Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative online teleoperation with spatial dynamic voting and a human "Tele-Actor"

Internet-based "online robots" now provide public access to remote locations such as museums and laboratories. The Tele-Actor is a collaborative online teleoperation system for distance learning that allows many students to simultaneously share control of a single mobile resource. Our goal is to preserve the educational advantages of field trips without the drawbacks of group travel. We propose the "spatial dynamic voting" (SDV) interface for multiple operator single robot (MOSR) teleoperation. The SDV collects, displays, and analyzes a sequence of spatial votes from multiple online operators at their Internet browsers. The votes drive the motion of a single mobile robot or human "Tele-Actor". The paper describes Version 3.0 of the system architecture, SDV interface, algorithms for automated goal selection, and metrics for collaboration and leadership. We report results from a July 2001 field test with 56 remote users.
In Vitro Inflammation Inhibition Model Based on Semi-Continuous Toll-Like Receptor Biosensing

A chemical inhibition model of inflammation is proposed by semi-continuous monitoring the density of toll-like receptor 1 (TLR1) expressed on mammalian cells following bacterial infection to investigate an in vivo-mimicked drug screening system. The inflammation was induced by adding bacterial lysate (e.g., Pseudomonas aeruginosa) to a mammalian cell culture (e.g., A549 cell line). The TLR1 density on the same cells was immunochemically monitored up to three cycles under optimized cyclic bacterial stimulation-and-restoration conditions. The assay was carried out by adopting a cell-compatible immunoanalytical procedure and signal generation method. Signal intensity relative to the background control obtained without stimulation was employed to plot the standard curve for inflammation. To suppress the inflammatory response, sodium salicylate, which inhibits nuclear factor-κB activity, was used to prepare the standard curve for anti-inflammation. Such measurement of differential TLR densities was used as a biosensing approach discriminating the anti-inflammatory substance from the non-effector, which was simulated by using caffeic acid phenethyl ester and acetaminophen as the two components, respectively. As the same cells exposed to repetitive bacterial stimulation were semi-continuously monitored, the efficacy and toxicity of the inhibitors may further be determined regarding persistency against time. Therefore, this semi-continuous biosensing model could be appropriate as a substitute for animal-based experimentation during drug screening prior to pre-clinical tests.
Improved Oral Delivery of N-(4-Hydroxyphenyl)Retinamide with a Novel LYM-X-SORB Organized Lipid Complex

Purpose: Fenretinide [N-(4-hydroxyphenyl)retinamide (4-HPR)] is a cytotoxic retinoid that suffers from a wide interpatient variation in bioavailability when delivered orally in a corn oil capsule. The poor bioavailability of the capsule formulation may have limited responses in clinical trials, and the large capsules are not suitable for young children. To support the hypothesis that a novel organized lipid matrix, LYM-X-SORB, can increase the oral bioavailability of fenretinide, fenretinide in LYM-X-SORB matrix and in a powderized LYM-X-SORB formulation was delivered to mice. Experimental Design: Fenretinide was delivered orally to mice as the contents of the corn oil capsule, in LYM-X-SORB matrix (4-HPR/LYM-X-SORB matrix) or in a LYM-X-SORB matrix powderized with sugar and flour (4-HPR/LYM-X-SORB oral powder). Levels of 4-HPR, and its principal metabolite, N-(4-methoxyphenyl)retinamide, were assayed in plasma and tissues. Results: In a dose-responsive manner, from 120 to 360 mg/kg/d, delivery to mice of 4-HPR in LYM-X-SORB matrix, or as 4-HPR/LYM-X-SORB oral powder, increased 4-HPR plasma levels up to 4-fold (P < 0.01) and increased tissue levels up to 7-fold (P < 0.01) compared with similar doses of 4-HPR delivered using capsule contents. Metabolite [N-(4-methoxyphenyl)retinamide] levels mirrored 4-HPR levels. Two human neuroblastoma murine xenograft models showed increased survival (P < 0.03), when treated with 4-HPR/LYM-X-SORB oral powder, confirming the bioactivity of the formulation. Conclusions: 4-HPR/LYM-X-SORB oral powder is a novel, oral drug delivery formulation, suitable for pediatric use, which warrants further development for the delivery of fenretinide in the treatment of cancer. A phase I clinical trial in pediatric neuroblastoma is in progress.
Measurement Based P2P Streaming Media System Topology Analysis

Snapshot is usually applied in p2p network topology analysis. In this paper, we develop the topology crawler software to probe the PPLive application. Based on the measured trace, we characterize the PPLive topology with metrics including degree distribution, clustering coefficient, network diameter, characteristic path length, connectivity matrix and reciprocity coefficient. In additional, we also use visualization methods (BOSAM and pajek) to analyzing the network. We compare the characteristics of PPLive with that of Gnutella, UUSee, and ER random network.
Active learning for Bayesian network models of biological networks using structure priors

Active learning methods aim at identifying measurements that should be done in order to benefit a learning problem maximally. We use Bayesian networks as models of biological systems and show how active learning can be used to select new measurements to be incorporated via structure priors. Improved performance of the methods is demonstrated with both simulated and real datasets.
Conditional sojourn time of optimal scheduling policy in a multi-class single-server queue ⋆

Based on the groundbreaking result of Gittins on the multiarmed bandit problem we provide a characterization of the optimal nonanticipating scheduling policy in a multi-class single-server queue. We apply Gittins’ framework to characterize the optimal policy when the service time distribution of the various classes belong to the set of Decreasing Hazard Rate (DHR) distributions, like Pareto or hyper-exponential. When there is only one class it is known that the Least Attained Service (LAS) policy is optimal. We show that in the multi-class case the optimal policy is a priority discipline, where jobs of the various classes depending on their attained service are classified into several priority levels. Using a tagged-job approach and the collective mark method we obtain, for every class, the mean sojourn time conditioned on the service requirement. Numerical computations show that the performance gain of Gittins’ policy can be significant.
An Improved Algorithm of Contour Initialization in Active Contour Model

An improved algorithm of Contour Initialization in GVF Snake Model is proposed in this paper based on detailed analysis of the problems in current active contour models: poor performance under interference, large computational cost, inability to converge to complex or rough contours and difficulty for setting initial contour, etc. Our method efficiently solved the problems in complex or rough contours initialization by connecting the initial points of different resolutions obtained by multi-scale edge detection methods based on wavelet transform and suitably controlling the number of GVF force field iterations. Experiments show that the initial contour can be accurately set close to the objective contour and successfully extract the objective contours with interferential edges and points. The new contour initialization algorithm has further reduced computational cost, improved the anti-jamming ability and extended the application range of GVF Snake model.
Automatic Conversion of Dialectal Tamil Text to Standard Written Tamil Text using FSTs

We present an efficient method to automatically transform spoken language text to standard written language text for various dialects of Tamil. Our work is novel in that it explicitly addresses the problem and need for processing dialectal and spoken language Tamil. Written language equivalents for dialectal and spoken language forms are obtained using Finite State Transducers (FSTs) where spoken language suffixes are replaced with appropriate written language suffixes. Agglutination and compounding in the resultant text is handled using Conditional Random Fields (CRFs) based word boundary identifier. The essential Sandhi corrections are carried out using a heuristic Sandhi Corrector which normalizes the segmented words to simpler sensible words. During experimental evaluations dialectal spoken to written transformer (DSWT) achieved an encouraging accuracy of over 85% in transformation task and also improved the translation quality of Tamil-English machine translation system by 40%. It must be noted that there is no published computational work on processing Tamil dialects. Ours is the first attempt to study various dialects of Tamil in a computational point of view. Thus, the nature of the work reported here is pioneering.
Netflow based system for NAT detection

Revealing the misuse of network resources is one of the important fields in the network security, especially for the network administrators. One of them is the use of unauthorized NAT (Network Address Translation) devices (e.g. small office routers or wireless access points) inside the network which introduces serious security issues. There are several techniques proposed on how to detect NAT devices in the computer networks, but all these methods suffer from high false positive rate. Also there is no study how to perform NAT detection using NetFlow data, often used for monitoring and forensics analysis in large networks. The contribution of our work consists of the following: i) we have transformed existing NAT detection techniques to work with NetFlow data, ii) we propose three new NAT detection approaches, iii) we have designed a prototype of NAT detection system, which aggregates the results from various NAT detection techniques in order to minimize false positive and false negative rates.
Stretch‐induced endothelin B receptor‐mediated apoptosis in vascular smooth muscle cells

Growing evidence suggests that a pressure‐induced increase in the synthesis of endothelin (ET‐1) is involved in arterial remodeling and, as a consequence, in the manifestation of chronic hypertension. To study potential stretch‐induced changes in gene expression and their functional consequences, we have cultured rat aortic smooth muscle cells (raSMC) and porcine aortic endothelial cells (PAEC) on flexible elastomer membranes. The cells were periodically stretched (up to 20% elongation, 0.5 Hz, 6 h) and the expression of prepro‐ET‐1 and that of the endothelin A and B receptors (ETA‐R and ETB‐R) were analyzed by semi‐quantitative RT‐PCR analysis and ELISA (ET‐1). In contrast to PAEC where ET‐1 synthesis was up‐regulated up to eightfold on exposure to cyclic stretch, ET‐1 synthesis in raSMC was decreased by more than 80% under these conditions. ETA R‐mRNA expression in stretched raSMC declined to 50% whereas ETB R‐mRNA levels were increased up to 10‐fold. One functional consequence of this apparent shift in receptor abundance was an apoptosis‐promoting action of exogenous ET‐1 (10 nM), as judged by the appearance of subdiploid peaks during FACS analysis, caspase‐3 activation and chromatin condensation. This ET‐1‐induced apoptosis appeared to be ETB‐R mediated, as it was completely suppressed by the ETB‐R antagonist BQ 788 but not by the ETA‐R antagonist BQ 123. Moreover, raSMC derived from homozygous spotting lethal rats, which lack a functional ETB‐R, showed no signs of apoptosis after exposure to cyclic strain and exogenous ET‐1. These findings suggest a central role for the endothelin system in the onset of hypertension‐induced remodeling in conduit arteries, which may proceed via an initial stretch‐induced apoptosis of the smooth muscle cells. —Cattaruzza, M. , Dimigen, C. , Ehrenreich, H. , Hecker, M. Stretch‐induced endothelin B receptor‐mediated apoptosis in vascular smooth muscle cells. FASEB J. 14, 991–998 (2000)
Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies.
QoS-Sensitive Protocol Processing In Shared-Memory Multiprocessor Multimedia Servers

The advent of high-speed nrtworks and demand for distributed multimedia applications now requires that the communication subsystems in end hosts (or simply hosts) be designed and implemented to facilitate and provide certain quality-of-service (QoS) guarantees. An application specifies its &OS requirements for each active connection in terms of several parameters such as end-to-end delay, delay jitter, and bandwidth; additional requirements regarding packet loss and in-order delivery can also be specified [l, 21. Additionally, the application may need to specify its traffic cliaracteristics on each connection in order for the host communication subsystem and network to provide the required guarantees. Acceptance of a guaranteed-QoS connection by the network implies a contract between the network and the application that the requirements of the latter will be met as long as the application honors its traffic specifications. Given appropriate support within the network t o establish and maintain such connections, we focus on the problem of maintaining QoS-guarantees within the communication Subsystem on the host’. In particular we consider shared-memory multiprocessor (SMMP) hosts since mediumto large-scale SMMPs are increasingly being employed as multimedia servers and desktop workstations.
Performance Enhancement Using Network Coding in Dynamic Source Routing

Network coding is a new technique that allows the nodes in the network to code the incoming data and transmit. Significant gains such as throughput improvement, robustness, complexity and security can be obtained by using network coding. Dynamic source routing is a reactive protocol for multi hop mobile Ad hoc networks. This paper proposes a better DSR technique using Network coding to reduce the number of transmissions in mobile ad hoc network and increasing throughput efficiency. The simulation results when compared with existing DSR protocol shows potential throughput improvement and communicates more information with fewer packet transmissions. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of organizing committee of the 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015).
Maximum likelihood receivers for space-time coded MIMO systems with gaussian estimation errors

Maximum likelihood (ML) receivers for space-time coded multiple-input multiple-output (MIMO) systems with Gaussian channel estimation errors are proposed. Two different cases are considered. In the first case, the conditional probability density function (PDF) of the channel estimate is assumed Gaussian and known. In the second case, the joint PDF of the channel estimate and the true channel gain is assumed Gaussian and known. In addition to ML signal detection for space-time coded MIMO with ML and minimum mean-squared-error channel estimation, ML signal detection without channel estimation is also studied. Two suboptimal structures are derived. The Alamouti space-time codes are used to examine the performances of the new receivers. Simulation results show that the new receivers can reduce the gap between the conventional receiver with channel estimation errors and the receiver with perfect channel knowledge at least by half in some cases.
Kitty: sketching dynamic and interactive illustrations

We present Kitty, a sketch-based tool for authoring dynamic and interactive illustrations. Artists can sketch animated drawings and textures to convey the living phenomena, and specify the functional relationship between its entities to characterize the dynamic behavior of systems and environments. An underlying graph model, customizable through sketching, captures the functional relationships between the visual, spatial, temporal or quantitative parameters of its entities. As the viewer interacts with the resulting dynamic interactive illustration, the parameters of the drawing change accordingly, depicting the dynamics and chain of causal effects within a scene. The generality of this framework makes our tool applicable for a variety of purposes, including technical illustrations, scientific explanation, infographics, medical illustrations, children's e-books, cartoon strips and beyond. A user study demonstrates the ease of usage, variety of applications, artistic expressiveness and creative possibilities of our tool.
Appearance-Based Biometric Recognition: Secure Authentication and Cancellability

Although, biometrics provide high-confidence and trusted security, they suffer from a fatal weakness that emerges from permanence and limitation in quantities. Such a drawback puts biometric data under a substantial risk of fraudulent, which makes the replacement of traditional authentication systems infeasible with the lack of proper biometric data protection. This paper presents a novel biometric protection method to generate secure facial biometric templates used in statistical-based recognition algorithms such as 2DPCA. Original biometrics are polynomially transformed to the secure domain, where cooccurrence matrices are used to generate the final templates. The paper presents a unique relationship established by the Hadamard product within the transformation. The generated secure templates are used in the same fashion as original biometrics for evaluations using 2DPCA without any change to the recognition algorithm. And yet, evaluations confirm high security with enhanced recognition accuracy by 3% and 4.5% over the original and other transformed data respectively.
Bazaar: Strengthening User Reputations in Online Marketplaces

Online marketplaces are now a popular way for users to buy and sell goods over the Internet. On these sites, user reputations--based on feedback from other users concerning prior transactions--are used to assess the likely trustworthiness of users. However, because accounts are often free to obtain, user reputations are subject to manipulation through white-washing, Sybil attacks, and user collusion. This manipulation leads to wasted time and significant monetary losses for defrauded users, and ultimately undermines the usefulness of the online marketplace. In this paper, we propose Bazaar, a system that addresses the limitations of existing online marketplace reputation systems. Bazaar calculates user reputations using a max-flow-based technique over the network formed from prior successful transactions, thereby limiting reputation manipulation. Unlike existing approaches, Bazaar provides strict bounds on the amount of fraud that malicious users can conduct, regardless of the number of identities they create. An evaluation based on a trace taken froma real-world online marketplace demonstrates that Bazaar is able to bound the amount of fraud in practice, while only rarely impacting non-malicious users.
Sphingosine Kinase 1 and Cancer: A Systematic Review and Meta-Analysis

Background Sphingosine kinase 1 (SK1) is a key regulator of the dynamic ceramide/sphingosine 1-phosphate rheostat balance and important in the pathological cancer genesis, progression, and metastasis processes. Many studies have demonstrated SK1 overexpressed in various cancers, but no meta-analysis has evaluated the relationship between SK1 and various cancers. Methods We retrieved relevant articles from the PubMed, EBSCO, ISI, and OVID databases. A pooled odds ratio (OR) was used to assess the associations between SK1 expression and cancer; hazard ratios (HR) were used for 5-year and overall survival. Review Manager 5.0 was used for the meta-analysis, and publication bias was evaluated with STATA 12.0 (Egger’s test). Results Thirty-four eligible studies (n = 4,673 patients) were identified. SK1 positivity and high expression were significantly different between cancer, non-cancer, and benign tissues. SK1 mRNA and protein expression levels were elevated in the cancer tissues, compared with the normal tissues. SK1 positivity rates differed between various cancer types (lowest [27.3%] in estrogen receptor-positive breast cancer and highest [82.2%] in tongue squamous cell carcinoma). SK1 positivity and high expression were associated with 5-year survival; the HR was 1.86 (95% confidence interval [CI], 1.18–2.94) for breast cancer, 1.58 (1.08–2.31) for gastric cancer, and 2.68 (2.10–3.44) for other cancers; the total cancer HR was 2.21 (95% CI, 1.83–2.67; P < 0.00001). The overall survival HRs were 2.09 (95% CI, 1.35–3.22), 1.56 (1.08–2.25), and 2.62 (2.05–3.35) in breast, gastric, and other cancers, respectively. The total effect HR was 2.21 (95% CI, 1.83–2.66; P < 0.00001). Conclusions SK1 positivity and high expression were significantly associated with cancer and a shorter 5-year and overall survival. SK1 positivity rates vary tremendously among the cancer types. It is necessary to further explore whether SK1 might be a predictive biomarker of outcomes in cancer patients.
A Recursive Treatment of Collocations

This article discusses the treatment of collocations in the context of a long-term project on the development of multilingual NLP tools. Besides classical two-word collocations, we will focus on the case of complex collocations (3 words or more) for which a recursive design is presented in the form of collocation of collocations. Although comparatively less numerous than two-word collocations, the complex collocations pose important challenges for NLP. The article discusses how these collocations are retrieved from corpora, inserted and stored in a lexical database, how the parser uses such knowledge and what are the advantages offered by a recursive approach to complex collocations.