Miracle-dz/UniFAR-FTUs huggingface dataset:
A favourable prognostic marker for EGFR mutant non-small cell lung cancer: immunohistochemical analysis of MUC5B

Objectives To determine the use of the mucin proteins MUC5B and MUC5AC as prognosis markers for non-small cell lung cancer (NSCLC) carrying epidermal growth factor receptor (EGFR) mutations. Setting Patients who underwent surgical resection at Nagasaki University Hospital and related facilities in Japan between June 1996 and March 2013. Participant 159 Japanese patients (male: n=103; female: n=56) with NSCLC, who underwent surgical resection (EGFR-mutant type: n=78, EGFR wild type: n=81). Results Patients whose tumours expressed MUC5B had significantly longer overall survival and relapse-free survival compared to the MUC5B-negative patients with EGFR mutant NSCLC (p=0.0098 and p=0.0187, respectively). In patients with EGFR wild-type NSCLC, there was no association with MUC5B expression. MUC5AC expression was not different between EGFR mutant and wild-type NSCLC. Conclusions Present findings indicate that MUC5B, but not MUC5AC, is a novel prognostic biomarker for patients with NSCLC carrying EGFR mutations but not for patients with NSCLC carrying wild-type EGFR.
Category Similarity as a Predictor for SVM Learning Performance

In this paper we propose a method for the prediction of learning performance in Support Vector Machines based on a novel definition of intra- and inter-class similarity. Our measure of category similarity can be easily estimated from the learning data. In the second part of the paper we provide experimental evidence to support the effectiveness of this measure.
Skin Color Detection Model Using Neural Networks and its Performance Evaluation

Problem statement: Skin color detection is used as a preliminary step in numerous computer vision applications like face detection, nudity recognition, hand gesture detection and person identification. In this study we present a pixel based skin color classification approach, for detecting skin pixels and non skin pixels in color images, using a novel neural network symmetric classifier. The neural classifiers used in the literature either uses a symmetric model with single neuron in the output layer or uses two separate neural networks (asymmetric model) for each of the skin and non-skin classes. The novelty of our approach is that it has two output layer neurons; one each for skin and non-skin class, instead of using two separate classifiers. Thus by using a single neural network classifier we have improved the separability between these two classes, eliminating additional time complexity that is needed in asymmetric classifier. Approach: Skin samples from web images of people from different ethnic groups were collected and used for training. Ground truth skin segmented images were obtained by using semiautomatic skin segmentation tool developed by the authors. The ground truth database of skin segmented images, thus obtained was used to evaluate the performance of our NN based classifier. Results: With proper selection of optimum classification threshold that varies from image to image the classifier gave the detection rate of more than 90% with 7% false positives on an average, Conclusion/Recommendations: It is observed that the neural network is capable of detecting skin in complex lighting and background environments. The classifier has the ability to classify the skin pixels belonging to people from different ethnic groups even when they are present simultaneously in an image. The proper choice of optimum classification threshold that varies from image to image is an issue here. Automatic computation of this optimum threshold for each image is desired in practical skin detection applications. This issue can be taken up as a future study, which will enable us to perform fully automatic skin segmentation with reduced false positives.
Heart Attack Prediction System Using Fuzzy C Means Classifier

Cardiovascular disease remains the biggest cause of deaths worldwide. The percentage of premature death from this disease ranges from 4% in high income countries and 42 % in low income countries. This shows the importance of predicting heart disease at the early stage. In this paper, a new unsupervised classification system is adopted for heart attack prediction at the early stage using the patient’s medical record. The information in the patient record are preprocessed initially using data mining techniques and then the attributes are classified using a Fuzzy C means classifier. In the classification stage 13 attributes are given as input to the Fuzzy C Means (FCM) classifier to determine the risk of heart attack. FCM is an unsupervised clustering algorithm, which allows one piece of data to belong to two or more clusters. The proposed system will provide an aid for the physicians to diagnosis the disease in a more efficient way. The efficiency of the classifier is tested using the records collected from 270 patients, which gives a classification accuracy of 92%. The result shows that the proposed clustering algorithm can predict the likelihood of patients getting a heart attack in a more efficient and cost effective way than the other well known algorithms.
Social Media Story Telling

The number of documents on the web increases rapidly and often there is an enormous information overlap between different sources covering the same topic. Since it is impractical to read through all posts regarding a subject, there is a need for summaries combining the most relevant facts. In this context combining information from different sources in form of stories is an important method to provide perspective, while presenting and enriching the existing content in an interesting, natural and narrative way. Today, stories are often not available or they have been elaborately written and selected by journalists. Thus, we present an automated approach to create stories from multiple input documents. Furthermore the developed framework implements strategies to visualize stories and link content to related sources of information, such as images, tweets and encyclopedia records ready to be explored by the reader. Our approach combines deriving a story line from a graph of interlinked sources with a story-centric multi-document summarization.
Evolution of PM nickel base superalloy processes and products

Industrial production of critical parts in aero engine by PM is now more than 30 years old. During this period, evolution of design principles and better evaluation of the impact of cleanliness has led to an evolution of metallurgy (grades and microstructure) and processes. The basis of this evolution will be presented and illustrated by examples taken from companies worldwide.
A Novel Function for a Glucose Analog of Blood Group H Antigen as a Mediator of Leukocyte-Endothelial Adhesion via Intracellular Adhesion Molecule 1*

The 4A11 antigen is a unique cytokine-inducible antigen up-regulated on rheumatoid arthritis synovial endothelium compared with normal endothelium. In soluble form, this antigen, Lewisy-6/H-5-2 (Ley/H), or its glucose analog, 2-fucosyllactose (H-2g), mediates angiogenesis. The Ley/H antigen is structurally related to the soluble E-selectin ligand, sialyl Lewisx, and is selectively expressed in skin, lymphoid organs, thymus, and synovium, suggesting that it may be important in leukocyte homing or adhesion. In the present study, we used H-2g as a functional substitute to demonstrate a novel property for Ley/H antigen in inducing leukocyte-endothelial adhesion. H-2g significantly enhanced the expression of human dermal microvascular endothelial cells (HMVECs) intercellular adhesion molecule-1 (ICAM-1), but not vascular cell adhesion molecule-1, E-selectin, and P-selectin. Immunoprecipitation and Western blotting showed glycolipids Ley-6, H-5-2, or the glucose analog H-2g quickly activated human microvascular endothelial cell line-1 (HMEC-1) Janus kinase 2 (JAK2) and that the JAK2 inhibitor, AG-490, completely inhibited HMVEC ICAM-1 expression and HL-60 adhesion to HMEC-1s. Use of a JAK/signal transducer and activator of transcription (STAT) profiling system confirmed that H-2g selectively activated STAT3 but not STAT1 and STAT2. AG-490 inhibited H-2g-induced Erk1/2 and PI3K-Akt activation, suggesting that JAK2 is upstream of the Erk1/2 and PI3K-Akt pathways. Furthermore, the JAK2 inhibitor AG-490, the Erk1/2 inhibitor PD98059, or the phosphatidylinositol 3-kinase inhibitor LY294002 or antisense oligodeoxynucleotides directed against JAK2, Erk1/2, or phosphatidylinositol 3-kinase blocked H-2g-induced HMVEC ICAM-1 expression and HL-60 adhesion to HMEC-1s. Hence, H-2g signals through JAK2 and its downstream signal transducers STAT3, Erk1/2, and phosphatidylinositol 3-kinase result in ICAM-1 expression and cell adhesion. Potential treatment strategies through the inhibition of JAK-dependent pathways to target H-2g signals may provide a useful approach in inflammation-driven diseases like rheumatoid arthritis.
Functional Impairment of the Vestibular End Organ Resulting From Impulse Noise Exposure

Objectives/Hypothesis To assess the effect of exposure to impulse noise, known to cause damage to the cochlea, on the vestibular part of the inner ear using short latency vestibular evoked potentials (VsEPs), which is a direct and objective test for evaluating the function of the vestibular end organs.
Delivering bioinformatics MapReduce applications in the cloud

The ever-increasing data production and availability in the field of bioinformatics demands a paradigm shift towards the utilization of novel solutions for efficient data storage and processing, such as the MapReduce data parallel programming model and the corresponding Apache Hadoop framework. Despite the evident potential of this model and existence of already available algorithms and applications, especially for batch processing of large data sets as in the Next Generation Sequencing analysis, bioinformatics MapReduce applications are yet to become widely adopted in the bioinformatics data analysis. We identify two prerequisites for their adaptation and utilization: (1) the ability to compose complex workflows from multiple bioinformatics MapReduce tools that will abstract technical details of how those tools are combined and executed allowing bioinformatics domain experts to focus on the analysis, and (2) the availability of accessible and flexible computing infrastructure for this type of data processing. This paper presents integration of two existing systems: Cloudgene, a bioinformatics MapReduce workflow framework, and CloudMan, a cloud manager for delivering application execution environments. Together, they enable delivery of bioinformatics MapReduce applications in the Cloud.
Elasticity and morphology of wet fiber networks

Fibrous materials are very commonplace in current technological applications. The study of their mechanics is an interesting topic that has previously been inspired by applications in the textile and paper industries, but also by modern composite materials. In many applications, humidity of the ambient atmosphere leads to condensation of liquid in a fiber network. Once liquid interfaces form, capillary effects lead to internal mechanical stresses.In this work, we investigate the effects of capillary stresses on disordered, two-dimensional networks of elastic fibers. To that end, we first study the morphologies and induced stresses of a liquid bridge forming between two cylindrical fibers. Then, we introduce a two-dimensional model system for disordered fiber networks with liquid interactions taking place at fiber crossings. After an overview of the topological properties of such a model network, we introduce a method for computer simulation of an elastic network in the presence of a wetting liquid that can accumulate in the fiber interstices and thereby deform the network. We test the model by comparison with analytical theory in a simple test case, and finally we present computer experiments characterizing the network deformation as a function of the most important model parameters, the fiber density and the capillary interaction strength.
Supporting concurrent applications in wireless sensor networks

It is vital to support concurrent applications sharing a wireless sensor network in order to reduce the deployment and administrative costs, thus increasing the usability and efficiency of the network. We describe Melete 1 , a system that supports concurrent applications with efficiency, reliability, flexibility, programmability, and scalability. Our work is based on the Maté virtual machine [1] with significant modifications and enhancements. Melete enables reliable storage and execution of concurrent applications on a single sensor node. Dynamic grouping is used for flexible, on-the-fly deployment of applications based on contemporary status of the sensor nodes. The grouping procedure itself is programmed with the TinyScript language. A group-keyed code dissemination mechanism is also developed for reliable and efficient code distribution among sensor nodes. Both analytical and simulation results are presented to study the impact of several key parameters and optimization techniques on the code dissemination mechanism. Simulation results indicate satisfactory scalability of our techniques to both application code size and node density. The usefulness and effectiveness of Melete is also validated by empirical study.
Multi-level holonification of multi-agent networks

A networked multi-agent system is a group of intelligent agents structured in a social network induced by agent interactions. As the size and diversity of the multi-agent system increase, the interactions and mutual influence of the agents in the structure become more complicated, and this makes the coordination of the system hard to deal with. Holonic models for multi-agent systems have been considered as one of promising models to manage large scale problems. This paper tackles one of the key problems in the design of holonic multi-agent systems. Here we propose a method to construct a multi-level holonic structure for a multi-agent network based on the centrality of the agents. The proposed method is applied to an urban traffic problem and the evaluation results prove its effectiveness.
Expression of the Human 5-Hydroxytryptamine1A Receptor in Sf9 Cells

The possibility that Spodoptera frugiperda (Sf9) cells can provide an intact cell setting for reconstitution of the human 5-hydroxytryptamine1A (5-HT1A) receptor with mammalian G protein subunits was explored. The 5-HT1A receptor was found to assume an uncoupled phenotype when expressed alone in Sf9 cells at relatively high levels (5-34 pmol of receptor/mg of membrane protein), i.e. agonist-binding to the receptor was characterized by a relatively high Kd and an insensitivity to GTP. Co-expression of the receptor with members of the αi “family” together with various combinations of β1 and γ subunits increased the affinity for agonists to that observed for the coupled form of receptor in mammalian cells, concomitant with conferrance of guanosine 5′-(β,γ-imino)triphosphate sensitivity. The agonists employed were [3H]8-hydroxy-N, N-dipropyl-2-aminotetralin ([3H] 8-OH-DPAT) and [125I]R(+)-trans-8-hydroxy-2-[N-n-propyl-N-(3′-iodo-2′-propenyl)amino]tetralin ([125I]8-OH-PIPAT). The binding of an antagonist, [125I]4-(2′-methoxyphenyl)-1-[2′-[N-(2″-pyridinyl)-p-iodobenzamido]ethyl] piperazine ([125I]p-MPPI), was unaffected by co-expression of G protein subunits. Both α and βγ subunits were required for optimal coupling. No differences were evident among αi1, αi2, αi3, αo, and αz when expressed with β1γ2 in this regard, nor among most permutations of β1γ subunits when expressed with αi1 (β1γ2 ≈ β1γ3 ≈ β1γ5 > β1γ1). αs and αq expressed with β1γ2 did not participate in coupling. These data support the conclusion that normal interactions between a mammalian receptor and a select array of G proteins can be established in intact Sf9 cells, and extend previous observations of 5-HT1A receptor coupling to Go and the pertussis toxin-insensitive G protein Gz.
Information Diffusion issues

In this report there will be a discussion for Information Diffusion. There will be discussions on what information diffusion is, its key characteristics and on several other aspects of these kinds of networks. This report will focus on peer to peer models in information diffusion. There will be discussions on epidemic model, OSN and other details related to information diffusion.
Distributed synchronous control units for dataflow graphs under allocation of telescopic arithmetic units

In order to enjoy the performance improvement effects of variable computation time arithmetic units at a system level, we propose a new synchronous control unit design methodology for dataflow graphs under allocation of a telescopic arithmetic unit, which is one of the well-known synchronous variable computation time arithmetic units. The proposed method generates an independent synchronous controller for each component arithmetic unit, and builds a distributed synchronous control unit through integrating the derived controllers. The distributed structure of the final synchronous control unit maximizes the performance improvement effect of telescopic arithmetic units through a complete preservation of original concurrency among operations.
Public Response to Obamacare on Twitter

Background The Affordable Care Act (ACA), often called “Obamacare,” is a controversial law that has been implemented gradually since its enactment in 2010. Polls have consistently shown that public opinion of the ACA is quite negative. Objective The aim of our study was to examine the extent to which Twitter data can be used to measure public opinion of the ACA over time. Methods We prospectively collected a 10% random sample of daily tweets (approximately 52 million since July 2011) using Twitter’s streaming application programming interface (API) from July 10, 2011 to July 31, 2015. Using a list of key terms and ACA-specific hashtags, we identified tweets about the ACA and examined the overall volume of tweets about the ACA in relation to key ACA events. We applied standard text sentiment analysis to assign each ACA tweet a measure of positivity or negativity and compared overall sentiment from Twitter with results from the Kaiser Family Foundation health tracking poll. Results Public opinion on Twitter (measured via sentiment analysis) was slightly more favorable than public opinion measured by the Kaiser poll (approximately 50% vs 40%, respectively) but trends over time in both favorable and unfavorable views were similar in both sources. The Twitter-based measures of opinion as well as the Kaiser poll changed very little over time: correlation coefficients for favorable and unfavorable public opinion were . 43 and . 37, respectively. However, we found substantial spikes in the volume of ACA-related tweets in response to key events in the law’s implementation, such as the first open enrollment period in October 2013 and the Supreme Court decision in June 2012. Conclusions Twitter may be useful for tracking public opinion of health care reform as it appears to be comparable with conventional polling results. Moreover, in contrast with conventional polling, the overall amount of tweets also provides a potential indication of public interest of a particular issue at any point in time.
A Multimodal Corpus for Studying Dominance in Small Group Conversations

We present a new multimodal corpus with dominance annotations on small group conversations. We used five-minute non-overlapping slices from a subset of meetings selected from the popular Augmented Multi-party Interaction (AMI) corpus. The total length of the annotated corpus corresponds to 10 hours of meeting data. Each meeting is observed and assessed by three annotators according to their level of perceived dominance. We analyzed the annotations with respect to dominance, status, gender and behavior. The results of the analysis reflect the findings in the social psychology literature on dominance. The described dataset provides an appropriate testbed for automatic dominance analysis.
Integrated method of ultrasonic attenuation and backscattering for characterization of microstructures in polycrystals

In structural materials the elastic properties of crystallites are often unknown, thus complicating model-based microstructure size determination. It is shown in this paper that measurement and evaluation of ultrasonic backscattering-to-attenuation ratios may be used to exclude unknown material characteristics and may be used advantageously for inverse mictostructural characterization of polycrystalline materials. The method is based on recently developed models for ultrasonic attenuation and backscattering in polycrystals with elongated grains. The method is demonstrated on experimental data for forged Ti alloy samples.
Confidence intervals for spectral mean and ratio statistics

We propose a new method, to construct confidence intervals for spectral mean and related ratio statistics of a stationary process, that avoids direct estimation of their asymptotic variances. By introducing a bandwidth, a self-normalization procedure is adopted and the distribution of the new statistic is asymptotically nuisance-parameter free. The bandwidth is chosen using information criteria and a moving average sieve approximation. Through a simulation study, we demonstrate good finite sample performance of our method when the sample size is moderate, while a comparison with an empirical likelihood-based method for ratio statistics is made, confirming a wider applicability of our method. Copyright 2009, Oxford University Press.
Immunosuppressant FTY720 inhibits thymocyte emigration

One major role of the thymus is to provide the peripheral immune system with mature T cells, but the mechanisms involving the cellular export are not fully understood. In this study, we examined the ability of a novel immunosuppressive reagent, FTY720, to inhibit T cell export from the thymus. Daily administration of FTY720 at a dose of 1 mg / kg resulted in a marked decrease in the number of peripheral blood T lymphocytes. In the thymus, long‐term daily administration of FTY720 caused a three‐ to fourfold increase in the proportion of mature medullary thymocytes (CD4+CD8– and CD4–CD8+) as well as a slight decrease in the double‐positive cell (CD4+CD8+) ratio. Phenotypic analysis (TCRα β, H‐2Kd, CD44, CD69 and CD24) revealed that these increased subsets represent possible peripheral recent thymic emigrants. High level expression of L‐selectin by these subsets further suggests that they were prevented from leaving the thymus. By intrathymic labeling with fluorescein isothiocyanate, only one fourth of labeled cells could be detected in the lymph nodes and in the spleen of FTY720‐treated mice compared to saline‐treated control mice. Taken together, these results suggest that the immunosuppressive action of FTY720, at least in part, could be due to its inhibitory effect on T cell emigration from the thymus to the periphery.