Results of EU Parliamentary Elections 2019. EU Centre Background Brief 30 May 2019

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Workpiece Alignment for Hybrid Laser Aided Part Repair Process

Work piece alignment is a key issue for hybrid laser aided part repair, a process utilizing both machining and laser deposition. Proper alignment can greatly improve the accuracy of the repair process. This paper introduces a method for aligning a physical work piece and a CAD model using a Renishaw touch probe and software tools. Also discussed is a model for computing 5-axis CNC positions based on a desired work piece orientation.Mechanical Engineerin

A Review of Layer Based Manufacturing Processes for Metals

The metal layered manufacturing processes have provided industries with a fast method to build functional parts directly from CAD models. This paper compares current metal layered manufacturing technologies from including powder based metal deposition, selective laser sinstering (SLS), wire feed deposition etc. The characteristics of each process, including its industrial applications, advantages/disadvantages, costs etc are discussed. In addition, the comparison between each process in terms of build rate, suitable metal etc. is presented in this paper.Mechanical Engineerin

A Bibliometric Analysis of the Intellectual Landscape of Mobile Technology and Higher Education Research

Technology has become a crucial part of higher education. Higher education institutions have adapted to embrace technology-enabled classroom practices to meet the rising expectations of a varied student population while continually enhancing their learning experience. Mobile technology in higher education, in particular, has the opportunity to provide access to or improve education at a low cost with a less demanding infrastructure configuration. In the current study, the researchers aimed to better understand the intellectual landscape of mobile technology and higher education through bibliometric analysis of research articles published in the Scopus database. This research included a study of 277 papers published in Scopus-indexed peer-reviewed journals between 2006 and 2023. The citation network, co-citation analysis, and publication patterns were examined to discover influential work in this domain. Bibliometric analysis was used to identify the most notable journals, authors, nations, articles, and topics, followed by thoroughly examining the content of 277 papers in the identified clusters. The four major themes enumerated are—Rise of mobile learning, E-learning—the blended and collaborative way, Mobile Technologies in higher education, and Student Engagement in the times of mobile learning. The paper provides interesting insights into these emerging themes, the study will assist regulators, policymakers, and academic scholars in understanding the fundamentals of mobile technology and higher education and identifying pertinent topics for further research

Algebraic construction of semi bent function via known power function

The study of semi bent functions (2- plateaued Boolean function) has attracted the attention of many researchers due to their cryptographic and combinatorial properties. In this paper, we have given the algebraic construction of semi bent functions defined over the finite field F₂ⁿ (n even) using the notion of trace function and Gold power exponent. Algebraically constructed semi bent functions have some special cryptographical properties such as high nonlinearity, algebraic immunity, and low correlation immunity as expected to use them effectively in cryptosystems. We have illustrated the existence of these properties with suitable examples.Publisher's Versio

Alzheimers Disease Diagnosis using Machine Learning: A Review

Alzheimers Disease AD is an acute neuro disease that degenerates the brain cells and thus leads to memory loss progressively. It is a fatal brain disease that mostly affects the elderly. It steers the decline of cognitive and biological functions of the brain and shrinks the brain successively, which in turn is known as Atrophy. For an accurate diagnosis of Alzheimers disease, cutting edge methods like machine learning are essential. Recently, machine learning has gained a lot of attention and popularity in the medical industry. As the illness progresses, those with Alzheimers have a far more difficult time doing even the most basic tasks, and in the worst case, their brain completely stops functioning. A persons likelihood of having early-stage Alzheimers disease may be determined using the ML method. In this analysis, papers on Alzheimers disease diagnosis based on deep learning techniques and reinforcement learning between 2008 and 2023 found in google scholar were studied. Sixty relevant papers obtained after the search was considered for this study. These papers were analysed based on the biomarkers of AD and the machine-learning techniques used. The analysis shows that deep learning methods have an immense ability to extract features and classify AD with good accuracy. The DRL methods have not been used much in the field of image processing. The comparison results of deep learning and reinforcement learning illustrate that the scope of Deep Reinforcement Learning DRL in dementia detection needs to be explored.Comment: 10 pages and 3 figure

Paradoxical Immune Responses in Non-HIV Cryptococcal Meningitis

The fungus Cryptococcus is a major cause of meningoencephalitis in HIV-infected as well as HIV-uninfected individuals with mortalities in developed countries of 20% and 30%, respectively. In HIV-related disease, defects in T-cell immunity are paramount, whereas there is little understanding of mechanisms of susceptibility in non-HIV related disease, especially that occurring in previously healthy adults. The present description is the first detailed immunological study of non-HIV-infected patients including those with severe central nervous system (s-CNS) disease to 1) identify mechanisms of susceptibility as well as 2) understand mechanisms underlying severe disease. Despite the expectation that, as in HIV, T-cell immunity would be deficient in such patients, cerebrospinal fluid (CSF) immunophenotyping, T-cell activation studies, soluble cytokine mapping and tissue cellular phenotyping demonstrated that patients with s-CNS disease had effective microbiological control, but displayed strong intrathecal expansion and activation of cells of both the innate and adaptive immunity including HLA-DR+ CD4+ and CD8+ cells and NK cells. These expanded CSF T cells were enriched for cryptococcal-antigen specific CD4+ cells and expressed high levels of IFN-gamma as well as a lack of elevated CSF levels of typical T-cell specific Th2 cytokines -- IL-4 and IL-13. This inflammatory response was accompanied by elevated levels of CSF NFL, a marker of axonal damage, consistent with ongoing neurological damage. However, while tissue macrophage recruitment to the site of infection was intact, polarization studies of brain biopsy and autopsy specimens demonstrated an M2 macrophage polarization and poor phagocytosis of fungal cells. These studies thus expand the paradigm for cryptococcal disease susceptibility to include a prominent role for macrophage activation defects and suggest a spectrum of disease whereby severe neurological disease is characterized by immune-mediated host cell damage

Determination of Transformation Matrix in a Hybrid Multi-Axis Laser-Aided Manufacturing System and its Practical Implementation

The Laser Aided Manufacturing Process (LAMP) is a multi-axis hybrid manufacturing process comprised of both an additive process, laser deposition, and a subtractive process, CNC machining. Determination of transformation matrix is one of the most important tasks to bridge the gap between process planning (software) and real deposition/machining process. The first part of the paper discusses an algorithm for computing the position of point/points in three-dimensional space, using homogenous transformation matrices. The second part of the paper discusses about how the algorithm was used in practice to build 3-D parts and part-repair using hybrid manufacturing process

Multijurisdictional Approach to Biosurveillance, Kansas City

An electronic reporting system for a network of 22 laboratories was implemented in Kansas City, Missouri, with an independent organization acting as a data clearinghouse between the reporting laboratories and public health departments. The system ran in tandem with conventional reporting methods. Laboratory test orders and results were aggregated and mapped to a common nomenclature. Reports were delivered through a secure Internet connection to the Kansas City Health Department (KCHD); during the first 200 days of operation, 359 qualified results were delivered electronically to KCHD. Data were received more quickly than they were with conventional reporting methods: notification of chlamydia cases arrived 2 days earlier, invasive group A streptococcal disease cases arrived 2.3 days sooner, and salmonellosis cases arrived 2.7 days sooner. Data were more complete for all demographic fields, including address, age, sex, race, and date of birth. Two hundred fourteen cases reported electronically were not received by conventional means