Closed-loop Bayesian Semantic Data Fusion for Collaborative Human-Autonomy Target Search

In search applications, autonomous unmanned vehicles must be able to efficiently reacquire and localize mobile targets that can remain out of view for long periods of time in large spaces. As such, all available information sources must be actively leveraged -- including imprecise but readily available semantic observations provided by humans. To achieve this, this work develops and validates a novel collaborative human-machine sensing solution for dynamic target search. Our approach uses continuous partially observable Markov decision process (CPOMDP) planning to generate vehicle trajectories that optimally exploit imperfect detection data from onboard sensors, as well as semantic natural language observations that can be specifically requested from human sensors. The key innovation is a scalable hierarchical Gaussian mixture model formulation for efficiently solving CPOMDPs with semantic observations in continuous dynamic state spaces. The approach is demonstrated and validated with a real human-robot team engaged in dynamic indoor target search and capture scenarios on a custom testbed.Comment: Final version accepted and submitted to 2018 FUSION Conference (Cambridge, UK, July 2018

HARPS: An Online POMDP Framework for Human-Assisted Robotic Planning and Sensing

Autonomous robots can benefit greatly from human-provided semantic characterizations of uncertain task environments and states. However, the development of integrated strategies which let robots model, communicate, and act on such 'soft data' remains challenging. Here, the Human Assisted Robotic Planning and Sensing (HARPS) framework is presented for active semantic sensing and planning in human-robot teams to address these gaps by formally combining the benefits of online sampling-based POMDP policies, multimodal semantic interaction, and Bayesian data fusion. This approach lets humans opportunistically impose model structure and extend the range of semantic soft data in uncertain environments by sketching and labeling arbitrary landmarks across the environment. Dynamic updating of the environment model while during search allows robotic agents to actively query humans for novel and relevant semantic data, thereby improving beliefs of unknown environments and states for improved online planning. Simulations of a UAV-enabled target search application in a large-scale partially structured environment show significant improvements in time and belief state estimates required for interception versus conventional planning based solely on robotic sensing. Human subject studies in the same environment (n = 36) demonstrate an average doubling in dynamic target capture rate compared to the lone robot case, and highlight the robustness of active probabilistic reasoning and semantic sensing over a range of user characteristics and interaction modalities

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Active Collaborative Planning and Sensing in Human-Robot Teams

As they become increasing capable, autonomous robots can further benefit from human-provided semantic characterizations of uncertain task environments and states. However, the development of integrated strategies which let robots model, communicate, and act on such `soft data' remains challenging. This work presents a framework for active semantic sensing and planning in human-robot teams which addresses these gaps by developing algorithms and techniques to allow formally integrated semantic sensing and planning in human robot teams, leveraging advances in POMDP approximation, multi-modal semantic interaction, and Bayesian data fusion. This approach lets humans opportunistically impose model structure and dynamically extend the range of semantic soft data in uncertain environments, which otherwise yield little information to a lone robot. It also lets robots actively query humans for new semantic data which update understanding and beliefs of unknown environments for improved online planning. Dynamic target search simulations show that active collaborative semantic sensing leads to significant improvements in time and belief state estimates required for interception versus conventional planning, which relies on robotic sensing only. This thesis contains several contributions advancing the state of the art in human-robot collaborative planning. Chapter 3 derives and implements the VB-POMDP algorithm, which provides for continuous state POMDP planning under hybrid continuous-to-discrete semantic sensor observations modeled by softmax functions. Compared to previous methods, this algorithm scales construction of observation models to previously unreachable integrated planning and control problems. Chapter 4 scales the work of Chapter 3 even further, applying a hierarchical framework for the efficient solution of POMDPs in complex continuous state spaces. It also incorporates active human sensing into such problems, using a semantic dictionary of potential robotic queries to facilitate human-robot information transfer. Finally, Chapter 5 extends collaborative human-robot target search to unknown a priori environments, and presents a novel sketch-based approach to multi-level active semantic sensing which allows the transfer of both model and state information without the need for retraining

CliqueMS Validation Data

CliqueMSData Data used for the validation of CliqueMS (https://CRAN.R-project.org/package=cliqueMS) This repository contains the mzXML files corresponding to the novel LC-MS1 spectra used to validate CliqueMS. The raw data corresponding to these files has been obtained as explained below. The corresponding mzXML files have been obtained using the msconvert tool in ProteoWizard. This repository includes 3 files: standards.mzXML positive.mzXML negative.mzXML standards.mzXML - Mixture of standards Materials. MS1 grade acetonitrile (ACN), ammonium acetate (NH4Ac) and NH4OH were purchased from SDS (Peypin, France). Water was produced in an in-house Milli-Q purification system (Millipore, Molsheim, France). Formic acid and ammonium fluoride were purchased from Sigma-Aldrich (Steinheim, Germany). Standards: (-)riboflavine, 1,2-distearoyl-sn-glycero-3-phosphocholine, biotin, cholic acid, deoxycholic acid, L-methionine sulfoxide, thymine and uracil were purchased from Sigma-Aldrich (Steinheim, Germany). Standard mix preparation. All standards were pooled to a final concentration of 1ppm in H2O:ACN (5:95) with 0.1% formic acid. MS1 analyses. MS1 analyses were performed using an UHPLC system (1290 series, Agilent Technologies) coupled to a 6550 ESI-QTOF MS (Agilent Technologies) operated in positive (ESI+) electrospray ionization mode. A vial containing the standard mix was kept at -20ºC prior to MS1 analysis. Metabolites were separated using an Acquity UPLC BEH HILIC column (2.1 x 150 mm, 1.8 \mu m) and the solvent system was A1 = 20mM ammonium acetate and 15 mM NH4OH in water and B1 = 95% ACN and 5% H2O. The linear gradient elution started at 100% B (time 0--2 min) and finished at 75% A (10-15 min). The injection volume was 5 \mu L. ESI conditions: gas temperature, 150ºC; drying gas, 13 L min--1; nebulizer, 35 psig; fragmentor, 400 V; and skimmer, 65 V. The instrument was set to acquire over the m/z range 100--1500 in full-scan mode with an acquisition rate of 4 spectra/sec. MS/MS was performed in targeted mode, and the instrument was set to acquire over the m/z range 50--1000, with a default isolation width (the width half-maximum of the quadrupole mass bandpass used during MS/MS precursor isolation) of 4 m/z. The collision energy was fixed at 20 V. positive.mzXML & negative.mzXML - Complex Samples Materials. MS1 grade methanol (MeOH) and acetonitrile (ACN) and analytical grade chloroform (CHCl3) were purchased from SDS (Peypin, France). Water was produced in an in-house Milli-Q purification system (Millipore, Molsheim, France). Formic acid and ammonium fluoride were purchased from Sigma-Aldrich (Steinheim, Germany). Experimental Animals. Irs-2-deficient mice were generated initially on a C57BL6/J: SV129 background and then backcrossed to establish a pure C57BL6/J background. Thus, the offspring resulting from the breeding of Irs-2(2/2) with RIP-Irs-2 line were C57BL6/J. Metabolite extraction method. Retinas were first lyophilized and metabolites were extracted adding 190 uL of MeOH and 120 uL of H2O, then vortex during 30 seconds. Afterwards, samples were frozen during 1 min in liquid nitrogen (N2) and thawed by cold sonication during 30 seconds. This step was applied three times. Then 380 uL of chloroform were added and vortexed during 30 seconds. Finally, samples were centrifuged (15000 rpm, 15 min a 4ºC). The supernatant was extracted and dried. The sample was suspended in 100 uL of H2O:MeOH (1:1) and stored at -80ºC until further analysis. MS1 analyses. MS1 analyses were performed using an UHPLC system (1290 series, Agilent Technologies) coupled to a 6550 ESI-QTOF MS (Agilent Technologies) operated in positive (ESI+) or negative (ESI-) electrospray ionization mode. Vials containing extracted metabolites were kept at -20ºC prior to MS1 analysis. When the instrument was operated in positive ionization mode, metabolites were separated using an Acquity UPLC (HSS T3) C18 reverse phase (RP) column (2.1 x 150 mm, 1.8 \mu m) and the solvent system was A1 = 0.1% formic acid in water and B1 = 0.1% formic acid in acetonitrile. When the instrument was operated in negative ionization mode, metabolites were separated using an Acquity UPLC (BEH) C18 RP column (2.1 x 150 mm, 1.7 \mu m) and the solvent system was A2 = 1 mM ammonium fluoride in water and B2 = acetonitrile. The linear gradient elution started at 100% A (time 0--2 min) and finished at 100% B (10-15 min). The injection volume was 5 \mu L. ESI conditions: gas temperature, 150ºC; drying gas, 13 L min--1; nebulizer, 35 psig; fragmentor, 400 V; and skimmer, 65 V. The instrument was set to acquire over the m/z range 100--1500 in full-scan mode with an acquisition rate of 4 spectra/sec. MS/MS was performed in targeted mode, and the instrument was set to acquire over the m/z range 50--1000, with a default isolation width (the width half-maximum of the quadrupole mass bandpass used during MS/MS precursor isolation) of 4 m/z. The collision energy was fixed at 20 V. positive.mzXML and negative.mzXML files correspond to LC-MS1 spectra obtained for positive and negative ionization, respectively