Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Gaussian spatial modelling of Chagas disease in Argentina

We model the spatial distribution of prevalence of the most important Chagas disease vectors to enable predictive mapping of univariate and multivariate prevalence of the species vectors and the disease risk. We analyse both the binary variable of presence-absence of Chagas disease and the species richness in Argentina, in combination with meteorological and topographical covariates associated to the grid. We use several statistical techniques to produce distribution maps of presence-absence, and species richness including a hierarchical Bayesian framework within the context of multivariate geostatistical modelling. Our results show that, as expected, the inclusion of covariates improves the quality of the fitted models, and that there is spatial interaction between neighboring cells/pixels.
Clustering Algorithm in Possibilistic Exponential Fuzzy C-Mean Segmenting Medical Images

Different fuzzy segmentation methods were used in medical imaging from last two decades for obtaining better accuracy in various approaches like detecting tumours etc. Well-known fuzzy segmentations like fuzzy c-means (FCM) assign data to every cluster but that is not realistic in few circumstances. Our paper proposes a novel possibilistic exponential fuzzy c-means (PEFCM) clustering algorithm for segmenting medical images. This new clustering algorithm technology can maintain the advantages of a possibilistic fuzzy c-means (PFCM) and exponential fuzzy c-mean (EFCM) clustering algorithms to maximize benefits and reduce noise/outlier influences. In our proposed hybrid possibilistic exponential fuzzy c-mean segmentation approach, exponential FCM intention functions are recalculated and that select data into the clusters. Traditional FCM clustering process cannot handle noise and outliers so we require being added in clusters due to the reasons of common probabilistic constraints which give the total of membership’s degree in every cluster to be 1. We revise possibilistic exponential fuzzy clustering (PEFCM) which hybridize possibilistic method over exponential fuzzy c-mean segmentation and this proposed idea partition the data filters noisy data or detects them as outliers. Our result analysis by PEFCM segmentation attains an average accuracy of 97.4% compared with existing algorithms. It was concluded that the possibilistic exponential fuzzy c-means segmentation algorithm endorsed for additional efficient for accurate detection of breast tumours to assist for the early detection.
MEENAKSHI PRIYADARSHNI TISSUE CULTURE STUDIES OF HELIOTROPIUM INDICUM AN IMPORTANT MEDICINAL HERB FOR CALLUS INDUCTION AND MICRO PROPAGATION

Tissue culture studies of Heliotropium indicum (Boraginaceae) an important medicinal herb has been carried for induction of callus and multiple shoots from leaf, internodes and nodal explants. Internodal segments and leaves were inoculated in Murashige and Skoog (MS) (1962) medium, supplemented with 1.0 mg/l 3.0 mg/l concentrations of 2,4DichlorophenoxyAceticAcid(2,4-D), 3-Indole Butyric Acid (IBA) and αNaphthalene Acetic Acid (NAA) separately, along with two different concentrations of BAP and Kinetin. Higher percentage of response for callusing in internodal explant was obtained in MS+2.0 mg/l BAP + 3.0mg/l NAA which was 78%. This was followed by similar concentration of KN+IBA which was 66%. However, the higher percentage of response for callusing was obtained in MS+2.0 mg/l BAP + 2.0 mg/l IBA which was 67% followed by similar concentration of BAP+NAA. Kinetin at this concentration revealed lower percentage of response. It was observed that similar concentration of 2, 4-D, either with BAP or KIN revealed poor response for callusing in both the leaf and internodal explants. For multiple shoot induction the apical shoot and nodal explants were inoculated in MS+BAP or KN alone or with various concentrations of NAA, IAA or GA3. MS medium fortified with BAP alone could promote shoot bud induction in both the explants and it was 87% at 1.0 mg/l BAP, where the number of shoots was 5.4. The percent response was 92 at 1.0 mg/l concentration of Kinetin . When GA3 0.5mg/l was added, the percent response was 92 and number of shoots 12.8. For apical shoot the percent response was 94, number of shoots 14.8 at the same concentrations. Well grown plantlets were used for rooting, in 1⁄2 MS medium + various concentrations of IAA, NAA and IBA. Here, 0.2 mg/l IBA was found more suitable where mean number of roots as 14.6 per plantlet. Survival rate in the field condition was 76%.
Generalized self-similarity of intermittent plasma turbulence in space and laboratory plasmas

Statistical characteristics of plasma fluctuations in the solar wind (SW), the Earth’s magnetosphere and fusion devices are reviewed. The turbulence in all these media has a complicated multiscale structure and exhibits a generalized self-similarity in an extended scale range. The anomalous transport of mass and momentum is intermittent and is carried by sporadic plasma flux bursts with non-Gaussian statistics, long-range correlation and multifractality. Intermittent turbulent transport is characterized by superdiffusion with power law 〈δx2〉 ∝ τ , α ≈ 1.2–1.8. The structure functions in all these plasma environments are well fitted by the log-Poisson model of turbulence. Intermittent plasma turbulence displays universal properties and consists of quasi-1-D singular dissipative structures.
Small energy spread electron beams from laser wakefield acceleration by self-evolved ionization injection

We experimentally demonstrate generation of quasi-mono-energetic electrons from pure nitrogen gas via ionization injection induced by self-evolved laser pulses. By means of self-focusing and self-compression, we are able to reduce the injection length to 200 μ m and obtain the acceleration distance over several Rayleigh lengths that leads to the generation of quasi-mono-energetic electron beams with peak energy of 185 MeV and energy spread of 6%. This uncomplicated and maneuverable method suggests that the interaction of femtosecond laser pulses with moderate energy ∼1 J with pure nitrogen gas is advantageous for achieving stable and small energy spread electron beam.
Research on design of adaptive connecting mechanisms for the cable-net and panels of FAST

The reflector system of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) is designed to incorporate 4450 rigid panels supported by a flexible cable-net structure. The shape-changing operation that occurs in the process of observation will lead to a relative displacement between adjacent nodes in the cable-net. In addition, three nodes on a rigid panel are fixed with respect to each other. Thus, adaptive connecting mechanisms between panels and the cable-net are certainly needed. The present work focuses on the following aspects. Firstly, the degrees of freedom of adaptive connecting mechanisms were designed so that we can not only adapt the panel to the deformation of the cable-net, but also restrict the panel to its right place. Secondly, finite element and theoretical analyses were applied to calculate the scope of motion in adaptive connecting mechanisms during the cable-net’s shape-changing operation, thus providing input parameters for the design size of the adaptive connecting mechanisms. In addition, the gap size between the panels is also investigated to solve the trade-off between avoiding panel collisions and increasing the observation efficiency of FAST.
Plasmonic scattering nanostructures for efficient light trapping in flat CZTS solar cells

CZTS (Cu2ZnSnS4) is a promising absorbing layer in photovoltaic devices, due to it is low cost, abundancy, and non-toxicity. However, recent developments in CZTS solar cells showed efficiency reaching barely over 9%. The low efficiency of CZTS solar cells is the main obstacle for replacing conventional high cost bulk silicon photovoltaic with CZTS solar cells. Herein, we propose an alternative route for enhancing the efficiency of CZTS solar cells by using plasmonic scattering nanostructures on the top surface of the CZTS active layer. Metamaterial and plasmonic nanostructures can confine, absorb, guide or scatter incident light in the nanoscale. Each one of these phenomena totally depends on the material type, shape, and geometrical dimensions of the used nanostructures. Therefore, theoretical study of different shapes and materials can guide the highest performance of desired phenomena. In this work, we studied the effect of changing plasmonic metal nanopyramids height, periodicity, and tapering angle on light scattering inside active layer of the CZTS solar cells. By sweeping pyramids height from 100nm to 300nm, periodicity of closed nanopyramids from 100nm to 180nm, and using pyramid base length 25nm, 50nm, 75nm, we found good enhancements in light absorption inside the active layer over reference planar CZTS structures. Each plasmonic CZTS solar cell structure is designed and analyzed using there dimensional (3D) finite element method (FEM) simulations. Using periodic boundary condition for simulating a smaller cell, and with mesh size is ten times smaller than lowest simulated wavelength. Input port energy came from air mass 1.5 sun light over wavelength range from 300nm to 800nm. Also, we studied effect of replacing molybdenum with refractory plasmonics titanium nitride (TiN). TiN is a promising plasmonic material as it has a similar plasmonic properties to gold at visible wavelength. After using TiN, we found also enhancements in light absorption. These interesting results could open a new way of integrating plasmonic scattering nanostructure inside flat CZTS solar cell for higher efficiency.
Incorporating Turbulent Inflow Conditions In a Blade Element Momentum Model of Tidal Stream Turbines

Blade element momentum theory (BEMT) is a well-established method for evaluating the performance of turbines designed to extract energy from a flowing fluid. In this paper, we discuss a modified version of BEMT that allows for greater variation in the permissible inflow conditions, paying particular attention to inflow conditions that model turbulence in coastal waters in order to calculate the power output and other performance parameters of tidal stream turbines (TSTs). In the first part of the paper, we describe the modification we have made to standard BEMT analysis. In the second part, we describe how we create an appropriate representation of a turbulent tidal stream or marine current, and what parameters we can extract from measurements of a real current in order to create this representation. Some preliminary results are presented and their significance discussed.
PDCD1 single nucleotide genes polymorphisms confer susceptibility to juvenile-onset systemic lupus erythematosus

Abstract Juvenile-onset systemic lupus erythematosus (JSLE) is a multisystem autoimmune disease in which both the genetic and environmental factors seem to be involved in the etiopathogenesis of the disease. The aim of this study was to evaluate the association of programmed cell death 1 (PDCD1, also called PD-1) gene polymorphisms with JSLE susceptibility in Iranian population. In this case-control association study, three PDCD1 SNPs, including PD-1.1 G/A, PD-1.3 G/A and PD-1.9 C/T were genotyped in 50 Iranian patients with JSLE and 202 healthy unrelated controls, using PCR-RFLP method. The PD-1.1 A allele was found to be more frequent in the case group compared with controls (6% vs. 1.5%, p = 0.024). Moreover, the GG genotype was less frequent in cases than in controls (88% vs. 97%, p = 0.021). The other PDCD1 SNPs did not show association. At the haplotypic level, no significant differences was recognized between the two groups of case and control neither for the GAC (PD-1.1 G, PD-1.3 A, PD-1.9 C) nor for the GGC haplotype (PD-1.1 G, PD-1.3 G, PD-1.9 C). Our findings support the influence of the PD1.1 A SNP on the development of JSLE in Iranian population.
An O(n log n)-Time Algorithm for the Restriction Scaffold Assignment Problem

The restriction scaffold assignment problem takes as input two finite point sets S and T (with S containing more points than T ) and establishes a correspondence between points in S and points in T , such that each point in S maps to exactly one point in T and each point in T maps to at least one point in S. An algorithm is presented that finds a minimum-cost solution for this problem in O(n log n) time, provided that the points in S and T are restricted to lie on a line and the cost function delta is the L(1) metric. This algorithm runs in linear time, if S and T are presorted. This improves the previously best-known O(n (2))-time algorithm for this problem.
Middle school students’ attitudes towards the use of technology in mathematics lessons: does gender make a difference?

ABSTRACT The first aim of the study was to develop a valid and reliable scale to measure attitudes of middle-school students towards the use of technology in mathematics lessons and then, to examine elementary students’ attitudes towards the use of technology in mathematics lesson. The study further aimed to investigate gender differences in attitudes towards the use of technology in mathematics lessons. Data were collected from 571 middle-school students aged 10–14. Participating students were from five private and one public school in Ankara, Turkey and the schools were using various technological tools in mathematics lessons. As data collection instrument, Technology Use in Mathematics Lessons Attitude (TMLA) Scale was administered. Exploratory and confirmatory factor analysis results demonstrated that TMLA Scale was a valid and reliable tool to measure students’ attitudes towards the use of technology in mathematics lessons. In addition, descriptive analysis results revealed that middle-grade students had moderately high attitudes towards the use of technology. Moreover, independent sample t-test results indicated that female students possessed significantly higher attitudes towards the technology use in mathematics lessons when compared with male counterparts.
Fixed-Income Securities: Valuation, Risk Management and Portfolio Strategies

This textbook will be designed for fixed-income securities courses taught on MSc Finance and MBA courses. There is currently no suitable text that offers a 'Hull-type' book for the fixed income student market. This book aims to fill this need. The book will contain numerous worked examples, excel spreadsheets, with a building block approach throughout. A key feature of the book will be coverage of both traditional and alternative investment strategies in the fixed-income market, for example, the book will cover the modern strategies used by fixed-income hedge funds. The text will be supported by a set of PowerPoint slides for use by the lecturer First textbook designed for students written on fixed-income securities - a growing market Contains numerous worked examples throughout Includes coverage of important topics often omitted in other books i.e. deriving the zero yield curve, deriving credit spreads, hedging and also covers interest rate and credit derivatives
Structural design and optimization of deep-ultraviolet light-emitting diodes with AlxGa1−xN/AlyGa1−yN/AlxGa1−xN(x > y) p-electron blocking layer

Abstract. This work reports AlGaN-based deep ultraviolet light-emitting diode (DUV LED) possessing a specifically AlxGa1 − xN / AlyGa1 − yN / AlxGa1 − xN (x > y) structured p-electron blocking layer (p-EBL) to achieve the high external quantum efficiency (EQE). The impact of the p-EBL with AlyGa1 − yN insertion layer at different positions and with different AlN compositions on the hole and electron injection is systematically investigated. Our results show that, for the DUV LED structure in this work, both electrons and holes can be most efficiently injected into the active region by keeping the AlyGa1 − yN insertion layer near to the p-region. The AlN composition for the AlyGa1 − yN insertion layer has also to be optimized for maximizing the carrier injection.
Fast LP Algorithms for Portfolio Optimization

This paper describes two algorithms for financial portfolio optimization. These algorithms find optimal portfolios for a number of risk measures: CVaR, MAD, LSAD and dispersion CVaR. The algorithms work for discrete distributions of asset returns where optimization problems can be reduced to linear programs. The first algorithm solves the simple recourse problem as described by Klein Haneveld and Van der Vlerk using Benders decomposition method. The second algorithm finds an optimal solution to LP problem with the smallest distance to a given benchmark portfolio and is an adaptation of the least norm solution (called also normal solution) of linear programs due to Zhao and Li. The algorithms are implemented in R in the package PortfolioOptim.
Generation and visualization of large‐scale three‐dimensional reconstructions from underwater robotic surveys

Robust, scalable simultaneous localization and mapping (SLAM) algorithms support the successful deployment of robots in real‐world applications. In many cases these platforms deliver vast amounts of sensor data from large‐scale, unstructured environments. These data may be difficult to interpret by end users without further processing and suitable visualization tools. We present a robust, automated system for large‐scale three‐dimensional (3D) reconstruction and visualization that takes stereo imagery from an autonomous underwater vehicle (AUV) and SLAM‐based vehicle poses to deliver detailed 3D models of the seafloor in the form of textured polygonal meshes. Our system must cope with thousands of images, lighting conditions that create visual seams when texturing, and possible inconsistencies between stereo meshes arising from errors in calibration, triangulation, and navigation. Our approach breaks down the problem into manageable stages by first estimating local structure and then combining these estimates to recover a composite georeferenced structure using SLAM‐based vehicle pose estimates. A texture‐mapped surface at multiple scales is then generated that is interactively presented to the user through a visualization engine. We adapt established solutions when possible, with an emphasis on quickly delivering approximate yet visually consistent reconstructions on standard computing hardware. This allows scientists on a research cruise to use our system to design follow‐up deployments of the AUV and complementary instruments. To date, this system has been tested on several research cruises in Australian waters and has been used to reliably generate and visualize reconstructions for more than 60 dives covering diverse habitats and representing hundreds of linear kilometers of survey. © 2009 Wiley Periodicals, Inc.
The Enhancing Connections Program: A 6-State Randomized Clinical Trial of a Cancer Parenting Program

Objective—The purpose of this study was to test the efficacy of a cancer parenting program for child-rearing mothers with breast cancer, the Enhancing Connections Program. Primary goals were to decrease maternal depressed mood and anxiety, improve parenting quality, parenting skills and confidence, and enhance the child’s behavioral-emotional adjustment to maternal breast cancer. Method—A total of 176 mothers diagnosed within 6 months with Stage 0–III breast cancer and their 8–12 year old child were recruited from medical providers in 6 states: Washington, California, Pennsylvania, Minnesota, Arizona and Indiana. After consenting and obtaining baseline measures, study participants were randomized into experimental or control groups. Experimental mothers received five, 1-hour educational counseling sessions at 2week intervals; controls received a booklet and phone call on communicating and supporting their child about the mother’s cancer. Outcomes were assessed at 2 and 12 months. HHS Public Access Author manuscript J Consult Clin Psychol. Author manuscript; available in PMC 2016 December 03. Published in final edited form as: J Consult Clin Psychol. 2015 February ; 83(1): 12–23. doi:10.1037/a0038219. A uhor M anscript
Ψ -Eventual Stability of Differential Systems with Impulses

In our paper, we have established criterion of Ψ-Eventual Stability for impulsive differential systems with variable moments of impulses by using piecewise continuous auxiliary functions which are analogous to Lyapunov’s functions. The work of Bainov, Kulev and Soliman has been extended. An example has been given to support the theoretical result. In the example, the zero solution is not stable in the sense of Lyapunov but it is uniformly eventually stable. Moreover a weight function Ψ is also associated with state vectors.
Time series models based on the unrestricted skew-normal process

ABSTRACT The standard location and scale unrestricted (or unified) skew-normal (SUN) family studied by Arellano-Valle and Genton [On fundamental skew distributions. J Multivar Anal. 2005;96:93–116] and Arellano-Valle and Azzalini [On the unification of families of skew-normal distributions. Scand J Stat. 2006;33:561–574], allows the modelling of data which is symmetrically or asymmetrically distributed. The family has a number of advantages suitable for the analysis of stochastic processes such as Auto-Regressive Moving-Average (ARMA) models, including being closed under linear combinations, being able to satisfy the consistency condition of Kolmogorov’s theorem and providing the guarantee of the existence of such a SUN stochastic process. The family is able to be represented in a hierarchical form which can be used for the ease of simulation. In addition, it facilitates an EM-type algorithm to estimate the model parameters. The performances and suitability of the proposed model are demonstrated on simulations and using two real data sets in applications.
Exploring the Links Between Edge-Preserving Collaborative Filters via Power Watershed Framework

Edge-aware filtering is an important pre-processing step in many computer vision applications. In literature, there exist collaborative edge-aware filters that work well in practice but are based only on heuristics and/or principles. For instance, Tree Filter (TF) which is proposed recently based on a minimum spanning tree (MST) heuristic yields promising results. However the usage of an arbitrary MST for filtering is theoretically not justified. In this article, we introduce an edge-aware generalization of the TF, termed as UMST filter based on all MSTs. The major contribution of this paper is establishing theoretical links between filters based on MSTs and filters based on geodesics via the notion of Γ-convergence. More precisely, we compute the Γ-limit of Shortest Path Filters (SPFs) and show that it is the same as UMST filter. Consequently, TF can be viewed as an approximate Γ-limit of the SPFs, thereby providing a theoretical basis to it's working. Further, we propose and provide a detailed analysis of two different implementations of the UMST filter based on shortest paths.
Learning a 3D Generative Model

In this supplementary, we provide additional details about the architectures used for the Generator, the Discriminator, and about the stage-wise training schedules used in our method. We also provide additional ablation experiments on the use of the fixed-seed reconstruction noise, as mentioned in the main paper. Finally, we plan to make the code, pre-trained models and the newly acquired 3D scenes available, under appropriate licences, to the research community.