Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyperpolarized 3He magnetic resonance imaging ventilation defects in asthma: relationship to airway mechanics

In patients with asthma, magnetic resonance imaging (MRI) provides direct measurements of regional ventilation heterogeneity, the etiology of which is not well‐understood, nor is the relationship of ventilation abnormalities with lung mechanics. In addition, respiratory resistance and reactance are often abnormal in asthmatics and the frequency dependence of respiratory resistance is thought to reflect ventilation heterogeneity. We acquired MRI ventilation defect maps, forced expiratory volume in one‐second (FEV1), and airways resistance (Raw) measurements, and used a computational airway model to explore the relationship of ventilation defect percent (VDP) with simulated measurements of respiratory system resistance (Rrs) and reactance (Xrs). MRI ventilation defect maps were experimentally acquired in 25 asthmatics before, during, and after methacholine challenge and these were nonrigidly coregistered to the airway tree model. Using the model coregistered to ventilation defect maps, we narrowed proximal (9th) and distal (14th) generation airways that were spatially related to the MRI ventilation defects. The relationships for VDP with Raw measured using plethysmography (r = 0.79), and model predictions of Rrs>14 (r = 0.91, P < 0.0001) and Rrs>9 (r = 0.88, P < 0.0001) were significantly stronger (P = 0.005; P = 0.03, respectively) than with FEV1 (r = −0.68, P = 0.0001). The slopes for the relationship of VDP with simulated lung mechanics measurements were different (P < 0.0001); among these, the slope for the VDP‐Xrs0.2 relationship was largest, suggesting that VDP was dominated by peripheral airway heterogeneity in these patients. In conclusion, as a first step toward understanding potential links between lung mechanics and ventilation defects, impedance predictions were made using a computational airway tree model with simulated constriction of airways related to ventilation defects measured in mild‐moderate asthmatics.
jLDADMM: A Java package for the LDA and DMM topic models

In this technical report, we present jLDADMM---an easy-to-use Java toolkit for conventional topic models. jLDADMM is released to provide alternatives for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. jLDADMM is open-source and available to download at: this https URL
Micro-Optical Sectioning Tomography to Obtain a High-Resolution Atlas of the Mouse Brain

Better Brain Maps A high-resolution atlas of the complete neuronal connectivity in a whole brain should fundamentally advance our understanding of the organization and function of animal nervous systems. Now, A. Li. et al. (p. 1404, published online 4 November) describe an automated system, micro-optical sectioning tomography, that allowed three-dimensional mapping of the morphology and spatial location of neurons and traces of neurites in a whole, intact mouse brain. Acquisition of light microscopic data at 1-micrometer resolution for an entire mouse brain has been developed. The neuroanatomical architecture is considered to be the basis for understanding brain function and dysfunction. However, existing imaging tools have limitations for brainwide mapping of neural circuits at a mesoscale level. We developed a micro-optical sectioning tomography (MOST) system that can provide micrometer-scale tomography of a centimeter-sized whole mouse brain. Using MOST, we obtained a three-dimensional structural data set of a Golgi-stained whole mouse brain at the neurite level. The morphology and spatial locations of neurons and traces of neurites could be clearly distinguished. We found that neighboring Purkinje cells stick to each other.
Methodology for thermal diffusivity determination of metallic films at room temperature

An analytical model and a methodology for thermal diffusivity determination of metallic thin films at atmospheric pressure and room temperature are discussed. The analytical model is based on the one-dimensional heat conduction equation which allows us to estimate the thermal diffusivity value through the initial heating slope. To determine the thermal diffusivity value of metallic nanofilms, controlled micropulses were applied on them in order to measure changes in the electrical resistance and to estimate the corresponding changes of temperature in the transitory regime, where only the metallic film is heated. The proposed analytical model and the methodology were used to characterize Au and Al thin films thermally deposited on glass substrates. Preliminary results gave thermal diffusivity values of (40 ± 4) × 10-6 m2/s for an Au(40 nm) film, and (25 ± 3) ±10-6 m2/s for an Al(40 nm) film at room conditions (298 K, and atmospheric pressure).
An Clustering based AODV approach for MANET

A mobile ad hoc network (MANET) is a collection of wireless mobile nodes forming a temporary network without the aid of any fixed communication infrastructure. Due to limited resources, frequent network partitions and unpredictable topological changes, proactive clustering schemes incur high overheads in this environment. In this paper, we propose an on-demand, distributed clustering algorithm for MANETs based on an Ad hoc On-demand Distance Vector (AODV) routing protocol. The use of on-demand routing protocol information for clustering reduces clustering overhead because no clusters are maintained unless they are needed. The clustering algorithm’s stability was assessed using clustering metrics such as cluster head and cluster members lifetime. Based on this clustering scheme, a cluster-based routing protocol was proposed to add scalability to the AODV routing protocol. Using simulation, a comparison was made with a pure AODV protocol. Simulation experiments show that the scheme results in stable and scalable clusters and Cluster-AODV routing introduces less overhead than the pure AODV protocol without clustering.
The tyrosine phosphatase CD148 is excluded from the immunologic synapse and down-regulates prolonged T cell signaling

CD148 is a receptor-like protein tyrosine phosphatase up-regulated on T cells after T cell receptor (TCR) stimulation. To examine the physiologic role of CD148 in TCR signaling, we used an inducible CD148-expressing Jurkat T cell clone. Expression of CD148 inhibits NFAT (nuclear factor of activated T cells) activation induced by soluble anti-TCR antibody, but not by antigen-presenting cells (APCs) loaded with staphylococcal enterotoxin superantigen (SAg) or immobilized anti-TCR antibody. Immunofluorescence microscopy revealed that the extracellular domain of CD148 mediates its exclusion from the immunologic synapse, sequestering it from potential substrates. Targeting of the CD148 phosphatase domain to the immunologic synapse potently inhibited NFAT activation by all means of triggering through the TCR. These data lead us to propose a model where CD148 function is regulated in part by exclusion from substrates in the immunologic synapse. Upon T cell–APC disengagement, CD148 can then access and dephosphorylate substrates to down-regulate prolongation of signaling.
Can Herbal Medicine Cause Hematoma Enlargement of Hypertensive Intracerebral Hemorrhage within 24 hrs Time Window? A Retrospective Study of 256 Cases from a Single Center in China

A retrospective review was performed of consecutive patients presenting with HICH within 24 hours of ictus presenting between March 2008 and March 2013 who were diagnosed as having HICH by CT scan. Of the 256 patients who matched study inclusion standard, 43 patients hematoma was enlarged (16.8%). The number of the patients who did not take PBC or RBC herbal medicine, took the PBC herbal medicine, and took RBS herbal medicine was 19 (44.2%), 2 (4.7%), and 22 (51.2%) in hematoma enlargement group and 78 (36.6%), 26 (12.2%), and 109 (51.2%) in nonhematoma enlargement group, individually. There was no significant difference between two groups (P = 0.671). PBC and RBS herbal medicine did not increase the incidence of hematoma expansion of ICH within 24 hours after onset of symptom.
Computing graphical queries over XML data

The rapid evolution of XML from a mere data exchange format to a universal syntax for encoding domain-specific information raises the need for new query languages specifically conceived to address the characteristics of XML. Such languages should be able not only to extract information from XML documents, but also to apply powerful transformation and restructuring operators, based on a well-defined semantics. Moreover, XML queries should be natural to write and understand, as nontechnical persons also are expected to access the large XML information bases supporting their businesses. This article describes XML-GL, a graphical query language for XML data. XML-GL's uniqueness is in the definition of a graph-based syntax to express a wide variety of XML queries, ranging from simple selections to expressive data transformations involving grouping, aggregation, and arithmetic calculations. XML-GL has an operational semantics based on the notion of graph matching, which serves as a guideline both for the implementation of native processors, and for the adoption of XML-GL as a front-end to any of the XML query languages that are presently under discussion as the standard paradigm for querying XML data.
Angel Financing: Matching Start-Up Firms with Angel Investors

The hardest time to receive financing for a venture seems to be the time it is needed most: throughout the development and start-up stage. Unlike relatively established firms, new ventures do not have past performance to rely on to easily show potential investors its merits. Additionally, these businesses are among the riskiest investments that investors can make. Because of this, finding financing for an early venture requires lots of time and hard work, which can be frustrating at times. A typical entrepreneur begins by using personal savings or borrowing from friends and family to fund his/her venture. As the venture takes off, more financing will be needed. Until it proves successful, however, it will be hard to receive funding from banks and venture capitalists—firms that are organized as limited partnerships that provide funding for well developed firms usually in early-growth and rapid-growth stages of development. This creates a gap in financing that is often bridged through a source of funding called Angel Financing. One of the best providers of early stage funding is angel investors. In the chapters that follow I will explain what angel investing is, how they work, and what angels look for. This information will help entrepreneurs be better equipped to find an angel investor that matches with their venture and ultimately result in financing. However with all the angels that are out there, it is important to note that no two angels are exactly alike or will have the same investment criteria. This paper will discuss an array of criteria that goes into an angels decision to invest and will look specifically into Tech Coast Angels, an angel network, and what factors are most important to them based on their history of financing. The term entrepreneur has a wide range of meanings. It originates from the French word, entreprendre, which means " to undertake " (Quick MBA). In a business context, an entrepreneur is simply a person who starts a new business venture. A more elaborate definition however, is " a process through which individuals identify opportunities, allocate resources, and create value " (Entrepreneurship, Education, and Ethics). When we think of this definition we usually think of famous entrepreneurs such as Bill Gates, Steve Jobs, and Oprah Winfrey, among many others. When it comes to entrepreneurs, such as these and their new ventures, it is crucial to gain the most comprehensive information about the various funding …
The Missing Middle

The purpose of this paper is to provide evidence, and argue, that stunning as Indiaâ€™s success is, the potential â€“ and need â€“ is for still more reform and more rapid growth. 8 percent is a good rate of growth, but many are destined needlessly to be left behind for years to come if current trends persist: if growth in output and employment of unskilled-laborintensive manufacturing industries remains on its current trajectory, India is at risk of bifurcating the economy, with those benefiting from growth and those left out.
Information theoretic preattentive saliency: A closed-form solution

Employing an information theoretic operational definition of bottom-up attention from the field of computational visual perception, a very general expression for saliency is provided. As opposed to many of the current approaches to determining a saliency map, there is no need for an explicit, data-driven density estimation. Given the features, descriptors, or filter bank that one wants to use to describe the image content at every position, we provide a closed-form expression for the associated saliency at that location. This, indeed, makes explicit that what is considered salient depends on how, i.e., by means of which features, image information is described. We illustrate our result by determining a few specific saliency maps based on particular choices of features. One of them makes the link with the mapping underlying well-known Harris interest points, which is a result recently obtained in isolation. Another choice of features is, rather loosely, inspired by the success of histogram of oriented gradient descriptors and proves to provide state-of-the-art results on a collaborative benchmark for region of interest detection.
A Two-Level Programming Approach to Volume Propagation in Higher-Dimensional Spaces

A set of algorithms designed for the analysis of phase-space perturbation propagation in dynamical systems is presented. The most important tasks are approximate volume estimation and determining the subset of the perturbation surface that is tangent to current lines. The algorithms are developed in a generic, dimension-independent fashion, but they can be partially evaluated with respect to the dimension of the space, yielding dimension specific, efficient algorithms. The MuPAD implementation of the algorithms and supporting libraries is also discussed
Acute Suppression of Spontaneous Neurotransmission Drives Synaptic Potentiation

The impact of spontaneous neurotransmission on neuronal plasticity remains poorly understood. Here, we show that acute suppression of spontaneous NMDA receptor-mediated (NMDAR-mediated) neurotransmission potentiates synaptic responses in the CA1 regions of rat and mouse hippocampus. This potentiation requires protein synthesis, brain-derived neurotrophic factor expression, eukaryotic elongation factor-2 kinase function, and increased surface expression of AMPA receptors. Our behavioral studies link this same synaptic signaling pathway to the fast-acting antidepressant responses elicited by ketamine. We also show that selective neurotransmitter depletion from spontaneously recycling vesicles triggers synaptic potentiation via the same pathway as NMDAR blockade, demonstrating that presynaptic impairment of spontaneous release, without manipulation of evoked neurotransmission, is sufficient to elicit postsynaptic plasticity. These findings uncover an unexpectedly dynamic impact of spontaneous glutamate release on synaptic efficacy and provide new insight into a key synaptic substrate for rapid antidepressant action.
Investigation into the application of data mining techniques to classification of call centre data

Call centres are often the main and most critical customer contact point in organisations. Typically a call centre “help desk” receives requests in the form of free text descriptions of issues and forward the query to an appropriate specialist group within the organization. An error rate with respect to call classification and subsequent assignment will always exist due to various intrinsic human factors; hence opportunity exists for customer service improvement through error reduction. This paper examines the application of selected data mining techniques to automate classification of IT call centre enquiries in the company Cadbury Schweppes Asia Pacific. Research indicates classification based purely on basic word content appears to have limited capability beyond a certain level of accuracy, suggesting further sophistication in the filter task through techniques such as natural language rules may be required.
The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3

AbstractThe Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emiss.
Heteroscedastic Analysis of the Volatility of StockReturns in Nairobi Securities Exchange

Heteroscedasticity arises when the error term of a regression equation does not have a constant variance. Financial markets are known to be very uncertain a phenomenon called volatility which is a key variab le used in many financial applications such as investment, portfo lio construction, option pricing and hedging as well as market risk management. This study models the heteroscedasticity of volatility of stock returns in Nairobi Securities Exchange, NSE of Safarico m and Kenya Co mmercial Bank, KCB using daily return series fro m 9 th June 2008, to 31st December, 2010, using ARIMA-ARCH/ GA RCH models. The procedure for building the model involved model identificat ion, order determination, estimation of parameters and diagnostic check.Shapiro-Wilk testrejected the null hypothesis of normality for both series at 5% level of significance while Ph ilip Perron (PP) and Aug mented Dickey Fuller (ADF) reveal that price series were not stationary while returns series were stationary. All the return series exh ibit, leptokurtosis, volatility clustering and negative skewness. The estimation results reveal that ARIMA (1, 0, 0) -GA RCH (1, 1) and ARIMA (0, 0, 2)-GA RCH (1, 1) best fits Safarico m and KCB respectively. Investors who wish to avoid large, errat ic swings in portfolio returns may wish to structure their investments to produce a leptokurtic distribution. Further, researches shou ld focus on the calculation of value-at-risk (VaR) in the markets.
Molecular evolution of a Y-chromosomal repetitive sequence family in the genus Mus.

A 522-base-long Y-chromosomal sequence was isolated from a BALB/c genomic library and was designated "BF046. " It is repeated about 200 times in the male genome, and a difference was detected between the Mus musculus musculus and the M. m. domesticus type Y chromosomes. BF046-related sequences were present over the entire length of the Y chromosome as visualized by in situ hybridization. Southern blot analysis against DNAs isolated from eight species in the genus Mus showed that BF046-related sequences were amplified in the Y chromosomes of three closely related species: M. musculus, M. spicilegus, and M. spretus. To gain insight into the stability of the BF046 sequence family, we isolated 18 additional clones from these three mouse species and compared their sequences. The M. musculus sequences differed from the M. spicilegus and M. spretus sequences by two indels. The remaining parts of the sequences were very similar, but both parsimony and distance-based analytical methods divided the sequences into the same four subgroups, with each species having its own subgroup(s). Thus, the Y chromosomes of M. musculus, M. spicilegus, and M. spretus can be distinguished from one another.
Ontology Express : Statistical and Non-Monotonic Learning of Domain Ontologies from Text

Text mining has an important role to play in aiding experts to construct domain specific ontologies by highlighting the important classes, properties and relations that occur within large text collections. In this paper we propose a systematic framework for discovery of ontological types using typing information complemented with statistical filtering. Preliminary experiments are conducted on three corpora in the domain of molecular biology and results show that the top level types we obtain closely meet the intuitions and expectations of domain experts.
Shape based co-segmentation repairing by segment evaluation and object proposals

Repairing co-segmentation results by consistency evaluation shows the improvement of the co-segmentation performance. However, the existing co-segmentation refinement methods focus on color feature, while the mid-level features based repairing, such as shape, is ignored. In this paper, we propose a new shape based co-segmentation refinement method. An edge map based segment completeness evaluation and a shape based segment consistency evaluation are firstly proposed. Then, we use the initial segments and their evaluation scores to refine each result by employing the object proposals. By repeating such two evaluation and refinement steps, final refined results are obtained. Compared with traditional methods where only the bad segment is repaired, all segments are simultaneously evaluated and refined in an iteration process in our method to achieve better results. We verify our method based on Icoseg dataset. The results show larger IOU values than the original results.
Tunisian Arabic aeb Wordnet: Current State and Future Extensions

Nowadays, Internet communication and especially informal Internet communication such as social networks, blogs, etc. is directing politic, economic, financial and social environments all over the world. Consequently, Internet monitoring is taking more and more scale particularly in Tunisia suffering from unsteadiness since the politic revolution in 2011. In a Tunisian context, Internet communication is characterized by the increasing use of aeb language (i.e. an Arabic dialect called Tunisian Arabic). Therefore, Tunisian Internet monitoring needs primarily aeb language processing tools, especially an aeb lexicon. However, few aeb lexicon were developed seen the lack of written resources. Some of these lexicons are created from Arabic lexicons. They cover aeb lexicon originally Arabic and ignore the large borrowed aeb lexicon. Others are build using the informal Web. In fact, they need a rigorous linguistic verification, correction and validation. In this case, we suggest building a standard, large and robust Wordnet taking in charge phonetic. Our Wordnet is created by the expand approach used for EuroWordnet building as in [12], based on the bilingual English-Tunisian Arabic dictionary Peace corps dictionary prepared by the linguists: R. Ben abdelkader, A. Ayed and A. Naouar [13], and the last version of Princeton Wordnet PWN 3.1. Moreover, it is modelized according to ISO-LMF by a switable Wordnet-LMF model for aeb language. In this paper, we present aeb wordnet building approach, describe its current state and propose extensions.