ZrO₂ thin film samples were produced by the sol-gel dip coating method. Four different absorbed dose levels (such as ~ 0.4, 0.7, 1.2 and 2.7 Gray-Gy) were applied to ZrO₂ thin films. Hence, the absorbed dose of ZrO₂ thin film was examined as physical dose quantity representing the mean energy imparted to the thin film per unit mass by gamma radiation. Modification of the grain size was performed sensitively by the application of the absorbed dose to the ZrO₂ thin film. Therefore the grain size reached from ~50 nm to 87 nm at the irradiated ZrO₂ thin film. The relationship of the grain size, the contact angle, and the refractive index of the irradiated ZrO₂ thin film was investigated as being an important technical concern. The irradiation process was performed in a hot cell by using a certified solid gamma ray source with 0.018021 Ci as an alternative technique to minimize the utilization of extra toxicological chemical solution. Antireflection and hydrophilic properties of the irradiated ZrO₂ thin film were slightly improved by the modification of the grain size. The details on the optical and structural properties of the ZrO₂ thin film were examined to obtain the optimum high refractive index, self-cleaning and anti-reflective properties.

Simple mathematical expressions are given for the betweenness centrality of nodes in trees, forests and cycles. As application, a centrality test is given for when a network might be a forest.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

Forest is the main carbon sink of terrestrial ecosystem. Due to the unique growth characteristics of plants, the response of their growth status and physiological activities to climate change will affect the carbon cycle process of forest ecosystem. Based on the local scale CO₂ flux and temperature observation data recorded by the FLUXNET registration site and Harvard Forest FLUX observation tower from 2000 to 2012, combined with the phenological model, this paper analyzes the impact of temperature changes on CO₂ flux in temperate forest ecosystems. The results show that: (1) the maximum NEE in 2000–2012 was 298.13 g·m^-2·a^-1, which occurred in 2010. Except in the 2010 and 2011, the annual NEE in other years was negative. (2) NEE, GPP, temperature and phenology models have good fitting effects (R² > 0.8), which shows that the stable period of photosynthesis in temperate mixed forest ecosystem is mainly concentrated in summer, and vegetation growth is the dominant factor of carbon cycle in temperate mixed forest ecosystem. (3) The linear fitting results of the change time points of air temperature (maximum point, minimum point and 0 point date) and the change time points of NEE and GPP (maximum point, minimum point and 0 point date) show that there is a significant positive correlation between air temperature and CO₂ flux (P < 0.01), and the change of air temperature affects the carbon cycle process of temperate mixed forest ecosystem.

Due to its physicochemical properties, nanoparticles titanium dioxide (nTiO₂) is being put into mass production and widespread applications, which inevitably results in their increasing exposure to the water body. After it entering the water body, the chemical properties of nTiO₂ can be influenced by ion compositions, ion strength and pH, which affects their ecological risk. Excess of ammonium (NH₄⁺) fertilizer has contaminated soil and water environments. In this paper, the Zeta potentials and hydrodynamic radius of nTiO₂ were studied in NH₄⁺ solution compared to those in Na⁺ solution. In addition, the sedimentation rate of nTiO₂ was also investigated. The experiment results show that high pH inhibits the sedimentation of nTiO₂. Moreover, NH₄⁺ increases the stability of nTiO₂ more than Na⁺ at the same IS, which was attributed the more negative Zeta potentials and the smaller hydraulic radius. Our results provide a theoretical basis for evaluating the ecological risk of nTiO₂ in aqueous solution containing NH₄⁺.