Miracle-dz/UniFAR-FTUs huggingface dataset:
Coronary endothelial dysfunction as a predictor of intimal thickening in the long term after heart transplantation.

OBJECTIVES The mechanisms of cardiac allograft vasculopathy and its predisposing factors are multifactorial and as yet not well established. To determine the influence of endothelial dysfunction on the development of intimal thickening, we prospectively analyzed the vasomotor response to acetylcholine and nitroglycerin, as well as other donor and recipient variables. Findings were correlated with the coronary intimal thickness, which was evaluated by means of intravascular ultrasonography. METHODS Nineteen patients who had undergone heart transplantation 4.89 +/- 2.35 years previously and who had angiographically normal coronary arteries were included. Endothelial function was analyzed by quantitative coronary analysis of the vasomotor response of the left anterior descending artery to acetylcholine. An intimal thickness index, reflecting the percentage of intima obstructing the coronary lumen, was calculated. RESULTS Nine (47%) patients showed endothelial dysfunction, and the remaining 10 (53%) patients had a normal response. Four (44%) of 9 patients with a weight gain of greater than 20% after the operation showed endothelial dysfunction compared with none of the 10 patients with normal responses (P <.04). The severity of the intimal thickness correlated with the years after transplant (r = 0.45, P <.05). Patients with endothelial dysfunction had more intimal thickening than those without (32% +/- 17% vs 17% +/- 12%, respectively; P <.05). Furthermore, the degree of intimal thickening correlated with the magnitude of the vasomotor response to acetylcholine (r = -0.60, P =.006). No relationship was found between intimal thickness and the vasodilatory response to nitroglycerin. As independent variables for intimal thickness, multivariate analysis detected the magnitude of the response to acetylcholine (P =.0005), years after transplant (P =.01), and ischemic time (P =.03). CONCLUSIONS Cardiac allograft vasculopathy is a multifactorial disease the severity of which increases over time. Endothelial dysfunction is a predictive factor of intimal thickening severity. Predisposing factors that provoke endothelial injury, such as perioperative ischemic time and obesity, may contribute to the development of allograft vasculopathy.
Using local precision to compare search engines in consumer health information retrieval

We have conducted a user study to evaluate several generalist and health-specific search engines on health information retrieval. Users evaluated the relevance of the top 30 documents of 4 search engines in two different health information needs. We introduce the concepts of local and global precision and analyze how they affect the evaluation. Results show that Google surpasses the precision of all other engines, including the health-specific ones, and that precision differs with the type of clinical question and its medical specialty.
A Set of Protocols for Micropayments in Distributed Systems

Micropayments refer to low-value financial transactions ranging from several pennies to a few dollars. A big portion of electronic commerce occurring in the Internet belong to the category of micropayments. The cost of micropayments should be kept as low as possible in order for the service provider (the merchant) to profit from the low-value transactions. We propose several protocols for micropayments in distributed systems. Our main goal is to reduce the charging cost by choosing a suitable security model, a charging model, and cryptographic algorithms; and by employing the properties unique to the information goods. Our protocols satisfy the requirements of a payment system and are "cheap" in terms of computation costs, communication costs, and key management costs. We select the debit model for designing our protocols and base our protocols on the private key cryptosystems. We show that the existing authentication protocols and systems can be extended to handle micropayments in distributed systems. We also present possible extensions to our protocols.
Survey of the Nature and Prevalence of Patients' Noncompliance and Implications for Intervention

The problem of patients' noncompliance is discussed, noting possible biases in estimates of prevalence (18 to 82%) which may overestimate compliance rates and frequent failure to define conditions constituting compliance. This survey obtained information on the nature and incidence of noncompliance from a “healthy,” Census-based, sample (n = 148), age 20 to 79 years. Data were examined to identify relationships among variables in compliance and demographic characteristics. The typical household had 3.9 prescribed drugs, 46% of respondents chose generic products, 54% preferred tablets or pills, and 69% cited physicians as their primary information source on medications. Rates were identified for obtaining and using all prescribed drugs and following frequency and dose instructions for prescriptions. Full compliance was reported by 25%, and seriousness of illness was the most important factor cited as an influence.
Neuroscience and Reductionism: Some Realist Reflections

Organizational neuroscience (ON) is a rapidly emerging sub-field. Criticisms of its reductionism are common. Yet it is possible for practitioners and critics to engage. Such engagement is facilitated by realism. It agrees with the practitioners of ON that brain functions can in principle be measured and that causal influences can be identified. It agrees with the critics in stressing the centrality of context and the emergent nature of social processes. The claims and potentials of ON can best be grasped through realist principles.
Tracing the Region of Interest in Thermal Human Face for Respiration Monitoring

Monitoring respiration rate, i.e. the rate air is inhaled and exhaled is an important indicator of an individual’s health. Respiration rate is generally measured using sensors attached to the patient's body. These contact based methods have a number of limitations, for example the attached sensor can cause discomfort to the patients. A novel, automated, non-contact based method of respiration monitoring, based on thermal imaging of the skin surface centered on the tip of the nose for the nose breathing as well as the mouth region for the mouth breathing. These methods are developed as well as the Image processing techniques were used to enhance the thermal images, remove unwanted noise and segmented the ROI. In this study the shape and size of the region of interest (ROI) are investigated. The ROI represents the facial affected area most affected by exhaled air temperature changes. This area is the tip of the nose and the upper lip for the nose breathing and the mouth area for the mouth breathing. Segmenting the ROI was considered an important task in monitoring respiration by thermal imaging.
Performance of GAA poly-Si nanosheet (2nm) channel of junctionless transistors with ideal subthreshold slope

A junctionless (JL) gate-all-around (GAA) nanosheet polycrystalline silicon (poly-Si) 2nm channel thin-film transistor (TFT) has been successfully demonstrated. The sub-threshold swing (SS) of 61 mV/decade has been the record reported to date in JL TFTs, and the Ion/Ioff current ratio is 108. The cumulative distribution in nanosheet 2-nm channel is small. JL-GAA TFTs show a low drain-induced barrier lowering (DIBL) value of 6 mV/V for LG=60nm, excellent gate control and reduced sensitivity to temperature in terms of VTH and SS. The JL-GAA TFTs of good device characteristics along with simple fabrication are highly promising for future (system-on-panel) SOP and system-on-chip (SOC) applications.
Girls' spatial abilities: charting the contributions of experiences and attitudes in different academic groups.

BACKGROUND Gender-related differences in spatial abilities favouring males are well established but have also generated a great deal of controversy. Cross-cultural research, meta-analyses and training studies could show the influence of socio-cultural and experiential factors on spatial-test performance. However, little is known about how experiences and gender-role stereotypes mediate performance differences in this area. AIM The relationship between specific experiences (spatial activities, computer experience), achievement-related attitudes, and spatial abilities, i.e., mental-rotation ability was investigated with males and females in different academic subgroups. SAMPLE The sample comprised 112 female and 71 male undergraduates, majoring in arts, humanities and social sciences, sports, psychology and computational visualistics. METHODS A redrawn version of the Vandenberg and Kuse Mental Rotations Test (MRT) was administered and the participants completed a questionnaire about their spatial activities, computer experience, self-ratings regarding everyday spatial abilities, and attitudes towards mathematics and physics. RESULTS Mental Rotations Test performance was mainly affected by academic programme and gender, but the effect size of gender differences varied. It was largest with students majoring in arts, humanities and social sciences and smallest with those majoring in computational visualistics. Data analyses revealed statistically significant correlations with spatial activities and computer experience only for females. The relationship between test performance and scales of achievement-related self-concept also depended on gender. CONCLUSIONS Compared to males, females' spatial abilities are extremely vulnerable to and thus modifiable through attitudinal and experiential factors. This has considerable consequences for intervention programmes that could help to overcome the gender gap in spatial abilities.
Optimal Thin Torsion Rods and Cheeger Sets

We carry out an asymptotic analysis of the following shape optimization problem: a given volume fraction of elastic material must be distributed in a cylindrical design region of infinitesimal cross section in order to maximize resistance to a twisting load. We derive a limit rod model written in different equivalent formulations and for which we are able to give necessary and sufficient conditions characterizing optimal configurations. Eventually we show that for a convex design region and for very small volume fractions, the optimal shape tends to concentrate section by section near the boundary of the Cheeger set of the design. These results were announced in [G. Bouchitte, I. Fragala, and P. Seppecher, C. R. Math., 348 (2010), pp. 467–471].
Phase II clinical trial of bevacizumab and low-dose metronomic oral cyclophosphamide in recurrent ovarian cancer: a trial of the California, Chicago, and Princess Margaret Hospital phase II consortia.

PURPOSE Vascular endothelial growth factor (VEGF) plays an important role in the biology of ovarian cancer (OC). Inhibitors of VEGF suppress tumor growth in OC models. Metronomic chemotherapy, defined as frequent administration of low doses of cytotoxic chemotherapy, suppresses tumor growth, possibly by inhibiting angiogenesis. A phase II trial was conducted to evaluate the antitumor activity and adverse effects of bevacizumab and metronomic oral cyclophosphamide in women with recurrent OC. PATIENTS AND METHODS Patients with measurable disease and prior treatment with a platinum-containing regimen were eligible. Up to two different regimens for recurrent disease were allowed. Treatment consisted of bevacizumab 10 mg/kg intravenously every 2 weeks and oral cyclophosphamide 50 mg/d. The primary end point was progression-free survival at 6 months. Plasma levels of VEGF, E-selectin, and thrombospondin-1 were obtained serially. RESULTS Seventy patients were enrolled. The probability of being alive and progression free at 6 months was 56% (+/- 6% SE). A partial response was achieved in 17 patients (24%). Median time to progression and survival were 7.2 and 16.9 months, respectively. The most common serious toxicities were hypertension, fatigue, and pain. Bevacizumab-related toxicities included four episodes of gastrointestinal perforation or fistula, two episodes each of CNS ischemia and pulmonary hypertension, and one episode each of gastrointestinal bleeding and wound healing complication. There were three treatment-related deaths. Levels of VEGF, E-selectin, and thrombospondin-1 were not associated with clinical outcome. CONCLUSION The combination of bevacizumab and metronomic cyclophosphamide is active in recurrent OC. Further study of this combination is warranted.
Hybrid Beamforming With Selection for Multiuser Massive MIMO Systems

This paper studies a variant of hybrid beamforming, namely, hybrid beamforming with selection (HBwS), as an attractive solution to reduce the hardware cost of multiuser Massive Multiple-Input-Multiple-Output systems, while retaining good performance. Unlike conventional hybrid beamforming, in a transceiver with HBwS, the antenna array is fed by an analog beamforming matrix with <inline-formula><tex-math notation="LaTeX">$\bar{L}$</tex-math> </inline-formula> input ports, where <inline-formula><tex-math notation="LaTeX">$\bar{L}$</tex-math></inline-formula> is larger than the number of up/down-conversion chains <inline-formula><tex-math notation="LaTeX">$\bar{K}$</tex-math> </inline-formula>. A bank of switches connects the instantaneously best <inline-formula><tex-math notation="LaTeX"> $\bar{K}$</tex-math></inline-formula> out of the <inline-formula><tex-math notation="LaTeX">$\bar{L}$</tex-math> </inline-formula> input ports to the up/down-conversion chains. The analog beamformer is designed based on average channel statistics and therefore needs to be updated only infrequently, while the switches operate based on instantaneous channel knowledge. HBwS allows use of simpler hardware in the beamformer that only need to adjust to the statistics, while also enabling the effective analog beams to adapt to the instantaneous channel variations via switching. This provides better user separability, beamforming gain, and/or simpler hardware than some conventional hybrid schemes. In this paper, a novel design for the analog beamformer is derived and approaches to reduce the hardware and computational cost of a multiuser HBwS system are explored. In addition, we study how <inline-formula> <tex-math notation="LaTeX">$\bar{L}$</tex-math></inline-formula>, the switch bank architecture, the number of users and the channel estimation overhead impact system performance.
Genetic Variance and Genotype-by-Environment Interaction of Immune Response in Aedes aegypti (Diptera: Culicidae)

ABSTRACT Immune response can be negatively affected by resource limitation, so it is expected that organisms evolve strategies to minimize the impact of this environmental outcome. Phenotypic plasticity in immune response could represent a genetic response to face such situations. We investigated the effects of high and low quality and quantity of food at the larval stage on two important immune components, phenoloxidase activity (PO) and nitric oxide production (NO) measured in adults of the Dengue vector, Aedes aegypti. We reared families to determine the magnitude and pattern of expression of genetic variance, environmental variance and genotype-by-environment interaction (GEI). In addition, we quantified whether there were differences in plastic immune responses in both sexes. Our results indicated additive variance for PO and NO, but rearing environment did not produce differences among individuals. For NO and PO in males, there were large differences among families in plasticity, as indicated by the different slopes produced by each reaction norm. Therefore, there is additive genetic variation in plasticity for NO production and PO activity. One possible interpretation of these results is that different genotypes may be favored to fight pathogens under the different food quality situations. Males and females showed similar overall GEI strategies but there were differences in PO and NO. Males showed a phenotypic correlation between PO and NO, but we did not find genetic correlations between immune parameters in both sexes.
Impaired Mitochondrial Substrate Oxidation in Muscle of Insulin-Resistant Offspring of Type 2 Diabetic Patients

Insulin resistance is the best predictor for the development of diabetes in offspring of type 2 diabetic patients, but the mechanism responsible for it remains unknown. Recent studies have demonstrated increased intramyocellular lipid, decreased mitochondrial ATP synthesis, and decreased mitochondrial density in the muscle of lean, insulin-resistant offspring of type 2 diabetic patients. These data suggest an important role for mitochondrial dysfunction in the pathogenesis of type 2 diabetes. To further explore this hypothesis, we assessed rates of substrate oxidation in the muscle of these same individuals using 13C magnetic resonance spectroscopy (MRS). Young, lean, insulin-resistant offspring of type 2 diabetic patients and insulin-sensitive control subjects underwent 13C MRS studies to noninvasively assess rates of substrate oxidation in muscle by monitoring the incorporation of 13C label into C4 glutamate during a [2-13C]acetate infusion. Using this approach, we found that rates of muscle mitochondrial substrate oxidation were decreased by 30% in lean, insulin-resistant offspring (59.8 ± 5.1 nmol · g−1 · min−1, P = 0.02) compared with insulin-sensitive control subjects (96.1 ± 16.3 nmol · g−1 · min−1). These data support the hypothesis that insulin resistance in skeletal muscle of insulin-resistant offspring is associated with dysregulation of intramyocellular fatty acid metabolism, possibly because of an inherited defect in the activity of mitochondrial oxidative phosphorylation.
Fuzzy Rule based Enhanced Homomorphic Encryption in Cloud Computing

a day's internet services are one of the most popular services for transferring data and information. Cloud Computing is also based on internet services used for storing, transferring and many more operations related to data & work. As it is based on internet services, security is one of the major concerns in this. Numbers of methods or algorithms were implemented for securing data and information. And when the data or information is to be used it has to be decrypted so that it could be used for further process. This becomes a major concern as time consumption increased. So, to solve this issue a new fully homomorphic environment has been introduces in cloud computing. This resolves the time consumption issue but introduce a new issue that is storage space consumption. This work is introduces a new enhanced fuzzy based fully homomorphic environment. As fuzzy is a artificial intelligent system, here it is rule based intelligent system which work on 27 defined rules and helps to achieve this objective of reduces space consumption issue by using lossless compression. Comparative analysis can be done & proves that this enhanced environment is very secure and reduces burden of the network as well.
School choice as the problem of educational governance in a pluralistic frame

The aim of this article is to indicate critical aspects related to contemporary educational governance in a pluralistic frame. The problem of educational governance is shown from the angle of school choice, i.e. choice as a response to differentiated social pluralism, and choice as a move toward democratic governance, to stress the era of active citizenship and a postdichotomised, network-based providers’ model. Using three ideal-typical educational governance models, the article illustrates how the role of choice, the meaning of education, and the education system’s ability to contribute to the public good has been changed. The conceptual model of integrative choice and reflexive educational governance is proposed by combining deliberative forums and the mechanism design approach.
A comparative study of two prediction models for brain tumor progression

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were calculated as average over the four patients. Experimental results show that both the manifold learning and deep neural network models produced better results compared to using raw data and principle component analysis (PCA), and the deep learning model is a better method than manifold learning on this data set. The averaged sensitivity and specificity by deep learning are comparable with these by the manifold learning approach while its precision is considerably higher. This means that the predicted abnormal points by deep learning are more likely to correspond to the actual progression region.
Smart Monitoring Embedded Service for Energy-Efficient and Sustainable Management in Data Centers

Information technologies (IT) currently represent 2% of CO 2 emissions. In recent years, a wide variety of IT solutions have been proposed, focused on increasing the energy efficiency of network data centers. Monitoring is one of the fundamental pillars of these systems, providing the information necessary for adequate decision making. However, today’s monitoring systems (MSs) are partial, specific and highly coupled solutions. This study proposes a model for monitoring data centers that serves as a basis for energy saving systems, offered as a value-added service embedded in a device with low cost and power consumption. The proposal is general in nature, comprehensive, scalable and focused on heterogeneous environments, and it allows quick adaptation to the needs of changing and dynamic environments. Further, a prototype of the system has been implemented in several devices, which has allowed validation of the proposal in addition to identification of the minimum hardware profile required to support the model.