Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of intraductal papilloma without atypia of the breast diagnosed on core biopsy: Size and sampling matter

Due to the potential for atypia (atypical ductal or lobular hyperplasia) or carcinoma (in situ or invasive) on excision, aggressive reflex surgical excision protocols following core biopsy diagnosis of papillary lesions of the breast (ie, intraductal papilloma) are commonplace. Concepts in risk stratification, including radiologic‐pathologic correlation, are emerging in an effort to curb unnecessary surgeries. To this end, we examined all excised intraductal papillomas diagnosed at our institution from 2010‐2015 (N = 336) and found an overall atypia rate of 20%. To investigate further, we stratified all excised papillomas according to total lesion size (range = 1‐40 mm) and found that the atypia rate for lesions ≤1.2 cm (16% with atypia) was statistically significantly lower (P = .008) than the atypia rate for lesions >1.2 cm (36% with atypia). To explore to effects of radiologic‐pathologic correlation on the ability of the core biopsy to accurately predict nonatypical lesions we assessed thirteen consecutive paired nonatypical core biopsy/follow‐up surgical excision specimens for the percent of the total lesion (on imaging) sampled by the core biopsy (measured histologically). None of the thirteen paired specimens showed upgrade on excision (0/13); the percent of total lesion sampled by biopsy in this cohort averaged 59%. We propose that in the absence of discordant clinical/radiological findings, small lesions (≤1.2 cm) with radiologic‐pathologic concordance (>50% sampling of total lesion by core biopsy) may safely forego surgery for close clinical and radiographic follow‐up.
Linguistic Disorders and Pathologies An International Handbook

This handbook is geared towards the following aims: Reviewing the state of research on disordered language perception and production in adults and children. Describing and discussing present attempts at modelling human language processing by using linguistic disorders and pathologies as a data base. Presenting diagnostic and therapeutic concepts. Pointing out gaps and inconcistencies in current knowledge and theories. In bringing together knowlegde of different sources and disciplines under a common roof, the editors have achieved a comprehensive overview of the state of the art in the field of language pathology. Because of the diversity of the disciplines contributing to this scientific field, the chapters differ clearly in theories and methodologies. Yet this handbook represents a clear and common interdisciplinary contribution to linguistic disorders and pathologies and, furthermore, demonstrates the amount of interdisciplinary interaction still required. We chose this title in order to encompass as broadly as possible abnormalities and alterations of language perception, comprehension and production in adults and children, including nonpathological disorders. This handbook will be of interest to anybody involved with disordered language and/or language and speech disturbances, such as linguists and psychologists working in related research areas or teaching related subjects, scientists analyzing and modelling linguistic and cognitive processes (e.g. in Cognitive Psychology, Psycholinguistics, Neurolinguistics, Neuropsychology, Behavioural Neurology, Artificial Intelligence Research, and Cognitive Science), clinicians dealing with aquired or developmental language disorders, and speech pathologists and therapists. Besides presenting the state of the art, the handbook provides rich bibliographical information for research workers, clinicians, and advanced students.
Month of birth predicted reproductive success and fitness in pre-modern Canadian women

Conditions experienced during early development affect human health and survival in adulthood, but whether such effects have consequences for fitness is not known. One surrogate for early conditions is month of birth, which is known to influence health and survival in many human populations. We show that in nineteenth century Canada, month of birth predicted a woman's fitness measured by the number of grandchildren produced, with the genetic contribution to the following generations by women born in different months differing by over seven grandchildren. This difference was mainly caused by differences in the reproductive rates of both mothers and their offspring, rather than differences in their survival. Women born in the best months of the year had longer reproductive lifespans, larger numbers of live births and raised more offspring to adulthood than those who were born in the worst months. Furthermore, the offspring of those women born in the best months also had greater reproductive rates, suggesting that month of birth also influenced a mother's ability to invest in her offspring. Our results suggest that early conditions may have important consequences for human lifetime reproductive performance within and between generations, and that timing of birth had large effects on fitness in this rural community.
Analyzing Polemics Evolution from Twitter Streams Using Author-based Social Networks

The construction of social network graphs from online networks data has become nowadays a common track to analyze these data. Typical research questions in this domain are related to profile building, interest’s recommendation, and trending topics prediction. However, few work has been devoted to the analysis of the evolution of very short and unpredictable events, called polemics. Also, experts do not use tools coming from social network graphs analysis and classical graph theory for this analysis. In this way, this article shows that such analysis lead to a colossal amount of data collected from public social sources like Twitter. The main problem is collecting enough evidences about a non-predictable event, which requires capturing a complete history before and during the course of this event, and processing them. To cope with this problem, while waiting for an event, we captured social data without filtering it, which required more than a TB of disk space. Then, we conduct a time-related social network analysis. The first one is dedicated to the study of the evolution of the actor interactions, using time-series built from a total of 33 graph theory metrics. A Big Data pipeline allows us to validate these techniques on a complex dataset of 284 millions of tweets, analyzing 56 days of the Volkswagen scandal.
Forest dynamics and climate sensitivity of an endangered Carolina hemlock community in the southern Appalachian Mountains, USA

During the last century, the eastern United States has functionally lost two major tree species (American chestnut and American elm), two more, eastern and Carolina hemlock, will likely be functionally extinct during much of their ranges by 2050. Carolina hemlock forests are geographically limited to high elevations in the southern Appalachian Mountains and are considered to be endangered. We collected forest stand, composition, and tree age data at the beginning of a hemlock woolly adelgid (HWA) infestation. Prior to the arrival of HWA, Carolina hemlocks were healthy and densely populated in the overstory and understory. While Carolina hemlock regenerated successfully and continuously from 1850 to 2010, the development of this Carolina hemlock forest will be altered by the HWA and may result in an increase in the density of northern red oak, white oak, mountain laurel, and Catawba rhododendron. Carolina hemlocks prefer cool, wet summers with older trees experiencing greater reductions in radial growth th.
Breast Cancer Survivability Prediction via Classifier Ensemble

—This paper presents a classiﬁer ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classiﬁer ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to ﬁnd the most important features among the four groups that maximizes the weighted average F-score of a certain classiﬁcation algorithm. The ensemble component uses three different classiﬁers, each of which models different set of features from SEER through the features selection module. On top of them, another classiﬁer is used to give the ﬁnal decision based on the output decisions and conﬁdence scores from each of the underlying classiﬁers. Different classiﬁcation algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classiﬁers and Na¨ıve Bayes for the classiﬁer ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.
Memory deficits for heard and lip-read speech in young and adult poor readers

Short-term memory for heard and lipread speech was investigated in children and adults who suffered from developmental reading backwardness. The results showed that with heard and lipread lists, both groups had normal recency and suffix effects, but recall of the items from the middle serial positions was relatively impaired if compared with normal readers. It is argued that poor underspecified phonological representations are not the major cause of the reduced span in the poor readers, because such a deficit would be reflected in the recency part of the serial position curve. It is suggested that the memory impairment might be related to a reduced articulation rate.
Simulation of Denial of Service (DoS) Attack using Matlab and Xilinx

As the Internet is growing – so is the vulnerability of the network. Companies now days are spending huge amount of money to protect their sensitive data from different attacks that they face. DoS or Denial Of Service attacks are one of such kind of attacks. In this paper, we at first recognize different kinds of DoS attacks and then propose a new methodology to simulate those.
Remifentanil-induced Postoperative Hyperalgesia and Its Prevention with Small-dose Ketamine

Background:Remifentanil-induced secondary hyperalgesia has been documented experimentally in both animals and healthy human volunteers, but never clinically. This study tested the hypotheses that increased pain sensitivity assessed by periincisional allodynia and hyperalgesia can occur after relatively large-dose intraoperative remifentanil and that small-dose ketamine prevents this hyperalgesia. Methods:Seventy-five patients undergoing major abdominal surgery were randomly assigned to receive (1) intraoperative remifentanil at 0.05 &mgr;g ·kg−1 ·min−1 (small-dose remifentanil); (2) intraoperative remifentanil at 0.40 &mgr;g ·kg−1 ·min−1 (large-dose remifentanil); or (3) intraoperative remifentanil at 0.40 &mgr;g ·kg−1 ·min−1 and 0.5 mg/kg ketamine just after the induction, followed by an intraoperative infusion of 5 &mgr;g · kg−1 · min−1 until skin closure and then 2 &mgr;g ·kg−1 ·min−1 for 48 h (large-dose remifentanil–ketamine). Pain scores and morphine consumption were recorded for 48 postoperative hours. Quantitative sensory tests, peak expiratory flow measures, and cognitive tests were performed at 24 and 48 h. Results:Hyperalgesia to von Frey hair stimulation adjacent to the surgical wound and morphine requirements were larger (P < 0.05) and allodynia to von Frey hair stimulation was greater (P < 0.01) in the large-dose remifentanil group compared with the other two groups, which were comparable. There were no significant differences in pain, pressure pain detection threshold with an algometer, peak flow, cognitive tests, or side effects. Conclusion:A relatively large dose of intraoperative remifentanil triggers postoperative secondary hyperalgesia. Remifentanil-induced hyperalgesia was prevented by small-dose ketamine, implicating an N-methyl-d-aspartate pain-facilitator process.
Reconceptualizing ST®E(A)M(S) Education for Teacher Education

This article examines science, technology, engineering, and math (STEM) education as represented in North American educational contexts. In this article we will argue that the dominant view of STEM education as currently circulated and practiced in the United States and Canada is not much more than an acronym of discrete disciplinary areas. We offer a critical review of popular literature about STEM education and argue that too much emphasis in popular culture is currently on a quick fix of recent global economic conditions. Critical inquiry is proposed as a method for teacher candidates to reflexively deliberate on why curriculum integration (i.e., ®), the arts and humanities (i.e., (A)) and sustainability education (i.e., (S)) are important areas of STEM education. We discuss why an integrated view of ST®E(A)M(S) education that honors disciplinary content but does not succumb to disciplinary isolation is needed.
A Graph Signal Processing Perspective on Functional Brain Imaging

Modern neuroimaging techniques provide us with unique views on brain structure and function; i.e., how the brain is wired, and where and when activity takes place. Data acquired using these techniques can be analyzed in terms of its network structure to reveal organizing principles at the systems level. Graph representations are versatile models where nodes are associated to brain regions and edges to structural or functional connections. Structural graphs model neural pathways in white matter, which are the anatomical backbone between regions. Functional graphs are built based on functional connectivity, which is a pairwise measure of statistical interdependency between pairs of regional activity traces. Therefore, most research to date has focused on analyzing these graphs reflecting structure or function. Graph signal processing (GSP) is an emerging area of research where signals recorded at the nodes of the graph are studied atop the underlying graph structure. An increasing number of fundamental operations have been generalized to the graph setting, allowing to analyze the signals from a new viewpoint. Here, we review GSP for brain imaging data and discuss their potential to integrate brain structure, contained in the graph itself, with brain function, residing in the graph signals. We review how brain activity can be meaningfully filtered based on concepts of spectral modes derived from brain structure. We also derive other operations such as surrogate data generation or decompositions informed by cognitive systems. In sum, GSP offers a novel framework for the analysis of brain imaging data.
Identifying the Influentials in Blogosphere

Blogging becomes a popular way for a Web user to publish information on the Web. Bloggers write blog posts, share their likes and dislikes, voice their opinions, provide suggestions, report news, and form groups in Blogosphere. As its size doubled for every 6 months, Blogosphere is expanding with about 175,500 daily blogs. Bloggers form their virtual communities of similar interests. Activities happened in Blogosphere affect the external world in many ways. The conventional journalism now looks more into this form of participatory journalism for events of special interests, and collective wisdoms are tapped for unique deals and great opportunities. In order to track and understand the development on Blogosphere, in the past, researchers have focused on finding influential blog sites. Regardless of a blog site being influential or not, inspired by the high impact of the influentials in a physical community, we endeavor to identify the influential bloggers in a virtual community (a blog site). There are many non-influential blog sites (“the long tail”) and they can still have their influential bloggers. Active bloggers are not necessarily influential ones. There may be more than one influential blogger at one site given the nature of Blogosphere. Influential bloggers can impact other fellow bloggers in various ways. In this paper, recognizing the challenges of identifying influential bloggers, we investigate what constitutes influential bloggers, present a preliminary model to quantify an influential blogger to pave the way for a robust model that allows for finding various types of the influentials. To illustrate these issues, we conduct experiments with data from a real blog site, evaluate many aspects of identifying influential bloggers, and discuss unique challenges. We conclude with interesting findings and future work.
Dirac Charge Quantization and Generalized Differential Cohomology

The main new result here is the cancellation of global anomalies in the Type I superstring, with and without D-branes. Our argument here depends on a precise interpretation of the 2-form abelian gauge field using KO-theory; then the anomaly cancellation follows from a geometric form of the full Atiyah-Singer index theorem for families of Dirac operators. This is a refined version of the Green-Schwarz mechanism. It seems that a geometric interpretation of this mechanism-the cancellation of local and global fermion anomalies against local and global anomalies in the electric coupling of an abelian gauge field-always proceeds in a similar manner. For example, a previous paper with M. Hopkins (hep-th/0002027) explains the cancellation of anomalies in Type II with D-branes in these terms. The focal point of this paper is a general discussion about abelian gauge fields and Dirac charge quantization. Namely, we argue that quantization of charge is implemented in the functional integral by interpreting abelian gauge fields as cochains in a generalized differential cohomology theory. Our exposition includes elementary examples as well as examples from superstring theory. The mathematical underpinnings of differential cohomology are currently under development; we only give a sketch here. The anomaly cancellation in Type I depends on properties of a certain quadratic form in KO-theory, which we analyze in an appendix written jointly with M. Hopkins. In particular, the usual equation ``Tr R^2 = Tr F^2'' is refined to an equation in the KO-theory of spacetime.
Accelerated Estimation of Frequency Classes in Site‐Heterogeneous Profile Mixture Models

Abstract As a consequence of structural and functional constraints, proteins tend to have site‐specific preferences for particular amino acids. Failing to adjust for heterogeneity of frequencies over sites can lead to artifacts in phylogenetic estimation. Site‐heterogeneous mixture‐models have been developed to address this problem. However, due to prohibitive computational times, maximum likelihood implementations utilize fixed component frequency vectors inferred from sequences in a database that are external to the alignment under analysis. Here, we propose a composite likelihood approach to estimation of component frequencies for a mixture model that directly uses the data from the alignment of interest. In the common case that the number of taxa under study is not large, several adjustments to the default composite likelihood are shown to be necessary. In simulations, the approach is shown to provide large improvements over hierarchical clustering. For empirical data, substantial improvements in likelihoods are found over mixtures using fixed components.
Speech development and auditory performance in children after cochlear implantation

Background: The aim of this study was to determine the auditory performance of congenitally deaf children and the effect of cochlear implantation (CI) on speech intelligibility. Methods: A prospective study was undertaken on 47 children in a pediatric tertiary referral center for CI. All children were deaf prelingually and were younger than 8 years of age. They were followed up until 5 years after implantation. Auditory performance was assessed by using the categories of auditory performance (CAP) scale and speech intelligibility rating which evaluated the spontaneous speech of each child before and at frequent intervals for five years after implantation. Results: Pre-lingually deaf children showed significant improvement in auditory performance after implantation. Six months after implantation 91% of children had the ability to respond to speech sounds. At the end of year one, 96% of children could discriminate speech sounds and 84% of children who reached the three year interval could understand common phrases without lip-reading. After cochlear implantation, the difference between the speech intelligibility rating increased significantly each year for 3 years (p<0.05) and did not plateau up to 5 years after implantation. The changes in auditory performance and speech development were parallel. Conclusion: The results indicated the ability of cochlear implantations to significantly improve auditory receptive skills and subsequently speech development in young congenitally deaf children.
Implementation of Hash Function Generator on Schematic to Program Translator(SPT)

The hash function plays an important role in information security such as a digital signature. However, in recent years, it is a field of rapidly changing industries such as break of SHA-1, it can be said that the time is now required for ease of development and testing of hash functions. GUI based block cipher development environment named SPT as a cryptographic development environment was proposed in 2014. It realized an environment in which block cipher development can be performed. However, SPT can't develop hash functions, it has not been completed as a comprehensive cryptographic development environment. This paper proposes a cryptographic development environment named SPT2 according with a hash function by adding several functions to SPT and shows its effectiveness. MD5 generated by SPT2 was confirmed to work properly. Moreover, processing speed of MD5 generated by SPT2 is compared with the OpenSSL's MD5 and the reference code that was described in RFC1321. The comparison results of their speed are as follows: top was OpenSSL's MD5, second was generated by SPT2, last was the reference code.
Heritability of blood pressure traits and the genetic contribution to blood pressure variance explained by four blood-pressure-related genes

Objective To study the heritability of four blood pressure traits and the proportion of variance explained by four blood-pressure-related genes. Methods All participants are members of an extended pedigree from a Dutch genetically isolated population. Heritability and genetic correlations of systolic blood pressure, diastolic blood pressure, mean arterial pressure and pulse pressure were assessed using a variance components approach (SOLAR). Polymorphisms of the α-adducin (ADD1), angiotensinogen (AGT), angiotensin II type 1 receptor (AT1R) and G protein β3 (GNB3) genes were typed. Results Heritability estimates were significant for all four blood pressure traits, ranging between 0.24 and 0.37. Genetic correlations between systolic blood pressure, diastolic blood pressure and mean arterial pressure were high (0.93–0.98), and those between pulse pressure and diastolic blood pressure were low (0.05). The ADD1 polymorphism explained 0.3% of the variance of pulse pressure (P = 0.07), and the polymorphism of GNB3 explained 0.4% of the variance of systolic blood pressure (P = 0.02), 0.2% of mean arterial pressure (P = 0.05) and 0.3% of pulse pressure (P = 0.06). Conclusion Genetic factors contribute to a substantial proportion of blood pressure variance. In this study, the effect of polymorphisms of ADD1, AGT, AT1R and GNB3 explained a very small proportion of the heritability of blood pressure traits. As new genes associated with blood pressure are localized in the future, their effect on blood pressure variance should be calculated.