Improving Bayesian Graph Convolutional Networks using Markov Chain Monte Carlo Graph Sampling

In the modern age of social media and networks, graph representations of real-world phenomena have become incredibly crucial. Often, we are interested in understanding how entities in a graph are interconnected. Graph Neural Networks (GNNs) have proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification. However, in most of these tasks, the graph data we are working with may be noisy and may contain spurious edges. That is, there is a lot of uncertainty associated with the underlying graph structure. Recent approaches to modeling uncertainty have been to use a Bayesian framework and view the graph as a random variable with probabilities associated with model parameters. Introducing the Bayesian paradigm to graph-based models, specifically for semi-supervised node classification, has been shown to yield higher classification accuracies. However, the method of graph inference proposed in recent work does not take into account the structure of the graph. In this paper, we propose Neighborhood Random Walk Sampling (NRWS), a Markov Chain Monte Carlo (MCMC) based graph sampling algorithm that utilizes graph structure, improves diversity among connections, and yields consistently competitive classification results compared to the state-of-the-art in semi-supervised node classification

Early Childhood Education Trajectories and Transitions: A study of the experiences and perspectives of parents and children in Andhra Pradesh, India. Young Lives Working Paper 52

This paper explores diverse pathways through early childhood in the context of Andhra Pradesh state, India. The particular focus is on experiences of pre-school and transitions to primary school. The paper is based on analysis of Young Lives survey data (n=1950) collected for a group of young children born at the beginning of the millennium, plus in-depth qualitative research with a small sub-sample (n=24). We start from the premise that children’s earliest educational experiences can have a crucial influence on their lifelong adjustments and achievements. Superficially, the evidence from Young Lives research is quite positive, suggesting equitable access to early childhood provision as well as high levels of primary school attendance. However, overall percentages are misleading and disguise major differences in early transition experiences. Many of these differences are shaped by the co-existence of a long established network of government anganwadis under the Integrated Child Development Services (ICDS) programme, alongside a rapidly growing (relatively unregulated) private sector at both pre-school and primary levels. Parental decision making around private versus government education has been fuelled by the possibility of improved life opportunities in a rapidly changing economy and the attractiveness of English medium teaching, even at the earliest stages (more commonly available in the private sector). The paper identifies four quite distinct trajectories related to availability and choice of pre-school and primary school. Parental aspirations for individual boys and girls combined with beliefs about relative quality of government and private schools seem to shape individual trajectories in ways that seem likely to reproduce or even reinforce inequities related to wealth, location, caste and gender. The consequence for children is in many cases having to cope with multiple transitions during their early years, which may entail changing schools in an effort to ‘up-grade’ in perceived quality (e.g. from a government to private school), or moving into distant hostels or with relatives in order to attend better schools or to access grades unavailable locally

The effects of machining process variables and tooling characterisation on the surface generation: modelling, simulation and application promise

The paper presents a novel approach for modelling and simulation of the surface generation in the machining process. The approach, by integrating dynamic cutting force model, regenerative vibration model, machining system response model and tool profile model, models the complex surface generation process. Matlab Simulink is used to interactively perform the simulation in a user-friendly, effective and efficient manner. The effects of machining variables and tooling characteristics on the surface generation are investigated through simulations. CNC turning trials have been carried out to evaluate and validate the approach and simulations presented. The proposed approach contributes to comprehensive and better understanding of the machining system, and is promising for industrial applications with particular reference to the optimisation of the machining process based on the product/component surface functionality requirements

Multi-scale simulation of the nano-metric cutting process

Molecular dynamics (MD) simulation and the finite element (FE) method are two popular numerical techniques for the simulation of machining processes. The two methods have their own strengths and limitations. MD simulation can cover the phenomena occurring at nano-metric scale but is limited by the computational cost and capacity, whilst the FE method is suitable for modelling meso- to macro-scale machining and for simulating macro-parameters, such as the temperature in a cutting zone, the stress/strain distribution and cutting forces, etc. With the successful application of multi-scale simulations in many research fields, the application of simulation to the machining processes is emerging, particularly in relation to machined surface generation and integrity formation, i.e. the machined surface roughness, residual stress, micro-hardness, microstructure and fatigue. Based on the quasi-continuum (QC) method, the multi-scale simulation of nano-metric cutting has been proposed. Cutting simulations are performed on single-crystal aluminium to investigate the chip formation, generation and propagation of the material dislocation during the cutting process. In addition, the effect of the tool rake angle on the cutting force and internal stress under the workpiece surface is investigated: The cutting force and internal stress in the workpiece material decrease with the increase of the rake angle. Finally, to ease multi-scale modelling and its simulation steps and to increase their speed, a computationally efficient MATLAB-based programme has been developed, which facilitates the geometrical modelling of cutting, the simulation conditions, the implementation of simulation and the analysis of results within a unified integrated virtual-simulation environment

Direct evidence for thymic function in adult humans.

The understanding of human thymic function and evaluation of its contribution to T cell homeostasis are matters of great importance. Here we report the development of a novel assay to quantitate the frequency and diversity of recent thymic emigrants (RTEs) in the peripheral blood of humans. Such cells were defined by the presence of T cell receptor (TCR) rearrangement deletion circles (DCs), episomal byproducts of TCR-beta V(D)J rearrangement. DCs were detected in T cells in the thymus, cord blood, and adult peripheral blood. In the peripheral blood of adults aged 22 to 76 years, their frequency was highest in the CD4(+)CD45RA(+) CD62L(+) subpopulation of naive T cells. TCR DCs were also observed in other subpopulations of peripheral blood T cells, including those with the CD4(+)CD45RO(-)CD62L(+) and CD4(+)CD45RO(+)CD62L(+) phenotypes. RTEs were observed to have more than one Vbeta rearrangement, suggesting that replenishment of the repertoire in the adult is at least oligoclonal. These results demonstrate that the normal adult thymus continues to contribute, even in older individuals, a diverse set of new T cells to the peripheral circulation

Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms

Learning disentangled causal representations is a challenging problem that has gained significant attention recently due to its implications for extracting meaningful information for downstream tasks. In this work, we define a new notion of causal disentanglement from the perspective of independent causal mechanisms. We propose ICM-VAE, a framework for learning causally disentangled representations supervised by causally related observed labels. We model causal mechanisms using learnable flow-based diffeomorphic functions to map noise variables to latent causal variables. Further, to promote the disentanglement of causal factors, we propose a causal disentanglement prior that utilizes the known causal structure to encourage learning a causally factorized distribution in the latent space. Under relatively mild conditions, we provide theoretical results showing the identifiability of causal factors and mechanisms up to permutation and elementwise reparameterization. We empirically demonstrate that our framework induces highly disentangled causal factors, improves interventional robustness, and is compatible with counterfactual generation

Synthetic, physical, and photolytic properties of linear and cyclic oligogermanes

The following dissertation focuses on the synthesis and characterization of unique linear, branched, cyclic germanium compounds to further the knowledge and scope of organometallic chemistry of the element. In chapter II a 2-germanium atom end capping reagent was used for synthesis of longer linear oligomer using monohydride Ph3GeGePh2H. This species was observed to be thermally unstable upon heating the material to 200 °C. Thermal decomposition products were identified as Ph3GeH and assumed germylene (Ph2Ge:), which subsequently polymerized. Reactions were monitored by NMR (1H and 13C) spectroscopy and characterized using X-ray crystallography.A series of linear oligomers R3Ge(GePh2)nGeR3 (n = 0 or 1), were synthesized and subsequently photolyzed. The photodecomposition pathways of these compounds were analyzed after exposure to UV-C light (280-100 nm) in the presence of acetic acid, acting as a germylene trapping agent. Resulting photoproducts showed germylene (Ph2Ge:) extrusion and germyl radical formation (R3Ge) to yield R2Ge(H)OAc and R3GeOAc, R3GeH and R3GeGeR3 respectively. Photoproducts were identified by 1H NMR, electron impact gas-chromatography (EI-GC/MS), and high resolution accurate mass-mass spectrometry (HRAM-MS). Three branched oligogermanes (Me3Ge)3GePh, (Me2ButGe)3GePh, (Me2PhGe)3GePh, and (Bu3nGe)3GePh were synthesized and characterized. All species were prepared and characterized by NMR (1H, 13C, and 73Ge) and HRAM-MS. The varying substituent composition on the peripheral R3Ge- groups provided insight on the electronic properties studied by cyclic/differential pulse voltammetry (CV and DPV) and UV-visible spectroscopy.Chapter V describes the synthesis of a series Pri3Ge(GePh2)nGePri3 (n = 0-3) linear oligomers. Compounds were characterized using NMR (1H and 13C), UV-vis, and CV/DPV. A bathochromic shift was seen via Ge - Ge chain elongation, and species became easier to oxidize. Crystals of the pentagermane showed dichroism and luminescence, the smallest discrete oligomer to exhibit polymeric like properties. The final chapter focuses on the synthesis of perarylated cyclotetra- (Ar2Ge)4 and cyclopentagermanes (Ar2Ge)5 (Ar = 2,5-xylyl), using Ar2GeCl2 as the precursor. These species were selected to increase solubility in ring opening reactions with an alkali metal. Crystals were only obtained in experimental conditions for (Ar2Ge)4. However, the expected product turned out to be a germyl-substituted cyclogermane ClGeAr2(Ge4Ar7), the first compound of its class to be synthesized

Dynamic behavior of drill-shaft-drive assembly subjected to cutting loads

Drilling is one of the most important and common machining operations carried out in manufacturing industry. In drilling, the parameters such as hole-roundness, location and size, and interior surface finish are important for the proper functioning in the assembly. All of these parameters are related to the orbital motion of the drill during the drilling operation, which mainly arises from the lateral vibrations of the twist drill in a plane. In order to understand the dynamics of the process during drilling, a simplified two-dimensional model for the transverse motion of the drill rotating in a hole with clearance is employed. The model includes parameters such as the drill rotational speed, clearance between the drill and the hole, stiffness ratio of workpiece and drill, dry friction between the workpiece and the drill, and cutting force modulation factor. The effects of these parameters on the drill orbital motion and hole-quality of the workpiece are investigated