Miracle-dz/UniFAR-FTUs huggingface dataset:
Lymphocytic Colitis Is Associated with Increased Pro-Inflammatory Cytokine Profile and Up Regulation of Prostaglandin Receptor EP4

Microscopic colitis (MC) is comprised of two entities, lymphocytic (LC) and collagenous colitis. Up to 20% of patients with chronic diarrhea that have a normal appearing colonoscopy will be diagnosed with MC. Since MC was first described less than 40 years ago, little is known about the mechanisms involved in disease pathogenesis. Nonsteroidal anti-inflammatory drugs are associated with an increased risk of MC and some reports suggest a dysregulation in prostaglandin production. Recent genome wide screens have found an association between prostaglandin receptor EP4 expression and inflammatory bowel disease; however, EP4 expression has never been studied in MC. The aim of this study was to assess colonic mucosal inflammatory cytokine profiles in patients with LC and to assess expression of the prostaglandin receptor EP4. Colonic mucosal biopsies were obtained from patients undergoing colonoscopy for investigation of diarrhea and in those undergoing colon cancer screening. Following histological assessment, expression of cytokines and the prostaglandin receptor EP4 was analyzed using real-time reverse transcriptase-PCR and immunohistochemistry. Patients with LC had markedly increased mRNA expression for TNF-α, IFN-γ and IL-8 compared to normal controls (p<0.001). No significant differences were noted for IL-1β, IL-4, IL-10 or IL-12/23. Interestingly, those with LC had increased EP4 receptor expression, which positively correlated with increased TNF-α expression. This is the first report to demonstrate that LC is associated with increased TNF-α, INF-γ and IL-8 concurrent with a marked up-regulation of EP4. These findings add to our knowledge on the pathogenesis of LC and may give rise to possible new therapeutic and/or diagnostic tools in the management of MC.
Taking as an act of sharing

We present findings from the deployment of a mobile application, Take and Give, which allows users to place image files in a virtual folder or 'Pocket' on a mobile phone. This content can be viewed by a set of 'Buddies', who can, if they wish, attempt to take ownership of a file for themselves, following which they can keep it, delete it, or place it in the Pocket of someone else. There is only one version of each file, creating a twist on traditional sharing technologies. We report findings from a three week trial of the application in an office space, and describe how Take and Give provided a means of self-presentation and supported a sense of awareness, mutual attentiveness and connectedness. Our findings suggest that the taking of unique content can be an engaging form of sharing and can facilitate awareness and connectedness between people.
Foundation of a Framework to Support Knowledge Management in the Field of Context-Aware and Pervasive Computing

In this paper we propose a framework to combine Knowledge Management and context-aware and pervasive computing, emphasizing on synchronization and adaptation issues of workflow processes in mobile settings. The key aspect of the proposed framework is to enable adaptive, two-way interaction between context-aware systems and users in mobile settings. In contrast to existing concepts, we aim at capturing active feedback from users, which should contribute to the Organizational Memory, after being reviewed, evaluated and classified. Thus, users would not only act as consumers but also as suppliers of relevant information and knowledge to the system and other users. In addition, the concept includes existing approaches to adapt to, for instance, different Quality of Service levels in order to provide a maximum level of local autonomy. We suggest using the adaptation concept to also support adjustments to cross-cultural differences in perceiving and communicating information and knowledge. Our work is motivated by the need for a distributed, context-aware and pervasive computing framework to support maintenance and administration tasks related to the International Monitoring System (IMS) of the CTBTO PrepCom, an international organization located in Vienna, Austria.
Tutor design for speech-based interfaces

Speech-based applications commonly come with web-based or printed manuals. Alternatively, the dialogue can be designed so that users should be able to start using the application on their own. We studied an alternative approach, an integrated tutor. The tutor participates in the interaction when new users learn to use a speech-based system. It teaches the users how to operate the system and monitors user actions to be certain that the users do indeed learn. In this paper we describe our experiences with the design and the iterative development of an integrated tutor. Expert evaluation and two user tests were conducted with different versions of the tutor. The results show that the tutor can effectively guide new users. We identify the six most important lessons learned, the most important being that it is essential to spot problems by monitoring user actions, especially when novice users are tutored.
Building a Lexical Domain Map From Text Corpora

In information retrieval the task is to extract from the database ~dl ,and only the documents which are relevant to a user query, even when the query and the documents use little common vocabul~u'y. In this paper we discuss the problem of automatic generation of lexical relations between words ,and phrltses from large text corpora :rod their application to automatic query expansion ill information retrieval. Reported here ,are some preliminary resuhs and observations from the experiments with a 85 million word Wall Street Journal dalabase and a 45 million word San Jose Mercury News database (piu'ts of 0.5 billion word TIPSTER/TREC datab`ase).
Effect of Lymph Node Number on Survival of Patients with Lymph Node-Negative Gastric Cancer according to the 7th Edition UICC TNM System

Background For the patients with node-negative gastric cancer, the 7th edition classification does not define the minimum number of lymph nodes necessary. We aimed to explore the prognostic significance of examined lymph nodes and determine how many nodes must be examined. Methodology/Principal Findings 435 patients underwent D2 gastrectomy with node-negative gastric cancer between December 1992 and December 2006 were obtained. Patients were classified into 4 groups by the number of negative LNs examined during surgery (1-6LNs, 7-10 LNs, 11-15 LNs, and > = 16 LNs). Stratified and Cox regression analyses were used to evaluate the association between survival and the number of negative LNs. Survival was significantly better in the > = 16 LNs, compared with the 1-5 LNs, 6-10 LNs and 11-15 LNs group in T2-4 patients; Multivariate analysis demonstrated tumor size, depth of invasion, 7th UICC stage and the number of examined nodes are strongly independent predictors of survival. Conclusions This study first demonstrates that patients with lymph node-negative gastric cancer underwent D2 dissection should have at least 16 LNs examined, especially in advanced gastric cancer. These results are a reasonable supplement to our previous tumor-ratio-metastasis staging system and a stratification criterion in clinical pratice.
Trace fragment selection within method-based JVMs

Java virtual machines have historically employed either a "wholemethod" or a "trace" methodology for selecting regions of code for optimization. Adaptive whole-method optimization primarily leverages intra-procedural optimizations derived from classic static compilation techniques whereas trace optimization utilizes an interpreter to select, manage, and dispatch inter-procedural fragments of frequently executed code. In this paper we present our hybrid approach for supplementing the comprehensive strengths of a whole-method JIT compiler with the inter-procedural refinement of trace fragment selection and show that that the two techniques would be mutually beneficial. Using the "interpreterless" Jikes RVM as a foundation, we use our trace profiling subsystem to identify an application's working set as a collection of hot traces and show that there is a significant margin for improvement in instruction ordering that can be addressed by trace execution. Our benchmark hot-trace profiles indicate that 20% of transitions between machine-code basic blocks as laid out by the JIT compiler are non-contiguous, many of which are transfers of control flow to locations outside of the current virtual memory page. Additionally, the analyses performed by the adaptive whole-method JIT compiler allow for better identification of trace starting and stopping locations, an improvement over the popular next-executing-tail (NET) trace selection scheme. We show minimal overhead for trace selection indicating that inter-procedural trace execution provides an opportunity to improve both instruction locality as well as compiler-directed branch prediction without significant run-time cost.
IMAGE ANALYSIS OF CARBIDE

Because of the decisive innuence of the carbide distribution on the mechanical properties of high speed steels its estimation is an important step of steel quality inspection. Currently metallographers classify the distributions by assigning micrographs to a standard chart consisting of 28 reference images arranged in 4 rows and 7 colums. These classiications as well as the standard chart itself are not based on quantitative measures but on the qualitative visual impression of the metallographers. We present image analysis methods, which model the visual classiication process. Apart from various features, which reeect parameters used in the visual decision process, additional features are extracted in frequency domain to improve the automatic classiication. First promising results of classiication experiments based on these quantitative features are discussed and a prototype of anàctive inspection system' for fully-automatic steel specimen classiication using the described methods is introduced. 1 MOTIVATION Ledeburitic steels occupy a special position among tool steels. After solidiication the microstructure of these steels posesses a carbide eutectic, which decisively innuences the mechanical properties of the tool steel. In addition to the amount of carbides their arrangement (i.e the carbide distribution) and the size of the carbide particles (i.e the carbide particle size) essentially determine the properties of the tools made of these steels. Several sientiic investigations showed the correlation between the mechanical properties and the carbide distribution and particle size of tool steels (see 1], 2], 3]). Therefore, the characterization of tool steels has to include the estimation of the carbide distribution and particle size. To make comparative examination of microstructure feasible in practice microstructural standard charts, which describe the quality of a ledeburitic steel qualitatively, were determined emperically. In order to get a quantitative description of the standard chart and to eliminate the subjectivity of the human classiication we are developing image analysis methods for an automatic classiication of steel specimens. Using the BB ohler standard chart for High Speed Steels (see Fig. 3) we present a feature extraction method with rst classiication results and give an outlook on an active inspection system for fully-automatic classiication of metallographic specimens.
Dynamics of microbial propagation: Models considering inhibitors and variable cell composition

Mathematical models for microbial growth in batch and continuous cultures are formulated. The models have been referred to as distributed models since the microbial population in a culture is looked upon as protoplasmic mass distributed uniformly throughout the culture. Growth is regarded as the increase in this mass by conversion of medium components into biological mass and metabolic products. Two sets of models have been presented. The first arise from introducing additional considerations into the model proposed by Monod to account for the stationary phase and the phase of decline in a batch culture. These have been referred to as unstructured, distributed models since they do not recognize any form of structure in the protoplasmic mass. The models in the second set are referred to as structured, distributed models. Structure is introduced by considering the protoplasmic mass to be composed of two groups of substances which interact with each other and with substances in the environment to produce growth. The structured models account for the dependence of growth on the past, history of the cells; thus they predict all growth phases observed in batch cultures, whereas the unstructured models do not predict a lag phase. The full implications of the models for continuous propagation, as determined by the method of stability analysis and transient calculations, are discussed. The models prediet a number of new results and should be confronted with experiments.
2016 Ieee International Conference on Big Data (big Data) Lightweight System for Ne-tagged News Headlines Corpus Creation

— Named Entity Identification (NEI) is the task of identifying named entities from textual data. While NEI for English language can be done with considerable accuracy owing to tools like Stanford NER tagger, the accuracy in case of Indian languages like Hindi is comparatively poor. One of the reasons for this is the lack of sufficiently large annotated corpora in Indian languages on which NE-taggers can be trained. In this paper, we describe a lightweight, automated process of tagging named entities in Hindi news headlines to create a huge silver standard corpus of NE-tagged news headlines. We show, via experiments, that the use of our corpus to train NE-taggers produces comparable results to the use of gold standard training corpus. Although we have applied the process majorly to Hindi language only, our method can also be applied to other languages provided they fulfill certain requirements which are necessitated by our process.
Evolution by Means of Genetic Programming of Analog Circuits that Perform Digital Functions

This paper demonstrates the ability of genetic programming to evolve analog circuits that perform digital functions and mixed analog-digital circuits. The evolved circuits include two purely digital circuits (a 100 nano-second NAND circuit and a two-instruction arithmetic logic unit circuit) and one mixed-signal circuit, namely a three-input digital-to-analog converter.
Proceedings of the 2nd workshop on Middleware for pervasive and ad-hoc computing

The Middleware Advanced Workshops program started in 2000 with the 1st Workshop on Reflective Middleware in New York. The surprising success of this first workshop, both in number of submission and number of participants, motivated the continuation of the Workshop program in the following events of the Middleware series. In Heidelberg, Middleware'2001 hosted two well attended workshops on Mobile Computing and Electronic Commerce, always focusing on research within the middleware area. In Rio, Middleware'2003 expanded the program with an open Call for Workshops that resulted in four high-quality workshops: Mobile and Ad-Hoc Computing, Reflective and Adaptive Middleware, Grid Computing, and Model-Driven Approaches. The preparation for the 2004 edition of the Middleware workshops started in late 2003 with the Call for Workshop Proposals. We received seven good, well planned proposals and, with the help of experts in the Middleware field, four workshops were selected. The selection criteria was based on adherence to the conference theme and objectives, capacity of attracting a good number of researchers and practitioners, whether the proposal was backed by well-known, active researchers in the field, and the overall formal quality of the proposal. For the first time, we will host a Doctoral Symposium, equivalent to similar events in other conferences such as OOPSLA. It is organized by Edward Curry from the National University of Ireland and Doug Lea from SUNY Oswego. During the Doctoral Symposium, 8 PhD candidates will present their theses work to a first-class Mentor Committee composed of some of the top Middleware researchers in the world. The goal of the symposium is to expose the students to helpful criticism before their thesis defense. Students beginning their research are also encouraged to attend the workshop as observers to better understand how to structure a research project and learn from the experience of others. The first edition of the Symposium will be highly international with the participation of PhD candidates from Brazil, Germany, Netherlands, Spain, Switzerland, and the United Kingdom. The Workshop on Middleware for Grid Computing was very successful in Rio and now, organized by Bruno Schulze (LNCC, Brazil) and Radha Nandkumar (NCSA/UIUC, USA), is in its second edition. It received 48 paper submissions from which 15 papers were selected. This workshop will also host a specific poster session with 9 posters. The Workshop on Middleware for Pervasive and Ad-Hoc Computing also started well in Rio and this year, organized by Paddy Nixon from Strathclyde University (UK) grew both in quantity and quality attracting papers from the lead researchers in the international community. Last but not least, the Workshop on Adaptive and Reflective Middleware continues very healthy. In its third edition it continues to be a venue for researchers working on the middleware core, finding new ways of structuring it to make it more flexible, adaptable, and efficient. This year, it is being organized by Fabio Costa (UFG, Brazil) and Nanbor Wang (Tech-X Corp., USA).
Parameter Sensitivity in Rank-Biased Precision Yuye

Rank-Biased Precision (RBP) is a retrieval evaluation metric that assigns an effectiveness score to a ranking by computing a geometricly weighted sum of document relevance values, with the monotonicly decreasing weights in the geometric distribution determined via a persistence parameter p. Despite exhibiting various advantageous traits over well known existing measures such as Average Precision, RBP has the drawback of requiring the designer of any experiment to choose a value for p. Here we present a method that allows retrieval systems evaluated using RBP with differentp values to be compared. The proposed approach involves calculating two critical bounding relevance vectors for the original RBP score, and using those vectors to calculate the range of possible RBP scores for any other value of p. Those bounds may then be sufficient to allow the outright superiority of one system over the other to be established. In addition, the process can be modified to handle any RBP residuals associated with either of the two systems. We believe the adoption of the comparison process described in this paper will greatly aid the uptake of RBP in evaluation experiments.
Question Answering on Romanian, English and French Languages

This paper describes UAIC’s Question Answering systems participating in the ResPubliQA 2010 competition, designed to answer questions on a juridical corpora in Romanian, English and French monolingual tasks. Our systems adhere to the classical architecture of a Question Answering system, with an emphasis on simplicity and real time answers: only shallow parsing was used for question processing, the indexes for the retrieval module were built at coarse-grained paragraph level, and the answer extraction component used simple pattern-based rules and lexical similarity metrics for candidate answer ranking.
Geometric Optimization of Relative Link Lengths for Biomimetic Robotic Fish

This paper focuses on the design of fishlike underwater robots using an optimization approach to choose relative link lengths. Considering both ichthyologic characteristics and mechatronic constraints, the optimal link-length ratios are numerically calculated by an improved constrained cyclic variable method. Comparative results, before and after the optimization, demonstrate the enhanced performance
Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks

The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio.
Poor Growth and Pneumonia Seasonality in Infants in the Philippines: Cohort and Time Series Studies

Children with poor nutrition are at increased risk of pneumonia. In many tropical settings seasonal pneumonia epidemics occur during the rainy season, which is often a period of poor nutrition. We have investigated whether seasonal hunger may be a driver of seasonal pneumonia epidemics in children in the tropical setting of the Philippines. In individual level cohort analysis, infant size and growth were both associated with increased pneumonia admissions, consistent with findings from previous studies. A low weight for age z-score in early infancy was associated with an increased risk of pneumonia admission over the following 12 months (RR for infants in the lowest quartile of weight for age z-scores 1.28 [95% CI 1.08 to 1.51]). Poor growth in smaller than average infants was also associated with an increased risk of pneumonia (RR for those in the lowest quartile of growth in early infancy 1.31 [95%CI 1.02 to 1.68]). At a population level, we found that seasonal undernutrition preceded the seasonal increase in pneumonia and respiratory syncytial virus admissions by approximately 10 weeks (pairwise correlation at this lag was −0.41 [95%CI −0.53 to −0.27] for pneumonia admissions, and −0.63 [95%CI −0.72 to −0.51] for respiratory syncytial virus admissions). This lag appears biologically plausible. These results suggest that in addition to being an individual level risk factor for pneumonia, poor nutrition may act as a population level driver of seasonal pneumonia epidemics in the tropics. Further investigation of the seasonal level association, in particular the estimation of the expected lag between seasonal undernutrition and increased pneumonia incidence, is recommended.