Miracle-dz/UniFAR-FTUs huggingface dataset:
A Method of Hand Gesture Segmentation and Tracking with Appearance Based on Probability Model

A novel probability model is presented using the probability-based method of moving information selection together with the skin color probability distribution image. After the division of the images, the moving information is obtained by the use of the statistical frame difference method. In order to locate the accurate location of the hand position, the center of the hand is found via moving value and skin color information. From the seed point, region growth method is proposed for the initiate of the hand region to obtain the size and position of a search window. The current size and location of the tracked hand are used to forecast and track the search window in the next video image. Then the segmentation and tracking of the dynamic hand are realized. Experiments show that this method is so robust to noise and complex backgrounds that it can track the moving object with the shape of hand changing. Additionally, tracking the hand accurately is feasible in a real-time way. Furthermore it can be used for the segmentation and the tracking of a moving object with special color.
Methicillin-resistant Staphylococcus aureus ulcerative keratitis in a Thoroughbred racehorse

ABSTRACT We report the first case of methicillin-resistant Staphylococcus aureus (MRSA) keratitis in a racehorse. A 5-year-old mare developed punctate keratitis after racing. The corneal ulcer continued to expand despite ophthalmic antimicrobial therapy. On day 6, a conjunctival graft surgery was performed. The mare was euthanized, following colitis and laminitis development on day 10. MRSA was isolated from the corneal swab taken at the time of euthanasia. Immunohistochemical analysis demonstrated gram-positive and anti-S. aureus monoclonal antibody-positive cocci infiltration of the corneal stroma; and a diagnosis of MRSA ulcerative keratitis was made. An ophthalmic antimicrobial against the isolated MRSA did not improve the ocular lesion. The MRSA strain was found to be staphylococcal cassette chromosome mec type II, a strain frequently isolated from humans in Japan.
A Cucumber Mosaic Virus Based Expression System for the Production of Porcine Circovirus Specific Vaccines

Potential porcine circovirus type 2 (PCV2) capsid protein epitopes, suitable for expression on the surface of cucumber mosaic virus (CMV) particles were determined by a thorough analysis of the predicted PCV capsid protein structure. The ab initio protein structure prediction was carried out with fold recognition and threading methods. The putative PCV epitopes were selected on the basis of PCV virion models and integrated into the plant virus coat protein, after amino acid position 131. The recombinants were tested for infectivity and stability on different Nicotiana species and stable recombinant virus particles were purified. The particles were tested for their ability to bind to PCV induced porcine antibodies and used for specific antibody induction in mice and pigs. The results showed that PCV epitopes expressed on the CMV surface were recognized by the porcine antibodies and they were also able to induce PCV specific antibody response. Challenge experiment with PCV2 carried out in immunized pigs showed partial protection against the infection. Based on these results it was concluded that specific antiviral vaccine production for the given pathogen was feasible, offering an inexpensive way for the mass production of such vaccines.
RGB-D Object Recognition from Hand-Held Object Teaching

For RGB-D object recognition, conventional methods only focus on classification, which neglects the importance of humans for object segmentation and object concept learning in the interaction and has limitations when transferring the learned knowledge to general indoor scenes. In this paper, we propose a system that humans can teach robots object concepts and instances by the way of handheld object recognition, a newly research topic in RGB-D object recognition, then these concepts and instances are transferred to more general indoor scenes to recognize target objects. Unlike traditional approaches of RGB-D object recognition, human-machine interaction is considered in our system, in which robots can obtain the object region from object segmentation and enhance its own interactive learning ability. In addition, we propose an RGB-D object dataset to match the hand-held object dataset. In experiments, we use CNN to learn feature representation of RGB-D images in the hand-held training object dataset and RGB-D test object dataset respectively. Experimental results show that our system has a strong capability in RGB-D object recognition.
Mild cognitive impairment. Part 1: clinical characteristics and predictors of dementia.

OBJECTIVE To critically review and evaluate existing knowledge on the conceptual limits and clinical usefulness of the diagnosis of mild cognitive impairment (MCI) and the neuropsychological assessment and short- and long-term prognosis thereof. METHODS We conducted a systematic search of the PubMed and Web of Science electronic databases, limited to articles published in English between 1999 and 2012. Based on the search terms mild cognitive impairment or MCI and epidemiology or diagnosis, we retrieved 1,698 articles, of which 248 were critically eligible (cross-sectional and longitudinal studies); the abstracts of the remaining 1,450 articles were also reviewed. RESULTS A critical review on the MCI construct is provided, including conceptual and diagnostic aspects; epidemiological relevance; clinical assessment; prognosis; and outcome. The distinct definitions of cognitive impairment, MCI included, yield clinically heterogeneous groups of individuals. Those who will eventually progress to dementia may present with symptoms consistent with the definition of MCI; conversely, individuals with MCI may remain stable or return to normal cognitive function. CONCLUSION On clinical grounds, the cross-sectional diagnosis of MCI has limited prognostic relevance. The characterization of persistent and/or progressive cognitive deficits over time is a better approach for identification of cases at the pre-dementia stages, particularly if these cognitive abnormalities are consistent with the natural history of incipient Alzheimer's disease.
Proteomic Characterization of Perisynaptic Astrocytes in Synaptic Plasticity

Astrocytes are the most abundant cell type in the brain and mediate a myriad offunctions, including neurogenesis, ion homeostasis, metabolic support, clearance oftoxic substances and responses to brain injuries. Alterations in astrocyte functionhave been linked with neurological disorders such as epilepsy, depression, dementiaand schizophrenia, and thus the continued study of astrocytic contributions tosynaptic function are of clinical and societal relevance. In this thesis I have evaluatedthe potential utility of several preparations for the assessment of astrocyte proteinsinvolved in the regulation of synaptic plasticity, and employed the most suitable ofthese preparations to measure regulation in astrocyte protein levels in models ofsynaptic plasticity. I have characterized several preparations that can be used toevaluate astrocyte contributions to synaptic plasticity and identified numerousastrocyte-enriched proteins regulated by synaptic plasticity that can be targeted infuture studies to elaborate upon the mechanisms of action of astrocytes in bothphysiological and pathological contexts.
Adult transitional theory and transfer shock in higher education: practices from the literature

Purpose This paper aims to outline foundational research on adult transition theory and transfer shock in higher education to provide the reader with a theoretical and practical framework for the library-focused articles in this special issue. Design/methodology/approach This paper is a review of relevant higher education literature related to transfer shock and core research related to adult transitional theory. Findings Transition is a period in-between moments of stability. The state of confusion and disorientation caused by the transition of transfer students from one academic culture to another is a form of culture shock known as transfer shock. “Transfer shock” refers to the decline in academic performance by transfer students immediately following transition to an institution of higher education and the corresponding recovery prevalent for most students in succeeding semesters. Recent studies have expanded the definition of transfer shock to include the academic and social factors that contribute to attrition and lack of degree persistence. Key factors that correlate to transfer students’ success or failure include gender, race, time of transfer, GPA, prior academic success, faculty collaboration, level of engagement with degree program and campus support. Originality/value Although most literature on transfer students published by librarians includes literature reviews citing relevant articles, it lacks an extensive literature review collecting research from social science and education literature.
Research of Low SNR Crack Denoising Based on Kernel Anisotropic Diffusion

We propose a new kernel anisotropic diffusion filter for denoising low signal-to-noise ratio (SNR) crack images of straddle-type monorail beam surface. This method incorporates an enhancement operator into the diffusion steps, and then the low dimensional data is promoted to high dimensional space according to the characteristic of noise uniformly distributing in the multidimensional space, also average absolute difference value of automatic diffusion termination criterion is introduced to enhance the efficiency of diffusion. In addition, a different edge enhancement weight is explored to achieve the appropriate result. This method achieved much better noise suppression with minimum edge blurring compared with median filter and the original anisotropic diffusion filter when it was tested on the low SNR crack image of straddle-type monorail beam surface of 0.4mm width.
A large-scale analysis of query logs for assessing personalization opportunities

Query logs, the patterns of activity left by millions of users, contain a wealth of information that can be mined to aid personalization. We perform a large-scale study of Yahoo! search engine logs, tracking 1.35 million browser-cookies over a period of 6 months. We define metrics to address questions such as 1) How much history is available? , 2) How do users' topical interests vary, as reflected by their queries? , and 3) What can we learn from user clicks? We find that there is significantly more expected history for the user of a randomly picked query than for a randomly picked user. We show that users exhibit consistent topical interests that vary between users. We also see that user clicks indicate a variety of special interests. Our findings shed light on user activity and can inform future personalization efforts.
An empirical study assessing the effect of seeit 3D on comprehension

A study to assess the effect of SeeIT 3D, a software visualization tool is presented. Six different tasks in three different task categories are assessed in the context of a large open-source system. Ninety-seven subjects were recruited from three different universities to participate in the study. Two methods of data collection: traditional questionnaires and an eye-tracker were used. The main goal was to determine the impact and added benefit of SeeIT 3D while performing typical software tasks within the Eclipse IDE. Results indicate that SeeIT 3D performs significantly better in one task category namely overview tasks but takes significantly longer when completing bug fixing tasks. Scores obtained by the subjects in the SeeIT 3D group are 13% better and 45% faster for overview tasks.
Europe's Future with the Euro

I discuss the prospects of the economic future of the European Union (EU) in the light of the adoption of the Euro. The monetary policy of the European Central Bank (ECB) and countries' fiscal policies are the only tools that can effectively reduce macroeconomic imbalances in the EU countries. For the ECB's policy to be effective, the member states need to be on similar business cycles. The EU countries from 1993 until 2002 exhibited large disparities in terms of income, unemployment and industry concentration. In the first part of the thesis I consider microeconomic aspects of fiscal policy. I show that the policies the European Commission put in place to reduce these differences produced a reduction in concentration of the industries, but at the same time created an increase in specialization of the EU regions and countries. I look, in particular, at the location of the high tech industry and show that it evolved in the same way as most of the manufacturing industries in the EU. Since 1999, macroeconomic conditions in the twelve of the EU countries that have adopted the common currency (the Euro) may be studied in terms of the interaction between the ECB and 12 independent national fiscal policies. Recent theories suggest that if these authorities have the same objectives in terms of output and price stability, then their objectives can be attained and an optimal economic outcome will occur; in all other situations the outcome will be sub-optimal. In the second part of the thesis I estimate a modified Taylor Rule and show that monetary authorities in the EU from 1993 until 2002 were solely concerned with the reduction of inflation. My estimation of Taylor-type Rules for fiscal policy suggests that national fiscal authorities tried, over the same time period, to reduce both inflation and unemployment. So, both 3 authorities were employing broadly compatible countercyclical policies. This is promising for the EU's economic future for it means that the optimal economic outcome in terms of price and output stability can be attained. An important part of the EU's path to monetary union is the creation of the European System of Central Banks and the ECB. The European Union thus offers the grounds for a unique experiment since from 1993 until 1999 all of the EU central banks became independent. Economists suggest independent central banks are more inflation averse and thus encourage fiscal authorities to become …
How powerful is adiabatic quantum computation?

The authors analyze the computational power and limitations of the recently proposed 'quantum adiabatic evolution algorithm'. Adiabatic quantum computation is a novel paradigm for the design of quantum algorithms; it is truly quantum in the sense that it can be used to speed up searching by a quadratic factor over any classical algorithm. On the question of whether this new paradigm may be used to efficiently solve NP-complete problems on a quantum computer, we show that the usual query complexity arguments cannot be used to rule out a polynomial time solution. On the other hand, we argue that the adiabatic approach may be thought of as a kind of 'quantum local search'. We design a family of minimization problems that is hard for such local search heuristics, and establish an exponential lower bound for the adiabatic algorithm for these problems. This provides insights into the limitations of this approach. It remains an open question whether adiabatic quantum computation can establish an exponential speed-up over traditional computing or if there exists a classical algorithm that can simulate the quantum adiabatic process efficiently.
Data Transmission Scheduling Based on RTS/CTS Exchange for Periodic Data Gathering Sensor Networks

SUMMARY One challenging issue of sensor networks is extension of overall network system lifetimes. In periodic data gathering applications, the typical sensor node spends more time in the idle state than active state. Consequently, it is important to decrease power consumption during idle time. In this study, we propose a scheduling scheme based on the history of RTS/CTS exchange during the setup phase. Scheduling the transmission during transfer phase enables each node to turn off its RF circuit during idle time. By tracing ongoing RTS/CTS exchange during the steady phase, each node knows the progress of the data transfer process. Thereby, it can wait to receive packets for data aggregation. Simulation results show a 160–260% longer system lifetime with the proposed scheduling scheme compared to
Localization of multiple sound sources based on a CSP analysis with a microphone array

Accurate localization of multiple sound sources is indispensable for the microphone array-based high quality sound capture. For single sound source localization, the CSP (cross-power spectrum phase analysis) method has been proposed. The CSP method localizes a sound source as a crossing point of sound directions estimated using different microphone pairs. However, when localizing multiple sound sources, the CSP method has a problem that the localization accuracy is degraded due to cross-correlation among different sound sources. To solve this problem, this paper proposes a new method which suppresses the undesired cross-correlation by synchronous addition of CSP coefficients derived from multiple microphone pairs. Experiment results in a real room showed that the proposed method improves the localization accuracy when increasing the number of the synchronous addition.
pFilter: global information filtering and dissemination using structured overlay networks

The exponential data growth rate of the Internet makes it increasingly difficult for people to find desired information in a timely fashion. Information filtering and dissemination systems allow users to register persistent queries called user profiles, and notify users when relevant files become available. Existing such systems, however, either are not scalable, or do not support matching of unstructured documents (e.g., text, HTML, image, audio or video files) that account for a significant percentage of Internet contents. We propose pFilter a global-scale, decentralized information filtering and dissemination system for unstructured documents. To handle potentially billions of documents for millions of subscribers, pFilter connects a large number of computers into a structured peer-to-peer overlay network. Computers in the overlay collectively publish or collect documents, build indices, register profiles, filter and disseminate documents. Profiles and documents are distributed through the network according to their semantics such that they can be matched efficiently and accurately without excessive flooding. pFilter employs scalable application-level multicast to deliver matching documents to a large number of interested parties efficiently.
Notch–RBP-J signaling controls the homeostasis of CD8− dendritic cells in the spleen

Signaling through Notch receptors and their transcriptional effector RBP-J is essential for lymphocyte development and function, whereas its role in other immune cell types is unclear. We tested the function of the canonical Notch–RBP-J pathway in dendritic cell (DC) development and maintenance in vivo. Genetic inactivation of RBP-J in the bone marrow did not preclude DC lineage commitment but caused the reduction of splenic DC fraction. The inactivation of RBP-J in DCs using a novel DC-specific deleter strain caused selective loss of the splenic CD8− DC subset and reduced the frequency of cytokine-secreting CD8− DCs after challenge with Toll-like receptor ligands. In contrast, other splenic DC subsets and DCs in the lymph nodes and tissues were unaffected. The RBP-J–deficient splenic CD8− DCs were depleted at the postprogenitor stage, exhibited increased apoptosis, and lost the expression of the Notch target gene Deltex1. In the spleen, CD8− DCs were found adjacent to cells expressing the Notch ligand Delta-like 1 in the marginal zone (MZ). Thus, canonical Notch–RBP-J signaling controls the maintenance of CD8− DCs in the splenic MZ, revealing an unexpected role of the Notch pathway in the innate immune system.
Construction and Analysis of Japanese-English Broadcast News Corpus with Named Entity Tags

We are aiming to acquire named entity (NE) translation knowledge from nonparallel, content-aligned corpora, by utilizing NE extraction techniques. For this research, we are constructing a Japanese-English broadcast news corpus with NE tags. The tags represent not only NE class information but also coreference information within the same monolingual document and between corresponding Japanese-English document pairs. Analysis of about 1,100 annotated article pairs has shown that if NE occurrence information, such as classes, number of occurrence and occurrence order, is given for each language, it may provide a good clue for corresponding NEs across languages.
Rate-distortion analysis of nonlinear quantisers for video coders

Quantisation is used in video coders such as MPEG in association with rate control scheme to regulate the data rate of compressed video bit stream entering the transmission buffer. When the transmission data rate is limited the quantiser has a crucial effect on video data rate and video quality. The quantiser step size is generally determined by a linear non-adaptive method with respect to the buffer occupancy. In this paper, we investigate in the framework of rate-distortion theory two adaptive nonlinear quantiser control functions, sigmoidal and unimodal, which achieve superior video rate control performance while maintaining similar video quality to the linear case. Their performance for video rate fluctuation has also been analysed in both analytic and experimental ways.
Adaptation to learning styles in E-Learning: Approach evaluation

It is obvious that we all have different approaches to learning. Psychologists call these individual differences learning styles (LS). Researchers provide recommendations for possible instructional strategies to support some LS in educational settings and, in particular, in web-based environments. The problem with most existing implementations is that the systems are bound to a certain LS model, and the LS representation it involves is defined and implemented by the designers of the system. The purpose of our approach is to separate definition of strategies from the system implementation and to allow authors or psychologists to define their own strategies in a domain- and LS-model independent way. We define a language for specifying instructional strategies and strategies for monitoring a learner's preferences, and a way of applying and visualizing them in the AHA! (Adaptive Hypermedia Architecture) system. This paper presents the results of our approach evaluation from the point of view of LS authoring easiness and satisfaction with the resulting adaptation.
The Effect of the Clearance Value of Impeller and Draft-tube for the Performance of Stamping Multistage Centrifugal Pumps

Change the clearance between the outer edge of the impeller and the draft tube to get a good performance, simulated by the commercial software CFX of CFD. The paper numerically calculates the flow of stamping and welding multistage centrifugal pumps, forecasts its properties, studies the changes which impact its performance in space, gets the reasonable scope of space for stamping and welding multistage centrifugal pumps. It provides a theoretical basis for the design of stamping and welding multistage centrifugal pumps, improves the performance of the centrifugal pump in practical application, increases the operating efficiency of the pump
Robust Design of Linear MIMO Transceiver for Low SNR

In practical systems, the design of linear MIMO transceivers should be robust to partial or imperfect channel state information (CSI). This paper considers the case in which only the second-order statistics of the channel is known at the transmitter while the receiver has a perfect CSI. In such a case, it is possible to optimally design robust MIMO transceivers based on a general cost function covering several well known performance criteria. In particular, two families are considered in detail: Schur-convex and Schur-concave functions. Approximations are used in the low SNR regime to obtain simple optimization problems that can be readily solved. Numerical examples show substantial gains compared to other methods