Calamintha nepeta (L.) Savi and its main essential oil constituent pulegone: biological activities and chemistry

Medicinal plants play an important role in the treatment of a wide range of diseases, even if their chemical constituents are not always completely recognized. Observations on their use and efficacy significantly contribute to the disclosure of their therapeutic properties. Calamintha nepeta (L.) Savi is an aromatic herb with a mint-oregano flavor, used in the Mediterranean areas as a traditional medicine. It has an extensive range of biological activities, including antimicrobial, antioxidant and anti-inflammatory, as well as anti-ulcer and insecticidal properties. This study aims to review the scientific findings and research reported to date on Calamintha nepeta (L.) Savi that prove many of the remarkable various biological actions, effects and some uses of this species as a source of bioactive natural compounds. On the other hand, pulegone, the major chemical constituent of Calamintha nepeta (L.) Savi essential oil, has been reported to exhibit numerous bioactivities in cells and animals. Thus, this integrated overview also surveys and interprets the present knowledge of chemistry and analysis of this oxygenated monoterpene, as well as its beneficial bioactivities. Areas for future research are suggested

The application of prolate spheroidal wave functions to the detection and estimation of bandlimited signals

Prolate spheroidal wave functions for solution of Fredholm equation for bandlimited signal detectio

Band limited image restoration by linear mean-square estimation

Linear estimator optimum for data on finite interval for restoration of image

Application of Neural Network Methods Based on Genetic Algorithm for Breast Cancer Prediction

Cancer is a major challenge for mankind. Cancer can affect various parts of the body. This deadly disease can be detected in people of all ages. However, the risk of cancer increases with increasing age. Breast cancer is the most common cancer among women, and form largest cause of death for women as well. Then there are problems in the detection of breast cancer, resulting in the patient experiencing unnecessary treatment and cost. Insimilar studies, there are several methods used but there are problems due to the shape of the cancer cells are nonlinear. Neural networks can solve these problems, but neural network is weak in terms of determining the value of the parameter, so it needs to be optimized. Genetic algorithm is one of the optimization methods is good, therefore the values ​​of the parameters of the neural network will be optimized by using a genetic algorithm so as to get the best value of the parameter. Neural Network-based GA algorithm has the higher accuracy value than just using Neural Network algorithm. This is evident from the increase in value for the accuracy of the model Neural Network algorithm by 95.42% and the accuracy of algorithm-based Neural Network algorithm GA (Genetic Algorithm) of 96.85% with a difference of 1.43% accuracy. So it can be concluded that the application of Genetic Algorithm optimization techniques to improve the accuracy values on Neural Network algorithm

MIGRATION AND HUMAN CAPITAL IN ITALIAN AGRICULTURAL LABOUR MARKET: A CASE STUDY ANALYSIS

During the last years Italy, a country characterized by a long history of emigration, has seen a quickly growth of the phenomenon of immigration. Our Nation seems to be a “docking point” for new and substantial flow of immigrants mainly from Eastern Europe looking for new work opportunities. The profile of these people is usually characterized by high level of education as well as flexibility and adaptability. For the national economy in general, and for the agricultural sector in particular, this new migration flows represent an effective answer to the aversion for the agricultural job expressed by many potential autochthon workers. Which are the characteristics of extra-community agricultural labour? Which are the characteristics of migration flows linked to the agricultural labour in three provinces of one of the main agricultural regions in Italy? Based on National Institute of Welfare information’s (INPS), the research underlines the diversification of this phenomenon among Italian regions as well as its dynamism. In Italy, during the last five years, the proportions of foreign agricultural workers increased up to 50%, and peaked in four Italian regions: Friuli Venezia Giulia, Campania, Piemonte and Emilia-Romagna. In Emilia-Romagna, in particular, immigrants represent almost a quarter of total agricultural workers and most of them aged less than forty years. The analysis of information about labour market in the agricultural sector in some Emilia-Romagna provinces shows that immigrants are concentrated in few farms. Farmer prefers to engage homogeneous ethnic groups to assure cultural affinity among the employees. In the local agricultural labour market the immigrants coming from Eastern Europe, in particular from Poland and Romania, are aged between 22 and 36 years, are unemployed in their country, they have a driving license and a good knowledge of Italian and English language.Agricultural Labour Markets, Immigrant Workers, Human Capital, Skills, Agribusiness, Labor and Human Capital, J43, J61, J24,

The Influence of Work-Family Conflict, Workload, and Work Pressure as Mediating Variables on the Performance of Female Employees

Purpose – The main purpose of this study was to assess how Work-Family conflict, workload, and work stress function as mediating factors influencing the performance of female employees at BPS (Central Bureau of Statistics) in the West Sumatra Province.  Methodology – This quantitative investigation was conducted using a survey approach, with the sample consisting of 188 married or formerly married female employees out of a total of 128 participants. A questionnaire was used as an instrument which was designed using Google form and consisted of 58 questions. Furthermore, the sampling was carried out using Cluster Sampling, with districts/cities serving as the clusters. Descriptive statistical and Partial Least Square (PLS) analyses were adopted for the data analysis process using the Smart PLS 3.2.3 program. Findings – The results showed that workload and Work-Family conflict had a positive influence on both work pressure and the performance of female employees. Meanwhile, Work-Family conflict and work pressure negatively influenced the performance of female employees. A negative influence was also observed on the performance of women employees due to Work-Family conflict, mediated through work pressure. Originality – This research investigated the influence of Work-Family conflict and workload on the performance of women employees, mediated by job pressure