scholarly journals Effect of Pavement Friction Factors on Skid Resistance of Highway Pavements using Prediction Models

2019 ◽  
Vol 8 (9) ◽  
pp. 1184-1190
Keyword(s):  
Surface Texture ◽  
Prediction Models ◽  
Strong Association ◽  
Asphalt Mixture ◽  
Climatic Conditions ◽  
Contact Friction ◽  
Significant Feature ◽  
Skid Resistance ◽  
Climate Conditions ◽  
Form Type

There are many features for road pavements, in which the most significant feature is skid resistance. Skid resistance is referred to as the contact (friction) among the pavement surface and automobile tires. Essentially, this feature is vital to guarantee adequate road secureness and it takes a fundamental part during specific climatic conditions. The aim of this research is targeted at distinguishing the primary attributes that impact skid resistance, so that the rates of traffic collisions that occur as a result of insufficient skid resistance specifically in wet climate conditions, are minimized. Throughout this research, designs to calculate the association of surface texture form, automobile velocity, tire type and the type of asphalt mixture on skid resistance were created and applied to evaluate the significance of each attribute as well as enhancing the secureness of roads. Hence, the attributes influencing skid resistance were chosen and evaluated utilizing the SPSS program. Also, the British Pendulum Skid Resistance Tester was utilized in order to evaluate the skid resistance of various surface textures. The outcomes obtained by this study proved that there is a strong association among surface texture, wheel form, type of mixture and automobile velocity, where R2 =96.5%. Moreover, the outcomes advocated the necessity of applying operating method designs to minimize duration and exertion as well as computing the influence of these attributes on skid resistance. The ingenuity of this research is in its concept which advocates that the manipulation of skid resistance operation method results in enhanced road security and minimizes collisions, which respectively diminishes fatality rates.

scholarly journals Predicting the Potential Global Geographical Distribution of Two Icerya Species under Climate Change

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 684
Author(s):  
Yang Liu ◽  
Juan Shi
Keyword(s):  
Climate Change ◽  
South America ◽  
Prediction Models ◽  
Climatic Conditions ◽  
Future Climate Change ◽  
Scientific Management ◽  
Climate Change Scenarios ◽  
Climate Conditions ◽  
Invasive Pests ◽  
Suitable Habitats

Climate change is predicted to alter the geographic distribution of a wide variety of taxa, including insects. Icerya aegyptiaca (Douglas) and I. purchasi Maskell are two polyphagous and invasive pests in the genus Icerya Signoret (Hemiptera: Monophlebidae) and cause serious damage to many landscape and economic trees. However, the global habitats suitable for these two Icerya species are unclear. The purpose of this study is to determine the potentially suitable habitats of these two species, then to provide scientific management strategies. Using MaxEnt software, the potential risk maps of I. aegyptiaca and I. purchasi were created based on their occurrence data under different climatic conditions and topology factors. The results suggested that under current climate conditions, the potentially habitable area of I. aegyptiaca would be much larger than the current distribution and there would be small changes for I. purchasi. In the future climate change scenarios, the suitable habitats of these two insect species will display an increasing trend. Africa, South America and Asia would be more suitable for I. aegyptiaca. South America, Asia and Europe would be more suitable for I. purchasi. Moreover, most of the highly habitat suitability areas of I. aegyptiaca will become concentrated in Southern Asia. The results also suggested that “min temperature of coldest month” was the most important environmental factor affecting the prediction models of these two insects. This research provides a theoretical reference framework for developing policies to manage and control these two invasive pests of the genus Icerya.

A global climatic risk assessment of pitch canker disease

2009 ◽  
Vol 39 (11) ◽  
pp. 2246-2256 ◽  
Author(s):  
Rebecca J. Ganley ◽  
Michael S. Watt ◽  
Lucy Manning ◽  
Eugenia Iturritxa
Keyword(s):  
Strong Association ◽  
Climatic Conditions ◽  
Pitch Canker ◽  
Global Risk ◽  
Climate Conditions ◽  
Canker Disease ◽  
Forest Industries ◽  
Commercial Species ◽  
Pinus Spp ◽  
Predicted Risk

Pitch canker is a devastating disease of Pinus spp. and Pseudotsuga menziesii (Mirb.) Franco. The pathogen responsible for this disease, Fusarium circinatum Nirenberg & O'Donnell, has spread to many countries within the last three decades. The susceptibility of the widely planted commercial species Pinus radiata D.Don to this pathogen has been of concern to pine forest industries worldwide. Using the process-based distribution program CLIMEX, the global risk of pitch canker establishment was predicted based on a number of climatic variables. The predicted risk of pitch canker establishment by CLIMEX fit well with regions known to have the disease, such as the southeastern United States and Spain. Conversely, the model predicted that the climate in California was not optimal for pitch canker, which fits with the observed lower frequency of natural infections and the strong association with insects in this region. Likewise, Chile, which is known to have F. circinatum in the nurseries but not in the plantation forests, was also predicted to have marginal to suitable climatic conditions for pitch canker establishment. Regions of China, Brazil, Australia, and New Zealand were predicted to have optimal climate conditions for disease establishment. Thus, continued strict quarantine regulations are recommended to prevent the establishment and spread of this pathogen in these countries.

Ecological specificities of the interaction between animal breeding and climate changes, caused by greenhouse gas emissions

2017 ◽  
Vol 4 (3) ◽  
pp. 62-72
Author(s):  
O. Zhukorsky ◽  
O. Nykyforuk ◽  
N. Boltyk
Keyword(s):  
Greenhouse Gases ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Climatic Conditions ◽  
Animal Breeding ◽  
Gas Emissions ◽  
Climate Conditions ◽  
Emissions Inventory ◽  
Theoretical Substantiation ◽  
Global Problems

Aim. Proper development of animal breeding in the conditions of current global problems and the decrease of anthropogenic burden on environment due to greenhouse gas emissions, caused by animal breeding activity, require the study of interaction processes between animal breeding and external climatic conditions. Methods. The theoretical substantiation of the problem was performed based on scientifi c literature, statistical informa- tion of the UN Food and Agriculture Organization and the data of the National greenhouse gas emissions inventory in Ukraine. Theoretically possible emissions of greenhouse gases into atmosphere due to animal breeding in Ukraine and specifi c farms are calculated by the international methods using the statistical infor- mation about animal breeding in Ukraine and the economic-technological information of the activity of the investigated farms. Results. The interaction between the animal breeding production and weather-and-climate conditions of environment was analyzed. Possible vectors of activity for the industry, which promote global warming and negative processes, related to it, were determined. The main factors, affecting the formation of greenhouse gases from the activity of enterprises, aimed at animal breeding production, were characterized. Literature data, statistical data and calculations were used to analyze the role of animal breeding in the green- house gas emissions in global and national framework as well as at the level of specifi c farms with the consid- eration of individual specifi cities of these farms. Conclusions. Current global problems require clear balance between constant development of sustainable animal breeding and the decrease of the carbon footprint due to the activity of animal breeding.

scholarly journals Relationship between Relative Maturity and Grain Yield of Maize (Zea mays L.) Hybrids in Northwest New Mexico for the 2003–2019 Period

Agriculture ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 290
Author(s):  
Koffi Djaman ◽  
Curtis Owen ◽  
Margaret M. West ◽  
Samuel Allen ◽  
Komlan Koudahe ◽  
...  
Keyword(s):  
New Mexico ◽  
Grain Yield ◽  
Sprinkler Irrigation ◽  
Growing Season ◽  
Climatic Conditions ◽  
Agricultural Science ◽  
Production Optimization ◽  
Science Center ◽  
Early Season ◽  
Climate Conditions

The highly variable weather under changing climate conditions affects the establishment and the cutoff of crop growing season and exposes crops to failure if producers choose non-adapted relative maturity that matches the characteristics of the crop growing season. This study aimed to determine the relationship between maize hybrid relative maturity and the grain yield and determine the relative maturity range that will sustain maize production in northwest New Mexico (NM). Different relative maturity maize hybrids were grown at the Agricultural Science Center at Farmington ((Latitude 36.69° North, Longitude 108.31° West, elevation 1720 m) from 2003 to 2019 under sprinkler irrigation. A total of 343 hybrids were grouped as early and full season hybrids according to their relative maturity that ranged from 93 to 119 and 64 hybrids with unknown relative maturity. The crops were grown under optimal management condition with no stress of any kind. The results showed non-significant increase in grain yield in early season hybrids and non-significant decrease in grain yield with relative maturity in full season hybrids. The relative maturity range of 100–110 obtained reasonable high grain yields and could be considered under the northwestern New Mexico climatic conditions. However, more research should target the evaluation of different planting date coupled with plant population density to determine the planting window for the early season and full season hybrids for the production optimization and sustainability.

scholarly journals Prediction Models of Shear Parameters and Dynamic Creep Instability for Asphalt Mixture under Different High Temperatures

Polymers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2542
Author(s):  
Junxiu Lv ◽  
Xiaoyuan Zhang
Keyword(s):  
Shear Stress ◽  
Shear Strength ◽  
Stress Level ◽  
Prediction Models ◽  
Asphalt Mixture ◽  
Confining Pressure ◽  
Shear Strength Parameters ◽  
Dynamic Creep ◽  
Shear Stress Level ◽  
Creep Instability

This study mainly investigates the prediction models of shear parameters and dynamic creep instability for asphalt mixture under different high temperatures to reveal the instability mechanism of the rutting for asphalt pavement. Cohesive force c and internal friction angle φ in the shear strength parameters for asphalt mixture were obtained by the triaxial compressive strength test. Then, through analyzing the influence of different temperatures on parameters c and φ, the prediction models of shear strength parameters related to temperature were developed. Meanwhile, the corresponding forecast model related to confining pressure and shear strength parameters was obtained by simplifying the calculation method of shear stress level on the failure surface under cyclic loading. Thus, the relationship of shear stress level with temperature was established. Furthermore, the cyclic time FN of dynamic creep instability at 60 °C was obtained by the triaxial dynamic creep test, and the effects of confining pressure and shear stress level were considered. Results showed that FN decreases exponentially with the increase in stress levels under the same confining pressure and increases with the increase in confining pressure. The ratio between shear stress level and corresponding shear strength under the same confining pressure was introduced; thus, the relationship curve of FN with shear stress level can eliminate the effect of different confining pressures. The instability prediction model of FN for asphalt mixture was established using exponential model fitting analysis, and the rationality of the model was verified. Finally, the change rule of the parameters in the instability prediction model was investigated by further changing the temperature, and the instability forecast model in the range of high temperature for the same gradation mixture was established by the interpolation calculation.

Human occupation strategies and related environmental-climate during the middle and late Holocene in central Pampas of Argentina

The Holocene ◽  
2018 ◽  
Vol 29 (2) ◽  
pp. 244-261 ◽  
Author(s):  
Pablo G Messineo ◽  
Marcela S Tonello ◽  
Silvina Stutz ◽  
Alfonsina Tripaldi ◽  
Nahuel Scheifler ◽  
...  
Keyword(s):  
Late Holocene ◽  
Specific Activity ◽  
Climatic Conditions ◽  
Hard Material ◽  
Human Occupation ◽  
Climate Conditions ◽  
Lithic Assemblage ◽  
Depositional Rate ◽  
Archeological Site ◽  
Middle And Late Holocene

The main objective of this work is to generate and integrate interpretations of human occupation strategies and inferences of the environmental-climatic conditions in the central Pampas during the middle and late Holocene. We present a novel archeological–geological–paleoecological analysis in the area of the Cabeza de Buey lake, placed in an aeolian landscape. During the middle Holocene, two events of human occupations were recognized at Laguna Cabeza de Buey 2 archeological site. Both events present a small amount of lithic materials, a low diversity of tools and activities developed with them (principally hard material), and the hunting and primary processing of artiodactyls. These evidences suggest a locus of specific activity associated with an ephemeral human settlement under climate conditions drier than present and the presence of small, brackish, and shallow water bodies. For the late late Holocene, the hunter-gatherer occupation has a higher depositional rate of lithic assemblage, stones with diverse origins, presence of pottery fragments, a great lithic tool diversity, knapping techniques, and activities developed with these tools (processing wood, bone, hide, non-woody plant, and soft material). These evidences reveal an occupation with a higher degree of recurrence represented by a locus of multiple activities associated with a more stable landscape, such as an environment of dunes fixed by grass vegetation, and the establishment of a permanent water body. The different environmental characteristics for the middle and late Holocene in this area promoted that human groups develop two different patterns of mobility, settlement and use of space.

scholarly journals Potential of Sunflower-Legume Intercropping: A Way Forward in Sustainable Production of Sunflower in Temperate Climatic Conditions

2021 ◽  
Author(s):  
Brankica Babec ◽  
Srđan Šeremešić ◽  
Nada Hladni ◽  
Nemanja Ćuk ◽  
Dušan Stanisavljević ◽  
...  
Keyword(s):  
Red Clover ◽  
Climatic Conditions ◽  
Sustainable Production ◽  
Oilseed Crop ◽  
Common Vetch ◽  
General Belief ◽  
Climate Conditions ◽  
Sole Crop ◽  
Sole Cropping ◽  
Almost All

Changing climate conditions coupled with the transformations of cultivation practices and land use in sole crop-based sunflower production may significantly decline yield stability of this oilseed crop. Given that sunflower takes the third place in the world oilseed market, with 45 million tons per year, and in the fourth place in vegetable oil production, it is necessary to adapt production technologies toward sustainable agriculture. Considering that, the goal of the research was to analyze and beneficial sustainable production technology of sunflower in intercropping systems. A four-year trial was conducted in Serbia’s agroecological rain-fed conditions (45°34’23.2"N 19°86’18.9"E) using a split-plot design. Two oil types and one confectionary sunflower hybrid were intercropped with common vetch, red clover and alfalfa. Analyses showed that intercropping of sunflower with common vetch resulted in the decrease in almost all sunflower trait values. Also, sunflower × alfalfa intercropping provided to be the most appropriate. The yield of NS Gricko and Rimi PR were statistically on the same level with sole cropping, while alfalfa biomass had better results when intercropped with NS Gricko as compared to sole cropping. Concerning the general belief that yields are more stable in intercropping than in sole crop, further research in this respect is needed, in addition to the research of time and method of sowing.

scholarly journals Dynamic Modulus Prediction of a High-Modulus Asphalt Mixture

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chaohui Wang ◽  
Songyuan Tan ◽  
Qian Chen ◽  
Jiguo Han ◽  
Liang Song ◽  
...  
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Multiple Regression ◽  
Dynamic Modulus ◽  
Prediction Error ◽  
Prediction Models ◽  
Asphalt Mixture ◽  
High Modulus ◽  
Output Stability ◽  
Svm Model

Dynamic modulus is a key evaluation index of the high-modulus asphalt mixture, but it is relatively difficult to test and collect its data. The purpose is to achieve the accurate prediction of the dynamic modulus of the high-modulus asphalt mixture and further optimize the design process of the high-modulus asphalt mixture. Five high-temperature performance indexes of high-modulus asphalt and its mixture were selected. The correlation between the above five indexes and the dynamic modulus of the high-modulus asphalt mixture was analyzed. On this basis, the dynamic modulus prediction models of the high-modulus asphalt mixture based on small sample data were established by multiple regression, general regression neural network (GRNN), and support vector machine (SVM) neural network. According to parameter adjustment and cross-validation, the output stability and accuracy of different prediction models were compared and evaluated. The most effective prediction model was recommended. The results show that the SVM model has more significant prediction accuracy and output stability than the multiple regression model and the GRNN model. Its prediction error was 0.98–9.71%. Compared with the other two models, the prediction error of the SVM model declined by 0.50–11.96% and 3.76–13.44%. The SVM neural network was recommended as the dynamic modulus prediction model of the high-modulus asphalt mixture.

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