Miracle-dz/UniFAR-FTUs huggingface dataset:
Fatty acid composition of serum lipid fractions in type 2 diabetic patients with microalbuminuria.

OBJECTIVE To determine the fatty acid composition of serum phospholipid, triglyceride, and cholesterol ester fractions and to analyze the lipid profile of microalbuminuric type 2 diabetic patients. RESEARCH DESIGN AND METHODS A case-control study was conducted with 72 patients: 37 were normoalbuminuric (urinary albumin excretion rate [UAER] <20 microg/min), and 35 were microalbuminuric (UAER 20-200 microg/min). After 4 weeks of a standardized diet, the fatty acid composition of phospholipid, triglyceride, and cholesterol ester fractions was determined by gas chromatography. Total cholesterol and triglycerides were measured by enzymatic-colorimetric methods; cholesterol HDL by double precipitation with heparin, MnCl(2), and dextran sulfate; and apolipoprotein B by immunoturbidimetry. RESULTS Microalbuminuric patients showed a lower proportion of polyunsaturated fatty acids (24.8 +/- 11.0%), especially of the n-6 family (21.7 +/- 10.5%), in triglyceride fraction than normoalbuminuric patients (34.1 +/- 11.3%, P = 0.001 and 31.4 +/- 11.5%, P < 0.001, respectively). Patients with microalbuminuria also presented higher levels of saturated fatty acids in triglyceride fraction (43.4 +/- 18.0% vs. 34.7 +/- 13.1%, P = 0.022). In the logistic regression analysis, only the proportion of polyunsaturated fatty acids in triglyceride fraction remained significantly associated with microalbuminuria (odds ratio [OR] 0.92, 95% CI 0.85-0.98, P = 0.019). Total cholesterol, HDL cholesterol, triglyceride, and apolipoprotein B levels were similar in normo- and microalbuminuric patients. CONCLUSION Microalbuminuria in type 2 diabetic patients is associated with low polyunsaturated fatty acid contents in serum triglyceride fraction. This association may represent a risk factor for cardiovascular disease and may contribute to the progression of renal disease.
Niche-Specific Activation of the Oxidative Stress Response by the Pathogenic Fungus Candida albicans

ABSTRACT Candida albicans is a major opportunistic pathogen of humans. The pathogenicity of this fungus depends upon its ability to deal effectively with the host defenses and, in particular, the oxidative burst of phagocytic cells. We have explored the activation of the oxidative stress response in C. albicans in ex vivo infection models and during systemic infection of a mammalian host. We have generated C. albicans strains that contain specific green fluorescent protein (GFP) promoter fusions and hence act as biosensors of environmental oxidative stress at the single-cell level. Having confirmed that CTA1-, TRX1-, and TTR1/GRX2-GFP reporters respond specifically to oxidative stress, and not to heat shock, nitrosative, or osmotic stresses, we used these reporters to show that individual C. albicans cells activate an oxidative stress response following phagocytosis by neutrophils, but not by macrophages. Significantly, only a small proportion of C. albicans cells (about 4%) activated an oxidative stress response during systemic infection of the mouse kidney. The response of these cells was generally equivalent to exposure to 0.4 mM hydrogen peroxide in vitro. We conclude that most C. albicans cells are exposed to an oxidative stress when they come into contact with neutrophils in the bloodstream of the host but that oxidative killing is no longer a significant threat once an infection has been established in the kidney.
Cardiac Grafting of Engineered Heart Tissue in Syngenic Rats

BackgroundCell grafting has emerged as a novel approach to treat heart diseases refractory to conventional therapy. We hypothesize that survival and functional and electrical integration of grafts may be improved by engineering cardiac tissue constructs in vitro before grafting. Methods and ResultsEngineered heart tissue (EHT) was reconstituted by mixing cardiac myocytes from neonatal Fischer 344 rats with liquid collagen type I, matrigel, and serum-containing culture medium. EHTs were designed in circular shape (inner/outer diameter: 8/10 mm; thickness: 1 mm) to fit around the circumference of hearts from syngenic rats. After 12 days in culture and before implantation on uninjured hearts, contractile function of EHT was measured under isometric conditions. Baseline twitch tension amounted to 0.34±0.03 mN (n=33) and was stimulated by Ca2+ and isoprenaline to 200±12 and 185±10% of baseline values, respectively. Despite utilization of a syngenic model immunosuppression (mg/kg BW: azathioprine 2, cyclosporine A 5, methylprednisolone 2) was necessary for EHT survival in vivo. Echocardiography conducted 7, 14, and 28 days after implantation demonstrated no change in left ventricular function compared with pre-OP values (n=9). Fourteen days after implantation, EHTs were heavily vascularized and retained a well organized heart muscle structure as indicated by immunolabeling of actinin, connexin 43, and cadherins. Ultrastructural analysis demonstrated that implanted EHTs surpassed the degree of differentiation reached before implantation. Contractile function of EHT grafts was preserved in vivo. ConclusionsEHTs can be employed for tissue grafting approaches and might serve as graft material to repair diseased myocardium.
Ephrin B1 Is Expressed on Neuroepithelial Cells in Correlation with Neocortical Neurogenesis

To identify molecules involved in neurogenesis, we have raised monoclonal antibodies against embryonic day 12.5 mouse telencephalon. One antibody, monoclonal antibody 25H11, stains predominantly the ventricular zone of the anterior and lateral telencephalon. Purification of the 25H11 antigen, a 47 kDa integral membrane protein, from ≈2500 mouse telencephali reveals its identity with ephrin B1. Ephrin B1 appears at the onset of neocortical neurogenesis, being first expressed in neuron-generating neuroepithelial cells and rapidly thereafter in virtually all neuroepithelial cells. Expression of ephrin B1 persists through the period of neocortical neurogenesis and is downregulated thereafter. Ephrin B1 is present on the ventricular as well as basolateral plasma membrane of neuroepithelial cells and exhibits an ventricular-high to pial-low gradient across the ventricular zone. Expression of ephrin B1 is also detected on radial glial cells, extending all the way to their pial endfeet, and on neurons in the mantle/intermediate zone but not in the cortical plate. Our results suggest that ephrin B1, presumably via ephrin–Eph receptor signaling, has a role in neurogenesis. Given the ventricular-to-pial gradient of ephrin B1 on the neuroepithelial cell surface and its known role in cell migration in other systems mediated by its repulsive properties, we propose that ephrin B1 may be involved in the migration of newborn neurons out from the ventricular zone toward the neocortex.
Developing a Web-Based Advisory Expert System for Implementing Traffic Calming Strategies

Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented.
Understanding Unemployment Dynamics : The Role of Time Aggregation

This paper uses weekly data from the Survey of Income and Program Participation (SIPP) to estimate the role of time aggregation in measuring gross labor force flows and unemployment dynamics. Time aggregation is substantial: gross flows estimated from monthly data understate the true number of transitions by 15–24 percent. Time aggregation in both separations to unemployment and accessions from unemployment comoves positively with the business cycle. The effect from time aggregation on separations is roughly offset by its effect on accessions, however, creating no meaningful cyclical bias in measured gross flows or hazard rates. Contrary to claims by Hall (2006) and Shimer (2007), separation hazard rates calculated from the SIPP and the Current Population Survey are strongly countercyclical and remain so after adjusting for time aggregation. In addition, the separation hazard rate contributes fully one-half of the cyclical variance of the steady-state unemployment rate after adjusting for time aggregation. JEL codes: J63, J64, E32, C22, C42
Serious Games Integration in Companies: A Research and Application Framework

Serious Games are games that educate, train and inform using entertainment principles. Serious Games have the potential for application in companies. However, less investigation has been focused on how to integrate Serious Games in to companies. The authors have developed a classification framework to help understand the different ways serious games can be used in companies. In order to achieve this aim, cases of serious games were identified from experts, conferences, events, developer companies and the Gala Network. These cases were reviewed to identify serious games relevant to business and management. From these, cases were collected of serious games application/use in companies. These were then classified according to the types of use in the classification framework. The identified ways serious games can be used in companies were: in corporate training, for change management, through viral diffusion and Gamification. A case study of each type of use is presented in the paper. Finally, future work towards the refinement of the framework that can add to theory building for research in the use and integration of serious games in companies is discussed.
EARLY HEART DISEASE PREDICTION USING DATA MINING TECHNIQUES

The successful application of data mining in highly visible fields like e-business, marketing and retail has led to its application in other industries and sectors. Among these sectors just discovering is healthcare. The Healthcare industry is generally “information rich”, but unfortunately not all the data are mined which is required for discovering hidden patterns & effective decision making . Discovery of hidden patterns and relationships often goes unexploited. Advanced data mining modeling techniques can help remedy this situation. This research paper intends to use data mining Classification Modeling Techniques, namely, Decision Trees, Naive Bayes and Neural Network, along with weighted association Apriori algorithm and MAFIA algorithm in Heart Disease Prediction. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting heart disease.
Bayesian Model Selection Methods for Mutual and Symmetric $k$-Nearest Neighbor Classification

The $k$-nearest neighbor classification method ($k$-NNC) is one of the simplest nonparametric classification methods. The mutual $k$-NN classification method (M$k$NNC) is a variant of $k$-NNC based on mutual neighborship. We propose another variant of $k$-NNC, the symmetric $k$-NN classification method (S$k$NNC) based on both mutual neighborship and one-sided neighborship. The performance of M$k$NNC and S$k$NNC depends on the parameter $k$ as the one of $k$-NNC does. We propose the ways how M$k$NN and S$k$NN classification can be performed based on Bayesian mutual and symmetric $k$-NN regression methods with the selection schemes for the parameter $k$. Bayesian mutual and symmetric $k$-NN regression methods are based on Gaussian process models, and it turns out that they can do M$k$NN and S$k$NN classification with new encodings of target values (class labels). The simulation results show that the proposed methods are better than or comparable to $k$-NNC, M$k$NNC and S$k$NNC with the parameter $k$ selected by the leave-one-out cross validation method not only for an artificial data set but also for real world data sets.
An Experimental Study of the Influence of Limited Time Horizon on Positivity Effects among Young Adults Using Eye-Tracking

Compared to younger adults, older adults attend more to positive stimuli, a positivity effect. Older adults have limited time horizons, and they focus on maintaining positive affect, whereas younger adults have unlimited time horizons, and they focus on acquiring knowledge and developing skills. Time horizons were manipulated by asking participants (66 young adults, M age = 20.5 yr., SD = 1.2) to think that their lives would end in three years. Some participants focused on what they would do in these three years (life focus), whereas others focused on the fact that they would die in three years (death focus). Attentional biases to facial expressions of happiness, sadness, fear, anger, and disgust were measured. Participants viewed 20 slides including pairings of a happy face with each of the negative emotions. The dependent measure was the relative attention paid to the faces on each slide. Participants in the experimental conditions exhibited a positivity effect compared to participants in the control condition, although some results suggested that this effect was weaker in the death focus condition than in the life focus condition.
Real time trajectory based hand gesture recognition

The recognition of hand gestures from image sequences is an important and challenging problem. This paper presents a robust solution to track and recognize a list of hand gestures from their trajectory. The main tools of the proposed solution are robust kernel density estimation and the related mean shift algorithm, used in both video tracking and trajectory segmentation. The gesture definition is based on strokes in order to allow the use of a low complexity gesture recognition method. The gesture recognition process is trivial, being reduced to a syntactic analysis of the feature vector avoiding the necessity of complex classification methods based on curve matching. Despite the restrictions derived from the stroke based definition of gestures, the low computational complexity of the algorithm allows its implementation on low-cost processing systems.
Removing dynamic 3D objects from point clouds of a moving RGB-D camera

Most state-of-the-art visual simultaneous localization and mapping (SLAM) systems are designed for applications in static environments. However, during a SLAM process, dynamic objects in the field-of-view of the camera will affect the accuracy of visual odometry and loop-closure detection. In this paper, we present a solution to removing dynamic objects from RGB images and their corresponding depth images when a RGB-D camera is mounted on a mobile robot for visual SLAM. We transform two selected successive images to the same image coordinate frame through feature matching. Then we detect candidate image pixels of dynamic objects by applying a threshold to the image difference between the two images. Furthermore, we utilize depth information of the candidate pixels to decide whether true dynamic objects are found. Finally, in order to extract a complete 3-dimensional (3D) dynamic object, we find the correspondence between the object and a cluster of the point cloud computed from RGB-D images. To evaluate the performance of detecting and removing dynamic objects, we do experiments in various indoor scenarios, which demonstrate the efficiency of the proposed algorithm.
Designing Special Post-Processing Rules for SVM-Based Chinese Word Segmentation

We participated in the Third International Chinese Word Segmentation Bakeoff. Specifically, we evaluated our Chinese word segmenter NEUCipSeg in the close track, on all four corpora, namely Academis Sinica (AS), City University of Hong Kong (CITYU), Microsoft Research (MSRA), and University of Pennsylvania/University of Colorado (UPENN). Based on Support Vector Machines (SVMs), a basic segmenter is designed regarding Chinese word segmentation as a problem of character-based tagging. Moreover, we proposed postprocessing rules specially taking into account the properties of results brought out by the basic segmenter. Our system achieved good ranks in all four corpora.
STRUCTURE, ACTION, AND OUTCOMES: THE DYNAMICS OF POWER IN SOCIAL EXCHANGE*

Two levels of power - the structure of power in exchange networks, and the strategic use of power resources by actors - affect the frequency and distribution of exchange outcomes. Theories of power and exchange suggest alternative hypotheses about how structural power and strategic action are related to each other and to outcomes. These are tested with data from a series of experiments in which power relations are based on control over rewards and punishments. Both structural power and its strategic use have substantial effects on exchange outcomes, but structure and action are related only weakly to each other. Their relative effects on exchange outcomes vary with the base of power. Structural power has stronger effects on reward exchange, and strategic action on punishment exchange. The asymmetry of reward exchange in the relation, the traditional measure of power use in powerldependence theory, is affected by both. Social scientists have conceptualized power in various ways: as a structural potential (Bierstedt 1950; Wrong 1968; Emerson 1962), as a process of behavioral or tactical influence (Rubin and Brown 1975; Michener and Suchner 1972; Tedeschi and Bonoma 1972), and as the successful outcome of influence (Dahl 1957; Mayhew, Gray, and Richardson 1969; Simon 1957). I argue that a complete analysis of power must include all three facets. Understanding the relations among them requires integrating concepts at "micro" and "macro" levels of analysis (Alexander 1987; Munch and Smelser 1987). The "macro" level of power is the structure of control that provides the opportunities and constraints within which the "micro" level of power, the strategic behavior of actors, operates. Together, structure and action produce outcomes of consequence for actors and relationships. I investigate how structure and action affect the amount and distribution of exchange in power/dependence relations. Previous research on power and exchange has studied only the relations between power structure (the struc* This work was supported by a grant from the National Science Foundation (SES-84 19872). I am
Examining the effects of frustration on working memory capacity

Attention-Deficit/Hyperactivity Disorder (ADHD) is associated with numerous pejorative outcomes in adults such as low frustration tolerance and deficits in central executive functioning. The present study aims to examine (1) the effect of induced frustration on working memory capacity (WMC) and (2) the unique contribution of ADHD symptoms and other commonly comorbid disorders (i.e., anxiety/depression and alcohol use) to frustration. Participants (N=66) were randomly assigned to either the control group (n=32) or the experimental group (n=34). The Frustration Induction Procedure (FIP) was administered to participants in the experimental group and a neutral, non-frustrating task was administered to a control group. A factor-analytic framework was utilized to assess WMC based on performance on three computerized tasks. WMC and baseline frustration levels were assessed both prior to and after inducing frustration. Participants provided four subjective ratings of frustration and blood pressure was assessed at four time points to assess changes in baseline frustration ratings and blood pressure. Results suggest that we were able to systematically induce subjective frustration for participants in the experimental group relative to the control group. WMC, however, was not associated with induced frustration in the present study, highlighting a need to examine the extent to which additional working memory-related performance variables (i.e., reaction time, latency to first response) are related to frustration. Finally, results indicate that ADHD symptoms, rather than anxiety/depression symptoms and hazardous drinking behavior, predict baseline frustration
Modelling a hormone-inspired controller for individual- and multi-modular robotic systems

For all living organisms, the ability to regulate internal homeostasis is a crucial feature. This ability to control variables around a set point is found frequently in the physiological networks of single cells and of higher organisms. Also, nutrient allocation and task selection in social insect colonies can be interpreted as homeostatic processes of a super-organism. And finally, behaviour can also represent such a control scheme. We show how a simple model of hormone regulation, inspired by simple biological organisms, can be used as a novel method to control the behaviour of autonomous robots. We demonstrate the formulation of such an artificial homeostatic hormone system (AHHS) by a set of linked difference equations and explain how the homeostatic control of behaviour is achieved by homeostatic control of the internal ‘hormonal’ state of the robot. The first task that we used to check the quality of our AHHS controllers was a very simple one, which is often a core functionality in controller programmes that are used in autonomous robots: obstacle avoidance. We demonstrate two implementations of such an AHHS controller that performs this task in differing levels of quality. Both controllers use the concept of homeostatic control of internal variables (hormones) and they extend this concept to also include the outside world of the robots into the controlling feedback loops: As they try to regulate internal hormone levels, they are forced to keep a homeostatic control of sensor values in a way that the desired goal ‘obstacle avoidance’ is achieved. Thus, the created behaviour is also a manifestation of the acts of homeostatic control. The controllers were evaluated using a stock-and-flow model that allowed sensitivity analysis and stability tests. Afterwards, we have also tested both controllers in a multi-agent simulation tool, which allowed us to predict the robots' behaviours in various habitats and group sizes. Finally, we demonstrate how this novel AHHS controller is suitable to control a multi-cellular robotic organism in an evolutionary robotics approach, which is used for self-programming in a gait-learning task. These examples shown in this article represent the first step in our research towards autonomous aggregation and coordination of robots to higher-level modular robotic organisms that consist of several joined autonomous robotic units. Finally, we plan to achieve such aggregation patterns and to control complex-shaped robotic organisms using AHHS controllers, as they are described here.
An SDR-based Experimental Setup for OFDM-based Radar

—We present a software radio-based testbed for live testing of OFDM radar algorithms. Unlike previous testing setups, the hardware used (Universal Software Radio Peripherals) was low-cost and low-power, thus making the measurement setup both ﬂexible and easy to use. The hardware can be easily battery powered. Both stationary and mobile measurements in realistic scenarios were performed.