Miracle-dz/UniFAR-FTUs huggingface dataset:
Electroacupuncture Attenuates 5′-Guanidinonaltrindole-Evoked Scratching and Spinal c-Fos Expression in the Mouse

The present study was undertaken to investigate the influence of electroacupuncture (EA) on compulsive scratching in mice and c-Fos expression elicited by subcutaneous (s.c.) administration of a known puritogen, 5′-guanidinonaltrindole (GNTI) to the neck. Application of EA to Hegu (LI4) and Quchi (LI11) acupoints at 2 Hz, but not 100 Hz, attenuated GNTI-evoked scratching. In mice pretreated with the µ opioid receptor antagonist naloxone, EA 2 Hz did not attenuate GNTI-evoked scratching, whereas EA at 2 Hz did attenuate GNTI-evoked scratching in mice pretreated with the κ opioid receptor antagonist nor-binaltorphimine. Moreover, intradermal (i.d.) administration of the selective µ opioid receptor agonist [d-Ala2, N-Me-Phe4, Gly5-ol]-enkephalin acetate (DAMGO) attenuated GNTI-evoked scratching behavior, while s.c. administration of DAMGO was ineffective. GNTI provoked c-Fos expression on the lateral side of the superficial layer of the dorsal horn of the cervical spinal cord. Application of 2 Hz EA to LI4 and LI11 decreased the number of c-Fos positive nuclei induced by GNTI. It may be concluded that application of 2 Hz EA to LI4 and LI11 attenuates scratching behavior induced by GNTI in mice and that the peripheral µ opioid system is involved, at least in part, in the anti-pruritic effects of EA.
Knowledge Management & E-Learning

: Given the interdependence of the public and private sectors and simultaneous and massive impact of widespread disasters on the entire community, this paper investigates the use of information technologies, specifically geospatial information systems, within the multi-organizational community to effectively co-create value during disaster response and recovery efforts. We present and examine in depth a participatory action research project in a disaster-experienced coastal community conducted during the 2006-2014 time period. The results of the action research project and analysis of a survey completed by stakeholders leads to a list of findings, in particular those related to developing a model of next generation learning design where students are co-creators of value to the smart cities.
Enhancing Sensor Array Intelligence by Bayesian Fusion of Information Multiplicity Generated by Multiple Processors

The paper presents a new data processing method for sensor array based pattern recognition problem. The primary motivation is to improve the odor recognition efficiency of electronic nose systems. The method creates a set of virtual experts in which individual expert members are defined by a different combination of a feature extractor and a radial basis function (RBF) neural network classifier. In this work the outputs from five different linear feature extraction methods: principal component analysis (PCA), independent component analysis (ICA), singular value decomposition (SVD), linear discriminant analysis (LDA) and partial-least-square regression (PLSR), are fed separately as inputs to five different RBF neural networks. The parameters defining each RBF network are optimized separately by training them as independent decision makers. Since a given feature extractor processes raw data with specific perspective about the data structure, and RBF network generates a set of class likelihood values, the set of virtual experts generate alternate sets of class likelihood values. Bayesian product rule for fusion is then applied for combining these class likelihood values into class posterior probabilities. The class declaration is finally done by maximum posterior probability. The method has been validated by analyzing 9 chemical and 7 non-chemical data sets. The enhancement in classification rate up to 33.3 % has been found. The reason for system performance improvement is that the multiple feature extractors generate varied representations of raw data by exploring diversity of hidden attributes, and Bayesian fusion works on the extended information provided by several experts. Copyright © 2014 IFSA Publishing, S. L.
Metabolic syndrome and its components among rheumatoid arthritis patients: A comprehensive updated systematic review and meta-analysis

Background Estimating the current global prevalence of metabolic syndrome (MetS), and its components, among rheumatoid arthritis (RA) patients is necessary in order to formulate preventative strategies and to ensure there are adequate community resources available for these patients. Furthermore, the association between RA and MetS is controversial and has not previously been comprehensively assessed. Therefore, the present study aimed to: 1) determine the prevalence of MetS, and its components, among RA patients across the world 2) update the odds ratio of MetS in RA patients, compared to healthy controls, using a comprehensive systematic review and meta-analysis. Methods International databases, including: the Web of Science, PubMed, Scopus, Embase, CINAHL and other relevant databases were searched to identify English language articles which reported the prevalence and risk of MetS in RA patients between January 2000 and August 2016. The meta-analysis only included studies which clearly described the time and location of the study, utilised adequate sampling strategies, and appropriate statistical analyses. Results The meta-analyses of prevalence (70 studies [n = 12612]) and risk (43 studies [n = 35220]) of MetS in RA patients were undertaken separately. The overall pooled prevalence of MetS was 30.65% (95% CI: 27.87–33.43), but this varied from 14.32% (95% CI: 10.59–18.05) to 37.83% (95% CI: 31.05–44.61), based upon the diagnostic criteria used. The prevalence of MetS also varied slightly between males (31.94%, 95% CI: 24.37–39.51) and females (33.03%, 95% CI: 28.09–37.97), but this was not statistically significant. The overall pooled odds ratio (OR) of MetS in RA patients, compared to healthy controls, was 1.44 (95% CI: 1.20–1.74), but this ranged from 0.70 (95% CI: 0.27–1.76) to 4.09 (95% CI: 2.03–8.25), depending on the criteria used. The mean age and diagnostic criteria of MetS were identified as sources of heterogeneity in the estimated odds ratios between studies (P<0.05). Conclusions According to the high prevalence of MetS in RA patients, and high risk of MetS, measuring metabolic syndrome in RA patients is strongly recommended. Furthermore, as high waist circumference (WC) is the most common metabolic syndrome component, more attention must be paid to nutrition and weight loss among those with RA.
Suppression of MAPK/JNK-MTORC1 signaling leads to premature loss of organelles and nuclei by autophagy during terminal differentiation of lens fiber cells

Although autophagic pathways are essential to developmental processes, many questions still remain regarding the initiation signals that regulate autophagy in the context of differentiation. To address these questions we studied the ocular lens, as the programmed elimination of nuclei and organelles occurs in a precisely regulated spatiotemporal manner to form the organelle-free zone (OFZ), a characteristic essential for vision acuity. Here, we report our discovery that inactivation of MAPK/JNK induces autophagy for formation of the OFZ through its regulation of MTORC1, where MAPK/JNK signaling is required for both MTOR activation and RPTOR/RAPTOR phosphorylation. Autophagy pathway proteins including ULK1, BECN1/Beclin 1, and MAP1LC3B2/LC3B-II were upregulated in the presence of inhibitors to either MAPK/JNK or MTOR, inducing autophagic loss of organelles to form the OFZ. These results reveal that MAPK/JNK is a positive regulator of MTORC1 signaling and its developmentally regulated inactivation provides an inducing signal for the coordinated autophagic removal of nuclei and organelles required for lens function.
Blind Watermarking Based on the Wavelet Transform

This paper proposes a blind watermarking scheme based on the wavelet transform. We generate a pseudo-random sequence by an ID logistic map as operands and control codes. The original image is decomposed into ten subbands by the 3-level wavelet transform and the original watermark is transformed into a noise watermark. Then, the noise watermark is used to replace the third or fourth bit of the integer part of the absolute values of wavelet coefficients in LH3 or HL3 randomly. Simulation results indicate 1) the proposed scheme can resist JPEG2000 compression attack with compression ratio above 10.31; 2) the PSNRs of the watermarked images are larger than 43; 3) the performance of the proposed scheme is better than an existing scheme
The Impacts of Post-TRIPS Patent Reforms on the Structure of Exports

We study the effects of reforms in the legal scope of patent rights (PRs) on the international pattern of sectoral exports, before and after implementation of the Trade-Related Aspects of Intellectual Property Rights (TRIPS) Agreement at the World Trade Organization (WTO), in a generalized factor-proportions framework. We find that, conditional on factor endowments and intensities, a country with stronger PRs tends to have greater exports to the United States in patent-intensive sectors. These effects are significantly positive throughout the sample but are considerably larger in the post-TRIPS era. These impacts grow over time in developing economies, roughly in line with the implementation of TRIPS obligations. There is also evidence that changes over time in national PRs positively affect growth in exports. These results hold after controlling for alternative determinants of international trade and correcting for endogeneity.
Content Based Video Retrieval by Genre Recognition Using Tree Pruning Technique

— Recent advances in technology have made tremendous amount of multimedia content available. The amount of video content is increasing, due to which the systems that improve the access to the video is needed. Efficiency of the retrieval system depends upon the search method used in the system. The use of inappropriate search method may degrade the performance of the retrieval system. During past years, multimedia storage grows and cost of storing digital data is also cheaper. So there is huge amount of videos available in the multimedia database. It is very difficult task to retrieve the relevant videos from the large database as per the user needs. Hence an effective video retrieval system is required to retrieve the relevant videos from the large database. In order to create an effective video retrieval system, visual perception must be taken into account. In this paper, we have proposed an algorithm for video retrieval based on genre of the video. This algorithm extracts the key frames based on motion detection, Regions of interest with the objects are detected using bounding box method and are annotated over the video and compared with the similar objects from the knowledge based prepared for various genre videos for recognition of objects. It also uses a tree based classifier to identify the genre of the query video and to retrieve the same genre videos from the video database.
Long-term Streaming Media Server Workload Analysis and Modeling

Currently Internet hosting centers and content distribution networks leverage statistical multiplexing to meet the performance requirements of a number of competing hosted network services Developing e cient resource allocation mechanisms for such services requires an understanding of both the short term and long term behavior of client access patterns to these competing services At the same time streaming media services are becoming increasingly popular presenting new challenges for designers of shared hosting services These new challenges result from fundamentally new characteristics of streaming media relative to traditional web objects principally di erent client access patterns and signi cantly larger computational and bandwidth overhead associated with a streaming request To understand the characteristics of these new workloads we use two long term traces of streaming media services to develop MediSyn a publicly available streaming media workload generator In summary this paper makes the following contributions i we model the long term behavior of network services capturing the process of le introduction and changing le popularity ii we present a novel generalized Zipf like distribution that captures recently observed popularity of both web objects and streaming media not captured by existing Zipf like distributions and iii we capture a number of characteristics unique to streaming media services including le duration encoding bit rate session duration and non stationary popularity of media accesses
Title Towards Cross-Community Effects in Scientific Communities

Community effects on the behaviour of individuals, the community itself and other communities can be observed in a wide range of applications. This is true in scientific research, where communities of researchers have increasingly to justify their impact and progress to funding agencies. Previous work has tried to explain these phenomena by analysing co-citation graphs with methods from social network analysis and graph mining. More recent approaches have supplemented this with techniques from textual clustering. However, there is still a great potential for increasing the quality and accuracy of this analysis, especially in the context of cross-community effects. In this work, we present existing approaches and discuss their strengths and weaknesses. Based on this, we choose two closely related communities and propose novel ideas to detect and explain cross-community effects with a special focus on their characteristics in a given timeline. The outcome is a roadmap for advanced analysis of cross-community effects, which promises valuable insights for all areas of scientific research.
Feature Tracking in Video and Sonar Subsea Sequences with Applications

This paper deals with automatic target tracking in video and sonar subsea sequences, an essential capability for automating tasks currently performed by remotely operated vehicles under pilot control. We describe two trackers, one for video sequences, the other for sector scan sonar sequences. No assumptions are made about the images, scene, or motion observed. To illustrate applications, we report results of our systems for 3-D structure reconstruction and panoramic mosaic building from video sequences and describe in some detail our path planning and obstacle avoidance system using sonar sequences.
Part-based room categorization for household service robots

A service robot that operates in a previously-unseen home environment should be able to recognize the functionality of the rooms it visits, such as a living room, a bathroom, etc. We present a novel part-based model and an approach for room categorization using data obtained from a visual sensor. Images are represented with sets of unordered parts that are obtained by object-agnostic region proposals, and encoded using state-of-the-art image descriptor extractor - a convolutional neural network (CNN). An approach is proposed that learns category-specific discriminative parts for the part-based model. The proposed approach was compared to the state-of-the-art CNN trained specifically for place recognition. Experimental results show that the proposed approach outperforms the holistic CNN by being robust to image degradation, such as occlusions, modifications of image scaling, and aspect changes. In addition, we report non-negligible annotation errors and image duplicates in a popular dataset for place categorization and discuss annotation ambiguities.
Negotiating the Culture of the Academy: Chinese Graduate Students in Canada

This paper presents the process and results of a narrative inquiry into the stories of eight Chinese international graduate students. Results show three main commonalities in participants’ education narratives in China: parental influence, the exam system and independent study. In the Canadian setting, specific aspects of the academic culture are experienced as permeable (written work, lab work, tests and reading ability) or impermeable (in-class discussions, oral presentations, group work, oral discourse, communicating with local people). Discussion articulates participants’ use of unique personal resources, which results in distinctive trajectories of entry into and navigation within this new academic culture. Resume Cet article presente le processus et les resultats d'une enquete narrative de huit etudiants internationaux chinois de troiseme cycle. Les resultats montrent les trois elements communs dans la narration des participants: l'influence des parents, le systeme des examens, et l'etude individuelle. Dans le cadre canadien, les participants ont reconnu des aspects specifiques de la culture academique comme permeables (travaux ecrits, travaux de laboratoire,les examens et competence en lecture) ou impermeables (discussions en classe, presentations orales, travaux en groupes, entretiens oraux, et communication avec les habitants locaux). La discussion clarifie l'usage d'uniques ressources personnelles par chaque participant La discussion clarifie l'usage d'uniques ressources personnelles par chaque participant dont le resultat definit des trajectoires distinctifs d'entree et de navigation au cœur de cette nouvelle culture academique. The authors wish to acknowledge the direction and support of Dr. Nombuso Dlamini throughout this research initiative. Introduction When students embark on a graduate program, they must come to terms with the specific values, hierarchies, discourses and requirements of its academic culture (Tanaka, 2002). This interpretive community can be an arena of aspiration and achievement or it can provide opportunities for negotiating or resisting that which is being discovered and experienced (Bartolomae, 1986). Through participating in this complex process of learning the academic culture, outsiders can be
Named Entity Resolution in Chinese News Comments on the Web

News comment is a new text genre which people use to express their opinions on recent news events. Different from normal text corpus, news comments have some particular properties. The named entities in the news comments usually use some wrongly written words, informal abbreviations or aliases, which bring great difficulties for machine detection and understanding. This paper addresses the issue of named entity resolution in Chinese news comments on the web, which is a special case of coreference resolution. Traditional resolution algorithms have some limitations for this special task. In this paper, we first define the special task, and then propose a novel resolution algorithm with new features to improve the resolution performance. We manually labeled a benchmark dataset with 60 pieces of news and their corresponding comments downloaded from a popular Chinese news portal and the experimental results on the dataset show that our algorithm is effective for this special task.
The Walrasian Tatonnement to Economize on Cognitive Transaction Costs: An Experiment

This paper compares experimentally the price formation on a Walrasian Tatonnement and on a Call Market in a common value environment with insiders and gains from trade inspired by Plott and Sunder (1982). A game-theoretical analysis shows that these two institutions are strategically equivalent. In the experiment, the informational efficiency is almost perfect on the two trading venues indicating that agents coordinate on the fully revealing equilibrium. However, the gains from trade are higher on the Walrasian Tatonnement than on the Call Market. As uninformed agents' deviations from equilibrium are more frequent on this latter institution, the market experiences a lower liquidity. The Walrasian Tatonnement is interpreted as an "explicit" mechanism: during the trading process, tentative prices can be observed and the execution price is known before transactions occur. This pre-trade transparency which is not as high on the Call Market has no influence on equilibrium outcomes but yet helps subjects finding out equilibrium strategies. This paper supports the view that trading institutions should be designed including cognitively ergonomic features to fit the limited nature of human rationality.
Chemoresistance to Valproate Treatment of Bovine Leukemia Virus-Infected Sheep; Identification of Improved HDAC Inhibitors

We previously proved that a histone deacetylase inhibitor (valproate, VPA) decreases the number of leukemic cells in bovine leukemia virus (BLV)-infected sheep. Here, we characterize the mechanisms initiated upon interruption of treatment. We observed that VPA treatment is followed by a decrease of the B cell counts and proviral loads (copies per blood volume). However, all sheep eventually relapsed after different periods of time and became refractory to further VPA treatment. Sheep remained persistently infected with BLV. B lymphocytes isolated throughout treatment and relapse were responsive to VPA-induced apoptosis in cell culture. B cell proliferation is only marginally affected by VPA ex vivo. Interestingly, in four out of five sheep, ex vivo viral expression was nearly undetectable at the time of relapse. In two sheep, a new tumoral clone arose, most likely revealing a selection process exerted by VPA in vivo. We conclude that the interruption of VPA treatment leads to the resurgence of the leukemia in BLV-infected sheep and hypothesize that resistance to further treatment might be due to the failure of viral expression induction. The development of more potent HDAC inhibitors and/or the combination with other compounds can overcome chemoresistance. These observations in the BLV model may be important for therapies against the related Human T-lymphotropic virus type 1.
Voxel-Based Analysis of T2 Hyperintensities in White Matter during Treatment of Childhood Leukemia

BACKGROUND AND PURPOSE: White matter (WM) hyperintensities on T2-weighted MR imaging are the most common imaging manifestation of neurotoxic effects of therapy for central nervous system (CNS) prophylaxis in childhood acute lymphoblastic leukemia (ALL). This study uses voxel-based analyses (VBA) of T2-weighted imaging of patients during treatment to identify which WM regions are preferentially damaged. MATERIALS AND METHODS: Two sets of conventional T2-weighted axial images were acquired on a 1.5T MR imaging scanner from 197 consecutive patients (85 female, 112 male; aged 1.0–18.9 years) enrolled on an institutional ALL treatment protocol. Images were acquired after completion of induction therapy and after the final of the 4 courses of intravenous high-dose methotrexate in consolidation therapy (3.9 ± 0.8 months apart). Voxel-wise statistical testing of the incremental change between normalized longitudinal T2 images was performed with radiologist reading (normal or abnormal) and treatment risk-group as covariates. RESULTS: Two highly significant bilateral clusters of T2 signal intensity change were identified in both 1-group and 2-group analyses. The regions were symmetric in size, shape, and average signal intensity. Increased T2-weighted signal intensity from these regions both within and between examinations were nonlinear functions of age at examination, and the difference between the examinations was greater for older subjects who received more intense therapy. CONCLUSIONS: These analyses identified specific WM tracts involving predominantly the anterior, superior, and posterior corona radiata and superior longitudinal fasciculus, which were at increased risk for the development of T2-weighted hyperintensities during therapy for childhood ALL. These vulnerable regions may be the cause of subsequent cognitive difficulties consistently observed in survivors.