The objective of this work was to evaluate the combined effect of bovine manure, Pseudomonas putida and Trichoderma aureoviride on the development of lettuce (Lactuca sativa). The promotion of plant growth by microorganisms may be a viable and sustainable alternative for lettuce crop management. The experimental design was entirely randomized with five treatments: T0 (witness without fertilization, P. putida and T. aureoviride), TE (cattle manure), TEB (cattle manure + P. putida), TEF (cattle manure + T. aureoviride), TEFB (cattle manure + P. putida + T. aureoviride) and ten repetitions each. The following variables were analyzed: germination velocity index (GVI), first count (FC), germination percentage (GP), leaf area index and productivity. The TEFB treatment proved to be a viable alternative for the production of lettuce, especially for small producers, since all the vegetable production in the region comes from family farming.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

In this study, we utilized a convolutional neural network (CNN) trained on microscopic images encompassing the SARS-CoV-2 virus, the protozoan parasite “plasmodium falciparum” (causing of malaria in humans), the bacterium “vibrio cholerae” (which produces the cholera disease) and non-infected samples (healthy persons) to effectively classify and predict epidemics. The findings showed promising results in both classification and prediction tasks. We quantitatively compared the obtained results by using CNN with those attained employing the support vector machine. Notably, the accuracy in prediction reached 97.5% when using convolutional neural network algorithms.

This work shows the results of the biosynthesis of silver nanoparticles using the microalga Chlorella sp, using growth media with different concentrations of glycerol, between 5%–20%, and different light and temperature conditions. The synthesis of nanoparticles was studied using supernatants and pellets from autotrophic, heterotrophic and mixotrophic cultures of the microalga. The presence of nanoparticles was verified by ultraviolet-visible spectroscopy and the samples showing the highest concentration of nanoparticles were characterized by scanning electron microscopy. The mixotrophic growth conditions favored the excretion of exopolymers that enhanced the reduction of silver and thus the formation of nanoparticles. The nanoparticles obtained presented predominantly ellipsoidal shape with dimensions of 108 nm × 156 nm and 87 nm × 123 nm for the reductions carried out with the supernatants of the mixotrophic cultures with 5% and 10% glycerol, respectively.

Entrepreneurial motivation has been one psychological factor that determines the success of MSMEs as it interacts with external factors. However, this has been scarcely studied in relation to women and the success of MSMEs. This study aims to analyze the effects of motivation and external factors on the success of women running MSMEs in the province of Jambi, Indonesia. A survey research methodology through the distribution of questionnaires on the motivation scale and the success of the MSMEs scale that were constructed by the authors was applied. The rating scale of the questionnaires was rated on a five-point Likert scale. A total of 325 women running MSMEs in Jambi City were given and returned the questionnaires. The results showed that motivation, which is comprised of self-confidence, risk-taking, results-orientedness, intelligence, and skills, has a significant effect on the success of MSMEs. Meanwhile, the success of MSMEs is significantly more affected by time and length of effort than loans or funds due to the decreasing trend of demand for goods and services.