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.

Agroforestry holds the key in providing alternative economically viable livelihood development and to support mountainous farmers to adapt to climate change. Innovative agroforestry interventions integrating animal production, horticulture etc into cropping systems exist that can help farmers improve yields and build resilience for supporting livelihoods particularly among marginal communities. But, the lack of knowledge, technical know-how and other information among the farmers are major barriers in adoption of agroforestry. Millions of the farmers of mountainous regions are already wrestling with water scarcity, which would be more severe in climate change scenario. The Himalayan regions are have been considered to be highly sensitive to climate change. Indeed, Innovative agroforestry interventions have the potential to conserve natural resources, improve productivity and provide resilience to climate change. The present paper highlights the need for developing innovative agroforestry interventions to promote various alternate livelihood options through diversification, adoption of high yielding varieties and development of innovative products from forest resources.  Of these spice based agroforetry, silvi-medicinal systems, Van silk cultivation, bamboo and ringal cultivation  and development and use of farm resources based products like  bamboo based composite structures, Seabuckthorn herbal tea, Ghingaroo juice  (Crataegus crenulata) and incense products etc holds a promising potential to be explored as better options for future scenario.

Cucumber Variety ‘Drite L108’ (Cucumis sativus L. Cv. Derit L108) was selected as the test material. In the solar greenhouse, different days (1, 3, 5, 7, 9 d) of light (PAR < 200 µmol·m^-2·s^-1) and normal light conditions were designed with shading nets to observe the growth indexes of cucumber plants and the changes of antioxidant enzyme activities in leaves. The results showed that: (1) continuous low light increased the SPAD (relative chlorophyll) value of cucumber leaves and decreased the net photosynthetic rate. The longer the continuous low light days are, the smaller the net photosynthetic rate of cucumber leaves and the worse the photosynthetic recovery ability would be. (2) The plant height, stem diameter and leaf area per plant were lower than CK, and the above indexes could not return to the normal level after 9 days of normal light recovery; the yield and marketability of cucumber fruit decreased under continuous low illumination. (3) The activities of SOD (superoxide dismutase) and POD (peroxidase) in cucumber leaves increased, the activities of CAT (catalase) first increased and then decreased, and the content of MDA (malondialdehyde) continued to increase. The longer the days of continuous light keep, the more seriously the cucumber leaves were damaged by membrane lipid peroxidation. After continuous light for more than 7 days, the metabolic function of cucumber leaves was difficult to recover to the normal level.

In this study, daily averages of air quality parameters were measured in two stations (S1 and S2) of the organized industrial district in Samsun. The meteorological variables were measured at only one station (S1), such as temperature, relative humidity, wind speed, solar radiation, and ambient pressure in 2007, and the daily promised limit for nitrogen dioxide has been especially exceeded at 206 times for 1^st station. However, exceeds of the limit value in 2006 for 1^st station was reduced by approximately 3.5 times. The daily nitrogen dioxide concentration did not exceed the daily limit of WHO^[1] as for 2^nd station. The results obtained showed that under the influence of dominant wind direction, the second station measurement results are higher than that of the first station. To determine all of the possible environmental effects, the measurements should be analyzed from a multi-point perspective.

Online transportation is a new type of service equipped with an internet network, and its presence in Indonesia is considered a service that disrupts the transportation sector. The government is faced with a complex policy problem to regulate online transportation. This article aims to reveal the role of policy actors in the media regarding policy issues and online transportation policy solutions. This article used qualitative analysis and the NPF policy narrative framework approach. This study found that licensing issues and Permenhub were problems that the DIY and Riau governments shared. More specific problems in Riau Province are related to violence issues, and that in DIY are related to congestion problems. The policy solution recommended by policy actors to the media is to make regional level regulations that technically regulate online transportation according to the area conditions.

Photocatalysis, an innovative technology, holds promise for addressing industrial pollution issues across aqueous solutions, surfaces, and gaseous effluents. The efficiency of photodegradation is notably influenced by light intensity and duration, underscoring the importance of optimizing these parameters. Furthermore, temperature and pH have a significant impact on pollutant speciation, surface chemistry, and reaction kinetics; therefore, process optimization must consider these factors. Photocatalytic degradation is an effective method for treating water in environmental remediation, providing a flexible and eco-friendly way to eliminate organic contaminants from wastewater. Selectivity in photocatalytic degradation is achieved by a multidisciplinary approach that includes reaction optimization, catalyst design, and profound awareness of chemical processes. To create efficient and environmentally responsible methods for pollution removal and environmental remediation, researchers are working to improve these components.