Approximate Bayesian inference for doubly robust estimation

Doubly robust estimators are typically constructed by combining outcome regression and propensity score models to satisfy moment restrictions that ensure consistent estimation of causal quantities provided at least one of the component models is correctly specified. Standard Bayesian methods are difficult to apply because restricted moment models do not imply fully specified likelihood functions. This paper proposes a Bayesian bootstrap approach to derive approximate posterior predictive distributions that are doubly robust for estimation of causal quantities. Simulations show that the approach performs well under various sources of misspecification of the outcome regression or propensity score models. The estimator is applied in a case study of the effect of area deprivation on the incidence of child pedestrian casualties in British cities

Evaluating unsupervised methods to size and classify suspended particles using digital in-line holography

Substantial information can be gained from digital in-line holography of marine particles, eliminating depth-of-field and focusing errors associated with standard lens-based imagingmethods.However, for the technique to reach its full potential in oceanographic research, fully unsupervised (automated) methods are required for focusing, segmentation, sizing, and classification of particles. These computational challenges are the subject of this paper, in which the authors draw upon data collected using a variety of holographic systems developed at Plymouth University, United Kingdom, from a significant range of particle types, sizes, and shapes. A new method for noise reduction in reconstructed planes is found to be successful in aiding particle segmentation and sizing. The performance of an automated routine for deriving particle characteristics (and subsequent size distributions) is evaluated against equivalent size metrics obtained by a trained operative measuring grain axes on screen. The unsupervised method is found to be reliable, despite some errors resulting from oversegmentation of particles. A simple unsupervised particle classification system is developed and is capable of successfully differentiating sand grains, bubbles, and diatoms from within the surfzone. Avoiding miscounting bubbles and biological particles as sand grains enables more accurate estimates of sand concentrations and is especially important in deployments of particle monitoring instrumentation in aerated water. Perhaps the greatest potential for further development in the computational aspects of particle holography is in the area of unsupervised particle classification. The simple method proposed here provides a foundation upon which further development could lead to reliable identification of more complex particle populations, such as those containing phytoplankton, zooplankton, flocculated cohesive sediments, and oil droplets

Acceleration of generalized hypergeometric functions through precise remainder asymptotics

We express the asymptotics of the remainders of the partial sums {s_n} of the generalized hypergeometric function q+1_F_q through an inverse power series z^n n^l \sum_k c_k/n^k, where the exponent l and the asymptotic coefficients {c_k} may be recursively computed to any desired order from the hypergeometric parameters and argument. From this we derive a new series acceleration technique that can be applied to any such function, even with complex parameters and at the branch point z=1. For moderate parameters (up to approximately ten) a C implementation at fixed precision is very effective at computing these functions; for larger parameters an implementation in higher than machine precision would be needed. Even for larger parameters, however, our C implementation is able to correctly determine whether or not it has converged; and when it converges, its estimate of its error is accurate.Comment: 36 pages, 6 figures, LaTeX2e. Fixed sign error in Eq. (2.28), added several references, added comparison to other methods, and added discussion of recursion stabilit

InP Photonic Integrated Circuit for 6.7GHz Spaced Optical Frequency Comb Generator

We have demonstrated a novel approach to photonically integrated optical frequency comb generation on Indium Phosphide (InP) using generic foundry platforms. The optical comb utilized a recirculating loop technique to generate 59 comb lines (within a 20 dB power envelope) which are separated by 6.7 GHz frequency spacing. All comb lines exhibit strong phase coherence as characterized by low phase noise measurements of -105 dBc/Hz at 100 kHz. The choice of InP as an integration platform allowed for an immediate optical amplification of the modulated sideband tones. This approach reduced the requirement for external high-power RF amplifiers and therefore made the entire system more compact and power efficient. The amplified recirculating loop comb occupied 6 x 0.7 mm2 area of InP chip and consisted of electro-optic phase modulator (EOPM) and semiconductor optical amplifier (SOA) components embedded within a short (12 mm long) waveguide loop, such that the round-trip loop frequency corresponding to the loop optical length equated to 6.7 GHz. Modulation frequencies equal to the round-trip loop frequency were used to generate broad comb spans

VPS18 recruits VPS41 to the human HOPS complex via a RING-RING interaction

Eukaryotic cells use conserved multisubunit membrane tethering complexes, including CORVET (class C core vacuole/endosome tethering) and HOPS (homotypic fusion and vacuole protein sorting), to control the fusion of endomembranes. These complexes have been extensively studied in yeast, but to date there have been far fewer studies of metazoan CORVET and HOPS. Both of these complexes comprise six subunits: a common four-subunit core and two unique subunits. Once assembled, these complexes function to recognise specific endosomal membrane markers and facilitate SNARE-mediated membrane fusion. CORVET promotes the homotypic fusion of early endosomes, while HOPS promotes the fusion of lysosomes to late endosomes and autophagosomes. Many of the subunits of both CORVET and HOPS contain putative C-terminal zinc-finger domains. Here, the contribution of these domains to the assembly of the human CORVET and HOPS complexes has been examined. Using biochemical techniques, we demonstrate that the zinc-containing RING (really interesting new gene) domains of human VPS18 and VPS41 interact directly to form a stable heterodimer. In cells, these RING domains are able to integrate into endogenous HOPS, showing that the VPS18 RING domain is required to recruit VPS41 to the core complex subunits. Importantly, this mechanism is not conserved throughout eukaryotes, as yeast Vps41 does not contain a C-terminal zinc-finger motif. The subunit analogous to VPS41 in human CORVET is VPS8, in which the RING domain has an additional C-terminal segment that is predicted to be disordered. Both the RING and disordered C-terminal domains are required for integration of VPS8 into endogenous CORVET complexes, suggesting that HOPS and CORVET recruit VPS41 and VPS8 via distinct molecular interactions.This work was supported by a Sir Henry Dale Fellowship, jointly funded by the Royal Society and the Wellcome Trust, to S.C.G. [098406/Z/12/Z], an Isaac Newton Trust/Wellcome Trust ISSF/University of Cambridge Joint Research Grant to S.C.G., and a Wellcome Trust Senior Research Fellowship [WT097997MA] to Ian Goodfellow (University of Cambridge)

Super-resolution far-field ghost imaging via compressive sampling

Much more image details can be resolved by improving the system's imaging resolution and enhancing the resolution beyond the system's Rayleigh diffraction limit is generally called super-resolution. By combining the sparse prior property of images with the ghost imaging method, we demonstrated experimentally that super-resolution imaging can be nonlocally achieved in the far field even without looking at the object. Physical explanation of super-resolution ghost imaging via compressive sampling and its potential applications are also discussed.Comment: 4pages,4figure

Recent advances in the detection and management of early gastric cancer and its precursors

Despite declines in incidence, gastric cancer remains a disease with a poor prognosis and limited treatment options due to its often late stage of diagnosis. In contrast, early gastric cancer has a good to excellent prognosis, with 5-year survival rates as high as 92.6% after endoscopic resection. There remains an East-West divide for this disease, with high incidence countries such as Japan seeing earlier diagnoses and reduced mortality, in part thanks to the success of a national screening programme. With missed cancers still prevalent at upper endoscopy in the West, and variable approaches to assessment of the high-risk stomach, the quality of endoscopy we provide must be a focus for improvement, with particular attention paid to the minority of patients at increased cancer risk. High-definition endoscopy with virtual chromoendoscopy is superior to white light endoscopy alone. These enhanced imaging modalities allow the experienced endoscopist to accurately and robustly detect high-risk lesions in the stomach. An endoscopy-led staging strategy would mean biopsies could be targeted to histologically confirm the endoscopic impression of premalignant lesions including atrophic gastritis, gastric intestinal metaplasia, dysplasia and early cancer. This approach to quality improvement will reduce missed diagnoses and, combined with the latest endoscopic resection techniques performed at expert centres, will improve early detection and ultimately patient outcomes. In this review, we outline the latest evidence relating to diagnosis, staging and treatment of early gastric cancer and its precursor lesions

Accuracy of endoscopic staging and targeted biopsies for routine gastric intestinal metaplasia and gastric atrophy evaluation study protocol of a prospective, cohort study: the estimate study

Introduction Patients with chronic atrophic gastritis (CAG) and intestinal metaplasia (IM) are at risk of developing gastric adenocarcinoma. Their diagnosis and management currently rely on histopathological guidance after random endoscopic biopsy sampling (Sydney biopsy strategy). This approach has significant flaws such as under-diagnosis, poor reproducibility and poor correlation between endoscopy and histology. This prospective, international multicentre study aims to establish whether endoscopyled risk stratification accurately and reproducibly predicts CAG and IM extent and disease stage. Methods and analysis Patients with CAG and/or IM on standard white light endoscopy (WLE) will be prospectively identified and invited to undergo a second endoscopy performed by an expert endoscopist using enhanced endoscopic imaging techniques with virtual chromoendoscopy. Extent of CAG/IM will be endoscopically staged with enhanced imaging and compared with standard WLE. Histopathological risk stratification through targeted biopsies will be compared with endoscopic disease staging and to random biopsy staging on WLE as a reference. At least 234 patients are required to show a 10% difference in sensitivity and accuracy between enhanced imaging endoscopy-led staging and the current biopsy-led staging protocol of gastric atrophy with a power (beta) of 80% and a 0.05 probability of a type I error (alpha). Ethics and dissemination The study was approved by the respective Institutional Review Boards (Netherlands: MEC2018-078; UK: 19/LO/0089). The findings will be published in peer-reviewed journals and presented at scientific meetings