Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationsh ip of the Process of Primary Care to Health Outcomes Primary Care Practice Coordination Versus Physician Continuity

The 1978 US Institute of Medicine report codif ied the four essentials of good primary care to include accessibility, comprehensiveness, coordination, and continuity. The most recent Institute of Medicine primary care report in 1994 continued to stress the importance of continuity while extending the definition beyond an individual physician’s care. I t is presumed that less continuous care might lead to less information communicated, duplication of services, and worse patient outcomes. Continuity has long been recognized as valuable to medical care, yet empirical evidence has not consistently supported the contention that higher continuity leads to better patient outcomes. Previous research, summarized in Table 1, has not simultaneously assessed relationships between physician continuity and technical quality of care, patient satisfaction, and cost. Nor has physician continuity been compared to other integrative practices that might improve coordination in health care systems and lead to better patient outcomes. The study presented here determined (1) whether physician continuity is associated with better patient outcomes and (2) whether practice structures are associated with better patient outcomes, independent of the level of physician continuity. Our outcomes are derived from those currently measured by all health plans seeking accreditation under National Committee on Quality Assurance standards.
Poster Abstract: An Efficient Authentication Model in Smart Grid Networks

A smart grid is envisioned as a promising platform for the next-generation power supply network, where the electricity is generated based on the demand from the consumers energy-use information. However, the security and privacy issues over insecure wireless communications are still big obstacles in the success of smart grid networks. In this paper, we present an efficient authentication model in smart grid networks. The proposed model justifies its feasibility with an early test-bed using off-the-shelf 802.15. 4 low- cost sensors. Moreover, this poster reports preliminary performance evaluation results, and shows that the proposed scheme is effective and efficient than the prior works.
The awareness of chest physicians about nutritional assessment in chronic obstructive pulmonary disease.

INTRODUCTION The number of studies that target nonpharmacologic treatments for chronic obstructive pulmonary disease (COPD) are increasing because no existing pharmacologic treatment modality for COPD leads to significant improvement in lung function.Positive effects can be observed in patients with COPD using nutritional support alone or as an adjunct to exercise. In this study, we aimed to evaluate the awareness of chest physicians about the nutritional state of patients with COPD. MATERIALS AND METHODS A questionnaire consisting of 15 multiple choice questions was conducted to 121 chest physicians. The questions were formed to evaluate the awareness of chest physicians on the patients' nutritional state and the importance of nutrition in COPD follow-up. RESULT In total, of the 121 physicians, only 3 (2.5%) reported undertaking routine assessment for nutritional state of patients with COPD. The rates of physicians who routinely questioned patients about weight loss and loss of appetite were 56.2% (n= 68) and 51.2% (n= 62), respectively. Forty-five (37.2%) physicians said that they usually started nutritional support if they detected weight loss in patients with COPD. CONCLUSION Although there is limited data on the benefits of nutritional supplementation for patients with COPD, some studies have suggested advantages of nutritional support against the progress of COPD. Our study showed that routine screening for malnutrition in patients with COPD is rare among chest physicians and this did not differ according to the hospitals in which they worked or from where they took their residency training. There is a need for further studies emphasizing the importance of nutritional state in the progress of COPD.
Vessel Labeling in Combined Confocal Scanning Laser Ophthalmoscopy and Optical Coherence Tomography Images: Criteria for Blood Vessel Discrimination

Introduction The diagnostic potential of optical coherence tomography (OCT) in neurological diseases is intensively discussed. Besides the sectional view of the retina, modern OCT scanners produce a simultaneous top-view confocal scanning laser ophthalmoscopy (cSLO) image including the option to evaluate retinal vessels. A correct discrimination between arteries and veins (labeling) is vital for detecting vascular differences between healthy subjects and patients. Up to now, criteria for labeling (cSLO) images generated by OCT scanners do not exist. Objective This study reviewed labeling criteria originally developed for color fundus photography (CFP) images. Methods The criteria were modified to reflect the cSLO technique, followed by development of a protocol for labeling blood vessels. These criteria were based on main aspects such as central light reflex, brightness, and vessel thickness, as well as on some additional criteria such as vascular crossing patterns and the context of the vessel tree. Results and Conclusion They demonstrated excellent inter-rater agreement and validity, which seems to indicate that labeling of images might no longer require more than one rater. This algorithm extends the diagnostic possibilities offered by OCT investigations.
MCC: A runtime verification tool for MCAPI user applications

We present a dynamic verification tool MCC for Multicore Communication API applications — a new API for communication among cores. MCC systematically explores all relevant interleavings of an MCAPI application using a tailor-made dynamic partial order reduction algorithm (DPOR). Our contributions are (i) a way to model the non-overtaking message matching relation underlying MCAPI calls with a high level algorithm to effect DPOR for MCAPI that controls the lower level details so that the intended executions happen at runtime; and (ii) a list of default safety properties that can be utilized in the process of verification. To our knowledge, this is the first push button model checker for MCAPI application writers that, at present, deals with an interesting subset of MCAPI calls. Our result is the demonstration that we can indeed develop a dynamic model checker for MCAPI that can directly control the non-deterministic behavior at runtime that is inherent in any implementation of the library without additional API modifications or additions.
Open and Closed World Assumptions in Data Exchange

Data exchange is the problem of finding an instance of a target schema, given an instance of a source schema and a specification of a mapping between the source and the target schemas, and answering queries over target instances. A schema mapping is a condition, often expressed in a fragment of first-order logic, that relates instances of source and target schemas. Most commonly it is a conjunction of sentences of the form
Hazardous drinking, depression, and anxiety among sexual-minority women: self-medication or impaired functioning?

OBJECTIVE Sexual-minority women are at heightened risk for a number of mental health problems, including hazardous alcohol consumption, depression, and anxiety. We examined self-medication and impaired-functioning models of the associations among these variables and interpreted results within a life course framework that considered the unique social stressors experienced by sexual-minority women. METHOD Data were from a sample of 384 women interviewed during the first two waves of the Chicago Health and Life Experiences of Women (CHLEW) study. RESULTS Covariance structure modeling revealed that (a) consistent with a self-medication process, anxiety was prospectively associated with hazardous drinking and (b) consistent with an impaired-functioning process, hazardous drinking was prospectively associated with depression. CONCLUSIONS Our findings support a life course perspective that interprets the mental health of adult sexual-minority women as influenced by adverse childhood experiences, age at drinking onset, first heterosexual intercourse, and first sexual identity disclosure, as well as by processes associated with self-medication and impaired functioning during adulthood.
Energy-distortion tradeoff with multiple sources and feedback

The energy-distortion tradeoff for lossy transmission of sources over multi-user networks is studied. The energy-distortion function E(D) is defined as the minimum energy required to transmit a source to the receiver within the target distortion D, when there is no restriction on the number of channel uses per source sample. For point-to-point channels, E(D) is shown to be equal to the product of the minimum energy per bit Ebmin and the rate-distortion function R(D), indicating the optimality of source-channel separation in this setting. It is shown that the optimal E(D) can also be achieved by the Schalkwijk-Kailath (SK) scheme, as well as separate coding, in the presence of perfect channel output feedback. Then, it is shown that the optimality of separation in terms of E(D) does not extend to multi-user networks. The scenario with two encoders observing correlated Gaussian sources in which the encoders communicate to the receiver over a Gaussian multiple-access channel (MAC) with perfect channel output feedback is studied. First a lower bound on E(D) is provided and compared against two upper bounds achievable by separation and an uncoded SK type scheme, respectively. Even though neither of these achievable schemes meets the lower bound in general, it is shown that their energy requirements lie within a constant gap of E(D) in the low distortion regime, for which the energy requirement grows unbounded. It is shown that the SK based scheme outperforms the separation based scheme in certain scenarios, which establishes the sub-optimality of separation in this multi-user setting.
An Analytical Evaluation of Network Security Modelling Techniques Applied to Manage Threats

The current ubiquity of information coupled with the reliance on such data by businesses has led to a great deal of resources being deployed to ensure the security of this information. Threats can come from a number of sources and the dangers from those insiders closest to the source have increased significantly recently. This paper focuses on techniques used to identify and manage threats as well as the measures that every organisation should consider to put into action. A novel game-based onion skin model has been proposed, combining techniques used in theory-based and hardware-based hardening strategies.
Effect of Pulse Energy on the Optical Properties of ZnS Thin Films Prepared Using Pulse Laser Technique

In these work four samples of ZnS thin films deposited on glass substrate using pulse laser deposition method with different pulse energies, the effect of the laser pulse energy on the optical properties of the four ZnS thin films fabricated was studied. Q-Switched Nd: YAG laser with the fundamental wavelength 1064 nm, laser Pulse energies of (125, 150, 175, and 200) mj with fixed number of pulses of 20, and pulse repetition rate of 5 Hz were used. The target to the substrate distance and angle were kept fixed. The film thicknesses were measured using FESEM measurement tool. The thickness of the deposited ZnS thin films was found to be linearly dependent on the pulse energy used. The transmission spectra in the tested region (532 to 915) nm were found to be in the range from 0.41 to 0.59% depending on the ZnS thin film thickness, and for each ZnS thin film the transmission spectrum is unique. The refractive indices of all samples were determined; and for each sample and it were found to change with wavelength, the highest refractive index of 5.6 at 915 nm was obtained for the sample of the smallest thickness 0.49 microns. Transmission spectra, absorption coefficients and the refractive indices they were in good agreement with the literature.
Learning from Demonstration for Shaping through Inverse Reinforcement Learning

Model-free episodic reinforcement learning problems define the environment reward with functions that often provide only sparse information throughout the task. Consequently, agents are not given enough feedback about the fitness of their actions until the task ends with success or failure. Previous work addresses this problem with reward shaping. In this paper we introduce a novel approach to improve model-free reinforcement learning agents' performance with a three step approach. Specifically, we collect demonstration data, use the data to recover a linear function using inverse reinforcement learning and we use the recovered function for potential-based reward shaping. Our approach is model-free and scalable to high dimensional domains. To show the scalability of our approach we present two sets of experiments in a two dimensional Maze domain, and the 27 dimensional Mario AI domain. We compare the performance of our algorithm to previously introduced reinforcement learning from demonstration algorithms. Our experiments show that our approach outperforms the state-of-the-art in cumulative reward, learning rate and asymptotic performance.
Intracellular cystine loading inhibits transport in the rabbit proximal convoluted tubule.

Cystinosis is an autosomal recessive disorder characterized by a high intracellular cystine concentration. To establish an in vitro model of this disorder and examine the mechanism of the proximal tubule transport defect seen with elevated intracellular cystine concentrations, rabbit proximal convoluted tubules (PCT) were perfused in vitro. PCTs were loaded with cystine using cystine dimethyl ester, a permeative methyl ester derivative. Bath cystine dimethyl ester (0.5 mM) reduced volume absorption (Jv) (0.67 +/- 0.07 to 0.15 +/- 0.09 nl/mm.min, P less than 0.01), bicarbonate transport (JTCO2) (47.2 +/- 4.9 to 11.1 +/- 2.8 pmol/mm.min, P less than 0.001) and glucose transport (JGLU) (34.1 +/- 1.5 to 19.7 +/- 1.5 pmol/mm.min, P less than 0.001). The methyl esters of leucine (0.5 mM), and tryptophan (0.5 and 2.0 mM) had no effect on these parameters. To examine if intracellular reduction of cystine to cysteine could contribute to the inhibition in transport, the effect of bath cysteine methyl ester on proximal tubular transport was examined. Bath cysteine methyl ester (2 but not 0.5 mM) resulted in an inhibition in Jv, JGLU, and JTCO2. Cystine dimethyl ester had no effect on mannitol or bicarbonate permeability. These data are consistent with intracellular proximal tubular cystine accumulation resulting in an inhibition of active transport.
Marginal likelihood for parallel series

Suppose that k series, all having the same autocorrelation function, are observed in parallel at points in time or space. From a single series of moderate length, the autocorrelation parameter ? can be estimated with limited accuracy, so we aim to increase the information by formulating a suitable model for the joint distribution of all series. Three Gaussian models of increasing complexity are considered, two of which assume that the series are independent. This paper studies the rate at which the information for ? accu mulates as k increases, possibly even beyond n. The profile log likelihood for the model with k(k + l)/2 covariance parameters behaves anomalously in two respects. On the one hand, it is a log likelihood, so the derivatives satisfy the Bartlett identities. On the other hand, the Fisher information for ? increases to a max imum at k = n/2, decreasing to zero for k > n. In any parametric statistical model, one expects the Fisher information to increase with additional data; decreasing Fisher information is an anomaly demanding an explanation.
Cardiogenic oscillation phase relationships during single-breath tests performed in microgravity.

We studied the phase relationships of the cardiogenic oscillations in the phase III portion of single-breath washouts (SBW) in normal gravity (1 G) and in sustained microgravity (microG). The SBW consisted of a vital capacity inspiration of 5% He-1.25% sulfurhexafluoride-balance O2, preceded at residual volume by a 150-ml Ar bolus. Pairs of gas signals, all of which still showed cardiogenic oscillations, were cross-correlated, and their phase difference was expressed as an angle. Phase relationships between inspired gases (e.g., He) and resident gas (n2) showed no change from 1 G (211 +/- 9 degrees) to microG (163 +/- 7 degrees). Ar bolus and He were unaltered between 1 G (173 +/- 15 degrees) and microG (211 +/- 25 degrees), showing that airway closure in microG remains in regions of high specific ventilation and suggesting that airway closure results from lung regions reaching low regional volume near residual volume. In contrast, CO2 reversed phase with He between 1 G (332 +/- 6 degrees) and microG (263 +/- 27 degrees), strongly suggesting that, in microG, areas of high ventilation are associated with high ventilation-perfusion ratio (VA/Q). This widening of the range of VA/Q in microG may explain previous measurements (G.K. Prisk, A.R. Elliott, H.J.B. Guy, J.M. Kosonen, and J.B. West J. Appl. Physiol. 79: 1290-1298, 1995) of an overall unaltered range of VA/Q in microG, despite more homogeneous distributions of both ventilation and perfusion.
Operation of TEAM I in a User Environment at NCEM

Abstract TEAM I is the final product of the Transmission Electron Aberration-corrected Microscope (TEAM) Project, a collaborative project funded by the Department of Energy with the goal of designing and building a platform for a next generation aberration-corrected electron microscope capable of image resolution of up to 50 pm. The TEAM instrument incorporates a number of new technologies, including spherical- and chromatic-aberration correction, an all-piezo-electric sample stage and an active-pixel direct electron detector. This article describes the functionality of this advanced instrumentation, its response to changes in environment or operating conditions, and its stability during daily operation within the National Center for Electron Microscopy user facility.
EEG-based affect states classification using Deep Belief Networks

Affective states classification has become an important part of the Brain-Computer Interface (HCI) study. In recent years, affective computing systems using physiological signals, such as ECG, GSR and EEG has shown very promising results. However, like many other machine learning studies involving physiological signals, the bottle neck is always around the database acquisition and the annotation process. To investigate potential ways to address this small sample problem, this paper introduces a Deep Belief Networks (DBN) based learning system for the EEG-based affective processing system. Through the greedy-layer pretraining using unlabeled data as well as a supervised fine-tuning process, the DBN-based approaches significantly reduced the number of labeled samples required. The DBN methods also acted as an application specific feature selector, by examining the weight vector between the input feature vector and the first invisible layer, we can gain much needed insights on the spatial or spectral locations of the most discriminating features. In this study, DBNs are trained on the narrow-band spectral features extracted from multichannel EEG recordings. To evaluate the efficacy of the proposed DBN-based learning system, we carried out an subject-independent affective states classification experiments on the DEAP database to classify 2-dimensional affect states. As a baseline to the proposed DBN approach, the same classification problem was also carried out using support vector machines (SVMs) and one-way ANOVA based feature selection process. The classification results shown that the proposed framework using Deep Belief Networks not only provided better classification performance, but also significantly lower the number of labeled data required to train such machine learning systems.
Interactivity-loss avoidance in event delivery synchronization for mirrored game architectures

Since the expansion of their market and their challenging requirements, massively multiplayer online games are gaining increasing attention in the scientific community. One of the key factors in this kind of application is represented by the ability to rapidly deliver game events among the various players over the network. Employing in this context mirrored game server architectures and adapting RED (random early detection) techniques borrowed from network queuing management, we are able to show sensible benefits in upholding interactivity and scalability, whilst preserving game state consistency and game evolution fluency at the player's side
Analysis of Intervehicle Communication to Reduce Road Crashes

The aim of this paper is to study the contribution of intervehicle communication (IVC) to reduce the number of secondary collisions caused by an accident. We assess the impact of broadcast protocols used to disseminate warning messages and the impact of IVC penetration ratio on the number of collisions. There are two main contributions in this paper. First, it addresses the analytical evaluation of broadcast protocols in Vehicular Ad hoc NETworks (VANETs). We propose a general framework based on point processes to evaluate the performance of this protocol. Our approach is based on the theory of point processes and Palm calculus. We derive, for a generic frame error rate (FER) function, simple formulas for computing the delay required to propagate messages. These formulas hold for any FER function, enabling the comparison of broadcast performance under different radio propagation environments. In the second part of this paper, we propose an analytical evaluation of the number of vehicles involved in a collision. This analysis allows us to study the impact of radio technology penetration ratio and the impact of safety message delivery delays on the number of collisions.
Searching over Secured Cloud by Preserving Privacy:SSPP

Cloud Computing has a great role in providing many flexible services to the users. The complexity in the data management is solved by outsourcing the relevant and sensitive data to the cloud. As privacy protection is a main concern in cloud storage, it can be maintained by keeping them encrypted. The sensitive documents are kept encrypted by using the symmetric key encryption. Earlier the works on searchable encryption was focusing on the single-keyword and the Boolean search. Later the multiple keywords are allowed to include in the search query. The search result obtained on considering each query which is included in the request. The relevance of the requested query keyword on the documents is evaluated by the similarity measure, co-ordinate matching. The synonyms of the requested queries are considered to increase the efficiency of the retrieval process. The co-occurrence probability of the keyword is taken in account for the sematic relationship. On analyzing the real world experiments the computational cost for the retrieval process over the secured data is reduced.