Discovering and Understanding High Performance Materials using Density Functional Theory: Quantum Mechanical Simulations and the Consequences of Symmetry

There are two primary ways that atomic level modeling data is used: materials prediction and understanding materials properties. This dissertation work encom- passes two studies, each of which explore one application. Both studies rely on the highly successful density functional theory (DFT) formalism but differ in that two different implementations of DFT are used on two different high performance materials. The first study on bulk magnesium (Mg) metal alloys explores materials prediction and relies on VASP, a commercially maintained plane-wave DFT code which has been used extensively to successfully study a wide range of materials. [1] The approach used in this first study is to ‘experiment’ within computational quantum mechanical simulations to improve the elastic properties of bulk Mg by altering its HCP lattice structure. We systematically study the influence of adding lithium (Li) as an alloy for two reasons: to maintain the lightweight benefits of Mg, and Li naturally occurs in a body centered cubic (BCC) crystal structure. The hypothesis is that an alloy with a more symmetric crystal structure will show im- proved properties, however we do not place any symmetry restrictions on the results of the structure search. We find that the addition of Li to Mg does improve the elastic properties of the resulting alloys; however it does not necessarily increase the symmetry. Five structures are found which belong to the convex hull, three of which are previously unreported. The second DFT study seeks to understand the electronic environment within lead sulfur (PbS) semiconductor nano-structures and utilizes the open-source Octopus code, designed for electron-ion dynamics in finite systems using time-dependent DFT in real time and real space and which has also been bench-marked extensively [2]. The aim of the second study is to understand at the most fundamental levels the impact reduced symmetry has on the electronic states and transitions at the level of the individual IR-light-absorbing quantum dot. We employ three toy models to isolate the impacts of reduced coordination, Pb-rich structures, and Peierls distortions. An in-depth analysis of the bonding through the charge density and electron localization function shows that the metavalent bonding observed in bulk PbS persists in the nanoscale regime. Changing the stoichiometry too far away from Pb:S = 1:1 results in the loss of semiconducting character and an overall metallic character prevails. When we place particular attention on the effects of atomic coordination, we observe enhanced electron localization clustered around the lowest coordinated atoms. Peierls distortions intensify the clustering behavior which lowers the energy of the occupied electronic states and increases the energy of the unoccupied states as deduced from density of states plots. The change in the electron localization is substantial only for a significant amount of low-coordinated atoms. A conclusion is made with an outlook to future work

Impact of demographic factors on recognition of persons with depression and anxiety in primary care in Slovenia

Background: Research has repeatedly shown that family physicians fail to diagnose up to 70% of patients with common mental disorders. Objective of the study is to investigate associations between persons' gender, age and educational level and detection of depression and anxiety by their family physicians.Methods: We compared the results of two independent observational studies that were performed at the same time on a representative sample of family medicine practice attendees in Slovenia. 10710 patients participated in Slovenian Cross-sectional survey and 1118 patients participated in a first round of a cohort study (PREDICT-D study). Logistic regression was used to examine the effects of age, gender and educational level on detection of depression and anxiety.Results: The prevalence of major depression and Other Anxiety Syndrome (OAS) amongst family practice attendees was low. The prevalence of Panic Syndrome (PS) was comparable to rates reported in the literature. A statistical model with merged data from both studies showed that it was over 15 times more likely for patients with ICD-10 criteria depression to be detected in PREDICT-D study as in SCS survey. In PREDICT-D study it was more likely for people with higher education to be diagnosed with ICD-10 criteria depression than in SCS survey.Conclusion: People with higher levels of education should probably be interviewed in a more standardized way to be recognised as having depression by Slovenian family physicians. This finding requires further validation

Design and Calibration of a Lightweight Physics-Based Model for Fluid-Mediated Self-Assembly of Robotic Modules

In this paper, we consider a system consisting of multiple floating robotic modules performing self-assembly. Faithfully modeling such a system and its inter-module interactions typically involves capturing the hydrodynamic forces acting on the modules using computationally expensive fluid dynamic modeling tools. This poses restrictions on the usability of the resulting models. Here, we present a new approach towards modeling such systems. First, we show how the hardware and firmware of the robotic modules can be faithfully modeled in a high-fidelity robotic simulator. Second, we develop a physics plugin to recreate the hydrodynamic forces acting on the modules and propose a trajectory-based method for calibrating the plugin model parameters. Our calibration method employs a Particle Swarm Optimization (PSO) algorithm, and consists of minimizing the difference between Mean Squared Displacement (MSD) data extracted from real and simulated trajectories of multiple robotic modules

Diversity and distribution of co-infecting Botryosphaeriaceae from Eucalyptus grandis and Syzygium cordatum in South Africa

Species in the fungal family Botryosphaeriaceae are latent pathogens on woody trees. These fungi often have a wide host range, which can include native and introduced hosts in an area. Multi-locus DNA sequence identification on a recent collection of Botryosphaeriaceae from Eucalyptus grandis and Syzygium cordatum trees in South Africa revealed cross-infectivity of several species, novel host associations and new country reports. Neofusicoccum eucalyptorum, Neofusicoccum kwambonambiense, Neofusicoccum parvum, Neofusicoccum australe and Lasiodiplodia pseudotheobromae were identified from both tree species, with L. pseudotheobromae and N. eucalyptorum isolated for the first time from S. cordatum, similar to N. kwambonambiense from Eucalyptus. This also represents the first report of L. pseudotheobromae from South Africa. Botryosphaeriaceae species on Eucalyptus species and S. cordatum are fairly well known from South Africa. However, this study revealed new associations, indicating that conclusions should not be generalized and that more intensive sampling from different areas and over time is likely to reveal distinct species and host association patterns.The National Research Foundation (NRF), members of the Tree Protection Co-operative Programme (TPCP) and the Department of Science and Technology (DST)/NRF Centre of Excellence in Tree Health Biotechnology (CTHB), South Africa. Open Access funded by SAAB.http://www.elsevier.com/locate/sajbhb2016Forestry and Agricultural Biotechnology Institute (FABI)Genetic

Greater impairment of postprandial triacylglycerol than glucose response in metabolic syndrome subjects with fasting hyperglycaemia

Abstract Objective: Studies have started to question whether a specific component or combinations of metabolic syndrome (MetS) components may be more important in relation to cardiovascular disease risk. Our aim was to examine the impact of the presence of raised fasting glucose as a MetS component on postprandial lipaemia. Methods: Men classified with the MetS underwent a sequential test meal investigation, in which blood samples were taken at regular intervals after a test breakfast (t=0 min) and lunch (t=330 min). Lipids, glucose and insulin were measured in the fasting and postprandial samples. Results: MetS subjects with 3 or 4 components were subdivided into those without (n=34) and with (n=23) fasting hyperglycaemia (≥ 5.6 mmol/l), irrespective of the combination of components. Fasting lipids and insulin were similar in the two groups, with glucose significantly higher in the men with glucose as a MetS component (P<0.001). Following the test meals, there was a higher maximum concentration (maxC), area under the curve (AUC) and incremental AUC (P≤0.016) for the postprandial triacylglycerol (TAG) response in men with fasting hyperglycaemia. Greater glucose AUC (P<0.001) and insulin maxC (P=0.010) was also observed in these individuals after the test meals. Multivariate regression analysis revealed fasting glucose to be an important predictor of the postprandial TAG and glucose response. Conclusion: Our data analysis has revealed a greater impairment of postprandial TAG than glucose response in MetS subjects with raised fasting glucose. The worsening of postprandial lipaemic control may contribute to the greater CVD risk reported in individuals with MetS component combinations which include hyperglycaemia

Human Computation and Convergence

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added references to page 1 and 3, and corrected typ

Monitoring plant functional diversity from space

The world’s ecosystems are losing biodiversity fast. A satellite mission designed to track changes in plant functional diversity around the globe could deepen our understanding of the pace and consequences of this change and how to manage it

Knowledge of dental academics about the COVID-19 pandemic: a multi-country online survey

Background: COVID-19 is a global pandemic affecting all aspects of life in all countries. We assessed COVID-19 knowledge and associated factors among dental academics in 26 countries. Methods: We invited dental academics to participate in a cross-sectional, multi-country, online survey from March to April 2020. The survey collected data on knowledge of COVID-19 regarding the mode of transmission, symptoms, diagnosis, treatment, protection, and dental treatment precautions as well as participants’ background variables. Multilevel linear models were used to assess the association between dental academics’ knowledge of COVID-19 and individual level (personal and professional) and country-level (number of COVID-19 cases/ million population) factors accounting for random variation among countries. Results: Two thousand forty-five academics participated in the survey (response rate 14.3%, with 54.7% female and 67% younger than 46 years of age). The mean (SD) knowledge percent score was 73.2 (11.2) %, and the score of knowledge of symptoms was significantly lower than the score of knowledge of diagnostic methods (53.1 and 85.4%, P &lt; 0.0001). Knowledge score was significantly higher among those living with a partner/spouse than among those living alone (regression coefficient (B) = 0.48); higher among those with PhD degrees than among those with Bachelor of Dental Science degrees (B = 0.48); higher among those seeing 21 to 30 patients daily than among those seeing no patients (B = 0.65); and higher among those from countries with a higher number of COVID-19 cases/million population (B = 0.0007). Conclusions: Dental academics had poorer knowledge of COVID-19 symptoms than of COVID-19 diagnostic methods. Living arrangements, academic degrees, patient load, and magnitude of the epidemic in the country were associated with COVD-19 knowledge among dental academics. Training of dental academics on COVID-19 can be designed using these findings to recruit those with the greatest need