Global Basis Research Articles

A machine learning approach for entropy due to natural convection flow of a nanofluid under the uniform inclined magnetic field

In this study, entropy generation of natural convection flow of Cu-water nanofluid under the influence of a uniform inclined magnetic field (MF) is firstly modeled by a machine learning approach using the data obtained from a numerical process. The two dimensional, time dependent dimensionless equations are numerically solved by using global radial basis function (RBF) method in spatial derivatives and the second order backward differentiation formula (BDF2) in time derivatives. In a set of combined dimensionless problem parameters, numerical simulations are performed. In the obtained data, the inputs are a set of combined dimnesionless problem parameters and the outputs are entropy indicators. Then, global and local entropy indicators are modeled by Neural Network (NN). In view of smaller mean squared error metric results, small number of layers or layer sizes in NN seems enough in smaller data while trilayer NN (TNN) is a better modeler in case of larger data.

Pseudospectral methods for continuous-time heterogeneous-agent models

We propose a pseudospectral method to solve heterogeneous-agent models in continuous time. The solution is approximated as a sum of smooth global basis functions, in our case polynomials represented by their values at Chebyshev nodes. We illustrate the method by applying it to a Krusell-Smith model. It solves the differential equations characterizing the steady-state efficiently and precisely, despite using only very few nodes. System dynamics are then automatically differentiated to simulate a linearized model. The full solution takes a third of a second and only uses standard software. A benchmark against finite differences shows that pseudospectral methods achieve far greater precision for a given number of nodes and for a given runtime. We conclude by discussing the methods' applicability, which is promising for smooth multi-dimensional models.

PARALLEL MESHLESS RADIAL BASIS FUNCTION COLLOCATION METHOD FOR NEUTRON DIFFUSION PROBLEMS

The meshless global radial basis function (RBF) collocation method is widely used to model physical phenomena in science and engineering. The method produces highly accurate solutions with an exponential convergence rate. However, due to the global approximation structure of the method, dense node distributions lead to long computation times and hinder the applicability of the technique. In order to overcome this issue, this study proposes a parallel meshless global RBF collocation algorithm. The algorithm is applied to 2-D neutron diffusion problems. The multiquadric is used as the RBF. The algorithm is developed with Mathematica and eight virtual processors are used in calculations on a multicore computer with four physical cores. The method provides accurate numerical results in a stable manner. Parallel speedup increases with the number of processors up to five and seven processors for external and fission source problems, respectively. The speedup values are limited by the constrained resource sharing of the multicore computer’s memory. On the other hand, significant time savings are achieved with parallel computation. For the four-group fission source problem, when 4316 interpolation nodes are employed, the utilization of seven processors instead of sequential computation decreases the computation time of the meshless approach by 716 s.

Enhancing XML-based Compiler Construction with Large Language Models: A Novel Approach

Considering the prevailing rule of Large Language Models (LLMs) applications and the benefits of XML in a compiler context. This manuscript explores the synergistic integration of Large Language Models with XML-based compiler tools and advanced computing technologies. Marking a significant stride toward redefining compiler construction and data representation paradigms. As computing power and internet proliferation advance, XML emerges as a pivotal technology for representing, exchanging, and transforming documents and data. This study builds on the foundational work of Chomsky's Context-Free Grammar (CFG). Recognized for their critical role in compiler construction, to address and mitigate the speed penalties associated with traditional compiler systems and parser generators through the development of an efficient XML parser generator employing compiler techniques. Our research employs a methodical approach to harness the sophisticated capabilities of LLMs, alongside XML technologies. The key is to automate grammar optimization, facilitate natural language processing capabilities, and pioneer advanced parsing algorithms. To demonstrate their effectiveness, we thoroughly run experiments and compare them to other techniques. This way, we call attention to the efficiency, adaptability, and user-friendliness of the XML-based compiler tools with the help of these integrations. And the target will be the elimination of left-recursive grammars and the development of a global schema for LL(1) grammars, the latter taking advantage of the XML technology, to support the LL(1) grammars construction. The findings in this research not only underscore the signification of these innovations in the field of compilation construction but also indicate a paradigm move towards the use of AI technologies and XML in the context of the resolution of programming traditional issues. The outlined methodology serves as a roadmap for future research and development in compiler technology, which paves the way for open-source software to sweep across all fields. Gradually ushering in a new era of compiler technology featuring better efficiency, adaptability, and all CFGs processed through existing XML utilities on a global basis.

Prevalence of Sexual Minority Adolescents Worldwide: A Systematic Review

Health research documenting sexual minority adolescents exists predominately in North American literature. However, sexual minority youth exist elsewhere in the world. This study aims to provide estimates of sexual minority adolescent populations worldwide. In this systematic review, we searched Medline, Embase, CAB direct, Sociology Collection, CINAHL, Academic Search Complete, LGBT Life, Bibliography of Native American Studies, Bibliography of Asian Studies, ERIC, and PsycINFO between 2008 and 2022. We included peer-reviewed publications that focused on youth and sexual orientation or youth and sexual behavior—youth in this study were people who were between 10 and 19 years of age. Examples of publications that were excluded from our study were qualitative studies, mixed-method studies, and interventions. Publications obtained from the search results underwent a country screen, a title and abstract screen, and a methods screen, before moving onto a full-text screen. We extracted the prevalence of sexual minority youth after full-text screening. We identified 42,711 results from searching the electronic databases and an additional 105 records via hand searching. After duplicates were removed, 32,213 articles were screened and 41 studies were eligible for this review. We found estimates of sexual minority adolescents in 47 countries, with at least one estimate for each World Health Organization region. The development of inclusive laws and policies is needed on a global basis to decrease health disparities in a community of people who are at higher risk of adverse health outcomes.

Invisible cancers: Seeing, knowing, enacting and proving cancers in Haiti

In Haiti, pathological confirmation of a cancer diagnosis is often delayed or impossible, imaging is expensive and imperfect, and many tests are unavailable. Physicians frequently struggle to establish cancers at a level of certainty required by “evidence based” standards, delaying definitive diagnosis and rendering some cancers permanently “suspected.” I use 22 months of participant observation at the two largest cancer treatment programs in Haiti, as well as throughout Haiti's fragmented healthcare system, to look closely at processes of diagnosis and management of suspected ‘cancers’ which may never fully come to be. I argue that as global oncology becomes increasingly standardized, local practices are forced into alignment with a global knowledge basis that governs the knowability/unknowability of cancer. Using three case studies drawn from this work, I examine relationships among visibility, power, expertise and the replication of inequity through the governance of knowledge production. Finally, I examine the implications of these processes for cancer care in the global south.

Solution of planar elastic stress problems using stress basis functions

The use of global displacement basis functions to solve boundary-value problems in linear elasticity is well established. No prior work uses a global stress tensor basis for such solutions. We present two such methods for solving stress problems in linear elasticity. In both methods, we split the sought stress σ into two parts, where neither part is required to satisfy strain compatibility. The first part, σ p , is any stress in equilibrium with the loading. The second part, σ h is a self-equilibrated stress field on the unloaded body. In both methods, σ h is expanded using tensor-valued global stress basis functions developed elsewhere. In the first method, the coefficients in the expansion are found by minimizing the strain energy based on the well-known complementary energy principle. For the second method, which is restricted to planar homogeneous isotropic bodies, we show that we merely need to minimize the squared L2 norm of the trace of stress. For demonstration, we solve nine stress problems involving sharp corners, multiple-connectedness, non-zero net force and/or moment on an internal hole, body force, discontinuous surface traction, material inhomogeneity, and anisotropy. The first method presents a new application of a known principle. The second method presents a hitherto unreported principle, to the best of our knowledge.

Modeling of Average Nusselt Number by Machine Learning and Interpolation Techniques

Abstract In this study, an important heat transfer, fluid flow parameter, and average Nusselt number Nu¯ are statistically modeled by using the data obtained from a numerical process. The two-dimensional, time-dependent dimensionless equations of natural convection (NC) flow either in the absence or in the presence of a uniform inclined magnetic field (MF) are numerically solved by using global radial basis function (RBF) method in spatial derivatives and the second-order backward differentiation formula (BDF2) in time derivatives. Numerical simulations are performed in a set of combined dimensionless problem parameters. A dataset with inputs Rayleigh number Ra, Prandtl number Pr, and output Nu¯ in the absence of MF and a dataset with inputs Ra, Pr, Hartmann number Ha, inclination angle γ, and output Nu¯ in the presence of inclined uniform MF are saved. The obtained data are separated into train and test sets. Then, Nu¯ is first modeled by Neural Networks (NN). Second, interpolation is also examined. In terms of mean squared error (MSE) metric, NN outputs give the best goodness of fit results compared to curve fitting on test data. On the other side, it is shown that interpolation is also an alternative for modeling. This modeling issue enables one to get the desired result without making heavy numerical calculations many times.

Lack of Dosage Balance and Incomplete Dosage Compensation in the ZZ/ZW Gila Monster (Heloderma suspectum) Revealed by De Novo Genome Assembly.

Reptiles exhibit a variety of modes of sex determination, including both temperature-dependent and genetic mechanisms. Among those species with genetic sex determination, sex chromosomes of varying heterogamety (XX/XY and ZZ/ZW) have been observed with different degrees of differentiation. Karyotype studies have demonstrated that Gila monsters (Heloderma suspectum) have ZZ/ZW sex determination and this system is likely homologous to the ZZ/ZW system in the Komodo dragon (Varanus komodoensis), but little else is known about their sex chromosomes. Here, we report the assembly and analysis of the Gila monster genome. We generated a de novo draft genome assembly for a male using 10X Genomics technology. We further generated and analyzed short-read whole genome sequencing and whole transcriptome sequencing data for three males and three females. By comparing female and male genomic data, we identified four putative Z chromosome scaffolds. These putative Z chromosome scaffolds are homologous to Z-linked scaffolds identified in the Komodo dragon. Further, by analyzing RNAseq data, we observed evidence of incomplete dosage compensation between the Gila monster Z chromosome and autosomes and a lack of balance in Z-linked expression between the sexes. In particular, we observe lower expression of the Z in females (ZW) than males (ZZ) on a global basis, though we find evidence suggesting local gene-by-gene compensation. This pattern has been observed in most other ZZ/ZW systems studied to date and may represent a general pattern for female heterogamety in vertebrates.

The creation of collective enterprises for social impact: An agency perspective

There is growing recognition of the important role that collective enterprises for social impact can play in resolving grand challenges. New forms of collective organisation are appearing on a global basis, yet we still know little about the process by which they are created. Paradoxically, the literature tends to rely on the concept of individual agency to explain the emergence of collective organisations. Based on inductive research of two French cases, our analysis unpacks the key role of collective agency in collective enterprises created for social impact. By revealing three dynamics – collective entrepreneurship, collective animatorship and collective organising – and their interrelations, this study provides conceptual clarification of the understudied notion of collective agency in entrepreneurship. The study also takes a fresh look at the creation of collective enterprises for social impact beyond the vision of a ‘heroic’ entrepreneur.

GLOCAL: A self-supervised learning framework for global and local motion estimation

Motions in videos are typically a mixture of local dynamic object motions and global camera motion, which are inconsistent in some cases, and even interfere with each other, causing difficulties in various downstream applications, such as video stabilization that requires the global motion, and action recognition that consumes local motions. Therefore, it is crucial to estimate them separately. Existing methods separate two motions from the mixed motion fields, such as optical flow. However, the quality of mixed motion determines the higher bounds of the performance. In this work, we propose a framework, GLOCAL, to directly estimate global and local motions simultaneously from adjacent frames in a self-supervised manner. Our GLOCAL consists of a Global Motion Estimation (GME) module and a Local Motion Estimation (LME) module. The GME module involves a mixed motion estimation backbone, an implicit bottleneck structure for feature dimension reduction, and an explicit bottleneck for global motion recovery based on the global motion bases with foreground mask under the training guidance of proposed global reconstruction loss. An attention U-Net is adopted for LME which produces local motions while excluding motion of irrelevant regions under the guidance of proposed local reconstruction loss. Our method can achieve better performance than the existing methods on the homography estimation dataset DHE and the action recognition dataset NCAA and UCF-101.

Energy-Stable Global Radial Basis Function Methods on Summation-By-Parts Form

Radial basis function methods are powerful tools in numerical analysis and have demonstrated good properties in many different simulations. However, for time-dependent partial differential equations, only a few stability results are known. In particular, if boundary conditions are included, stability issues frequently occur. The question we address in this paper is how provable stability for RBF methods can be obtained. We develop a stability theory for global radial basis function methods using the general framework of summation-by-parts operators often used in the Finite Difference and Finite Element communities. Although we address their practical construction, we restrict the discussion to basic numerical simulations and focus on providing a proof of concept.

Methodical approaches to valuation of intangible assets

Intangible assets in the activities of business entities can constitute a significant part of assets. Their valuation can be done in several ways, which are fundamentally different. Literature offers several methods for valuing intangible assets, which are based on three basic approaches. Each of them captures the value of the property based on different specific characteristics. The issue of intangible assets is also addressed by international accounting standards, the task of which is to guide the accounting and reporting of this type of assets so that the financial statements provide correct and complete information that is comparable on a global basis.

THE EFFECTS OF SOCIAL MEDIA ADVERTISING ON CONSUMERS AYURVEDIC BEAUTY PRODUCTS PURCHASING DECISION OF GENERATION ‘Y’: SPECIAL REFERENCE TO KURUNEGALA DISTRICT IN SRI LANKA

Technology enables consumers to examine product labeling and express critiques, among other capabilities. As a result, many businesses today have pages on social media networks to supplement the information held about products and services, which is held by consumer feedback about products and tends to relate more to a business after reading various reviews. There has been a noticeable increase in demand for cosmetics made with organic and natural components on a global basis. As a result, an increasing number of marketers are focusing on the Ayurvedic market sector, highlighting the importance of the cosmetic business as an essential and important part that demands serious attention in the modern environment. This study proposed the effects of social media advertising on consumer purchasing decisions of generation Y reference to Ayurvedic beauty products in Sri Lanka. The study is quantitative and descriptive in nature. The sample counted 384 respondents from generation Y using the purposive sampling technique. The results show that all the independent variables, credibility, entertainment, informativeness, and interactivity, have significant positive value and strong relationship with the dependent variable (consumer purchasing decision). This study provides a number of theoretical and practical guidelines on how ayurvedic beauty product manufacturers can effectively plan and implement their advertising campaigns over social media.

A Review of the Industrial Importance, Common Bacterial Diseases, and Zoonotic Risks of Freshwater Aquarium Fish.

Background: The ever-increasing popularity of home aquariums, most often involving freshwater varieties, has exploded in recent years partially due to the Coronavirus pandemic and related to stay-at-home public health precautions for social distancing. With this ever-increasing popularity of aquariums as a hobby, and whether this involves freshwater or marine fish species, a number of important economic, ecological, and public health issues arise for both fish and hobbyists alike. Materials and Methods: This review highlights the history and genesis of aquariums as both a hobby and an important economic factor (industrial, commercial) for many countries on a global basis. Types of aquarium fish are described, and culture conditions leading to homeostasis in aquatic environments are detailed. When these conditions are not met and aquatic systems are out of balance, the disease can result due to stressed fish. Results: Major bacterial diseases associated with freshwater aquarium fish are reviewed, as are potential human infections related to the care and maintenance of home aquaria. Conclusion: Besides, scientific information was also combined with the false facts of hobbyists who tried to identify and treat diseases during an outbreak in the aquarium. Finally, unresolved issues and important misconceptions regarding the field are discussed.

An immersed selective discontinuous Galerkin method in particle-in-cell simulation with adaptive Cartesian mesh and polynomial preserving recovery

In this paper, a selective discontinuous Galerkin (SDG) method and a polynomial preserving recovery (PPR) method are developed and integrated with the immersed-finite-element particle-in-cell (IFE-PIC) method, in order to carry out the plasma-material interaction simulation on adaptive Cartesian meshes (ACM). To significantly save the computational cost in practice, the PIC simulation often needs to use Cartesian meshes for the whole domain and the ACM for some focused regions in the plasma-material interaction problems. Therefore, we utilize the SDG method with immersed finite elements for the field solver of the IFE-PIC method, as the key technique to allow the local Cartesian mesh refinement which will generate hanging nodes. To minimize the degree of freedom of the SDG on the ACM and reduce the computational cost, a new selective technique of the discontinuous global basis functions is proposed for the SDG. Various types of nodes in the ACM are discussed for the implementation of this selective technique, including the hanging nodes. Meanwhile, the gathering and scattering steps of the PIC simulation also need to be appropriately performed on the ACM. The PPR method is a generic gradient recovery technique to be incorporated into the IFE-PIC method for more accurate force deposition on the ACM. In addition, two other algorithmic structures of the traditional IFE-PIC method have been modified to accommodate the ACM in the simulation, including a new mapping array structure for the particle positioning and a new charge deposition with some special particle positions in the ACM. As a result, the integrated immersed-selective-discontinuous-Galerkin particle-in-cell (ISDG-PIC) method can efficiently perform the plasma-material interactions simulation on the Cartesian meshes with local mesh refinement independent of the interface. Several numerical experiments are performed to demonstrate the convergence, efficiency, and applicability of the proposed ISDG-PIC method.

The Impact of Government Spending and Government Quality on Energy Poverty- A Global Evidence

This paper examines the impact of government spending and government quality on energy poverty. This study employs a sample covering 77 countries on a global basis during the period of 2007-2022. Using fixed effect regression for panel data, we find that government spending could alleviate energy poverty, as evidenced by higher access to electricity and clean fuel for cooking. These results are consistent across a number of robustness tests. We further find that the favorable impact of government spending is more pronounced among countries with better effectiveness. Overall, our findings provide relevant implications for countries to attain energy security as well as alleviate energy poverty.

Numerical homogenization by an adaptive Fourier spectral method on non-uniform grids using optimal transport

This article focuses on the computation of the solutions to periodic cell problems that arise in a number of homogenization schemes. Formulated in terms of a generic constitutive relation, encompassing the linear and non-linear cases, a model problem is intended to be discretized on a Fourier-basis and solved using a Fast Fourier Transform (FFT)-based iterative scheme. Such a spectral method, which makes use of a uniform grid and global basis functions, has inherent limitations for correctly capturing any localized features of the solution, such as singularities or discontinuities. An adaptive method is proposed here to overcome these shortcomings. It relies on the introduction of a non-homogeneous bijective mapping between the original physical domain and a computational domain, where the Fourier spectral method will be used to solve a transformed problem. This makes it possible both to discretize the original equations on a non-uniform grid, concentrating grid points where necessary to increase computational accuracy, and to maintain the use of standard FFT schemes. To compute the mapping, an approach based on optimal transport is proposed and a numerical scheme based on FFT tools is described. A number of adaptive strategies are then discussed, either based on a priori material-based considerations, or a posteriori using a preliminary solution. The properties of the transported problem in the computational domain are described and the applicability, up to minor modifications, of a number of standard iterative schemes is discussed. A set of numerical examples is included to assess the performances of the method, both in the case of linear conductivity and for a strongly non-linear elastoplastic problem, evaluating its results both qualitatively with full-field comparisons and quantitatively with error measurements relatively to the number of iterations, the discretization and the original material contrast. Overall, these results show that, for a given discretization and compared with a computation on a regular grid, a systematic gain in accuracy is obtained using the adaptive method on a non-uniform grid.

Difference between WMO Climate Normal and Climatology: Insights from a Satellite-Based Global Cloud and Radiation Climate Data Record

The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e., 1991–2020, be used to compute the climate normals of geophysical variables. A unique aspect of this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate-monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 and 2020, we illustrate the difference between the climate normal, as defined by guidelines from WMO on calculations of 30 yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing a climate normal for the recent 30-year period (1991–2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals.

A Fast Multi-Frequency Iterative Acoustic Boundary Element Method Solver Based on a Preconditioned Accelerated Recycling Strategy

Common multi-frequency solution strategies for acoustic systems are either associated with high computational costs or resort to model reduction strategies, which potentially induce considerable approximation errors. In that context, this work proposes a fast multi-frequency solver for acoustic Boundary Element Method (BEM) analyses that combines conventional preconditioners with an accelerated recycling strategy, achieving in that way a fast and accurate iterative solution. Specifically, by approximating both the system and the related preconditioner by individual affine expressions, an upfront Galerkin projection on a global deflation basis is facilitated, therefore enabling the deployment of the accelerated recycling scheme. The latter acts by accelerating the construction of the related deflation projectors, therefore leading to a significantly faster recycling procedure. Finally, the efficiency of the global deflation basis is guaranteed through an Automatic Krylov subspaces Recycling for Deflation (AKR-D) [D. Panagiotopoulos, W. Desmet and E. Deckers, An accelerated subspaces recycling strategy for the deflation of parametric linear systems based on model order reduction, Comput. Methods Appl. Mech. Eng. 403 (2023) 115765] algorithm and thus, the cumulative number of iterations required by an iterative solver within a frequency sweep is drastically decreased. The proposed multi-frequency solver is tested on two industrially relevant examples of an interior and an exterior scattering problem, benchmarked against the traditional solution strategies.