Nature-Inspired Approach Using Seasonal Comparison of Wind Speed With Spectral and Statistical Analysis

Seasonal analysis of wind speed includes elements of its evaluation and analysis for wind energy production in complex geographical areas. These analyses require wind energy systems to be set up, integrated, operated, and designed according to seasonal differences. Istanbul wind speed data were collected hourly and analyzed seasonally. When the results of the analysis are examined, no significant increase in seasonal transitions was observed, while certain changes were observed between summer and winter. Here, statistical analysis, Weibull distribution function, and signal processing-based PSD analysis for wind speed is performed. In addition, correlation analysis was made between the seasons. Although significant results were obtained in signal-based analyses, results were obtained for seasonal transitions in correlation analyses. Seasonal spectral densities were calculated in the spectral analysis of wind speed data. This study has important implications in terms of extraction of seasonal characteristics of wind speed, resource assessment, operation, investment, and feasibility.

Seasonal analysis of food items and feeding habits of endangered riverine catfish Rita rita (Hamilton, 1822)

This investigation presents the food and feeding activity of and endangered riverine catfish Rita rita, during February 2017-January 2018. A total of 225 fish individuals was analyzed for stomach contents by characterizing the dominant food items and morphometric features. The results divulged ten major food items consumed, preferably fish scales and eggs, teleost fishes, copepods, cladocerans, rotifers, and mollusks. Total length and body weight of fish varied between 9-34 cm (20.53 ± 6.90 cm) and 10-400 g (9125.94 ± 102.07 g), respectively. The index of relative importance (IRI%) showed the importance of rotifers over the other food items. Morisita’s index of diet overlap indicated seasonal variations in catfish diets with summer and monsoon displaying the least overlap, while maximum overlap during monsoon and winter seasons. The non-metric multidimensional scaling (nMDS) indicated the close association between the food items available during summer and winter seasons with a significant difference among the seasons (ANOSIM, R = 0.638, P = 0.013). Levin’s niche breadth index arranged in the order of 0.88>0.81>0.78>0.63>0.43 for the size classes of V, IV, III, II and I, respectively. The PCA explained 95.39% of the total variance among the food items and fish size groups. Small-sized fish individuals displayed a greater correlation with food items suitable for their mouth size. In conclusion, the variety and frequency of food items recorded indicated considerable feeding plasticity and opportunistic feeding behavior with a shift from carnivorous to omnivorous feeding nature. This study could render useful information on the food and feeding habits of R. rita and provide background for preparing its diet for future aquaculture practices.

Energy efficiency using Distributed Generation; Cafeteria of Engineer Faculty Campeche, Mexico

In the present work, an integral design of the cafeteria located at Faculty of Engineering of Autonomous University of Campeche is carried out. Four scenarios of Photo Voltaic (PV) generation have been studied. A 14 PV modules arrangement of 440 each, with azimuthal angle of 180º and a slope angle of 15º; the other is similar to the previous, but the slope angle was 19.85º. The following was a 24 PV modules arrangement of 440, with an azimuthal angle of 218º and a slope angle of 15º. The last arrangement consists of 24 PV modules arrangement of 440, with azimuthal angle of 218º and a slope angle of 19.85º. Where all of them are associated with the economic aspect to obtain greater efficiency of the plant with minimum recovery time. The free software System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL) has been employed. Complete seasonal analysis has also been performed considering Gran Demanda Media Ordinaria en México (GDMO de CFE in Mexico) within the period January 2020 to March 2021. The best results are energy generation 17,570 kWh. Capacity factor 19%. Energy performance 1,671 kWh/kW. Performance relation 0.74. Leveled cost 5.39 ¢/kWh. And return on investment in 0.6 years. The GD-PV plant prevents the emission into the atmosphere of 778.85 kg of CO2 equivalent.

Assessment of the relationship of the population’s medical care with the factors of earth and space weather

Introduction. In recent years, the influence of climatic factors on population health has become particularly relevant. With significant fluctuations in meteorological conditions, there is an overstrain and failure of the adaptation. This leads to disorders of the functioning of the cardiovascular and central nervous systems. The purpose of the study is to assess the relationship of the population’s medical care with climatic factors, based on the available databases of indicators of Earth and space weather and data on the frequency of the population’s medical care. Material and Methods. For the analysis, we used a database of the population’s access to medical care and variations of climatic factors from 19.12.2005 to 31.12.2009 in the Kalininsky district of St. Petersburg. The total number of environmental parameters included in the study was 237, and the number of requests for medical care was 2.444. Results. In this paper, we tested a model for assessing the relationship between the population’s access to medical care and Earth and space weather factors. Gender and seasonal analysis were carried out. Time dependencies were studied. The obtained data allowed us to form a list of climate indicators that affect the health of the population. Conclusion. The most significant climatic indicators associated with coronary heart disease were identified. The most dangerous season of the year is autumn. Women have a higher sensitivity to changes in Earth and space weather than men. Accounting for variations in space weather allows predicting changes in medical treatment requests in 2-5 days, accounting for variations in the Earth’s weather - in 1 day.

INFLUENCE OF WEATHER PARAMETERS ON THE INCIDENCE OF ROOT ROT (MACROPHOMINA PHASEOLINA) DISEASE IN MULBERRY

Root rot disease caused by M. is the major disease in mulberry. The study was conducted in 50 mulberry gardens covering 15 villages during the year 2012-13 by adopting random sampling method. The present survey was taken up in the viz., Coimbatore, Erode, , , , and to assess the incidence of root diseases. The environmental factors that most seriously affect the initiation and development of infectious plant disease are temperature and humidity of the air, amount of rainfall, soil temperature, moisture and fertility. These factors affect disease development through their influence on the growth and susceptibility of the host, on the multiplication and activity of the pathogen or on the interaction of host and pathogen relates to the severity of symptom development. Correlation studies have revealed that average temperature plays the key role in disease incidence invariably in all the locations studied except district, which had no correlation with any of the weather variables, studied. root rot incidence attained peak during a particular period of a month where weather parameters like Temperature, Relative Humidity, Rainfall, Soil Moisture, and Soil Temperature were favorable. The root rot incidence will be minimum if all these conditions are unfavorable. Seasonal analysis revealed that South West Monsoon season was the predominant season for root rot incidence in mulberry. All the locations had peak incidence during SWM season only. The least occurrence had no specific season as it occurs in all the remaining three seasons.

Annual Rainfall in Pernambuco, Brazil: Regionalities, Regimes, and Time Trends

This study aimed to identify the homogeneous zones, the regimes, and the local trends for annual and seasonal rainfall in the state of Pernambuco, Brazil. We collected seasonal and annual data on monthly rainfall from 45 weather stations in Pernambuco from 1987 to 2019. The data were organized yearly to identify the homogeneous rainfall zones based on Euclidean distance and Ward's coefficient. The mean annual value of each zone was calculated and the data were subjected to descriptive statistics analysis, analysis of rainfall regime with the Rain Anomaly Index, and time trend analysis using the Mann-Kendall method. The results show three homogeneous rainfall zones: 1 (semiarid), 2 (transition), and 3 (coastal), with mean values for annual rainfall of 562, 1032, and 1812 mm year-1, respectively. The precipitation regime showed the predominance of dry years as zones 1, 2, and 3 exhibited dry periods of 18, 17, and 15 years, respectively. Time trend analysis revealed a decrease in annual rainfall of 48.7 mm for Zone 1, 13.2 mm for Zone 2, and 204.4 mm for Zone 3, without statistical significance. Seasonal analysis demonstrated that Zone 1 presented a negative trend in the spring and a positive trend in Zone 2 in the summer, indicating changes in the rain seasonality.