Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent Advances in Telexistence

Telexistence is fundamentally a concept named for the technology that enables a human being to have a real-time sensation of being at a place other than where he or she actually exists, and to interact with the remote environment, which may be real, virtual, or a combination of both. It also refers to an advanced type of teleoperation system which enables an operator at the control to perform remote tasks dexterously with the feeling of existing in a surrogate robot. Although conventional telexistence systems the author proposed back in 1980 provide an operator the real-time sensation of being in a remote environment, persons in the remote environment have only the sensation that a surrogate robot is present, not the operator. Mutual telexistence aims to solve this problem so that the existence of the operator is apparent to persons in the remote environment by providing mutual sensations of presence. This enables humans to be seemingly everywhere at the same time, i.e., to be virtually ubiquitous. In this paper, recent advances in telexistence technology is reviewed with special focus on mutual telexistence using RPT (Retro-reflective Projection Technology) and telexistence communication using immersive booth dubbed TWISTER (Telexistence Wide-angle Immersive STERoscope).
Online encounters: a new method of creating participatory art

The emergence of Web 2.0 technologies has moved our social activities online, and revolutionised the way we meet people and how we communicate with each other on a day-to-day basis. In turn, this has developed new platforms for artists to create and present work in, to network with other practitioners, and for participatory work to flourish, with opportunity for worldwide collaborations. Online social networking has become part of our 21 Century culture, and is increasingly being incorporated into artworks, as a platform for collaboration; as a virtual space to encounter new art forms, new people and new networks; and to develop online communities.
Thyroid Cancer: Current Molecular Perspectives

The thyroid cancer is a rare oncological entity, representing no more than 1% of all human malignant neoplasms. Recently, it has been demonstrated a sharp increase in incidence of differentiated thyroid carcinoma, equally occurring in both sexes. So far, multiple genetic alterations have been identified in differentiated thyroid carcinoma, leading to investigate the clinical utility of genetic studies. In particular, molecular genetic approaches searching for gene mutations in the material collected by fine needle ago-biopsy may have a particular utility in small nodules and in those specimens with an indeterminate cytology. The expansion of knowledge about genetic mutations occurring in different thyroid tumors has characterized recent years, allowing the identification of a correlation between specific mutations and phenotypic characteristics of thyroid cancers, essential for their prognosis. This review will briefly report on the histological features and the new entity represented by thyroid microcarcinoma and will focus on both environmental and genetic aspects associated with the occurrence of thyroid cancer.
A new algorithm for estimating 3D structure and robot motion using visual tracking and IMU/compass

Monocular SLAM (Simultaneous Localization and Mapping) is popular in SLAM researches of the past few years. Filtering approaches and bundle adjustment style optimization are main popular strategies, with a lot of applications. This paper proposes a novel adaptive estimation based SLAM algorithm with application to a lake surface robot. Orientation and linear velocities of the robot, and accurate SURF feature tracking work as prerequisites of the algorithm. The algorithm is theoretically proved and experimentally validated in the paper. Key frames are selected in the SLAM process and stored with metric information of features points, to generate the environment map. Robot localization and sparse point based map could be estimated online at 50Hz with assistance of GPU. Moreover, dense point based map could be recovered offline for visualization. Finally, the corresponding experiments are carried out to validate performance of the new monocular visual SLAM algorithm.
Understanding users’ continuous content contribution behaviours on microblogs: an integrated perspective of uses and gratification theory and social influence theory

ABSTRACT Microblogs are revolutionising the way users produce, consume and distribute short content. The continuous content contributions of users are crucial for the sustainable development of microblogs. Knowledge regarding this user behaviour is scarce. Based on the uses and gratifications theory (U&G) and the social influence theory (SIT), this paper proposes an integrated research model with the aim of understanding the factors that affect users’ continuous content contribution behaviours (CCCB) on microblogs. The data were collected from 379 microblog users in China. The empirical results indicate that perceived gratification had a positive but surprisingly trivial effect on continuous content contribution behaviours. Social influence had a strong and significantly positive effect on users’ CCCB, it also had a positive moderating effect on the relationship between perceived gratification and CCCB. Users’ perceived gratification was positively affected by the antecedents of self-expression, anticipated extrinsic rewards and anticipated reciprocity but negatively affected by privacy concerns. The platform attributes of microblogs (i.e. accessibility and interactivity) also influenced users’ perceived gratification. This research contributes to social media research with regards to the theory of users’ CCCB.
A robust fuzzy logic adaptive PI controller for hydro power plants

The governor of hydro power plants should track frequency variations and at the same time provide good response to load disturbances. These two functions are contradictory and the system model changes with the operating point. This paper presents a robust fuzzy logic adaptive load-frequency controller for hydro power plants. The case study is Abbaspour power plant in Iran.
Analysis of a Novel Linear Doubly Salient Slot Permanent Magnet Motor

A novel linear doubly salient slot permanent magnet motor (LDSSPMM) is proposed in this paper. First, the topology and geometric parameters of the LDSSPMM with 12 slots (12s) are proposed and the basic operating principle is investigated. By analyzing the feasible slot/pole combinations and harmonic winding factors, 11 poles and 13 poles (11p/13p) are proved to have higher winding factor for working harmonic. In addition, the LDSSPMMs with 12s/11p and 12s/13p are optimized by global optimization with genetic algorithm. It is shown that 12s/13p is the optimal slot/pole combination. Finally, the electromagnetic performance of the 12s/13p LDSSPMM is investigated by 2-D finite-element analysis (FEA) and validated by 3-D FEA.
An experimental study of benchmarking functions for genetic algorithms

This paper presents a review and experimental results of major benchmarking functions used for the performance control of genetic algorithms (GAs). Parameters considered include the effect of population size, crossover probability and pseudo-random number generators. The general computational behavior of two basic GAs models, the Generational Replacement Model and the Steady State Replacement Model is evaluated.
Simulation Results of Domain based Security for Mobile Agents

In Mobile agent system, security issues are major problem. Mobile agents are autonomous software entity when a mobile agent works in the host environment some security problem raises, because mobile agent is a software entity it can be work in distributed network. It can suspend its execution in one host and resume its execution in another host . when mobile agent resume its execution, it can loss some of its important data. Mobile agent have their personal information like, internal code, state and password . These personal information are updated by host and another mobile agent working under that host environment. So that mobile agent systems are that in which various agents works concurrently and uses the resources of that host platform in random manner. An autonomous mobile agent is an executing program that can migrate from machine to machine in a heterogeneous network under its own control. An agent can either follow a pre-assigned path on the network or determine its itinerary based on the data collected from the network. Facilities for highly dynamic movement of code and data enables a program to take advantage of the locality of data. It also allows one to optimize between the requirements of low bandwidth, high latency and disconnected network connections. Mobile agent technology is used in distributed applications due to their properties of autonomy, a synchronicity and local resource management. Mobile agent technology results in significant new security threats from malicious agent and hosts. Mobile agent can travels in different number of hosts in distributed network. During the journey it can change its state and secret code and behave like a un trusted entity. So that the security problem occurs . mobile agent system employ a number of security features to address the various threats . despite this common need for security , there doesn't exists a generic trust and security model that covers all the level of their operation and that could be used as standard. Mobile agent technology has many benefits but it has a possibility of security threats from malicious agent platform. In this paper, an infrastructure is proposed to secure mobile agent from the agent platform in which they can execute to do their necessary computation, which is more suitable for industrial automation device which have low computation resources. In this infrastructure SGB (Security Guider Bank) serves as a group of agent platform, which is called domain. The SGB maintains information …
Research on Web Data Mining and Its Application in Electronic Commerce

With the rapid increase of available information online, especially with the growing popularity of electronic commerce, web data mining is being paid much attention. Combing web data mining and e-commerce has been a hot issue. Following paper focus on how to apply web mining to electronic commerce instead of the plethora or algorithms in data mining. We first introduce the concept, method and process of web data mining, and then some issues about data mining in e-commerce will be discussed. We will take a look at the applications of web data mining in e-commerce later. Keywords-Data mining;Web;electronic commerce;mining rules
INTERACTIVE AGENTS FOR MULTIMODAL EMOTIONAL USER INTERACTION

In this paper, Maxine, a powerful engine to develop applications with embodied animated agents is presented. The engine, based on the use of opensource libraries, enables multimodal real-time interaction with the user: via text, voice, images and gestures. Maxine virtual agents can establish emotional communication with the user through their facial expressions, the modulation of the voice and expressing the answers of the agents according to the information gathered by the system: noise level in the room, observer’s position, emotional state of the observer, etc. Moreover, the user’s emotions are considered and captured through images. For the moment, Maxine virtual agents have been used as virtual presenters and, a specific application, MaxinePPT, has been developed to allow non-programmers to create 3D presentations easily from classical PowerPoint presentations. Nevertheless, other applications are also envisaged.
Casual effect of methotrexate+etanercept/infliximab on survival of patients with rheumatoid arthritis

Background and objectives: Following the discovery of new drugs, physicians and pharmaceutical companies have become interested in examining patients’ mortality and morbidity rates. In this respect, the effects of methotrexate (MTX)+etanercept/infliximab (ETA/INF) therapy on the survival of rheumatoid arthritis patients (RA) were evaluated in this study using marginal structural piecewise constant baseline hazard model. Patients and methods: According to the standard protocol, MTX is considered as the first-line treatment for RA patients. If there is no adequate response to MTX, biologic drugs will be added. To compare the survival rates of RA patients in MTX- and MTX+ETA/INF-treated groups, the piecewise constant baseline hazard model was fitted. Then, due to the existence of the time-dependent confounder (VAS) which was affected by previous treatment, the weight for each person-time was calculated via the inverse probability treatment weighting method. These weights were then used by marginal structural piecewise constant baseline hazard model. Finally, these models were compared. Results: The median (IQR) of the follow-up period in patients receiving MTX+ETN/INF and MTX was 11 (15.25) and 11 (31), respectively, and the 8-year survival rate was reported by 70% versus 68%, respectively. First, the piece-wise constant baseline hazard model was fitted. Fitting the given model showed that MTX+ETA/INF had a significant effect on patients’ survival (HR=0.789, 95% CI [0.634, 0.983]). Second, marginal structural piecewise constant baseline hazard model was fitted. But, the results of this model revealed that MTX+ETA/INF did not have a significant impact on patients’ survival (HR=0.968, 95% CI [0.860, 1.090]). Conclusion: Adjusting the pain score over time as a time-dependent confounder via marginal structural piecewise constant baseline hazard model, it has been demonstrated that MTX+ETA/INF does not have a significant effect on patients’ survival rates. Therefore, a significant difference can be found between survival rates of these groups using longitudinal studies.
A COMPARISON OF SOME CLASSICAL APPROACHES TO OUTLIER DETECTION IN LINEAR REGRESSION

Five procedures for detecting outliers in linear regression are compared: sequential testing of the maximum studentized residual, Marasinghe's (1985) multistage procedure, and three procedures based on recursive residuals, calculated on adaptively-ordered observations. Four of these procedures test a no-outliers hypothesis. This hypothesis requires a rather stringent test criterion, meaning that moderate outliers often go undetected. The fifth procedure, the basic recursive-residual method, tests individual observations to identify outliers. This procedure is effective in identifying modest outliers, while by construction reducing masking of one outlier by another. When the data analyst's goal is to identify outliers/influential observations for further scrutiny and perhaps special treatment, not merely to justify their deletion, this procedure has advantages over the others.
A News-oriented Chinese-English Machine Translation System 1

This paper introduces a News-oriented Chinese-English Machine Translation system. Firstly, general information of the system is given. Secondly, the architecture of the system –– the micro-engine pipeline is introduced. Thirdly, the several main micro-engines in the system are discussed, including micro-engines for Chinese lexical analysis, example-based micro-engine, and rule-based microengine. Fourthly, linguistics resources used in this system are described. Finally, we will give the conclusion and the future works.
Environmental estrogens suppress hormones, behavior, and reproductive fitness in male fathead minnows

—This study explored the possibility that environmental estrogens in sewage effluent may reduce the reproductive fitness of adult male fish by suppressing their reproductive behaviors, including their ability to compete for nests and females. Male fathead minnows (Pimephales promelas) were exposed for three weeks to either blank control, effluent released by a sewage treatment plant (STPE), waterborne estradiol (E2), or a synthetic androgen (methyltestosterone [MT]). Afterward, fish were placed with females and a nest, and their behavior was monitored for 5 d in either the presence or the absence of a competing (unexposed control) male. Males exposed to either the STPE or E2 (∼50 ng/L, a level chosen to mimic the estrogenic content of the STPE) had elevated levels of circulating vitellogenin (p < 0.05) and lower levels of 11‐ketotestosterone (KT; p < 0.05). Nearly all STPE‐and E2‐exposed males spawned successfully in the absence of a competing male, but in both cases, exposed males suffered nearly total reproductive failure when they had to compete. Conversely, males exposed to MT (∼50 ng/L) outcompeted control males. Behavioral observations suggested that subtle differences in agonistic behaviors, typically associated with circulating androgens (i.e., KT), were responsible. We speculate that male fish exposed to estrogenic effluent in the field are less likely to reproduce successfully within large populations of wild fish, thereby causing abnormal and potentially detrimental patterns of gene flow within those populations.
Chemopreventive Activities of Shikonin in Breast Cancer

Copyright: © 2014 Duru N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Shikon (a Chinese herbal plant) has been used as an antitumor agent in complementary medicine for thousands of years [1,2]. Shikonin (SK), a key bioactive component of shikon with molecular weight of 288, has potent antitumor activity in a variety of human cancer cells [2-10] and is a novel natural compound in the database of the Developmental Therapeutics Program of the National Cancer Institute (NCI). SK inhibits tumor cell growth via various signaling cascades and different mechanisms including cell cycle arrest and induction of apoptosis [2-10]. SK administration produces no serious adverse events in clinical trials and animal studies [1,9,10]. Following ingestion, SK is metabolized in the gastrointestinal tract where it subsequently forms cycloshikonin and desoxyshikonin, which have no reported toxicity in vivo [11]. Finally, SK prevents chemical-induced gene mutations, and inhibits intestinal and skin tumorigenesis in vivo [12-14]. These results prove that SK has potential as a chemopreventive agent.
A Machine Learning Approach to Foreign Key Discovery

the problem of automatically discovering semantic as- sociations between schema elements, namely foreign keys. This problem is important in all applications where data sets need to be integrated that are structured in tables but without explicit foreign key constraints. If such constraints could be recovered automati- cally, querying and integrating such databases would become much easier. Clearly, one may find candidates for foreign key constraints in a given database instance by computing all inclu- sion dependencies (IND) between attributes. However, this set usually contains many false positives due to spurious set inclu- sions. We present a machine learning approach to tackle this problem. We first compute all INDs of a given schema and let each be judged by a binary classification algorithm using a small set of features that can be derived efficiently using standard SQL. We demonstrate the feasibility of this approach using cross- validation with several state-of-the-art classification algorithms. With the J48 algorithm, our approach consistently reaches F- measures above 80% and often close to 100% as evaluated on six different data sets from three different domains.
Grid voltage offset and harmonics rejection using second order generalized integrator and kalman filter technique

This paper proposes the application of second order generalized integrator (SOGI) and Kalman filter (KF) technique for the rejection of DC offset and harmonics from the distorted grid voltage waveform. The SOGI is used to estimate the orthogonal waveforms of grid voltage fundamental frequency component. On the other hand, the linear Kalman filter (LKF) is used to reject the DC offset and harmonics present in the distorted grid voltage waveform. The resonance and harmonic frequencies of the SOGI and LKF, respectively, are provided by the frequency locked loop (FLL). The proposed technique provides better results to reject the DC offset and harmonics as compared to the multiple SOGI (MSOGI) technique. The improved performance of the proposed technique is due to the use of LKF which not only rejects the DC offset and harmonics but also non-sensitive to the change of SOGI's gain. Synthetically generated grid voltage waveforms are used in MATLAB/Simulink to depict the superior performance of the proposed SOGI-LKF technique as compared to the MSOGI with/without offset rejection technique.
ASSIST: access controlled ship identification streams

The International Maritime Organization (IMO) requires a majority of cargo and passenger ships to use the Automatic Identification System (AIS) for navigation safety and traffic control. Distributing live AIS data on the Internet can offer a global view based on ships' status for both operational and analytical purposes to port authorities, shipping and insurance companies, cargo owners and ship captains and other stakeholders. Yet, uncontrolled, this distribution can seriously undermine navigation safety and security and the privacy of the various stakeholders. In this paper we present ASSIST, a system prototype based on our recently proposed access control framework, to protect data streams from unauthorized access. We demonstrate the effectiveness of the system in a real scenario with real AIS data streams.
Integrated pitch and MFCC extraction for speech reconstruction and speech recognition applications

This paper proposes an integrated speech front-end for both speech recognition and speech reconstruction applications. Speech is first decomposed into a set of frequency bands by an auditory model. The output of this is then used to extract both robust pitch estimates and MFCC vectors. Initial tests used a 128 channel auditory model, but results show that this can be reduced significantly to between 23 and 32 channels. A detailed analysis of the pitch classification accuracy and the RMS pitch error shows the system to be more robust than both comb function and LPC-based pitch extraction. Speech recognition results show that the auditory-based cepstral coefficients give very similar performance to conventional MFCCs. Spectrograms and informal listening tests also reveal that speech reconstructed from the auditory-based cepstral coefficients and pitch has similar quality to that reconstructed from conventional MFCCs and pitch.