An Experiential Model of Evaluation: Incorporating Graduate Students in the Collection and Reporting of Mixed-Method Data

A graduate level course was developed which incorporated the experiential learning philosophy of “learning by doing.” Students gained knowledge about program development and evaluation through using an on-line course management system as well as practicing what they learned during on-site evaluation visits. All background and supplementary reading materials, assignments, chats, and discussions were managed on-line. Students applied what they learned and collected quantitative and qualitative data while conducting site visits throughout the semester. Through this experiential learning evaluation course students made meaning from their direct experiences, took time to reflect upon their learning, and felt confident in their abilities as future evaluators. Having a number of graduate students from a variety of backgrounds added a breadth of content at little or no extra cost. This additional data can be used with program staff and stakeholders for continuous program improvement

Machine learning based interatomic potential for amorphous carbon

We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine learning representation of the density-functional theory (DFT) potential-energy surface, such interatomic potentials enable materials simulations with close-to DFT accuracy but at much lower computational cost. We first determine the maximum accuracy that any finite-range potential can achieve in carbon structures; then, using a hierarchical set of two-, three-, and many-body structural descriptors, we construct a GAP model that can indeed reach the target accuracy. The potential yields accurate energetic and structural properties over a wide range of densities; it also correctly captures the structure of the liquid phases, at variance with a state-of-the-art empirical potential. Exemplary applications of the GAP model to surfaces of “diamondlike” tetrahedral amorphous carbon ($\textit{ta}$-C) are presented, including an estimate of the amorphous material’s surface energy and simulations of high-temperature surface reconstructions (“graphitization”). The presented interatomic potential appears to be promising for realistic and accurate simulations of nanoscale amorphous carbon structures.V.L.D. gratefully acknowledges a postdoctoral fellowship from the Alexander von Humboldt Foundation and support from the Isaac Newton Trust (Trinity College Cambridge). This work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk) via EPSRC Grant No. EP/K014560/1

Many-Body Dispersion Correction Effects on Bulk and Surface Properties of Rutile and Anatase TiO2_2

Titanium dioxide (titania, TiO$_2$) is a widely studied material with diverse applications. Here, we explore how pairwise and many-body descriptions of van der Waals dispersion interactions perform in atomistic modeling of the two most important TiO$_2$ polymorphs, rutile and anatase. In particular, we obtain an excellent description of both bulk structures from density-functional theory (DFT) computations with the many-body dispersion (MBD) method of Tkatchenko and co-workers coupled to an iterative Hirshfeld partitioning scheme ("Hirshfeld-I"). Beyond the bulk, we investigate the most important crystal surfaces, namely, rutile (110), (101), and (100) and anatase (101), (100), and (001). Dispersion has a highly anisotropic effect on the different ($\textit{hkl}$) surfaces; this directly changes the predicted nanocrystal morphology as determined from Wulff constructions. The periodic DFT+MBD method combined with Hirshfeld-I partitioning appears to be promising for future large-scale atomistic studies of this technologically important material.V.L.D. gratefully acknowledges a postdoctoral fellowship from the Alexander von Humboldt Foundation. This work used the ARCHER UK National Supercomputing Service, access to which was granted via support for the UKCP consortium (Engineering and Physical Sciences Research Council Grant EP/K014560/1)

Is Kangaroo Care Effective in Reducing Procedural Pain in Neonates?

Objective: The objective of this systematic review is to determine whether Kangaroo Care is effective in reducing procedural pain in neonates

Preschool yards in a warmer climate : the impact of urban landscape design on microclimate for a healthy outdoor experience

På grund av klimatförändringarna och värmeböljor som följd har det drabbat städer hårdare på grund av att stadsutvecklingen präglas av förtätning och därmed är värmeöeffekten mer påtaglig. Detta ställer högre krav på att den urbana miljön kan hantera denna förändring för att ge människor en god livsmiljö. I detta arbete som grundar sig i fältstudier har vi valt att titta på hur barns utemiljö i förskola kan hantera framtidens värmeböljor för att minska risken att barns hälsa och välmående påverkas negativt. Utifrån studiens resultat konstateras att man i planeringskedjan måste beakta flera aspekter som påverkar barns utemiljö i förskola och i ledet påverkar barns utveckling och hälsa. De aspekter som en varierad vegetation och val av markmaterial är viktiga att beakta då dess andel och egenskaper påverkar temperaturen och förskolegårdens klimat samt i längden den urbana värmeöeffekten. Genom fält- och fallstudier kan det konstateras att förbättringar kan göras på många olika sätt, så väl stora som små. Bristande är naturligt material, vegetation och förebyggandet av goda sol- och skuggförhållanden för att säkerställa en god utevistelse.Due to climate change and subsequent heatwaves, cities have been hit harder because of urban development characterized by densification, making the urban heat island effect more pronounced. This puts higher demands on the urban environment to cope with this change to provide people with a good living environment. In this study, based on field research, we have chosen to examine how the outdoor environment of preschools can manage future heatwaves to reduce the risk of negative impacts on children's health and well-being. Based on the study's results, it is concluded that several aspects affecting the outdoor environment of preschools must be considered in the planning process, which in turn affects children's development and health. Aspects such as varied vegetation and choice of ground material are important to consider, as their proportion and characteristics influence the temperature and climate of the preschool yard, and ultimately the urban heat island effect. Through field and case studies, it can be noted that improvements can be made in many ways, both large and small. Deficiencies lie in natural materials, vegetation, and the provision of good sun and shade conditions to ensure a good outdoor experience

A general-purpose machine-learning force field for bulk and nanostructured phosphorus

Elemental phosphorus is attracting growing interest across fundamental and applied fields of research. However, atomistic simulations of phosphorus have remained an out- standing challenge. Here we show that a universally applicable force field for phosphorus can be created by machine learning (ML) from a suitably chosen ensemble of quantum- mechanical results. Our model is fitted to density-functional theory plus many-body dis- persion (DFT+MBD) data; its accuracy is demonstrated for the exfoliation of black and violet phosphorus (yielding monolayers of “phosphorene” and “hittorfene”); its transfer- ability is shown for the transition between the molecular and network liquid phases. An application to a phosphorene nanoribbon on an experimentally relevant length scale ex- emplifies the power of accurate and flexible ML-driven force fields for next-generation materials modelling. The methodology promises new insights into phosphorus as well as other structurally complex, e.g., layered solids that are relevant in diverse areas of chem- istry, physics, and materials science