Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring the evaluation and impact of scientific works and their authors

Problems for evaluation and impact of published scientific works and their authors are discussed. The role of citations in this process is pointed out. Different bibliometric indicators are reviewed in this connection and ways for generation of new bibliometric indices are given. The influence of different circumstances, like self-citations, number of authors, time dependence and publication types, on the evaluation and impact of scientific papers are considered. The repercussion of works citations and their content is investigated in this respect. Attention is paid also on implicit citations which are not covered by the modern bibliometrics but often are reflected in the peer reviews. Some aspects of the Web analogues of citations and new possibilities of the Internet resources in evaluating authors achievements are presented.
Tumor Vascular Permeability to a Nanoprobe Correlates to Tumor-Specific Expression Levels of Angiogenic Markers

Background Vascular endothelial growth factor (VEGF) receptor-2 is the major mediator of the mitogenic, angiogenic, and vascular hyperpermeability effects of VEGF on breast tumors. Overexpression of VEGF and VEGF receptor-2 is associated with the degree of pathomorphosis of the tumor tissue and unfavorable prognosis. In this study, we demonstrate that non-invasive quantification of the degree of tumor vascular permeability to a nanoprobe correlates with the VEGF and its receptor levels and tumor growth. Methodology/Principal Findings We designed an imaging nanoprobe and a methodology to detect the intratumoral deposition of a 100 nm-scale nanoprobe using mammography allowing measurement of the tumor vascular permeability in a rat MAT B III breast tumor model. The tumor vascular permeability varied widely among the animals. Notably, the VEGF and VEGF receptor-2 gene expression of the tumors as measured by qRT-PCR displayed a strong correlation to the imaging-based measurements of vascular permeability to the 100 nm-scale nanoprobe. This is in good agreement with the fact that tumors with high angiogenic activity are expected to have more permeable blood vessels resulting in high intratumoral deposition of a nanoscale agent. In addition, we show that higher intratumoral deposition of the nanoprobe as imaged with mammography correlated to a faster tumor growth rate. This data suggest that vascular permeability scales to the tumor growth and that tumor vascular permeability can be a measure of underlying VEGF and VEGF receptor-2 expression in individual tumors. Conclusions/Significance This is the first demonstration, to our knowledge, that quantitative imaging of tumor vascular permeability to a nanoprobe represents a form of a surrogate, functional biomarker of underlying molecular markers of angiogenesis.
Determine Task Demand from Brain Activity

Our society demands ubiquitous mobile devices that offer seamless interaction with everybody, everything, everywhere, at any given time. However, the effectiveness of these devices is limited due to their lack of situational awareness and sense for the users’ needs. To overcome this problem we develop intelligent transparent human-centered systems that sense, analyze, and interpret the user’s needs. We implemented learning approaches that derive the current task demand from the user’s brain activity by measuring the electroencephalogram. Using Support Vector Machines we can discriminate high versus low task demand with an accuracy of 92.2% in session dependent experiments, 87.1% in session independent experiments, and 80.0% in subject independent experiments. To make brain activity measurements less cumbersome, we built a comfortable headband with which we achieve 69% classification accuracy on the same task.
An EM Approach to OD Matrix Estimation

An EM Approach to OD MatrixEstimationRob ert J. Vanderb eiJames IannoneProgram in Statistics & Operations ResearchPrinceton UniversityPrinceton, NJ 08544March 29, 1994Technical Rep ort SOR-94-04AbstractConsider a \blackbox" havingIinput channels andJoutputchannels. Each arrival on an input channel gets routed through theblackbox and app ears on an output channel. The system is monitoredfor a xed time p erio d and a record is made of the numb er of arrivalson each input channel and the numb er of departures on each outputchannel. The OD (origination-destination) matrix estimation problemis to estimate, for eachiandj, the numb er of arrivals on channelthat depart on channelj.Weintro duce a Poisson sto chastic mo deland employ the EM algorithm to pro duce high likeliho o d estimates. Inthe case of estimation based on observations over a single time-p erio d,we analyze in detail the xed p oints of the EM algorithm showing thatevery vertex of a certain p olytop e of feasible matrices is a xed p ointand identifying a sp eci c interior xed p oint which is a saddle p ointfor the likeliho o d function.Research supp orted byAFOSR through grantAFOSR-91-0359.
Building a large Persian Verb Collection: A generative approach

Persian is an Iranian language within the Indo-Iranian branch of the Indo-European languages which is one of the major languages in the Heart Land (Middle East). Nevertheless, there are proportionately few studies on retrieval and analyses of Persian documents. In this case, suitable resources for Persian are becoming a vital necessity for the progress of language engineering researches. In this paper we tried to make a Persian Verb Collection -as a linguistic resource- which is needed in some NLP researches like verb and sentence detection, POS tagging, Lexicography and etc. We used a generative approach for building this collection from Persian Stems by Verbal Structures.
Employee Voice, Human Resource Practices, and Quit Rates: Evidence from the Telecommunications Industry

The authors draw on strategic human resource and industrial relations theories to identify the sets of employee voice mechanisms and human resource practices that are likely to predict firm-level quit rates, then empirically evaluate the predictive power of these variables using data from a 1998 establishment-level survey in the telecommunications industry. With respect to alternative voice mechanisms, they find that union representation predicts lower quit rates, even after they control for compensation and a wide range of other human resource practices that may be affected by collective bargaining. Also predicting lower quit rates is employee participation in offline problem-solving groups and in self-directed teams. No apparent association is found between quit rates and the availability of nonunion dispute resolution procedures. Regarding human resource practices, higher relative wages and internal promotion policies predict lower quit rates, and contingent staffing, electronic monitoring, and variable pay predict higher rates.
Chronic Ethanol Dysregulation and Steatosis Induced by Promoter Results in Macrophage TNF TRIF and IRF-3 Binding to the TNF

Chronic ethanol (EtOH) abuse results in the development of steatosis, alcoholic hepatitis, and cirrhosis. Augmented TNF- (cid:1) production by macrophages and Kupffer cells and signaling via the p55 TNF receptor have been shown to be critical for these effects of chronic EtOH; however, the molecular mechanisms leading to augmented TNF- (cid:1) production remain unclear. Using cell culture models and in vivo studies we demonstrate that chronic EtOH results in increased TNF- (cid:1) transcription, which is independent of NF- (cid:2) B. Using reporter assays and chromatin immunoprecipitation we found that this increased transcription is due to increased IRF-3 binding to and transactivation of the TNF promoter. As IRF-3 is downstream from the TLR4 adaptor TIR-domain-containing adapter-inducing IFN- (cid:3) (Trif), we demonstrate that macrophages from Trif (cid:4) / (cid:4) mice are resistant to this dysregulation of TNF- (cid:1) transcription by EtOH in vitro as well as EtOH-induced steatosis and TNF dysregulation in vivo. These data demonstrate that the Trif/IRF-3 pathway is a target to ameliorate liver dysfunction associated with chronic EtOH. The Journal of Immunology, 2008, 181: 3049–3056.
Detecting face region in binary image

Proposed here is a new face detection technique based on binary image. In this method, a color input image is converted to a gray image and then denoised using low pass filter. The denoised image is transformed with local window standard deviation and then binarized using adaptive thresholding method. The generated binary image has prominent boundary and facial features like eyebrow, eyes, nose and mouth regions which can be easily detected using morphological operations. The binary image is scanned vertically to find the probable region containing the face. Actual face location is found by detecting the location of eye-brow in the probable face region scanning horizontally. The method has been tested on several single shot database images and it is giving good performance of about 93%. It is also fast as compared to existing face detection schemes which require complex processing and involves training databases.
Childcare, work and immigration. Do Italian and foreign mothers behave differently?

In this paper we study two aspects of the decision-making process following the birth of a child: whether or not the mother works, and whether or not the couple provides the child with formal childcare. Focusing on Padova and its district (North-East Italy), we discuss differences in the strategies of Italian and foreign mothers, controlling for socio-economic status, opinions on women's roles, and family structure, using the Blinder-Oaxaca decomposition. Six to thirty months after the birth of a child, the proportion of foreign mothers who are not employed is more than double that of Italian mothers (51% vs. 21%). In addition, 25% of Italian women entrust their children to the care of their parents and in-laws, vs. only 13% of foreign women. Although there are differences in the effects of variables on participation at work in the two groups, what matters most is the different composition of Italian and foreign women, especially as regards education and partners’ characteristics. Even as regards the maximum price a couple is willing to pay for formal childcare, differences between the two groups can mostly be explained by differences in composition. Copyright © 2011 CSEA.
Antenna Pattern Measurement : Concepts and Techniques

The first article of this two-part series explores the basic concepts and techniques of antenna pattern measurement and evaluates the benefits and drawbacks of various measurement methods. The concepts relating to near-field and far-field pattern testing are discussed as well. The second article (see page 34) presents the theory and equations governing antenna properties and includes a complete description of a site calibration for pattern-measurement testing.
Differentially private publication of general time-serial trajectory data

Trajectory data, i.e., human mobility traces, is extremely valuable for a wide range of mobile applications. However, publishing raw trajectories without special sanitization poses serious threats to individual privacy. Recently, researchers begin to leverage differential privacy to solve this challenge. Nevertheless, existing mechanisms make an implicit assumption that the trajectories contain a lot of identical prefixes or n-grams, which is not true in many applications. This paper aims to remove this assumption and propose a differentially private publishing mechanism for more general time-series trajectories. One natural solution is to generalize the trajectories, i.e., merge the locations at the same time. However, trivial merging schemes may breach differential privacy. We, thus, propose the first differentially-private generalization algorithm for trajectories, which leverage a carefully-designed exponential mechanism to probabilistically merge nodes based on trajectory distances. Afterwards, we propose another efficient algorithm to release trajectories after generalization in a differential private manner. Our experiments with real-life trajectory data show that the proposed mechanism maintains high data utility and is scalable to large trajectory datasets.
A Phenomenological Study Concerning Turkish EFL Teachers’ Views on Differentiated Instruction

When implemented efficaciously, differentiated instruction (DI) is likely to provide scrupulous outcomes in its own right both for the language teacher and English language learners. However, it is also prone to presenting some obstacles, especially in countries like Turkey, where the common instruction is mostly given in mainstream classrooms. The purpose of this study was to ascertain Turkish EFL teachers’ views upon the rewarding sides of DI and the hindrances in its implementation. To achieve this goal, perceptions of ten Turkish EFL teachers, who had been applying DI in the same school for a certain time, were collected through written interviews. Data were analysed using phenomenological study techniques. Six major themes were derived from the analysis: heeding learners’ needs, boosting learner confidence, establishing better rapport, promoting involvement and interaction, experiencing difficulties in implementation and confronting mandatory interventions. These were quite relevant to understanding the contextual issues faced in the implementation of DI.
Mixture of the Riesz Distribution with Respect to a Multivariate Poisson

The aim of this article is to study a statistical model obtained by the mixture of the Riesz probability distribution on symmetric matrices with respect to a multivariate Poisson distribution. We show that this distribution is related to the modified Bessel function of the first kind. We then determine the domain of the means and the variance function of the generated natural exponential family.
Knowledge-Based Image Understanding: A Rule-Based Production System for X-Ray Segmentation

Image Understanding (IU) concerns the issues of how to interpret images. Knowledge-based image understanding studies the theory and techniques of computational image understanding, which uses explicit, independent knowledge about the images, such as their context and objects in them, as well as knowledge about the imaging system. Two related disciplines, Artificial Intelligence (AI) and Image Processing (IP), can contribute significantly to image understanding. A rule-based production system is a widely used knowledge representation technique, which may be used to capture various kinds of knowledge, such as perceptual, functional, and semantic knowledge, in image understanding system. This paper addresses some issues of knowledge-based approach to image understanding, presents a rule-based production system for X-ray segmentation, and proposes its expansion of incorporation with multiple knowledge sources. Here we just present the segmentation part of our research project, which aims at applying knowledge-based approach to interpret X-ray images of bone and to identify the fractured regions.
A practical TDOA positioning method for CDMA2000 mobile network

The location technology based on time difference of arrival (TDOA) is one of the key technologies in The 3rd Generation Telecommunication. In this paper, TDOA positioning method based on modified Chan algorithm for CDMA2000 mobile network is proposed. Pilot delay measurement is adopted to realize TDOA positioning parameter detection. A mathematical model of TDOA positioning is established and the location solving method under ideal Gauss circumstance is put forward. In accordance with the trait of Non Light of Sight (NLOS) propagation delay obeying index distribution in the mobile communication environment, NLOS estimation covariance correction method is presented to decrease the NLOS influence upon positioning accuracy. Theoretical analysis and simulation results show that the positioning method in discussion is possessed with good qualities of positioning in actual channel environment. Meanwhile, with the low computational complexity, the proposed algorithm is well applied to mobile location of CDMA2000 telecommunication systems.
An Improved Localization Algorithm for Wireless Sensor Network Based on the Selection of Benchmark Anchor Node

To improve the localization precision of nodes in Wireless sensor network (WSN), this paper analyses the source of the localization error in the least square localization algorithm (LSL), and it can be concluded that the minimum cumulative relative distance error of the benchmark anchor node directly influence the localization precision. Based on the analyses, this paper proposes an improved least square algorithm, which is the minimum cumulative related distance error in LSL (LSL-MCR) algorithm. In the improved algorithm, we give a new principle to choose the benchmark anchor node. The simulation results indicate that the proposed algorithm can improve the localization precision of the unknown nodes.
Size distributions of elemental carbon in a coastal urban atmosphere in South China: characteristics, evolution processes, and implications for the mixing state

Elemental carbon (EC), as one of the primary light-absorbing components in the atmosphere, has a significant impact on both regional and global climate. The environmental impacts of EC are strongly dependent on its particle size. Little is known about the size distribution characteristics of EC particles in the ambient environments of China. We here report size distributions of EC in the urban area of Shenzhen in South China. EC consistently exhibited two modes, a fine and a coarse mode. The majority of EC (~80%) in this coastal metropolitan city resided in particles smaller than 3.2 ? m in diameter. The fine mode peaked at around either 0.42 ? m or 0.75 ? m. While the mode at 0.42 ? m could be ascribed to fresh vehicular emissions in this region, the mode at 0.75 ? m had to be a result of particle growth from smaller EC particles. We made a theoretical investigation of the particle growth processes that were responsible for EC particles to grow from 0.42 ? m to 0.75 ? m in the atmosphere. Our calculations indicate that the EC peak at 0.75 ? m could not be produced through either coagulation or H2SO4 condensation; both were too slow to lead to significant EC growth. Hygroscopic growth was also calculated to be impossible. Instead, addition of sulfate through in-cloud processing was found to be able to significantly grow EC particles to explain the EC peak at 0.75 ? m. We also estimated from the EC size distributions the mixing state of EC. In the droplet size, at least 45? 60% of EC mass in the summer samples and 68% of EC mass in the winter samples was internally mixed with sulfate as a result of in-cloud processing. Such information on EC needs to be considered in modeling aerosol optical properties in this region. Our results also suggest that the in-cloud processing of primary EC particles could enhance light absorbing capacities through mixing EC and sulfate.
COSMIC EVOLUTION OF STAR FORMATION IN TYPE-1 QUASAR HOSTS SINCE z = 1

We present Spitzer Infrared Spectrograph observations of a complete sample of 57 Sloan Digital Sky Survey type-1 quasars at z ∼ 1. Aromatic features at 6.2 and/or 7.7 μm are detected in about half of the sample and show profiles similar to those seen in normal galaxies at both low and high redshift, indicating a star formation origin for the features. Based on the ratio of aromatic to star formation infrared (SFIR) luminosities for normal star-forming galaxies at z ∼ 1, we have constructed the SFIR luminosity function (LF) of z ∼ 1 quasars. As we found earlier for low-redshift Palomar-Green (PG) quasars, these z ∼ 1 quasars show a flatter SFIR LF than do z ∼ 1 field galaxies, implying the quasar host galaxy population has on average a higher star formation rate (SFR) than the field galaxies do. As measured from their SFIR LF, individual quasar hosts have on average LIRG-level SFRs, which mainly arise in the circumnuclear regions. By comparing with similar measurements of low-redshift PG quasars, we find that the comoving SFIR luminosity density in quasar hosts shows a much larger increase with redshift than that in field galaxies. The behavior is consistent with pure density evolution since the average SFR and the average SFR/BH accretion rate in quasar hosts show little evolution with redshift. For individual quasars, we have found a correlation between the aromatic-based SFR and the luminosity of the nuclear radiation, consistent with predictions of some theoretical models. We propose that type-1 quasars reside in a distinct galaxy population that shows elliptical morphology but that harbors a significant fraction of intermediate-age stars and is experiencing intense circumnuclear star formation.
Formation of Central Massive Objects via Tidal Compression

For a density that is not too sharply peaked toward the center, the local tidal field becomes compressive in all three directions. Available gas can then collapse and form a cluster of stars in the center, including or even being dominated by a central black hole. We show that for a wide range of (deprojected) Sérsic profiles in a spherical potential, the tidal forces are compressive within a region that encloses most of the corresponding light of observed nuclear clusters in both late- and early-type galaxies. In such models, tidal forces become disruptive nearly everywhere for relatively large Sérsic indices n≳ 3.5. We also show that the mass of a central massive object (CMO) required to remove all radial compressive tidal forces scales linearly with the mass of the host galaxy. If CMOs formed in (progenitor) galaxies with n ∼ 1, we predict a mass fraction of ~0.1% to 0.5%, consistent with observations of nuclear clusters and supermassive black holes. While we find that tidal compression possibly drives the formation of CMOs in galaxies, beyond the central regions and on larger scales in clusters disruptive tidal forces might contribute to prevent gas from cooling.
Performance Analysis of Fast Fourier Transform For Complex Data Vectors on Different Systems Using Sequential and Parallel Approach

The Fast Fourier Transform is very useful in many applications like weather forecasting, Computational Fluid Dynamics Problem, Automobile crash Analysis. In this paper ,the execution of Fast Fourier Transform is analyzed and the results are compared based on serial and parallel programming on different processors. When the execution of Fast Fourier Transform of complex data vectors using OpenMP for parallel execution is tested then it is giving better results as compared to serial execution. In the parallel approach the result is varying with the number of cores available in the system. The program using OpenMP is tested by varying the value of N. N is length of vector. To measure the performance using Fast Fourier Transform ,the parameters used for comparison are Time and MFLOPS. The programs of Fast Fourier Transform based on different approaches were tested on dual core and quad core machines. The first model used is Intel(R) Pentium(R) CPU G640 consider for testing with processor speed of 2.80GHz and CPU's speed is 1700 MHz and second model Intel(R) Core(TM) i3 with processor speed is 2.53 GHz and CPU's speed is 931 MHz Both the models having different processors and they are giving different performance. It has been observed that the performance of Fast Fourier Transform is found improved when the processors executed their code using parallel approach as compared to sequential approach and we can say its a better utilization of processor time . On Dual core processor for N value 33554432, the performance is 502.27 MFLOPS and time required is 16.7 seconds using sequential approach and the performance is 681.6 MFLOPS and time required is 12.30 seconds using parallel approach. On Quad core machine, we have achieved successfully the performance of about 597.27 MFLOPS and time required is 14.04 seconds using parallelism and for the same N value 33554432,the getting on quad core processor and for sequential execution getting 368.32 MFLOPS and time required is 22.77 seconds .