Tracing the Chromospheric and Coronal Magnetic Field with AIA, IRIS, IBIS, and ROSA Data

The aim of this study is to explore the suitability of chromospheric images for magnetic modeling of active regions. We use high-resolutionimages (≈0.2"-0.3"), from the Interferometric Bidimensional Spectrometer in the Ca II 8542 Å line, the Rapid Oscillations in the Solar Atmosphere instrument in the Hα 6563Å line, the Interface Region Imaging Spectrograph in the 2796Å line, and compare non-potential magnetic field models obtainedfrom those chromospheric images with those obtained from images of the Atmospheric Imaging Assembly in coronal (171 Å, etc.) and inchromospheric (304 Å) wavelengths. Curvi-linear structures are automatically traced in those images with the OCCULT-2 code, to which we forward-fitted magnetic field lines computed with the Vertical-current Approximation Nonlinear Force Free Field code. We find that the chromospheric images: (1) reveal crisp curvi-linear structures (fibrils, loop segments, spicules) that are extremely well-suited for constraining magnetic modeling; (2) that these curvi-linear structures arefield-aligned with the best-fit solution by a median misalignment angle of μ2 ≈ 4°–7° (3) the free energy computed from coronal data may underestimate that obtained from chromospheric data by a factor of ≈2–4, (4) the height range of chromospheric features is confined to h≲4000 km, while coronal features are detected up to h = 35,000 km; and (5) the plasma-β parameter is β ≈ 10^-5 - 10^-1 for all traced features. We conclude that chromospheric images reveal important magnetic structures that are complementary to coronal images and need to be included in comprehensive magnetic field models, something that is currently not accomodated in standard NLFFF codes.

Data for the co-expression and purification of human recombinant CaMKK2 in complex with calmodulin in Escherichia coli

Calcium/calmodulin-dependent kinase kinase 2 (CaMKK2) has been implicated in a range of conditions and pathologies from prostate to hepatic cancer. Here, we describe the expression in Escherichia coli and the purification protocol for the following constructs: full-length CaMKK2 in complex with CaM, CaMKK2 'apo', CaMKK2 (165-501) in complex with CaM, and the CaMKK2 F267G mutant. The protocols described have been optimized for maximum yield and purity with minimal purification steps required and the proteins subsequently used to develop a fluorescence-based assay for drug binding to the kinase, "Using the fluorescent properties of STO-609 as a tool to assist structure-function analyses of recombinant CaMKK2"

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

A Data Driven Tool supported CLD Creation Approach

The creation of Causal Loop Diagrams (CLDs) is a major phase in the System Dynamics (SD) life-cycle, since the created CLDs express dependencies and feedback in the system under study, as well as, guide modellers in building meaningful simulation models. The cre-ation of CLDs is still subject to the modeller's domain expertise (mental model) and her ability to abstract the system, because of the strong de-pendency on semantic knowledge. Since the beginning of SD, available system data sources (written and numerical models) have always been sparsely available, very limited and imperfect and thus of little benefit to the whole modelling process. However, in recent years, we have seen an explosion in generated data, especially in all business related domains that are analysed via Business Dynamics (BD). In this paper, we intro-duce a systematic tool supported CLD creation approach, which analyses and utilises available disparate data sources within the business domain. We demonstrate the application of our methodology on a given business use-case and evaluate the resulting CLD. Finally, we propose directions for future research to further push the automation in the CLD creation and increase confidence in the generated CLDs.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Outlier effects on robust joint modelling of longitudinal and survival data

Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

An Analysis of the Implementation and Perceived Effectiveness of the SchoolMAX Family Portal

ABSTRACT Title of Document: AN ANALYSIS OF THE IMPLEMENTATION AND PERCEIVED EFFECTIVENESS OF THE SCHOOLMAX FAMILY PORTAL Warren Wesley Watts, Doctor of Education, 2015 Directed By: Margaret J. McLaughlin, Ph.D. Department of Counseling, Higher Education and Special Education School districts have spent millions of dollars implementing student information systems that offer family portals with web-based access to parents and students. One of the main purposes of these systems is to improve school-to-home communication. Research has shown that when school-to-home communication is implemented effectively, parent involvement improves and student achievement increases (Epstein, 2001). The purpose of the study was to (a) understand why parents used or refrained from using the family portal and (b) determine what barriers to use might exist. To this end, this descriptive study identified the information parent users accessed in the SchoolMAX family portal, determined how frequently parents accessed the portal, and ascertained whether parents perceived an increase in communication with their children about academic matters after they began accessing the portal. Finally, the study sought to identify whether barriers existed that prevented parents from using the family portal. The inquiry employed three data sources to answer the aforementioned queries. These sources included (a) a survey sent electronically to 19,108 parents who registered online for the SchoolMAX family portal; (b) SchoolMAX portal usage data from the student information system for system usage between January 1, 2015 and June 30, 2015; and (c) a paper survey sent to 691 parents of students that had never used the SchoolMAX family portal in one elementary school, one middle school and one high school that were representative of other schools in the district. Survey results indicated that parents at all grade levels used the family portal. Usage data also confirmed that approximately 19% of the students had parents who monitored their progress through the family portal. Usage data also showed that parents were monitoring approximately 25% of students in secondary schools (6th – 12th grade) and 16% of students in elementary schools. Of the wide menu of resources available through the SchoolMAX family portal, parents used three areas most frequently: attendance, daily grades, and report cards. Approximately 70% of parents responded that their communication had improved with their children about academic matters since they started using the SchoolMAX family portal, and 90% of parents responded that the SchoolMAX family portal was an effective or somewhat effective tool. Parents also expressed interest in the addition of additional information to the SchoolMAX family portal. Specifically, the top three additions parents wanted to see included homework assignments, high stakes test scores, and graduation requirements. Parents also reported that 92% of them spoke to their children at least 2 to 3 times per week about academics. Due to the low response rate of the parent non-user survey, potential barriers to using the SchoolMAX family portal could not be addressed in this study. However, this issue may be a useful research topic in a future study. Keywords: school to home communication, student information systems, family portal, parent portal