Miracle-dz/UniFAR-FTUs huggingface dataset:
Oligodendrocyte survival, loss and birth in lesions of chronic-stage multiple sclerosis.

One of the hallmarks of the human demyelinating disease multiple sclerosis is the inability to compensate adequately for the loss of myelin and of oligodendrocytes, the myelin-forming cells of the CNS. Oligodendrocyte precursor cells, a potential source of oligodendrocytes, have been identified in lesions of chronic multiple sclerosis, but it is not known whether they develop into new, fully differentiated oligodendrocytes, capable of remyelination. Sections of post-mortem multiple sclerosis tissue were therefore immunolabelled with antibodies to galactocerebroside (GalC), the first oligodendrocyte-specific molecule to be expressed by differentiating oligodendrocyte precursor cells, and myelin oligodendrocyte glycoprotein (MOG), a marker for mature oligodendrocytes. In total, 23 lesions from 15 subjects with chronic progressive multiple sclerosis were analysed. The immunolabelling revealed that chronic multiple sclerosis lesions contain only small numbers of immature, process-bearing, GalC-positive oligodendrocytes (0-2 cells/mm(2) in 10 micrometer thick sections); they had a relatively large, pale nucleus (maximum diameter: 9.9 +/- 0.9 micrometer). Although they appeared to make contact with surrounding demyelinated axons, most immature oligodendrocytes appeared not to be engaged in myelination. These findings suggest that oligodendrocyte differentiation of precursor cells is a rare event in chronic multiple sclerosis, which is consistent with the general failure of myelin repair during the later stages of this disease. The lesions in the collection, in particular those with recent demyelinating activity, contained another distinct population of oligodendrocytes. It consisted of small, round cells with a small, dense nucleus (maximum diameter: 6.8 +/- 0.8 micrometer) that expressed both GalC and MOG but lacked processes, suggesting that these cells were mature oligodendrocytes that had survived the loss of their myelin sheaths, i.e. they were demyelinated oligodendrocytes. In the most recent lesions in the collection, the demyelinated oligodendrocytes were found in large numbers throughout the centre of the lesion (up to 700 cells/mm(2)), while in the older lesions they were found only at the edges. Moreover, when the borders of these older lesions still contained numerous macrophages, they tended to contain more demyelinated oligodendrocytes than those lacking macrophages. These findings suggest that mature, demyelinated oligodendrocytes gradually disappear from lesion areas with increasing age of the lesion. The present study thus suggests that the failure of myelin repair in at least some cases of chronic multiple sclerosis is due to (i) the loss of demyelinated oligodendrocytes from lesion areas and (ii) the failure of the oligodendrocyte precursor population to expand and generate new oligodendrocytes. Gaining further insight into these processes may prove crucial for the development of remyelination promoting strategies.
Book Review: Ontological Semantics, by Sergei Nirenburg and Victor Raskin

In this book, Nirenburg and Raskin present an important body of work in computational linguistics that they and their colleagues have been developing over the past 20 years. For a unifying perspective, they organize their assumptions, theories, and techniques around the theme of ontological semantics. Along the way, they critique many alternative views of semantics, which they distinguish from their own. Their analyses contribute to a much-needed debate about the history and future of computational linguistics, but to preserve some balance, teachers and students should keep a few of the alternatives on their reference shelf. The book is divided into two parts: a philosophical part I and a practical part II. The first part consists of an introductory chapter 1 and four chapters that survey important but controversial issues about linguistics, both theoretical and computational. In those chapters, the authors make a good case for their version of ontological semantics, but the alternatives are not treated in detail. In part II, the authors present their text-meaning representation (TMR) and demonstrate how it is used in language analysis. Any discussion of technical material must use some notation, and TMR is sufficiently flexible to illustrate a wide range of semantic-based methods that could be adapted to many other formalisms. For most readers, part II would be the more important. Chapter 1 is a good 25-page overview of computational linguistics with an emphasis on semantics. Students and novices, however, need examples, and none are given until chapter 6. The authors suggest that ‘‘a well-prepared and/or uninterested reader’’ skip the remainder of part I and go straight to chapter 6, which begins with an excellent five-page example. The authors follow that advice when they teach courses from this text. In Chapter 2, the authors present their ‘‘Prolegomena to the Philosophy of Linguistics. ’’ Their ideas are well taken, and some are as old as Socrates: Examine the assumptions, challenge conventional wisdom, and test conclusions against experience. The basis of their approach is what they call the four components of a scientific theory:
Monetary policy rules based on real-time data

In recent years, simple policy rules have received attention as a means to a more transparent and effective monetary policy. Often, however, the analysis is based on unrealistic assumptions about the timeliness of data availability. This permits rule specifications that are not operational and ignore difficulties associated with data revisions. This paper examines the magnitude of these informational problems using Taylor's rule as an example. I demonstrate that the real-time policy recommendations differ considerably from those obtained with the ex post revised data and are revised substantially even a year after the relevant quarter. Further, I show that estimated policy reaction functions obtained using the ex post revised data can yield misleading descriptions of historical policy. Using Federal Reserve staff forecasts I show that in the 1987-1992 period simple forward-looking specifications describe policy better than comparable Taylor-type specifications, a fact that is largely obscured when the analysis is based on the ex post revised data.
Interference Coordination in Cellular OFDMA Networks

Orthogonal frequency division multiple access is the basis for several emerging mobile communication systems. Prominent examples are the 3GPP long term evolution as the successor of UMTS high-speed packet access and the IEEE 802.16 system, advanced by the WiMax forum. On a system level, OFDMA is basically a combination of time and frequency division multiple access. In cellular TDM/FDM systems, inter-cell interference is a major issue that traditionally has been solved by avoiding the use of the same frequency bands in adjacent cells. However, this solution incurs a waste of precious frequency resources. An attractive alternative is the use of beamforming antennas in combination with interference coordination mechanisms, where the transmission of adjacent base stations is coordinated to minimize inter-cell interference. Interference coordination is an important aspect of the system level, which influences many other issues, such as network planning or scheduling mechanisms. In this article, we give an overview of interference coordination as it would apply, for example, to IEEE 802.16e and review the relevant literature. We also discuss and compare interference coordination algorithms, which can be based either on global system knowledge or purely on local system knowledge.
IHS-RD-Belarus at SemEval-2016 Task 1: Multistage Approach for Measuring Semantic Similarity

This paper describes the system for rating the degree of semantic equivalence between two text snippets developed by IHS-RD-Belarus for the SemEval 2016 STS shared task (Task 1). To predict the human ratings of text similarity we use a support vector regression model with multiple features representing similarity and difference scores calculated for each pair of sentences
Speech and Language Processing: an Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Computational Lexical Semantics 19.1 Word Sense Disambiguation: Overview

He was white and shaken, like a dry martini. This chapter introduces a series of topics related to computing with word meanings, or computational lexical semantics. Roughly in parallel with the sequence of topics in Ch. 18, we'll introduce computational tasks associated with word senses, relations among words, and the thematic structure of predicate-bearing words. We begin with word sense disambiguation, the task of examining word tokens in context and determining which sense of each word is being used. WSD is a task with a long history in computational linguistics, and as we will see, is a non-trivial undertaking given the somewhat elusive nature of many word senses. Nevertheless, there are robust algorithms that can achieve high levels of accuracy given certain reasonable assumptions. We next look at algorithms for computing relationships between words, with a particular focus on word similarity, and the hypernym, hyponym, and meronym WordNet relations introduced in Ch. 18. Relations such as these play important roles in applications such as question answering, natural language generation, automatic essay grading and plagiarism detection. Finally, we describe algorithms for semantic role labeling, also known as case role or thematic role assignment. These algorithms generally use information extracted from parses of the kind introduced in Ch. 12 to assign semantic roles such as AGENT, THEME and INSTRUMENT to the phrases in a sentence with respect to particular predicates. Our discussion of compositional semantic analyzers in Ch. 17 pretty much ignored the issue of lexical ambiguity. It should be clear by now that this is an unreasonable
So Much to Do Before I Sleep: Investigating Adolescent-Perceived Barriers and Facilitators to Sleep

Adolescent sleep deprivation is a pressing public health issue in the United States as well as other countries. The contexts of adolescents’ lives are changing rapidly, but little is known about the factors that adolescents themselves believe affect their sleep. This study uses a social-ecological framework to investigate multiple levels of perceived influence on sleep patterns of urban adolescents. Data were drawn from interviews and surveys conducted in three California public high schools. Most participants identified homework as their primary barrier to sleep, particularly those engaged in procrastinating, multitasking, or those with extracurricular demands. Results indicate that the home context has important implications for adolescent sleep, including noise, household rules, and perceived parent values. These findings identify important areas for future research and intervention, particularly regarding the roles of parents.
A study on information transfer of international crude oil futures price base on VAR-GARCH-BEKK model

Crude oil future price plays an important role in the world oil price mechanism. The crude oil future price changes will transfer information to other oil market through Volatility Spillover Effects, so the crude oil future price has been the focus of attention. From the situation of recent years, the oil future market develops rapidly and future markets play a price in the discovery function in some way. The future price has become a benchmark in oil market. In order to further reveal the price formation mechanism, the transmission and market efficiency of the oil future markets, as well as the efficiency of information transfer between the future and spot market, this paper is based on the analysis of theories and methods. It selects the NYMEX WTI crude oil future prices and WTI crude oil spot price for representative to analyze the price volatility characteristics, basic statistical characteristics of earnings, and long-run equilibrium relationship between the two markets.
A Genome-Wide Association Study (GWAS) for Bronchopulmonary Dysplasia

OBJECTIVE: Twin studies suggest that heritability of moderate-severe bronchopulmonary dysplasia (BPD) is 53% to 79%, we conducted a genome-wide association study (GWAS) to identify genetic variants associated with the risk for BPD. METHODS: The discovery GWAS was completed on 1726 very low birth weight infants (gestational age = 250–296/7 weeks) who had a minimum of 3 days of intermittent positive pressure ventilation and were in the hospital at 36 weeks’ postmenstrual age. At 36 weeks’ postmenstrual age, moderate-severe BPD cases (n = 899) were defined as requiring continuous supplemental oxygen, whereas controls (n = 827) inhaled room air. An additional 795 comparable infants (371 cases, 424 controls) were a replication population. Genomic DNA from case and control newborn screening bloodspots was used for the GWAS. The replication study interrogated single-nucleotide polymorphisms (SNPs) identified in the discovery GWAS and those within the HumanExome beadchip. RESULTS: Genotyping using genomic DNA was successful. We did not identify SNPs associated with BPD at the genome-wide significance level (5 × 10−8) and no SNP identified in previous studies reached statistical significance (Bonferroni-corrected P value threshold .0018). Pathway analyses were not informative. CONCLUSIONS: We did not identify genomic loci or pathways that account for the previously described heritability for BPD. Potential explanations include causal mutations that are genetic variants and were not assayed or are mapped to many distributed loci, inadequate sample size, race ethnicity of our study population, or case-control differences investigated are not attributable to underlying common genetic variation.
A multi-wavelength study of the IRAS Deep Survey galaxy sample - II. The far-IR properties

Context. The luminosity function (LF) is a basic tool in the study of galaxy evolution since it constrains galaxy formation models. The earliest LF estimates in the IR and far-IR spectral ranges seem to suggest strong evolution. Deeper samples are needed to confirm these predictions. We have a useful IR data set, which provides a direct link between IRAS and ISO surveys, and the forthcoming deeper Spitzer Space Telescope and Akari cosmological surveys, to address this issue. Aims. This data set allows us to derive the 60 μ m local LF to sensitivity levels 10 times deeper than before, to investigate evolutionary effects up to a redshift of 0.37, and, using the 60/15 μ m bi-variate method, to analyze the poorly known 15 μ m local LF of galaxies. Methods. We exploited our ISOCAM observations of the IRAS Deep Survey (IDS) fields, to correct the $60~\mu$m fluxes for confusion effects and observational biases. We find indications of a significant incompleteness of the IDS sample, still one of the deepest far-IR selected galaxy samples, below $\simeq$$80~$mJy. We have reliable identifications and spectroscopic redshifts for 100% of a complete subsample comprising 56 sources with $S(60~\mu {\rm m})> 80$ mJy. Results. With our spectroscopic coverage we construct the 60 μ m LF for a sample complete down to 80 mJy. This LF extends over three orders of magnitude in luminosity, from 9 up to more than 12 in $\log(L_{60}/L_{\odot})$. Despite the fact that the redshift range of our sample exceeds $z=0.3$, the $V/V_{\rm max}$ test gives $\langle V/V_{\rm max} \rangle$ = 0.51 ± 0.06, consistent with a uniform distribution of sources. A more direct test, whereby the LF was measured in each of four different redshift intervals, does not point out any signature of evolution. On the other hand, the rest-frame 15 μ m local LF we derive, extends up to $\log(L_{15}/L_{\odot})=12$ and predicts 10 times more sources at $\log(L_{15}/L_{\odot})=11$ than before.
Preparing Introverted Learners in Elementary Classrooms for a World that Privileges Extroversion

Social interaction makes up a large part of society; people are constantly required to communicate with others whether that is through face-to-face conversations, phone or e-mail (Dow, 2013). Shockingly nearly half of society identify as introverts, a personality type which views social interactions as intimidating, overwhelming, scary and less preferred (Dow, 2013). It is important to consider ways in which educators can effectively prepare introverted students to be successful in an extroverted world. The purpose of this study is to learn how teachers meet the needs of introverted learners while sufficiently preparing them for the world that privileges extroversion. I explored literature and interviewed teachers finding that flexibility in teaching and encouragement are important in introverted students school success. Further, the use of differentiated instruction and assessment best supports introverted students’ learning styles. Differentiated instruction allows introvert students to build confidence in their abilities. Students can access information and demonstrate their learning in ways they are most comfortable with, leading to confidence in verbally sharing ideas. This study is important to the education community because introverted students are misunderstood in the classroom, leading teachers to ineffectively prepare them for an extroverted world.
Time management and attitude towards science as predictors of academic success in an enabling science subject: A preliminary exploratory study

The number of males entering higher education via an enabling pathway is increasing with noticeable diversity in age groups. Previous research undertaken by the authors began exploring the factors that inhibit or enhance the male experience within an enabling course. This paper will expand upon this research with a deeper focus into the male experience through personalised accounts derived from individual interviews. Using qualitative methodology and narrative inquiry, the findings provide a deeper understanding of the issues that males of different ages face when creating a new identity as a university student. The lens of transformative theory will underpin this research through exploring frames of reference that align to the students’ experiences. Portraits are woven into the narrative
Graphical models for marked point processes based on local independence

Summary. A new class of graphical models capturing the dependence structure of events that occur in time is proposed. The graphs represent so‐called local independences, meaning that the intensities of certain types of events are independent of some (but not necessarilly all) events in the past. This dynamic concept of independence is asymmetric, similar to Granger non‐causality, so the corresponding local independence graphs differ considerably from classical graphical models. Hence a new notion of graph separation, which is called δ‐separation, is introduced and implications for the underlying model as well as for likelihood inference are explored. Benefits regarding facilitation of reasoning about and understanding of dynamic dependences as well as computational simplifications are discussed.
A machine learning based approach for the detection and recognition of Bangla sign language

Speech impaired people are detached from the mainstream society due to the lacking of proper communication aid. Sign language is the primary means of communication for them which normal people do not understand. In order to facilitate the conversation conversion of sign language to audio is very necessary. This paper aims at conversion of sign language to speech so that disabled people have their own voice to communicate with the general people. In this paper, Hand Gesture recognition is performed using HOG (Histogram of Oriented Gradients) for extraction of features from the gesture image and SVM (Support Vector Machine) as classifier. Finally, predict the gesture image with output text. This output text is converted into audible sound using TTS (Text to Speech) converter.
Interesting event detection through hall of fame rankings

Everything is relative. Cars are compared by gas per mile, websites by page rank, students based on GPA, scientists by number of publications, and celebrities by beauty or wealth. In this paper, we study the characteristics of such entity rankings based on a set of rankings obtained from a popular Web portal. The obtained insights are integrated in our approach, coined Pantheon. Pantheon maintains sets of top-k rankings and reports identified changes in a way that appeals to users, using a novel combination of different characteristics like competitiveness, information entropy, and scale of change. Entity rankings are assembled by combining entity type attributes with data-driven categorical constraints and sorting criteria on numeric attributes. We report on the results of an experimental evaluation using real-world data obtained from a basketball statistics website.
Multivariate Extreme Value Theory And Its Usefulness In Understanding Risk

Abstract This paper gathers recent results in the analysis of multivariate extreme values and illustrates their actuarial application. We review basic and essential background on univariate extreme value theory and stochastic dependence and then provide an introduction to multivariate extreme value theory. We present important concepts for the analysis of multivariate extreme values and collect research results in this area. We draw particular attention to issues related to extremal dependence and show the importance of model selection when fitting an upper tail copula to observed joint exceedances. These ideas are illustrated on four data sets: loss amount and allocated loss adjustment expense under insurance company indemnity claims, lifetimes of pairs of joint and lastsurvivor annuitants, hurricane losses in two states, and returns on two stocks. In each case the extremal dependence structure has an important financial impact.
A Real-Time Vehicle Navigation Algorithm in Sensor Network Environments

In a large-scale wireless sensor traffic network, collecting and processing of the global real-time traffic information are often unreliable. Making real-time navigation decision becomes an arduous task. To address this issue, an efficient wireless-sensor-network-based real-time vehicle navigation algorithm is proposed, in which multiple local traffic information is considered to make a navigation decision in a quick and accurate way. At the same time, a general distance metric is defined for the processing of both exact and fuzzy data. In addition, the algorithm can provide various navigation decisions according to the choice of different attributes to meet the diverse navigation requirements of drivers. Simulation results show the suitability and efficiency of the proposed algorithm.
Evaluating Mid-air List Interaction for Spatial Audio Interfaces

Selecting items from lists is a common task in many applications. For wearable devices where no display is available, list selection can be challenging. To explore potential solutions we present four user studies evaluating mid-air gestures to interact with lists in an eyes-free interface. We found that a spatialized audio list in the shape of a 110~degree arc angled towards the dominant hand was a comfortable and usable layout for most users. A selection takes less than 10.6 seconds on average and error rates are below 4% when users locate and select an item in an unknown, unordered list of 20 items. For lists of 10 items the mean selection time is 5.5 seconds or less, and error rates drop below 1.4%. We compared monophonic to binaural playback of feedback sounds (musicons) and found no statistical difference for task completion times or error rates between the conditions. We also implemented and evaluated a music player application to showcase spatial audio list selection in an applied scenario.