UWB linear array for 3D microwave imaging

Microwave imaging is being investigated by many research groups for its po- tential in medical diagnostic and treatment elds. Microwave signals are to sensitive to small changes into the dielectric properties of the objects under test which can be related to their physiological state. The use of UWB signals ( 3.1 - 10.6 GHz ) allow a good compromise between penetration and resolution. Moreover in the last years UWB frequency range has strongly exploited in med- ical imaging research eld, due to its characteristics of low-cost implementation and low-power used. The objective of this work is the design and the fabrication of multiplexed slot antenna array, that will be used in a 3D arrayed microwave tomographic system for medical imaging. This system is characterized by a rotation of mul- tiplexed linear antenna array around the object under test. With the aim of reducing the acquisition time it is replaced the vertical movement with a real antenna array. In the chapter 1 the introduction of medical imaging will be pre- sented and the system requirements are described. In the chapters 2 the basic concepts of UWB microstrip slot antennas and feeding methods will be analyzed respectively. In chapter 3 the individual array elements will be chosen and two array con gurations will be designed. In chapter 4 the feeding networks will be planned and simulated, the prototypes will be fabricated and the simulation data will be compared with measurement results. Finally the calibration will be done and the array con guration with the best performance will be chosen. In chapter 5 the conclusions will be deduced and the future works will be proposed

Atherosclerotic Cardiovascular Disease –The Gut Microbiome as a Risk Factor

As it remains, cardiovascular disease (CVD) has been the leading cause of mortality across the globe accounting for as many as 17.9 million deaths per year and projected to increase to more than 23.6 million deaths by 2030.1 Of the CVD related deaths, the majority are due to acute myocardial infarctions (AMI) and cerebral vascular accidents (CVA) and are associated with modifiable risk factors such as obesity, dyslipidemia, hypertension, and diabetes.2 Lifestyle modifications for decreasing these risk factors have been actively emphasized in healthcare, but do not eliminate the risks entirely. In addition to diet, exercise, and smoking cessation, other modifiable risk reduction should be explored. One area of particular interest pertains to the gut microbiome. As the understanding of gut health expands, the connections between microbiome disruptions and disease processes, such as cardiovascular disease, have suggested microbiota may affect health risks. Advances in the ability to analyze the plethora microbiota in the human gut have made it possible to both identify and quantify specific innate bacteria. This ability has provided a better understanding of the roles, functions, and potential alterations of the gut microbiome that are seen in various disease processes. Analyzing alterations of the gut microbiome, if any, in persons with CVD or its risk factors is a key first step. Then, identifying any associations between an altered gut microbiome and dietary ASCVD risk factors, specifically obesity and dyslipidemia, may enhance not only the understanding of the underlying pathophysiology, but also the prospects of finding means to reduce these risks

Considering the earth as common good: a key driver for innovation and competitiveness in business

Принимая во внимание то обстоятельство, что простые материалы, подтверждающие обоснованность тезиса «Земля является общим благом» заставляет корпорации проводить инновации и адаптировать новые бизнес-модели, которые увеличивают ценность продукции и значительно снижают ее стоимость за счет преобразования своей организации. Материалы статьи основаны на примерах взаимной выгодности.Taking into account the simple evidence “the Earth is a common good” brings corporations to innovate and adapt new business models that bring more value to their products and drastically reduce their cost through the reshaping of their organization. A lecture based on win-win examples

Change Point Detection for Process Data Analytics Applied to a Multiphase Flow Facility

Change point detection becomes increasingly important because it can support data analysis by providing labels to the data in an unsupervised manner. In the context of process data analytics, change points in the time series of process variables may have an important indication about the process operation. For example, in a batch process, the change points can correspond to the operations and phases defined by the batch recipe. Hence identifying change points can assist labelling the time series data. Various unsupervised algorithms have been developed for change point detection, including the optimisation approach which minimises a cost function with certain penalties to search for the change points. The Bayesian approach is another, which uses Bayesian statistics to calculate the posterior probability of a specific sample being a change point. The paper investigates how the two approaches for change point detection can be applied to process data analytics. In addition, a new type of cost function using Tikhonov regularisation is proposed for the optimisation approach to reduce irrelevant change points caused by randomness in the data. The novelty lies in using regularisation-based cost functions to handle ill-posed problems of noisy data. The results demonstrate that change point detection is useful for process data analytics because change points can produce data segments corresponding to different operating modes or varying conditions, which will be useful for other machine learning tasks

Academic Self-concept in University Students: Their Association with Parents’ Educational Level and Previous Experience in Higher Education

The aim of this research is to associate academic self-concept with the educational level of the parents and previous experiences of students in higher education. It is a cross-sectional study that evaluated 1093 students from a private university in Chile. The instruments used were the academic self-concept scale (ASCS), the variables of educational level of the parents and students previous experience in higher education. Bivariate correlations were made using the Spearman coefficient, associations using Pearson’s Chi-Square, and mean difference using the Mann-Whitney U between ASCS with the parents’ educational level and previous experience in higher education. The outcomes indicate correlation, association and mean difference (p < .05) between the ASCS and the educational level of the mother when she has university studies, as well as with the existence of previous experiences in higher education, being the father’s educational level of no significant impact. In conclusion, academic self-concept is greater when students have a mother with university studies and when they have previous experiences in higher education