Miracle-dz/UniFAR-FTUs huggingface dataset:
Elastin-Coated Biodegradable Photopolymer Scaffolds for Tissue Engineering Applications

One of the main open issues in modern vascular surgery is the nonbiodegradability of implants used for stent interventions, which can lead to small caliber-related thrombosis and neointimal hyperplasia. Some new, resorbable polymeric materials have been proposed to substitute traditional stainless-steel stents, but so far they were affected by poor mechanical properties and low biocompatibility. In this respect, a new material, polypropylene fumarate (PPF), may be considered as a promising candidate to implement the development of next generation stents, due to its complete biodegradability, and excellent mechanical properties and the ease to be precisely patterned. Besides all these benefits, PPF has not been tested yet for vascular prosthesis, mainly because it proved to be almost inert, while the ability to elicit a specific biological function would be of paramount importance in such critical surgery applications. Here, we propose a biomimetic functionalization process, aimed at obtaining specific bioactivation and thus improved cell-polymer interaction. Porous PPF-based scaffolds produced by deep-UV photocuring were coated by elastin and the functionalized scaffolds were extensively characterized, revealing a stable bound between the protein and the polymer surface. Both 3T3 and HUVEC cell lines were used for in vitro tests displaying an enhancement of cells adhesion and proliferation on the functionalized scaffolds.
Traffic event detection from road surveillance vide os based on fuzzy logic

This work is about the autonomous detection of a road traffic incident by exploiting road surveillance camera videos. Timely and autonomous detection of an incident is paramount for the reduction of traffic congestion so that countermeasures can be taken at the earliest. This paper presents a novel Fuzzy Logic based analysis framework and a video based traffic data extraction scheme to decide upon the right traffic conditions. The existing road traffic analysis approaches as reported in literature do not extract data from the road camera videos; rather they use already available data to validate their schemes. However, in the proposed approach a complete scheme is proposed which takes a raw road camera video and autonomously extracts the relevant data for the subsequent Fuzzy Logic based traffic analysis. To show the efficacy of the proposed scheme, unprocessed surveillance videos of both urban and motorway scenarios are used. The results indicate that the traffic flow and their statistics are adequately determined through the proper selection of membership functions and rule formulation. Owing to the use of fuzzy logic, our proposed framework is seen to be robust enough to reject the noisy data coming from surveillance videos.
Empirical Evaluation of Bug Linking

To collect software bugs found by users, development teams often set up bug trackers using systems such as Bugzilla. Developers would then fix some of the bugs and commit corresponding code changes into version control systems such as svn or git. Unfortunately, the links between bug reports and code changes are missing for many software projects as the bug tracking and version control systems are often maintained separately. Yet, linking bug reports to fix commits is important as it could shed light into the nature of bug fixing processes and expose patterns in software management. Bug linking solutions, such as ReLink, have been proposed. The demonstration of their effectiveness however faces a number of issues, including a reliability issue with their ground truth datasets as well as the extent of their measurements. We propose in this study a benchmark for evaluating bug linking solutions. This benchmark includes a dataset of about 12,000 bug links from 10 programs. These true links between bug reports and their fixes have been provided during bug fixing processes. We designed a number of research questions, to assess both quantitatively and qualitatively the effectiveness of a bug linking tool. Finally, we apply this benchmark on ReLink to report the strengths and limitations of this bug linking tool.
Locked in Sequence and Stuck on Skills in a College-for-All Culture for Urban Latinx Youth

This case study of one small urban California high school enrolling predominantly low-socioeconomic status (SES) Latinx youth and many emergent bilinguals found that a college-for-all school culture, guided by leadership and school vision, was enacted in classrooms as caring, safe, productive spaces promoting college-going comportment. However, support exceeded challenge, with routine scaffolds and formulaic activity. There was less evidence of learning opportunities that challenged intellectual capacities and students’ analytic processes. Instruction overall maintained a sequential format of support, study skills, and content skills before challenging disciplinary work, with basic and intermediate academic literacies seldom embedded in activity that engaged higher order thinking, creativity, and imagination.
Learning with few examples: An empirical study on leading classifiers

Learning algorithms proved their ability to deal with large amount of data. Most of the statistical approaches use defined size learning sets and produce static models. However in specific situations: active or incremental learning, the learning task starts with only very few data. In that case, looking for algorithms able to produce models with only few examples becomes necessary. The literature's classifiers are generally evaluated with criterion such as: accuracy, ability to order data (ranking). But this classifiers' taxonomy can dramatically change if the focus is on the ability to learn with just few examples. To our knowledge, just few studies were performed on this problem. The study presented in this paper aims to study a larger panel of both algorithms (9 different kinds) and data sets (17 UCI bases).
Modulation scaling for real-time energy aware packet scheduling

Portable wireless communication systems operate on a limited battery supply, and energy efficiency is therefore crucial. Voltage scaling techniques have been proposed to lower the energy consumption of embedded processors and real-time operating systems have incorporated these schemes in their task scheduling engine. However, the actual data transmission itself constitutes a major portion of the total energy consumption in these wireless communication systems. In this paper, we extend the scaling notion to the realm of wireless communications and propose a novel technique called modulation scaling to decrease the energy consumed during data transmission. Modulation scaling trades off energy consumption against transmission delay and as such, introduces the concept of energy awareness in communications. We investigate how modulation scaling can be exploited to design a dynamic power management engine at the level of the radio. This engine coordinates the packet transmission schedule while optimizing energy efficiency. We demonstrate such a power management module for real-time traffic and show that it reduces the energy consumption of data transmissions by up to 50 % through smart traffic scheduling.
How to achieve the optimal DMT of selective fading MIMO channels?

In this paper, we extend the non-vanishing determinant (NVD) criterion to the selective fading channel case. A new family of split NVD parallel codes, that satisfies this design criterion, is proposed to achieve the optimal diversity multiplexing tradeoff (DMT) derived by Coronel and Bölcskei, IEEE ISIT, 2007. This result is of significant interest not only in its own right, but also because it settles a long-standing debate in the literature related to the optimal DMT of selective fading channels.
The Synthesis of Symmetrical Waveguide Circulators *

A method for synthesizing symmetrical wavegnide circulators by adjusting the eigenvalues of the scattering matrix is described. This procedure is particularly useful for the design of very compact circulators in the form of waveguide junctions containhg ferrite obstacles. Permissible structural symmetries for a circulator are listed, and a standard form for the scattering matrix of a symmetrical circulator is defined. The synthesis procedure is then described in detail, stating the conditions to be imposed on the scattering matrix eigenvalues, and an expression is obtained for the changes in the eigenvalues due to the placing of anisotropic material within the junction. By applying the theory to Allen’s 4-port turnstile circulator, it is shown that the use of a matched turnstile junction and a reflectionless Faraday rotator is not essential. The theory is also applied to the design of novel 3and 4-port circulators, and two 6-port circulators, one of which may be used as a 5-position waveguide switch, are described. Some experimental results are presented for a compact 3-port circulator in the form of an H-plane Y junction, in 1 inch by ~ inch waveguide, containing a ferrite post obstacle. This circulator, which operates with a bias field of approximately 25 oersted, has a useful bandwidth of 3 per cent. Greater bandwidths would be expected in a Stripline or a fin-line version of tils device.
Content based Image Retrieval and Classification using Support Vector Machine

Content Based Image Retrieval (CBIR) is a traditional and developing trend in Digital Image Processing. Therefore the use of CBIR to search and retrieve the query image from wide range of database is increasing. In this paper we are going to explore an efficient image retrieval technique which uses local color, shape and texture features. So, efficient image retrieval algorithms based on RGB histograms, Geometric moment and Co-occurrence Model is proposed for color, shape and texture respectively. Results based on this approach are found encouraging in terms of color, shape and texture image classification accuracy. After the features are selected, an SVM classifier is trained to distinguish between relevant and irrelevant images accordingly.
Molecular Evolution of Zika Virus during Its Emergence in the 20th Century

Zika virus (ZIKV) is a mosquito-borne flavivirus first isolated in Uganda in 1947. Although entomological and virologic surveillance have reported ZIKV enzootic activity in diverse countries of Africa and Asia, few human cases were reported until 2007, when a Zika fever epidemic took place in Micronesia. In the context of West Africa, the WHO Collaborating Centre for Arboviruses and Hemorrhagic Fever at Institut Pasteur of Dakar (http://www.pasteur.fr/recherche/banques/CRORA/) reports the periodic circulation of ZIKV since 1968. Despite several reports on ZIKV, the genetic relationships among viral strains from West Africa remain poorly understood. To evaluate the viral spread and its molecular epidemiology, we investigated 37 ZIKV isolates collected from 1968 to 2002 in six localities in Senegal and Côte d'Ivoire. In addition, we included strains from six other countries. Our results suggested that these two countries in West Africa experienced at least two independent introductions of ZIKV during the 20th century, and that apparently these viral lineages were not restricted by mosquito vector species. Moreover, we present evidence that ZIKV has possibly undergone recombination in nature and that a loss of the N154 glycosylation site in the envelope protein was a possible adaptive response to the Aedes dalzieli vector.
Review of: David Temperley, The Cognition of Basic Musical Structures Cambridge, MA: MIT Press, 2001, 404 pp. ISBN 0-262-20134-8.

In The Cognition of Basic Musical Structures, David Temperley presents a computational theory of music cognition that is deeply influenced by Lerdahl and Jackendoff’s (1983) A Generative Theory of Tonal Music (henceforth, GTTM). Like Lerdahl and Jackendoff, Temperley attempts to explain the cognition of commonpractice music by means of a system that generates structural descriptions from musical ‘surfaces’. As in GTTM, the hypothesis underlying Temperley’s theory is that the analysis it generates for a passage of common-practice music correctly describes certain aspects of how the passage is interpreted by listeners who are experienced in the idiom.
The m-reduction in conformal field theory as the Morita equivalence on two-tori

We study the Morita equivalence for field theories on noncommutative two-tori. For rational values of the noncommutativity parameter θ (in appropriate units) we show the equivalence between an abelian noncommutative field theory and a nonabelian theory of twisted fields on ordinary space. We concentrate on a particular conformal field theory (CFT), the one obtained by means of the m-reduction procedure [1], and show that the Morita equivalence also holds at this level. An application to the physics of a quantum Hall fluid at Jain fillings ν = m/(2pm+1) is explicitly considered in order to further elucidate such a correspondence.
The Effect of Vertical Wind Shear on Radiative-Convective Equilibrium States

Abstract Using a three-dimensional cloud ensemble model, a systematic exploration is undertaken of radiative–convective equilibrium states as a function of the structure and magnitude of an imposed background flow with vertical shear. In such simulations, mesoscale organization appears naturally, independent of the particulars of the initial condition. As the magnitude of an imposed low-level shear increases, the convection becomes increasingly organized in lines or arcs, propagating broadly downshear, as predicted by earlier work. When the shear is very strong, the convection tends to organize into lines at an angle to the shear, such that the line-normal component is not far from its theoretical optimal value. Midlevel shear favors shear-parallel lines, but if it occurs in conjunction with sufficiently strong low-level shear, the convection can become very strongly organized into lines or arcs generally orthogonal to the low-level shear. Optimal organization occurs when the depth of the shear layer is c.
Aerosol retrieval from remote sensing image using artificial neural network

The usual method of aerosol retrieval using remote sensing is interpolation of look-up-table (LUT), but it is too time-consuming. However, artificial neural network for nonlinear problem has been not applied widely for aerosol retrieval before. In this paper, aerosol optical depth (AOD) is retrieved using two methods: interpolation and neural network. Then, the retrieval capabilities of the two methods were compared. By comparison, not only is the retrieval error of the neural network within acceptable range, but also it can reduce much processing time.
Assembly mechanisms of RNA pseudoknots are determined by the stabilities of constituent secondary structures

Understanding how RNA molecules navigate their rugged folding landscapes holds the key to describing their roles in a variety of cellular functions. To dissect RNA folding at the molecular level, we performed simulations of three pseudoknots (MMTV and SRV-1 from viral genomes and the hTR pseudoknot from human telomerase) using coarse-grained models. The melting temperatures from the specific heat profiles are in good agreement with the available experimental data for MMTV and hTR. The equilibrium free energy profiles, which predict the structural transitions that occur at each melting temperature, are used to propose that the relative stabilities of the isolated helices control their folding mechanisms. Kinetic simulations, which corroborate the inferences drawn from the free energy profiles, show that MMTV folds by a hierarchical mechanism with parallel paths, i.e., formation of one of the helices nucleates the assembly of the rest of the structure. The SRV-1 pseudoknot, which folds in a highly cooperative manner, assembles in a single step in which the preformed helices coalesce nearly simultaneously to form the tertiary structure. Folding occurs by multiple pathways in the hTR pseudoknot, the isolated structural elements of which have similar stabilities. In one of the paths, tertiary interactions are established before the formation of the secondary structures. Our work shows that there are significant sequence-dependent variations in the folding landscapes of RNA molecules with similar fold. We also establish that assembly mechanisms can be predicted using the stabilities of the isolated secondary structures.
A Review on Nonlinear Methods Using Electroencephalographic Recordings for Emotion Recognition

Electroencephalographic (EEG) recordings are receiving growing attention in the field of emotion recognition, since they monitor the brain’s first response to an external stimulus. Traditionally, EEG signals have been studied from a linear viewpoint by means of statistical and frequency features. Nevertheless, given that the brain follows a completely nonlinear and nonstationary behavior, linear metrics present certain important limitations. In this sense, the use of nonlinear methods has recently revealed new information that may help to understand how the brain works under a series of emotional states. Hence, this paper summarizes the most recent works that have applied nonlinear methods in EEG signal analysis for emotion recognition. This paper also identifies some nonlinear indices that have not been employed yet in this research area.
On convergence of non-linear extended state observer for multi-input multi-output systems with uncertainty

In this study, the convergence of non-linear extended state observer (ESO) for a class of multi-input multi-output non-linear systems with uncertainty is studied. The unknown part that comes from either the system itself or the external disturbance is considered as an augmented state. The state variable and augmented state are estimated simultaneously through the ESO. It is shown that with the pertinent choice of non-linear functions for observer, the error between the state and observer can be as small as desired when the high-gain tuning parameter is sufficiently small. The current control for permanent-magnet synchronous motor is applied.
Gaining insight into programs that analyze programs: by visualizing the analyzed program

Visualization of a program typically entails low level views of the programexecution state showing, for example,method invocations or relations amongst heap objects. In most cases, this would imply visualization of the executable program. However there is a certain genre of programs that analyze or transform other programs. These programs could be compilers, static bug detectors, test suite analyzers, model to model transformers etc. In such cases, very often, it helps to visualize what is happening to the input program rather than the analyzer program. It is for such programs that we describe a configurable, analysis framework. For ease of exposition, we call the analyzer programthe "manipulate" program, and the input programthe "puppet" program. To facilitate the visualization, we instrument the manipulate program to generate a dump as it analyzes the puppet program. Using the "dump", we reconstruct the interprocedural control flow graph of the puppet program and then visualize the flow of the manipulate program over the puppet program. We use colors to highlight different events in the manipulate program. Using this scheme, we are able to (1) gain insight into the manipulate program; (2) collect useful information / statistics about the puppet program.We have implemented the visualizer in a tool called "INSIGHT". We ran INSIGHT on a static debugging tool (the manipulate program) called XYLEM. XYLEM applies static analysis to find potential null pointer exceptions in a puppet program, as for example, the Apache Ant program. We report the insights gained by running XYLEM through INSIGHT on ANT and other puppet programs.
NCBI GEO: archive for functional genomics data sets—10 years on

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi. nlm.nih. gov/geo/.
Another approach to save energy in OFDM systems

In this paper, we propose an energy-efficient error correction scheme to lower the power consumption of the ADCs in the OFDM system. The proposed opportunistic error correction scheme is based on resolution adaptive ADCs and fountain codes. The key idea is to reduce the dynamic range of the channel by discarding part of the channel in deep fading. Correspondingly, the power consumption in ADCs can be decreased. In our approach, each sub-carrier transports a fountain-encoded packet. The receiver only decodes fountain-encoded packets with high SNR. Others are discarded. To compensate for the discarded packets, a high order modulation is used. The new error correction layer does not require perfect channel knowledge, so it can be applied in a real system. With our approach and 16-QAM, the energy consumption in ADCs is reduced by around 73% with non-perfect channel estimation comparing to the traditional IEEE 802.11a system under the same channel conditions and throughput.
The Evolution of Organismal Complexity in Angiosperms as Measured by the Information Content of Taxonomic Descriptions

We describe an information theoretic method for measuring relative organismal complexity. The complexity measure is based on the amount of information contained in formal taxonomic descriptions of organisms. We examine the utility of this measure for quantifying the complexity of plant families. The descriptions are subjective by nature, but we find a significant correlation in the complexity values of plant families from two independently authored sets of formal taxonomic descriptions. An analysis of the evolution of complexity across angiosperms found evidence of a pattern of increasing complexity. Our measure of complexity provides an operational definition of complexity that may be applied to any group of organisms and will enable further empirical studies of the evolution of complexity.
A Comparative Study of Various Controllers for Static Synchronous Series Compensator Integrated with Superconducting Magnetic Energy Storage System

A transient stability analysis is done for a multi-area power system with Static Synchronous Series Compensator (SSSC) integrated with Superconducting Magnetic Energy Storage (SMES) system. The SSSC is realized with Voltage Source Inverters (VSI) and the SMES is realized as a coil. The real and reactive power reference values are set constant and a three phase fault is created in one of the transmission lines and the power output from the generator and the load angle of the machine are analysed for three cases: first one with conventional PI controller, the second with fuzzy logic controller and the third with neural network controller. The comparative results are tabulated and it is inferred that the intelligent controllers perform well under transient stability conditions compared to the conventional controller. Matlab 7.0Simulink software is used as a platform for the simulation.