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.

Eco-friendly and greener barrier materials are required to replace the synthetic packaging materials as they produce a threat to environment. These can be fabricated by natural polymers such as cellulose nanofiber (CNF). The sustainability of CNF was so amazing due to its potential for circular economy and provides alternative platform for synthetic plastics. The challenging task to fabricate CNF films still existed and also current methods have various limitations. CNF films have good oxygen permeability and the value was lower than synthetic plastics. However, CNF films have poor water vapour permeability and higher than that of synthetic plastics. The fabrication method is one of strong parameters to impact on the water permeability of CNF films. The deposition of CNF suspension on the stainless-steel plate via spraying, is a potential process for fabrication for CNF films acting as barrier material against water vapour. In spraying process, the time required to form CNF films in diameter of 15.9 cm was less than 1 min and it is independent of CNF content in the suspension. The uniqueness of CNF films via the spraying process was their surfaces, such as rough surface exposed to air and smooth surface exposed to stainless steel. Their surfaces were investigated by SEM, AFM and optical profilometry micrographs, confirming that the smooth surface was evaluated notable lower surface roughness. The spray coated surface was smooth and glossy and its impact on the water vapor permeability remains obscure. The spraying process is a flexible process to tailor the basis weight and thickness of CNF films can be adjusted by the spraying of CNF suspension with varying fibre content. The water vapour permeability of CNF films can be tailored via varying density of CNF films. The plot between water vapour transfer rate (WVTR)/water vapour and density of CNF films has been investigated. The WVP of spray coated CNF films varied from 6.99 ± 1.17 × 10⁻¹¹ to 4.19 ± 1.45 × 10⁻¹¹ g/m.s.Pa. with the density from 664 Kg/m³ to 1,412.08 Kg/m³. The WVP of CNF films achieved with 2 wt% CNF films (1,120 Kg/m³) was 3.91 × 10⁻¹¹ g/m.s.Pa. These values were comparable with the WVP of synthetic plastics. Given this correspondence, CNF films via spraying have a good barrier against water vapour. This process is a potential for scale up and commercialization of CNF films as barrier materials.

This study provides an empirical examination of the design and modification of China’s urban social security programme. In doing so, this study complements the popular assumption regarding the correlation between economic growth and social security development. Focusing on the economic and political motivations behind the ruling party’s decision to implement social security, this study first discusses the modification of urban social security and welfare in China. It then empirically demonstrates the mechanisms behind the system’s operation. This study proposes the following hypothesis: in a country like China, a change in the doctrine of the ruling party will affect government alliances, negating the positive impact of economic growth on the development of social security. In demonstrating this hypothesis, this study identifies a political precondition impacting the explanatory power of popular conceptions of social security development.

In most studies on hydroclimatic variability and trend, the notion of change point detection analysis of time series data has not been considered. Understanding the system is crucial for managing water resources sustainably in the future since it denotes a change in the status quo. If this happened, it is difficult to distinguish the time series data’s rising or falling tendencies in various areas when we look at the trend analysis alone. This study’s primary goal was to describe, quantify, and confirm the homogeneity and change point detection of hydroclimatic variables, including mean annual, seasonal, and monthly rainfall, air temperature, and streamflow. The method was employed using the four-homogeneity test, i.e., Pettitt’s test, Buishand’s test, standard normal homogeneity test, and von Neumann ratio test at 5% significance level. In order to choose the homogenous stations, the test outputs were divided into three categories: “useful”, “doubtful”, and “suspect”. The results showed that most of the stations for annual rainfall and air temperature were homogenous. It is found that 68.8% and 56.2% of the air temperature and rainfall stations respectively, were classified as useful. Whereas, the streamflow stations were classified 100% as useful. Overall, the change point detection analyses timings were found at monthly, seasonal, and annual time scales. In the rainfall time series, no annual change points were detected. In the air temperature time series except at Edagahamus station, all stations experienced an increasing change point while the streamflow time series experienced a decreasing change point except at Agulai and Genfel hydro stations. While alterations in streamflow time series without a noticeable change in rainfall time series recommend the change is caused by variables besides rainfall. Most probably the observed abrupt alterations in streamflow could result from alterations in catchment characteristics like the subbasin’s land use and cover. These research findings offered important details on the homogeneity and change point detection of the research area’s air temperature, rainfall, and streamflow necessary for the planers, decision-makers, hydrologists, and engineers for a better water allocation strategy, impact assessment and trend analyses.

The performance of five cauliflower cultivars in conventional and alternative phytosanitary management—without the use of synthetic pesticides—was evaluated. Two experiments were conducted at Epagri, Ituporanga Experimental Station in February 2018 and 2019. A randomized block design with four repetitions was adopted, with twenty plants of each cultivar as plots. The seedlings were transplanted on millet and mucuna straw at a spacing of 0.5 m × 0.8 m. We evaluated agronomic yield, inflorescence quality, pest damage and plant diseases, especially bacterial and fungal rots. The cauliflower hybrids Vera, Verona and Serena stood out in productivity and quality, being the most indicated for sowing in off-season crops, in the Alto Vale do Itajaí region. The most productive cultivars were less damaged by bacterial diseases and defoliating caterpillars and without interference of whitefly infestation on yield. The results also reveal that it is possible to control pests and diseases with phytosanitary products of lower toxicity, i.e., with lower residues of synthetic pesticides.

The xanthorrhiza species of the genus Arracacia belongs to the Apiaceae family and is known for its ability to generate tuberous reservoir roots that are harvested annually and marketed fresh in South American countries such as Colombia, Brazil, Venezuela, Peru, Bolivia and Ecuador. In Colombia, arracacha is planted mainly in 15 departments and the regional cultivars are differentiated by the color of the leaves, petiole and tuberous root, the best known being amarilla común or paliverde, yema de huevo, and cartagenera. There are studies that have characterized regional materials by applying a limited number of descriptors, but they do not allow knowing the morphology and phenotypic differentiation of each one; therefore, their definition and characterization constitute a support in breeding programs that allow the efficient use of the genetic potential and increase the knowledge about the diversity of cultivars. Phenotypic characterization and description of three cultivars was performed during two production cycles (2016 and 2018) in two phases (vegetative and productive) applying 74 morphological variables (42 qualitative and 32 quantitative) organized in seven groups of variables: plant, leaf, leaflet, petiole, propagule, stock and tuberous root. A factorial analysis for mixed data (FAMD) was performed, which incorporated a multivariate analysis with all variables and identified 11 discriminant variables, 8 qualitative and 3 quantitative, which can be used in processes of characterization of arracacha materials. A morphological description of each cultivar was made, which means that this is the first complete characterization study of regional arracacha materials in Colombia.