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Prediction of Fluctuations in a Chaotic Cancer Model Using Machine Learning

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SSRN

SSRN 2022年

作者： Sayari, Elaheh da Silva, Sidney Tiago Iarosz, Kelly C. Viana, Ricardo L. Szezech, José Danilo Batista, Antonio Marcos Post-Graduation in Science State University of Ponta Grossa PR Ponta Grossa Brazil Federal University of Paraná PR Curitiba Brazil Faculdade de Telêmaco Borba FATEB Telêmaco Borba Paraná Brazil Graduate Program in Chemical Engineering Federal Technological University of Paraná PR Ponta Grossa Brazil Department of Physics Federal University of Paraná PR Curitiba Brazil Institute of Physics University of São Paulo SP São Paulo Brazil Mathematics and Statistics Department State University of Ponta Grossa PR Ponta Grossa Brazil

Cancer is a group of diseases and the second leading cause of death according to World Health Organization. Mathematical and computational methods have been used to explore the cancer cells spread and the mechanism of their growth. We study a cancer model that exhibits both periodic and chaotic attractors. It describes the interactions among host, effector immune, and cancer cells. It is observed fluctuations in the population of cells. The fluctuation range can be associated with the appearance of tumour cells. In this work, we use machine learning algorithms for the prediction of fluctuations. We show that our machine learning classification is able to identify fluctuations that are associated with the growth rate of cancer cells. © 2022, The Authors. All rights reserved.

关键词： Cancer cells

Artificial Neural Network Models to Examine the Relationship between Saturated Soil Hydraulic Conductivity and Co-Driven Factors at the Watershed Scale

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SSRN

SSRN 2023年

作者： Soares, Mauricio Fornalski Siqueira, Tirzah Moreira Nunes, Romulo Félix Pedrollo, Olavo Correa Reichardt, Klaus Barros, Willian Silva Timm, Luís Carlos Water Resources Post-Graduate Program Center of Technological Development Federal University of Pelotas Campus Porto Rua Gomes Carneiro n. 01 Rio Grande do Sul PelotasCEP: 96010-610 Brazil Center of Engineering Federal University of Pelotas Rio Grande do Sul Pelotas Brazil Soil and Water Management and Conservation Post-Graduate Program Faculty of Agronomy Federal University of Pelotas Rio Grande do Sul Pelotas Brazil Hydraulic Researchs Institute Federal University of Rio Grande do Sul Rio Grande do Sul Porto Alegre Brazil Soil Physics Laboratory CENA Department of Crop Production ESALQ University of São Paulo Piracicaba São Paulo Brazil Department of Statistics Federal University of Pelotas Campus Universitário s/n Rio Grande do Sul Capão do LeãoCEP: 96010-900 Brazil Department of Rural Engineering Faculty of Agronomy Federal University of Pelotas Campus Universitário s/n Rio Grande do Sul Capão do LeãoCEP: 96010-900 Brazil

Saturated soil hydraulic conductivity (KSat) is a key soil attribute that affects hydrological processes in the soil surface layer. It is well known that KSat is difficult to be obtained in the field, requires time and expensive equipment, skilled labor and, due to its variability, requires many samples and can hardly be extrapolated. Artificial neural networks (ANNs) are powerful no-linear mathematical models to estimate KSat from different soil hydro-physical and environmental input variables as well as by using dimensionless variables generated by database resizing techniques from principal component analyses (PCA). The present study aimed to construct artificial neural network models for predicting KSat using soil attributes and different land uses as input variables at a watershed scale. The study was carried out in the Ellert Creek watershed of about 0.7 km2, Brazil, in which an experimental grid consisted of 178 sampling points was established. Data of soil bulk density, total porosity, microporosity, macroporosity, soil organic carbon content, sand, silt and clay, and KSat were determined at each point in the 0-20 cm layer. A land-use map was derived from satellite images and used to identify the land use around each soil sampling point. PCA was applied to the original data set and selected PCs were used as input variables for ANN modeling. Two PCs were selected and the results suggest that their inclusion as input parameters, both or individually, combined with the original data, increased the performance of the analyzed ANN models, when compared to similar models with only original data and without PCs. The use of ANN models showed that the variation of KSat in the ECW watershed is not only associated to soil hydrological and environment covariates, but also to PCs which are orthogonal linear recombinations that resume the main sources of variation of the original data sets. © 2023, The Authors. All rights reserved.

关键词： Soils

Forgery blind inspection for detecting manipulations of gel electrophoresis images

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arXiv 2020年

作者： Shao, Hao-Chiang Cheng, Ya-Jen Duh, Meng-Yun Lin, Chia-Wen Dept. Statistics and Information Science Fu Jen Catholic University Taiwan Office of Neuroscience Program of Academia Sinica Institute of Molecular Biology Academia Sinica Taiwan Dept. Electrical Engineering National Tsing Hua University Taiwan

Recently, falsified images have been found in papers involved in research misconducts. However, although there have been many image forgery detection methods, none of them was designed for molecular-biological experiment images. In this paper, we proposed a fast blind inquiry method, named FBIGEL, for integrity of images obtained from two common sorts of molecular experiments, i.e., western blot (WB) and polymerase chain reaction (PCR). Based on an optimized pseudo-background capable of highlighting local residues, FBIGEL can reveal traceable vestiges suggesting inappropriate local modifications on WB/PCR images. Additionally, because the optimized pseudo-background is derived according to a closed-form solution, FBIGEL is computationally efficient and thus suitable for large scale inquiry tasks for WB/PCR image integrity. We applied FBIGEL on several papers questioned by the public on PUBPEER, and our results show that figures of those papers indeed contain doubtful unnatural patterns. Copyright © 2020, The Authors. All rights reserved.

关键词： Polymerase chain reaction

Determinants of Generalized Anxiety, Depression, and Subjective Sleep Quality among University Students during COVID-19 Pandemic in Bangladesh

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Dr. Sulaiman Al Habib Medical Journal 2021年第1期3卷 27-35页

作者： Shovo, Taufiq-E-Ahmed Ahammed, Benojir Khan, Bayezid Jahan, Nusrat Shohel, Tunvir Ahamed Hossain, Tanvir Islam, Nazrul Sociology Discipline Social Science School Khulna University Khulna Bangladesh School of Humanities and Social Science Faculty of Education and Arts University of Newcastle Callaghan Australia Statistics Discipline Science Engineering & Technology School Khulna University Khulna Bangladesh Development Studies Discipline Social Science School Khulna University Khulna Bangladesh Social and Political Science (SPS) Program Faculty of Arts Monash University Melbourne Australia Forestry and Wood Technology Discipline Life Science School Khulna University Khulna Bangladesh

The aim of this study was to determine the risk factors associated with generalized anxiety, depression, and subjective sleep quality among university students during the Coronavirus Disease 2019 (COVID-19) pandemic in Bangladesh. Data for this web-based cross-sectional study were collected from 1317 university students from 49 universities using a self-administered e-questionnaire in the last week of April 2020. Findings suggest that university students have been experiencing heightened generalized anxiety (51%), depression (45.9%), and poor subjective sleep quality (27.1%). Results also indicate that university students were severely frightened about COVID-19. The severity of fear and geographical locations were the key determinants in shaping the state of mind as well as subjective sleep quality of university students. It is, therefore, strongly recommended to initiate not only effective strategies to reduce the transmission of COVID-19 but also a strict monitoring mechanism to detect the presence of mental ailments among university students, and to offer necessary supports through family, community, and institutional agencies to curb psychological problems, especially during this unprecedented health emergency.

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Exponential acceleration of macroscopic quantum tunneling in a Floquet Ising model

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arXiv 2023年

作者： Grattan, George Barton, Brandon A. Feeney, Sean Mossi, Gianni Patnaik, Pratik Sagal, Jacob C. Carr, Lincoln D. Oganesyan, Vadim Kapit, Eliot Quantum Engineering Program Colorado School of Mines 1523 Illinois St CO Golden80401 United States Department of Computer Science Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Physics Colorado School of Mines 1523 Illinois St CO Golden80401 United States KBR Inc. 601 Jefferson St. HoustonTX77002 United States NASA Ames Research Center Moffett FieldCA94035 United States Department of Physics and Astronomy College of Staten Island CUNY Staten IslandNY10314 United States Physics program and Initiative for the Theoretical Sciences The Graduate Center CUNY New YorkNY10016 United States Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States

The exponential suppression of macroscopic quantum tunneling (MQT) in the number of elements to be reconfigured is an essential element of broken symmetry phases. Slow MQT is also a core bottleneck in quantum algorithms, such as traversing an energy landscape in optimization, and adiabatic state preparation more generally. In this work, we demonstrate the possibility to accelerate MQT through Floquet engineering with the application of a uniform, high frequency transverse drive field. Using the ferromagnetic phase of the transverse field Ising model in one and two dimensions as a prototypical example, we identify three qualitatively distinct regimes as a function of drive strength: (i) for weak drive, the system exhibits exponentially slow MQT alongside robust magnetic order, as expected;(ii) at intermediate drive strength, we find polynomial decay of rates alongside vanishing magnetic order consistent with critical or paramagnetic state;(iii) at very strong drive strengths both the tunnelling rate and time-averaged magnetic order remain finite with increasing system size. We support these claims with extensive full wavefunction and matrix-product state numerical simulations, and theoretical analysis. An experimental test of these results presents a technologically important and novel scientific question accessible on NISQ-era quantum computers. © 2023, CC BY.

关键词： Ising model

Direct Comparison of RT-ddPCR and Targeted Amplicon Sequencing for SARS-CoV-2 Mutation Monitoring in Wastewater

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SSRN

SSRN 2022年

作者： Lou, Esther G. Sapoval, Nicolae McCall, Camille Bauhs, Lauren Carlson-Stadler, Russell Kalvapalle, Prashant Lai, Yanlai Palmer, Kyle Penn, Ryker Rich, Whitney Wolken, Madeline Ensor, Katherine B. Hopkins, Loren Treangen, Todd J. Stadler, Lauren B. Department of Civil and Environmental Engineering Rice University 6100 Main Street MS 519 HoustonTX77005 United States Department of Computer Science Rice University 6100 Main Street HoustonTX77005 United States Systems Synthetic and Physical Biology Graduate Program Rice University 6100 Main Street HoustonTX77005 United States Houston Health Department 8000 N. Stadium Dr. HoustonTX77054 United States Department of Statistics Rice University 6100 Main Street MS 138 HoustonTX77005 United States

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3;hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing. © 2022, The Authors. All rights reserved.

关键词： SARS

Study of nonlinear wave equation of optical field for solotonic type results

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Partial Differential Equations in Applied Mathematics 2025年 13卷

作者： Ullah, Ikram Bilal, Muhammad Shah, Dawood Khan, Hasib Alzabut, Jehad Alkhawar, Hisham Mohammad School of Mathematics and Statistics Central South University Changsha Hunan 410083 China Department of Mathematics Abdul Wali Khan University Mardan Khyber Pukhton Khwkha 23200 Pakistan Department of Mathematics University of Malakand Dir Lower Khyber Pukhton Khwkha 18000 Pakistan Department of Mathematics and Sciences Prince Sultan University P.O. Box 66833 Riyadh 11586 Saudi Arabia Department of Mathematics Shaheed Benazir Bhutto Uniersity Sheringal Dir Upper 18000 Khyber Pakhtunkhwa Pakistan Department of Industrial Engineering OSTIM Technical University Ankara 06374 Turkey Center for Research and Innovation Asia International University Yangiobod MFY G'ijduvon street House 74 Bukhara Uzbekistan Preparatory Year Program Computer Department Prince Sultan University Riyadh 11586 Saudi Arabia

This paper uses the fractional perturbed Gerdjikov–Ivanov (PGI) model, a basic mathematical framework in mathematical physics and nonlinear dynamics, to examine complex wave structures using the M-fractional operator and modified Extended Direct Algebraic Method (mEDAM). We find a wide variety of new optical wave solutions, such as kink-type, dark, brilliant, periodic, combo, exponential, trigonometric, and hyperbolic solutions. our examine the dynamic behavior and free parameters of these soliton solutions using contour plots and three-dimensional charts. The uniqueness of the study is shown by the noteworthy consistency and divergence of our results from earlier answers. This work makes a substantial contribution to the PGI model's ability to extract many solitary wave solutions. The proposed suggested method shows dependability while assessing analytical solutions for fractional differential equations. This research intends to extend mathematical approaches for solving fractional differential equations, which will enable answers to a wide range of practical scientific and engineering problems, including implications for ultrafast pulse transmission in optical fibers. © 2025 The Authors

关键词： Advancements in mathematical modeling Fractional differential equations Fractional perturbed Gerdjikov–Ivanov (PGI) model Mathematical physics Modified Extended Direct Algebraic Method (mEDAM) Nonlinear optics Optical communication Solitary wave solutions

The effect of time delay for synchronisation suppression in neuronal networks

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arXiv 2022年

作者： Hansen, Matheus Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Batista, Antonio M. Macau, Elbert E.N. Institute of Science and Technology Federal University of São Paulo - UNIFESP São José dos Campos SP São Paulo Brazil Institute of Physics University of São Paulo SP São Paulo Brazil Faculdade de Telêmaco Borba FATEB Telêmaco Borba Paraná Brazil Graduate Program in Chemical Engineering Federal Technological University of Paraná PR Ponta Grossa Brazil State University of Ponta Grossa PR Ponta Grossa Brazil Mathematics and Statistics Department State University of Ponta Grossa PR Ponta Grossa Brazil

We study the time delay in the synaptic conductance for suppression of spike synchronisation in a random network of Hodgkin Huxley neurons coupled by means of chemical synapses. In the first part, we examine in detail how the time delay acts over the network during the synchronised and desynchronised neuronal activities. We observe a relation between the neuronal dynamics and the syaptic conductance distributions. We find parameter values in which the time delay has high effectiveness in promoting the suppression of spike synchronisation. In the second part, we analyse how the delayed neuronal networks react when pulsed inputs with different profiles (periodic, random, and mixed) are applied on the neurons. We show the main parameters responsible for inducing or not synchronous neuronal oscillations in delayed networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Synchronization

Simulation of deterministic compartmental models for infectious diseases dynamics

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arXiv 2021年

作者： Batista, Antonio M. De Souza, Silvio L. T. Iarosz, Kelly C. Almeida, Alexandre C. L. Szezech, José D. Gabrick, Enrique C. Mugnaine, Michele Dos Santos, Gefferson L. Caldas, Iberê L. Postgraduate Program in Sciences State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Physics Institute University of São Paulo São PauloSP05508-090 Brazil Federal University of São João del-Rei Campus Centro-Oeste DivinópolisMG Brazil Faculdade de Telêmaco Borba FATEB Telêmaco BorbaPR Brazil Graduate Program in Chemical Engineering Federal Technological University of Paraná Ponta GrossaPR Brazil Statistics Physics and Mathematics Department Federal University of São João del-Rei Ouro BrancoMG Brazil Department of Physics Federal University of Paraná CuritibaPR Brazil

Infectious diseases are caused by pathogenic microorganisms and can spread through different ways. Mathematical models and computational simulation have been used extensively to investigate the transmission and spread of infectious diseases. In other words, mathematical model simulation can be used to analyse the dynamics of infectious diseases, aiming to understand the effects and how to control the spread. In general, these models are based on compartments, where each compartment contains individuals with the same characteristics, such as susceptible, exposed, infected, and recovered. In this paper, we cast further light on some classical epidemic models, reporting possible outcomes from numerical simulation. Furthermore, we provide routines in a repository for simulations. © 2021, CC BY.

关键词： Microorganisms