Climate and vegetation are variables of the physical space that have a dynamic and interdependent relationship. Flora modifies climatic elements and gives rise to a microclimate whose characterization is a function of regional climatic conditions and vegetation structure. The objective of this work was to compare the climatic variations (inside and outside) of the Caldén Forest in the Parque Luro Provincial Reserve. Temperature, relative humidity, wind speed, wind direction and precipitation data from two meteorological stations for 2012 were analyzed and statistically compared. The influence of the forest on climatic parameters was demonstrated and it was found that the greatest variations were in wind speed, daily temperature and precipitation.

Using a newly developed data set, we analyze the effects of infrastructure investment on economic performance in Portugal. A vector-autoregressive approach estimates the elasticity and marginal products of twelve types of infrastructure investment on private investment, employment, and output. We find that the largest long-term accumulated effects come from investments in railroads, ports, airports, health, education, and telecommunications. For these infrastructures, the output multipliers suggest that these investments pay for themselves through additional tax revenues. For investments in ports, airports and education infrastructures, the bulk of the effects are short-term demand-side effects, while for railroads, health, and telecommunications, the impact is mostly of a long-term and supply-side nature. Finally, investments in health and airports exhibit decreasing marginal returns, with railroads, ports, and telecommunications being relatively stable. In terms of the other infrastructure assets, the economic effects of investments in municipal roads, electricity and gas, and refineries are insignificant, while investments in national roads, highways, and waste and waste water have positive economic effects but too small to improve the public budget. Clearly, from a policy perspective, not all infrastructure investments in Portugal are created equal.

A total of 25 SSR primers were screened on 37 putative F₁s derived from the five different crosses. Identified cross specific highly informative SSRs primers, i.e., 14 for the first cross, 10 for the second, 12 for the third and 6 each for fourth and fifth crosses. For the first cross Bhagwa × Daru 17, four primers (HvSSRT_375, NRCP_SSR9, NRCP_SSR12 and NRCP_SSR92) were found to be highly informative with higher 100% hybrid purity index (HPI), PIC (~0.52), and observed heterozygosity (Ho, range 0.87–0.93) values, and two F₁s namely H₁ and H₂ were found to be highly heterotic with a heterozygosity index (HI) of 92.85%. Similarly, for Bhagwa × Nana, three primers (HvSSRT_375, HvSSRT_605 and NRCP_SSR19) had higher HPI (70%–100%), PIC (0.52–0.69), and Ho (0.75–0.33) values, and three F₁s H₁, H₂, and H₄ had 70% (HI). For Bhagwa × IC318712, four SSRs (HvSSRT_254, HvSSRT_348, HvSSRT_826 and NRCP_SSR95) had higher Ho (~0.83), HPI (100%) and PIC (~0.52) values, and four F₁s H₂, H₇, H₉, and H₁₀ showed 91.66% (HI). For Bhagwa × Nayana, HvSSRT_605, HvSSRT_826, and HvSSRT_432, and for Ganesh × Nayana, HVSSRT_375, HVSSRT_605, and HvSSRT_826 were found informative. These markers will be highly useful in developing maps of populations.

Himalayan ‘Ecotone’ temperate conifer forest is the cradle of life for human survival and wildlife existence. Human intervention and climate change are rapidly degrading and declining this transitional zone. This study aimed to quantify the floristic structure, important value index (IVI), topographic and edaphic variables between 2019 and 2020 utilizing circular quadrant method (10m × 10m). The upper-storey layer consisted of 17 tree species from 12 families and 9 orders. Middle-storey shrubs comprise 23 species representing 14 families and 12 orders. A total of 43 species of herbs, grasses, and ferns were identified from the ground-storey layer, representing 25 families and 21 orders. Upper-storey vegetation structure was dominated by Pinus roxburghii (22.45%), while middle-storey vegetation structure was dominated by Dodonaea viscosa (7.69%). However, the ground layer vegetation was diverse in species composition and distribution. By using Ward’s agglomerative clustering technique, the floral vegetation structure was divided into three floral communities. Ailanthus altissima, Pinus wallichiana, and P. roxburghii had the highest IVI values in Piro–Aial (Group 2), Piwa–Quin (Group 3) and Aial–Qugal (Group 2). The IVI values for Aesculus indica, Celtis australis, and Quercus incana in Aial-Qugal (Group 2) were not determined. Nevertheless, eleven of these species had 0 IVI values in Piro–Aial (Group 2) and Piwa–Quin (Group 3). Based on the CCA ordination biplot, significant differences were observed in floral characteristics and distribution depending on temperature, rainfall, soil pH, altitude, and topographic features. Based on Ward’s agglomerative clustering, it was found that Himalayan ‘Ecotone’ temperate conifer forests exhibit a rich and diverse floristic structure.

Hybrid nanofluids have several potential applications in various industries, including electronics cooling, automotive cooling systems, aerospace engineering, and biomedical applications. The primary goal of the study is to provide more information about the characteristics of a steady and incompressible stream of a hybrid nanofluid flowing over a thin, inclined needle. This fluid consists of two types of nanoparticles: non-magnetic nanoparticles (aluminium oxide) and magnetic nanoparticles (ferrous oxide). The base fluid for this nanofluid is a mixture of water and ethylene glycol in a 50:50 ratio. The effects of inclined magnetic fields and joule heating on the hybrid nanofluid flow are considered. The Runge-Kutta fourth-order method is used to numerically solve the partial differential equations and governing equations, which are then converted into ordinary differential equations using similarity transformations. Natural convection refers to the fluid flow that arises due to buoyancy forces caused by temperature differences in a fluid. In the context of an inclined needle, the shape and orientation of the needle have significantly affected the flow patterns and heat transfer characteristics of the nanofluid. These analyses protest that raising the magnetic parameter results in an increase in the hybrid nanofluid thermal profile under slip circumstances. Utilizing the potential of hybrid nanofluids in a variety of technical applications, such as energy systems, biomedicine, and thermal management, requires an understanding of and ability to manipulate these effects.

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.