In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

Phytochemical and antioxidant analysis of some varieties of Capsicum was evaluated. Mature Capsicum varieties were collected across the State. The seeds were removed, sun-dried for 3 days, stored for 2 weeks at 15 ºC–25 ºC in polythene bags before planting. Saponins, tannins, flavonoids, alkaloids and cardiac glycosides were present in abundant, moderate and trace amounts. Combined anthraquinones were absent in all varieties. Yellow (0.810 ± 0.0006 µg/mL), red long dry (0.211 ± 0.0006 µg/mL) and round peppers (2.527 ± 0.0003 µg/mL) had the largest values for total phenol, flavonoids and tannins. Shombo and yellow peppers had the largest (0.270 ± 0.002 µg/mL) and least (0.102 ± 0.001 µg/mL) capsaicin content. The antioxidant activities varied across the varieties. At 100 µg/mL of methanol, yellow (45%) and round peppers (45%) had largest mean absorbances for 2,2-Diphenyl-1-Picrylhydrazyl (DPPH) Radical Scavenging Activity while sub-shombo pepper (23%) had the least. For Ferric Reducing Antioxidant Power (FRAP), yellow (0.63 ± 0.001 µg/mL) and sub-shombo peppers (0.55 ± 0.001µg/mL) had the largest and least values at 100 µg/mL of methanol. At 100 µg/mL of methanol, red long dry (0.112 ± 0.001) and shombo peppers (0.101 ± 0.001) had the largest and least values for the nitric oxide scavenging activity. This study shows that Capsicum varieties exhibit bioactive componds similarities and variations with implications in hybridization, taxonomy and conservation.

Objective: This study aimed to examine the psychometric properties of the 21-item Depression, Anxiety, and Stress Scale (DASS-21) in a sample of Moroccan students. Method: A total of 208 Moroccan students participated in this study. The dimensionality of the DASS-21 scale was assessed using exploratory factor analysis. Construct validity was assessed using the Stress Perception (PSS-10), State Anxiety (SAI), and Depression (CESD-10) scales. Results: Correlation analyses between Depression, Anxiety, and Stress subscales showed significant results. The exploratory factor analysis results confirmed the DASS’s three-dimensional structure. Furthermore, correlation analyses revealed positive correlations between the DASS-18 sub-dimensions and the three scales for Stress (PSS-10), Anxiety (SAI), and Depression (CESD-10). Conclusion: In line with previous work, the results of this study suggest that the DASS-18 reflect adequate psychometric properties, making it an appropriate tool for use in the university context.

Peru is a country open to the world economy and to national and foreign investments; therefore, economic activities of an industrial, commercial and service nature in general are developed. It also has a wide variety of natural resources, which is why the state has chosen to apply differentiated treatment in the tax field to certain types of business activities by granting certain “benefits” and “incentives”. However, due to a lack of knowledge about tax legislation, they are not used adequately. In this context, the objective was to analyze the level of knowledge of the legislation, tax and its impact on the development of their operations in formal business aquaculture in the ring circumlacustrine of the region in 2021. It was developed under a descriptive correlational design with a sample of 80 circumlacustrine ring aquaculture companies. The results indicated that there is a low level of knowledge about tax legislation on the part of the owners of aquaculture companies, which negatively affects the development of their formal operations in the circumlacustrine ring of the Puno region. As a consequence, it has a negative impact on the formalization of companies since they do not know about the benefits and tax incentives and even less about the tax regimes to which they are subject as taxpayers; therefore, aquaculture companies are in the informality category in a high percentage.

Nanocomposites are high performance materials which reveal rare properties. Nanocomposites have an estimated annual growth rate of 25% and fastest demand to be in engineering plastics and elastomers. Their prospective is so prominent that they are valuable in numerous areas ranging from packaging to biomedical applications. In this review, the various types of matrix nanocomposites are discussed highlighting the need for these materials, their processing approaches and some recent results on structure, properties and potential applications. Perspectives include need for such future materials and other interesting applications. Being environmentally friendly, applications of nanocomposites propose new technology and business opportunities for several sectors of the aerospace, automotive, electronics and biotechnology industries.

Mobile banking has become very important in today’s life as technological advancements have led bank clients to use banking services. Clients’ attitudes toward mobile banking services are based on their expectations is the background of this research. So, the main objective is to observe the purposeful conduct in mind of clients to adopt mobile banking services. This study also examines the influence of six variables on financial services clients’ desire to utilize mobile banking services, including perceived benefits, perceived ease of use, trust, security, perceived privacy, and technology expertise. Consequently, the goal of this study is to find out the crucial and deciding factors that may influence clients’ willingness to use mobile banking features in Bangladesh as a developing country. The sample shaped for this research is 310 respondents from Bangladesh a developing country. For analytical purposes, SEM has been used to test hypotheses. The results show that in Bangladesh, factors like perceived value, security, and technological aptitude greatly determine whether a customer will utilize mobile banking. Financial institutions have proven to be successful in serving clients through mobile phones. Clients have made good use of mobile banking only to save money, cost, and labor. The research suggests that mobile banking operations must be timely and accurate, the transaction process must be short, interactivity, convenience of usage, and so on. The findings have important implications for bank regulatory authority, management, bankers, and executives who wish to increase mobile banking usage to secure their long-term profitability.