Miracle-dz/UniFAR-FTUs huggingface dataset:
Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry

Background: The extent to which clinical breast cancer risk prediction models can be improved by including information on known susceptibility SNPs is not known. Methods: Using 750 cases and 405 controls from the population-based Australian Breast Cancer Family Registry who were younger than 50 years at diagnosis and recruitment, respectively, Caucasian and not BRCA1 or BRCA2 mutation carriers, we derived absolute 5-year risks of breast cancer using the BOADICEA, BRCAPRO, BCRAT, and IBIS risk prediction models and combined these with a risk score based on 77 independent risk-associated SNPs. We used logistic regression to estimate the OR per adjusted SD for log-transformed age-adjusted 5-year risks. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC). Calibration was assessed using the Hosmer–Lemeshow goodness-of-fit test. We also constructed reclassification tables and calculated the net reclassification improvement. Results: The ORs for BOADICEA, BRCAPRO, BCRAT, and IBIS were 1.80, 1.75, 1.67, and 1.30, respectively. When combined with the SNP-based score, the corresponding ORs were 1.96, 1.89, 1.80, and 1.52. The corresponding AUCs were 0.66, 0.65, 0.64, and 0.57 for the risk prediction models, and 0.70, 0.69, 0.66, and 0.63 when combined with the SNP-based score. Conclusions: By combining a 77 SNP-based score with clinical models, the AUC for predicting breast cancer before age 50 years improved by >20%. Impact: Our estimates of the increased performance of clinical risk prediction models from including genetic information could be used to inform targeted screening and prevention. Cancer Epidemiol Biomarkers Prev; 25(2); 359–65. ©2015 AACR.
A DASH-TYPE CRYPTOCHROME GENE FROM LENTINULA EDODES

Fruiting body formation of mushrooms, a characteristically morphological differentiation observed in eukaryotic microorganisms, is affected by several environmental factors such as temperature, light and humidity. Especially, light is known to be one of the most important environmental signals and influences morphogenesis. In Lentinula edodes (Shiitake), blue light is required for initiation of the fruiting body formation. Therefore, photoreceptors, which are capable of light stimuli, are important for adaptation to immediate environments. Blue light photoreceptors are generally divided into two distinct classes, phototropins and cryptochromes. We previously reported that PHRA/PHRB, a blue-light photoreceptor complex in L. edodes, could regulate the transcription of the tyrosinase gene in a light-dependent manner. The PHRA belongs to the phototropin family; no cryptochrome, however, has been identified in basidiomycetes. In this study, we report the isolation of a cryptochrome-encoding gene in L. edodes, designated Le.cry. Le.CRY, the expression product of Le.cry, contained a DNA photolyase domain and a FAD-binding domain, and was homologous to dash-type cryptochrome proteins in the photolyase/cryptochrome family. Gene expressions of Le.cry, phrA and phrB were analyzed by quantitative RT-PCR during fruiting body formation (primordia, immature and mature fruiting bodies) and parts of fruiting body. The transcription levels of phrA and phrB were similar during fruiting body formation and in parts of fruiting body, whereas Le.cry showed the unique expression pattern. The differential expressions of Le.cry and phrA/phrB imply that Le.CRY might be involved in a light signaling pathway different from that mediated by PHRA/PHRB.
Whole-body PET/CT scanning: estimation of radiation dose and cancer risk.

PURPOSE To estimate the radiation dose from whole-body fluorine 18 ((18)F)-fluorodeoxyglucose (FDG) positron emission tomographic (PET)/computed tomographic (CT) studies and to evaluate the induced cancer risk to U.S. and Hong Kong populations. MATERIALS AND METHODS Fluorine 18-FDG PET/CT studies obtained by using a 64-detector CT unit and one of three CT protocols were evaluated. CT protocol A consisted of 120 kV; rotation time, 0.5 second; pitch, 0.984; 100-300 mA; and noise level, 20. CT protocol B was the same as A, except for a fixed tube current of 250 mA. CT protocol C consisted of 140 kV; rotation time, 0.5 second; pitch, 0.984; 150-350 mA; and noise level, 3.5. CT doses were measured in a humanoid phantom equipped with thermoluminescent dosimeters. Doses from (18)F-FDG PET scanning were estimated by multiplying the (18)F-FDG radioactivity (370 MBq) with dose coefficients. Effective doses were calculated according to International Commission on Radiological Protection publication 103. Lifetime attributable risk (LAR) of cancer incidence was estimated according to the National Academies' Biological Effects of Ionizing Radiation VII Report. RESULTS Effective doses with protocols A, B, and C, respectively, were 13.45, 24.79, and 31.91 mSv for female patients and 13.65, 24.80, and 32.18 mSv for male patients. The LAR of cancer incidence associated with the dose was higher in the Hong Kong population than in the U.S. population. For 20-year-old U.S. women, LARs of cancer incidence were between 0.231% and 0.514%, and for 20-year-old U.S. men, LARs of cancer incidence were between 0.163% and 0.323%; LARs were 5.5%-20.9% higher for the Hong Kong population. The induced cancer risks decreased when age at exposure increased. CONCLUSION Whole-body PET/CT scanning is accompanied by substantial radiation dose and cancer risk. Thus, examinations should be clinically justified, and measures should be taken to reduce the dose.
Cloud Computing Service Level Agreement Issues and Challenges: A Bibliographic Review

Cloud Computing provides parallel computing and emerged as an efficient technology to meet the challenges of rapid growth of data. With the number of benefits come serious challenges related to poor Quality of Service (QoS) and standards offered by cloud providers. This is due to lack of uniformity in-terms of Service Level Agreements (SLAs) offered by various providers. The lack of uniformity is considered as a major barrier to the adoption of cloud technology. Due to confusion and absence of universal agreed SLAs, different quality of services is being provided. Currently there is no uniform performance model agreed by all stakeholders; which can provide performance criteria to measure, evaluate, and benchmark the level of services offered by various cloud providers in the industry. With the implementation of General Data Protection Regulation (GDPR) in the near future and demand from cloud users to have Green SLAs that provides better resource allocations mechanism, there will be serious implications for the cloud providers and its consumers due to lack of uniformity in SLAs and variable standards of service offered by various cloud providers. This paper is an attempt to conduct a detailed review in Service Level Agreement issues, discuss the SLA life cycle, the negotiation, and assurance challenges faced by cloud users while agreeing on SLA. The paper is an attempt to highlight problems and challenges due to lack of standards or uniformity in SLAs faced by the cloud industry. Until there is a uniform performance model that stipulates certain agreed metrics in the SLA which the entire industry follows there will be different QoS offered by cloud providers which will be serious challenge to the adoption of cloud technology.
Chapter 2 Anemia and Aging or Anemia of Aging ?

represent 12% of the US population and by the year 2030 they are expected to represent 20% (1). The segment of the population increasing more rapidly than any other involves individuals over 85, the so called “oldest old. ” The mean life expectancy of the population was around 60 years in 1900, is currently 80 for women and 76 for man and is expected to rise to 84 and 80, respectively, in 2030 (1). This epidemic presents medical and social implications. Aging is associated with increased prevalence of chronic diseases, disabilities and functional dependence, that in turn lead to increased demand for medical services as well as for social services and care-giving (2, 3). While aging cannot be prevented, the complications of aging may be preventable or at least delayed. Compression of morbidity may prolong the independence and improve the quality of life of the older aged person and at the same time it may minimize the management-related costs (4, 5). This chapter explores the interactions of anemia and aging that are of interest for at least three reasons. First, incidence and prevalence of anemia increase with aging (6–8). Second anemia may represent the early sign of an underlying serious disease such as cancer, hypothyroidism or malabsorption (6). Third, anemia itself is associated with increased mortality and disability (7). It is reasonable to expect that prompt and effective management of anemia may help compress the aging-related morbidity. The causes and the management of anemia in the older aged person will be studied after reviewing the biology of aging. Chapter 2
Moral Hazard, Social Catastrophe: The Changing Face of Vulnerability along the Hurricane Coasts

The social vulnerability of the American population is not evenly distributed among social groups or between places. Some regions may be more susceptible to the impacts of hazards than other places based on the characteristics of the people residing within them. As we saw with Hurricane Katrina, when coupled with residencies in high-risk areas such as the hurricane coasts, differential vulnerabilities can lead to catastrophic results. The geographic discrepancies in social vulnerability also necessitate different mitigation, post-response, and recovery actions. Given temporal and spatial changes in social vulnerability in the future, a one-size-fits-all approach to preparedness, response, recovery, and mitigation may be the least effective in reducing vulnerability or improving local resilience to hazards.
Nine decades of North Sea sole and plaice distribution

Recent studies based mainly on research survey data suggest that within the North Sea, sole Solea solea and plaice Pleuronectes platessa have exhibited distribution shifts in recent decades—on average southward for sole and northward to deeper waters for plaice. Various hypotheses may account for such shifts, including climate change effects and more intensive fishing in southern and shallower waters; but the relatively short time-span of datasets analysed so far (� 3 decades) has complicated the separation of these two effects. We have made use of a unique dataset of catch and effort data for British North Sea trawlers; these cover nine decades (spanning the period 1913 – 2007) and are spatially detailed by ICES rectangle (0.58 latitude by 18 longitude). We quantify, for the first time, long-term distribution changes of North Sea sole and plaice over a period approaching a century, and demonstrate that the distribution shift in plaice was attributable to climate change rather than to fishing, but that both climate and fishing played a role in the distribution shift of sole. The discussion also highlights the potential impact of additional factors, including eutrophication, prey availability, and habitat modification.
State estimation using multibody models and unscented Kalman filters

Over the last years, state estimation in mechanical systems has gained interest with the recent development of real-time state estimation using MBSs (Multibody Systems). In practice, the knowledge of the system’s states allows to improve the closed-loop performances of it, reducing the use of expensive sensors by replacing them with virtual sensors, and finally improving reliability by making the system fault tolerant. On the one hand, numerous works address the synthesis of optimal observers for linear mechanical systems through the KF (linear Kalman Filter). On the other hand, when nonlinear mechanical systems are considered, such as MBSs, only sub-optimal approaches based on the LKF (Linearized KF) have usually been adopted to ensure high-frequency and hard real-time estimation. Indeed, up to now, the use of other types of nonlinear observers using MBSs has only been investigated marginally. The lack of such observers in this field of engineering is mainly due to the difficulty in performing fast integration of the nonlinear equations of motion for MBSs, which usually involve high frequency dynamics and severe nonlinearities. In [1], it is shown how the improvements in multibody dynamics raise the possibility to employ complex models in real-time state observers. The estimation was performed through the EKF (Extended KF) in its continuous form (also known as EKBF (Extended Kalman-Bucy Filter)). Generally speaking, the EKF is the most widely used algorithm for nonlinear estimation. It makes use of the nonlinear system model to perform the time update, but propagates the mean and covariance of the states through the linearized model. As long as the system remains linear on the timescale of the updates, the linearization error and consequently the estimation error stay small and accuracy is guaranteed. However, when nonlinearities are severe, EKF often gives unreliable or divergent estimates. On top of that, the linearization requires a Jacobian matrix which could either be difficult to calculate or not exist. Implementation difficulties are particularly relevant if the system model is modeled by DAE (Differential Algebraic Equations) as it is common in MBSs. Recent developments in Kalman filtering algorithms make possible to overcome part of the EKF shortcomings. The SPKFs (Sigma-Point Kalman Filters), also called LRKFs (Linear Regression Kalman Filters), use a set of deterministically calculated weighted samples, also named sigma-points or even regression points [2]. This set has to capture at least the first and second order moments of the actual state probability distribution. Each sigma-point is then individually propagated through the nonlinear system equations. The posterior statistics are approximated using simple functions involving the transformed sigma-points. Thereby, this approximation, that does not require the calculation of a Jacobian matrix, is more accurate than the EKF linearization. Different sigma-point set definitions lead to different filter characteristics that allow to give priority to estimation accuracy or to computational efficiency. The
Belowground traits of herbaceous species in young coniferous forests of the Olympic Peninsula, Washington

Variation in belowground traits of herbaceous species may influence their ability to persist and spread during and after the closed-canopy period of forest development. In 40- to 60-year-old closed-canopy, coniferous forests of the Olympic Peninsula, Washington, we excavated root and rhizome systems of 11 herbaceous species to compare morphology, vegetative spread, and proportion of biomass in belowground structures. All species were perennial and most were rhizomatous; four species were nonclonal. Of the seven clonal species, only two (Maianthemum dilatatum and Oxalis oregana) spread extensively (mean lateral spread >50 cm) by belowground perennating structures. The proportion of total biomass in belowground structures varied considerably among species (21-85%) and was higher for deciduous than for evergreen species. High variability in belowground traits suggests that multiple strategies may contribute to survival during closed-canopy conditions. For species with a high proportion of belowground biomass, we suggest that the ability to store resources or to acquire new resources through lateral spread may contribute to persistence in dense coniferous forests.
Evaluating SLAM Approaches for Microsoft Kinect

The weak performances of GPS within buildings is the reason for a lot of different approaches for indoor positioning, e.g., by using WiFi or odometry. The current position of a person is crucial, for example, for location based services that increase not only outside of buildings. Navigation systems in subway stations is just one obvious example, where GPS fails to deliver the necessary information. Especially in the field of visual odometry, there are many approaches. But all of them are either based on normal 2d camera systems or on expensive 3d camera systems. In the presented approach, we use a Microsoft Kinect, as these systems are inexpensive and widespread. We evaluate how different state of the art techniques like RANSAC or ICP can be used in combination with the Kinect and how they perform in different indoor scenarios. Our evaluation shows that those techniques can be used for the Kinect but have their shortcomings in different scenarios. For that reason, a hybrid technique was developed which combines those methods using a Kinect specialized ICP weight function. In addition, we use a loop detection algorithm to further optimize the accuracy. Finally, we present our results obtained during tests in three different test environments. This paper presents the result of different SLAM approaches implemented on the Microsoft Kinect in order to calculate trajectories. Keywords-slam, kinect, odometry, indoor positioning.
Unsupervised Aspect Discovery from Online Consumer Reviews

The success of on-line review websites has led to an overwhelming number of on-line consumer reviews. These reviews have become an important tool for consumers when making a decision to purchase a product. This growth has led to the need for applications that enable this information to be presented in a way that is meaningful. These applications often rely on domain specific semantic lexicons which are both expensive and time consuming to make. The following thesis proposes an unsupervised approach for product aspect discovery in on-line consumer reviews. We apply a two step hierarchical clustering process in which we first cluster based on the semantic similarity of the contexts of terms and then on the similarity of the hypernyms of the cluster members. The method also includes a process for assigning class labels to each of the clusters. Finally an experiment showing how the proposed methods can be used to measure aspect based sentiment is performed. The methods proposed in this thesis are evaluated on a set of 157,865 reviews from a major commercial website and found that the two-step clustering process increases cluster F-scores over a single round of clustering. Finally, the proposed methods are compared to a state of the art topic modelling approach by Titov and McDonald (2008).
Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data

This paper investigates the behavior of the EUR/CZK, EUR/HUF and EUR/PLN spot exchange rates in the period 2002–2008, using 5-minute intraday data. The authors find that daily returns on the corresponding exchange rates scaled by model-free estimates of daily realized volatility are approximately normally distributed and independent over time. On the other hand, daily realized variances exhibit substantial positive skewness and very persistent, long-memory type of dynamics. The authors estimate a simple three-equation model for daily returns, realized variance and the time-varying volatility of realized variance. The model captures all salient features of the data very well and can be successfully employed for constructing point, as well as density forecasts for future volatility. The authors also discuss some issues associated with measuring volatility from the noisy high-frequency data and employ a simple correction that accounts for the distortions present in our dataset.
Explaining convergence of OECD welfare states: a conditional approach

Existing studies have found only limited empirical evidence of welfare state convergence. Moreover, although there are good theoretical reasons both for and against welfare state convergence, there are virtually no studies that have explicitly tested the assumed effects. We argue that the concept of conditional convergence helps to both better describe and explain the phenomenon. By applying error correction models, we examine conditional convergence of various types of social expenditure in 21 OECD countries between 1980 and 2005. Our empirical findings go beyond the existing literature in two respects. First, we show that there is very strong evidence of convergence across all categories of social expenditure when conditional factors are taken into account. Second, we demonstrate that the speed of convergence is highly driven by globalization and European Union membership and shaped by existing welfare state structures.
Title Model of an Encrypted Cloud Relational DatabaseSupporting Complex Predicates in WHERE Clause

Even though the concept of a Database-as-aService (DaaS) is becoming more popular and offers significant expenditure cuts, enterprises are still reluctant to migrate their data storing and processing to the cloud. One of the reasons to that is a lack of solid security guarantees. Encrypted database is one of the major approaches to address the security of cloud data processing. However, in order to provide processing capabilities over encrypted data, multiple techniques need to be combined and adjusted to work together. This paper introduces a modular and extensible framework model of an encrypted database, which makes it possible to execute a wide range of queries, including those with complex arithmetic expressions, retaining data privacy even with an adversary gaining full access to the database server. Proposed model could be used as a basis for encrypted database systems with various functional requirements. Keywords-cloud database security; querying encrypted data; complex query predicates;
Dynamics of phytoplankton diversity structure and primary productivity in the English Channel

The dynamics of the phytoplankton assemblage, the physical, chemical and biologi- cal parameters, and primary productivity and production were monitored in the central English Channel along a transect between Ouistreham and Portsmouth from January to December 2010. The spatial patterns of the phytoplankton assemblage were controlled by the hydrological charac- teristics of the water masses, and the annual structure of the phytoplankton assemblage was char- acteristic of the central English Channel and was controlled by seasonality. The spring bloom was dominated by a single species, Chaetoceros socialis, and associated with low microphytoplankton evenness and Shannon-Wiener indices, whereas the evenness index was high from late spring to winter and associated with the proliferation of pico- and nanophytoplankton cells. We identified 2 species responsible for harmful algal blooms, Phaeocystis globosa, which dominated the commu- nity in the northern part of the Seine Bay in May, and Lepidodinium chlorophorum, which domi- nated the community near the French coast in September. We examined the relationship between microphytoplankton diversity and maximum primary production and productivity. We found a negative parabolic relationship between the diversity indices (evenness and Shannon-Wiener) and maximum primary production, and a positive parabolic relationship between the number of taxa (richness) and maximum primary production. However, we found no relationship between maximum productivity and the evenness or richness indices. High levels of productivity were measured during the increasing abundance of pico and nanophytoplankton cells, highlighting the importance of taking the dominant functional group into account, rather than the degree of diver- sity, when explaining the level of productivity.