Miracle-dz/UniFAR-FTUs huggingface dataset:
GeoSense An open publishing platform for visualization , sharing , and social analysis of geospatial data

Current systems for geospatial data visualization demand that users have expert level knowledge, advanced technical capability, and design acumen to produce results. These inherent complexities prevent many users from uncovering deeper meaning or hidden narratives within geospatial data. We suggest that geovisualization can be made more approachable while also leveraging collective intelligence from connected communities through shared data and analysis. To address this, we present GeoSense: an open publishing platform for information visualization, social collaboration, and geospatial analysis of multivariate data sources. We provide a robust suite of tools for users who have little knowledge of the intricacies of GIS and are looking to better understand the spatial and temporal qualities of geospatial data. GeoSense proposes that design may be used as a lens to enhance human understanding and provide insight where new and provocative discoveries can be uncovered through visual analysis and shared cognition. Thesis supervisor: Dr. Hiroshi Ishii Jerome B. Wiesner Professor of Media Arts and Sciences Associate Director, MIT Media Lab Program in Media Arts and Sciences GeoSense An open publishing platform for visualization, sharing, and social analysis of geospatial data.
Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment

A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition is often treated with a stent that diverts the blood flow from the aneurysm sac back to the original vessel. Prior to treatment, neuroradiologists need to decide on the optimal stent configuration and judge the long‐term rupture risk, for which blood flow information is essential. Modern patient‐specific simulations can model the hemodynamics for various stent configurations, providing important indicators to support the decision‐making process. However, the necessary visual analysis of these data becomes tedious and time‐consuming, because of the abundance of information. We introduce a comprehensive comparative visualization that integrates morphology with blood flow indicators to facilitate treatment assessment. To deal with the visual complexity, we propose a details‐on‐demand approach, combining established medical visualization techniques with innovative glyphs inspired by information visualization concepts. In an evaluation we have obtained informal feedback from domain experts, gauging the value of our visualization.
Stability analysis of M-dimensional asynchronous swarms with a fixed communication topology

Coordinated dynamical swarm behavior occurs when certain types of animals forage for food or try to avoid predators. Analogous behaviors can occur in engineering systems (e.g. in groups of autonomous mobile robots or UAVs). In this paper, we study a model of an M-dimensional (M /spl ges/ 2) asynchronous swarm with a communication topology, where each member only communicate with fixed neighbors, to provide conditions under which collision-free convergence can be achieved with finite-size swarm members that have proximity sensors and neighbor position sensors that only provide delayed position information. Moreover, we give conditions under which an M-dimensional asynchronous mobile swarm following an "edge-leader" can maintain cohesion during movements even in the presence of sensing delays and asynchronism, and analyze the swarm movement flexibility. Such stability analysis is of fundamental importance if one wants to understand the coordination mechanisms for groups of autonomous vehicles or robots where inter-member communication channels are less than perfect and collisions must be avoided.
Just do it: simple monadic equational reasoning

One of the appeals of pure functional programming is that it is so amenable to equational reasoning. One of the problems of pure functional programming is that it rules out computational effects. Moggi and Wadler showed how to get round this problem by using monads to encapsulate the effects, leading in essence to a phase distinction - a pure functional evaluation yielding an impure imperative computation. Still, it has not been clear how to reconcile that phase distinction with the continuing appeal of functional programming; does the impure imperative part become inaccessible to equational reasoning? We think not; and to back that up, we present a simple axiomatic approach to reasoning about programs with computational effects.
Nanofluidic flowmeter using carbon sensing element

The field of nanofluidics dealing with nL fluids is growing, and sensors for monitoring ever smaller flow rates (/spl sim/nL/min) are needed. This paper presents a new, sensitive micromachined thermal sensor for measuring flow rates. The integrated sensor uses a high-TCR (temperature coefficient of resistance) carbon sensing element obtained from ion-implanted parylene. The ion-implanted carbon element has a high temperature coefficient of resistance of -2%//spl deg/C and is embedded in a freestanding microchannel suspended from the substrate. The developed sensor has been characterized for flow measurements with a volumetric flow sensitivity of 380 /spl mu/V/(nl/min) under a constant current bias with a power consumption of only 28 /spl mu/W. To our knowledge, this is the first such nanofluidic carbon flow sensor and its sensitivity is better than any of flow sensors reported to date.
Properties of Alanine Dehydrogenase and Aspartase from Propionibacterium freudenreichii subsp. shermanii

During lactate fermentation by Propionibacterium freudenreichii subsp. shermanii ATCC 9614, the only amino acid metabolized was aspartate. After lactate exhaustion, alanine was one of the two amino acids to be metabolized. For every 3 mol of alanine metabolized, 2 mol of propionate, 1 mol each of acetate and CO2, and 3 mol of ammonia were formed. The specific activity of alanine dehydrogenase was 0.08 U/mg of protein during lactate fermentation, and it increased to 0.9 U/mg of protein after lactate exhaustion. Alanine dehydrogenase and aspartase, key enzymes in the metabolism of alanine and aspartate, respectively, were partially purified, and some of their properties were studied. Alanine dehydrogenase had a pH optimum of 9.2 to 9.6 and high Km values for both NAD+ (1 to 4 mM) and alanine (7 to 20 mM). Activity was inhibited by low concentrations of pyruvate and NADH. The pH optimum of aspartase decreased from ∼7.5 to ∼6.4 when the MgCl2 and aspartate concentrations were decreased. Plots of aspartate concentration versus activity showed either hyperbolic or sigmoidal kinetics (interaction coefficient, up to a value of 3.1), depending on pH and MgCl2 concentration. MgCl2 was either an activator or an inhibitor, depending on pH and its concentration. Aspartase activity was inhibited by low concentrations of fumarate. The properties of alanine dehydrogenase and aspartase are consistent with the finding that aspartate is metabolized during lactate fermentation, while alanine is only fermented after lactate exhaustion and then at a slow rate.
Sequence Kernel Association Test for Survival Traits

Rare variant tests have been of great interest in testing genetic associations with diseases and disease‐related quantitative traits in recent years. Among these tests, the sequence kernel association test (SKAT) is an omnibus test for effects of rare genetic variants, in a linear or logistic regression framework. It is often described as a variance component test treating the genotypic effects as random. When the linear kernel is used, its test statistic can be expressed as a weighted sum of single‐marker score test statistics. In this paper, we extend the test to survival phenotypes in a Cox regression framework. Because of the anticonservative small‐sample performance of the score test in a Cox model, we substitute signed square‐root likelihood ratio statistics for the score statistics, and confirm that the small‐sample control of type I error is greatly improved. This test can also be applied in meta‐analysis. We show in our simulation studies that this test has superior statistical power except in a few specific scenarios, as compared to burden tests in a Cox model. We also present results in an application to time‐to‐obesity using genotypes from Framingham Heart Study SNP Health Association Resource.
Deprivatization of Disbelief?: Non-Religiosity and Anti-Religiosity in 14 Western European Countries

Abstract This article aims to move beyond media discourse about “new atheism” by mapping and explaining anti-religious zeal among the public at large in 14 Western European countries. We analyze data from the International Social Survey Program, Religion III, 2008, to test two theories about how country-level religiousness affects anti-religiosity and its social bases: a theory of rationalization and a theory of deprivatization of disbelief. Hypotheses derived from the former are contradicted, whereas those derived from the latter are largely confirmed. Anti-religiosity is strongest among disbelievers and among the higher educated in the most religious countries and among the older generations in today's most secularized countries.
Kinetics of Circulating Plasma Cell-Free DNA in Paediatric Classical Hodgkin Lymphoma

Levels of plasma cell-free DNA (cfDNA) of a large series of children with classical Hodgkin lymphoma (cHL) were evaluated and analyzed at diagnosis and during chemotherapy treatment in relation with clinical characteristics. CfDNA levels in cHL patients were significantly higher compared with controls (p=0.002). CfDNA at diagnosis was correlated with presence of B symptoms (p=0.027) and high erythrocyte sedimentation rate (p=0.049). We found that the increasing of plasma cfDNA after first chemotherapy cycle seems to be associated with a worse prognosis (p=0.049). Levels of plasma cfDNA might constitute an interesting non-invasive tool in cHL patients' management.
Epstein-Barr Virus EBNA-3C Is Targeted to and Regulates Expression from the Bidirectional LMP-1/2B Promoter

ABSTRACT Epstein-Barr virus (EBV) nuclear antigen 3C (EBNA-3C) is essential for EBV-mediated immortalization of human B lymphocytes and regulates both the cell cycle and transcription. Transient reporter gene assays have implicated a pivotal role for EBNA-3C in the regulation of transcription of the majority of latency-associated genes expressed during the EBV growth program, including the viral oncoprotein LMP-1. To examine the regulation of latency gene expression by EBNA-3C, we generated an EBV-positive cell line that inducibly expresses EBNA-3C. This cell line allowed us to examine expression from the endogenous latency gene promoters in the context of an actual latent infection and the presence of other EBNA proteins, in particular EBNA-2, which is presumed to coregulate transcription with EBNA-3C. EBNA-3C induced the expression of both LMP-1 and LMP-2B mRNAs from the bidirectional LMP-1/LMP-2B promoter. In contrast, no effect was seen on expression from the common EBNA promoter Cp, which is responsive to EBNA-3C in reporter assays. Activation of LMP expression was not the consequence of increases in EBNA-2, PU.1 or Spi-B transcription factors, all of which are believed to be critical for activation of LMP-1. Chromatin immunoprecipitation assays furthermore indicated that EBNA-3C is present at the bidirectional LMP-1/LMP-2B promoter. These results indicate that EBNA-3C directly activates the expression of LMP-1 and LMP-2B but is unlikely to significantly regulate EBNA expression via Cp under normal growth conditions.
Model-based Clustering With Probabilistic Constraints

The problem of clustering with constraints is receiving increasing attention. Many existing algorithms assume the specifled constraints are correct and consistent. We take a new approach and model the uncertainty of constraints in a principled manner by treating the constraints as random variables. The efiect of specifled constraints on a subset of points is propagated to other data points by biasing the search for cluster boundaries. By combining the a posteriori enforcement of constraints with the log-likelihood, we obtain a new objective function. An EM-type algorithm derived by variational method is used for e‐cient parameter estimation. Experimental results demonstrate the usefulness of the proposed algorithm. In particular, our approach can identify the desired clusters even when only a small portion of data participates in constraints.
Tackling soil diversity with the assembly of large, complex metagenomes

Significance Investigations of complex environments rely on large volumes of sequence data to adequately sample the genetic diversity of a microbial community. The assembly of short-read data into longer, more interpretable sequence currently is not possible for much of the research community because it requires specialized computational facilities. We present approaches that make de novo assembly of complex metagenomes more accessible. These approaches scale data size with community richness and subdivide the data into tractable subsets representing individual species. We applied these methods toward the assembly of two large soil metagenomes to identify important metagenomic references and show that considerably more data are needed to study the terrestrial microbiome comprehensively. The large volumes of sequencing data required to sample deeply the microbial communities of complex environments pose new challenges to sequence analysis. De novo metagenomic assembly effectively reduces the total amount of data to be analyzed but requires substantial computational resources. We combine two preassembly filtering approaches—digital normalization and partitioning—to generate previously intractable large metagenome assemblies. Using a human-gut mock community dataset, we demonstrate that these methods result in assemblies nearly identical to assemblies from unprocessed data. We then assemble two large soil metagenomes totaling 398 billion bp (equivalent to 88,000 Escherichia coli genomes) from matched Iowa corn and native prairie soils. The resulting assembled contigs could be used to identify molecular interactions and reaction networks of known metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes Orthology database. Nonetheless, more than 60% of predicted proteins in assemblies could not be annotated against known databases. Many of these unknown proteins were abundant in both corn and prairie soils, highlighting the benefits of assembly for the discovery and characterization of novelty in soil biodiversity. Moreover, 80% of the sequencing data could not be assembled because of low coverage, suggesting that considerably more sequencing data are needed to characterize the functional content of soil.
Robust Minimal Recursion Semantics

Deep and shallow processing techniques have complementary strengths and weaknesses. There are various ways in which deep and shallow techniques can be combined in practical systems to take advantage of the strengths of each approach. In this paper, I argue for the advantages of using a semantic representation as the interface between various types of deep and shallow processing. I illustrate how with a flat semantics approach, shallow processing can be regarded as producing a semantics which is underspecified with respect to deeper processing, but fully compatible with it. I describe the notion of specificity which results and illustrate its connection with specificity in typed feature structures. I also show how semantic composition rules designed for deep formalisms can be adapted to shallow processing. Some practical experiments are described using the tag sequence grammar from the RASP tools and the LinGO English Resource Grammar.1
Adaptive control of MEMS gyroscope using backstepping approach

In this paper, a new adaptive control system for MEMS (Microelectromechanical systems) vibratory gyroscope sensor is presented based on the backstepping approach. First, the dynamic model of a two-axis MEMS vibratory gyroscope is established based on Lagrange-Maxwell electromechanical equations. Next, backstepping design approach is used to drive the trajectory tracking errors to converge to zero rapidly with global asymptotical stability. However, the gyroscope parameters are difficult to obtain in advance in practical applications. Therefore, adaptive laws are derived to adapt the value of the parameter estimates in real-time, and an adaptive backstepping control law is implemented. Moreover, the unknown parameters may be identified, including the ambient angular rate, if the PE (persistent excitation) condition is satisfied. Finally, simulation results demonstrate the effectiveness of the proposed control scheme in terms of guaranteed stability and excellent tracking performance in the presence of unknown parameters and disturbances.
MicroRNA 92b Controls the G1/S Checkpoint Gene p57 in Human Embryonic Stem Cells

Human embryonic stem (ES) cells exhibit a shorter G1 cell cycle phase than most somatic cells. Here, we examine the role of an abundant, human ES cell‐enriched microRNA, miR‐92b, in cell cycle distribution. Inhibition of miR‐92b in human ES cells results in a greater number of cells in the G1 phase and a lower number in the S phase. Conversely, overexpression of miR‐92b in differentiated cells results in a decreased number of cells in G1 phase and an increased number in S‐phase. p57, a gene whose product inhibits G1 to S‐phase progression, is one of the predicted targets of miR‐92b. Inhibition of miR‐92b in human ES cells increases p57 protein levels, and miR‐92b overexpression in differentiated cells decreases p57 protein levels. Furthermore, miR‐92b inhibits a luciferase reporter construct that includes part of the 3′ untranslated region of the p57 gene containing the predicted target of the miR‐92b seed sequence. Thus, we show that the miRNA miR‐92b directly downregulates protein levels of the G1/S checkpoint gene p57. STEM CELLS 2009;27:1524–1528
Software Structure Analysis Using Network Theory

Software structure analysis is crucial in software testing. Using complex network theory, we present a series of methods and build a two-layer network model for software analysis, including network metrics calculation and features extraction. Through identifying the critical functions and reused modules, we can reduce nearly 80% workload in software testing on average. Besides, the structure network shows some interesting features that can assist to understand the software more clearly.
What can linguistics contribute to event extraction

This paper examines the question of how a linguistic analysis of a written document can contribute to identifying, tracking and populating the “eventualities” that are presented in the document, either directly or indirectly, and representing degrees of belief concerning them. It is our view that the role of lexical analysis (as exemplified in the research carried out in the FrameNet project) is greater than usually assumed, so this paper is partly an attempt to clarify the boundary between on the one hand the information that can be derived on the basis of linguistic knowledge alone (composed of lexical meanings and the meanings of grammatical constructions) and on the other hand, reasoning based on beliefs about the source of a document, world knowledge, and “common sense”. Since the general linguistic processes described in this paper will apply to eventualities in general (by which we mean acts, happenings, states of affairs, and relations, whether real, proposed, imagined, or denied ), our presentation will emphasize the linguistic processes themselves. In particular, we show that the kind of information produced by the lexicon-building project FrameNet can have a special role in contributing to text understanding, starting from the basic facts of the combinatorial properties of frame-bearing words (verbs, nouns, adjectives and prepositions) and arriving at the means of recognizing the anaphoric properties of specific unexpressed event participants, for all parts of speech, in defining a new layer of anaphora resolution and text cohesion. Using as a starting point the challenge text presented in the call for this workshop (hereafter referred to as the Hijacking text), we show the points at which a thorough linguistic analysis can articulate with the kind of simulation formalism demonstrated in X-schema diagram, Figure 2 , which itself incorporates a great deal of world knowledge connected with the events introduced in the Hijacking text.
9 The Voicelessness of Literature: Reorganizing National Heritage and Evidence-based Research on Literature

In the early 1920s, the reorganization of national heritage (zhengli guogu 整理国故) emerged in Chinese academia and swept across the country. In 1923, Zhang Pengchun 张彭春 (1892–1957) realized, “Chinese ‘learning’ all leans towards history—‘I am one who is fond of antiquity and earnest in seeking knowledge there. ’ The publicly recognized scholars of today, such as Liang [Qichao] and Hu [Shi], also devote themselves to reorganizing ancient texts. ”1 Liang Qichao had already made his reputation, but Hu Shi’s role as a ‘publicly recognized scholar’ was fairly new. Over the next several years, Liang Qichao and Hu Shi fundamentally differed in their attitudes towards traditional Chinese culture, and in many of their specific ideas, but both promoted national learning (guoxue 国学), which made its attractiveness that much greater. Zhang also wanted to research national learning, but knew his “foundation in ancient works is shallow. ” He still hoped “I can serve as an experiment for future students so they would know whether it is possible to research national learning without having read ancient texts. ”2 Allowing someone who has not read ancient texts to research national learning seemed a bit too romantic, but Zhang pointed out the attraction of national learning and confirms the contemporary recognition of the necessity for and validity of the subject.
An efficient mesh simplification method with feature detection for unstructured meshes and Web graphics

We present an efficient method of mesh simplification for geometric 3D models. The transmission of 3D models on the Internet is an important task. The data size of a 3D model is usually large to enable more detail to be represented. Hence, it is necessary to represent the 3D model while keeping the data size small and preserving its features, even if the meshes that constitute the model are unstructured. Although there are many methods for simplifying the meshes, most of them are time-consuming. Our approach is to obtain an adequate simplified model in a short amount of time. Therefore, the model provider can check the simplified result interactively before uploading to the server. After transmitting the simplified model, if the user at the client needs to get more details, by transmitting some necessary information, the progressively increasing model detail and the original model without losses could be reconstructed.