Exponent Index Research Articles

Synergetic Satellite Trend Analysis of Aerosol and Warm Cloud Properties ver Ocean and Its Implication for Aerosol‐Cloud Interactions

AbstractDecadal‐scale trends in aerosol and cloud properties provide important ways for understanding aerosol‐cloud interactions. In this paper, by using MODIS products (2003–2017), we analyze synergetic trends in aerosol properties and warm cloud properties over global ocean. Cloud droplet number concentration (CDNC) and aerosol parameters (aerosol optical depth, angstrom exponent, and aerosol index) show consistent decreasing trend over East Coast of the United States (EUS), west coast of Europe (WEU), and east coast of China (EC), and no significant trend in liquid water path is found over these regions during the period 2003–2017. Over regions with significant long‐term trends of aerosol loading and CDNC (e.g., EUS and WEU), the sensitivity of CDNC to aerosol loading based on the long‐term trend is closer to those derived from ground and aircraft observations and larger than those derived from instantaneous satellite observations, providing an alternative way for quantifying aerosol‐cloud interactions. A clear shift in the normalized probability density function of CDNC between the first 5 years (2003–2007) and the last 5 years (2013–2017) is found, with a decrease of around 50% in the occurrence frequency of high CDNC (>400 cm−3) over EUS and WEU. The relative variances of cloud droplet effective radius generally decrease with decreasing aerosol loading, providing large‐scale evidence for the effects of anthropogenic aerosols on the dispersion of cloud droplet size distribution. The long‐term satellite data sets provide great opportunities for quantifying aerosol‐cloud interactions and further confronting these interactions in climate models in the future.

Experimental and theoretical quantification of the relationship between electrical resistivity and hydrate saturation in porous media

An equivalent resistivity model is proposed and validated to determine hydrate saturation based on the experimentally measured resistivity. Experimentally, hydrate with different saturations is formed in an artificial sandpack to measure pressure, temperature, and resistivity as a function of time. The resistivity evolution includes induction of nucleation, large-scale hydrate nucleation, and hydrate rearrangement. Theoretically, a mathematical model on the basis of the parallel circuit principle is developed to quantify the relationship between resistivity and hydrate saturation by taking sand skeleton, temperature, brine salinity, and formation tortuosity into account. The formation tortuosity is expressed as a function of water relative permeability which can be determined by incorporating the existing semi-empirical models. In addition, the cementation exponent and saturation index in the Archie formula are empirically obtained by nonlinearly regressing the experimental measurements, while the sand skeleton resistivity, the correlation coefficient of formation tortuosity, and hydrate saturation index are introduced and determined in the equivalent resistivity models. It is found that the equivalent resistivity models are in a better agreement with the experimental measurements, while the Archie formula introduces an obviously larger error at higher hydrate saturation. Furthermore, it is recommended to use the dynamic porosity expressed as a function of hydrate saturation when characterizing the electrical properties and three-phase flow in porous media. Also, the equivalent resistivity models are found to have a less dependence on the accuracy of porosity compared with the Archie’s formula.

Morphological and Hemodynamic Risk Factors for Middle Cerebral Artery Aneurysm: a Case-Control Study of 190 Patients

This study analyzed morphometric and hemodynamic parameters of aneurysmal and non-aneurysmal middle cerebral artery (MCA) bifurcations and their relationship with optimal values derived from the principle of minimum work (PMW). The study included 96 patients with MCA aneurysm and 94 controls. Aneurysm patients presented with significantly higher values of the radius and cross-sectional area of the MCA trunk, angle between the post-bifurcation branches (α angle) and volume flow rate (VFR) and had significantly lower values of junction exponent and pulsatility index than the controls. The Φ1 and Φ2 angles (angles between the MCA trunk axis and the larger and smaller branch, respectively) and α angle in all groups were significantly larger than the optimal PMW-derived angles. The most important independent predictors of MCA aneurysm were junction exponent (odds ratio, OR = 0.42), α angle (OR = 1.07) and VFR (OR = 2.36). Development of cerebral aneurysms might be an independent effect of abnormalities in hemodynamic and morphometric factors. The risk of aneurysm increased proportionally to the deviation of morphometric parameters of the bifurcation from their optimal PMW-derived values. The role of bifurcation angle in aneurysm development needs to be explained in future research as the values of this parameter in both aneurysm patients and non-aneurysmal controls in were scattered considerably around the PMW-derived optimum.

The Monitoring of Milling Tool Tipping by Estimating Holder Exponents of Vibration

The gradual tool wear is unavoidable in the machining process, it directly influences the surface integrity and dimensional tolerances of the components. The tool condition monitoring (TCM) systems have the capacity to make full use of the cutting potential of the cutting tools, which is of great significance for improving production efficiency and ensuring product quality. In milling titanium alloys, tool tipping is one of the main failure modes. Therefore, this study focuses on establishing a tool tipping monitoring approach for the milling process. The singularity analysis method based on wavelet transform was employed to characterize the variation of vibration waveforms quantitatively with the Holder Exponent (HE) index. The probability density distribution and statistical analysis were adopted to extract effective HE features from the HE indexes to correlate with the different tool conditions. The mutual information method was adopted to rank the discriminability of the HE statistical parameters. Then, several machine learning (ML) models were established with the screened HE features. Finally, the results of the experiments indicate that the Support Vector Machine (SVM) model has the highest classification accuracy and can provide practical guides on the tool changes.

An analytical framework for rectangular FGM tapered plate resting on the elastic foundation

This article presented the free vibration analysis of tapered rectangular functionally graded material (FGM) plates resting on the two-parameter (Winkler and Pasternak) elastic foundation model. Higher-order shear deformation theory (HSDT) to satisfy the traction free boundary conditions on the top and bottom surface of the sigmoid FGM (S-FGM) plate. The material properties are varied according to the two simple power-law distributions of volume fractions of the constituents. The thickness of the plate linearly varies in the y–direction to both sides of the middle plane. The variational Hamilton principle establishes the equation of motions, and Galerkin-Vlasov’s method is used to solve the equation of motion. The free vibration is evaluated with the inclusion of an elastic foundation with different taper ratios. A parametric study has been investigated for the different span ratio, aspect ratio, volume exponent index, taper ratio, and combination of elastic foundation.

Neutron yield from Z-pinches at generation of the power-degree spectrum of fast deuterons

The neutron yield from the plasma of deuterium Z-pinch is analyzed with a power-law spectrum of fast deuterons in the energy range from several hundred keV to several MeV. The influence of the typical energies of fast deuterons and the exponent index of the spectrum is considered. The efficiency of neutron generation is estimated by the ratio of the neutron yield to the average deuteron energy. It was shown that when generating fast deuterons with energies of the order of 1 MeV, the reaction rate is much higher than for Maxwellian plasma with a temperature of the order of 10 keV.

AN AEROSOL TYPE CLASSIFICATION METHOD BASED ON REMOTE SENSING DATA IN GUANGDONG, CHINA

Abstract. This paper provides an aerosol classification method based on remote sensing data in Guangdong, China in year 2010 and 2011. Aerosol Optical Depth, Angstrom Exponent and Ultraviolet Aerosol Index, as important properties of aerosols, are introduced into classification. Data of these three aerosol properties are integrated to establish a 3-dimension dataset, and k-means clustering algorithm with Mahalanobis distance is used to find out four clusters of the dataset, which respectively represents four aerosol types of urban-industrial, dust, biomass burning and mixed type. Prior knowledge about the understanding of each aerosol type is involved to associate each cluster with aerosol type. Temporal variation of the aerosol properties shows similarities between these two years. The proportion of aerosol types in different cities of Guangdong Province is also calculated, and result shows that in most cities urban-industrial aerosols takes the largest proportion while the mixed type aerosols takes the second place. Classification results prove that k-means cluster algorithm with Mahalanobis distance is a brief and efficient method for aerosol classification.

Multifractal analysis of uterine electromyography signals to differentiate term and preterm conditions.

In this study, an attempt has been made to identify the origin of multifractality in uterine electromyography signals and to differentiate term (gestational age > 37 weeks) and preterm (gestational age ≤ 37 weeks) conditions by multifractal detrended moving average technique. The signals obtained from a publicly available database, recorded from the abdominal surface during the second trimester, are used in this study. The signals are preprocessed and converted to shuffle and surrogate series to examine the source of multifractality. Multifractal detrended moving average algorithm is applied on all the signals. The presence of multifractality is verified using scaling exponents, and multifractal spectral features are extracted from the spectrum. The variation of multifractal features in term and preterm conditions is analyzed statistically using Student's t-test. The results of scaling exponents show that the uterine electromyography or electrohysterography signals reveal multifractal characteristics in term and preterm conditions. Further investigation indicates the existence of long-range correlation as the primary source of multifractality. Among all extracted features, strength of multifractality, exponent index, and maximum and peak singularity exponents are statistically significant ( p < 0.05) in differentiating term and preterm conditions. The coefficient of variation is found to be lower for strength of multifractality and peak singularity exponent, which reveal that these features exhibit less inter-subject variance. Hence, it appears that multifractal analysis can aid in the diagnosis of preterm or term delivery of pregnant women.

Computation of mixed-mode stress intensity factors in functionally graded materials by natural element method

This paper is concerned with the numerical calculation of mixed-mode stress intensity factors (SIFs) of 2-D isotropic functionally graded materials (FGMs) by the natural element method (more exactly, Petrov-Galerkin NEM). The spatial variation of elastic modulus in non-homogeneous FGMs is reflected into the modified interaction integral M(1,2). The local NEM grid near the crack tip is refined, and the directly approximated strain and stress fields by PG-NEM are enhanced and smoothened by the patch recovery technique. Two numerical examples with the exponentially varying elastic modulus are taken to illustrate the proposed method. The mixed-mode SIFs are parametrically computed with respect to the exponent index in the elastic modulus and external loading and the crack angle and compared with the other reported results. It has been justified from the numerical results that the present method successfully and accurately calculates the mixed-mode stress intensity factors of 2-D non-homogeneous functionally graded materials.

Evaluation of stress intensity factors in functionally graded materials by natural element method

This paper is concerned with the numerical evaluation of the stress intensity factors (SIFs) of 2-D isotropic functionally graded materials (FGMs) by the natural element method (more exactly, Petrov-Galerkin NEM). The spatial variation of elastic modulus in inhomogeneous FGMs is reflected into the modified interaction integral $${\tilde M^{(1,2)}}$$ . The local NEM grid near the crack tip is refined, and the strain and stress fields that were directly approximated by PG-NEM were enhanced and smoothened by the patch recovery technique. Numerical examples with the exponentially varying elastic modulus are taken to illustrate the proposed method. The stress intensity factors are parametrically evaluated with respect to the exponent index in the elastic modulus and the crack length, and those were compared with the other reported results. It has been justified from the numerical results that the present method successfully and accurately evaluates the stress intensity factors of 2-D inhomogeneous functionally graded materials.

Vegetation Dynamics and Diverse Responses to Extreme Climate Events in Different Vegetation Types of Inner Mongolia

As the global climate has changed, studies on the relationship between vegetation and climate have become crucial. We analyzed the long-term vegetation dynamics and diverse responses to extreme climate changes in Inner Mongolia, based on long-term Global Inventory Monitoring and Modelling Studies (GIMMS) NDVI3g datasets, as well as the eight extreme precipitation indices and six extreme temperature indices that are highly correlated with the occurrence of droughts or floods, heat or cold temperature disasters, and vegetation growth in Inner Mongolia. These datasets were analyzed using linear regression analysis, the Hurst exponent index, residual analysis, and the Pearson correlation analysis. The results showed the following: (1) The vegetation dynamical changes exhibited trends of improvement during 1982 to 2015, and 68% of the vegetation growth changes in Inner Mongolia can be explained by climate changes. (2) The extreme precipitation indices exhibited a slight change, except for the annual total wet–day precipitation (PRCPTOT). The occurrence of extreme cold temperatures showed a significant decline, while the occurrence of extreme warm temperatures showed an upward trend in Inner Mongolia. (3) The typical steppe, desert steppe, and forest steppe regions are more sensitive to extreme large precipitation, and the forest regions are more sensitive to extreme warm temperatures. (4) Extreme precipitation exhibits a one-month lagged effect on vegetation that is larger than the same-month effects on the grassland system. Extreme temperature exhibits same-month effects on vegetation, which are larger than the one-month lagged effects on the forest system. Therefore, studies of the relationship between extreme climate indices and vegetation are important for performing risk assessments of droughts, floods, and other related natural disasters.

Characterization of aerosol type based on aerosol optical properties over Baghdad, Iraq

Aerosol optical depth (AOD), Angstrom exponent (AE), and ozone monitoring instrument aerosols index (OMI-AI) data, derived from MODerate Resolution Imaging Spectroradiometer (MODIS) and OMI sensor on board NASA’s Aqua satellite and NASA-Aura satellite platforms, have been analyzed and classified over Baghdad, Iraq, for an 8-year period (2008–2015). In order to give an obvious understanding of temporal inconsistency in the characteristics and classification of aerosols during each season separately, PREDE POM-02 sky radiometer measurements of AOD, carried out during a 2-year period (2014–2015), were compared with MODIS–Aqua AODs. On seasonal bases, MODIS–Aqua AODs corroborate well with ground-based measurements, with correlation coefficients ranging between 0.74 and 0.8 and RMSE ranging from 0.097 to 0.062 during spring and autumn seasons respectively. The overall satellite- and ground-based measurement comparisons showed a good agreement with correlation coefficients of 0.78 and RMSE of 0.066. These results suggest that MODIS–Aqua gives a good estimate of AOD. Analysis of MODIS–Aqua data for the 8-year period showed that the overall mean AOD, AE, and OMI-AI over Baghdad were 0.44 ± 0.16, 0.77 ± 0.29, and 1.34 ± 0.33 respectively. AOD records presented a unique peak which was extended from mid-spring (April) to mid-summer (July) while the AE annual variability indicated a more complicated behavior with minimum values during the period from late spring (May) to early autumn (September). The maximum AOD and OMI-AI values occurred during summer while their minimum values occurred during winter. The AE showed an opposite behavior to that of AOD such that the highest AE values occurred during autumn and winter and the lowest values happened during spring and summer. This behavior may be attributed to the domination of coarse aerosol particles during autumn and winter seasons and fine aerosol particles during spring and summer seasons. A Hybrid Single-Particle Lagrangian Integrated Trajectory model was utilized to determine the source of air mass transport and to recognize the variability of aerosol origin regions. Finally, AOD, AE, and OMI-AI values have been employed to identify several aerosol types and to present seasonal heterogeneity in their contribution based on their origins.

Time series analysis of a binary gas-solid conical fluidized bed using radioactive particle tracking (RPT) technique data

In current work, the radioactive particle tracking (RPT) technique has been used to investigate the behavior of gas-solid conical mono and binary fluidized bed. The dynamics of the bed has been analyzed using both time-averaged and fluctuation quantities at different gas inlet velocities and bed compositions. The binary bed was composed of glass beads of two different diameters 1 mm and 0.6 mm. The bed of 0:100, 50:50 and 100:0 by wt % of both the particles were investigated. Time-averaged quantities like mean axial velocities, RMS velocities, and granular temperature indicate that behavior of conical bed at the top and bottom sections are significantly different. Gas-solid interactions mainly dominate the bottom section while particle-particle interaction plays a critical role at the top section. Further, time series and chaos analysis of RPT data were performed. Hurst exponent, autocorrelation coefficient, and mixing index were calculated through time series analysis. The results indicate that better mixing is observed in conical bed even at low velocity compared to cylindrical fluidized-bed. It also reveals a regime transition around 5.7 m/s gas inlet velocity. Finally, Kolmogorov entropy and correlation dimension calculated through chaos analysis of RPT data confirm flow regime transition at gas inlet velocity around 5.7 m/s, for all the examined bed compositions.

Vegetation restoration projects and their influence on runoff and sediment in China

The vegetation status in China has undergone obvious changes since vegetation restoration projects were widely implemented in 1999. Based on a statistical analysis and the Hurst exponent index method, the spatial and temporal characteristics of vegetation change and its influence on runoff and sediment in China was analyzed using the Normalized Difference Vegetation Index (NDVI). The results showed that the change of vegetation coverage (E) in China from 2000 to 2015 was 5.64%. There was substantial variation in the spatial distribution of E values. There was a significant increase in the vegetation coverage in the areas covered by five vegetation restoration projects. It was found that 83.34% of the whole of China had experienced a continuous improvement in vegetation coverage. The largest increase in vegetation coverage occurred in the middle of the Loess Plateau and the middle of northeast China, while the largest decrease occurred in some areas of the Qinghai-Tibet Plateau and Xinjiang. Areas of vegetation degradation should be given special attention, with suitable control measures put in place. The slope angle with the largest increase in vegetation coverage was in the range of 15°–25°. Aspect had little effect on vegetation restoration. Vegetation restoration around the Hu Line, in which the precipitation was between 400 and 500 mm, was better and faster than in other regions. Vegetation coverage was linked to annual precipitation, and increased steadily with precipitation until a value of 500 mm was reached, after which it remained stable. Vegetation restoration did not reduce runoff, but it did reduce the sediment concentration. This study provided useful information for decision-makers involved in vegetation restoration projects and environmental management, especially in fragile ecological environments in arid and alpine areas.

Analysis of uterine electromyography signals in preterm condition using multifractal algorithm.

In this work, an attempt has been made to analyze the preterm (gestation period $\leq 37$ weeks) condition using uterine electromyography (EMG) signals and multifractal detrended fluctuation analysis (MFDFA). The signals recorded from the electrodes placed on the surface of abdomen are used for this study and these are obtained from a publically available online database. These signals are preprocessed using 4-pole digital Butterworth filter. The preprocessed signals are subjected to MFDFA to extract multifractal features namely maximum singularity exponent, peak singularity exponent, strength of multifractality and exponent index. Generalized Hurst exponent extracted from the signals indicate that uterine EMG signals show multifractal behavior in preterm condition. Among the extracted features the coefficient of variation is found to be lower for peak singularity exponent. This indicates that this feature have lower inter-subject variability. Hence, it appears that the multifractal features can help in the assessment of uterine EMG signals for preterm detection.

Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China

Satellite remote sensing has been widely used to retrieve aerosol optical depth (AOD), which is an indicator of air quality as well as radiative forcing. The dark target (DT) algorithm is applied to low reflectance areas, such as dense vegetation, and the deep blue (DB) algorithm is adopted for bright-reflecting regions. However, both DT and DB algorithms ignore the effect of surface bidirectional reflectance. This paper provides a method for AOD retrieval in arid or semiarid areas, in which the key points are the accurate estimation of surface reflectance and reasonable assumptions of the aerosol model. To reduce the uncertainty in surface reflectance, a minimum land surface reflectance database at the spatial resolution of 500 m for each month was constructed based on the moderate-resolution imaging spectroradiometer (MODIS) surface reflectance product. Furthermore, a bidirectional reflectance distribution function (BRDF) correction model was adopted to compensate for the effect of surface reflectance anisotropy. The aerosol parameters, including AOD, single scattering albedo, asymmetric factor, Ångström exponent and complex refractive index, are determined based on the observation of two sunphotometers installed in northern Xinjiang from July to August 2014. The AOD retrieved from the MODIS images was validated with ground-based measurements and the Terra-MODIS aerosol product (MOD04). The 500 m AOD retrieved from the MODIS showed high consistency with ground-based AOD measurements, with an average correlation coefficient of ~0.928, root mean square error (RMSE) of ~0.042, mean absolute error (MAE) of ~0.032, and the percentage falling within the expected error (EE) of the collocations is higher than that for the MOD04 DB product. The results demonstrate that the new AOD algorithm is more suitable to represent aerosol conditions over Xinjiang than the DB standard product.

Spatiotemporal characteristics of aerosols and their trends over mainland China with the recent Collection 6 MODIS and OMI satellite datasets.

With the rapid development of China's economy and high rate of industrialization, environmental pollution has become a major challenge for the country. The present study is aimed at analyzing spatiotemporal heterogeneities and changes in trends of different aerosol optical properties observed over China. To achieve this, Collection 6 Level 3 data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS; 2002-2016) and Ozone Monitoring Instrument (OMI; 2005-2016) sensors were used to investigate aerosol optical depth (AOD550), Ångstrӧm exponent (AE470-660), and Absorption Aerosol Index (AAI). The spatial distribution of annual mean AOD550 was noticed to be high over economically and industrialized regions of the east, south, and northeast of China, while low aerosol loadings were located over rural and less-developed areas of the west and northeast of China. High AE470-660 (> 1.0) values were characterized by the abundance of fine-mode particles and vice versa, likely attributed to large anthropogenic activities. Similarly, high AOD with corresponding high AE and low AAI was characterized over the urban-industrialized regions of the central, east, and south of China during most of the months, being more pronounced in June and July. On seasonal scale, AOD values were found to be high during spring, followed by the summer and autumn, and low during the winter season. It is also evident that all aerosol parameters showed a single-peak frequency distribution in all seasons over entire China. Further, the annual, monthly, and seasonal spatial trends revealed a decreasing trend in AOD over most regions of China, except in the southwest of China, which showed a positive increasing trend. Significant increasing trends were noted in AAI for all the seasons, particularly during autumn and winter, resulting in a large amount of the absorbing type of aerosols produced from biomass burning and desert dust.

Appraisal of long term groundwater quality of peninsular India using water quality index and fractal dimension

A review has been made to understand the hydrogeochemical behaviour of groundwater through statistical analysis of long term water quality data (year 2005–2013). Water Quality Index (WQI), descriptive statistics, Hurst exponent, fractal dimension and predictability index were estimated for each water parameter. WQI results showed that majority of samples fall in moderate category during 2005–2013, but monitoring site four falls under severe category (water unfit for domestic use). Brownian time series behaviour (a true random walk nature) exists between calcium \((\mathrm{Ca}^{2+})\) and electric conductivity (EC); magnesium \((\mathrm{Mg}^{2+})\) with EC; sodium \((\mathrm{Na}^{+})\) with EC; sulphate \((\mathrm{SO}_{4}^{2-})\) with EC; total dissolved solids (TDS) with chloride \((\mathrm{Cl}^{-})\) during pre- (2005–2013) and post- (2006–2013) monsoon season. These parameters have a closer value of Hurst exponent (H) with Brownian time series behaviour condition (\(H=0.5\)). The result of times series analysis of water quality data shows a persistent behaviour (a positive autocorrelation) that has played a role between \(\mathrm{Cl}^{-}\) and \(\mathrm{Mg}^{2+}\), \(\mathrm{Cl}^{-}\) and \(\mathrm{Ca}^{2+}\), TDS and \(\mathrm{Na}^{+}\), TDS and \(\mathrm{SO}_{4}^{2-}\), TDS and \(\mathrm{Ca}^{2+}\) in pre- and post-monsoon time series because of the higher value of H (>1). Whereas an anti-persistent behaviour (or negative autocorrelation) was found between \(\mathrm{Cl}^{-}\) and EC, TDS and EC during pre- and post-monsoon due to low value of H. The work outline shows that the groundwater of few areas needs treatment before direct consumption, and it also needs to be protected from contamination.

Fractal Inspection and Machine Learning-Based Predictive Modelling Framework for Financial Markets

This paper presents a novel framework to conduct empirical investigation and carry out predictive modelling on daily index prices of Bombay stock exchange, Dow Jones Industrial Average, Hang Seng Index, NIFTY 50, NASDAQ and NIKKEI, representing developed and emerging economies. We examine the equity markets in detail to check whether they follow pure random walk models or not. Mandelbrot’s rescaled range analysis-based Hurst exponent and fractal dimensional index have been estimated to assess the dynamics of the daily prices of the chosen stock indices. Four advanced machine learning algorithms for predictive modelling—adaptive neuro-fuzzy inference system, dynamic evolving neuro-fuzzy inference system, Jordan neural network, support vector regression and random forest—have been used to build forecasting frameworks to predict the future index prices. Fractal inspection strongly rejects random walk hypothesis and suggests that the considered stock indices exhibit significant persistent trend. The results of the predictive modelling exercises show that prices can be effectively forecasted. The research framework and the overall findings can be useful for the investors and traders to a large extent.

Effect of Oxidized Starch on Morphology, Rheological and Tensile Properties of Low-Density Polyethylene/Linear Low-Density Polyethylene/Thermoplastic Oxidized Starch Blends

In this work, morphology, rheological and tensile properties of low-density polyethylene/linear low-density polyethylene/thermoplastic oxidized starch (LDPE/LLDPE/TPOS) blends are studied. The blends of LDPE/LLDPE (70/30, w/w) containing 0–20 wt% TPOS in the presence of 3 wt% of PE-grafted maleic anhydride (PE-g-MA) as a compatibilizer are prepared by a twin screw extruder and then converted to appropriate thin films using an extrusion film blowing machine. Scanning electron microscopic images show that there is a relative good dispersion of oxidized starch particles in PE matrices. However, as TPOS content in the blends increases, the starch particle size increases too. The rheological analyses indicate that TPOS can decrease the elasticity and viscosity of the blends. The LDPE/LLDPE/TPOS blends show power-law behavior and as the TPOS content increases the power-law exponent (n) and consistency index (K) decrease. The ultimate tensile strength and elongation at break of the final blend films reduce, when TPOS content increases from 5 to 20 wt%. However, the required mechanical properties for packaging applications are achieved when 10 wt% oxidized starch is added, according to ASTM D4635.