Patient Experiences in a Linguistically Diverse Safety Net Primary Care Setting: Qualitative Study

Background: The patient-centered medical home model intends to improve patient experience and primary care quality. Within an urban safety net setting in Northern California, United States, these desired outcomes are complicated by both the diversity of the patient community and the care continuity implications of a residency program. Objective: The objective of our study was to understand the patient experience beyond standardized satisfaction measures. Methods: We conducted a qualitative study, interviewing 19 patients from the clinic (English-, Spanish-, or Mien-speaking patients). Results: Some themes, such as the desire to feel confident in their doctor, emerged across language groups, pointing to institutional challenges. Other themes, such as distrust in care being provided, were tied distinctly to speaking a language different from one’s provider. Still other themes, such as a sense of powerlessness, were related to cultural differences and to speaking a language (Mien) not spoken by staff. Conclusions: Findings illuminate the need to understand cultural behaviors and interactional styles in a diverse patient population to create a high-quality medical home

Early Goal-Directed Top-Down Influences in the Production of Speech

It was recently reported that the conscious intention to produce speech affects the speed with which lexical information is retrieved upon presentation of an object (Strijkers et al., 2011). The goal of the present study was to elaborate further on the role of these top-down influences in the course of planning speech behavior. In an event-related potentials (ERP) experiment, participants were required to overtly name pictures and words in one block of trials, while categorizing the same stimuli in another block of trials. The ERPs elicited by the naming task started to diverge very early on (∼170 ms) from those elicited by the semantic categorization task. Interestingly, these early ERP differences related to task intentionality were identical for pictures and words. From these results we conclude that (a) in line with Strijkers et al. (2011), goal-directed processes play a crucial role very early on in speech production, and (b) these task-driven top-down influences function at least in a domain-general manner by modulating those networks which are always relevant for the production of language, irrespective of which cortical pathways are triggered by the input

Experimental and Computational Studies of Temperature Gradient Driven Molecular Transport in Gas Flows through Nano/Micro-Scale Channels

Studies at the University of Southern California have shown that an unconventional solid-state device, the Knudsen Compressor, can be operated as a micro-scale pump or compressor. The critical components of Knudsen Compressors are gas transport membranes, which can be formed from porous materials or densely packed parallel arrays of channels. An applied temperature gradient across a transport membrane creates a thermal creep pumping action. Experimental and computational techniques that have been developed for the investigations will be discussed. Experimental studies of membranes formed from machined aerogels, activated by radiant heating, have been used to investigate thermal creep flows. In computational studies several approaches have been employed: the direct simulation Monte Carlo (DSMC) method, and discrete ordinate solutions of the ellipsoidal statistical (ES) and Bhatnagar-Gross-Krook (BGK) kinetic models. Beyond the study of Knudsen Compressor performance, techniques discussed in this paper could be used to characterize the properties of gas flows in nano/micro-scale channels

Learning to See before Learning to Act: Visual Pre-training for Manipulation

Does having visual priors (e.g. the ability to detect objects) facilitate learning to perform vision-based manipulation (e.g. picking up objects)? We study this problem under the framework of transfer learning, where the model is first trained on a passive vision task, and adapted to perform an active manipulation task. We find that pre-training on vision tasks significantly improves generalization and sample efficiency for learning to manipulate objects. However, realizing these gains requires careful selection of which parts of the model to transfer. Our key insight is that outputs of standard vision models highly correlate with affordance maps commonly used in manipulation. Therefore, we explore directly transferring model parameters from vision networks to affordance prediction networks, and show that this can result in successful zero-shot adaptation, where a robot can pick up certain objects with zero robotic experience. With just a small amount of robotic experience, we can further fine-tune the affordance model to achieve better results. With just 10 minutes of suction experience or 1 hour of grasping experience, our method achieves ~80% success rate at picking up novel objects.Comment: Accepted to ICRA 2020. Porject page: http://yenchenlin.me/vision2action

iNeRF: Inverting Neural Radiance Fields for Pose Estimation

We present iNeRF, a framework that performs mesh-free pose estimation by "inverting" a Neural RadianceField (NeRF). NeRFs have been shown to be remarkably effective for the task of view synthesis - synthesizing photorealistic novel views of real-world scenes or objects. In this work, we investigate whether we can apply analysis-by-synthesis via NeRF for mesh-free, RGB-only 6DoF pose estimation - given an image, find the translation and rotation of a camera relative to a 3D object or scene. Our method assumes that no object mesh models are available during either training or test time. Starting from an initial pose estimate, we use gradient descent to minimize the residual between pixels rendered from a NeRF and pixels in an observed image. In our experiments, we first study 1) how to sample rays during pose refinement for iNeRF to collect informative gradients and 2) how different batch sizes of rays affect iNeRF on a synthetic dataset. We then show that for complex real-world scenes from the LLFF dataset, iNeRF can improve NeRF by estimating the camera poses of novel images and using these images as additional training data for NeRF. Finally, we show iNeRF can perform category-level object pose estimation, including object instances not seen during training, with RGB images by inverting a NeRF model inferred from a single view.Comment: Website: http://yenchenlin.me/inerf

Reconstruction of the metabolic network of Pseudomonas aeruginosa to interrogate virulence factor synthesis

Virulence-linked pathways in opportunistic pathogens are putative therapeutic targets that may be associated with less potential for resistance than targets in growth-essential pathways. However, efficacy of virulence-linked targets may be affected by the contribution of virulence-related genes to metabolism. We evaluate the complex interrelationships between growth and virulence-linked pathways using a genome-scale metabolic network reconstruction of Pseudomonas aeruginosa strain PA14 and an updated, expanded reconstruction of P. aeruginosa strain PAO1. The PA14 reconstruction accounts for the activity of 112 virulence-linked genes and virulence factor synthesis pathways that produce 17 unique compounds. We integrate eight published genome-scale mutant screens to validate gene essentiality predictions in rich media, contextualize intra-screen discrepancies and evaluate virulence-linked gene distribution across essentiality datasets. Computational screening further elucidates interconnectivity between inhibition of virulence factor synthesis and growth. Successful validation of selected gene perturbations using PA14 transposon mutants demonstrates the utility of model-driven screening of therapeutic targets

China Earthquake Reconnaissance Report: Performance of Transportation Structures during the May 12, 2008, M7.9 Wenchuan Earthquake

This report documents the lessons learned from damage caused in the May 12, 2008, M7.9 earthquake in Wenchuan County, China. The damage to the 14 observed bridges reminded the researchers of damage suffered during the 1971 San Fernando Earthquake in California. The bridges had few seismic details such as long seats, large shear keys, or tightly spaced transverse reinforcement. Most arch and girder bridges collapsed due to surface rupturing of the seismic faults in the Longmen-Shan thrust zone. A significant portion of roadways and bridges were pushed away or buried by landslides in the steep slopes of mountainous terrain. Damage to bridge superstructure included unseating of girders, longitudinal and transverse offset of decks, pounding at expansion joints, and shear key failure. The bearings of several girder bridges were either crushed or displaced significantly. The substructure and foundation of bridges were subjected to shear and flexural cracks, concrete spalling, stirrup rupture, excessive displacement, and loss of stability. More damage occurred in simply supported bridges than in continuous spans. Curved bridges either collapsed or suffered severe damage. Evidence of directivity effects on bridges near the earthquake epicenter was observed during the earthquake. The San Fernando earthquake significantly changed the seismic design and construction of bridges in the United States. The Wenchuan earthquake is expected to have the same significance for China\u27s bridge engineers