Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Analysis of Multilayer Microstrip Problems by Modified Fast Directional Multilevel Algorithm

─ Fast directional multilevel algorithm (FDMA) combined with quad-tree structure is presented for analyzing multilayer microstrip problems. This method is successfully applied to analyze scattering in free space and it is extended to solve multilayer mircrostrip problems in this paper. The quad-tree structure is employed for the layer containing the microstrip patch, and then the defined of far field for every observed group is modified. There is only Kernel evaluation in low rank representation so that the surface-wave is extracted for the far-field Green’s functions expansion when the dielectric substrate is thick or relative permittivity is large. The memory requirement and the CPU time per iteration of the multilayer microstrip structure is presented, which show the accuracy and efficiency of this method. Index Terms Modified fast directional multilevel algorithm, multilayer microstrip structures, Sparameters, and transmission coefficient.
Graph Clustering Via a Discrete Uncoupling Process

A discrete uncoupling process for finite spaces is introduced, called the Markov Cluster Process or the MCL process. The process is the engine for the graph clustering algorithm called the MCL algorithm. The MCL process takes a stochastic matrix as input, and then alternates expansion and inflation, each step defining a stochastic matrix in terms of the previous one. Expansion corresponds with taking the $k$th power of a stochastic matrix, where $k\in\N$. Inflation corresponds with a parametrized operator $\Gamma_r$, $r\geq 0$, that maps the set of (column) stochastic matrices onto itself. The image $\Gamma_r M$ is obtained by raising each entry in $M$ to the $r$th power and rescaling each column to have sum 1 again. In practice the process converges very fast towards a limit that is invariant under both matrix multiplication and inflation, with quadratic convergence around the limit points. The heuristic behind the process is its expected behavior for (Markov) graphs possessing cluster structure. The process is typically applied to the matrix of random walks on a given graph $G$, and the connected components of (the graph associated with) the process limit generically allow a clustering interpretation of $G$. The limit is in general extremely sparse and iterands are sparse in a weighted sense, implying that the MCL algorithm is very fast and highly scalable. Several mathematical properties of the MCL process are established. Most notably, the process (and algorithm) iterands posses structural properties generalizing the mapping from process limits onto clusterings. The inflation operator $\Gamma_r$ maps the class of matrices that are diagonally similar to a symmetric matrix onto itself. The phrase diagonally positive semi-definite (dpsd) is used for matrices that are diagonally similar to a positive semi-definite matrix. For $r\in\N$ and for $M$ a stochastic dpsd matrix, the image $\Gamma_r M$ is again dpsd. Determinantal inequalities satisfied by a dpsd matrix $M$ imply a natural ordering among the diagonal elements of $M$, generalizing the mapping of process limits onto clusterings. The spectrum of $\Gamma_{\infty} M$ is of the form $\{0^{n-k}, 1^k\}$, where $k$ is the number of endclasses of the ordering associated with $M$, and $n$ is the dimension of $M$. This attests to the uncoupling effect of the inflation operator.
In Silico characterization of STK11- a protein involved in PJ Syndrome

Studies of hereditary cancer syndromes have contributed greatly to our understanding of molecular events involved in tumor genesis. One such syndrome of our interest is Peutz-Jeghers Syndrome, a hereditary disease, in which there is predisposition to benign and malignant tumors of many organ systems. Here, we investigate the genes responsible for the Peutz-Jeghers syndrome (PJS) and the pathway of disease causing mechanism. The STK11, Serine/Threonine Kinase 11, commonly known as LKB1 is the gene responsible for this syndrome. This gene is coding a protein of length 433 amino acids, 48.6 kDa. The protein sequence is retrieved from the protein database of NCBI. The analysis of this protein is performed using various in silico methods.
Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems

When solving constraint satisfaction problems (CSPs), it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases.
OF A MESH GENERATED WITH THE M ESH-M ATCHING ALGORITHM : APPLICATION TO EXOPHTALMIA AND MAXILLOFACIAL COMPUTER AIDED SURGERY

Objective: An automatic mesh regularization procedure was proposed in order to achieve the numerical feasibility of the Finite Element Analysis. Design: The algorithm has been implemented for tetrahedrons, wedges and hexahedrons. Background: One of the main drawbacks of three-dimensional model generation is consumption due to the manual three-dimensional meshing procedure. In a previous study, the authors demonstrated the ability of the Mesh Matching algorithm to automatically generate customized three-dimensional meshes from an already existing model. For anatomical structures, some element irregularities can occur after the use of the Mesh-Matching algorithm, making any finite element analysis impossible. Methods: A process based on the study of the singularity of the Jacobian matrix is used to iteratively correct them. Results: The method was successfully evaluated on an academic test case (cubic structure meshed with hexahedrons) and on clinical applications (face and orbit meshes). Conclusions : The use of the combination of the Mesh-Matching algorithm with the regularization phase presented here seems to automatically generate new finite element meshes. Nevertheless, no guaranty, in terms of convergence, can be given, since the regularization algorithm is iterative.
Under-reporting of energy intake in the 1997 National Nutrition Survey.

AIMS To estimate the level of under-reporting of energy intake by gender, age, ethnicity and body size (normal, overweight, obese) in the 1997 National Nutrition Survey (NNS97) in New Zealand. METHODS Data were from 4,258 participants (1,808 men and 2,450 women aged 15 years and over) who completed the 24-hour diet recall; the primary methodology used in the NNS97. Under-reporting was assessed using the ratio of reported energy intake to estimated resting metabolic rate (EI: RMRest). Cut-off limits were used to identify percentages of under-reporters in the various subgroups. RESULTS Mean EI: RMRest was 1.40 for all participants (1.51 for men, 1.30 for women, p<0.001) with older age being associated with lower EI: RMRest (p<0.001). There were no significant differences in mean EI: RMRest between ethnic groups for men. Mean EI: RMRest for women were: Maori 1.46, European 1.29, and Pacific 1.37 (p<0.01). A larger body size was associated with a significantly lower EI: RMRest especially for women. Percentages of 'definite' under-reporters (individual EI: RMRest <0.9) were as follows: men 12%, women 21%; Europeans 16%, Maori 23% and Pacific 26%; normal weight (11%), overweight (19%) and obese (27%) participants; and from 10% in the youngest to 23% in the oldest age group (p<0.001 for all results). CONCLUSION In this study, in agreement with the literature, women, older people and obese people under-reported more than men, younger people and non-obese people. Possible ethnic differences in under-reporting rates need further study. Care is needed in interpreting the energy intake data from the NNS97.
The OU-ISIR Gait Database Comprising the Large Population Dataset and Performance Evaluation of Gait Recognition

This paper describes the world's largest gait database-the “OU-ISIR Gait Database, Large Population Dataset”-and its application to a statistically reliable performance evaluation of vision-based gait recognition. Whereas existing gait databases include at most 185 subjects, we construct a larger gait database that includes 4007 subjects (2135 males and 1872 females) with ages ranging from 1 to 94 years. The dataset allows us to determine statistically significant performance differences between currently proposed gait features. In addition, the dependences of gait-recognition performance on gender and age group are investigated and the results provide several novel insights, such as the gradual change in recognition performance with human growth.
Dexamethasone-mediated oncogenicity in vitro and in an animal model of glioblastoma.

OBJECTIVEDexamethasone, a known regulator of mesenchymal programming in glioblastoma (GBM), is routinely used to manage edema in GBM patients. Dexamethasone also activates the expression of genes, such as CEBPB, in GBM stem cells (GSCs). However, the drug's impact on invasion, proliferation, and angiogenesis in GBM remains unclear. To determine whether dexamethasone induces invasion, proliferation, and angiogenesis in GBM, the authors investigated the drug's impact in vitro, in vivo, and in clinical information derived from The Cancer Genome Atlas (TCGA) cohort.METHODSExpression profiles of patients from the TCGA cohort with mesenchymal GBM (n = 155) were compared with patients with proneural GBM by comparative marker selection. To obtain robust data, GSCs with IDH1 wild-type (GSC3) and with IDH1 mutant (GSC6) status were exposed to dexamethasone in vitro and in vivo and analyzed for invasion (Boyden chamber, human-specific nucleolin), proliferation (Ki-67), and angiogenesis (CD31). Ex vivo tumor cells from dexamethasone-treated and control mice were isolated by fluorescence activated cell sorting and profiled using Affymetrix chips for mRNA (HTA 2.0) and microRNAs (miRNA 4.0). A pathway analysis was performed to identify a dexamethasone-regulated gene signature, and its relationship with overall survival (OS) was assessed using Kaplan-Meier analysis in the entire GBM TCGA cohort (n = 520). RESULTSThe mesenchymal subgroup, when compared with the proneural subgroup, had significant upregulation of a dexamethasone-regulated gene network, as well as canonical pathways of proliferation, invasion, and angiogenesis. Dexamethasone-treated GSC3 demonstrated a significant increase in invasion, both in vitro and in vivo, whereas GSC6 demonstrated a modest increase. Furthermore, dexamethasone treatment of both GSC3 and GSC6 lines resulted in significantly elevated cell proliferation and angiogenesis in vivo. Patients with mesenchymal GBM had significant upregulation of dexamethasone-regulated pathways when compared with patients with proneural GBM. A prognostic (p = 0.0007) 33-gene signature was derived from the ex vivo expression profile analyses and used to dichotomize the entire TCGA cohort by high (median OS 12.65 months) or low (median OS 14.91 months) dexamethasone signature.CONCLUSIONSThe authors present evidence that furthers the understanding of the complex effects of dexamethasone on biological characteristics of GBM. The results suggest that the drug increases invasion, proliferation, and angiogenesis in human GSC-derived orthotopic tumors, potentially worsening GBM patients' prognoses. The authors believe that careful investigation is needed to determine how to minimize these deleterious dexamethasone-associated side effects in GBM.
Goodness of fit test for higher order binary Markov chain models

Abstract When the interest is in making statements about change based on repeated measurements of discrete data, one way to do so is using Markov chain models. Goodness of fit test to find a good model is very important in analyzing the underlying patterns and relationships in the repeated measures data. To test for the various associations in the models, the likelihood ratio and Wald tests are used. However, it has been observed that the efficient score tests can provide equally good tests and can provide an easier alternative. In this paper, we provide an extension of Tsiatis method for goodness of fit test on higher order Markov chains. In our method, we follow the approach of Tsiatis goodness of fit test in logistic regression models. New method provided in this paper is applied to real-life data to examine the suitability of the techniques.
AN AUTOMATIC TEST REGENERATION TECHNIQUE FOR IMPROVING STATE MODEL COVERAGE

Automated test regeneration intends to ensure high coverage of the system model from an existing test suite. Most of the existing coverage analysis techniques conclude their task by measuring coverage achieved so far by existing test suite. Hence, regenerating test cases for the untested elements is a research issue. To consider the coverage result, and incorporate UML diagram and source syntax information for regenerating useful test cases is a challenging task. An automatic test regeneration technique to achieve high coverage of state model is proposed in this thesis. The architecture of the proposed technique is supported by three modules for the test regeneration. The first module processes the inputted UML diagrams, source code and test suite, as XML elements, source class and test steps respectively. The second module measures the model coverage result achieved through the test steps which directs the final module to regenerate test cases for the uncovered methods. The final module combines coverage result, the extracted UML and source syntax together to regenerate unit and integration test cases. The combination of coverage result, UML element and source syntax leads to executable and effective test cases. Experiments have been conducted on three test projects to assess the effectiveness of the proposed technique. Two of these projects were used by existing techniques and another one was developed as an academic project. On average 97% of the regenerated test cases are executable transition sequences. The incorporation of state model method signature and software source syntax leads to executable test cases. The experimental result also shows that on average 54.23% and 43.23% improvements of the existing test suite are achieved in transition and state coverage respectively. The consideration of the coverage result allows the proposed technique to focus in covering the untested interaction sequences in the classes and thus, improves coverage of the existing test suite.
Optimization of Process Parameters in Oriented Strand Board Manufacturing by Taguchi Method

Optimization of process parameters in oriented strand board (OSB) manufacturing is a vital issue for improving product quality. In this study, the Taguchi method (TM) was applied to determine the effects of production factors such as adhesive ratio, press pressure, and pressing time on the thermal conductivity of OSB. Obtained results showed that adhesive ratio is the main factor affecting thermal conductivity. Press pressure and pressing time are the second and third most important factors influencing thermal conductivity, respectively. The study also identified the optimal values of factors that minimize thermal conductivity.
A generalized model for visualizing library popularity, adoption, and diffusion within a software ecosystem

The popularity of super repositories such as Maven Central and the CRAN is a testament to software reuse activities in both open-source and commercial projects alike. However, several studies have highlighted the risks and dangers brought about by application developers keeping dependencies on outdated library versions. Intelligent mining of super repositories could reveal hidden trends within the corresponding software ecosystem and thereby provide valuable insights for such dependency-related decisions. In this paper, we propose the Software Universe Graph (SUG) Model as a structured abstraction of the evolution of software systems and their library dependencies over time. To demonstrate the SUG's usefulness, we conduct an empirical study using 6,374 Maven artifacts and over 6,509 CRAN packages mined from their real-world ecosystems. Visualizations of the SUG model such as ‘library coexistence pairings’ and ‘dependents diffusion’ uncover popularity, adoption and diffusion patterns within each software ecosystem. Results show the Maven ecosystem as having a more conservative approach to dependency updating than the CRAN ecosystem.
Metabolic Syndrome, Insulin Resistance and Fatty Liver in Obese Iranian Children

Background: Obesity is a global epidemic and its morbidities such as metabolic syndrome, insulin resistance, and fatty liver leads to a spectrum of psycho-social and medical consequences. Objectives: The objective of this study was to investigate the prevalence of fatty liver in obese Iranian children and its' association with metabolic syndrome and insulin resistance. Patients and Methods: 102 obese Iranian children, referred to pediatric clinics from March 2011 to March 2012, were enrolled in this cross-sectional study. All the patients were visited by a pediatric endocrinologist, a pediatric gastroenterologist and an expert radiologist in the evaluation of fatty liver grading. Results: The grade of fatty liver was higher in older children (P = 0.001). It was also more in taller and heavier children (P = 0.000). The more the BMI was, the more the fatty liver grade was (P = 0.002). Severity of fatty liver according to liver sonography in patient had a positive relationship with waist circumference, hip circumference, serum TG, serum FBS, serum fasting insulin, serum ALT, systolic blood pressure and HOMA index and had a negative correlation with the level of alkaline phosphatase. Severity of fatty liver also had a close relationship with the presence of acanthosis nigricans and HOMA index. Conclusions: Prevalence of fatty liver is high in our obese children. It was associated with criteria of metabolic syndrome and insulin resistance, so visceral fat may participate in the pathogenesis of the metabolic syndrome or merely serve as a marker of increased risk for the metabolic complications of obesity.
Defining appropriate outcome measures in pulmonary arterial hypertension related to systemic sclerosis: a Delphi consensus study with cluster analysis.

OBJECTIVE Outcome measures for pulmonary arterial hypertension associated with systemic sclerosis (PAH-SSc) are only partially validated. The aim of the present study was to establish an expert consensus regarding which outcome measures are most appropriate for clinical trials in PAH-SSc. METHODS Sixty-nine PAH-SSc experts (rheumatologists, cardiologists, pulmonologists) rated a list of disease domains and measurement tools in an Internet-based 3-stage Delphi consensus study. In stages 2 and 3, the medians of domains and measurement tools and frequency distributions of ratings, along with requests for re-ratings, were distributed to respondents to provide feedback. A final score of items was identified by means of cluster analysis. RESULTS The experts judged the following domains and tools as most appropriate for randomized controlled trials in PAH-SSc: lung vascular/pulmonary arterial pressure and cardiac function both measured by right heart catheterization and echocardiography, exercise testing measured by 6-minute walking test and oxygen saturation at exercise, severity of dyspnea measured on a visual analog scale, discontinuation of treatment measured by (serious) adverse events, quality of life/activities of daily living measured by the Short Form 36 and Health Assessment Questionnaire disability index, and global state assessed by physician measured by survival. CONCLUSION Among experts in PAH-SSc, a core set of outcome measures has been defined for clinical trials by Delphi consensus methods. Although these outcome measures are recommended by this expert group to be used as an interim tool, it will be necessary to formally validate the present measures, as well as potential research measures, in further studies.
Curcumin-loaded Chitosan Tripolyphosphate Nanoparticles as a safe, natural and effective antibiotic inhibits the infection of Staphylococcus aureus and Pseudomonas aeruginosa in vivo

Background: Curcumin as a yellow natural compound extracted from turmeric root is known it as an antibacterial agent. One of the nanoparticles ability is to decrease the defects of usual drug delivery systems. Chitosan is a low toxic, biodegradable, biocompatible and safe polymer which is used in production of nanoparticles. Nanoparticles like chitosan-tripolyphosphate (TPP) are able to increase antibacterial properties of curcumin. Materials and Methods: Curcumin-loaded chitosan-TPP nanoparticles containing chitosan, curcumin and TPP salt were synthesized by ionotropic gelation methods. First, the skin of anesthetized mice was inoculated with staphylococcus aureus and pseudomonas aeruginosa suspension. Then the infected mice were treated with curcumin-loaded chitosan-TPP nanoparticles for 3 days. Following that, antibacterial characteristics of the mice treated with curcumin-loaded chitosanTPP nanoparticles were evaluated by bacterial culture of these mice. Results: Our results showed the size of 160 ± 10 nm and the charge of +7 ± 2 mV in curcumin-loaded chitosan-TPP nanoparticles. These nanoparticles were also spiral shape. The encapsulation efficiency of curcumin in chitosan-TPP nanoparticles was 75 ± 2%. Bacterial culture showed that curcumin-loaded chitosan-TPP nanoparticles inhibited staphylococcus aureus and pseudomonas aeruginosa growth. Conclusions: Our study demonstrated that curcumin-loaded chitosan-TPP nanoparticles can be utilized as a potent agent in treatment of Staphylococcus aureus and Pseudomonas aeruginosa infections.