Miracle-dz/UniFAR-FTUs huggingface dataset:
A Social Network Ontology for Semantic Web Enabled Collaboration

Social networks have first been studied by social scientists to understand the patterns of relationships between people. More recently, social networking on the Internet capitalizes on the Web’s latent structure as a meta-network of social connections to boost computer-supported collaboration in conjunction with the use of Semantic Web metadata. Such metadata are generally machine-created and per se lack certification or trust grading. This paper examines how social network information can be used to accelerate reliable metadata creation. In particular, we focus on the application of Web annotations to leverage asynchronous collaboration through the Semantic Web by introducing the notion of a user’s Web personality to model the various trust levels in collaboration.
Anti-Islet Cell Antibodies From NOD Mice

We produced a panel of monoclonal autoantibodies from the spleen cells of prediabetic nonobese diabetic mice. The antibodies were selected on the basis of their ability to bind to the surface of nondiabetic mouse islet cells, and from >4000 hybridomas screened, 35 islet-reactive antibodies were isolated. Most of these reagents also bind to nondiabetic rat and human islet cells and β-cell tumor lines. A few of the antibodies were found to be reactive with insulin. When tested for cross-reactivity with other cell types, most of the antibodies were found to be islet specific.
Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach

This paper presents an algorithm that generates collision-free trajectories in three dimensions for multiple vehicles within seconds. The problem is cast as a non-convex optimization problem, which is iteratively solved using sequential convex programming that approximates non-convex constraints by using convex ones. The method generates trajectories that account for simple dynamics constraints and is thus independent of the vehicle's type. An extensive a posteriori vehicle-specific feasibility check is included in the algorithm. The algorithm is applied to a quadrocopter fleet. Experimental results are shown.
Age‐associated changes in cognitive function in highly educated adults: emerging myths and realities

The effects of education and continued intellectual engagement on age‐associated cognitive change were investigated in a sample of 102 members of the professional and college communities in the metro Atlanta Georgia area (ages 30–76). All participants were administered a 60‐minute battery that measured different aspects of memory, intelligence and cognitive performance. Age‐associated declines in performance were detected on the digit symbol measure of intelligence. Conversely, positive but non‐significant trends were detected on the picture completion, arithmetic and similarities subtests. Age effects were also noted on some measures of the Wisconsin Card Sorting Test and both versions of the Trail Making Test. The findings suggest that at least among the highly educated, certain cognitive abilities may receive some degree of amelioration as a consequence of continued intellectual engagement. However, the effects may be associated more with compensation rather than protection against the effects of ageing. Copyright © 2000 John Wiley & Sons, Ltd.
Local Businesses as Attractors or Preventers of Neighborhood Disorder

While businesses may attract potential offenders and thus be conducive to disorder, the number of employees could offset this by exercising social control on offenders. This study uses data from different sources to test this expectation across 278 Dutch neighborhoods in the four largest cities of the Netherlands, using multivariate multilevel analysis to disentangle individual perception differences of disorder and neighborhood effects. Attention is paid to traditional explanations of disorder (i.e., poverty, residential mobility, and ethnic heterogeneity). Results show a positive relationship between business presence and neighborhood disorder. We do not find consistent results of the number of employees (i.e., bigger businesses are not always better or worse). Our research demonstrates that the presence of neighborhood businesses could rival the effects of social disorganization theory.
Fabrication of monolithic 1-Chip FBAR duplexer for W-CDMA handsets

FBAR filters and duplexers have high power handling capability, high Q factors, good thermal stability, a low volume, a low cost and IC compatibility their applications have been gradually increased in RF systems. However, there is no published papers and research about FBAR 1-chip duplexer, which was fabricated with Tx and Rx filters because that is a very challenging task. We report for the first time that a monolithic 1-chip RF filter is achieved with the size of 2.5 mm times 2.5 mm using a suspended membrane thin film bulk acoustic resonator (FBAR) technology to meet stringent demand for miniaturization and monolithic integration of duplexers in RF communication systems. In this work, a novel 1-chip duplexer is designed by EM(electromagnetic) simulation and RF circuit simulation using HFSS and ADS. The highest insertion losses in the pass-band (1920-1980, 2110-2170 MHz) are measured below 3.5 dB. In the Rx band(2110-2170 MHz) the attenuation is the over 45 and the attenuation in the Rx band is the over 54 dB.
Quantifying Collective Attention from Tweet Stream

Online social media are increasingly facilitating our social interactions, thereby making available a massive “digital fossil” of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of “collective attention” on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or “tweets. ” Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. “Retweet” networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era.
The use of visual search for knowledge gathering in image decision support

This paper presents a new method of knowledge gathering for decision support in image understanding based on information extracted from the dynamics of saccadic eye movements. The framework involves the construction of a generic image feature extraction library, from which the feature extractors that are most relevant to the visual assessment by domain experts are determined automatically through factor analysis. The dynamics of the visual search are analyzed by using the Markov model for providing training information to novices on how and where to look for image features. The validity of the framework has been evaluated in a clinical scenario whereby the pulmonary vascular distribution on Computed Tomography images was assessed by experienced radiologists as a potential indicator of heart failure. The performance of the system has been demonstrated by training four novices to follow the visual assessment behavior of two experienced observers. In all cases, the accuracy of the students improved from near random decision making (33%) to accuracies ranging from 50% to 68%.
Differential gene expression profiles of whole lesions from patients with oral lichen planus.

BACKGROUND The molecular biological properties of oral lichen planus (OLP) are largely unknown. The aim of this study was to identify the genes responsible for its pathogenesis at the genome scale using DNA microarray technology. METHODS The RNA samples extracted from the specimens of nine OLP patients and nine controls were analyzed with Affymetrix GeneChip. Real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis was applied to confirm GeneChip results. RESULTS A total of 985 differentially expressed genes (629 up-regulated and 356 down-regulated) were identified. These genes were involved in many function classifications and biochemical pathways. The results of quantitative RT-PCR analysis of FOXP3, VEGFA, ANGPT1, MMP1, and SCGB2A2 were consistent with their changes demonstrated by GeneChip. CONCLUSIONS This study showed the gene expression profiles of OLP, which were quite distinct from that of healthy controls. These results presented a global view of physiopathologic processes in lesions, which will give important clues to understand pathogenesis and identify new therapeutic targets of OLP.
A Maximum Flow Approach to the Volumetric Reconstruction Problem

We present a 3D reconstruction technique based on the maximum-flow formulation. Starting with a set of calibrated images, we globally search for the most probable 3D model given the photoconsistency and the spatial continuity constraints. This search is done radially from the center of the reconstruction volume; therefore imposing a radial topology. The fact that cameras are arbitrarily positioned around the scene presents challenges for managing occlusion, especially when applying global smoothing. We solve this problem by proposing an iterative occlusion management mechanism, and a new way of looking at surface smoothing and discontinuities that takes photoconsistency into account. Experiments show that our method is relatively fast and robust when dealing with simple objects, even in noisy conditions.
Neurogenomic Signatures of Successes and Failures in Life-History Transitions in a Key Insect Pollinator

Abstract Life-history transitions require major reprogramming at the behavioral and physiological level. Mating and reproductive maturation are known to trigger changes in gene transcription in reproductive tissues in a wide range of organisms, but we understand little about the molecular consequences of a failure to mate or become reproductively mature, and it is not clear to what extent these processes trigger neural as well as physiological changes. In this study, we examined the molecular processes underpinning the behavioral changes that accompany the major life-history transitions in a key pollinator, the bumblebee Bombus terrestris. We compared neuro-transcription in queens that succeeded or failed in switching from virgin and immature states, to mated and reproductively mature states. Both successes and failures were associated with distinct molecular profiles, illustrating how development during adulthood triggers distinct molecular profiles within a single caste of a eusocial insect. Failures in both mating and reproductive maturation were explained by a general up-regulation of brain gene transcription. We identified 21 genes that were highly connected in a gene coexpression network analysis: nine genes are involved in neural processes and four are regulators of gene expression. This suggests that negotiating life-history transitions involves significant neural processing and reprogramming, and not just changes in physiology. These findings provide novel insights into basic life-history transitions of an insect. Failure to mate or to become reproductively mature is an overlooked component of variation in natural systems, despite its prevalence in many sexually reproducing organisms, and deserves deeper investigation in the future.
Advanced Approaches to Diagnose and Treat the Chronic Autoimmune Disorders: Multimodal Molecular Imaging

Pathology and dynamics of particular cells and the molecular components of immune system is still challenging to be traced within living organisms. The techniques of molecular imaging (MI) are promising tools to monitor the immune system at work, to improve or allow personalized diagnostics and treatment, especially of the autoimmune diseases. In this study some possible targets for MI and biosensing are discussed. The personalized medicine, in addition to bioinformatics-based systemic approach, requires extensive research and novel high-throughput technologies like next generation of imaging, biosensing experimental systems based on microfluidics, nanotechnology, femtochemistry, superresolution (STED, STORM, PALM, SOFI, etc.), label-free imaging, spectroscopy (including TCSPC), MRI, multimodal optical methods, accoustic imaging through ultrasonic waves, nuclear medicine methods like SPECT and PET. Moreover, dedicated designs of modular Lab-on-Chip solutions are of high demand to perform multipurpose cell measurement and give a possibility to flexibly interact with sensed objects.
A differential-fed unidirectional antenna for ultra-wideband applications

A novel differential-fed magneto-electric dipole antenna with unidirectional radiation pattern is proposed. Based on the differential feed scheme presented in [1], a new pair of differential feeds is developed to provide an ultra-wideband impedance matching. Instead of a planar reflector, a rectangular box-shaped reflector is utilized to reduce the fluctuation of the antenna gain. The proposed antenna achieves an impedance bandwidth (SWR ≤ 2) of 132% from 2.48 to 12.12 GHz and a gain varying between 7.16 and 14.1 dBi. Over the operating frequency range, radiation patterns with low cross polarization and low back radiation have mainbeams fixing broadside direction.
Creating Interactive Macaronic Interfaces for Language Learning

We present a prototype of a novel technology for second language instruction. Our learn-by-reading approach lets a human learner acquire new words and constructions by encountering them in context. To facilitate reading comprehension, our technology presents mixed native language (L1) and second language (L2) sentences to a learner and allows them to interact with the sentences to make the sentences easier (more L1-like) or harder (more L2-like) to read. Eventually, our system should continuously track a learner’s knowledge and learning style by modeling their interactions, including performance on a pop quiz feature. This will allow our system to generate personalized mixed-language texts for learners.
Multihop Routing In Self-Organizing Wireless Sensor Networks

Wireless sensor networks have emerged in the past decade as a result of recent advances in microelectronic system fabrication, wireless communications, integrated circuit technologies, microprocessor hardware and nano-technology, progress in adhoc networking routing protocols, distributed signal processing, pervasive computing and embedded systems. As routing protocols are application specific, recent advances in wireless sensor networks have led to many new protocols specifically designed for routing. Efficient routing in a sensor network requires that the routing protocol must minimize energy dissipation and maximize network life time. In this paper we have implemented several multihop flat based routing protocols like Flooding, Gossiping and a cluster based protocol MultihopLEACH which does inter-cluster and intra-cluster multihopping using TinyOs and TOSSIM simulator. Evaluation and comparison reveals that Multihop-LEACH protocol utilizes less power and least delay compared to other protocols. We further evaluated the Multihop-LEACH protocol with varying probability of clustering to extend the network life time.
Photophysics on surfaces: determination of absolute fluorescence quantum yields from reflectance spectra.

A method for the calculation of absolute fluorescence quantum yields for dyes attached to solid particles based on reflectance measurements is reported. The same procedure allows calculation of true reflectance spectra (free of fluorescence) for highly fluorescent materials as well. Samples ofcresyl violet were immobilized by adsorption on microgranular cellulose in the concentration range 4.5 x 10(-9) to 3.8 x 10(-6) mol g(-1). Diffuse and total reflectance spectra were recorded with and without insertion of an optical absorption filter between the output of the integrating sphere of a reflectance spectrometer and the photodetector in order to block fluorescence partially. From these data, the relative emission spectrum of the dye, the filter transmission spectrum, and the detector sensitivity, true reflectances and absolute fluorescence quantum yields were recovered. Observed fluorescence quantum yields, affected by dye aggregation and inner filter effects, were concentration and wavelength dependent, ranging approximately between 0.1 and 0.6. The analysis of remission function spectra showed that dye aggregation is negligible up to a concentration of 1.41 x 10(-7) mol g(-1). Fluorescence data were corrected for reemission and reabsorption using a suitable model [Lagorio, M. G. ; Dicelio, L. E. ; Litter, M. I. ; San Roman, E. J. Chem. Soc. , Faraday Trans. 1998, 94, 419]. Application of this model to samples showing no aggregation yielded a wavelength-independent true fluorescence quantum yield of 0.60 +/- 0.05, similar to values found in solution. The usage of cresyl violet as a reference for the evaluation of fluorescence quantum yields for weakly fluorescing samples in the solid phase is discussed.
A Comparative analysis: QA evaluation questions versus real-world queries

This paper presents a comparative analysis of user queries to a web search engine, questions to a Q&A service (answers.com), and questions employed in question answering (QA) evaluations at TREC and CLEF. The analysis shows that user queries to search engines contain mostly content words (i.e. keywords) but lack structure words (i.e. stopwords) and capitalization. Thus, they resemble natural language input after case folding and stopword removal. In contrast, topics for QA evaluation and questions to answers.com mainly consist of fully capitalized and syntactically well-formed questions. Classification experiments using a na¨ive Bayes classifier show that stopwords play an important role in determining the expected answer type. A classification based on stopwords is considerably more accurate (47.5% accuracy) than a classification based on all query words (40.1% accuracy) or on content words (33.9% accuracy). To simulate user input, questions are preprocessed by case folding and stopword removal. Additional classification experiments aim at reconstructing the syntactic wh-word frame of a question, i.e. the embedding of the interrogative word. Results indicate that this part of questions can be reconstructed with moderate accuracy (25.7%), but for a classification problem with a much larger number of classes compared to classifying queries by expected answer type (2096 classes vs. 130 classes). Furthermore, eliminating stopwords can lead to multiple reconstructed questions with a different or with the opposite meaning (e.g. if negations or temporal restrictions are included). In conclusion, question reconstruction from short user queries can be seen as a new realistic evaluation challenge for QA systems.
Disease Detection and Symptom Tracking by Retrieving Information from the Web

This paper proposes techniques for preliminary disease detection and personal symptom tracking adopting concepts and methods of web information retrieval. The proposed approaches are inspired by web users’ behavior. People look for information of symptoms from Internet. Therefore, considering information in Web pages, the developed system proposes possible diseases related to one or more queried symptoms. Moreover, these queried symptoms would be recorded in the query log so that the user could utilize these records to trace the history of symptoms, further to manage their own health or provide them to doctors as reference. As ranking detected diseases needs professional knowledge, we instead evaluate relevancy of retrieved sentences containing detected diseases in both strict and lenient metrics. Experimental results support the proposed ranking approach. The techniques described in this paper are also implemented to develop an Android application called “Health Generation”. In this application, the detected disease is further linked to its Wikipedia introduction and the nearby clinics are listed. Users can utilize the GPS function provided by cell phones to plan the route for them. Through the proposed approaches and the application to provide medical information and solutions according to users’ need and further to help users manage their health is the aim of this research.
Sudden cardiac death prediction using ECG signal derivative (Heart Rate Variability): A review

Sudden cardiac death (SCD) prediction using Electrocardiogram (ECG) signal is a popular area of research because of the seriousness of the matter. There are tons of papers published in this research which available online. Severe importance for prediction and recent development of new algorithms fuels this research further. There are numerous methods to detect or predict SCD based on Heart Rate Variability (HRV), T-Wave Alternans (TWA), Heart Rate Turbulence (HRT), Signal Averaged Electrocardiogram (SA-ECG), Data Mining, and Non Linear Analysis to state few. Researchers favors statistical analysis over other classifier (Neural network, KNN etc.,) based methods since it gives more perspective to the research findings. Various statistical methods like Kaplan-Meier method, t-test, Mann-Whitney U test, Wilk's Lambda test were carried out to describe correlation between ECG derived parameters (HRV, TWA, HRT etc.,) and SCD. Even though there are many papers published, none of them are clinically practicable because of its own limitations. In this review, we would see methods and techniques based on HRV used by researchers in order to detect and predict sudden cardiac death.
Study of folate receptor genes in nonsyndromic familial and sporadic cleft lip with or without clef palate cases

Folate receptor family members (FOLRs) mediate the delivery of 5‐methyltetrahydrofolate to the interior of, out of within, or between cells in a process known as potocytosis. Three FOLRs and a pseudogene map to 11q13.4. The aim of this study was to verify whether FOLRs could be responsible for the onset of nonsyndromic cleft lip with or without cleft palate (CL/P). Linkage and linkage disequilibrium between genetic markers and disorder were analyzed. Patients and their mothers from 71 familial CL/P pedigrees and 75 sporadic cases from Italian population were investigated by PCR‐SSCP analysis. Data from mutation scanning allowed us to find only a silent mutation in FOLR1 present in a mother and her child. Our findings do not support FOLR1 and FOLR2 genes in the onset of CL/P. © 2004 Wiley‐Liss, Inc.