Miracle-dz/UniFAR-FTUs huggingface dataset:
Trans-Oral Brush Biopsies and Quantitative PCR for EBV DNA Detection and Screening of Nasopharyngeal Carcinoma

Objectives To evaluate a newly developed noninvasive ambulatory, quantitative polymerase chain reaction (Q-PCR) Epstein-Barr virus (EBV) DNA detection and screening system (NP Screen™) for nasopharyngeal carcinoma (NPC). Study Design Correlation of the nasopharyngeal epithelial EBV-DNA levels and clinical findings by nasopharyngoscopy and final pathologic diagnosis of NPC with biopsy. Setting Multicenter ENT/Oncology clinics in Hong Kong (Radiation Oncology Clinic at the Queen Elizabeth Hospital and Radiation Oncology Clinic and Head and Neck Clinic, Queen Mary Hospital, University of Hong Kong) and in Toronto, Canada (the Otolaryngology-Head and Neck Clinic at the Rouge Valley Health System and 2 large ENT practices in Toronto). Methods A single-use trans-oral brush was used for rapid, nontraumatic nasopharyngeal (NP) epithelial cells DNA harvest in 600 Chinese patients, combined with a preservation and shipping kit for remote, real-time Q-PCR EBV DNA determinations. Results All 600 patients had NP brushings using NP Screen in an ambulatory environment, and no adverse events or complications were recorded. A final 578 patients were included with sufficient amount of DNA for completion of the Q-PCR assay. Of these 578 patients, 94 were confirmed positive for NPC histologically. The study yielded a sensitivity of 98.9%, specificity of 99.3%, positive predictive value (PPV) of 96.9%, and negative predictive value (NPP) of 99.7% for NP Screen in detecting NPC. Endoscopy had a sensitivity of 94%, specificity 97.1%, PPV 85%, and NPP 98.9%. Conclusions The trans-oral brushing system fulfills the characteristics of a noninvasive, sensitive, specific detection method suitable for routine, large-scale ambulatory NPC risk assessment for high-risk NPC populations.
Reliability of the Roland - Morris Disability Questionnaire (Thai version) for the evaluation of low back pain patients.

OBJECTIVE To determine the reliability of the Thai version of the Roland - Morris disability questionnaire in low back pain patients. MATERIAL AND METHOD To develop Thai version of the Roland - Morris disability questionnaire and test it in 120 low back pain patients. Reliability of the Thai version of the Roland - Morris disability questionnaire was assessed by internal consistency using Cronbach's alpha coefficient. RESULTS The overall Cronbach's alpha coefficient of the scale was 0.83. The Cronbach's alpha coefficient of each question in the Thai version of the Roland - Morris disability questionnaire exceeded 0.7 (range, 0.71- 0.93). The Cronbach's alpha coefficient tested in acute or chronic low back pain patients whether they have back pain only or back pain with radiculopathy which also exceeded 0.7 (range, 0.83-0.87). CONCLUSION The Thai version of the Roland - Morris disability questionnaire is a reliable tool for assessing functional disability of low back pain in Thai patients.
PDB-REPRDB: a database of representative protein chains from the Protein Data Bank (PDB) in 2003

PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). Started at the Real World Computing Partnership (RWCP) in August 1997, it developed to the present system of PDB-REPRDB. In April 2001, the system was moved to the Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) (http://www.cbrc.jp/); it is available at http://www.cbrc. jp/pdbreprdb/. The current database includes 33 368 protein chains from 16 682 PDB entries (1 September, 2002), from which are excluded (a) DNA and RNA data, (b) theoretically modeled data, (c) short chains (1<40 residues), or (d) data with non-standard amino acid residues at all residues. The number of entries including membrane protein structures in the PDB has increased rapidly with determination of numbers of membrane protein structures because of improved X-ray crystallography, NMR, and electron microscopic experimental techniques. Since many protein structure studies must address globular and membrane proteins separately, this new elimination factor, which excludes membrane protein chains, is introduced in the PDB-REPRDB system. Moreover, the PDB-REPRDB system for membrane protein chains begins at the same URL. The current membrane database includes 551 protein chains, including membrane domains in the SCOP database of release 1.59 (15 May, 2002).
An interactive agent system for supporting knowledge-based recommendation: a case study on an e-novel recommender system

With the fast development of e-commerce, a large number variety of information existed on the Internet. Many researches tend to design a recommender system for assisting users to search the information that they have interested over the internet. The knowledge-based recommendation is one of solutions to guide the users to provide their needs, and further create a user preference model. In the past, agents commonly played the role of information retriever in a recommender system. Agents have the capability of autonomy and cooperation to assist in collecting the users' profiles and analyzing users' preferences. However, few of researches adopted embodied conversational agents (ECAs) to interact with users. In this study, we design an interactive agent system to support the knowledge-based recommendation. In addition to recommend products by using the knowledge from users' profiles, the knowledge-based approach also emphasizes the system should explain the cause of the recommendation result. For this reason, this study used ECAs to promote and explain recommendation results. As a result, our proposed system could reach the purpose of advertising products and receiving user feedbacks. In this paper, to demonstrate the usability of our system, we implement the interactive agent system in an e-novel web site, called Angel City, for recommending e-novels to readers.
Efficient Induction of Finite State Automata

This paper introduces a new algorithm for the induction of complex finite state automata from samples of behaviour. The algorithm is based on information theoretic principles. The algorithm reduces the search space by many orders of magnitude over what was previously thought possible. We compare the algorithm with some existing induction techniques for finite state automata and show that the algorithm is much superior in both run time and quality of inductions.
Chatbot Evaluation and Database Expansion via Crowdsourcing

Chatbots use a database of responses often culled from a corpus of text generated for a different purpose, for example ﬁlm scripts or interviews. One consequence of this approach is a mismatch between the data and the inputs generated by participants. We describe an approach that while starting from an existing corpus (of interviews) makes use of crowdsourced data to augment the response database, focusing on responses that people judge as inappropriate. The long term goal is to create a data set of more appropriate chat responses; the short term consequence appears to be the identiﬁcation and replacement of particularly inappropriate responses. We found the version with the expanded database was rated signiﬁcantly better in terms of the response level appropriateness and the overall ability to engage users. We also describe strategies we developed that target certain breakdowns discovered during data collection. Both the source code of the chatbot, TickTock, and the data collected are publicly available.
Classi cation of News Stories Using Support Vector Machines

Given a data set and a data mining task such as classiication, there are two main reasons for performing feature space reduction. The rst is to improve the accuracy of the algorithm. In a domain such as text mining, the common technique of parameterizing each document as a vector of words results in thousands of dimensions. The performance of many learning algorithms decreases as the dimensionality of the input space increases. Support Vector Machines (SVMs) Vap95], which are based on Vapnik's statistical learning theory, can be used as a clas-siication technique and have been shown by Joachims Joa98] to be reasonably immune to the high dimensionality of text feature spaces. The second reason for performing feature space reduction is to decrease the overall size of the data set in order to conserve storage space and minimize the amount of time required to handle the data and run the mining algorithms. Even with SVMs, very large data sets may warrant feature space reduction because of this second class of problems. This paper describes the results of an experiment to train SVMs to classify print, television, and radio news sources. Tests were performed to compare full text versus feature space reduction using a natural language processing technique and reduction using information gain. The results show that while the size of the data set can be reduced by an order of magnitude with natural language processing, this results in a signiicant loss in both recall and precision. However, both the precision and recall achieved with the SVMs trained with the full text and information gain representations were higher than what was achieved with the K-nearest-neighbors algorithm. Also, three term weighting methods, TFIDF, TF, and binary are compared for use with the SVMs. Representations with TFIDF and TF weights produced similar results, while the binary weighting method resulted in a signiicant loss in recall.
Isolation of a neural chondroitin sulfate proteoglycan with neurite outgrowth promoting properties

Proteoglycans are expressed in various tissues on cell surfaces and in the extracellular matrix and display substantial heterogeneity of both protein and carbohydrate constituents. The functions of individual proteoglycans of the nervous system are not well characterized, partly because specific reagents which would permit their isolation are missing. We report here that the monoclonal antibody 473HD, which binds to the surface of early differentiation stages of murine astrocytes and oligodendrocytes, reacts with the chondroitin sulfate/dermatan sulfate hybrid epitope DSD-1 expressed on a central nervous system chondroitin sulfate proteoglycan designated DSD-1-PG. When purified from detergent- free postnatal days 7 to 14 mouse brain extracts, DSD-1-PG displays an apparent molecular mass between 800-1,000 kD with a prominent core glycoprotein of 350-400 kD. Polyclonal anti-DSD-1-PG antibodies and monoclonal antibody 473HD react with the same molecular species as shown by immunocytochemistry and sequential immunoprecipitation performed on postnatal mouse cerebellar cultures, suggesting that the DSD-1 epitope is restricted to one proteoglycan. DSD-1-PG promotes neurite outgrowth of embryonic day 14 mesencephalic and embryonic day 18 hippocampal neurons from rat, a process which can be blocked by monoclonal antibody 473HD and by enzymatic removal of the DSD-1- epitope. These results show that the hybrid glycosaminoglycan structure DSD-1 supports the morphological differentiation of central nervous system neurons.
Development of Wearable Controller with Gloves and Voice Interface for Humanoids ’ Whole-body Motion Generation *

In this paper, we describe humanoid’s whole body motion creation system for offline motion creation and online motion operation to perform various tasks. In practical tasks of our daily life, precise positions of left and right hand and angles of fingers are important. On the other hand, an attitude of the torso or configuration of the lower body is desired to be determined automatically considering dynamical balance, a vision sensor’s view, etc. In order to realize such motion creation system, an intuitive interface for hand positions and finger-bending angles and an autonomy that optimizes motions of other parts of body is necessary. Therefore, we developed a hardware device which detects hand positions and finger-bending angles of an operator. We also propose a whole body motion creation system from data of the device we develop in this paper. We show the result of online motion operation experiments using a whole body humanoid robot H7. Key Words— Humanoid, Control Interface, Wearable Controller, Voice Command Interface, Hand-Centered WholeBody Motion Control
Predictive models on improvement of spatial abilities in controlled training

Improving spatial ability in the academic curriculum is crucial for engineering degrees. Prior research has shown that spatial abilities can be trained; that's why in this work we propose several kinds of short duration trainings aimed to improve those abilities. We have established a ranking based on the improvement rate that the student may reach knowing his starting level before undertaking training. These trainings take place before starting the academic course so students don't receive theoretical or practical contents of Graphic Engineering during the week. Before training and after its completion, the level of spatial ability is measured through validated tools for this aim. We perform a statistical analysis obtaining the gains from higher to lower levels of spatial skills acquired through each training (videogame/ augmented reality/ sketching/ descriptive geometry). With data from all training, the curves have been set up by least squares (linear, exponential, algorithm, potential and polynomial). The most suitable predictive model for all cases is the linear one.
High-Power and Widely Tunable All-Fiber Raman Laser

A high-power and widely tunable all-fiber Raman laser is demonstrated. The Raman fiber laser has been tuned over a range of 60 nm from 1075 to 1135 nm and delivers up to 5.0 W of Stokes output power for 6.5 W of launched pump power. Efficiencies ranging from 76.1 to 93.1% and laser thresholds from 0.78 to 2.59 W have been measured. The spectrum of the depolarized Raman gain coefficient of the germanosilicate fiber has also been inferred from our experimental measurements.
Development of the NIST Robot Crane Teleoperation Controller

An inexpensive and easy to operate controller has been developed for the teleoperation control of the NIST Robot Crane. This robot crane has the Stewart platform parallel link manipulator design, with cables as parallel links and winches as actuators. The controller is currently capable of rate-position control and force control of the crane platform. The control action can take place with respect to the base-frame coordinate axes, the moving platform coordinate axes, or the tool-tip coordinate axes. The front panel display of the controller is designed to interact with the operator in simple, easy to understand, menu selection type icons. Critical parameters are displayed in real time plots and digital displays. A 3-D animation window of the workspace and the moving crane platform can help the operator with command planning and premotion detecting of collisions. The operator can interact with the controller without the need for any computer programming knowledge and without having to type any commands. The rate-position movement commands are input from a spaceball or a Stewart mechanism joy-stick. Critical control mode selection choices can be made from a set of nine buttons attached to the spaceball joystick support.
Modeling Internet Effects on Civic Participation

This article examines the role of the Internet as a source of political information and a sphere for public expression. Informational media use, whether traditional news sources or online public affairs content, is expected to foster interpersonal political discussion and online civic messaging, contributing to increased civic participation. Using two-wave national panel survey data, three types of synchronous structural equation models are tested: cross sectional (relating individual differences), fixed effects (relating intraindividual change), and auto regressive (relating aggregate change). All models reveal that online media complement traditional media to foster political discussion and civic messaging. These two forms of political expression, in turn, influence civic participation. Other variable orderings are tested to compare the theorized model to alternative causal specifications. Results reveal that the model produces the best fit, empirically and theoretically, with the influence of the Internet, rivaling the mobilizing power of traditional modes of information and expression.
Methods to Improve the Spatial Resolution of EEG

Theoretical models and experimental EEG data were examined to quantify the spatial resolution of scalp surface recordings of EEG. The results suggest that scalp EEG electrodes are mostly sensitive to activity correlated over large areas of the superficial neocortical surface, with smaller contributions from deeper sources. The surface Laplacian of the scalp surface potential is shown to be an estimate of the cortical surface potential. To accurately compute the surface Laplacian, the 3-dimensional spline algorithm has been developed to minimize aliasing errors by applying a smoothing filter based on the effective size of each electrode. The splinegenerated surface Laplacian improves the spatial resolution of EEG by reducing the sensitivity of each electrode to only a local region of neocortical tissue beneath the electrode.
ANTIBODIES TO GRANULOCYTIC EHRLICHIAE IN WHITE-FOOTED AND COTTON MICE IN EASTERN UNITED STATES

Serum samples, collected from Peromyscus leucopus (white-footed mouse) or Peromyscus gossypinus (cotton mouse) during 1987 through 1990 in Florida, Georgia, Maryland, Mississippi, and North Carolina (USA), and in 1997 in southern Connecticut were analyzed by indirect fluorescent antibody (IFA) staining methods or Western blot procedures for antibodies to granulocytic ehrlichiae. Of the 82 sera from white-footed mice in Connecticut tested by IFA methods with either the BDS or NCH-1 strain of the human granulocytic ehrlichiosis (HGE) agent, 45 (55%) and 42 (51%) of the samples contained antibodies to these strains, respectively, at concentrations ranging from 1:80 to 1:2560. One (2%) of 43 sera from P. leucopus captured in Assateague Island (Maryland) had a titer of 1:80, while three (20%) of 15 sera from P. gossypinus, captured in Sapelo Island (Georgia) and four (40%) of 10 sera from cotton mice caught in Amelia Island (Florida) had antibodies to the NCH-1 strain at titers of 1:160 to 1:1,280. Fifty-five sera from P. leucopus in Cape Hatteras (North Carolina) and 30 sera from P. gossypinus in Mississippi were negative. Western blot analyses confirmed seropositivity for 19 (95%) of 20 mouse sera positive by IFA staining methods, including samples from both mouse species captured in Connecticut, Maryland, or Florida. There were key banding patterns to proteins having molecular masses of about 44, 80, 105, 110, or 120 kDa. Both serologic assays can be used to determine if mice have been exposed to granulocytic ehrlichiae. These rodents also may be useful in surveillance programs to identify endemic sites for HGE and in performing laboratory studies on immune responses to the etiologic agent.
EMOTIONALITY AND SOCIAL PRESENCE: STORIES OF LEARNING ONLINE

This paper employs storying and self-reports to exa mine the role of emotionality as it relates to social presence and learning online. It examines th links between social presence and the social support provided by family, friends and the wider c ommunity and the way these contribute to identity which is seen as always changing, always i n process, multiple, and contradictory. Of particular interest is the importance of the bios in facilitating or impeding student learning, the fears and reservations students have about building relationships and working online, the ways in which family support can complicate and interfere w ith learning, the emotional labour required of the learner to maintain family and social relations hip , the ways in which students react to variations in social and academic capital, the effe ct of emotionality on work performance, and the role of the tutor in assisting students toward what Ting Toomey (in Weber, 2005) has called ‘mindful identity negotiation’.
dbCerEx: A Web-Based Database for the Analysis of Cervical Cancer Transcriptomes

Background Cervical cancers are ranked the second-most hazardous ailments among women worldwide. In the past two decades, microarray technologies have been applied to study genes involved in malignancy progress. However, in most of the published microarray studies, only a few genes were reported leaving rather a large amount of data unused. Also, RNA-Seq data has become more standard for transcriptome analysis and is widely applied in cancer studies. There is a growing demand for a tool to help the experimental researchers who are keen to explore cervical cancer gene therapy, but lack computer expertise to access and analyze the high throughput gene expression data. Description The dbCerEx database is designed to retrieve and process gene expression data from cervical cancer samples. It includes the genome wide expression profiles of cervical cancer samples, as well as a web utility to cluster genes with similar expression patterns. This feature will help researchers conduct further research to uncover novel gene functions. Conclusion The dbCerEx database is freely available for non-commercial use at http://128.135. 207.10/dbCerEx/, and will be updated and integrated with more features as needed.
Identification and spatial distribution of the mRNA encoding the gp49 component of the gilthead sea bream, Sparus aurata, egg envelope

A cDNA encoding the precursor of one of the major components of gilthead sea bream, Sparus aurata, egg envelope has been cloned by reverse transcriptase polymerase chain reaction (RT‐PCR) techniques. The clone was isolated starting from total RNA extracted from the liver of spawning female fish and estradiol‐17β–treated male fish. Sequence analysis revealed that the cDNA encoded a protein of 405 aa corresponding to 49‐kDa component (termed gp49), a glycoprotein belonging to the N‐linked type. The gp49 protein is homologous to the ZI‐3 of medaka Oryzias latipes, the mammalian ZPC and ZPC homologues of Xenopus laevis (xlZPC) and carp Cyprinus carpio (ccZPC). In addition, the open reading frame also encodes an additional aa sequence, the signal peptide, located in the N‐terminal region of the protein.
Comparing Tag Clustering Algorithms for Mining Twitter Users' Interests

This paper addresses the problem of mining users' interest from the vast, noise, unstructured and dynamic data generated on social media sites, taking Twitter as case study. The mining process uses different Natural Language Processing techniques to extract the relevant words from subscribers' tweets and applies cluster analysis over them. We evaluate the performance of three different tag clustering algorithms -PAM, Affinity Propagation and UPGMA- when considering the hyperlink structure of Wikipedia as external source for semantic closeness among words. We provide a solution which can be developed without any a-priori knowledge about the number and category of topics, neither a priori knowledge about the users we are applying the extraction for. This solution is based on using an unsupervised measure of the clustering quality (Silhouette width) to estimate the parameters of the cluster analysis. Finally, as human feedback is not as reliable as expected, we validate the approach by using Twitter hash tags - the implicit classifying method used by Twitter users to organise their tweets.
Large-scale quantum technology based on luminescent centers in crystals

Luminescent defects in crystals are prime candidates for the creation of a quantum technology given their superlative spin coherence lifetimes. Here we describe the main features of a quantum technology based on crystalline defects which builds upon the impressive recent achievements in diamond research. The basic features of the architecture and the requirements for its implementation are outlined, together with experimental progress and practical considerations towards its realization.