Estimated Research Articles

Online interventions for the mental health and well-being of parents of children with additional needs: Systematic review and meta-analysis.

Parents of children with additional needs experience compromised physical and mental health and higher stress, and their ability to engage in meaningful occupations is impacted by their additional caregiving tasks. Online interventions targeting mental health, stress, and well-being for parents of children with additional needs have potential to increase supports alongside occupational therapy direct services. The aims of this review are to systematically identify and synthesise evidence of effectiveness of online interventions aimed at improving mental health, stress, and well-being of parents of children with additional needs. Eight databases were searched up to July 2024 to identify online interventions for parents of children with additional needs. Studies were appraised for methodological quality. Standardised effect sizes were calculated, and meta-analyses of randomised control trials (RCTs) were conducted on outcomes of mental health, well-being, and stress. There was no consumer or community involvement. Systematic screening identified 30 papers that met inclusion criteria. Most were RCTs or controlled clinical trials (CCTs) with 'moderate' quality ratings: Three were designed by occupational therapists. There was substantial variation in intervention types, methods of delivery, outcomes, and outcome measures used. The pooled standardised effect size estimates (ES) and the lower and upper confidence intervals (CI) of online interventions from RCTs post-interventions were significant for mental health ES = 0.47, 95% CI (0.18, 0.77), p = 0.002; stress ES = 1.27, 95% CI (0.56, 1.98), p = 0.000; and well-being ES = 0.65, 95% CI (1.2, 0.06), p = 0.03, respectively. The online interventions that aimed to improve mental health, stress, and well-being included in this meta-analysis were effective. Occupational therapists supporting families play an important role in guiding parents of children with additional needs to evidence-based interventions to support them with addressing their own mental health and well-being needs.

Ki-67 Testing in Breast Cancer: Assessing Variability With Scoring Methods and Specimen Types and the Potential Subsequent Impact on Therapy Eligibility.

Abemaciclib was originally FDA approved for patients with ER-positive/HER2-negative breast cancer with Ki-67 expression ≥20%. However, there were no guidelines provided on which specimen to test or which scoring method to use. We performed a comprehensive study evaluating the variation in Ki-67 expression in breast specimens from 50 consecutive patients who could have been eligible for abemaciclib therapy. Three pathologists with breast expertise each performed a blinded review with 3 different manual scoring methods [estimated (EST), unweighted (UNW), and weighted (WT) (WT recommended by the International Ki-67 in Breast Cancer Working Group)]. Quantitative image analysis (QIA) using the HALO platform was also performed. Three different specimen types [core needle biopsy (CNB) (n=63), resection (RES) (n=52), and axillary lymph node metastasis (ALN) (n=50)] were evaluated for each patient. The average Ki-67 for all specimens was 14.68% for EST, 14.46% for UNW, 14.15% for WT, and 11.15% for QIA. For the manual methods, the range between the lowest and highest Ki-67 for each specimen between the 3 pathologists was 8.44 for EST, 5.94 for WT, and 5.93 for UNW. The WT method limited interobserver variability with ICC1=0.959 (EST ICC1=0.922 and UNW=0.949). Using the aforementioned cutoff of Ki-67 ≥20% versus <20% to determine treatment eligibility, the averaged EST method yields 20 of 50 patients (40%) who would have been treatment-eligible, versus 15 (30%) for the UNW, 17 (34%) for the WT, and 12 (24%) for the QIA. There was no statistically significant difference in Ki-67 among the 3 specimen types. The average Ki-67 difference was 4.36 for CNB vs RES, 6.95 for CNB versus ALN, and RES versus ALN (P=0.93, 0.99, and 0.94, respectively). Our study concludes that further refinement in Ki-67 scoring is advisable to reduce clinically significant variation.

Second-based queue length estimation with fusing MMW and low penetration rate CAV trajectory data

This paper combines millimeter-wave radar (MMW) data with connected autonomous vehicle (CAV) trajectory data to estimate queue length on a second-by-second basis. Firstly, queued vehicles on multiple lanes with the same traffic movement are mapped to a virtual lane. Then, the presence of CAV or human-driven vehicle (HDV) for any given queueing index is determined. A Bayesian joint probability model is subsequently established for queue length expectation, considering the existence of the queued vehicle type as a condition. The average time headway and dissipation speed distribution are derived from departure timestamps, which allows for the calculation of the prior probability ratio of queue length. Lastly, the maximum likelihood estimation (EM) algorithm is employed for iteratively estimating the CAV penetration rate. Simulation results demonstrate the method offers a compelling trade-off between precision and second-based real-time performance, while field test results further confirm the wide applicability under various traffic conditions.

Kvaal’s dental age estimation method applied to Brazilian adults—a cross-sectional test of validity

BackgroundDental age estimation of adults is a challenging procedure in forensic odontology. Radiographic techniques have enabled non-invasive age estimation of adults since the 90’s. Kvaal’s method based on the deposition of secondary dentin has demonstrated broad applicability in several populations. Population-specific studies with this method, however, are scarce in South America. This study tested the validity of Kvaal’s method in a sample of radiographs of Brazilian adults. The sample consisted of 192 periapical radiographs of 106 females (55.2%) and 86 males (44.8%) with ages between 20 and 80 years old. The permanent maxillary right (n = 84, 43.8%) and left (n = 108, 56.2%) central incisors were assessed based on Kvaal’s method.ResultsLin’s coefficient of concordance between estimated (EA) and chronological (CA) ages was 0.800 (IC95% = 0.753; 0.847) (p < 0.001). The mean difference between EA and CA was − 2.84 years (p < 0.001). For females and males, separately, the mean differences between EA and CA were − 3.82 years (CI95% = − 5.38; − 2.25) (p < 0.001) and − 1.86 years (CI95% = − 3.56; − 0.17) (p = 0.031), respectively. Underestimations were predominant and increased with time.ConclusionAfter 28 years of the original publication, Kvaal’s method remains reliable for non-invasive dental age estimation of adults, especially for the analysis of the permanent maxillary central incisors of Brazilian individuals.

Analytical Variability of Hematological Methods for White Blood Cell Counts in Prairie Rattlesnakes (Crotalus viridis)

Abstract Evaluating leukocytes provides insight in the overall health of animals by characterizing pathologies related to infection, inflammation, and stress. In reptile species, many leukocyte quantification methods are used to evaluate white blood cell parameters; however, agreement and analytical variability between the various methods have yet to be reported and critically assessed in many species, including the prairie rattlesnake (Crotalus viridis). The objectives of this study were 1) to test agreement between hematology parameters determined by phloxine -based stain (EO), Natt &amp; Herricks (NH), and estimate (EST) methods using fresh whole blood and lithium-heparinized blood, 2) to determine the agreement between estimates from a veterinary student and from a board-certified clinical pathologist; and, 3) to determine the analytical variability of EO, NH, and EST methods. Venipuncture was performed in 27 adult snakes and agreement was then assessed using Bland-Altman plots and Passing-Bablock regression between all methods. There was a variable degree of proportional and constant error between many of the quantification methods, but descriptive statistics for all methods fell within biologically relevant values. There was good agreement in EST between the clinical pathologist and veterinary student, but the student had a significantly higher mean WBC in fresh whole blood. The lowest analytical variability was observed with NH method (15.4%), while the highest was observed with the EST (58.6% for clinical pathologist, 59.4% for veterinary student). These results identify the intrinsic variability in reptile hematological methods currently used and emphasize the need to develop a singular diagnostic standard for leukocyte quantification in reptile species.

Tire and Engine Sources Contribution to Vehicle Interior Noise and Vibration Exposure Levels

The main objective of the research presented in this paper is to enhance driver-passengers comfort of a vehicle that in turn leads to better vehicle safety and stability. The focus was put on studying the interior vibration and noise contributions originated from tire-road and engine-transmission subsystems, due to their significant impact on the dynamic performance of the vehicle. The noise and vibration measurements were recorded at the driver’s head position and on the driver legs room. Furthermore, the influence of different tire types and road surface textures on the vehicle interior noise and vibration were considered. The results indicate that the widely used conventional engine mounts and tires in commercial vehicles cannot fulfill the conflicting requirements for the best isolation concerning both road surface and engine-transmission induced excitations. The values of driver’s head position sound pressure level and floor vibration acceleration broadband averages originate for engine-transmission are lower than that for tire-road interaction. Furthermore, the values of RMS, crest factor, kurtosis and IRI for the vehicle waveform were estimated for vehicle speeds, tire types and road surface textures. Moreover, the percentage contribution for both interior noise and vibration originated from tire-road interaction is higher than the one from vehicle engine-transmission system in all the vehicle speed range, tire type and road surface texture considered.

Family characteristics and income: Evidence from Indonesia

&lt;div data-canvas-width="597.4487772549016"&gt;Balance in the form of linkages between socioeconomic aspects of a region is the key to economic stability. This economic stability is essential to achieve community welfare, so existing interventions must be considered considering that a slight change in one aspect will affect the economic balance. With the achievement of community welfare, the economic development of a region can be said to be good, which also has implications for handling existing socioeconomic problems. However, the misalignment of education level, gender, internet access, and marital status of each district/city area triggers differences in income levels. Therefore, through this study, it is expected to be able to answer whether factors such as education level, gender, internet access, and marital status are factors that influence the magnitude of income levels, especially in DIY Provinces. By using IFLS-5 data processed through an estimat ion method using logistic regression, test results were obtained that gender and internet access factors significantly affected the amount of people's income. In contrast, the level of education and marital status did not significantly affect the income of people in DIY Province&lt;/div&gt;

Variant ADRC design paradigm for controlling uncertain dynamical systems

This article discusses a novel design paradigm for controllers based on the active disturbance rejection methodology. The current approach focuses on the linear version, known as LADRC, for application in the control problems of uncertain nonlinear systems. The choice of such a method is due to its well-known properties of robustness against parametric uncertainties, external disturbances, and unmodeled dynamics of the system. Some variants of the LADRC method have already been reported in the literature. The common feature verified in all of them is using a parameterized state-feedback control law fed by an extended state estimator (ESO), which is responsible for estimating the state variables and non-measurable signals of the plant. The ADRC paradigm proposed in this work consists of modifying the structure of the ESO by defining the input signal as an additional plant state variable. The key idea of adopting such a modification is to force the desired control law to be generated directly from an ESO estimate. The stability and convergence properties of the resulting closed-loop system are discussed and numerical simulations and experimental results illustrate the controller’s performance.

Models, Algorithms and Applications of DynasTIM Real-Time Traffic Simulation System

Intelligent Transportation Systems (ITS) have the potential to improve traffic conditions and reduce travel delays. As a decision support software system for ITS, DynasTIM is based on the principle of dynamic traffic assignment and developed for real-time online simulation, prediction and optimization of dynamic traffic flows in urban or expressway networks. This paper introduces the models, algorithms and some typical applications of DynasTIM. The main contents include: the functional architecture; the application architecture of the system; dynamic OD (Origin-Destination) flows estimation method with novel formula for assignment matrix computation; mesoscopic traffic model using variable-length speed influence region and calibrating speed online based on connected vehicles data; and parallel SPSA algorithm based urban area signal optimization method. The functions of DynasTIM are implemented basically through three main modules: state estimation (ES), state prediction and control strategy optimization (PS&amp;CSO), and guidance strategy optimization (GSO). The case study is aimed at the populated Futian Central Business District (CBD) road network in Shenzhen, China, which has an area of about 7 square kilometers. Based on the archived turning counts collected from 359 video traffic detection locations, DynasTIM was calibrated offline for this network, in order to validate the capability of simulating actual traffic conditions, and to set up basic conditions for testing signal optimization methods. The results show that the simulation output flows of DynasTIM have fairly good matching accuracy with the real surveillance flows in the field. Furthermore, for the CBD network with 38 signalized intersections, the signal optimization method is evaluated and better signal timing plans are found which can reduce about 13% average travel delay, compared with the signal plans currently implemented in the field.

A large sample-sized study on dental development of children treated at the Central Dental Clinic (OCEx) of the Brazilian Army.

To test and compare the performance of two radiographic methods for dental age estimation on a large sample of Brazilian boys and girls. The sample consisted of 1.990 panoramic radiographs of Brazilian children (age: 3-15.9years) equally balanced based on sex. The sample was distributed into ten age categories, each with up to 200 children. Age estimation was performed with Willems' (2001) and Demirjian's (1973) methods. Estimated (EA) and chronological (CA) ages were compared. The performances of the methods were quantified based on sex and age category. The overall differences between CA and EA for Willems' method in boys and girls were 0.06 and - 0.02, respectively. For Demirjian's method, the differences were 0.60 and 0.74, respectively. The overestimations of Demirjian's method were statistically significant (p < 0.001). Willems' method reached the best outcomes among children between 3 and 12years, while Demirjian's best performances were between the ages of 7 and 10years. Willems' method led to differences between CA and AE that were acceptable for clinical and forensic practice. Age estimation may guide clinical decisions based on treatment timing. Validating international tools is necessary to promote evidence-based practice and country-specific application. This study overcame the limitations of previous research to provide a more realistic perspective of the performance of age estimation methods in Brazilian children. Willems' method had a superior performance compared to Demirjian's method and led to outcomes that were better than most studies with the Brazilian population.

Bias in regression coefficient estimates when assumptions for handling missing data are violated: a simulation study

&#x0D; Background&#x0D; The purpose of this simulation study is to assess the performance of multiple imputation compared to complete case analysis when assumptions of missing data mechanisms are violated.&#x0D; Methods&#x0D; The authors performed a stochastic simulation study to assess the performance of Complete Case (CC) analysis and Multiple Imputation (MI) with different missing data mechanisms (missing completely at random (MCAR), at random (MAR), and not at random (MNAR)). The study focused on the point estimation of regression coefficients and standard errors.&#x0D; Results&#x0D; When data were MAR conditional on Y, CC analysis resulted in biased regression coefficients; they were all underestimated in our scenarios. In these scenarios, analysis after MI gave correct estimates. Yet, in case of MNAR MI yielded biased regression coefficients, while CC analysis performed well.Conclusion&#x0D; The authors demonstrated that MI was only superior to CC analysis in case of MCAR or MAR. In some scenarios CC may be superior over MI. Often it is not feasible to identify the reason why data in a given dataset are missing. Therefore, emphasis should be put on reporting the extent of missing values, the method used to address them, and the assumptions that were made about the mechanism that caused missing data.

Market Potential for Quality Certified Dried Fish: A Consumer Choice Experiment in the Galle District of Sri Lanka

The Dried fish is the most common processed fish consumed in Sri Lanka. The country imports dried fish since local production only satisfie s 61% of the demand. Local producers face marketing challenges because of the low price they receive. This may cause by non-compliance with product quality standards. However, there is a lack of empirical information on consumer behavior for dried fish. Therefore, the study focused on estima ting consumers’ willingness to pay for the key features considered when purchasing dried fish and determining their preference. The study was a consumer survey comprisin g 180 households, divided 60 households into each of the urban, rural, and estate sectors in Galle District, including a choice experiment. The results indicate that the average weekly consumpti on of dried fish per capita in Galle is 115.2 g, with no significant difference between sectors (p&gt;0.05). Sprat is the most prefe rred species in all sectors, followed by Yellow fintuna in urban and rural areas and Bigeye scads in estates. Smell and appearance are the key organoleptic features that the consumers considered while over 50% preferred dried fish with a fresh and well-dried appearance. The results of the Choice experiment showed that the consumers preferred locally produced, sun-dried, quality-certified dried fish. Urban and rural consumers are willing to pay an extra amount of SLR 374.21 and 325.89 respectively for 100 g of quality certified dried fish compared to non-certified. Therefore, the study recommends that producers should encourage to obtain quality certifications by providing financial, educational, and technological support.

Static-Errorless Rotor Position Estimation Method Based on Linear Extended State Observer for IPMSM Sensorless Drives

This article presents a static-errorless rotor position estimation method based on the linear extended state observer (LESO) for interior permanent magnet synchronous motor (IPMSM) drives. Two second-order LESOs are utilized to estimate the α-β axis back-EMFs. A third-order LESO is incorporated into the quadrature phase-locked loop (QPLL) to achieve a high robustness of position tracking against external disturbance. In addition, considering that the nonideal back-EMF will bring DC and harmonic fluctuation errors to the estimated position, an enhanced LESO-based QPLL with static-errorless rotor position estimation is proposed. On the one hand, the DC position esti mation error caused by the phase lag of the back-EMF estimator is analyzed and compensated. On the other hand, to suppress the position harmonic fluctuations induced from the nonsinusoidal back-EMFs, a second-order generalize integrator (SOGI) is embedded in the feedforward path of the LESO-based QPLL. The experimental results on the 1.0 kW IPMSM drive platform show that, compared to the conventional method, the proposed method can achieve better position estimation performance both in steady-state operation and in transient-state operation.

Application of the London Atlas Software App 2nd edition for the radiographic assessment of dental development.

Assessing the dental development of children and adolescents is an important part of treatment planning. The radiographic visualization of dental developmental stages prior to age estimation is currently feasible by means of digital software apps. Testing the existing software tools is necessary to safeguard application in practice. This study applied the London Atlas Software App 2nd edition™ for dental age estimation in Brazilian children. The software was applied to 1.104 digital panoramic radiographs of females (n = 509) and males (n = 595) with ages between 6 and 15.99 years (mean = 10.88 ± 2.84 years). The sample included at least 100 individuals similarly distributed based on sex within 10 age categories of one year each (6├ 15.99) years. Metrics of errors were quantified between the estimated (EA) and chronological (CA) ages. The mean absolute errors among females and males were 0.56 and 0.60 years, respectively (overall = 0.58 years for the combined sample). The lower error values were observed in the age interval of 6 ├ 9.99 years. Error values above one year were detected in older age intervals (10 ├ 15.99 years). Statistically significant differences in dental development were not observed between females and males (p> 0.05). The London Atlas Software App 2nd edition led to specific error rates that can be acceptable for case-specific clinical applications. In the forensic field, caution is advised if the application is planned in the transition between late childhood and early adolescence - when third molars play a major role among the scarce developing teeth. Key words:Brazil, children, dental age estimation, forensic dentistry, radiology.

Semi-Nonparametric Generalized Autoregressive Conditional Heteroscedasticity Model with Application to Bitcoin Volatility Estimation

This study raises the problem of modeling conditional volatility under the random shocks’ normality assumption violation. To obtain more accurate esti ma tes of GARCH process parameters and conditional volatilities, we propose two semi-nonparametric GARCH models. The implementation of the proposed methods is based on an adaptation of the [Gallant, Nychka, 1987] semi-nonparametric method to the family of GARCH models. The approach provides a flexible estimation procedure by approximating the unknown density of random shocks both using po­lynomials (PGN-GARCH) and splines (SPL-GARCH). To study the properties of the obtained estimators and compare them with alternatives, we conducted an ana­lysis of simulated data considering forms of distributions other than normal. As a result, statistical evidence was found in favor of the significant advantage of the proposed methods over the classical GARCH model and some other counterparts introduced earlier in the literature. Further, the proposed PGN-GARCH and SPL-GARCH models were applied to study Bitcoin conditional volatility dynamics. Du­ring the analysis, we found statistical evidence that Bitcoin distribution of shocks in returns differs from normal. Probably due to this reason the proposed SPL-GARCH model was able to demonstrate an advantage over alternative GARCH models according to the information criteria.

Adaptive Robust Least-Squares Smoothing Algorithm

The Kalman smoothing algorithm is widely use d in offline data processing in GNSS to improve filter calcu lation accuracy. When there are measurement outliers or b iased random models, the adaptive Kalman smoothing algo rithm can reduce their impact on the smoothing results to a certain extent. Nevertheless, the adaptive Kalman smoothi ng algorithm usually has difficulty obtaining optimal estim ation in a complex observation environment due to the inhe rent defects of the algorithm itself. Therefore, we propose a n adaptive robust least-squares smoothing algorithm. The row and column transformation of the least-square smooth noise covariance matrix is realized by constructing an orth ogonal space transformation matrix, and the noise covaria nce estimation problem of the Kalman filter is transformed into the problem of solving the variance covariance compo nent elements under a specific matrix structure. In additio n, by selecting the observation value with the largest stand ardized residual to determine whether it is gross error, we avoid the gross error misjudgment problem caused by the t wo-factor robust estimation method under least-square sm oothing, and further improve the smoothing accuracy. Fina lly, two experiments are studied to compare the performan ce of the new algorithm and the state-of-the-art algorithms. The proposed algorithm has demonstrated better perform ance in terms of robustness and estimation accuracy.

Machine learning algorithms for soybean yield forecasting in the Brazilian Cerrado

We evaluated different machine learning (ML) models for predicting soybean productivity up to 1 month in advance for the Matopiba agricultural frontier (States of Maranhão, Tocantins, Piauí, and Bahia). We collected meteorological data on the NASA-POWER platform and soybean yield on the SIDRA/IBGE base between 2008 and 2017. The ML models evaluated were random forest (RF), artificial neural networks, radial base support vector machines (SVM_RBF), linear model and polynomial regression. To assess the performance of the models, cross-validation was used, obtaining the value of precision by R2 , accuracy by root mean square error (RMSE), and trend by the mean error of the estimate (EME). The results showed that the RF algorithm achieves the highest precision and accuracy, with R2 of 0.81, RMSE of 176.93 kg ha-1 and trend (EME) of 1.99 kg ha-1 . On the other hand, the SVM_RBF algorithm showed the lowest performance, with R2 of 0.74, RMSE of 213.58 kg ha-1 and EME of -15.06 kg ha-1 . The average yield values predicted by the models were within the expected range for the region, which has a historical average value of 2.730 kg ha-1 . All models had acceptable precision, accuracy and trend indices, which makes it possible to use all algorithms to be applied in the prediction of soybean crop yield, observing the particularities of the region to be studied, in addition to being a useful tool for agricultural planning and decision making in soy-producing regions such as the Brazilian Cerrado. © 2021 Society of Chemical Industry.

Induction and maintenance of remission with mycophenolate mofetil in ANCA-associated vasculitis: a systematic review and meta-analysis.

Uncertainties exist about the use of mycophenolate mofetil (MMF) in anti-neutrophil cytoplasmatic antibody (ANCA)-associated vasculitis (AAV), particularly for remission maintenance. Systematic review and meta-analysis of phase II and III trials assessing the use of MMF in AAV, granulomatosis with polyangiitis and microscopic polyangiitis (MPA). A comprehensive search of several databases (Medline, EMBASE, Cochrane, Web of Science, Scopus) from inception to 5 May 2020 has been conducted. Trial data were extracted to estimate odds ratios (ORs) and estimates (ES) for MMF efficacy (remission-induction and maintenance). Severe adverse effects (SAEs) were collected. From 565 articles captured, 10 met the predefined criteria, 5 phase II and 5 III trials; 4 assessed remission-induction, 3 remission maintenance and 3 both. The pooled OR for remission-induction at 6 months was 1.06 (95% confidence interval 0.74, 1.52), with no significant difference by subgroup meta-analysis of trials stratified by different study-level features (i.e. kidney disease, MPA, myeloperoxidase-ANCA positivity, newly diagnosed disease) (P&gt;0.05). The overall ES for remission maintenance at the end of follow-up ranged between 51% and 91% (I2=74.8%). Subgroup meta-analysis identified kidney involvement as a possible source of heterogeneity, yielding a significantly higher rate of sustained remission in trials enrolling only patients with kidney involvement (92%, 76-100%) versus those enrolling patients with and without kidney involvement (56%, 45-66%). Results were similar in multiple sensitivity analyses. During follow-up, the frequency of SAEs in MMF-based treatment arms was 31.8%. In AAV, MMF use was significantly associated with higher sustained remission rates in trials enrolling only patients with kidney involvement. These findings might influence clinical practice.

Het Atlantis van de Middelnederlandse ridderepiek : Een schatting van het tekstverlies met methodes uit de ecodiversiteit

It is well known that the study of historical literature is impeded by the incom- plete transmission of sources: due to a century-long loss of sources, inevitably, a large number of texts is no longer known to us. As such, our current perspective on the literary diversity of the past is probably underestimating the actual wealth of texts that once existed. Statistical methods from eco-diversity can assist us in adjusting this esti- mate in a quantitative and precise manner. Applied to Middle Dutch chivalric epics, these methods suggest that prior estimates of text loss may be too conservative: the methods estimate that up to half of the original texts have been lost (and possibly many more).

Effect of wind velocity and flare height parameters on pollution dispersion from one flare with zonal method

With increasing growth of industrial units in developing countries and pollutants produced by these units, nowadays distribution and dispersion modelling of atmosphere pollutants especially in urban areas is an inevitable importance. Dispersion modelling of atmosphere pollutants is a methodology to estimate focus and concentration values of pollutants related to emission source in different seasons. In current study, using numerical analysis, a thermal diffusion of flare and focus values of industrial pollutants simulation using air zonal methodology has been presented. After studying pollutants emission in open area, validation has been done using laboratory data results and computational fluid dynamics method. The results of this study indicate the ability of presented air zonal methodology to predict thermal diffusion of flare and distribution concentration of pollutant source and information gained from this analysis. Then an exploration of effective parameters in pollution emission such as wind velocity, flare height, and pollution emission rate in downstream has been done. As the results show, when wind velocity rises by 130%, pollution will reach far away from production source and with increase in flare height by 25%, the pollution concentration values on the ground has been reduced by 44%. Also with addition of barrier in pollution dispersion path, pollution level will increase by 60%.