAE. Assuming that L/N is fixed, we establish the existence of an estimator that asymptotically achieves the Cramer-Rao bound without any knowledge of the locations of the nonzero elements of x as N rarr infin , for A a random Gaussian matrix whose elements are drawn i.i. d. according to N (0,1) .