Gastroesophageal reflux and pulmonary fibrosis in scleroderma: a study using pH-impedance monitoring

RATIONALE: Interstitial lung disease (ILD) in patients with systemic sclerosis (SSc) is associated with increased morbidity and mortality. Gastroesophageal reflux (GER) is considered a contributing factor in the pathogenesis of ILD. OBJECTIVES: To characterize GER (acid and nonacid) in patients with SSc with and without ILD. METHODS: Patients with SSc underwent pulmonary high-resolution computer tomography (HRCT) scan and 24-hour impedance-pH monitoring off-proton pump inhibitor therapy. The presence of pulmonary fibrosis was assessed using validated HRCT-scores. Reflux monitoring parameters included number of acid and nonacid reflux episodes, proximal migration of the refluxate, and distal esophageal acid exposure. Unless otherwise specified, data are presented as median (25th-75th percentile). MEASUREMENTS AND MAIN RESULTS: Forty consecutive patients with SSc (35 female; mean age, 53 yr; range, 24-71; 15 patients with diffuse and 25 with limited SSc) were investigated; 18 (45%) patients with SSc had pulmonary fibrosis (HRCT score >or= 7). Patients with SSc with ILD had higher (P < 0.01) esophageal acid exposure (10.3 [7.5-15] vs. 5.2 [1.5-11]), higher (P < 0.01) number of acid (41 [31-58] vs. 19 [10-23]) and nonacid (25 [20-35] vs. 17 [11-19]) reflux episodes, and higher (P < 0.01) number of reflux episodes reaching the proximal esophagus (42.5 [31-54] vs. 15 [8-22]) compared with patients with SSc with normal HRCT scores. Pulmonary fibrosis scores (HRCT score) correlated well with the number of reflux episodes in the distal (r(2) = 0.637) and proximal (r(2) = 0.644) esophagus. CONCLUSIONS: Patients with SSc with ILD have more severe reflux (i.e., more reflux episodes and more reflux reaching the proximal esophagus). Whether or not the development of ILD in patients with SSc can be prevented by reflux-reducing treatments needs to be investigated.

Lag Camera: A Moving Multi-Camera Array for Scene-Acquisition

Many applications, such as telepresence, virtual reality, and interactive walkthroughs, require a three-dimensional(3D)model of real-world environments. Methods, such as lightfields, geometric reconstruction and computer vision use cameras to acquire visual samples of the environment and construct a model. Unfortunately, obtaining models of real-world locations is a challenging task. In particular, important environments are often actively in use, containing moving objects, such as people entering and leaving the scene. The methods previously listed have difficulty in capturing the color and structure of the environment while in the presence of moving and temporary occluders. We describe a class of cameras called lag cameras. The main concept is to generalize a camera to take samples over space and time. Such a camera, can easily and interactively detect moving objects while continuously moving through the environment. Moreover, since both the lag camera and occluder are moving, the scene behind the occluder is captured by the lag camera even from viewpoints where the occluder lies in between the lag camera and the hidden scene. We demonstrate an implementation of a lag camera, complete with analysis and captured environments.

Spare Time Activity Sheets from Photo Albums

Given arbitrary pictures, we explore the possibility of using new techniques from computer vision and artificial intelligence to create customized visual games on-the-fly. This includes coloring books, link-the-dot and spot-the-difference popular games. The feasibility of these systems is discussed and we describe prototype implementation that work well in practice in an automatic or semi-automatic way.

Method of collaborative detection of autonomous transport vehicles based on laser rangefinder data

To master changing performance demands, autonomous transport vehicles are deployed to make inhouse material flow applications more flexible. The socalled cellular transport system consists of a multitude of small scale transport vehicles which shall be able to form a swarm. Therefore the vehicles need to detect each other, exchange information amongst each other and sense their environment. By provision of peripherally acquired information of other transport entities, more convenient decisions can be made in terms of navigation and collision avoidance. This paper is a contribution to collective utilization of sensor data in the swarm of cellular transport vehicles.

The influence of yield surface shape and damage in the depth-dependent response of bone tissue to nanoindentation using spherical and Berkovich indenters

Prevention and treatment of osteoporosis rely on understanding of the micromechanical behaviour of bone and its influence on fracture toughness and cell-mediated adaptation processes. Postyield properties may be assessed by nonlinear finite element simulations of nanoindentation using elastoplastic and damage models. This computational study aims at determining the influence of yield surface shape and damage on the depth-dependent response of bone to nanoindentation using spherical and conical tips. Yield surface shape and damage were shown to have a major impact on the indentation curves. Their influence on indentation modulus, hardness, their ratio as well as the elastic-to-total work ratio is well described by multilinear regressions for both tip shapes. For conical tips, indentation depth was not statistically significant (p<0.0001). For spherical tips, damage was not a significant parameter (p<0.0001). The gained knowledge can be used for developing an inverse method for identification of postelastic properties of bone from nanoindentation.

Embedding of human vertebral bodies leads to higher ultimate load and altered damage localisation under axial compression

Computer tomography (CT)-based finite element (FE) models of vertebral bodies assess fracture load in vitro better than dual energy X-ray absorptiometry, but boundary conditions affect stress distribution under the endplates that may influence ultimate load and damage localisation under post-yield strains. Therefore, HRpQCT-based homogenised FE models of 12 vertebral bodies were subjected to axial compression with two distinct boundary conditions: embedding in polymethylmethalcrylate (PMMA) and bonding to a healthy intervertebral disc (IVD) with distinct hyperelastic properties for nucleus and annulus. Bone volume fraction and fabric assessed from HRpQCT data were used to determine the elastic, plastic and damage behaviour of bone. Ultimate forces obtained with PMMA were 22% higher than with IVD but correlated highly (R2 = 0.99). At ultimate force, distinct fractions of damage were computed in the endplates (PMMA: 6%, IVD: 70%), cortex and trabecular sub-regions, which confirms previous observations that in contrast to PMMA embedding, failure initiated underneath the nuclei in healthy IVDs. In conclusion, axial loading of vertebral bodies via PMMA embedding versus healthy IVD overestimates ultimate load and leads to distinct damage localisation and failure pattern.

Prometheus Framework for Fuzzy Information Retrieval in Semantic Spaces

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data (such as location data, ontology-backed search queries, in- and outdoor conditions) the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

Understanding virtual experience and telepresence - a review and synthesis of literature

To enable buyers to be better informed before purchasing, products and services can be virtually experienced on the internet. Research into virtual experience (VE) and the related construct of telepresence (TP) as means of online marketing has made great progress in recent years. However, there is still disagreement in the literature concerning the exact understanding of these terms. In this study, the two terms are analyzed by means of a systematically executed literature review, differentiated from one another, and their understandings explained. This study is to our knowledge the first to compare the concepts of VE and TP in a systematic way. The analysis shows that TP is regarded as the feeling of presence conveyed by a communication medium. VE, on the other hand, is to be defined as an active state of a consumer through the use of computer-based presentation formats, and constituting a subtype of TP. These findings are intended to help VE and TP become more uniformly understood and make it easier to compare the results of future studies. Finally, from the literature review, it is possible to derive focal points for research in future studies.

Aggression, impulsivity and serotonin in drug dependence

Aggression, impulsivity, and central serotonergic function were evaluated in two groups of human volunteers; one group having a history of substance dependence (DRUG+) and another group with no drug use history (DRUG$-$). The hypothesis was that DRUG+ subjects would be more aggressive, more impulsive, and have attenuated serotonergic function. Results showed that DRUG+ subjects behaved more aggressively in a computer paradigm of aggression and also reported more aggression on questionnaires than DRUG$-$ subjects. In a computer paradigm of impulsivity, the DRUG+ group showed a lesser ability to delay gratification than the DRUG$-$ group in the last session of testing. The DRUG+ subjects also reported more venturesomeness and problems associated with low impulse control on questionnaires. Serotonergic function was measured through the neuroendocrine and hypothermic response to an orally administered serotonin (5-HT) agonist specific to the 5-HT$\rm\sb{1A}$ receptor subtype (ipsapirone). The neuroendocrine responses did not differ between DRUG$\pm$ groups, indicating no difference in the sensitivity of the presynaptic or postsynaptic 5-HT$\rm\sb{1A}$ receptors. An unexpected result was that the indicator hormone, cortisol, was at a lower baseline level in the DRUG+ group than the DRUG$-$ group. Lowered cortisol levels have been previously noted in children at high risk foul antisociality and future drug use. A principal components analysis including impulsivity, aggression, and serotonergic function measures produced three unique factors. The factors, Antisocial Tendency and Self-Control and Serotonergic Function combined to produce a significant regression equation explaining 36% of variability in the DRUG$\pm$ groups. These factors included measures of aggression, impulsivity, mood, and educational attainment. These results suggest that the current measures of aggression and impulsivity were predictive of a drug dependence disorder but that neuroendocrine function is not yet a useful indicator of drug dependence status. ^