Genomic Variation: What Does It Mean?

New technologies have given us the ability to detect genomic variation at resolutions 50-100 times greater than earlier tests. The good news is that we can now detect variations that help explain developmental delays, autism, or multiple congenital anomalies in up to 20% of children. The bad news is that we can also detect small missing or extra pieces of chromosomes that remain unexplained: that is, we don’t know whether they have any clinical significance at all. The rapid pace of technological change may have outpaced the lab’s ability to interpret, providers’ abilities to explain, and patients’ abilities to understand the test results. This Issue Brief summarizes a series of studies examining the uncertainties revolving around chromosomal microarray testing, which has become the new standard of practice in genetic testing of children with unexplained anomalies

The impact of COVID-19 and the conflict in Ukraine on the return and risk of DJIA stocks

Every crisis has an impact on the global economy, on national economies and also causes disruptions in the financial market. Economic theory expects repeated economic crises. In the past, economic crises were mostly a rare phenomenon. Currently, the frequency of their outbreaks is higher. Therefore it can be assumed with certainty that the crisis caused by Covid-19 and the crisis caused by the conflict in Ukraine are not the last global crises that will affect the global economy and, therefore, the world financial and stock markets. In history, every recession in the stock markets was only temporary, so investing during a crisis is also of great opportunity, even if it has its peculiarities. When investing, the investor must emphasize a certain level of risk and the expected returns. The contribution aims to present the possible use of income and risk analysis in investment operations by investors so that an unquestionable certainty of the invested financial amount and a satisfactory return are ensured. The analysis of these indicators was carried out on historical data of selected components of the stock index Dow Jones Industrial Average (DJIA) in the pre-crisis period, in the crisis period caused by the Covid-19 virus, and in the crisis period caused by the war conflict in Ukraine. The presented approach of analysing the returns and risk of DJIA index shares provides the investor with an effective tool for deciding on the placement of available funds on the financial market in individual segments in all three monitored periods

The impact of COVID-19 and the conflict in Ukraine on the return and risk of DJIA stocks

Every crisis has an impact on the global economy, on national economies and also causes disruptions in the financial market. Economic theory expects repeated economic crises. In the past, economic crises were mostly a rare phenomenon. Currently, the frequency of their outbreaks is higher. Therefore it can be assumed with certainty that the crisis caused by Covid-19 and the crisis caused by the conflict in Ukraine are not the last global crises that will affect the global economy and, therefore, the world financial and stock markets. In history, every recession in the stock markets was only temporary, so investing during a crisis is also of great opportunity, even if it has its peculiarities. When investing, the investor must emphasize a certain level of risk and the expected returns. The contribution aims to present the possible use of income and risk analysis in investment operations by investors so that an unquestionable certainty of the invested financial amount and a satisfactory return are ensured. The analysis of these indicators was carried out on historical data of selected components of the stock index Dow Jones Industrial Average (DJIA) in the pre-crisis period, in the crisis period caused by the Covid-19 virus, and in the crisis period caused by the war conflict in Ukraine. The presented approach of analysing the returns and risk of DJIA index shares provides the investor with an effective tool for deciding on the placement of available funds on the financial market in individual segments in all three monitored periods

Location problem of Osmia cornuta nesting aids for optimum pollination.

The economic contribution of insect pollinators is evident as they contribute to higher crop yield quantity and quality. The management of bee species is key to crop production, especially where wild and domesticated bees are in low abundance. Several bee species have been identified as possible candidates for replacing, or at least supplementing, the decreasing number of honey bees. Our research seeks to address the location problem as regards nesting aids for Osmia cornuta bees in orchards using mathematical programming models for determining the optimal location of nesting aids and optimizing the management of solitary bees. A differential evolution algorithm is used to solve a location model of Osmia cornuta nesting aids for optimum pollination. Instead of a random ad hoc location of nesting aids in an orchard, or at the edge of an orchard, we utilize an effective optimization tool to determine locations which will optimize pollination by alternative pollinators, and increase the economic output of an agricultural business. The importance of this proposed model is likely to increase with agricultural intensification, and the decrease of the numbers of wild pollinators

Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis

Research background: Using the marginal means and contrast analysis of the target variable, e.g., claim severity (CS), the actuary can perform an in-depth analysis of the portfolio and fully use the general linear models potential. These analyses are mainly used in natural sciences, medicine, and psychology, but so far, it has not been given adequate attention in the actuarial field. Purpose of the article: The article's primary purpose is to point out the possibilities of contrast analysis for the segmentation of policyholders and estimation of CS in motor third-party liability insurance. The article focuses on using contrast analysis to redefine individual relevant factors to ensure the segmentation of policyholders in terms of actuarial fairness and statistical correctness. The aim of the article is also to reveal the possibilities of using contrast analysis for adequate segmentation in case of interaction of factors and the subsequent estimation of CS. Methods: The article uses the general linear model and associated least squares means. Contrast analysis is being implemented through testing and estimating linear combinations of model parameters. Equations of estimable functions reveal how to interpret the results correctly. Findings & value added: The article shows that contrast analysis is a valuable tool for segmenting policyholders in motor insurance. The segmentation's validity is statistically verifiable and is well applicable to the main effects. Suppose the significance of cross effects is proved during segmentation. In that case, the actuary must take into account the risk that even if the partial segmentation factors are set adequately, statistically proven, this may not apply to the interaction of these factors. The article also provides a procedure for segmentation in case of interaction of factors and the procedure for estimation of the segment's CS. Empirical research has shown that CS is significantly influenced by weight, engine power, age and brand of the car, policyholder's age, and district. The pattern of age's influence on CS differs in different categories of car brands. The significantly highest CS was revealed in the youngest age category and the category of luxury car brands

Chromosomal Microarray Testing in Children with Autism Spectrum Disorders: Clarifying Uncertainties and Improving Understanding

This workshop addresses the utilization of chromosomal microarray (CMA) testing for children with Autism Spectrum Disorder (ASD). We focus on the impact of uncertainties, explore how families understand and make meaning of CMA results, and suggest ways to reduce uncertainties in order to improve understanding and utilization of test results