Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the dark sector of the universe using cosmological observables

Although the Standard Model of particle physics has been a phenomenal success in modelling known particles and predicting new, theoretically founded particles, it is known to be incomplete. And while the Standard Model of cosmology has been a phenomenal success in modelling the evolution of the Universe, it too has open questions that remain unresolved. In this thesis, we aim to address properties of new physics models that are being developed that aim to answer these questions. In particular, we wish to focus on and examine in detail the connection between the dark sector of the Universe and the visible sector. In examining this connection, we may use cosmological observables to place strict limits on new theories that go beyond the Standard Model. In the first part of this thesis we will address the flow of energy from the visible sector to the hidden via a phenomenon known as freeze-in. Here, we explore the effects that early-time, ultraviolet energy transfer may have on the infrared, late-time evolution of a dark matter candidate. We use a simplified hidden-sector model to highlight the notion that operators that are typically considered early may have relevant late-time effects. Following this, we consider the reverse energy flow, and consider how dark-sector energy injection via decays of electromagnetic radiation may affect the products of Big Bang Nucleosynthesis. In this section, we focus on arbitrary light particle (< 100 MeV) decays, and identify how direct and indirect alteration of the light element abundances can be constrained using the measured values today. Direct alteration is caused by photodissociation, while indirect effects are felt through changes in the radiation energy density. Finally, we consider a full and rich dark sector, consisting of a non-Abelian SU(3) gauge force. This new gauge field presents itself as glueballs after a confining transition. We study the effects of this confining transition, as well as the subsequent dynamic evolution of the spectrum of glueballs produced. In the final chapter, we examine how decays to Standard Model particles via higher-dimensional, nonrenormalizable operators can place stringent limits on the parameter space of this gauge force.
Final patterns and bifurcation analysis of the odd-periodic Swift–Hohenberg equation with respect to the period

ABSTRACT We study the bifurcation analysis of the Swift–Hohenberg equation (SHE) with the odd-periodic condition as period parameter λ moves. Motivated by Peletier and Rottschäfer [Pattern selection of solutions of the Swift–Hohenberg equations. Phys D. 2004;194:95–126] and Peletier and Williams [Some canonical bifurcations in the Swift–Hohenberg equation. SIAM J Appl Dyn Syst. 2007;6:208–235], with the complete proof based on center manifold reduction, we show how the periodic SHE bifurcates from the trivial solution to an attractor when λ passes a critical number, and mainly when a gap collapsed to a point, and an overlapped interval emerges. Peletier and Williams provided the local behavior about nontrivial solutions of the SHE depending on critical lengths or the overlapped interval based on -norm. In this paper, by dropping the symmetric condition given in the paper by Peletier and Williams, we extend their results and find the explicit stationary solution of the SHE. We also present several numerical results explaining our results.
A review of pollutants emissions in various pressure gain combustors

Recent years have witnessed a significant growth in the advancement and study of various unsteady combustors because of the prospective stagnation pressure gain offered by them. The pressure gain combustion produced by this class of combustors is poised to produce a step-change increase in the thermodynamic efficiency of gas-turbine engines. The current manuscript is oriented toward presenting a review on the pollutant emission characteristics of these devices; specifically, studies done so far on wave rotor combustors, pulsejet combustors, pulse detonation combustors, and rotating detonation combustors are evaluated. Because of the inherent fluid dynamic unsteadiness peculiar to pressure gain combustion devices, their emissions behavior is not well understood, and is notably different from the more conventional, steady combustors. The global view provided herein is expected to further the understanding of pressure gain combustion systems and ascertain the practicality of implementing them in real-world applications.
A technique of flux reconstruction at the interfaces of nonconforming grids for aeroacoustic simulations

A flux reconstruction technique is presented to perform aeroacoustic computations using implicit high‐order spatial schemes on multiblock structured grids with nonconforming interfaces. The use of such grids, with mesh spacing discontinuities across the block interfaces, eases local mesh refinements, simplifies the mesh generation process, and thus facilitates the computation of turbulent flows. In this work, the spatial discretization consists of sixth‐order finite‐volume implicit schemes with low‐dispersion and low‐dissipation properties. The flux reconstruction is based on the combination of noncentered schemes with local interpolations to define ghost cells and compute flux values at the grid interfaces. The flow variables in the ghost cells are calculated from the flow field in the grid cells using a meshless interpolation with radial basis functions. In this study, the flux reconstruction is applied to both plane and curved nonconforming interfaces. The performance of the method is first evaluated by performing two‐dimensional simulations of the propagation of an acoustic pulse and of the convection of a vortex on Cartesian and wavy grids. No significant spurious noise is produced at the grid interfaces. The applicability of the flux reconstruction to a three‐dimensional computation is then demonstrated by simulating a jet at a Mach number of 0.9 and a diameter‐based Reynolds number of 4×105 on a Cartesian grid. The nonconforming grid interface located downstream of the jet potential core does not appreciably affect the flow development and the jet sound field, while reducing the number of mesh points by a factor of approximately two.
Lung imaging and computer-aided diagnosis

A Novel Three-Dimensional Framework for Automatic Lung Segmentation from Low- Dose Computed Tomography Images Ayman El-Baz, Georgy Gimel'farb, Robert Falk, and Mohamed Abo El-Ghar Incremental Engineering of Lung Segmentation Systems Avishkar Misra, Arcot Sowmya, and Paul Compton 3D MGRF-Based Appearance Modeling for Robust Segmentation of Pulmonary Nodules in 3D LDCT Chest Images Ayman El-Baz, Georgy Gimel'farb, Robert Falk, and Mohamed Abo El-Ghar Ground-Glass Nodule Characterization in High-Resolution Computed Tomography Scans Kazunori Okada Four-Dimensional Computed Tomography Lung Registration Methods Anand P. Santhanam, Yugang Min, Jannick P. Rolland, Celina Imielinska, and Patrick A. Kupelian Pulmonary Kinematics via Registration of Serial Lung Images Tessa Cook, Gang Song, Nicholas J. Tustison, Drew Torigian, Warren B. Gefter, and James Gee Acquisition and Automated Analysis of Normal and Pathological Lungs in Small Animals Using Computed Microtomography Xabier Artaechevarria, Mario Ceresa, Arrate Munoz- Barrutia, and Carlos Ortiz-de- Solorzano Airway Segmentation and Analysis from Computed Tomography Benjamin Irving, Andrew Todd-Pokropek, and Paul Taylor Pulmonary Vessel Segmentation for Multislice CT Data: Methods and Applications Jens N. Kaftan and Til Aach A Novel Level Set-Based Computer-Aided Detection System for Automatic Detection of Lung Nodules in Low-Dose Chest Computed Tomography Scans Ayman El-Baz, Aly Farag, Georgy Gimel'farb, Robert Falk, and Mohamed Abo El-Ghar Model-Based Methods for Detection of Pulmonary Nodules Paulo R. S. Mendonca, Rahul Bhotika, and Robert Kaucic Concept and Practice of Genetic Algorithm Template Matching and Higher Order Local Autocorrelation Schemes in Automated Detection of Lung Nodules Yongbum Lee, Takeshi Hara, DuYih Tsai, and Hiroshi Fujita Computer-Aided Detection of Lung Nodules in Chest Radiographs and Thoracic CT Kenji Suzuki Lung Nodule and Tumor Detection and Segmentation Jinghao Zhou and Dimitris N. Metaxas Texture Classification in Pulmonary CT Lauge Sorensen, Mehrdad J. Gangeh, Saher B. Shaker, and Marleen de Bruijne Computer-Aided Assessment and Stenting of Tracheal Stenosis Romulo Pinho, Kurt G. Tournoy, and Jan Sijbers Appearance Analysis for the Early Assessment of Detected Lung Nodules Ayman El-Baz, Georgy Gimel'farb, Robert Falk, Mohamed Abo El-Ghar, and Jasjit Suri Validation of a New Image-Based Approach for the Accurate Estimating of the Growth Rate of Detected Lung Nodules Using Real Computed Tomography Images and Elastic Phantoms Generated by State-of-the-Art Microfluidics Technology Ayman El-Baz, Palaniappan Sethu, Georgy Gimel'farb, Fahmi Khalifa, Ahmed Elnakib, Robert Falk, Mohamed Abo El-Ghar, and Jasjit Suri Three-Dimensional Shape Analysis Using Spherical Harmonics for Early Assessment of Detected Lung Nodules Ayman El-Baz, Matthew Nitzken, Georgy Gimel'farb, Eric Van Bogaert, Robert Falk, Mohamed Abo El-Ghar, and Jasjit Suri Index
An assessment of the impact of oceanic initial conditions on the interaction of upper ocean with the tropical cyclones in the Arabian Sea

ABSTRACT The Regional Ocean Modelling System (ROMS) is utilised to estimate the cyclone-induced mixing and cooling associated with two tropical cyclones, namely Phet and Nilofar over the Arabian Sea (AS). Numerical experiments were carried out with realistic and idealistic oceanic conditions to assess the impact of oceanic initial condition and stratification on the interaction of upper ocean with the tropical cyclones in the AS. The model simulated profiles of temperature and baroclinic kinetic energy are analysed to examine the post-cyclonic cooling and vertical distribution of inertial kinetic energy which interacts with the upper-ocean stratification. Following the cyclone-induced upwelling, the inertial mixing acts to deepen the mixed layer depth (MLD) up to 50 and 100 m from its initial values of 15 and 22 m for the Phet and Nilofar, respectively. The analysis suggests that the combined effect of higher maximum sustained winds and slower translational speed of Nilofar cyclone leads to the excessive cooling (by 1.5°C) of the sea surface as compared to Phet. A decrement in the magnitude of cooling is observed when oceanic initial stratification was altered. The available baroclinic velocity shear at different depths found to modulate the magnitude of upper-ocean cooling in different model experiments.
On the design of stable, high performance sigma delta modulators

The sigma delta architecture of analog-to-digital (A/D) converters is especially applicable to digitizing most bio-signals. High order single-bit sigma delta modulators provide high resolution and linearity with low circuit complexity but require careful design to avoid unstable states. Many existing methods of designing these systems have few degrees of freedom, rely extensively on simulations, and do not provide guarantees about stability. The problem of designing sigma delta modulators with high performance and a clear indicator of the performance versus stability is addressed in this dissertation. This is done by developing a model of the sigma delta modulator that more accurately represents the system including robustness against the nonlinearities due to the quantizer element. After introducing many stability criteria from literature, those most suited to design are identified and the model adjusted to allow these criteria to be applied. High performance is maintained by using the generalized Kalman-Yakubovič-Popov (GKYP) lemma to maximize noise rejection in the signal band using a semidefinite programming (SDP) framework that also permits the use of H∞, H2, and `1 norm-based stability constraints on the system. Several designs using this framework are presented and their relative merits discussed. Examples include an aggressive noise shaping design to compete with existing methods on the basis of performance and designs with guaranteed stability for a range of input signals. The performance-stability trade-off for the different stability constraints using this work is examined and motivated by simulation results.
A Semi-Supervised High-Level Feature Selection Framework for Road Centerline Extraction

Accurate road centerline extraction is very important for many vital applications. In the road extraction, the acquisition of labeled data is time-consuming; thus, there is only a small amount of labeled samples in reality. To solve the problem of limited labeled samples, a semi-supervised road centerline extraction is proposed, which incorporates high-level feature selection, Markov random field (MRF), and ridge transversal method. The proposed road extraction approach consists of three steps: multiple features extraction, semi-supervised road area extraction, and road centerlines extraction. To get more abstract and discriminative high-level features, we apply multiple-feature adaptive sparse representation in mid-level features in different views generated by different prototype sets. To obtain an accurate road area result, we combine the feature learning framework with MRF. Then, we integrate Gabor filters and nonmaxima suppression with the ridge transversal method to extract centerlines. It is verified the proposed method achieves comparable performance with the state-of-the-art methods in terms of visual and quantitative aspects.
Bending and interlayer shear moduli of ultrathin boron nitride nanosheet

We investigate the bending rigidity of ultrathin hexagonal boron nitride nanosheet (BNNS) through quantifying its self-folded conformations on flat substrates by using atomic force microscopy and atomistic simulations. The bending stiffness of two to six layers of BNNS is found to follow a power function of its thickness with a power index of ~2.35 and is substantially higher than that of comparable graphene. In contrast, monolayer graphene possesses a higher stiffness than its h-BN counterpart. We attribute the high bending stiffness of multilayer BNNS to its partially ionic B–N bondings and corrugated electronic structures, which result in one order of magnitude stronger interlayer shear interaction in h-BN than in graphene. The higher out-of-plane bending and interlayer shear rigidities suggest that unlike graphene, BNNS is less prone to interlayer delamination-induced structural inhomogeneities (e.g. shearing, rippling and kinks) and thus is suitable as a building block for atomically thin electronics and a reinforcing filler for nanocomposites.
Vacancy-assisted core transformation and mobility modulation of a-type edge dislocations in wurtzite GaN

In this study, core structure dependent dislocation dynamics of a-type edge dislocation in three slip systems (basal, prismatic and pyramidal) of wurtzite GaN have been investigated using classical molecular dynamics simulations. All potential a-type edge dislocation cores in the shuffle and glide planes of the three slip systems have been identified, and the corresponding dislocation dynamics were examined. Our calculations reveal that for all of the three slip systems, all of the shuffle cores are planar glissile and mobile, while being non-planar sessile and immobile for all of the glide cores. We further show that vacancy can be used to activate the motion of glide cores via core transition from glide to shuffle, which is also valid for AlN and InN. The critical shear stresses for the motion of glide cores are also determined at various vacancy concentrations. Our study clarifies core structure dependent dislocation dynamics characteristics and provides ways in tuning dislocation motions in wurtzite crystals.
Gridded Statistical Downscaling Based on Interpolation of Parameters and Predictor Locations for Summer Daily Precipitation in North China

Few statistical downscaling applications have provided gridded products that can provide downscaled values for a no-gauge area as is done by dynamical downscaling. In this study, a gridded statistical downscaling scheme is presented to downscale summer precipitation to a dense grid that covers North China. The main innovation of this scheme is interpolating the parameters of single-station models to this dense grid and assigning optimal predictor values according to an interpolated predictand–predictor distance function. This method can produce spatial dependence (spatial autocorrelation) and transmit the spatial heterogeneity of predictor values from the large-scale predictors to the downscaled outputs. Such gridded output at no-gauge stations shows performances comparable to that at the gauged stations. The area mean precipitation of the downscaled results is comparable to other products. The main value of the downscaling scheme is that it can obtain reasonable outputs for no-gauge stations.
Group-Oriented Task Allocation for Crowdsourcing in Social Networks

Previous crowdsourcing studies often adopted the individual-oriented approach that outsources a task to an individual worker or team formation-based approach that outsources a task to an artificially formed team of workers. Nowadays, workers are often naturally organized into groups through social networks. To address such common issue of grouped workers in real crowdsourcing systems, this article explores a novel crowdsourcing paradigm in which the task allocation targets are naturally existing worker groups but not individual workers or artificially formed teams as before. Because a natural group might not possess all required skills and needs to coordinate with other groups in the social network contexts for performing a complex task, a concept of contextual crowdsourcing value is presented to measure a group’s capacity to complete a task by coordinating with its contextual groups, which determines the priority that the group is assigned the task; then, the task allocation algorithms, including the allocations of groups and the workers actually participating in executing the task, are designed. The experiments on a real-world dataset show that our presented group-oriented approach can nearly always achieve better synergy performance, consistency performance, conflict performance, adaptability, and effectiveness on reducing costs, as compared with previous benchmark individual-oriented and team formation approaches.
STUDY OF FACTORS LIKE SMOKING AND ITS ASSOCIATION WITH INFLAMMATION AND CARDIOVASCULAR RISKS IN PRE-DIABETIC AND DIABETIC PATIENTS.

Dr.Varsha chowdhry and Dr.Deepa thadani. Assistant professor Department of Biochemistry :Professor & HOD department of biochemistry ,Jawahar lal Nehru medical college and attached group of hospital ajmer,Rajasthan 305001. Manuscript Info Abstract . Manuscript History Received: 24 May 2019 Final Accepted: 26 June 2019 Published: July 2019
SANDWICH-TYPE OUTCOME BASED ON A DUAL LINEAR OPERATOR

By using a dual linear operator that we define it on meromorphic multivalent functions (MMF) in the punctured unit disk U∗, we derive some third-order differential subordination and superordination outcomes by taking into account the appropriate class of admissible functions. Sufficient conditions are determined to yield the best dominant and the best subordinant, respectively. Moreover, sandwich-type outcome is obtained. AMS Subject Classification: 30C45, 30C50, 26A33
Solution of Newell-Whitehead-Segel equation by variational iteration method with He's polynomials

This article seeks to extend the variational iteration method (VIM) with He’s polynomials for the approximate solution of nonlinear Newell-Whitehead-Segel equation (NWSE). Lagrange multiplier in correction functional is determined with the help of variational theory, and then homotopy perturbation method (HPM) is employed to dissolve the nonlinear terms. Thus a successful series is obtained with these iterations which are termed as He’s polynomials. Result shows that this method is highly accurate and comes closer very quickly to the exact solution. We formulate three possible cases of NWSE to show the capability and ability of the present method. The valuable outcome discloses that the proposed strategy is very convenient, straightforward and can be utilized to linear and nonlinear problems.
Phase coding of competing memories along the hippocampal theta oscillation in human MEG

How can the human brain retrieve unique memories, given the vast amount of overlapping information available in memory? The aim of the present study is to understand what role hippocampal theta oscillations play in this mnemonic selection process. Computational models propose that phase coding along a slow (theta) oscillation provides an efficient way of separating relevant, to-be-remembered information from overlapping, currently irrelevant information (Lisman & Jensen, 2013; Norman et al., 2006). In the present study, we used a newly developed approach (Kerren, Linde-Domingo, Hanslmayr, & Wimber, 2018) for analysing periodic memory reactivation in non-invasive magnetoencephalographic (MEG) data. We show that to-be-remembered memories are reactivated at a specific phase along a slow (7Hz) hippocampal oscillation, and that the brain codes competing memories at a different phase of the oscillatory cycle. This is the first demonstration of phase shifts in periodic memory reactivation signals in humans, and provides new insights into how the brain handles mnemonic competition on a millisecond time scale.
Adaptive Output-Feedback Control for Dual Overhead Crane System With Enhanced Anti-Swing Performance

In industrial practice, to improve transportation capability, there has been increasing applications for dual overhead crane systems (DOCSs). Compared with single overhead crane systems (SOCSs), DOCSs are more dangerous and difficult for human operators to manipulate due to their extremely complex system dynamics. Furthermore, more people, usually not less than three, are required to guarantee the safety of a typical transportation process of DOCS, which is not only of low efficiency but also causes a waste of human resources. Due to the above facts, it is concluded that automation of DOCS has great practical significance. To promote this process, a high-performance nonlinear controller is proposed in this article, which can better suppress the payload swing due to the incorporation of more swing-related information. Besides, only position signals are required for feedback, which is more practical for industrial application. Another highlight of the proposed method lies in the fact that it can well conquer the payload mass uncertainty with an adaption law, so that many corresponding adverse effects are eliminated. The performance of the proposed method is not only theoretically proved by rigorous mathematical analysis, but also validated with convincing hardware experiments.