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Investigation of performance measures of power generating unit of sewage treatment plant

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Journal of Physics: Conference Series 2021年第1期1714卷

作者： Monika Saini Drishty Goyal Ashish Kumar Deepak Sinwar Department of Mathematics & Statistics School of Basic Science Manipal University Jaipur Jaipur–303007 India Department of Computer and Communication Engineering Manipal University Jaipur Jaipur-303007 Rajasthan India

The main objective of present study to investigate the availability and profit of power generation systems established in sewage treatment plants. The sewage treatment plant is an industry in which waste sewage water has been treated and waste is used to generate power. For this purpose, a mathematical model has been proposed by considering constant failure and repair rates. The power generating unit in sewage treatment plant comprises six subsystems as sludge digester, gas holding tank, gas burner, gas scrubber, gas engine and power generation. By using appropriate redundancy technique in model development Chapman-Kolmogorov differential equations has been drawn with the help of the Markov birth death process. Availability and profit have been analysed based on making variation in the failure and repair rates. The numerical and graphical results have been depicted for a particular case. The derived results have been discussed with system designers and found useful.

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Electro-mechanically guided growth and patterns

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arXiv 2020年

作者： Du, Y. Su, Y. Lü, C. Chen, W. Destrade, M. Department of Engineering Mechanics Zhejiang University Hangzhou310027 China Department of Civil Engineering Zhejiang University Hangzhou310058 China Key Lab of Soft Machines Smart Devices of Zhejiang Province Zhejiang University Hangzhou310027 China Soft Matter Research Center Zhejiang University Hangzhou310027 China School of Mathematics Statistics and Applied Mathematics NUI Galway University Road Galway Ireland Sonny Astani Department of Civil and Environmental Engineering University of Southern California Los AngelesCA90089 United States

Several experiments have demonstrated the existence of an electro-mechanical effect in many biological tissues and hydrogels, and its actual influence on growth, migration, and pattern formation. Here, to model these interactions and capture some growth phenomena found in Nature, we extend volume growth theory to account for an electro-elasticity coupling. Based on the multiplicative decomposition, we present a general analysis of isotropic growth and pattern formation of electro-elastic solids under external mechanical and electrical fields. As an example, we treat the case of a tubular structure to illustrate an electro-mechanically guided growth affected by axial strain and radial voltage. Our numerical results show that a high voltage can enhance the non-uniformity of the residual stress distribution and induce extensional buckling, while a low voltage can delay the onset of wrinkling shapes and can also generate more complex morphologies. Within a controllable range, axial tensile stretching shows the ability to stabilise the tube and help form more complex 3D patterns, while compressive stretching promotes instability. Both the applied voltage and external axial strain have a significant impact on guiding growth and pattern formation. Our modelling provides a basic tool for analysing the growth of electro-elastic materials, which can be useful for designing a pattern prescription strategy or growth self-assembly in engineering. Copyright © 2020, The Authors. All rights reserved.

关键词： Self assembly

Modeling liquid water by climbing up Jacob’s ladder in density functional theory facilitated by using deep neural network potentials

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arXiv 2021年

作者： Zhang, Chunyi Tang, Fujie Chen, Mohan Zhang, Linfeng Qiu, Diana Y. Perdew, John P. Klein, Michael L. Wu, Xifan Department of Physics Temple University PhiladelphiaPA19122 United States HEDPS Center for Applied Physics and Technology College of Engineering Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Chemistry Temple University PhiladelphiaPA19122 United States Institute for Computational Molecular Science Temple University PhiladelphiaPA19122 United States

Within the framework of Kohn-Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately normed (SCAN) functional has been extensively demonstrated in recent years. Here, we further advance the modeling of water by building a more accurate model on the fourth rung of Jacob’s ladder with the hybrid functional, SCAN0. In particular, we carry out both classical and Feynman path-integral molecular dynamics calculations of water with the SCAN0 functional and the isobaric-isothermal ensemble. In order to generate the equilibrated structure of water, a deep neural network potential is trained from the atomic potential energy surface based on ab initio data obtained from SCAN0 DFT calculations. For the electronic properties of water, a separate deep neural network potential is trained using the Deep Wannier method based on the maximally localized Wannier functions of the equilibrated trajectory at the SCAN0 level. The structural, dynamic, and electric properties of water were analyzed. The hydrogen-bond structures, density, infrared spectra, diffusion coefficients, and dielectric constants of water, in the electronic ground state, are computed using a large simulation box and long simulation time. For the properties involving electronic excitations, we apply the GW approximation within many-body perturbation theory to calculate the quasiparticle density of states and bandgap of water. Compared to the SCAN functional, mixing exact exchange mitigates the self-interaction error in the meta-generalized-gradient approximation and further softens liquid water towards the experimental direction. For most of the water properties, the SCAN0 functional shows a systematic improvement over the SCAN functional. © 2021, CC BY.

关键词： Deep neural networks

Estimates of global SARS-CoV-2 infection exposure, infection morbidity, and infection mortality rates in 2020

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Global Epidemiology 2021年 3卷 100068页

作者： Ayoub, Houssein H. Mumtaz, Ghina R. Seedat, Shaheen Makhoul, Monia Chemaitelly, Hiam Abu-Raddad, Laith J. Mathematics Program Department of Mathematics Statistics and Physics College of Arts and Sciences Qatar University Doha Qatar Department of Epidemiology and Population Health American University of Beirut Beirut Lebanon Infectious Disease Epidemiology Group Weill Cornell Medicine-Qatar Cornell University Doha Qatar World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS Sexually Transmitted Infections and Viral Hepatitis Weill Cornell Medicine–Qatar Cornell University Qatar Foundation – Education City Doha Qatar Department of Population Health Sciences Weill Cornell Medicine Cornell University New York NY United States Department of Public Health College of Health Sciences QU Health Qatar University Doha Qatar

We aimed to estimate, albeit crudely and provisionally, national, regional, and global proportions of respective populations that have been infected with SARS-CoV-2 in the first year after the introduction of this virus into human circulation, and to assess infection morbidity and mortality rates, factoring both documented and undocumented infections. The estimates were generated by applying mathematical models to 159 countries and territories. The percentage of the world's population that has been infected as of 31 December 2020 was estimated at 12.56% (95% CI: 11.17–14.05%). It was lowest in the Western Pacific Region at 0.66% (95% CI: 0.59–0.75%) and highest in the Americas at 41.92% (95% CI: 37.95–46.09%). The global infection fatality rate was 10.73 (95% CI: 10.21–11.29) per 10,000 infections. Globally per 1000 infections, the infection acute-care bed hospitalization rate was 19.22 (95% CI: 18.73–19.51), the infection ICU bed hospitalization rate was 4.14 (95% CI: 4.10–4.18). If left unchecked with no vaccination and no other public health interventions, and assuming circulation of only wild-type variants and no variants of concern, the pandemic would eventually cause 8.18 million deaths (95% CI: 7.30–9.18), 163.67 million acute-care hospitalizations (95% CI: 148.12–179.51), and 33.01 million ICU hospitalizations (95% CI: 30.52–35.70), by the time the herd immunity threshold is reached at 60–70% infection exposure. The global population remained far below the herd immunity threshold by end of 2020. Global epidemiology reveals immense regional variation in infection exposure and morbidity and mortality rates. © 2021 The Authors

关键词： Coronavirus COVID Epidemiology Exposure Fatality Prevalence SARS-CoV-2 Severity

Analysis of chemical compound in essential oil from clove stem using the FTIR and GCMS methods

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AIP Conference Proceedings 2023年第1期2738卷

作者： Hermin Pancasakti Kusumaningrum Galih Wiji Agung Fakhri Santo Khoirudin Lailatul Khoiriyah Ardian Fikri Amrullah Farah Hanifah Handika Arya Listyanto Muhammad Zainuri I. Nyoman Widiasa Indra Gunawan Biotechnology Study Program Biology Department Faculty of Science and Mathematics Diponegoro University Jl. Prof. Soedharto SH. Tembalang Semarang 50275 Indonesia Department of Chemical Engineering Faculty of Engineering Diponegoro University Jl. Prof. Soedharto SH. Tembalang Semarang 50275 Indonesia Chemistry Department Faculty of Science and Mathematics Diponegoro University Jl. Prof. Soedharto SH. Tembalang Semarang 50275 Indonesia Marine Laboratory Faculty of Fisheries and Marine Sciences Diponegoro University Jl. Prof. Soedharto SH. Tembalang Semarang 50275 Indonesia

Clove (Syzigium aromaticum) is an essential oil-producing plant which is widely found in Indonesia. Essential oil was made from it flower buds, leaves and stems for toothpaste, soaps, cosmetics, perfumes and cigarettes industries. Clove oil has been used in medicinal purposes for relieving pain, treating infection, easing digestive upset, dental and topical application. The objectives of the GC-MS analysis is to measure the type and content of compounds present in the clove stem sample, while the FT-IR analysis is to obtain the infrared spectrum on the clove stem sample through emission or absorption of solids, liquids. and gases in the sample. The chemical functional groups that were read through FT-IR on stem clove oil indicated that it contained aromatic compounds in the form of eugenol and eugenol acetate. The eugenol compound was the main component of the clove stem. The results of GC-MS analysis showed the chemical composition of clove oil consists of 28 compounds with the dominant components of clove oil are eugenol and caryophyllene (93% and 4.80%).

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Revisiting minimum description length complexity in overparameterized models

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arXiv 2020年

作者： Dwivedi, Raaz Singh, Chandan Yu, Bin Wainwright, Martin Department of Operations Research & Information Engineering Cornell Tech Cornell University New York CityNY United States Microsoft Research SeattleWA United States Department of Statistics and Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA United States Department of Electrical Engineering and Computer Sciences and Mathematics Massachusetts Institute of Technology CambridgeMA United States

Complexity is a fundamental concept underlying statistical learning theory that aims to inform generalization performance. Parameter count, while successful in low-dimensional settings, is not well-justified for overparameterized settings when the number of parameters is more than the number of training samples. We revisit complexity measures based on Rissanen's principle of minimum description length (MDL) and define a novel MDL-based complexity (MDL-COMP) that remains valid for overparameterized models. MDL-COMP is defined via an optimality criterion over the encodings induced by a good Ridge estimator class. We provide an extensive theoretical characterization of MDL-COMP for linear models and kernel methods and show that it is not just a function of parameter count, but rather a function of the singular values of the design or the kernel matrix and the signal-to-noise ratio. For a linear model with n observations, d parameters, and i.i.d. Gaussian predictors, MDL-COMP scales linearly with d when d n. For kernel methods, we show that MDL-COMP informs minimax in-sample error, and can decrease as the dimensionality of the input increases. We also prove that MDL-COMP upper bounds the in-sample mean squared error (MSE). Via an array of simulations and real-data experiments, we show that a data-driven Prac-MDL-COMP informs hyper-parameter tuning for optimizing test MSE with ridge regression in limited data settings, sometimes improving upon cross-validation and (always) saving computational costs. Finally, our findings also suggest that the recently observed double decent phenomenons in overparameterized models might be a consequence of the choice of non-ideal estimators. © 2020, CC BY.

关键词： Mean square error

Tameness, powerful images, and large cardinals

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arXiv 2019年

作者： Boney, Will Lieberman, Michael Mathematics Department Texas State University San MarcosTX United States Institute of Mathematics Faculty of Mechanical Engineering Brno University of Technology Brno Czech Republic Department of Mathematics and Statistics Faculty of Science Masaryk University Brno Czech Republic

We provide comprehensive, level-by-level characterizations of large cardinals, in the range from weakly compact to strongly compact, by closure properties of powerful images of accessible functors. In the process, we show that these properties are also equivalent to various forms of tameness for abstract elementary classes. This systematizes and extends results of [BU17], [BTR16], [Lie18], and [LR16].03E55, 03C95, 18C35 Copyright © 2019, The Authors. All rights reserved.

关键词： Equivalence classes

Probabilistic connectivity of random graphs and their unions

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arXiv 2019年

作者： Bjorkman, Beth Hale, Matthew Lamkin, Thomas Robinson, Benjamin Thompson, Craig Iowa State University Department of Mathematics Department of Mechanical and Aerospace Engineering University of Florida Air Force Research Laboratory Sensors Directorate University of Arizona Program in Applied Mathematics

Graph-theoretic methods have seen wide use throughout the literature on multi-agent control and optimization. When communications are intermittent and unpredictable, such networks have been modeled using random communication graphs. When graphs are time-varying, it is common to assume that their unions are connected over time, yet, to the best of our knowledge, there are not results that determine the number of random graphs needed to attain a connected union. Therefore, this paper bounds the probability that individual random graphs are connected and bounds the same probability for connectedness of unions of random graphs. The random graph model used is a generalization of the classic Erdos-R ényi model which allows some edges never to appear. Numerical results are presented to illustrate the analytical developments made. Copyright © 2019, The Authors. All rights reserved.

关键词： Graph theory

Interval-valued intuitionistic fuzzy topological sub algebras (IVIFTS) in BF-algebras

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AIP Conference Proceedings 2021年第1期2375卷

作者： Venkata Subrahmanyam Sajja Dasari Ramesh K. V. S. Sarma Gudala Balaji Prakash B. V. Appa Rao 1Department of Mathematics Koneru Lakshmaiah Education Foundation Guntur-522502 Andhra Pradesh India 2Department of Mathematics Gayatri Vidya Parishad College for Degree and PG Courses (A) Engineering and Technology Program Visakhapatnam Andhra Pradesh India

The concept “interval-valued intuitionistic fuzzy sets (IVIFS)” was delivered through Atanassov’s and Gargov [21] in 1989 as a simplification of each IVFS and IFS. Satyanarayana et al. [3, 4] implemented the concept of IVIFSs to BF-sub-algebras and fuzzy ideals of BF-algebras. Further, the notion of an IVIFTS of BF-algebras are also discussed in this work.

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