Semantic Segmentation combines two sub-tasks: the identification of pixel-level image masks and the application of semantic labels to those masks. Recently, so-called Foundation Models have been introduced; general models trained on very large datasets which can be specialized and applied to more specific tasks. One such model, the Segment Anything Model (SAM), performs image segmentation. Semantic segmentation systems such as CLIPSeg and MaskRCNN are trained on datasets of paired segments and semantic labels. Manual labeling of custom data, however, is time-consuming. This work presents a method for performing segmentation for objects in video. Once an object has been found in a frame of video, the segment can then be propagated to future frames; thus reducing manual annotation effort. The method works by combining SAM with Structure from Motion (SfM). The video input to the system is first reconstructed into 3D geometry using SfM. A frame of video is then segmented using SAM. Segments identified by SAM are then projected onto the the reconstructed 3D geometry. In subsequent video frames, the labeled 3D geometry is reprojected into the new perspective, allowing SAM to be invoked fewer times. System performance is evaluated, including the contributions of the SAM and SfM components. Performance is evaluated over three main metrics: computation time, mask IOU with manual labels, and the number of tracking losses. Results demonstrate that the system has substantial computation time improvements over human performance for tracking objects over video frames, but suffers in performance.

Semantic mapping is the task of providing a robot with a map of its environment beyond the open, navigable space of traditional Simultaneous Localization and Mapping (SLAM) algorithms by attaching semantics to locations. The system presented in this work reads door placards to annotate the locations of offices. Whereas prior work on this system developed hand-crafted detectors, this system leverages YOLOv5 for sign detection and EAST for text recognition. Placards are localized by computing their pose from a point cloud in a RGB-D camera frame localized by a modified ORB-SLAM. Semantic mapping is accomplished in a post-processing step after robot exploration from video recording. System performance is reported in terms of the number of placards identified, the accuracy of their placement onto a SLAM map, the accuracy of the map built, and the correctness transcribed placard text.

UT Austin Villa has participated in five RoboCup@Home competitions, performing respectably in each. What is more exciting, however, is that we have begun a strong program of research that has been in part inspired by our efforts in this competition. It is our intention to build a comprehensive service robot system which is used in our laboratories, in a real-world deployment in our CS Department, and to compete in RoboCup@Home. In this Team Description Paper, you will find the highlights of our efforts and our plans for 2022.

Semantic mapping is the task of providing a robot with a map of its environment beyond the open, navigable space of traditional Simultaneous Localization and Mapping (SLAM) algorithms by attaching semantics to locations. The system presented in this work reads door placards to annotate the locations of offices. Whereas prior work on this system developed hand-crafted detectors, this system leverages YOLOv2 for detection and a segmentation network for segmentation. Placards are localized by computing their pose from a homography computed from a segmented quadrilateral outline. This work also introduces an Interruptable Frontier Exploration algorithm, enabling the robot to explore its environment to construct its SLAM map while pausing to inspect placards observed during this process. This allows the robot to autonomously discover room placards without human intervention while speeding up significantly over previous autonomous exploration methods.

The method of Frobenius Norm (FN) minimization of forward kinematic Jacobians is presented to minimize the sensitivity of a robotic manipulator. We demonstrate the effectiveness of this approach with a Monte Carlo simulation of an Assembler robot. The Assembler is described as a stack of Stewart Platforms designed for in-space assembly to aide NASA in deep space exploration. The translations and rotations between each Stewart Platform define the forward kinematics of the Assember, which analytically determine the end effector position and orientation. However, selecting the poses of each Stewart Platform which yield a desired end effector state, defined as the inverse kinematics, is an underconstrained nonlinear optimization problem for large Assembler stacks.

We are interested in the problem of time-optimal control of omnidirectional robots with bounded acceleration (TOC-ORBA). While there exist approximate solutions for such problems, and exact solutions with unbounded acceleration, exact solvers to the TOC-ORBA problem have remained elusive until now. In this paper, we present a real-time solver for true time-optimal control of omnidirectional robots with bounded acceleration. We first derive the general parameterized form of the solution to the TOC-ORBA problem by application of Pontryagin's maximum principle. We then frame the boundary value problem of TOC-ORBA as an optimization problem over the parameterized control space. To overcome local minima and poor initial guesses to the optimization problem, we introduce a two-stage optimal control solver (TSOCS): The first stage computes an upper bound to the total time for the TOC-ORBA problem and holds the time constant while optimizing the parameters of the trajectory to approach the boundary value conditions. The second stage uses the parameters found by the first stage, and relaxes the constraint on the total time to solve for the parameters of the complete TOC-ORBA problem. Furthermore, we implement TSOCS as a closed loop controller to overcome actuation errors on real robots in realtime. We empirically demonstrate the effectiveness of TSOCS in simulation and on real robots, showing that 1) it runs in real time, generating solutions in less than 0.5ms on average; 2) it generates faster trajectories compared to an approximate solver; and 3) it is able to solve TOC-ORBA problems with nonzero final velocities that were previously unsolvable in real-time.

This paper presents the changes in electromechanical design and a selection of the algorithms used by the UMass MinuteBots, a second-year RoboCup team from the University of Massachusetts Amherst. The team uses RoboCup as a research application area for both hardware and algorithms. We are actively researching many areas, including multi-agent kino-dynamic navigation, time-optimal control, system identification, and failure recovery. As a second-year team, our primary objectives for the 2018 RoboCup competition are to solidify basic soccer capabilities, develop more robust advanced tactics, and apply current state-of-the-art research whenever possible. As winners of the lower bracket in the 2017 competition, we expect to continue to improve and play competitively against all teams.

Introduction: Over-the-counter (OTC) medicines for heartburn and gas are accepted as safe and effective; however, lower health literacy and poor understanding of OTC product indications may increase inappropriate use. Clinical investigations of combination antacid plus simethicone for heartburn and gas are lacking. We investigated the efficacy and acceptability of a new combination OTC calcium carbonate antacid plus simethicone (CCASi) for relief of heartburn and gas symptoms. Methods: An open-label, non-randomized, single-site study evaluated subjects' self-reported efficacy and acceptability of a calcium carbonate 750 mg plus simethicone 250 mg coated chew for symptoms of heartburn and gas. Adults with self-described heartburn and gas who used >1 OTC antacid/anti-gas product within the past 30 days were enrolled. Subjects consumed 1-2 CCASi chews/day for 1 week and completed a questionnaire grading 5 symptom relief questions and 9 organoleptic attributes on 5-level Likert scales. Results were evaluated using qualitative and descriptive analyses. Results: 49 subjects (15 M, 34 F; mean age 49±16.3 yrs) completed the study. At baseline, subjects used a mean of 1.5 OTC antacid or anti-gas products; only 29% of subjects used at least 1 product in accordance with the labeled indication (Table). Pre-study heartburn and gas events/week were: 2-3 (29%); 4-5 (39%); and >6 (33%). During the study week, subjects consumed 10.7 chews/subject. Self-reported heartburn and gas events were: <1 (31%); 2-3 (22%); 4-5 (24%); and >6 (22%). The majority of subjects reported symptomatic relief from heartburn (77%) and gas (70%); time to relief was <30 minutes in 84% of subjects. Organoleptic assessment of texture attributes were: easy to chew (96%) and pleasantly chewy (92%). Assessment of taste attributes were: sweetness just right (82%) and flavor strength just right (78%). Subjects liked the taste (80%) and reported no unpleasant aftertaste (82%) or chalky taste (82%). 63% of subjects were more satisfied with CCASi than their usual product and 65% would use them in the future (Table). Conclusion: This study suggests consumers inappropriately take antacids for gas symptoms and may take multiple OTC products for relief beyond labeled indications. Subjects' acceptability of an OTC calcium carbonate 750 mg plus simethicone 250 mg coated chew for heartburn and gas was high with most preferring the new chew to their usual product. Organoleptic attributes scored higher than symptom relief.Table 1: Questionnaire Results

Health care providers are facing unprecedented pressures to reduce the cost of care and improve the quality and safety of care. These pressures are expected to lead to significant changes in the structure of the industry and the means used to reimburse care providers. Information technology (IT) is seen as a critical contributor to efforts to transform health care delivery. Leveraging a foundation of broadly adopted electronic health records, IT will have four core impacts: — Enabli and improving health care processes — Delivering knowledge to care providers — Engaging patients — Enabling sophisticated analyses of treatment effectiveness and efficiency For IT to achieve its potential research and innovation will be required in several areas.

Purpose: To use a positive control design to evaluate the safety, tolerability, and efficacy of split-dosed L-glucose, a non-nutritive enantiomer of D-glucose (Raymer, et al. 2003), as a bowel cleanser before colonoscopy. Methods: Males and nonpregnant females over 18 years who were scheduled to undergo outpatient colonoscopy at one of 3 study sites were eligible. Exclusion criteria included CHF and recent myocardial infarction. Subjects were gender balanced at each site and randomized in a 2:1 ratio to one of two split-dosed prep groups: L-glucose 52.8 g X 52.8 g or polyethylene glycol with ascorbic acid (PEG-AA, MoviPrep®) 1 L X 1 L, which served as a positive control. L-glucose subjects had a light breakfast then clear liquids for the rest of the day. L-glucose was given as two 8-oz (236 mL) doses at 6 pm the evening before colonoscopy and 4 hours before the exam. PEG-AA subjects were permitted a breakfast and light lunch per manufacturer's instructions. PEG-AA was given as two 1-L doses on the evening before and morning of colonoscopy. Bowel cleansing was rated using a global and a segmental scoring system. Laboratory parameters were tested at screening, after the second dose, and on the day following exam. Subjects completed a tolerability questionnaire. Results: 144 subjects (95 L-glucose, 49 PEG-AA) completed the protocol. Study groups were similar in age and ethnicity. Bowel preparation effectiveness is shown in the table below. Mean number of bowel movements in L-glucose subjects was 15.4 ± 6.8 (range 3-41). Side effects reported by L-glucose subjects included bloating (43.2%), anal irritation (37.9%), nausea (34.7%), weakness/faint feeling (18.9%), and vomiting (8.4%); most were rated mild in severity. Compared to males, females in the L-glucose group experienced higher incidences of all queried side effects and significantly higher incidences of nausea (F = 47.9%, M = 21.3%; p = 0.008) and weakness/faint feeling (F = 31.3%, M = 6.4%; p = 0.005). Small but measurable changes in serum electrolytes, liver function tests, and hematology from screening to exam were noted in L-glucose subjects, though none were clinically significant. There were no treatment-emergent serious adverse events. Willingness to repeat the bowel prep for a future exam was reported by 88.4% of L-glucose subjects. Conclusion: L-glucose provided excellent bowel cleansing for colonoscopy with acceptable tolerability in this proof-of-concept study. Females in the L-glucose group reported side effects more frequently than males, a finding that warrants further study. Additional blinded head-to-head studies of L-glucose and available bowel cleansers are needed to further evaluate the effectiveness and safety of this agent in preparation for colonoscopy. Disclosure: Dr Balaban - Consultant: Fleet Laboratories Dr Malek - Speaker's Bureau: Fleet Laboratories Dr Thompson - Consultant: Fleet Laboratories Sherrie McNamara - Employee: Fleet Laboratories. This research was supported by an industry grant from Fleet Laboratories.Table: Effectiveness of bowel cleansing

Purpose: To evaluate the safety, tolerance, and efficacy of three dosing strategies of L-glucose, a non-nutritive enantiomer of D-glucose (Raymer, et al. 2003), as a bowel cleanser prior to colonoscopy. Methods: Men and nonpregnant women over the age of 50 scheduled to undergo routine outpatient colonoscopy were eligible. Exclusion criteria included liver disease, CHF, and creatinine > 1.5 mg/dL. Study enrollment was designed to proceed sequentially in 3 escalating split-dosing cohorts of 24 subjects each (12M, 12F), with the lowest dose enrolling first: 24 g X 24 g, 36 g X 36 g, 48 g X 48 g. Subjects were admitted to one of two Phase I certified study facilities. All subjects drank clear liquids during the entire day before exam. L-glucose was administered as two 8-oz (236 mL) doses, one at 6 pm the evening before colonoscopy and one between 3-4 hours before exam. Bowel cleansing was rated using a global and segmental scoring system. Laboratory parameters were tested at screening, immediately before dosing, 2 hours after the second dose, and on the day following exam. Side effects were recorded by study personnel. Interim analyses of safety and efficacy were used to determine whether to enroll in the highest dosing cohort; if a target success rate of 21/24 Excellent (E) + Good (G) preps was not achieved in the lowest dosing groups, enrollment in the 48 g X 48 g cohort would proceed. Results: 72 subjects (24 in each cohort; 36M, 36F) were enrolled and completed the protocol. The cohorts were similar in age, ethnicity, and BMI. Bowel preparation success (E + G) was achieved in 19/24 (24 g), 21/24 (36 g), and 23/24 (48 g) subjects [see Table]. A dose-response relationship was observed for mean number of bowel movements: 7.6 ± 2.6 (24 g), 10.6 ± 3.9 (36 g), and 11.5 ± 5.5 (48 g). Tolerance to the bowel preparation process was rated “Good” or “Very Good” in 91.7% (24 g), 75.0% (36 g), and 87.5% (48 g). Side effects were reported as mild or moderate in all groups. Vomiting occurred in 2/24 (8.73%) 24 g subjects and 0/48 36 g and 48 g subjects. Taste was rated “Very Pleasant” or “Somewhat Pleasant” in 20/24 (24 g), 19/24 (36 g), and 20/24 (48 g) subjects. No adverse trends were observed in vital signs, routine hematology, serum chemistry, urinalysis, or liver function tests following treatment in each cohort. 70/72 (97.2%) subjects reported a willingness to take the preparation for a future exam.Table: Bowel preparation effectivenessConclusion: In this open-label feasibility study, L-glucose produced superior bowel cleansing in a split-dose of 48 g X 48 g with excellent tolerance and no significant adverse effects. Disclosure: Dr Balaban - Consultant, Fleet Laboratories Dr Thompson - Consultant, Fleet Laboratories. This research was supported by an industry grant from Fleet Laboratories.

We consider the interaction between interleukin-1 IL-1, its receptor IL-1RI, the receptor antagonist IL-1Ra and a decoy receptor (or trap) that binds both with the ligand and the antagonist. We study how the interaction between IL-1Ra and the decoy receptor influences the effect of either reagent on reducing the equilibrium concentration of the receptor–ligand complex. We obtain that, given a certain relationship among the equilibrium constants and the total concentrations of solutes, IL-1Ra can reverse the effect of the decoy receptor of decreasing the equilibrium concentration of the receptor–ligand complex. This finding derives from a mathematical result applicable to any reversible chemical reaction system comprising four species arranged in a square such that each species binds its two immediate neighbors. The result gives the monotonicity of the equilibrium concentrations of the complex species as functions of the total concentrations of the simple species.

Effective analysis of high throughput screening (HTS) data requires automation of dose-response curve fitting for large numbers of datasets. Datasets with outliers are not handled well by standard non-linear least squares methods, and manual outlier removal after visual inspection is tedious and potentially biased. We propose robust non-linear regression via M-estimation as a statistical technique for automated implementation. The approach of finding M-estimates by Iteratively Reweighted Least Squares (IRLS) and the resulting optimization problem are described. Initial parameter estimates for iterative methods are important, so self-starting methods for our model are presented. We outline the software implementation, done in Matlab and deployed as an Excel application via the Matlab Excel Builder Toolkit. Results of M-estimation are compared with least squares estimates before and after manual editing.

Recent development in automated patch-clamp platforms has transformed the preclinical drug development landscape by incorporating electrophysiological assays at early stages of drug screening. PatchXpress 7000A, an automated 16-channel parallel patch-clamp platform, has a higher throughput than the conventional whole cell patch clamp. We developed and optimized assay conditions for the human ether-a-go-go channel (hERG) on an automated patch-clamp system such as PatchXpress 7000A. We applied nonlinear mixed models to quantify the consistency of the assay from cell to cell and to provide an accurate measure of drug potency over the population of the same cell type. The well-known hERG blocker quinidine was used in the experiments. The results of this novel statistical approach are the estimate of the average potency for the population of the cells with high degree of accuracy and the estimate of the potency variability from cell to cell. This method revealed no significant difference in the potency estimates for our assay and for conventional patch-clamp platform. We suggest that the novel data analysis can accurately predict compound potency when the assay protocols may have a small number of test concentrations and repeated measurements. (JALA 2006;11:195–202)

The role of thermal unfolding as it pertains to thermodynamic properties of proteins and their stability has been the subject of study for more than 50 years. Moreover, exactly how the unfolding properties of a given protein system may influence the kinetics of aggregation has not been fully characterized. In the study of recombinant human Interleukin-1 receptor type II (rhuIL-1R(II)) aggregation, data obtained from size exclusion chromatography and differential scanning calorimetry (DSC) were used to model the thermodynamic and kinetic properties of irreversible denaturation. A break from linearity in the initial aggregation rates as a function of 1/T was observed in the vicinity of the melting transition temperature (T-m 53.5 degrees C), suggesting significant involvement of protein unfolding in the reaction pathway. A scan-rate dependence in the DSC experiment testifies to the nonequilibrium influences of the aggregation process. A mechanistic model was developed to extract meaningful thermodynamic and kinetic parameters from an irreversibly denatured process. The model was used to simulate how unfolding properties could be used to predict aggregation rates at different temperatures above and below the Tm and to account for concentration dependence of reaction rates. The model was shown to uniquely identify the thermodynamic parameters Delta C-p (1.3 +/- 0.7 kcal/mol-K), Delta H-m (74.3 +/- 6.8 kcal/mol), and T-m with reasonable variances.