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1.
Int J Mol Sci ; 22(11)2021 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-34199598

RESUMO

In this work, we use the next sub-volume method (NSM) to investigate the possibility of using the compartment-based ("on-lattice") model to simulate water radiolysis. We, first, start with a brief description of the reaction-diffusion master equation (RDME) in a spatially discretized simulation volume ("mesh"), which is divided into sub-volumes (or "voxels"). We then discuss the choice of voxel size and merging technique of a given mesh, along with the evolution of the system using the hierarchical algorithm for the RDME ("hRDME"). Since the compartment-based model cannot describe high concentration species of early radiation-induced spurs, we propose a combination of the particle-based step-by-step ("SBS") Brownian dynamics model and the compartment-based model ("SBS-RDME model") for the simulation. We, finally, use the particle-based SBS Brownian dynamics model of Geant4-DNA as a reference to test the model implementation through several benchmarks. We find that the compartment-based model can efficiently simulate the system with a large number of species and for longer timescales, beyond the microsecond, with a reasonable computing time. Our aim in developing this model is to study the production and evolution of reactive oxygen species generated under irradiation with different dose rate conditions, such as in FLASH and conventional radiotherapy.


Assuntos
DNA/química , Transferência Linear de Energia , Modelos Moleculares , Água/química , Algoritmos , Simulação por Computador , Difusão , Modelos Químicos , Método de Monte Carlo , Radiólise de Impulso
2.
Int J Mol Sci ; 22(11)2021 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-34199667

RESUMO

Nanoparticles (NPs) with a high atomic number (Z) are promising radiosensitizers for cancer therapy. However, the dependence of their efficacy on irradiation conditions is still unclear. In the present work, 11 different metal and metal oxide NPs (from Cu (ZCu = 29) to Bi2O3 (ZBi = 83)) were studied in terms of their ability to enhance the absorbed dose in combination with 237 X-ray spectra generated at a 30-300 kVp voltage using various filtration systems and anode materials. Among the studied high-Z NP materials, gold was the absolute leader by a dose enhancement factor (DEF; up to 2.51), while HfO2 and Ta2O5 were the most versatile because of the largest high-DEF region in coordinates U (voltage) and Eeff (effective energy). Several impacts of the X-ray spectral composition have been noted, as follows: (1) there are radiation sources that correspond to extremely low DEFs for all of the studied NPs, (2) NPs with a lower Z in some cases can equal or overcome by the DEF value the high-Z NPs, and (3) the change in the X-ray spectrum caused by a beam passing through the matter can significantly affect the DEF. All of these findings indicate the important role of carefully planning radiation exposure in the presence of high-Z NPs.


Assuntos
Cobre/uso terapêutico , Nanopartículas Metálicas/uso terapêutico , Neoplasias/radioterapia , Radiossensibilizantes/uso terapêutico , Bismuto/química , Bismuto/uso terapêutico , Cobre/química , Relação Dose-Resposta a Droga , Humanos , Nanopartículas Metálicas/química , Método de Monte Carlo , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Óxidos/química , Óxidos/uso terapêutico , Radiossensibilizantes/química , Dosagem Radioterapêutica
3.
Sensors (Basel) ; 21(13)2021 Jun 30.
Artigo em Inglês | MEDLINE | ID: mdl-34209114

RESUMO

Time-of-Flight (TOF) based Light Detection and Ranging (LiDAR) is a widespread technique for distance measurements in both single-spot depth ranging and 3D mapping. Single Photon Avalanche Diode (SPAD) detectors provide single-photon sensitivity and allow in-pixel integration of a Time-to-Digital Converter (TDC) to measure the TOF of single-photons. From the repetitive acquisition of photons returning from multiple laser shots, it is possible to accumulate a TOF histogram, so as to identify the laser pulse return from unwelcome ambient light and compute the desired distance information. In order to properly predict the TOF histogram distribution and design each component of the LiDAR system, from SPAD to TDC and histogram processing, we present a detailed statistical modelling of the acquisition chain and we show the perfect matching with Monte Carlo simulations in very different operating conditions and very high background levels. We take into consideration SPAD non-idealities such as hold-off time, afterpulsing, and crosstalk, and we show the heavy pile-up distortion in case of high background. Moreover, we also model non-idealities of timing electronics chain, namely, TDC dead-time, limited number of storage cells for TOF data, and TDC sharing. Eventually, we show how the exploit the modelling to reversely extract the original LiDAR return signal from the distorted measured TOF data in different operating conditions.


Assuntos
Modelos Estatísticos , Fótons , Eletrônica , Luz , Método de Monte Carlo
4.
BMC Plant Biol ; 21(1): 325, 2021 Jul 06.
Artigo em Inglês | MEDLINE | ID: mdl-34229602

RESUMO

BACKGROUND: Plant phylogeographic studies of species in subtropical China have mainly focused on rare and endangered species, whereas few studies have been conducted on taxa with relatively wide distribution, especially polyploid species. We investigated the cytotype and haplotype distribution pattern of the Actinidia chinensis complex, a widespread geographically woody liana with variable ploidy in subtropical China comprising two varieties, with three chloroplast fragments DNA (ndhF-rpl132, rps16-trnQ and trnE-trnT). Macroevolutionary, microevolutionary and niche modeling tools were also combined to disentangle the origin and the demographic history of the species or cytotypes. RESULTS: The ploidy levels of 3338 individuals from 128 populations sampled throughout the species distribution range were estimated with flow cytometry. The widespread cytotypes were diploids followed by tetraploids and hexaploids, whereas triploids and octoploids occurred in a few populations. Thirty-one chloroplast haplotypes were detected. The genetic diversity and genetic structure were found to be high between varieties (or ploidy races) chinensis and deliciosa. Our results revealed that these two varieties inhabit significantly different climatic niche spaces. Ecological niche models (ENMs) indicate that all varieties' ranges contracted during the Last Inter Glacial (LIG), and expanded eastward or northward during the Last Glacial Maximum (LGM). CONCLUSIONS: Pliocene and Plio-Pleistocene climatic fluctuations and vicariance appear to have played key roles in shaping current population structure and historical demography in the A. chinensis complex. The polyploidization process also appears to have played an important role in the historical demography of the complex through improving their adaptability to environmental changes.


Assuntos
Actinidia/classificação , Actinidia/citologia , Cloroplastos/classificação , Filogeografia , Teorema de Bayes , China , DNA de Cloroplastos/genética , Ecossistema , Variação Genética , Genética Populacional , Haplótipos/genética , Método de Monte Carlo , Ploidias
5.
Sensors (Basel) ; 21(13)2021 Jul 04.
Artigo em Inglês | MEDLINE | ID: mdl-34283123

RESUMO

Most indoor environments have wheelchair adaptations or ramps, providing an opportunity for mobile robots to navigate sloped areas avoiding steps. These indoor environments with integrated sloped areas are divided into different levels. The multi-level areas represent a challenge for mobile robot navigation due to the sudden change in reference sensors as visual, inertial, or laser scan instruments. Using multiple cooperative robots is advantageous for mapping and localization since they permit rapid exploration of the environment and provide higher redundancy than using a single robot. This study proposes a multi-robot localization using two robots (leader and follower) to perform a fast and robust environment exploration on multi-level areas. The leader robot is equipped with a 3D LIDAR for 2.5D mapping and a Kinect camera for RGB image acquisition. Using 3D LIDAR, the leader robot obtains information for particle localization, with particles sampled from the walls and obstacle tangents. We employ a convolutional neural network on the RGB images for multi-level area detection. Once the leader robot detects a multi-level area, it generates a path and sends a notification to the follower robot to go into the detected location. The follower robot utilizes a 2D LIDAR to explore the boundaries of the even areas and generate a 2D map using an extension of the iterative closest point. The 2D map is utilized as a re-localization resource in case of failure of the leader robot.


Assuntos
Robótica , Cadeiras de Rodas , Algoritmos , Método de Monte Carlo , Redes Neurais de Computação
6.
Sensors (Basel) ; 21(14)2021 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-34300553

RESUMO

This paper deals with bistatic track association and deghosting in the classical frequency modulation (FM)-based multi-static primary surveillance radar (MSPSR). The main contribution of this paper is a novel algorithm for bistatic track association and deghosting. The proposed algorithm is based on a hierarchical model which uses the Indian buffet process (IBP) as the prior probability distribution for the association matrix. The inference of the association matrix is then performed using the classical reversible jump Markov chain Monte Carlo (RJMCMC) algorithm with the usage of a custom set of the moves proposed by the sampler. A detailed description of the moves together with the underlying theory and the whole model is provided. Using the simulated data, the algorithm is compared with the two alternative ones and the results show the significantly better performance of the proposed algorithm in such a simulated setup. The simulated data are also used for the analysis of the properties of Markov chains produced by the sampler, such as the convergence or the posterior distribution. At the end of the paper, further research on the proposed method is outlined.


Assuntos
Algoritmos , Radar , Teorema de Bayes , Cadeias de Markov , Método de Monte Carlo
7.
Sensors (Basel) ; 21(14)2021 Jul 19.
Artigo em Inglês | MEDLINE | ID: mdl-34300657

RESUMO

Continuous monitoring of blood-glucose concentrations is essential for both diabetic and nondiabetic patients to plan a healthy lifestyle. Noninvasive in vivo blood-glucose measurements help reduce the pain of piercing human fingertips to collect blood. To facilitate noninvasive measurements, this work proposes a Monte Carlo photon simulation-based model to estimate blood-glucose concentration via photoplethysmography (PPG) on the fingertip. A heterogeneous finger model was exposed to light at 660 nm and 940 nm in the reflectance mode of PPG via Monte Carlo photon propagation. The bio-optical properties of the finger model were also deduced to design the photon simulation model for the finger layers. The intensities of the detected photons after simulation with the model were used to estimate the blood-glucose concentrations using a supervised machine-learning model, XGBoost. The XGBoost model was trained with synthetic data obtained from the Monte Carlo simulations and tested with both synthetic and real data (n = 35). For testing with synthetic data, the Pearson correlation coefficient (Pearson's r) of the model was found to be 0.91, and the coefficient of determination (R2) was found to be 0.83. On the other hand, for tests with real data, the Pearson's r of the model was 0.85, and R2 was 0.68. Error grid analysis and Bland-Altman analysis were also performed to confirm the accuracy. The results presented herein provide the necessary steps for noninvasive in vivo blood-glucose concentration estimation.


Assuntos
Fótons , Fotopletismografia , Simulação por Computador , Glucose , Humanos , Método de Monte Carlo
8.
Int J Mol Sci ; 22(13)2021 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-34210098

RESUMO

Muscle energetics reflects the ability of myosin motors to convert chemical energy into mechanical energy. How this process takes place remains one of the most elusive questions in the field. Here, we combined experimental measurements of in vitro sliding velocity based on DNA-origami built filaments carrying myosins with different lever arm length and Monte Carlo simulations based on a model which accounts for three basic components: (i) the geometrical hindrance, (ii) the mechano-sensing mechanism, and (iii) the biased kinetics for stretched or compressed motors. The model simulations showed that the geometrical hindrance due to acto-myosin spatial mismatching and the preferential detachment of compressed motors are synergic in generating the rapid increase in the ATP-ase rate from isometric to moderate velocities of contraction, thus acting as an energy-conservation strategy in muscle contraction. The velocity measurements on a DNA-origami filament that preserves the motors' distribution showed that geometrical hindrance and biased detachment generate a non-zero sliding velocity even without rotation of the myosin lever-arm, which is widely recognized as the basic event in muscle contraction. Because biased detachment is a mechanism for the rectification of thermal fluctuations, in the Brownian-ratchet framework, we predict that it requires a non-negligible amount of energy to preserve the second law of thermodynamics. Taken together, our theoretical and experimental results elucidate less considered components in the chemo-mechanical energy transduction in muscle.


Assuntos
Actomiosina/metabolismo , Adenosina Trifosfatases/metabolismo , Músculos/fisiologia , Animais , Humanos , Cinética , Modelos Biológicos , Método de Monte Carlo , Contração Muscular
9.
Sensors (Basel) ; 21(10)2021 May 12.
Artigo em Inglês | MEDLINE | ID: mdl-34066113

RESUMO

In this work, we propose and analyze a new concept of gamma ray imaging that corresponds to a gamma camera with a mobile collimator, which can be used in vivo, during surgical interventions for oncological patients for localizing regions of interest such as tumors or ganglia. The benefits are a much higher sensitivity, better image quality and, consequently, a dose reduction for the patient and medical staff. This novel approach is a practical solution to the overlapping problem which is inherent to multi-pinhole gamma camera imaging and single photon emission computed tomography and which translates into artifacts and/or image truncation in the final reconstructed image. The key concept consists in introducing a relative motion between the collimator and the detector. Moreover, this design could also be incorporated into most commercially available gamma camera devices, without any excessive additional requirements. We use Monte Carlo simulations to assess the feasibility of such a device, analyze three possible designs and compare their sensitivity, resolution and uniformity. We propose a final design of a gamma camera with a high sensitivity ranging from 0.001 to 0.006 cps/Bq, and a high resolution of 0.5-1.0 cm (FWHM), for source-to-detector distances of 4-10 cm. Additionally, this planar gamma camera provides information about the depth of source (with approximate resolution of 1.5 cm) and excellent image uniformity.


Assuntos
Câmaras gama , Tomografia Computadorizada de Emissão de Fóton Único , Artefatos , Estudos de Viabilidade , Humanos , Método de Monte Carlo , Imagens de Fantasmas
10.
Sensors (Basel) ; 21(10)2021 May 12.
Artigo em Inglês | MEDLINE | ID: mdl-34066224

RESUMO

Portable radiation detectors are widely used in environmental radiation detection and medical imaging due to their portability feature, high detection efficiency, and large field of view. Lutetium-yttrium oxyorthosilicate (LYSO) is a widely used scintillator in gamma radiation detection. However, the structure and the arrangement of scintillators limit the sensitivity and detection accuracy of these radiation detectors. In this study, a novel portable sensor based on a monolithic LYSO ring was developed for the detection of environmental radiation through simulation, followed by construction and assessments. Monte Carlo simulations were utilized to prove the detection of gamma rays at 511 keV by the developed sensor. The simulations data, including energy resolutions, decoding errors, and sensitivity, showed good potential for the detection of gamma rays by the as-obtained sensor. The experimental results using the VA method revealed decoding errors in the energy window width of 50 keV less than 2°. The average error was estimated at 0.67°, a sufficient value for the detection of gamma radiation. In sum, the proposed radiation sensor appears promising for the construction of high-performance radiation detectors and systems.


Assuntos
Lutécio , Ítrio , Raios gama , Método de Monte Carlo , Tomografia por Emissão de Pósitrons
11.
Phys Med ; 86: 98-105, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34082183

RESUMO

PURPOSE: Equipment refurbishment was performed to remove the beam-hardening filter (BHF) from the CyberKnife system (CK). This study aimed to confirm the change in the beam characteristics between the conventional CK (present-BHF CK) and CK after the BHF was removed (absent-BHF CK) and evaluate the impact of BHF removal on the beam quality correction factors kQ. METHODS: The experimental measurements of the beam characteristics of the present- and absent-BHF CKs were compared. The CKs were modeled using Monte Carlo simulations (MCs). The energy fluence spectra were calculated using MCs. Finally, kQ were estimated by combining the MC results and analytic calculations based on the TRS-398 and TRS-483 approaches. RESULTS: All gamma values for percent depth doses and beam profiles between each CK were less than 0.5 following the 3%/1 mm criteria. The percentage differences for tissue-phantom ratios at depths of 20 and 10 cm and percentage depth doses at 10 cm between each CK were -1.20% and -0.97%, respectively. The MC results demonstrated that the photon energy fluence spectrum of the absent-BHF CK was softer than that of the present-BHF CK. The kQ values for the absent-BHF CK were in agreement within 0.02% with those for the present-BHF CK. CONCLUSIONS: The photon energy fluence spectrum was softened by the removal of BHF. However, no remarkable impact was observed for the measured beam characteristics and kQ. Therefore, the previous findings of the kQ values for the present-BHF CK can be directly used for the absent-BHF CK.


Assuntos
Algoritmos , Planejamento da Radioterapia Assistida por Computador , Método de Monte Carlo , Fótons , Radiometria
12.
Int J Mol Sci ; 22(9)2021 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-34062825

RESUMO

With the distinguished properties in electronics, thermal conductivity, optical transparence and mechanics, graphene has a powerful potential in nanosensors, nano-resonators, supercapacitors, batteries, etc. The resonant frequency of graphene is an important factor in its application and working environment. However, the random dispersed porosities in graphene evidently change the lattice structure and destroy the integrity and geometrical periodicity. This paper focuses on the effects of random porosities in resonant frequencies of graphene. Monte Carlo simulation is applied to propagate the porosities in the finite element model of pristine graphene. The statistical results and probability density distribution of porous graphene with atomic vacancy defects are computed based on the Monte Carlo finite element model. The results of porous graphene with atomic vacancy defects are compared and discussed with the results of graphene with bond vacancy defects. The enhancement effects of atomic vacancy defects are confirmed in porous graphene. The influences of atomic vacancy defects on displacement and rotation vector sums of porous graphene are more concentrated in local places.


Assuntos
Análise de Elementos Finitos , Grafite/química , Método de Monte Carlo , Simulação por Computador , Porosidade , Condutividade Térmica
13.
Nat Commun ; 12(1): 3927, 2021 06 24.
Artigo em Inglês | MEDLINE | ID: mdl-34168142

RESUMO

Quantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol-1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.


Assuntos
Modelos Químicos , Benchmarking , Benzeno/química , Bases de Dados de Compostos Químicos , Difusão , Ligação de Hidrogênio , Método de Monte Carlo , Piridinas/química , Teoria Quântica , Eletricidade Estática , Uracila/química , Água/química
14.
J Occup Environ Hyg ; 18(7): 345-360, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-34129448

RESUMO

First responders may have high SARS-CoV-2 infection risks due to working with potentially infected patients in enclosed spaces. The study objective was to estimate infection risks per transport for first responders and quantify how first responder use of N95 respirators and patient use of cloth masks can reduce these risks. A model was developed for two Scenarios: an ambulance transport with a patient actively emitting a virus in small aerosols that could lead to airborne transmission (Scenario 1) and a subsequent transport with the same respirator or mask use conditions, an uninfected patient; and remaining airborne SARS-CoV-2 and contaminated surfaces due to aerosol deposition from the previous transport (Scenario 2). A compartmental Monte Carlo simulation model was used to estimate the dispersion and deposition of SARS-CoV-2 and subsequent infection risks for first responders, accounting for variability and uncertainty in input parameters (i.e., transport duration, transfer efficiencies, SARS-CoV-2 emission rates from infected patients, etc.). Infection risk distributions and changes in concentration on hands and surfaces over time were estimated across sub-Scenarios of first responder respirator use and patient cloth mask use. For Scenario 1, predicted mean infection risks were reduced by 69%, 48%, and 85% from a baseline risk (no respirators or face masks used) of 2.9 × 10-2 ± 3.4 × 10-2 when simulated first responders wore respirators, the patient wore a cloth mask, and when first responders and the patient wore respirators or a cloth mask, respectively. For Scenario 2, infection risk reductions for these same Scenarios were 69%, 50%, and 85%, respectively (baseline risk of 7.2 × 10-3 ± 1.0 × 10-2). While aerosol transmission routes contributed more to viral dose in Scenario 1, our simulations demonstrate the ability of face masks worn by patients to additionally reduce surface transmission by reducing viral deposition on surfaces. Based on these simulations, we recommend the patient wear a face mask and first responders wear respirators, when possible, and disinfection should prioritize high use equipment.


Assuntos
COVID-19/transmissão , Transmissão de Doença Infecciosa do Paciente para o Profissional/prevenção & controle , Máscaras/virologia , Respiradores N95/virologia , SARS-CoV-2 , Aerossóis , Microbiologia do Ar , Ambulâncias , COVID-19/prevenção & controle , Simulação por Computador , Socorristas , Contaminação de Equipamentos , Humanos , Método de Monte Carlo , Dispositivos de Proteção Respiratória/virologia , Comportamento de Redução do Risco , Transporte de Pacientes
15.
Phys Med ; 87: 1-10, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34091196

RESUMO

PURPOSE: This study aims to use GATE/Geant4 simulation code to evaluate the performance of dose calculations with Anisotropic Analytical Algorithm (AAA) in the context of lung SBRT for complex treatments considering images of patients. METHODS: Four cases of non-small cell lung cancer treated with SBRT were selected for this study. Irradiation plans were created with AAA and recalculated end to end using Monte Carlo (MC) method maintaining field configurations identical to the original plans. Each treatment plan was evaluated in terms of PTV and organs at risk (OARs) using dose-volume histograms (DVH). Dosimetric parameters obtained from DVHs were used to compare AAA and MC. RESULTS: The comparison between the AAA and MC DVH using gamma analysis with the passing criteria of 3%/3% showed an average passing rate of more than 90% for the PTV structure and 97% for the OARs. Tightening the criteria to 2%/2% showed a reduction in the average passing rate of the PTV to 86%. The agreement between the AAA and MC dose calculations for PTV dosimetric parameters (V100; V90; Homogeneity index; maximum, minimum and mean dose; CIPaddick and D2cm) was within 18.4%. For OARs, the biggest differences were observed in the spinal cord and the great vessels. CONCLUSIONS: In general, we did not find significant differences between AAA and MC. The results indicate that AAA could be used in complex SBRT cases that involve a larger number of small treatment fields in the presence of tissue heterogeneities.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Radiocirurgia , Algoritmos , Humanos , Pulmão , Neoplasias Pulmonares/cirurgia , Método de Monte Carlo , Dosagem Radioterapêutica , Planejamento da Radioterapia Assistida por Computador
16.
Phys Med ; 87: 73-82, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34120071

RESUMO

PURPOSE: In modulated radiotherapy, breathing motion can lead to Interplay (IE) and Blurring (BE) effects that can modify the delivered dose. The aim of this work is to present the implementation, the validation and the use of an open-source Monte-Carlo (MC) model that computes the delivered dose including these motion effects. METHODS: The MC model of the Varian TrueBeam was implemented using GATE. The dose delivered by different modulated plans is computed for several breathing patterns. A validation of these MC predictions is achieved by a comparison with measurements performed using a dedicated programmable motion platform, carrying a quality assurance phantom. A specific methodology was used to separate the IE and the BE. The influence of different motion parameters (period, amplitude, shape) and plan parameters (volume margin, dose per fraction) was also analyzed. RESULTS: The MC model was validated against measurement performed with motion with a mean 3D global gamma index pass rate of 97.5% (3%/3 mm). A significant correlation is found between the IE and the period and the antero-posterior amplitude of the motion but not between the IE and the CTV margin or the shape of motion. The results showed that the IE increases D2% and decreases the D98% of CTV with mean values of +6.9% and -3.3% respectively. CONCLUSIONS: We validated the feasibility to assess the IE using a MC model. We found that the most important parameter is the number of breathing cycles that must be greater than 20 for one arc to limit the IE.


Assuntos
Planejamento da Radioterapia Assistida por Computador , Radioterapia de Intensidade Modulada , Método de Monte Carlo , Imagens de Fantasmas , Dosagem Radioterapêutica
17.
Sci Rep ; 11(1): 11606, 2021 06 02.
Artigo em Inglês | MEDLINE | ID: mdl-34078929

RESUMO

The devastating trail of Covid-19 is characterized by one of the highest mortality-to-infected ratio for a pandemic. Restricted therapeutic and early-stage vaccination still renders social exclusion through lockdown as the key containment mode.To understand the dynamics, we propose PHIRVD, a mechanistic infection propagation model that Machine Learns (Bayesian Markov Chain Monte Carlo) the evolution of six infection stages, namely healthy susceptible (H), predisposed comorbid susceptible (P), infected (I), recovered (R), herd immunized (V) and mortality (D), providing a highly reliable mortality prediction profile for 18 countries at varying stages of lockdown. Training data between 10 February to 29 June 2020, PHIRVD can accurately predict mortality profile up to November 2020, including the second wave kinetics. The model also suggests mortality-to-infection ratio as a more dynamic pandemic descriptor, substituting reproduction number. PHIRVD establishes the importance of early and prolonged but strategic lockdown to contain future relapse, complementing futuristic vaccine impact.


Assuntos
COVID-19/epidemiologia , COVID-19/prevenção & controle , Número Básico de Reprodução , Teorema de Bayes , COVID-19/etiologia , Controle de Doenças Transmissíveis/métodos , Comorbidade , Suscetibilidade a Doenças , Humanos , Imunidade Coletiva , Índia/epidemiologia , Cinética , Aprendizado de Máquina , Cadeias de Markov , Modelos Teóricos , Método de Monte Carlo , Mortalidade , Reino Unido/epidemiologia
18.
Phys Rev Lett ; 126(17): 174301, 2021 Apr 30.
Artigo em Inglês | MEDLINE | ID: mdl-33988414

RESUMO

Echo location is a broad approach to imaging and sensing that includes both manmade RADAR, LIDAR, SONAR, and also animal navigation. However, full 3D information based on echo location requires some form of scanning of the scene in order to provide the spatial location of the echo origin-points. Without this spatial information, imaging objects in three-dimensional (3D) is a very challenging task as the inverse retrieval problem is strongly ill-posed. Here, we show that the temporal information encoded in the return echoes that are reflected multiple times within a scene is sufficient to faithfully render an image in 3D. Numerical modeling and an information theoretic perspective prove the concept and provide insight into the role of the multipath information. We experimentally demonstrate the concept by using both radio frequency and acoustic waves for imaging individuals moving in a closed environment.


Assuntos
Ecolocação , Imageamento Tridimensional/métodos , Modelos Teóricos , Animais , Simulação por Computador , Humanos , Método de Monte Carlo
19.
BMC Infect Dis ; 21(1): 476, 2021 May 25.
Artigo em Inglês | MEDLINE | ID: mdl-34034662

RESUMO

BACKGROUND: The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. METHODS: By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. RESULTS: We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. CONCLUSIONS: We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.


Assuntos
COVID-19/epidemiologia , Controle de Doenças Transmissíveis/métodos , Surtos de Doenças/estatística & dados numéricos , Modelos Teóricos , SARS-CoV-2 , COVID-19/transmissão , China/epidemiologia , Controle de Doenças Transmissíveis/organização & administração , Humanos , Cadeias de Markov , Método de Monte Carlo
20.
J Hazard Mater ; 413: 125465, 2021 07 05.
Artigo em Inglês | MEDLINE | ID: mdl-33930974

RESUMO

Cadmium (Cd) is a toxic heavy metal widely present in the environment. Estimating its internal levels for a given external exposure using toxicokinetic (TK) models is key to the human health risk assessment of Cd. In this study, existing Cd TK models were adapted to develop a one-compartment TK model and a multi-compartment physiologically based toxicokinetic (PBTK) model by estimating the characteristics of Cd kinetics based on Cd exposure data from 814 Chinese residents. Both models not only considered the effect of gender difference on Cd kinetics, but also described the model parameters in terms of distributions to reflect individual variability. For both models, the posterior distributions of sensitive parameters were estimated using the Markov chain-Monte Carlo method (MCMC) and the approximate Bayesian computation-MCMC algorithm (ABC-MCMC). Validation with the test dataset showed 1.4-22.5% improvement in the root mean square error (RMSE) over the original models. After a systematic literature search, the optimized models showed acceptable prediction on other Chinese datasets. The study provides a method for parameter optimization of TK models under different exposure environment, and the validated models can serve as new quantitative assessment tools for the risk assessment of Cd in the Chinese population.


Assuntos
Cádmio , Teorema de Bayes , Cádmio/toxicidade , China , Humanos , Cadeias de Markov , Método de Monte Carlo , Toxicocinética
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