Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute effects of intermittent pneumatic compression on popliteal artery blood flow.

OBJECTIVES To investigate the immediate effects of intermittent pneumatic foot and calf compression (IPFCC) on popliteal artery blood flow in symptom-free volunteers and to determine the reproducibility of color flow duplex imaging in the popliteal artery. DESIGN Cohort study. SETTING A university associated tertiary care hospital. PATIENTS Forty lower limbs of 30 volunteers without symptoms or noteworthy risk factors of peripheral vascular disease. INTERVENTIONS Popliteal artery blood flow was measured in the sitting position before, during, and after the application of IPFCC using color flow duplex imaging. The interobserver, intraobserver, and between occasion within-subject variability of the popliteal artery blood flow were evaluated in 5 symptom-free volunteers who had at least 5 color flow duplex imaging measurements taken at each of the above time points on 3 different days. MAIN OUTCOME MEASURES The arterial diameter, peak systolic, end diastolic, and reverse-flow velocities were measured, as well as the duration of forward flow during diastole before, during, and after IPFCC. The same variables were measured in 5 separate volunteers by 3 different observers, on 3 separate days, at 3 separate times to determine reproducibility. RESULTS Including all types of variability, the popliteal artery blood flow varied from 8% to 39% with a mean value of 19%. Since the diameter of the artery was obtained with less than 5% variability, the time average mean velocity was responsible for the high variation in flow. During application of the IPFCC, the popliteal artery blood flow increased significantly in all subjects (P<.001). The mean increase in the flow was 2.4 times the baseline values. The diameter of the arteries remained unchanged while the time average velocity increased significantly (P<.001). This velocity increase was due to marked elevation in the peak systolic and end diastolic velocities and diminution of the reverse-flow component, as well as a prolongation of the forward flow during diastole. After cessation of the pump, flow returned to baseline levels (P=.41) CONCLUSIONS Ultrasound-derived popliteal artery blood flow measurements show moderate variability. The application of IPFCC greatly enhances popliteal artery blood flow. The flow increase is due to a dramatic drop in the peripheral vascular resistance as the peak systolic and end diastolic flow velocities increase and the reverse-flow component diminishes. Its role in the treatment of lower extremity occlusive arterial disease needs to be determined.
Increased Levels of Markers of Microbial Exposure in Homes with Indoor Storage of Organic Household Waste

ABSTRACT As part of environmental management policies in Europe, separate collection of organic household waste and nonorganic household waste has become increasingly common. As waste is often stored indoors, this policy might increase microbial exposure in the home environment. In this study we evaluated the association between indoor storage of organic waste and levels of microbial agents in house dust. The levels of bacterial endotoxins, mold β(1→3)-glucans, and fungal extracullar polysaccharides (EPS) of Aspergillus andPenicillium species were determined in house dust extracts as markers of microbial exposure. House dust samples were collected in 99 homes in The Netherlands selected on the basis of whether separated organic waste was present in the house. In homes in which separated organic waste was stored indoors for 1 week or more the levels of endotoxin, EPS, and glucan were 3.2-, 7.6-, and 4.6-fold higher, respectively (all P < 0.05), on both living room and kitchen floors than the levels in homes in which only nonorganic residual waste was stored indoors. Increased levels of endotoxin and EPS were observed, 2.6- and 2.1-fold (P < 0.1), respectively, when separated organic waste was stored indoors for 1 week or less, whereas storage of nonseparated waste indoors had no effect on microbial agent levels (P > 0.2). The presence of textile floor covering was another major determinant of microbial levels (P < 0.05). Our results indicate that increased microbial contaminant levels in homes are associated with indoor storage of separated organic waste. These increased levels might increase the risk of bioaerosol-related respiratory symptoms in susceptible people.
Caring in the Information Age: Personal Online Networks to Improve Caregiver Support

Background It is becoming increasingly important to find ways for caregivers and service providers to collaborate. This study explored the potential for improving care and social support through shared online network use by family caregivers and service providers in home care. Methods This qualitative study was guided by Rogers’ Theory of Diffusion of Innovations [NY: Free Press; 1995], and involved focus group and individual interviews of service providers (n = 31) and family caregivers (n = 4). Interview transcriptions were analyzed using descriptive, topic, and analytic coding, followed by thematic analysis. Results The network was identified as presenting an opportunity to fill communication gaps presented by other modes of communication and further enhance engagement with families. Barriers included time limitations and policy-related restrictions, privacy, security, and information ownership. Conclusion Online networks may help address longstanding home-care issues around communication and information-sharing. The success of online networks in home care requires support from care partners. Future research should pilot the use of online networks in home care using barrier and facilitator considerations from this study.
Uncertainty Visualization for Crisis Management in Smart Grid Environments

Visual analytics systems are in place within smart grid environments to alleviate crisis situations by allowing decision makers to perceive and understand the severity of a crisis situation. However, errors in measurements that are propagated due to various reasons (such as data transformations, errors in measurement devices etc.) can make the decision makers less confident in deriving information. Therefore, analysis and visualization of uncertainty within such data has become important. In this paper we utilize two uncertainty propagation techniques: sampling and Monte Carlo simulation, to propagate uncertainties inherent in power data within our smart grid environment, and compare their performance to best fit our use-case. We found that the Monte Carlo simulation method is most suitable for measuring uncertainty in our application domain. Further, we identified most effective visual metaphors to communicate uncertainty to the crisis managers.
Extraction of information from video sound tracks - Can we detect simultaneous events?

Detecting and tracking broad sound classes in audio documents is an important step toward their structuration. In the case of complex audio scenes, such as the sound track of a TV broadcast, one problem is that several classes of sound maybe present simultaneously. It is therefore important to detect such superimposed events. Most methods would necessitate to estimate a model for each combination of sound classes that is to be detected, which is intractable in practice since it requires a lot of manual labelling. In this paper, we propose and compare several approaches to detect simultaneous events using only the models of the base classes we are interested in. Two main approaches are compared: model combination and binary hypothesis tests. The results show that the best results are obtained with the model combination approach.
THE EFFECT OF TIME DELAY ON THE ABILITY TO CONTROL UNSTABLE SYSTEMS

This experiment examined the effect of time delays on the ability to stabilize an inverted pendulum. The results were determined by examining the amount of time the system's oscillations remained bounded before increasing exponentially. This was done for each combination of time delay and pendulum length covered in this experiment. The results showed that for a pendulum length of 49 meters, all time delays in the identified range were able to be stabilized. The results also showed that for a pendulum length of 2.45 meters, no time delays in the identified range were able to be stabilized.
A WL-SPPIM Semantic Model for Document Classification

In this paper, we explore SPPIM-based text classification method, and the experiment reveals that the SPPIM method is equal to or even superior than SGNS method in text classification task on three international and standard text datasets, namely 20newsgroups, Reuters52 and WebKB. Comparing to SGNS, although SPPMI provides a better solution, it is not necessarily better than SGNS in text classification tasks. Based on our analysis, SGNS takes into the consideration of weight calculation during decomposition process, so it has better performance than SPPIM in some standard datasets. Inspired by this, we propose a WL-SPPIM semantic model based on SPPIM model, and experiment shows that WL-SPPIM approach has better classification and higher scalability in the text classification task compared with LDA, SGNS and SPPIM approaches.
Characteristics of many-objective test problems and penalty parameter specification in MOEA/D

Recently a number of evolutionary many-objective algorithms have been proposed using uniformly generated weight vectors. Those algorithms can be viewed as improved versions of MOEA/D with the PBI (penalty-based boundary intersection) function. Reference lines are uniformly specified using the weight vectors in the normalized objective space. The basic idea of those algorithms is to find a single solution along each reference line. Whereas a different search mechanism has been devised in each algorithm, solution assignment to reference lines is commonly based on the distance to the nearest reference line. This solution assignment can be interpreted as using a larger penalty value in MOEA/D with PBI. Actually, MOEA/D with PBI works well on frequently-used many-objective test problems DTLZ1-4 when a large penalty value is used. However, the shape of the contour lines of the PBI function suggests the use of a small penalty value for many-objective problems. Moreover, good results have been reported in the literature for many-objective knapsack problems when a small penalty value was used. In this paper, we discuss why good results are obtained from a large penalty value from a viewpoint of characteristics of DTLZ1-4 as test problems. Our discussions on the use of a large penalty value also explain why good results are obtained by recently-proposed weight vector-based evolutionary many-objective algorithms.
What Causes Gender Differences in the Participation and Intensity of Lifelong Learning

We use recent advances in the statistical analysis of Oaxaca-Blinder decompositions for non-linear models to analyse the contribution of individual variables to total gender differences in participation and duration of training. Results suggest that effects stemming from the intra-household division of labour contribute significantly to gender differences, but that segregation of the labour market as well as differences in the access to training by tenure, age, occupation, profession and sectors are more important.
A new closed-form approximations for MRC receiver over non-identical Weibull fading channels

In this paper, we derive a novel probability density function (PDF)-based expression for various performance criteria with L-branch maximal-ratio combining over independent and not necessarily identical Weibull fading channels. Approximating the output SNR by a simple H-distribution, useful closed formulas for cumulative distribution function, moment generating function, outage probability, amount of fading, average capacity, and average symbol error rate for some M-ary modulation schemes are derived in terms of Meijer G-function. All results are illustrated and validated by computed simulations using Mathematica software.
Proteomics equipped with multiplexing toward ultra high throughput

MS‐based quantitative proteomics is a powerful technology to study virtually almost all biological and clinical samples. Although it has been known to be a high‐throughput method, an MS analysis of a higher number of samples remains to be challenging practically and economically. In this issue, the use of multiplexing strategy for quantitative analysis of proteomes and phosphoproteomes has been demonstrated by Paulo et al. (Proteomics 2015, 15, 462–473) to better understand in vivo effects of two small molecule inhibitors on a mouse model. Within the short period of drug treatment, it has been found that the protein alteration is minimal in three tissues tested, whereas the phosphorylation level was widely altered.
Entropie en Traitement du Signal Entropy in Signal Processing

Le principal objet de cette communication est de faire une r´etro perspective succincte de l’utilisation de l’entropie et du principe du maximum d’entropie dans le domaine du traitement du signal. Apr`es un bref rappel de quelques d´eﬁnitions et du principe du maximum d’entropie, nous verrons successivement comment l’entropie est utilis´ee en s´eparation de sources, en mod´elisation de signaux, en analyse spectrale et pour la r´esolution des probl`emes inverses lin´eaires. Mots cl´es : Entropie, Entropie crois´ee, Distance de Kullback, Information mutuelle, Estimation spectrale, Probl`emes inverses Abstract The main object of this work is to give a brief overview of the diﬀerent ways the entropy has been used in signal and image processing. After a short introduction of diﬀerent quantities related to the entropy and the maximum entropy principle, we will study their use in diﬀerent ﬁelds of signal processing such as : source separation, model order selection, spectral estimation and, ﬁnally, general linear inverse problems.
Receptor Activator of NF-κB Ligand Stimulates Recruitment of SHP-1 to the Complex Containing TNFR-Associated Factor 6 That Regulates Osteoclastogenesis1

Receptor activator of NF-κB ligand (RANKL) is essential for differentiation and function of osteoclasts. The negative signaling pathways downstream of RANKL are not well characterized. By retroviral transduction of RAW264.7 cells with a dominant negative Src homology 2 domain-containing phosphatase-1 (SHP-1)(C453S), we studied the role of tyrosine phosphatase SHP-1 in RANKL-induced osteoclastogenesis. Over-expression of SHP-1(C453S) significantly enhanced the number of tartrate-resistant acid phosphatase-positive multinuclear osteoclast-like cells in response to RANKL in a dose-dependent manner. RANKL induced the recruitment of SHP-1 to a complex containing TNFR-associated factor (TRAF)6. GST pull down experiments indicated that the association of SHP-1 with TRAF6 is mediated by SHP-1 lacking the two Src homology 2 domains. RANKL-stimulated IκB-α phosphorylation, IκB-α degradation and DNA binding ability of NF-κB were increased after over-expression of SHP-1(C453S). However, RANKL-induced phosphorylation of mitogen-activated protein kinases, extracellular signal-regulated kinase, c-Jun N-terminal kinase, and p38 mitogen-activated protein kinase, was unchanged. In addition, SHP-1 regulated RANKL-stimulated tyrosine phosphorylation of p85 subunit of phosphatidylinositol 3 kinase and the phosphorylation of Akt. Increased numbers of osteoclasts contribute to severe osteopenia in Mev/Mev mice due to mutation of SHP-1. Like RAW264.7 cells expressing SHP-1(C453S), the bone marrow macrophages of Mev/Mev mice generated much more osteoclast-like cells than that of littermate controls in response to RANKL. Furthermore compared with controls, RANKL induces enhanced association of TRAF6 and RANK in both RAW264.7 cells expressing SHP-1(C453S) and bone marrow macrophages from Mev/Mev mice. Therefore, SHP-1 plays a role in signals downstream of RANKL by recruitment to the complex containing TRAF6 and these observations may help to understand the mechanism of osteoporosis in Mev/Mev mice.
Distributed algorithms for content allocation in interconnected content distribution networks

Internet service providers increasingly deploy internal CDNs with the objective of reducing the traffic on their transit links and to improve their customers' quality of experience. Once ISP managed CDNs (nCDNs) become commonplace, ISPs would likely provide common interfaces to interconnect their nCDNs for mutual benefit, as they do with peering today. In this paper we consider the problem of using distributed algorithms for computing a content allocation for nCDNs. We show that if every ISP aims to minimize its cost and bilateral payments are not allowed then it may be impossible to compute a content allocation. For the case of bilateral payments we propose two distributed algorithms, the aggregate value compensation (AC) and the object value compensation (OC) algorithms, which differ in terms of the level of parallelism they allow and in terms of the amount of information exchanged between nCDNs. We prove that the algorithms converge, and we propose a scheme to ensure ex-post individual rationality. Simulations performed on a real AS-level network topology and synthetic topologies show that the algorithms have geometric rate of convergence, and scale well with the graphs' density and the nCDN capacity.
In-band full-duplex transceiver technology for 5G mobile networks

In-band full-duplex is a promising air interface technique to tackle several of the key challenges of next generation (5G) mobile networks. Simultaneous transmission and reception in the same frequency band increases the throughput and spectral efficiency, and reduces the air interface delay. Its implementation in 5G systems, however, restrains the full-duplex transceiver design requirements. Two analog integrated circuit solutions are presented and evaluated in the frame of 5G applications. The first design is a self-interference cancelling front-end implemented in 65nm CMOS, and the second design is an electrical-balance duplexer implemented in 0. 18μm RF SOI CMOS. Both designs are attractive in the context of 5G; they allow dense integration, are configurable to support alternative and legacy standards, are compatible with conventional antenna(s), and they provide an attractive full-duplex performance for wireless communications.
ExoInterfaces: novel exosceleton haptic interfaces for virtual reality, augmented sport and rehabilitation

We developed novel haptic interfaces, FlexTorque and FlexTensor that enable realistic physical interaction with real and Virtual Environments. The idea behind FlexTorque is to reproduce human muscle structure, which allows us to perform dexterous manipulation and safe interaction with environment in daily life. FlexTorque suggests new possibilities for highly realistic, very natural physical interaction in virtual environments. There are no restrictions on the arm movement, and it is not necessary to hold a physical object during interaction with objects in virtual reality. Because the system can generate strong forces, even though it is light-weight, easily wearable, and intuitive, users experience a new level of realism as they interact with virtual environments.
NEEM: An Agent Based Meeting Augmentation System

This document introduces project Neem, its goals and directions, and its motivation. Project Neem at the University of Colorado is concerned with improving distributed multimedia meetings. A major novel aspect of this research is the use of intelligent artificial agents as full-fledged meeting participants. Goals of this interdisciplinary project include the enhancement of group interaction understanding, and the creation and testing of a prototype distributed meeting environment. Research methods include theoretical modeling, meetings analyses, prototype implementation and testing in real world environments, and meeting metrics development and application. Tools for understanding the social and organizational context of these meetings include the SYMLOG methodology applied by social agents, and the IBIS methodology applied by organizational agents. The work described herein is part of an ongoing effort within the Collaboration Technology Research Group at the University of Colorado to understand human collaboration, and to assist and enhance that collaboration via technology.
Nonverbal communication in depression

List of figures List of tables Preface 1. Introduction 2. Relating nonverbal behaviour to psychological disorders 3. Social interaction and affective state of depression 4. Longitudinal study during the course of depression - methodological aspects 5. Facial expression of mood and emotions 6. Gaze and speech 7. Gestures 8. Exemplary single cases 9. Nonverbal reaction patterns 10. Nonverbal expression of mood - general discussion and conclusions Appendixes References Index of authors Subject index.
Bromocriptine‐Desipramine Protocol in Treatment of Cocaine Addiction

Thirty‐six male cocaine abusers, in withdrawal, were studied for 99 days in a double‐blind design. Treatment with bromocriptine was significantly more effective than placebo in alleviating withdrawal symptoms. Adding desipramine to the bromocriptine regimen was significantly more effective than either placebo or bromocriptine alone. The authors hypothesize that these results support a model of dopamine depletion and receptor supersensitivity in cocaine withdrawal.
A Data Mining based Approach to Detect Attacks in Information System Filtering

information system filtering from malicious attacks has become an important issue with increasing popularity of information system filtering. Data mining is the analysis of observational data sets to find unsuspected relationships and to summarize the data novel ways that are both understandable and useful to data owners. Information systems are entirely based on the input provided by users or customers, they tend to become highly prone to attacks. To prevent such attacks several mechanisms can be used. In this paper, we show that the unsupervised clustering one of the data mining technique can be used for attack detection for all types of attacks. This method is based on computing detection attributes modeled on basic descriptive statistics. Our study showed that attribute based unsupervised clustering algorithm can detect spam users with high degree of accuracy and fewer misclassified genuine users regardless of attack strategies.
Table Header Detection and Classification

In digital libraries, a table, as a specific document component as well as a condensed way to present structured and relational data, contains rich information and often the only source of . that information. In order to explore, retrieve, and reuse that data, tables should be identified and the data extracted. Table recognition is an old field of research. However, due to the diversity of table styles, the results are still far from satisfactory, and not a single algorithm performs well on all different types of tables. In this paper, we randomly take samples from the CiteSeerX to investigate diverse table styles for automatic table extraction. We find that table headers are one of the main characteristics of complex table styles. We identify a set of features that can be used to segregate headers from tabular data and build a classifier to detect table headers. Our empirical evaluation on PDF documents shows that using a Random Forest classifier achieves an accuracy of 92%.