Miracle-dz/UniFAR-FTUs huggingface dataset:
Long‐Term Survival of Individuals Born With Congenital Heart Disease: A Systematic Review and Meta‐Analysis

Background Estimates of long‐term survival are required to adequately assess the variety of health and social services required by those with congenital heart disease (CHD) throughout their lives. Methods and Results Medline, Embase, and Scopus were searched from inception to June 2015 using MeSH headings and keywords. Population‐based studies that ascertained all persons born with CHD within a predefined area and reported survival estimates at ≥5 years were included. Unadjusted survival estimates for each CHD subtype at ages 1 year, 5 years, 10 years, and so forth were extracted. Pooled survival estimates for each age were calculated using meta‐analyses. Metaregression was performed to examine the impact of study period on survival. Of 7840 identified articles, 16 met the inclusion criteria. Among those with CHD, pooled 1‐year survival was 87.0% (95% CI 82.1–91.2), pooled 5‐year survival was 85.4% (95% CI 79.4–90.5), and pooled 10‐year survival was 81.4% (95% CI 73.8–87.9). There was significant heterogeneity of survival estimates among articles (P<0.001 for 1‐, 5‐, and 10‐year survival). A more recent study period was significantly associated with greater survival at ages 1 year (P=0.047), 5 years (P=0.013), and 10 years (P=0.046). Survival varied by CHD subtype, with 5‐year survival being greatest for those with ventricular septal defect (96.3%, 95% CI 93.7–98.2) and lowest for those with hypoplastic left heart (12.5%, 95% CI 0.0–41.4). Conclusions Among persons with CHD, the mortality rate is greatest during the first year of life; however, this systematic review and meta‐analysis showed that survival decreases gradually after infancy and into adulthood.
Bayesian Estimation and Inference Using Stochastic Electronics

In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream.
Phosphorylation of the Cap-Binding Protein Eukaryotic Translation Initiation Factor 4E by Protein Kinase Mnk1 In Vivo

ABSTRACT Eukaryotic translation initiation factor 4E (eIF4E) binds to the mRNA 5′ cap and brings the mRNA into a complex with other protein synthesis initiation factors and ribosomes. The activity of mammalian eIF4E is important for the translation of capped mRNAs and is thought to be regulated by two mechanisms. First, eIF4E is sequestered by binding proteins, such as 4EBP1, in quiescent cells. Mitogens induce the release of eIF4E by stimulating the phosphorylation of 4EBP1. Second, mitogens and stresses induce the phosphorylation of eIF4E at Ser 209, increasing the affinity of eIF4E for capped mRNA and for an associated scaffolding protein, eIF4G. We previously showed that a mitogen- and stress-activated kinase, Mnk1, phosphorylates eIF4E in vitro at the physiological site. Here we show that Mnk1 regulates eIF4E phosphorylation in vivo. Mnk1 binds directly to eIF4G and copurifies with eIF4G and eIF4E. We identified activating phosphorylation sites in Mnk1 and developed dominant-negative and activated mutants. Expression of dominant-negative Mnk1 reduces mitogen-induced eIF4E phosphorylation, while expression of activated Mnk1 increases basal eIF4E phosphorylation. Activated mutant Mnk1 also induces extensive phosphorylation of eIF4E in cells overexpressing 4EBP1. This suggests that phosphorylation of eIF4E is catalyzed by Mnk1 or a very similar kinase in cells and is independent of other mitogenic signals that release eIF4E from 4EBP1.
Web-Serving Health with ST-Guide

ST-Guide is a computer-interpretable clinical guidelines development, verification, and implementation project focused on primary care to chronic disease patients. It can be used to implement guides in different modes: authoritarian, apprentice, specialist, and auditor. Only specialist and authoritarian modes are functional in this release. This paper presents the projectpsilas web services module, which complies to WSDL and SOAP open standards. ST-Guidepsilas web services architecture allows external computer systems to implement guidelines independently of its underlying operating system and programming language. The kind of technology presented in this paper is considered fundamental to widespread highest standard medical knowledge.
HIERARCHICAL HYBRID ENERGY EFFICIENT DISTRIBUTED CLUSTERING ALGORITHM

The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in applications such as environment monitoring, disaster management, healthcare and security surveillance. In wireless sensor network an efficient arrangement of network topology is required for energy optimization. Clustering has been proposed as an effective way of organizing sensor networks. Current clustering algorithms usually utilize two techniques, selecting cluster heads with more residual energy and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. In this paper, Heed (a Hybrid Energy Efficient Distributed clustering algorithm), one of the pioneers algorithm for clustering WSN, has been investigated. Three mechanisms to improve the Heed algorithm namely Unequal Heed, Hierarchical Heed and Relay Heed have been proposed. Simulation results have shown that Hierarchical Heed offers around 36% of energy savings for the clustering process and 69% energy savings for the routing process compared to the Heed algorithm.
GOOD, BAD, UP, AND DOWN BETAS: WHAT IS ACTUALLY PRICED?*

Stock returns are determined both by news about cas h flows and news about discount rates (Campbell and Vuolteenaho (2004)). In this paper we test whether asymmetric preferences for losses versus gains like in Ang, Chen, and Xing (20 06) also affect the pricing of cash flow versus discount rate news. For this, we construct a new fo ur-fold beta decomposition, distinguishing cash flow and discount rate betas in both up and do wn markets. We test which of the four betas is priced most consistently in the cross-section of CR SP stock returns. Our results indicate that the downside cash flow beta and downside discount rate beta carry the largest premium. We subject our result to an extensive number of robustness ana lyses, including the alternative decomposition methods for cash flow and discount rate news of Chen and Zhao (2008). The downside cash flow risk is priced most consistently across samples, pe riods, and methodologies. The cash flow premia estimates decrease with company size. Moreover, in terms of their economic contribution in explaining the level of average realized returns , it appears that the importance of both up and down discount rate news dominates the contribution of downside cash flow risk.
Microbleeds and Silent Brain Infarctions Are Differently Associated with Cognitive Dysfunction in Patients with Advanced Periventricular Leukoaraiosis

Background Leukoaraiosis, microbleeds, and silent brain infarctions are phenotypes of small vessel disease. Leukoaraiosis is the most prevalent, and advanced periventricular leukoaraiosis is regarded as a strong predictor of cognitive dysfunction. Microbleeds and silent brain infarctions sometimes coexist with leukoaraiosis. This study aims to analyze the effects of microbleeds and silent brain infarctions on cognitive function of patients with advanced periventricular leukoaraiosis. Methods 227 patients with advanced periventricular leukoaraiosis were divided into control, MB, SBI, and MB&SBI groups. The presence and locations of microbleeds and silent brain infarctions were evaluated. Mini-Mental State Examination, Montreal Cognitive Assessment, Clock Drawing Test and Verbal Fluency Test were performed. Chi-square test and ANOVA to compare the characteristics of four groups, multiple linear regressions to identify the risk factors for cognitive dysfunction. Results The scores in all four tests were lower in the MB and MB&SBI groups while only the scores in Clock Drawing Test and Verbal Fluency Test were lower in the SBI group than in the control group. Age and the presence of microbleeds were independent risk factors for the lower scores in all four tests, whereas the presence of silent brain infarctions was the only independent risk factor for the lower scores in Clock Drawing Test and Verbal Fluency Test. Lobar microbleeds had the most significant effect on cognitive function. Conclusion Microbleeds and silent brain infarctions were associated differently with cognitive impairment of patients with advanced periventricular leukoaraiosis. The effect of lobar microbleeds was the most significant.
Selfdual strings and loop space Nahm equations

We give two independent arguments why the classical membrane fields should be take values in a loop algebra. The first argument comes from how we may construct selfdual strings in the M5 brane from a loop space version of the Nahm equations. The second argument is that there appears to be no infinite set of finite-dimensional Lie algebras (such as su(N) for any N) that satisfies the algebraic structure of the membrane theory.
An Efficient Method For Road Extraction For Urban Planning

The uses of road map in daily activities are numerous but it is a hassle to construct and update a road map whenever there are changes. research on Automatic Road Extraction (ARE) was explored to solve the difficulties in updating road map. The research started with using Satellite Image (SI), or in short, the ARESI project. A Hybrid Simple Colour Space Segmentation and Edge Detection (Hybrid SCSSEDGE) algorithm was developed to extract roads automatically from satellite-taken images. The extracted road regions are validated by using a segmentation method. These results are valuable for building road map and detecting the changes of the existing road database. The proposed Hybrid Simple Colour Space Segmentation and Edge Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks fully automatic, where the user only needs to input a high-resolution satellite image and wait for the result. Moreover, this system can work on complex road network and generate the extraction result in seconds.
Institutional Logics and Entrepreneurship: Struggling for Legitimacy in the Emerging Bio-Energy Field

Citing a scholarly movement towards contextualized entrepreneurship research, this dissertation explains and encourages new reflection on the entrepreneurship process and its role in the transition to a sustainable society. The goal is to re-examine and resituate entrepreneurship processes through an Institutional Logics Perspective – a new approach to culture, structure, and process. Building on a two-year qualitative study with Dutch entrepreneurs who aim to commercialize bio-energy technologies – which replaces fossil fuel energy and reduces carbon emissions – the author provides evidence that to build new organizational forms that merge environmental and commercial values, entrepreneurs navigate their complex institutional environment through an assemblage process. An assemblage process is where seemingly coherent and stable institutional logics are assembled together to give new purpose and meaning to activities. This study shows how entrepreneurs synthesize institutional complements and reconcile or avoid institutional conflicts to construct new environmental-commercial hybrids. Further results demonstrate that to acquire resources from potential stakeholders, entrepreneurs use symbolic practices – metaphors, allegory, actions, and objects - to represent themselves beyond a functional dimension. They aim to gain a perception of legitimacy according to one or more institutional logics present, which, in turn, works to reinforce or subvert dominant institutional paradigms. More qualitative data reveals how entrepreneurs engage in institutional work to alter the arrangements and properties of institutional logics when their claims are seen as illegitimate. Entrepreneurs in small, marginalized groups are seen as sectarian associations that enact different modes, scopes, and scales of institutional work compared to entrepreneurs working alone. In addition, examining two longitudinal survey databases through regression analyses, the author finds evidence that entrepreneurs employing ‘clean’ technologies – alternative energy, new waste and water remediation technologies – are more likely to seek legitimacy by enacting strategies that go beyond product development. These legitimacy strategies differ from entrepreneurs using biotechnology and information and communication technologies. Moreover, entrepreneurs commercializing ‘clean’ technologies are more likely to view environmental regulations as a barrier to their development yet these regulations also significantly lead to venture growth over time. Ultimately, these findings have a number of implications into how, and under what conditions, entrepreneurs are able to access, activate, change, and/or produce new institutional logics. They work to explain how entrepreneurs create new organizational forms, alter the bases of legitimacy judgments, generate resource availability, and develop new sustainable markets.
Polychlorinated biphenyls (PCBs) and neurological development in children: a systematic review

BACKGROUND Polychlorinated biphenyls (PCBs) are complex mixtures of persistent contaminants that are widespread in the environment. Newborns are exposed across the placenta and through breast feeding. Experimental animal studies have indicated that PCBs are neurotoxic. The neurological effects of these compounds on children are not clear.Methods—A systematic review of literature on the relation between neurological development in children and exposure to polychlorinated biphenyls. RESULTS Seven follow up studies evaluated the effect of prenatal exposure to PCBs. Two of these studies evaluated highly exposed children. In newborns, an increase of the abnormal reflexes was observed in all four studies evaluating it. During the first months of life, a decrease in motor skills was observed in four of the five studies that investigated psychomotor development; deficits in the acquisition of cognitive skills were observed only in one study assessing non-highly exposed populations. At 4 years of age, an effect on the cognitive areas was observed in four of the five studies that evaluated it. Postnatal exposure to PCBs through breast feeding was not clearly related to any effect on neurological development. CONCLUSIONS These studies suggest a subtle adverse effect of prenatal PCBs exposure on child neurodevelopment. Differences in study design, inconsistency in some of the results, and the lack of adequate quantitative exposure data, do not allow the derivation of the degree of risk associated with neurodevelopmental effects at current levels of exposure.
Optic disc segmentation by incorporating blood vessel compensation

Glaucoma is one of the main causes of blindness worldwide. Segmentation of vascular system and optic disc is an important step in the development of an automatic retinal screening system. In this paper we present an unsupervised method for the optic disc segmentation. The main obstruction in the optic disc segmentation process is the presence of blood vessels breaking the continuity of the object. While many other methods have addressed this problem trying to eliminate the vessels, we have incorporated the blood vessel information into our formulation. The blood vessel inside of the optic disc are used to give continuity to the object to segment. Our approach is based on the graph cut technique, where the graph is constructed considering the relationship between neighboring pixels and by the likelihood of them belonging to the foreground and background from prior information. Our method was tested on two public datasets, DIARETDB1 and DRIVE. The performance of our method was measured by calculating the overlapping ratio (Oratio), sensitivity and the mean absolute distance (MAD) with respect to the manually labeled images. Experimental results demonstrate that our method outperforms other methods on these datasets.
Dynamic virtual optical networks supporting uncertain traffic demands [invited]

This paper focuses on the concept of dynamic virtual optical networks (VONs) as a key enabling technology to support the requirements of the future Internet. To address the unpredictable nature of services and their characteristics, dynamic and on-demand planning and replanning of VONs is required. This paper proposes the use of novel modeling approaches to specifically consider the uncertain nature of traffic requests. In addition, it studies mechanisms to evaluate and minimize the impact of this uncertainty on the availability and efficiency of the virtual resources, considering at the same time requirements such as service resilience and security. The effect of periodic VON replanning is investigated and the relevant trade-offs are identified. Our modeling results show that taking into consideration the dynamic and uncertain nature of services provides significant benefits regarding the ability of the infrastructure to support these services and the associated resource efficiency.
Significant Level in V-detector Generation Algorithm

The V-detector generation algorithm is a kind of negative selection algorithm (NSA) inspired by biological immune system (BIS). In this paper, V-detector generation algorithm is simply introduced. The problem that V-detector generation algorithm can not meet the change of parameters in significant level is also pointed out. This problem will cause instable algorithm performance. In the meantime, it will cause the algorithm failed under the circumstance of some parameter values. This paper analyzed the reason that caused the problem theoretically and the relevant solution is proposed. The experiment results showed that the proposed solution solved the problem existed in original algorithm successfully and make the performance more stable and reliable. The improved algorithm can really adapt to different values of significant level and obtain better detection performance.
Review of Multiscale Simulation in Submicron Heat Transfer

Over thelastdecade, interestin thesimulationof microandnano-scale heattransferhasleadto thedevelopmentof a varietyof modelsandnumerical methods for phonon transpor t in semiconductorsanddielectrics.These models spandirect simulationusingmoleculardynamics,a rangeof modelsof varying fidelity basedon theBoltzmanntranspor t equation, aswell as simplerhyperbolic extensionsto theclassicalFourier heatconduction equation. Thepaperreviews thebasicsof phonontransport in crystals,available models for phonon transpor t, aswell asnumerical methods for solving the equationsresultingfrom thesemodels. Recommend ationsaremadefor futurework.
The Challenge of Facilitating Child Adoption the Case of Child and Security Office in Bahir Dar City Administration

Adoption has connotation for creating healthy and ethical societies who contributes the development of a country in different aspects. The research objective is to investigate the challenges of Bahir Dar city administration women and children affair office when facilitating child adoption. In order to achieve the research objectives, the researcher employed qualitative research approach through case study design. The researcher used non probability sampling techniques. In order to collect the data, primary and secondary data were used. Thematic and document analysis were employed to analysis the data. The findings of the research indicated that Bahir Dar city administration women and children affair office when facilitating child adoption faced many challenges. such as, Bureaucratic system, scarcity of budget, low understanding and cooperation, low transport services, low/shortage human power, the interest of parents to adopt infant children, lack of information, low community perception on adoption, low participation of the society, unfamiliar of adopt parents, lack of special attention for children those are faced by diseases. And the researcher conclude that child adoption facilitating faced so many problems. And recommendation are forwarded depend on the conclusion.
A new river flooding scheme for global climate applications: Off‐line evaluation over South America

[1] Given their strong interaction with both climate and the carbon cycle, wetlands and surface waters need to be parameterized in global general circulation models. For this purpose, a new simple flooding river scheme is proposed and evaluated over South America. The flood dynamics is described through the coupling between the ISBA land surface model and the TRIP river routing model including a prognostic flood reservoir. This reservoir fills when the river height exceeds a critical value and vice versa. The reservoir interacts with the soil hydrology through infiltration and with the overlying atmosphere through precipitation interception and free water surface evaporation. The model is tested in off-line mode using the 10-year ISLSCP-2 atmospheric forcing. The evaluation is made against satellite-derived inundation estimates as well as in situ river discharge observations. Besides a basin-scale increase in annual surface evaporation, the results show improved monthly discharges over the Amazon and Parana rivers, as well as a reasonable agreement between the simulated flooded areas and satellite-derived inundation estimates.
Noncoherent relay selection for bidirectional cooperative networks

In this paper we propose a new noncoherent relay selection strategy for two-way relay cooperative networks. In our proposed scenario, channel state information (CSI) or feedback link is not needed, neither for relay selection nor for data detection. We assume Mary frequency shift keying (FSK) modulation for our transmission scheme and decode-and-forward (DF) protocol for our system relaying method. Relay selection is performed based on a min-max criterion on the received instantaneous signal energies at the relay nodes. Furthermore, by using energy detectors at both destination nodes the transmitted signal is decoded. We present a closed-form formula for the average symbol error rate (ASER) of the proposed noncoherent selection method. We also provide high signal-to-noise-ratio (SNR) analysis and the achievable diversity order for the proposed selection method. Finally we present a simulation study to corroborate the analytical results and to demonstrate the performance of the introduced noncoherent selection method.