Miracle-dz/UniFAR-FTUs huggingface dataset:
Ranking Web Search Results Using Personal Preferences

The diversity of content on the web has exploded exponentially, while our vocabulary to parse it remains at a relative plateau. It is increasingly difficult for search engines to understand what the user really wants by considering only the query terms [1]. For instance, a wildlife photographer searching for “jaguar” is probably looking for information on the animal, while an automobile enthusiast is probably looking for the sports car. In this paper, we present a study of algorithms for personalizing search results based on the user’s search history.
Domain adaptation methods for ECG classification

The detection and classification of heart arrhythmias using Electrocardiogram signals (ECG) has been an active area of research in the literature. Usually, to assess the effectiveness of a proposed classification method, training and test data are extracted from the same ECG record. However, in real scenarios test data may come from different records. In this case, the classification results may be less accurate due to the statistical shift between these samples. In order to solve this issue, we investigate, in this paper, the capabilities of two domain adaption methods proposed recently in the literature of machine learning. The first is known as domain transfer SVM, whereas the second is the importance weighted kernel logistic regression method. To assess the effectiveness of both methods, the MIT-BIH arrhythmia database is used in the experiments.
Comprehensive Multiplex One-Step Real-Time TaqMan qRT-PCR Assays for Detection and Quantification of Hemorrhagic Fever Viruses

Background Viral hemorrhagic fevers (VHFs) are a group of animal and human illnesses that are mostly caused by several distinct families of viruses including bunyaviruses, flaviviruses, filoviruses and arenaviruses. Although specific signs and symptoms vary by the type of VHF, initial signs and symptoms are very similar. Therefore rapid immunologic and molecular tools for differential diagnosis of hemorrhagic fever viruses (HFVs) are important for effective case management and control of the spread of VHFs. Real-time quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) assay is one of the reliable and desirable methods for specific detection and quantification of virus load. Multiplex PCR assay has the potential to produce considerable savings in time and resources in the laboratory detection. Results Primers/probe sets were designed based on appropriate specific genes for each of 28 HFVs which nearly covered all the HFVs, and identified with good specificity and sensitivity using monoplex assays. Seven groups of multiplex one-step real-time qRT-PCR assays in a universal experimental system were then developed by combining all primers/probe sets into 4-plex reactions and evaluated with serial dilutions of synthesized viral RNAs. For all the multiplex assays, no cross-reactivity with other HFVs was observed, and the limits of detection were mainly between 45 and 150 copies/PCR. The reproducibility was satisfactory, since the coefficient of variation of Ct values were all less than 5% in each dilution of synthesized viral RNAs for both intra-assays and inter-assays. Evaluation of the method with available clinical serum samples collected from HFRS patients, SFTS patients and Dengue fever patients showed high sensitivity and specificity of the related multiplex assays on the clinical specimens. Conclusions Overall, the comprehensive multiplex one-step real-time qRT-PCR assays were established in this study, and proved to be specific, sensitive, stable and easy to serve as a useful tool for rapid detection of HFVs.
Sparse Representation-Based SAR Image Target Classification on the 10-Class MSTAR Data Set

Recent years have witnessed an ever-mounting interest in the research of sparse representation. The framework, Sparse Representation-based Classification (SRC), has been widely applied as a classifier in numerous domains, among which Synthetic Aperture Radar (SAR) target recognition is really challenging because it still is an open problem to interpreting the SAR image. In this paper, SRC is utilized to classify a 10-class moving and stationary target acquisition and recognition (MSTAR) target, which is a standard SAR data set. Before the classification, the sizes of the images need to be normalized to maintain the useful information, target and shadow, and to suppress the speckle noise. Specifically, a preprocessing method is recommended to extract the feature vectors of the image, and the feature vectors of the test samples can be represented by the sparse linear combination of basis vectors generated by the feature vectors of the training samples. Then the sparse representation is solved by l 1 -norm minimization. Finally, the identities of the test samples are inferred by the reconstructive errors calculated through the sparse coefficient. Experimental results demonstrate the good performance of SRC. Additionally, the average recognition rate under different feature spaces and the recognition rate of each target are discussed.
Glamour vs . Value : The Real Story April

Does stock market misvaluation affect investment? We use cross-sectional variation between glamour (high stock price) and value (low stock price) portfolios to test whether there is a relations hip between misvaluation and fixed investment. In a large sample of U.S. firms over the period 1980-2001, glamour firms invest substantially more than value firms. If glamour firms are responding to misvaluation rather than fundamentals, then they may be investing too much. We describe and implement four new tests designed to distinguish whether the high investment of glamour firms is the result of fundamental shocks or misvaluation shocks: investment reversals, stock market returns of " overinvesting " glamour firms, the time path of the marginal product of capital, and overreaction tests. In addition, we provide parametric estimates of the effect of misvaluation on investment; the parametric estimates suggest that a one standard deviation increase in misvaluation raises investment by more than 40%. We consider the possibility that overinvestment might be due to excessive optimism on the part of managers-and present empirical specifications designed to detect whether either the active financing mechanism (cheap equity finance) or managerial excess optimism influence overinvestment.
Ambient Search: A Document Retrieval System for Speech Streams

We present Ambient Search, an open source system for displaying and retrieving relevant documents in real time for speech input. The system works ambiently, that is, it unobstructively listens to speech streams in the background, identifies keywords and keyphrases for query construction and continuously serves relevant documents from its index. Query terms are ranked with Word2Vec and TF-IDF and are continuously updated to allow for ongoing querying of a document collection. The retrieved documents, in our case Wikipedia articles, are visualized in real time in a browser interface. Our evaluation shows that Ambient Search compares favorably to another implicit information retrieval system on speech streams. Furthermore, we extrinsically evaluate multiword keyphrase generation, showing positive impact for manual transcriptions.
Trypanosoma cruzi IIc: Phylogenetic and Phylogeographic Insights from Sequence and Microsatellite Analysis and Potential Impact on Emergent Chagas Disease

Trypanosoma cruzi, the etiological agent of Chagas disease, is highly genetically diverse. Numerous lines of evidence point to the existence of six stable genetic lineages or DTUs: TcI, TcIIa, TcIIb, TcIIc, TcIId, and TcIIe. Molecular dating suggests that T. cruzi is likely to have been an endemic infection of neotropical mammalian fauna for many millions of years. Here we have applied a panel of 49 polymorphic microsatellite markers developed from the online T. cruzi genome to document genetic diversity among 53 isolates belonging to TcIIc, a lineage so far recorded almost exclusively in silvatic transmission cycles but increasingly a potential source of human infection. These data are complemented by parallel analysis of sequence variation in a fragment of the glucose-6-phosphate isomerase gene. New isolates confirm that TcIIc is associated with terrestrial transmission cycles and armadillo reservoir hosts, and demonstrate that TcIIc is far more widespread than previously thought, with a distribution at least from Western Venezuela to the Argentine Chaco. We show that TcIIc is truly a discrete T. cruzi lineage, that it could have an ancient origin and that diversity occurs within the terrestrial niche independently of the host species. We also show that spatial structure among TcIIc isolates from its principal host, the armadillo Dasypus novemcinctus, is greater than that among TcI from Didelphis spp. opossums and link this observation to differences in ecology of their respective niches. Homozygosity in TcIIc populations and some linkage indices indicate the possibility of recombination but cannot yet be effectively discriminated from a high genome-wide frequency of gene conversion. Finally, we suggest that the derived TcIIc population genetic data have a vital role in determining the origin of the epidemiologically important hybrid lineages TcIId and TcIIe.
Methods for Measuring Sedimentation Rates in Bottomland Hardwood ( BLH ) Wetlands

PURPOSE: This note describes four methods that can be used to measure sedimentation rates in BLH forests and other wetland systems. Time are: a modified sediment trap method, called a sediment disk; use of a feldspar clay marker horizon; use of *37cesiumfor dating cores; and a dendrogeomorphic method. The advantages and disadvantages of the methods are discussed and their application to wetland regulation and evaluation considered.
Color palette generation for image classification by bag-of-colors

There are a large number of colors to represent images (e.g. 256256256 = 16,777,216 colors in an RGB color space) on computers. Since there are too many colors to handle, a large number of colors are reduced by quantization in the image processing in general. When we perform a uniform color quantization, we often get colors which do not fit the real world. Therefore, typical colors should be learned from real world images to generate a practical color palette. The bag-of-visual words based only on local features of grayscale pixel values provides the state of the art technology in the field of image classification, retrieval and recognition. Therefore it is expected to improve the performance by adding the color information to the local features. However, if we increase the number of features to extract from images, it costs memory and time for computation. Moreover, the increase of features affects the performance of recognition. The aim of this paper is to generate appropriate color palette for image classification by the bag-of-colors with less computation time and as few colors as possible to improve the accuracy of image classification.
Improving error performance of Joint Channel and Network Coding in Multiple Access Relay Channel

In this paper, we propose a technique to improve the performance of Joint Channel and Network Coding (JCNC) scheme in Multiple Access Relay Channel (MARC). This technique is motivated by the observation that decoding quality is improved when channel output can be processed iteratively. Using different permutation patterns for different users, we enabled more scenarios that destination can apply iterative decoding, thereby achieving an improvement in the overall performance. The proposed scheme is evaluated for Gaussian channels and Rayleigh fading channels, and it is shown to perform well in both cases. A comparative study is also given, and it is shown that up to 3dB and 6dB gain from the original JCNC scheme is achievable in AWGN and Rayleigh fading channels respectively.
A new SVM bound for information retrieval

Support vector machines have met with a significant success in machine learning field, especially handling high dimensional classification tasks. Although various performance estimators for SVM have been proposed, the based bound of kernel methods have quite margin to improve the capability. In this paper, a novel Alpha-SV bound has been proposed, which are based on the span bound of the leave-one-out procedure. Experiments have shown that the proposed estimators are both effective and stable.
A overview of 3D reconstruction based on factorization

The problem of recovering both structure and motion from 2D image sequences is an important and essential task in the field of computer vision. During the last two decades, many approaches have been proposed for different applications. Among which, factorization based methods are widely studied and attracted many attentions in the computer vision society, since this kind of approach deals with all the data in all images uniformly, thus may achieve good robustness and accuracy. The factorization methods of recovering the 3D structure and motion of an object from image sequence are introduced systematically and detailedly in this paper, from the point of view on rigid object and non-rigid object. Merits and drawbacks of the techniques mentioned are analyzed and compared. Finally, some problems of current theories and methods are proposed, the problems which need further research and the development trend of this domain are presented.
Implementing BFS-based Traversals of RDF Graphs over MapReduce Efficiently

Big data describes data sets that grow so large that they become unpractical to be processed by traditional tools like database management systems, content management systems, advanced statistical analysis software, and so forth. The reason why they came into the attention of the research community is that the infrastructure to handle these data sets has become more affordable due to Cloud Computing and MapReduce based open-source frameworks. Moreover the effectiveness of analysis on such data sets is supported by Semantic Web technologies, which employ the Resource Description Framework (RDF) model to represent data via a graph-shaped representation. In this paper we present an approach for efficiently implementing traversals of RDF graphs over MapReduce that is based on the Breadth First Search (BFS) strategy for visiting (RDF) graphs to be decomposed and processed according to the MapReduce framework. We demonstrate how such implementation speedsup the analysis of RDF graphs with respect to competitor approaches. Experimental results clearly support our contribution.
Annoyance Caused by Noise and Air Pollution during Pregnancy: Associated Factors and Correlation with Outdoor NO2 and Benzene Estimations

This study aimed to describe the degree of annoyance among pregnant women in a Spanish cohort and to examine associations with proximity to traffic, NO2 and benzene exposure. We included 2457 participants from the Spanish Childhood and Environment study. Individual exposures to outdoor NO2 and benzene were estimated, temporally adjusted for pregnancy. Interviews about sociodemographic variables, noise and air pollution were carried out. Levels of annoyance were assessed using a scale from 0 (none) to 10 (strong and unbearable); a level of 8 to 10 was considered high. The reported prevalence of high annoyance levels from air pollution was 11.2% and 15.0% from noise; the two variables were moderately correlated (0.606). Significant correlations between NO2 and annoyance from air pollution (0.154) and that from noise (0.181) were observed. Annoyance owing to noise and air pollution had a low prevalence in our Spanish population compared with other European populations. Both factors were associated with proximity to traffic. In multivariate models, annoyance from air pollution was related to NO2, building age, and country of birth; annoyance from noise was only related to the first two. The health burden of these exposures can be increased by stress caused by the perception of pollution sources.
EFL Jordanian Students’ Reaction to Written Comments on Their Written Work: A Case Study

This paper examines how Jordanian EFL students at Jerash University react to their teachers’ written feedback. In addition, the study, in its wide focus concentrates on the effect of teachers’ written feedback on students writing processes. Qualitative method was used to collect data from twenty students who belong to B.A English Language at Jerash University in their third year of study during the academic year 2014/ 2015. On one hand, the study indicates that students vary in their attitude toward teachers’ written feedback and the majority of EFL students reveal that they perceived teachers' written feedback to be useful for them in their writing processes on the other. In its conclusion, this study reveals that teachers’ written feedback have twin effects; the first one presents improving and orientating students’ revision skills, while the second one reveals the enhancement in the Jordanian EFL students’ overall writing quality.
Optimization of resistances in RL snubbers for power distribution network of integrated circuits

Resonance of parasitic impedances in power distribution network (PDN) can increase leakage of the simultaneous switching noise current from integrated circuits (ICs) in the radio frequency (RF) range. The leaking SSN current is a major possible source of the conducted electromagnetic interference (EMI). A method have been proposed to control the PDN resonance by inserting a parallel RL circuit, RL snubber, to damp the resonance. In the previous work, the optimal resistance of the RL snubbers had been determined based on an equivalent circuit of PDN where equivalent series inductances (ESLs) on package had been neglected. In this work, the equivalent circuit was improved as the ESLs on package were taken into account because they were comparable to those on-board and not negligible. A method determining the optimal resistance was also improved. The RL snubbers were applied with the improved optimal resistance to a typical PDN. Effects of the RL snubbers in reducing the RF power current and in improving the power integrity were demonstrated in circuit simulations. Results of the demonstration confirmed that the improved method for optimal resistance gives more EMI reduction and better PI than the method in the previous work.
Traffic Performance Analysis of Manet Routing Protocol

The primary objective of this research work is to study and investigate the performance measures of Gossip Routing protocol and Energy Efficient and Reliable Adaptive Gossip routing protocols. We use TCP and CBR based traffic models to analyze the performance of above mentioned protocols based on the parameters of Packet Delivery Ratio, Average End-to-End Delay and Throughput. We will investigate the effect of change in the simulation time and Number of nodes for the MANET routing protocols. For Simulation, we have used ns-2 simulator.
Acidification of the Oxygen Scavenging System in Single-Molecule Fluorescence Studies: In Situ Sensing with a Ratiometric Dual-Emission Probe

For most of the single-molecule fluorescence studies to date, biomolecules of interest are labeled with small organic dyes which suffer from their limited photostability evidenced by blinking and photobleaching. An enzymatic oxygen scavenging system of glucose oxidase and catalase is widely used to improve the dye photostability but with the unfavorable side effect of producing gluconic acid. It is known that accumulation of this byproduct in solution can lead to considerable acidification, but the uncertainty in its severity under experimentally relevant conditions has been a long-standing area of concern due to the lack of a suitable assay. In this paper we report a fluorescence-based analytical assay for quantitatively assessing the acidification of oxygen scavenging systems in situ. By using a ratiometric, dual-emission dye, SNARF-1, we observed the presence and, for the first time, measured the severity of solution acidification due to the oxygen scavenging system for a number of conditions relevant to single-molecule studies. On the basis of the quantitative analysis of the acidification profile under these conditions, practical guidelines for optimizing the oxygen scavenging system are provided. This in situ assay should be applicable to a large variety of future single-molecule fluorescence studies.
Accelerating Select where and Select Join Queries on a GPU

This paper presents implementations of a few selected SQL operations using theCUDA programming framework on the GPU platform. Nowadays, the GPU’sparallel architectures give a high speed-up on certain problems. Therefore, thenumber of non-graphical problems that can be run and sped-up on the GPUstill increases. Especially, there has been a lot of research in data mining onGPUs. In many cases it proves the advantage of oﬄoading processing fromthe CPU to the GPU. At the beginning of our project we chose the set ofSELECT WHERE and SELECT JOIN instructions as the most common op-erations used in databases. We parallelized these SQL operations using threemain mechanisms in CUDA: thread group hierarchy, shared memories, andbarrier synchronization. Our results show that the implemented highly parallelSELECT WHERE and SELECT JOIN operations on the GPU platform canbe signiﬁcantly faster than the sequential one in a database system run on theCPU.
Accent in Athematic Nouns in Vedic Sanskrit and Its Development from PIE

An Optimality Theoretic analysis of accent in Vedic Sanskrit athematic nouns is presented that builds on an analysis of the same nouns in Proto-Indo-European. The two accent patterns of Vedic (columnar and alternating) are explained by the language’s preference to realize underlying accent (where underlying accent on a root beats underlying accent on a suffix) and to put accent on the stem-final syllable if there is no underlying accent. The accentless vocative of Vedic is explained if this ending is dominant and causes an accent deletion. This dominant ending was inherited from PIE and is analyzed with OT antifaithfulness constraints.
Efficient Cargo Delivery into Adult Brain Tissue Using Short Cell-Penetrating Peptides

Zebrafish brains can regenerate lost neurons upon neurogenic activity of the radial glial progenitor cells (RGCs) that reside at the ventricular region. Understanding the molecular events underlying this ability is of great interest for translational studies of regenerative medicine. Therefore, functional analyses of gene function in RGCs and neurons are essential. Using cerebroventricular microinjection (CVMI), RGCs can be targeted efficiently but the penetration capacity of the injected molecules reduces dramatically in deeper parts of the brain tissue, such as the parenchymal regions that contain the neurons. In this report, we tested the penetration efficiency of five known cell-penetrating peptides (CPPs) and identified two– polyR and Trans – that efficiently penetrate the brain tissue without overt toxicity in a dose-dependent manner as determined by TUNEL staining and L-Plastin immunohistochemistry. We also found that polyR peptide can help carry plasmid DNA several cell diameters into the brain tissue after a series of coupling reactions using DBCO-PEG4-maleimide-based Michael’s addition and azide-mediated copper-free click reaction. Combined with the advantages of CVMI, such as rapidness, reproducibility, and ability to be used in adult animals, CPPs improve the applicability of the CVMI technique to deeper parts of the central nervous system tissues.