In order to maximize the potential energy utilization of agricultural and forestry waste and sludge, the experimental research on co-pyrolysis was carried out for two kinds of sludge (urban industrial sludge, paper sludge) and a typical biomass straw. The results show that adding biomass can effectively improve sludge pyrolysis characteristics; biomass straw and sludge, there are complex interactive effects between components in the co-pyrolysis process, and the characteristic parameters show nonlinear changes. When industrial sludge is mixed with straw, with the increase of straw content, the initial temperature of pyrolysis gradually decreases, the termination temperature increases, the peak of pyrolysis reaction rate and the corresponding temperature gradually increase, and the pyrolysis index gradually increases; when paper sludge is mixed with straw, with the increase of straw content, the initial temperature of pyrolysis gradually decreases, the termination temperature increases, the peak of pyrolysis reaction rate gradually increases, while the peak corresponding temperature gradually decreases, and the pyrolysis index gradually decreases. Combined with characteristic parameters and reaction kinetics analysis, it is suggested that the straw mixing proportion should be controlled at about 25% during the co-pyrolysis of industrial sludge and straw. During the co-pyrolysis of paper sludge and straw, it is suggested to control the straw blending ratio at about 75%.

This paper uses Public Choice analysis to examine the case for and experience with Public-Private Partnerships (PPPs). A PPP is a contractual platform which connects a governmental body and a private entity. The goal is to provide a public sector program, service, or asset that would normally be provided exclusively by a public sector entity. This paper focuses on PPPs in developed countries, but it also draws on studies of PPPs in developing countries. The economics literature generally defines PPPs as long-term contractual arrangements between a public authority (local or central government) and a private supplier for the delivery of services. The private sector supplier takes responsibility for building infrastructure components, securing financing of the investment, and then managing and maintaining this facility.

However, in addition to those formed through contracts, PPPs may take other forms such as those developed in response to tax subvention or coercion, as in the case of regulatory mandates. A key element of PPP is that the private partner takes on a significant portion of the risk through a schedule of specified remuneration, contingency payments, and provision for dispute resolution. PPPs typically are long-term arrangements and involve large corporations on the private side, but may also be limited to specific phases of a project.

The types of PPPs discussed in this paper exclude arrangements which may result from government mandates such as the statutory emission mandates imposed on automobile manufacturers and industrial facilities (e.g., power plants). It also excludes PPP-like organizations resulting from US section 501(c)(3) of the Internal Revenue Code, which provides tax subsidies for certain public charities, scientific research organizations, and organizations whose goals are to prevent cruelty to animals or erect public monuments at no expense to the government. This paper concludes that an array of Public Choice tools are applicable to understanding the emergence, success, or failure of PPPs. Several short case studies are provided to illustrate the practicalities of PPPs. 

This project is carried out to assess the remediation effect on soil contaminated by molybdenum (Mo), one of heavy metals, through the use of an energy crop, sunflowers. This project explores the integration of phytohormones and chelates in the phytoremediation of soils contaminated by heavy metals, and further assesses the operational measures of remedying heavy-metal contaminated soil with sunflowers, in addition to the related environmental factors. Then the project explores phytohormones and heavy metals on the growth scenario explants (explants morphological analysis) through the experiment. The results indicate that GA₃ can increase the growth rate of the plants. The average incremental growth of the heavy-metal-added-only group is 21.0 cm; of the GA₃-added group it is 21.9 cm; of the EDDS-added group, it is 20.3 cm; of the GA₃+ EDDS-added group, it is 21.7 cm. Compared with the conventional methods of phytoremediation, these integrated measures can actually spur the growth of plants.

Fire is one of the most serious hazards, which causes many economic, social, ecological, and human damages every year in the world. Fire in forests and natural ecosystems destroys wood, regeneration, forest vegetation, as well as soil erosion and forest regeneration problems (due to the dryness of the weather and the weakness of the soil). Awareness of the extent of the zones that have been fired is important for forest management. On the other hand, the difficulty of fieldwork due to the high cost and inaccessible roads, etc. reveals the need for using remote sensing science to solve this problem. In this research, MODIS satellite images were used to detect and determine the fire extent of Golestan province forests in northern Iran. MID13q1 and MOD13q1 images were used to detect the normal conditions of the environment. The 15-year time series data were provided for the NDVI and NDMI indicators in 2000-2015. Then, the behavior of indicators in the fire zone was studied on the day after the fire. The burned zones by the fire were specified by determining the appropriate threshold and then, they were compared to long-term normals. In the NDMI and NDVI indicators, the mean of the numeric value threshold limit for determining the burnt pixels was respectively 1.865 and 0.743 of the reduction in their normal long-term period, which are selected as fire pixels. The results showed that the NDMI index could determine the extent of the burned zone with the accuracy of 95.15%.

Attempts were made in the present study to design and develop skeletally modified ether linked tetraglycidyl epoxy resin (TGBAPSB), which is subsequently reinforced with different weight percentages of amine functionalized mullite fiber (F-MF). The F-MF was synthesized by reacting mullite fiber with 3-aminopropyltriethoxysilane (APTES) as coupling agent and the F-MF structure was confirmed by FT-IR. TGBAPSB reinforced with F-MF formulation was cured with 4,4’-diamino diphenyl methane (DDM) to obtain nanocomposite. The surface morphology of TGBAPSB-F-MF epoxy nanocomposites was investigated by XRD, SEM and AFM studies. From the study, it follows that these nanocomposite materials offer enhancement in mechanical, thermal, thermo-mechanical, dielectric properties compared to neat (TGBAPSB) epoxy matrix. Hence we recommend these nanocomposites for a possible use in advanced engineering applications that require both toughness and stiffness.

With the development of social economy, the current urban traffic problem is more prominent. In order to solve this problem very well, the idea of establishing intelligent traffic management came into being. The establishment of intelligent traffic management, cannot do without the signal launch and reception. Therefore, how to set up some wireless signal transmitting device in time to travel on the road motor vehicles to send traffic information and how to achieve full coverage of the signal and signal stability is our article to discuss the issue. For the first question, we must separate the motorway and non-motorway from all roads. Motorway lanes are usually straight and long. While the bends are usually just sidewalks or bike lanes (non-motorized lanes). So the 121 road can be clustered analysis, clustering of the two indicators for each road length (the distance between the adjacent points) and the collection point of density (by drawing, you can observe the more curved the denser the road collection point, so the road curvature into the collection point of the intensity), the result of clustering can get 48 motor lanes. And then through regress function regression and data fitting to achieve an approximate description of each type of motor vehicle description model, so that each road in a given latitude (latitude) coordinates to determine the latitude (longitude) coordinates and the corresponding altitude. For the problem of two, according to the meaning of the road to know the signal strength is only related to the distance between the sampling point and the launch device, so you can 'the motor vehicle between the signal reception is relatively close to' this indicator into ' The average of the distance between all the sampling points and the transmitting device is close to '. By reading the data will be latitude and longitude conversion distance length, so that the maximum value as small as possible. The position of the launcher can be obtained by programming by MATLAB. When considering the altitude, only the position of the transmitting device can be changed. (9.7824,56.7720), and the position coordinates when considering the altitude are D (9.7459, 56.7586, 73.5645), and the position coordinate of the signal device is B (9.7824, 56.7720). For question three, note the effect of the original signal device A on the result. We still use the average of the distance between all the sampling points of the road and the launcher to characterize the stability of the signal reception. The average distance of all non-motorized trains to the original signal device A is first determined, and then the average distance of all non-motorized lanes from the new signal device B is set, and the signal acceptance strength of the non-motorized lane can be used to characterize. And then use the same method in question two to determine the location of the new signal transmitter. Finally, the coordinates of the position of the new signal device are E (9.7459,56.7586,73.5645).