Miracle-dz/UniFAR-FTUs huggingface dataset:
An automated computerized methodology for the segmentation of in vivo acquired DSA images: application in the New Zealand hindlimb ischemia model

In-vivo dynamic visualization and accurate quantification of vascular networks is a prerequisite of crucial importance in both therapeutic angiogenesis and tumor anti-angiogenesis studies. A user independent computerized tool was developed, for the automated segmentation and quantitative assessment of in-vivo acquired DSA images. Automatic vessel assessment was performed employing the concept of image structural tensor. Initially, vasculature was estimated according to the largest eigenvalue of the structural tensor. The resulted eigenvalue matrix was treated as gray-matrix from which the vessels were gradually segmented and then categorized in three main sub-groups; large, medium and small-size vessels. The histogram percentiles, corresponding to 85%, 65% and 47% of prime eigenvalue gray-matrix were optimally found to give the thresholds T1, T2 and T3 respectively, for extracting vessels of different size. The proposed methodology was tested on a series of DSA images in both normal rabbits (group A) and in rabbits with experimental induced chronic hindlimb ischemia (group B). As a result an automated computerized tool was developed to process images without any user intervention in either experimental or clinical studies. Specifically, a higher total vascular area and length were calculated in group B compared to group A (p=0.0242 and p=0.0322 respectively), which is in accordance to the fact that significantly more collateral arteries are developed during the physiological response to the stimuli of ischemia.
Distributed Denial of Service Attacks Detection Method Based on Conditional Random Fields

In order to detect distributed denial of service (DDoS) attacks accurately and efficiently, a new detection model based on conditional random fields (CRF) was proposed. The CRF based model incorporates the signature-based and anomaly-based detection methods to a hybrid system. The selected features include source IP entropy, destination IP entropy, source port entropy, destination port entropy, protocol number and etc. The CRF based model combines these IP flow entropies and other fingerprints into a normalize entropy as the feature vectors to depict the states of the monitoring traffic. The training method of the detection model uses the L-BFGS algorithm. And the model only needs to inspect the IP header fields of each packet, which makes it possible for real-time implementation even on real time network traffic. The CRF based model may have the ability to detect new form of forthcoming attacks, because it is independent from any specific DDoS flooding attack tools. The experiment results show that the CRF based method has higher detection accuracy and sensitivity as well as lower false positive alarms. Experiment with KDD CUP1999, DARPA 2000 and generated attack datasets, the CRF based model outperforms other well-known detection methods such as Naive Bayes, KNN, SVM and etc. The accuracy goes beyond 95.0% and the false alarm rate is less than 5.0%. Meanwhile, the CRF based model is robust under massive background network traffic.
Joint Sparse Recovery Method for Compressed Sensing With Structured Dictionary Mismatches

In traditional compressed sensing theory, the dictionary matrix is given a priori, whereas in real applications this matrix suffers from random noise and fluctuations. In this paper, we consider a signal model where each column in the dictionary matrix is affected by a structured noise. This formulation is common in direction-of-arrival (DOA) estimation of off-grid targets, encountered in both radar systems and array processing. We propose to use joint sparse signal recovery to solve the compressed sensing problem with structured dictionary mismatches and also give an analytical performance bound on this joint sparse recovery. We show that, under mild conditions, the reconstruction error of the original sparse signal is bounded by both the sparsity and the noise level in the measurement model. Moreover, we implement fast first-order algorithms to speed up the computing process. Numerical examples demonstrate the good performance of the proposed algorithm and also show that the joint-sparse recovery method yields a better reconstruction result than existing methods. By implementing the joint sparse recovery method, the accuracy and efficiency of DOA estimation are improved in both passive and active sensing cases.
Topological Detection of Chessboard Pattern for Camera Calibration

Most works on camera calibration are directed to the stage of parameter estimation, while the phase matching is not always addressed. Most of applications assume that the correspondences are established in advance or require user intervention. Since the automatic applications require that the entire pattern is detected, which is difficult in most cases. This work aims to identify patterns of camera calibration automatically where the pattern can not be fully detected. Therefore, a corner detection and a topological filter are presented. The correspondence is done using neighboring properties on a geometric mesh and the sub-pixel location is threshold independent. The results show that the algorithm provides a robust detection even when the pattern is partially occluded.
Hodnocení vlivu cestovního ruchu na krajinu Nízkého Jeseníku

S rozvojem cestovniho ruchu se nejen u nas, ale take ve světě stale castěji objevuji informace o negativnim vlivu cestovniho ruchu na krajinu. Nasledujici přispěvek se zabýva analýzou faktorů vlivu cestovniho ruchu na krajinu Nizkeho Jeseniku metodami GIS. V zasadě byly navrženy tři stěžejni soubory dat (specificka environmentalni hodnota uzemi, potencial cestovniho ruchu a zatiženi krajiny infrastrukturou cestovniho ruchu), jejichž vzajemne vztahy umožnily řesenou problematiku kvantifikovat a klasifikovat. Každý ze tři stěžejnich souborů byl na zakladě vicevrcholoveho rozděleni jevů kvantifikovan a výsledne hodnoty byly nejdřive vztaženy k plose obci, nasledně pak na ramcove krajinne typy, což umožnilo aplikovat ziskane relativni hodnoty i na rozsahlejsi krajinnou jednotku. Přispěvek je soucasti doktorskeho výzkumu.
Insect urban ecology : aphid interactions with natural enemies and mutualists

Cities are novel and fast changing environments. We have little understanding of how urbanisation affects ecological patterns and processes. In Chapter One I review the literature (with an emphasis on arthropods) concerning the general effects of urbanisation on biodiversity, how urban greenspaces are structured, the main characteristics of urban ecological populations and communities, and how trophic dynamics and species interactions are affected by urban environments. The experimental chapters of this thesis focuses on addressing gaps in knowledge concerning how species interactions respond to increasing levels of urbanisation, by using aphids and their natural enemies and ant mutualists as a model system. In Chapter Two I explore the local and fine scale environmental drivers of naturally occurring assemblages of aphids, and their coccinelid and syrphid predators, in urban gardens. Ladybirds are the only group affected by increased urbanisation, while aphids and hoverflies vary as a function of host plant abundance and garden plant richness, which in themselves are indirect consequences of urbanisation. In Chapter Three, I investigate the main biotic and abiotic factors that affect the recruitment of naturally occurring predators, parasitoids and mutualists in experimental colonies placed on an urbanisation gradient. In Chapter Four, I build on this to consider how two aphid species, each differentially attended by mutualists, are influenced by urbanisation. In both chapters I found a higher sensitivity of predators to increased urbanisation, while ants appear to particularly benefit from the creation of these novel habitats. In Chapter Five I explore if there is a differential response of predator functional groups to urban green spaces, and I confirm my hypothesis that specialist predators respond more strongly to increased abundance and size of green space in urban areas. In Chapter Six I investigate which features of urban habitats have a greater influence in the outcome of interspecific competition, and my results suggest that an increased abundance of ants in urban habitats may act in concert with abiotic features of urbanisation to affect the dynamics of competition synergistically. In the seventh and final chapter, I discuss the main findings, contributions and future directions in the field of urban ecology.
Image interpolation using classification-based neural networks

Standard image interpolation methods generally use a uniform interpolation filter on the entire image. To achieve a better performance on specific structures, some content adaptive interpolation methods, such as Kondo's method (1), have been introduced. However, these content adaptive methods are limited to fit image data into a linear model in each class. We investigate replacing the linear model by a flexible non-linear model, such as a feed-forward neural network. This results in a new interpolation algorithm based on known classification, but achieving better results. In this paper, such a classification-based neural network approach and its evaluation are presented. Both objective and subjective image quality results indicate that the proposed method gives an additional improvement in the interpolated image quality 1 .
Latent Periodicity of Many Genes

Development of mathematical methods for study of symbolical sequence periodicity gets special significance nowadays. First of all it is concerned with the successful determination of DNA sequences from various genomes and accumulation of a great number of amino acid sequences. Therefore there is a problem for mathematics and biologists to be solved to determine the structural features of these sequences and to find the biological meaning of the revealed structural features of the sequences. One of such structural features is a periodicity of symbolic sequences. Earlier comprehensive mathematical methods were developed for study of periodicity of continuous and discrete numerical sequences, using Fourier transformation and allowing to define the spectral density of a numerical sequence. However, such application of Fourier transformation demands presentation of a symbolical sequence as a numerical sequence in which the properties of any symbolical text should be displayed unequivocally. The most widely used is the method, including construction from the given symbolical sequence ofm sequences consisting of numbers zero and one, and formed according to the law: x(i, j) = 1, if the symbol ai occupies a site j, and x(i, j) = 0 in all other cases. Here A = {a1, a2, . , am} is the alphabet of a symbolical sequence and m is the size of the alphabet of a symbolical sequence. Then the Fourier transformation is applied to each of such numerical sequence and the Fourier-harmonics are calculated, corresponding to i-type symbols, as well as matrix structural factors, corresponding to pair correlation of symbols [6]. However, in our opinion the given method works rather well for study of periodicity of symbolical sequences with relatively short length (which is smaller than the size of the symbolical sequence alphabet). For the periods with the length greater than the size of the symbolical sequence alphabet, there is a possibility of “decomposition” of the statistical importance of the longer periods in favor of the shorter ones. Thus it turns out that statistical importance of the longer period is a kind of “spread” onto the statistical importance of the shorter periods, i.e. there is an effect of attenuation of harmonics with longer periods in favor of harmonics with shorter periods. This effect will be even stronger for cases, where there are several replacements in periodic sequences, in such sequences periods could not be simply identical. The main purpose of this work is to show our results for study of the DNA sequences by ID method and to show the existence of the latent periodicity in lot of gene DNA sequences.
A survey of literature on the teaching of introductory programming

Three decades of active research on the teaching of introductory programming has had limited effect on classroom practice. Although relevant research exists across several disciplines including education and cognitive science, disciplinary differences have made this material inaccessible to many computing educators. Furthermore, computer science instructors have not had access to a comprehensive survey of research in this area. This paper collects and classifies this literature, identifies important work and mediates it to computing educators and professional bodies. We identify research that gives well-supported advice to computing academics teaching introductory programming. Limitations and areas of incomplete coverage of existing research efforts are also identified. The analysis applies publication and research quality metrics developed by a previous ITiCSE working group [74].
Effect of obesity on survival in epithelial ovarian cancer

T he retrospective analysis of an ovarian cancer collective by Pavelka et al. showed a higher percentage of stage I disease (according to the International Federation of Gynecology and Obstetrics staging system) in obese patients and a trend toward an unfavorable survival in patients with advanced-stage disease. This led the authors to suggest that obesity has a negative effect on tumor biology and is an adverse prognostic factor in ovarian cancer. Our own data speak against this hypothesis. First, Pavelka et al. used the documented higher incidence of ovarian cancer in obese patients as a natural argument for a more aggressive tumor behavior in case of disease. They should be aware that factors of influence may play different roles in both situations. Examples are the BRCA1/BRCA2 mutations, which promote ovarian cancer incidence but are associated with a more favorable outcome, and parity, which reduces ovarian cancer incidence but has an adverse effect on survival. Second, the authors used only 216 datasets for their statements after various exclusion processes. They did not state the initial number of patients or the number of patients excluded for various reasons, making it impossible to estimate the magnitude of the potential bias. Therefore, we repeated the analyses in our collective of >1000 patients with ovarian carcinoma, including 695 datasets with complete information on body mass index, tumor stage and grade, tumor-associated death, and long-term survival. Among these were 121 patients who had an additional immunohistochemical profile of the primary tumor. Analyses of this collective regarding other aspects have been published. In summary, we observed no influence of obesity on tumor stage, tumor grade, tumor proliferation (Ki-67 antigen), or on the expression of the steroid hormone receptors, estrogen and progesterone. Thus, factors that clearly are linked with aggressive tumor biology or targets of obesity-associated, endogenous steroid hormone action failed to show any positive correlation. On the contrary, tumors in obese patients showed a slight and not significant trend toward better tumor differentiation and lower proliferation. Kaplan-Meier survival analyses revealed no influence of obesity, even when patients with or without postoperative residual tumor were considered. We are aware of the risks of obesity, its relation to cancer incidence, and the fact that obesity generally should be avoided. However, there is no serious evidence that obesity has a significant influence on the biology and prognosis of ovarian cancer.
Ubitem: a framework for interactive marketing in location-based gaming environment

Mobile game and advertising are evolving rapidly and becoming the key of mobile contents market. More powerful mobile devices have enabled the creation of better and richer mobile games and advertising. This paper proposes a framework, called Ubitem, which addresses many of the issues that are characteristic of mobile gaming and advertising. Ubitem facilitates time and location-sensitive, interactive marketing by enabling users with the location-aware technology capability to collect nearby items such as m-coupons and redeem the items in the close participating stores. We believe that mobile advertising within location-based gaming will most likely enable much richer entertaining experiences as well as the advertisers get superior responses from the users by linking a virtual game play and real-life action.
Determination of the Representative Socioeconomic Level by BSA in the Mexican Republic

The aim of this article is to determine the socioeconomic level (SEL) with disaggregation of the Basic Statistical Area (BSA) in the Mexican Republic. The methodology used is the one established by the Mexican Association of Market Research Agencies (AMAI) along with the National Institute of Statistics and Geography (INEGI). The Clustering of the BSAs was carried out according to variables contained in the Population and Housing Census of 2010, through Gaussian mixture models, learning neural networks and finally, by defining the labels corresponding to each SEL. We found the existence of a representative SEL for each BSA. In addition, the definition of each socioeconomic level shows good results with an average of 90.86% of correctly labeled elements.
Immobilization of DNA Aptamers on Polyester Cloth for Antigen Detection by Dot Blot Immunoenzymatic Assay (Aptablot)

A simple dot blot immunoenzymatic assay system was developed using polyester cloth coated with an oligo-DNA aptamer to provide a high-affinity macroporous surface for the efficient capture of a model protein analyte (thrombin) in complex sample matrices such as foods. Bound thrombin was detected immunoenzymatically using a peroxidase-linked antithrombin antibody and a chromogenic substrate. A unique feature of this approach, which we have termed “aptablot,” is the facile immobilization of DNA aptamers on the polyester surface by cross-linking with a brief exposure to ultraviolet light, and the simple assay format obviating the need for specialized instruments. The assay principle described herein should be broadly applicable to many situations where analytes must be detected in complex samples, with the main limiting factor being the availability of suitable DNA aptamers.
Resource sharing of pipelined custom hardware extension for energy-efficient application-specific instruction set processor design

Application-Specific Instruction set Processor (ASIP) has become an increasingly popular platform for embedded systems because of its high performance and flexibility. Energy efficiency is critical for portable and embedded devices, and should be addressed separately from performance consideration. The hardware extension in ASIPs can speed-up program execution, but also incurs area overhead and static energy consumption of the processors. Traditional data path merging techniques reduce circuit overhead by reusing hardware resources for executing multiple custom instructions. However, they introduce structural hazard for custom instructions on extended processors, and hence reduce the performance improvement. In this paper, we introduce a pipelined configurable hardware structure for the hardware extension in ASIPs, so that structural hazards can be remedied. With multiple subgraphs of operations selected for custom hardware realization, we devise a novel operation-to-hardware mapping algorithm based on Integer Linear Programming (ILP) to automatically construct a resource-efficient pipelined configurable hardware extension. We demonstrate that different resource sharing schemes would affect both the hardware overhead and datapath delay of the custom instructions. We analyze the design tradeoffs between resource efficiency and performance improvement, and present the design space exploration results.
On the Control of the Permanent Magnet Synchronous Motor: An Active Disturbance Rejection Control Approach

This brief presents an active disturbance rejection control scheme for the angular velocity trajectory tracking task on a substantially perturbed, uncertain, and permanent magnet synchronous motor. The presence of unknown, time varying, and load-torque inputs, unknown system parameters, and the lack of knowledge of the initial shaft's angular position, prompts a high-gain generalized proportional integral (GPI) observer-based active disturbance rejection (ADR) controller. This controller is synthesized on the basis of the differential flatness of the system and the direct measurability of the system's flat outputs, constituted by the motor's angular displacement and the d-axis current. As a departure from many previous treatments, the d-q-axis currents model is here computed on the basis of the measured displacement and not on the basis of the unknown position. The proposed high-gain GPI observer-based ADR controller is justified in terms of a singular perturbation approach. The validity and robustness of the scheme are verified by means of realistic computer simulations, using the MATLAB/SIMULINK-PSIM package.
Use of baseflow indices to delineate baseflow dominated and rapid response flow dominated watersheds.

1.1 Use of baseflow indices to delineate baseflow dominated and rapid response flow dominated watersheds Ramesh Rudra, Imran Ahmed, Alamgir A. Khan, Kamal G. Singh, Pradeep K Goel, Mohammad Khayer and Trevor Dickinson School of Engineering, University of Guelph, Guelph ON N1G 2W1 Canada Ontario Ministry of Environment and Climate Change, 125 Resources Road, Toronto ON M7A 1N3 Canada Email: rrudra@uoguelph.ca http://dx.doi. org/10.7451/CBE.2015. 57.1.1 Received: 2015 June 25, Accepted: 2015 July 23, Published: 2015 July 30. 12
A CD8+ T cell immune evasion protein specific to Epstein-Barr virus and its close relatives in Old World primates

γ1-Herpesviruses such as Epstein-Barr virus (EBV) have a unique ability to amplify virus loads in vivo through latent growth-transforming infection. Whether they, like α- and β-herpesviruses, have been driven to actively evade immune detection of replicative (lytic) infection remains a moot point. We were prompted to readdress this question by recent work (Pudney, V.A., A.M. Leese, A.B. Rickinson, and A.D. Hislop. 2005. J. Exp. Med. 201:349–360; Ressing, M.E., S.E. Keating, D. van Leeuwen, D. Koppers-Lalic, I.Y. Pappworth, E.J.H.J. Wiertz, and M. Rowe. 2005. J. Immunol. 174:6829–6838) showing that, as EBV-infected cells move through the lytic cycle, their susceptibility to EBV-specific CD8+ T cell recognition falls dramatically, concomitant with a reductions in transporter associated with antigen processing (TAP) function and surface human histocompatibility leukocyte antigen (HLA) class I expression. Screening of genes that are unique to EBV and closely related γ1-herpesviruses of Old World primates identified an early EBV lytic cycle gene, BNLF2a, which efficiently blocks antigen-specific CD8+ T cell recognition through HLA-A–, HLA-B–, and HLA-C–restricting alleles when expressed in target cells in vitro. The small (60–amino acid) BNLF2a protein mediated its effects through interacting with the TAP complex and inhibiting both its peptide- and ATP-binding functions. Furthermore, this targeting of the major histocompatibility complex class I pathway appears to be conserved among the BNLF2a homologues of Old World primate γ1-herpesviruses. Thus, even the acquisition of latent cycle genes endowing unique growth-transforming ability has not liberated these agents from evolutionary pressure to evade CD8+ T cell control over virus replicative foci.