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.

Several studies have discussed the benefits of blockchain in human resources management (HRM) policies to support the efficiency of HRM routine practices in organizations. The discussion ranges from selection and recruitment to employee separation. With the growing interest in digital application usage, research focused on utilization and effective measurement is needed. However, the existing literature review on blockchain-based HRM practices linked to cost efficiency still needs to be improved. Hence, this study aims to review current studies on blockchain human resources management systematically. This study investigates the trends in blockchain application usage in terms of practices, methodologies, and settings. This study used a literature survey and Publish or Perish software with Google Scholar and Scopus as the databases. 123 articles published in 19 journals from 2010 to 2022 were selected. This study used systematic data to reveal trends in HRM practices and qualitative inductive analysis to define relevant themes within the topic. The results show that blockchain applications for efficiency are used mainly in the recruitment and selection process, ranging from personal data verification to the quality of decision-making in skill development and maintenance. Five HRM practices have been discussed, indicating potential explorative and exploitative future research to improve the effectiveness of using blockchain in HRM practices.

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.

Modelling and simulation have now become standard methods that serve to cut the economic costs of R&D for novel advanced systems. This paper introduces the study of modelling and simulation of the infrared thermography process to detect defects in the hydroelectric penstock. A 3-D penstock model was built in ANSYS version 19.2.0. Flat bottom holes of different sizes and depths were created on the inner surface of the model as an optimal scenario to represent the subsurface defect in the penstock. The FEM was applied to mimic the heat transfer in the proposed model. The model’s outer surface was excited at multiple excitation frequencies by a sinusoidal heat flux, and the thermal response of the model was presented in the form of thermal images to show the temperature contrast due to the presence of defects. The harmonic approximation method was applied to calculate the phase angle, and its relationship with respect to defect depth and defect size was also studied. The results confirmed that the FEM model has led to a better understanding of lock-in infrared thermography and can be used to detect subsurface defects in the hydroelectric penstock.

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.