Diabetes is a complex condition,and the causes are still not fully understood.However,a growing body of evidence suggests that exposure to air pollution could be linked to an increased risk of diabetes.Specifically,ex...Diabetes is a complex condition,and the causes are still not fully understood.However,a growing body of evidence suggests that exposure to air pollution could be linked to an increased risk of diabetes.Specifically,exposure to certain pollutants,such as particulate Matter and Ozone,has been associated with higher rates of diabetes.At the same time,air pollution has also been linked to an increased risk of thyroid cancer.While there is less evidence linking air pollution to thyroid cancer than to diabetes,it is clear that air pollution could have severe implications for thyroid health.Air pollution could increase the risk of diabetes and thyroid cancer through several mechanisms.For example,air pollution could increase inflammation in the body,which is linked to an increased risk of diabetes and thyroid cancer.Air pollution could also increase oxidative stress,which is linked to an increased risk of diabetes and thyroid cancer.Additionally,air pollution could increase the risk of diabetes and thyroid cancer by affecting the endocrine system.This review explores the link between diabetes and air pollution on thyroid cancer.We will discuss the evidence for an association between air pollution exposure and diabetes and thyroid cancer,as well as the potential implications of air pollution for thyroid health.Given the connections between diabetes,air pollution,and thyroid cancer,it is essential to take preventive measures to reduce the risk of developing the condition.展开更多
The effects of bacterial strain, salinity and pH on the bioleaching of a complex ore using mesophilic and extremely thermophilic bacteria were investigated and the statistical analysis of the results was performed usi...The effects of bacterial strain, salinity and pH on the bioleaching of a complex ore using mesophilic and extremely thermophilic bacteria were investigated and the statistical analysis of the results was performed using ERGUN’s test. The extreme thermophiles were shown to display superior kinetics of dissolution of zinc compared with the mesophiles as confirmed by the statistical analysis. Bioleaching performance of the extreme thermophiles is found to improve in response to the increase in acidity (pH from 2.0 to 1.0) whilst the activity of the mesophiles is adversely affected by decreasing pH. Statistical analysis of the bioleaching data indicates that the effect of pH is insignificant in the range of pH 1.0-1.2 for the extreme thermophiles and pH 1.4-2.0 for the mesophiles. Salinity is shown to have a suppressing effect on the mesophiles. However, the extreme thermophiles appear to be halophilic in character as they could operate efficiently under saline conditions (1%-4%Cl- (w/v)).展开更多
This work presents a computational matrix framework in terms of tensor signal algebra for the formulation of discrete chirp Fourier transform algorithms. These algorithms are used in this work to estimate the point ta...This work presents a computational matrix framework in terms of tensor signal algebra for the formulation of discrete chirp Fourier transform algorithms. These algorithms are used in this work to estimate the point target functions （impulse response functions） of multiple-input multiple-output （MIMO） synthetic aperture radar （SAR） systems. This estimation technique is being studied as an alternative to the estimation of point target functions using the discrete cross-ambiguity function for certain types of environmental surveillance applications. The tensor signal algebra is presented as a mathematics environment composed of signal spaces, finite dimensional linear operators, and special matrices where algebraic methods are used to generate these signal transforms as computational estimators. Also, the tensor signal algebra contributes to analysis, design, and implementation of parallel algorithms. An instantiation of the framework was performed by using the MATLAB Parallel Computing Toolbox, where all the algorithms presented in this paper were implemented.展开更多
This paper presents an extension of mathematical static model to dynamic problems of micropolar elastic plates, recently developed by the authors. The dynamic model is based on the generalization of Hellinger-Prange-R...This paper presents an extension of mathematical static model to dynamic problems of micropolar elastic plates, recently developed by the authors. The dynamic model is based on the generalization of Hellinger-Prange-Reissner (HPR) variational principle for the linearized micropolar (Cosserat) elastodynamics. The vibration model incorporates high accuracy assumptions of the micropolar plate deformation. The computations predict additional natural frequencies, related with the material microstructure. These results are consistent with the size-effect principle known from the micropolar plate deformation. The classic Mindlin-Reissner plate resonance frequencies appear as a limiting case for homogeneous materials with no microstructure.展开更多
Ag–CdO composites are still one of the most commonly used electrical contact materials in low-voltage applications owing to their excellent electrical and mechanical properties.Nevertheless,considering the restrictio...Ag–CdO composites are still one of the most commonly used electrical contact materials in low-voltage applications owing to their excellent electrical and mechanical properties.Nevertheless,considering the restriction on using Cd due to its toxicity,it is necessary to find alternative materials that can replace these composites.In this study,the synthesis of Ag-ZnO alloys from Ag-Zn solid solutions was investigated by hot mechanochemical processing.The hot mechanochemical processing was conducted in a modified attritor mill at 138℃under flowing O2 at 1200 cm3/min for 3.0 h.The microstructure and phase evolution were investigated using X-ray diffractometry,field emission gun scanning electron microscopy and transmission electron microscopy.The results suggest that it is possible to complete the oxidation of Ag-Zn solid solution by hot mechanochemical processing at a low temperature and short time.This novel synthesis route can produce Ag-ZnO composites with a homogeneous distribution of nanoscale ZnO precipitates,which is impossible to achieve using the conventional material processing methods.Considering the fact that the fundamental approach to improving electric contact material performance resides in obtaining uniform dispersion of the second-phase in the Ag matrix,this new processing route could open the possibility for Ag-ZnO composites to replace non-environmentally friendly Ag-CdO.展开更多
The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are resp...The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)techniques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model’s result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.展开更多
文摘Diabetes is a complex condition,and the causes are still not fully understood.However,a growing body of evidence suggests that exposure to air pollution could be linked to an increased risk of diabetes.Specifically,exposure to certain pollutants,such as particulate Matter and Ozone,has been associated with higher rates of diabetes.At the same time,air pollution has also been linked to an increased risk of thyroid cancer.While there is less evidence linking air pollution to thyroid cancer than to diabetes,it is clear that air pollution could have severe implications for thyroid health.Air pollution could increase the risk of diabetes and thyroid cancer through several mechanisms.For example,air pollution could increase inflammation in the body,which is linked to an increased risk of diabetes and thyroid cancer.Air pollution could also increase oxidative stress,which is linked to an increased risk of diabetes and thyroid cancer.Additionally,air pollution could increase the risk of diabetes and thyroid cancer by affecting the endocrine system.This review explores the link between diabetes and air pollution on thyroid cancer.We will discuss the evidence for an association between air pollution exposure and diabetes and thyroid cancer,as well as the potential implications of air pollution for thyroid health.Given the connections between diabetes,air pollution,and thyroid cancer,it is essential to take preventive measures to reduce the risk of developing the condition.
文摘The effects of bacterial strain, salinity and pH on the bioleaching of a complex ore using mesophilic and extremely thermophilic bacteria were investigated and the statistical analysis of the results was performed using ERGUN’s test. The extreme thermophiles were shown to display superior kinetics of dissolution of zinc compared with the mesophiles as confirmed by the statistical analysis. Bioleaching performance of the extreme thermophiles is found to improve in response to the increase in acidity (pH from 2.0 to 1.0) whilst the activity of the mesophiles is adversely affected by decreasing pH. Statistical analysis of the bioleaching data indicates that the effect of pH is insignificant in the range of pH 1.0-1.2 for the extreme thermophiles and pH 1.4-2.0 for the mesophiles. Salinity is shown to have a suppressing effect on the mesophiles. However, the extreme thermophiles appear to be halophilic in character as they could operate efficiently under saline conditions (1%-4%Cl- (w/v)).
文摘This work presents a computational matrix framework in terms of tensor signal algebra for the formulation of discrete chirp Fourier transform algorithms. These algorithms are used in this work to estimate the point target functions （impulse response functions） of multiple-input multiple-output （MIMO） synthetic aperture radar （SAR） systems. This estimation technique is being studied as an alternative to the estimation of point target functions using the discrete cross-ambiguity function for certain types of environmental surveillance applications. The tensor signal algebra is presented as a mathematics environment composed of signal spaces, finite dimensional linear operators, and special matrices where algebraic methods are used to generate these signal transforms as computational estimators. Also, the tensor signal algebra contributes to analysis, design, and implementation of parallel algorithms. An instantiation of the framework was performed by using the MATLAB Parallel Computing Toolbox, where all the algorithms presented in this paper were implemented.
文摘This paper presents an extension of mathematical static model to dynamic problems of micropolar elastic plates, recently developed by the authors. The dynamic model is based on the generalization of Hellinger-Prange-Reissner (HPR) variational principle for the linearized micropolar (Cosserat) elastodynamics. The vibration model incorporates high accuracy assumptions of the micropolar plate deformation. The computations predict additional natural frequencies, related with the material microstructure. These results are consistent with the size-effect principle known from the micropolar plate deformation. The classic Mindlin-Reissner plate resonance frequencies appear as a limiting case for homogeneous materials with no microstructure.
基金financially supported by the FONDECYT(Project No.11100284)the Metallurgy Department of University of Atacama for the XRD and SEM analysis(Projects EQM130125 and EQUV 003)
文摘Ag–CdO composites are still one of the most commonly used electrical contact materials in low-voltage applications owing to their excellent electrical and mechanical properties.Nevertheless,considering the restriction on using Cd due to its toxicity,it is necessary to find alternative materials that can replace these composites.In this study,the synthesis of Ag-ZnO alloys from Ag-Zn solid solutions was investigated by hot mechanochemical processing.The hot mechanochemical processing was conducted in a modified attritor mill at 138℃under flowing O2 at 1200 cm3/min for 3.0 h.The microstructure and phase evolution were investigated using X-ray diffractometry,field emission gun scanning electron microscopy and transmission electron microscopy.The results suggest that it is possible to complete the oxidation of Ag-Zn solid solution by hot mechanochemical processing at a low temperature and short time.This novel synthesis route can produce Ag-ZnO composites with a homogeneous distribution of nanoscale ZnO precipitates,which is impossible to achieve using the conventional material processing methods.Considering the fact that the fundamental approach to improving electric contact material performance resides in obtaining uniform dispersion of the second-phase in the Ag matrix,this new processing route could open the possibility for Ag-ZnO composites to replace non-environmentally friendly Ag-CdO.
文摘The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)techniques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model’s result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.
