Miracle-dz/UniFAR-FTUs huggingface dataset:
Sound imagery contributes to foot Mi-based BCI even through it does not influence on the sensorimotor rhythms

Recently, brain-computer interfaces (BCIs) attract much attention as novel human interfaces such as exoskeleton, powered-wheelchair, and P300-based speller. One of the EEG feature called event-related (de)synchronization (ERD/S) is used for the BCI, because it can be caused by motor execution (ME), motor imagery (MI), or motor observation (MO). ERD is a relative power decrease during ME/MI/MO, whereas ERS is a relative power increase after the termination of ME/MI/MO. Thus, not only healthy but also paralyzed patients can use BCIs. It is expected to improve quality of life and to be a neurore-habilitation system for paralyzed. Previous studies indicate that visual and auditory feedback corresponding to MI provide better training effect than non-feedback. From these previous studies, we hypothesized that imagining movement and sound at the same time could enhance ERD/S. We investigated this hypothesis by conducting an experiment. Furthermore, we considered that just motor imagery and motor imagery with sound imagery could be classified by support vector machine (SVM). As a result, we found that there are no significant differences between ERD/S during just MI and during MI with sound imagery, however the classification accuracy between just MI and MI with sound imagery is comparable to the classification accuracy between rest and just MI.
The microcirculation and inflammation: modulation of leukocyte‐endothelial cell adhesion

The accumulation of leukocytes in inflamed tissue results from adhesive interactions between leukocytes and endothelial cells within the microcirculation. These adhesive interactions and the excessive filtration of fluid and protein that accompanies an inflammatory response are largely confined to one region of the microvasculature: postcapillary venules. The nature and magnitude of the leukocyte–endothelial cell adhesive interactions that take place within postcapillary venules are determined by a variety of factors, including expression of adhesion molecules on leukocytes and/or endothelial cells, products of leukocyte (superoxide) and endothelial cell (nitric oxide) activation, and the physical forces generated by the movement of blood along the vessel wall. The contribution of different adhesion molecules to leukocyte rolling, adherence, and emigration in venules is discussed. Emerging views on potential endogenous antiadhesion molecules produced by endothelial cells as well as the influence of alterations in shear rate on leukocyte adhesion are addressed. Finally, the pathophysiological significance of the microvascular responses to inflammation are discussed in terms of adhesion‐directed strategies for the treatment of different cardiovascular diseases and circulatory disorders. J. Leukoc. Biol. 55: 662–675; 1994.
School Organizational Contexts, Teacher Turnover, and Student Achievement

We study the relationship between school organizational contexts, teacher turnover, and student achievement in New York City (NYC) middle schools. Using factor analysis, we construct measures of four distinct dimensions of school climate captured on the annual NYC School Survey. We identify credible estimates by isolating variation in organizational contexts within schools over time. We find that improvements in school leadership especially, as well as in academic expectations, teacher relationships, and school safety are all independently associated with corresponding reductions in teacher turnover. Increases in school safety and academic expectations also correspond with student achievement gains. These results are robust to a range of threats to validity suggesting that our findings are consistent with an underlying causal relationship.
UT Austin Villa 2003: A New RoboCup Four-Legged Team

The UT Austin Villa RoboCup 2003 Four-Legged Team was a new entry in the ongoing series of RoboCup legged league ompetitions. The team development began in mid-January of 2003, at whi h time none of the team members had any familiarity with the Aibos. Without using any RoboCup-related ode from other teams, we entered a team in the Ameri an Open ompetition at the end of April, and met with some su ess at the annual RoboCup ompetition that took pla e in Padova, Italy at the beginning of July. In this report, we des ribe both our development pro ess and the te hni al details of its end result, the UT Austin Villa team. The main ontributions of this paper are (i) a roadmap for new teams entering the ompetition who are starting from s rat h, and (ii) full do umentation of the algorithms behind our approa h with the goal of making them fully repli able.
Mapping corpus-based semantic role annotations from TreeBank and FrameNet to CG and Cyc

This paper presents an quantitative comparison of the se- mantic role inventories in two corpus-based resources for computational linguistics, TreeBank and FrameNet, along with the semantic roles from two knowledge representation frameworks, OpenCyc and Conceptual Graphs. In addition, experiments are done to illustrate the degree to which knowledge from the corpus-based resources can be transferred to the knowledge base resources. One benet of this is that new annotations in eect can be generated. In particular, there will eectiv ely be tagged data of the OpenCyc and Conceptual Graphs semantic roles, suitable for use in inferring the role usages.
Japan's Imbalance of Payments

During the past three decades, Japan’s current account experienced five large swings. The yen appreciated considerably in periods when the current account boomed, and it depreciated whenever Japan’s external performance weakened. However, there has always been a certain lag in the adjustment of the exchange rate. This paper tries to explain these empirical regularities. It argues that as a result of the large movements of the current account, the flows of cash between Japan and ist trading partners fluctuated considerably, which in turn influenced the demand for yen relative to other currencies. To the extent that these cash flows were lagging the current account—primarily because of the Japanese lending abroad—the exchange rate’s response to external imbalances occurred with a delay. Based on the estimated maturity structure of Japan’s foreign lending, the paper constructs a measure of payment flows across Japanese borders, which is shown to follow the movements of the exchange rate very closely. The empirical findings raise doubts regarding the feasibility of proposals to depreciate the yen in order to help Japan out of its current economic crisis.
An Architecture to Facilitate Membership and Service Management in Trusted Communities

Ubiquitous connectivity today allows many users to remain connected regardless of location with various kinds of communities. This paper studies challenges in building trusted communities that encompass both new users as well as users already possessing credentials from other well known connectivity providers, federations, content providers and social networks. We postulate that trusted communities are initially created as a means to access some services, but become enriched with user created services. We present an architecture aimed at managing the complexity of service composition, access as well as guarantees of authenticity. Since users possess multiple credentials from various identity providers, we address this in our architecture from the service access perspective. In addition, our model explicitly takes into account cases where users may temporarily be granted access to a community’s services based on recommendations from existing members.
A Multidisciplinary Model of Dementia Care in an Underserved Retirement Community, Made Possible by Telemedicine

The need for memory specialists is increasing as the incidence of dementia rapidly rises across the globe. In rural areas, demand for these specialists far outstrips supply. It is increasingly difficulty for patients to receive care in a timely manner. In this paper, we document our experience using videoconference telemedicine to bring a multidisciplinary model of care to a rural retirement community in Southern California. To our knowledge, we are one of the first to integrate telemedicine into dementia care on this large a scale. Given the relatively remote location, patients and neurologists have previously had to travel great distances and bear with long wait times. With neurological consultation by telemedicine and a local team consisting of a geriatrician, a neuropsychologist, and a case manager, we have been able to provide comprehensive dementia care in this underserved area, comparable to university-affiliated California Alzheimer’s Disease Centers, typically found only in major metropolitan areas. We have shown that telemedicine can be very effective in improving access and quality of dementia care.
RDBMS in Bioinformatics: The Bioconductor Experience

Bioconductor (http://www.bioconductor.org/) is an open source collection of resources aimed at transparently advancing the theory and practice of bioinformatics, with a focus on expression arrays and the R statistical computing environment. I will sketch the key data structures and data flow processes addressed in Bioconductor thus far. I will review the role played by RDBMS in the development and curation of packaged annotation networks and in the analysis of Serial Analysis of Gene Expression (SAGE) libraries. Non-relational database technologies such as BerkeleyDB and HDF5 have also played a role in tools for archiving and navigating expression array data. At present the role of RDBMS in Bioconductor is less pronounced than had been anticipated. This will change as requirements for query optimization, data structure standardization, and greater volumes of data and metadata emerge.
Uplink allocation beyond choke/unchoke: or how to divide and conquer best

Motivated by emerging cooperative P2P applications we study new uplink allocation algorithms for substituting the rate-based choke/unchoke algorithm of BitTorrent which was developed for non-cooperative environments. Our goal is to shorten the download times by improving the uplink utilization of nodes. We develop a new family of uplink allocation algorithms which we call BitMax, to stress the fact that they allocate to each unchoked node the maximum rate it can sustain, instead of an 1/(k + 1) equal share as done in the existing BitTorrent. BitMax computes in each interval the number of nodes to be unchoked, and the corresponding allocations, and thus does not require any empirically preset parameters like k. We demonstrate experimentally that Bit-Max can reduce significantly the download times in a typical reference scenario involving mostly ADSL nodes. We also consider scenarios involving network bottlenecks caused by filtering of P2P traffic at ISP peering points and show that BitMax retains its gains also in these cases.
On-Line Handwriting Recognition Using Hidden Markov Models

New global information-bearing features improved the modeling of individual letters, thus diminishing the error rate of an HMM-based on-line cursive handwriting recognition system. This system also demonstrated the ability to recognize on-line cursive handwriting in real time. The BYBLOS continuous speech recognition system, a hidden Markov model (HMM) based recognition system, is applied to on-line cursive handwriting recognition. With six original features, delta x, delta y, writing angle, delta writing angle, PenUp/PenDown bit, and sgn(x-max(x)), the baseline system obtained a word error rate of 13.8% in a 25K-word lexicon, 86-character set, writer-independent task. Four new groups of features, a vertical height feature, a space feature, hat stroke features, and substroke features, were implemented to improve the characterization of vertical height, inter-word space, and other global information. With the new features, the system obtained a word error rate of 9.1%, a 34% reduction in error. Additionally, the space feature and the substroke features each reduced the word error rate approximately 15%. In addition, we demonstrated real-time, large vocabulary, writer-independent, online cursive handwriting recognition without sacrificing much recognition accuracy of the baseline system by implementing minor modifications to the baseline handwriting recognition system. The details of the on-line cursive handwriting recognition system, the feature experiments, and the real-time demonstration system are presented. Thesis Supervisors: Dr. John Makhoul and Dr. Victor W. Zue Titles: Chief Scientist, Speech and Language Department, BBN Corp. and Senior Research Scientist, Dept. of EECS, MIT
A Taxonomy of Agent Technologies for Ubiquitous Computing Environments

The design, development and deployment of Mobile Agent (MA) systems for high-level inference and surveillance in wireless sensor networks and RFID systems have drawn increasing attention in the past decade. To answer how the state-of-the-art of MA in a wide range of ubiquitous and sensor environments is, this paper investigates the current progress of MA. It proposes a taxonomy, by which MA systems in ubiquitous computing environments are decomposed and discussed. Then, this paper provides insights into the strengths and weaknesses of existing efforts. Finally, it presents a series of solutions from the viewpoint of various roles of MA in ubiquitous environments and situations.
Evaluation of Activity Patterns in Quinpirole-Treated Rats

The present study aims to evaluate in rats the activity changes associated to treatments with D2-like receptor agonists using a simple behavioral procedure. Rats receiving a single dose of 1 mg/kg quinpirole or vehicle were scored for 6 spontaneous behaviors at different post-injection times. In each time point, the animals were placed in testing cages for 12 min and video-recorded during the last 2 min. The number of forelimb steps and the time spent sniffing were significantly increased by 15 min post-injection in the quinpirole group. Forelimb steps remained increased for at least 24 h. Scores of time spent sniffing, as well as time inactive and number of hindlimb steps appeared greatly altered at 90 and 180 min, but not at later time points. By 48 h, no differences between control and quinpirole-treated rats were observed. In conclusion, the simple behavioral procedure here proposed—or adaptations of it—provides a sensitive test to evaluate the time course of the effects of D2-like receptor agonists on rat spontaneous activity. Additionally, this test takes into account context-dependent sensitization. It can be adapted to different treatment conditions. This methodology would be useful for the preclinical screening of D2-like receptor drugs, using reduced numbers of animals to test those doses and treatment schedules producing less side-effects.
A new posterior based audio-visual integration method for robust speech recognition

We describe the development of a multistream HMM based audio-visual speech recognition (AVSR) system and a new method for integrating the audio and visual streams using frame level posterior probabilities. This is compared to the standard feature concatenation and weighted product methods in speaker-dependent tests using our own multimodal database, by examining speech recognition robustness to corruption in either stream. For corruption in the audio stream we use additive noise at different SNR levels, and for corruption in the video stream we use MPEG4 compression at different bitrates as well as image blurring using Gaussian filters. We provide very promising results which demonstrate the robustness of the new method.
CoEvolutionary Approaches in Cognitive Robotic System Design

In recent years, a large number of research efforts have been directed towards implementing cognitive robotic systems. One of the approaches for accomplishing cognitive system design is by following an optimization procedure. In particular, following this approach, the complete structure of the cognitive system is described by a set of parameters, while an optimization process is utilized to explore the parameters domain, identifying those values that give the cognitive system an appropriate behavior, according to a set of human-specified design criteria.
Self-Talk Theory, Research, and Applications: Some Personal Reflections

I am honored to have the opportunity to comment on the eight articles that make up the first Special Issue of an international journal focusing on self-talk in sport. The introductory article does an excellent job of tracing some of the important historical developments (theoretically, empirically, and practically) in the self-talk literature so I will not provide any historical perspective on the extant self-talk research. Rather, first I will comment on each article, noting what I perceive to be an important contribution to the self-talk literature (and sometimes the sport psychology literature in general). Then, based on my academic and practical knowledge in the area of self-talk, I will offer some suggestions for future research from conceptual, empirical, and methodological perspectives. In addition, I also offer some practical suggestions that coaches, athletes, and personal trainers/exercise leaders could use when working with athletes and exercisers. Before getting into these research and practical suggestions, a brief review of some of the unique and interesting parts of some of the articles within the Special Issue will be discussed.
The Climate Adaptation Frontier

Climate adaptation has emerged as a mainstream risk management strategy for assisting in maintaining socio-ecological systems within the boundaries of a safe operating space. Yet, there are limits to the ability of systems to adapt. Here, we introduce the concept of an “adaptation frontier”, which is defined as a socio-ecological system’s transitional adaptive operating space between safe and unsafe domains. A number of driving forces are responsible for determining the sustainability of systems on the frontier. These include path dependence, adaptation/development deficits, values conflicts and discounting of future loss and damage. The cumulative implications of these driving forces are highly uncertain. Nevertheless, the fact that a broad range of systems already persist at the edge of their frontiers suggests a high likelihood that some limits will eventually be exceeded. The resulting system transformation is likely to manifest as anticipatory modification of management objectives or loss and damage. These outcomes vary significantly with respect to their ethical implications. Successful navigation of the adaptation frontier will necessitate new paradigms of risk governance to elicit knowledge that encourages reflexive reevaluation of societal values that enable or constrain sustainability.
Defining and Evaluating Classification Algorithm for High-Dimensional Data Based on Latent Topics

Automatic text categorization is one of the key techniques in information retrieval and the data mining field. The classification is usually time-consuming when the training dataset is large and high-dimensional. Many methods have been proposed to solve this problem, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the Latent Dirichlet Allocation (LDA) algorithm and the Support Vector Machine (SVM). LDA is first used to generate reduced dimensional representation of topics as feature in VSM. It is able to reduce features dramatically but keeps the necessary semantic information. The Support Vector Machine (SVM) is then employed to classify the data based on the generated features. We evaluate the algorithm on 20 Newsgroups and Reuters-21578 datasets, respectively. The experimental results show that the classification based on our proposed LDA+SVM model achieves high performance in terms of precision, recall and F1 measure. Further, it can achieve this within a much shorter time-frame. Our process improves greatly upon the previous work in this field and displays strong potential to achieve a streamlined classification process for a wide range of applications.
Preanalytical external quality assessment of the Croatian Society of Medical Biochemistry and Laboratory Medicine and CROQALM: finding undetected weak spots

Introduction The aim of this paper is to present results of first two years of preanalytical external quality assessment (EQA) in Croatia. Materials and methods This paper summarizes results from 6 rounds of preanalytical EQA during 2014-2016 in 161-175 Croatian laboratories (number ranged between cycles). EQA was designed as an online survey of the compliance with National recommendations for phlebotomy (NRP). Forty-seven questions in 5 categories are analyzed (materials and equipment, patient identification, patient preparation, sampling and storage). Additionally, preanalytical cases are presented. Overall performance scores (Question score (Qscore) for compliance with NRP and Case score (Cscore) for preanalytical cases) are calculated for each question/case as a proportion of laboratories with satisfactory procedure (x 100). Qscores and Cscores ≥ 70 were classified as acceptable (maximal score = 100). Results In investigation of compliance with NRP, acceptable Qscores were obtained for 34/47 questions. The lowest scores were observed for the availability of sterile disposable tourniquets (Qscore = 15) and safe-sharp needles (Qscore = 34), obtaining patients address as an identifier (Qscore = 21), using glycolysis inhibitor tubes for glucose concentration measurement (Qscore = 21) and verification of manufacturers declarations on temperature and time of storage (Qscore = 31). There was no statistically significant difference in overall Qscore according to different categories of phlebotomy procedures (P = 0.284). The results of preanalytical cases showed acceptable Cscore values for all cases (89-96). Conclusion First two years of preanalytical EQA showed good compliance with the NRP and excellent expertise in resolving complex preanalytical issues. Major critical spots are lack of availability of safe-sharp needles, disposable tourniquets and glucose inhibitor tubes.
Computer Vision Techniques for Automatic Structural Assessment of Underground Pipes

Pipeline surface defects such as cracks cause major problems for asset managers, particularly when the pipe is buried under the ground. The manual inspection of surface defects in the underground pipes has a number of drawbacks, including subjectivity, varying standards, and high costs. An automatic inspection system using image processing and artificial intelligence techniques can overcome many of these disadvantages and offer asset managers an opportunity to significantly improve quality and reduce costs. This article presents a system for the application of computer vision techniques to the automatic assessment of the structural condition of underground pipes. The algorithm consists of image preprocessing, a sequence of morphological operations to accurately extract pipe joints and laterals (where smaller pipe is connected to main bigger pipe), and statistical filters for detection of surface cracks in the pipeline network. The proposed approach can be completely automated and has been tested on over 1,000 scanned images of underground pipes from major cities in North America.