Human Robot Interaction and Usability Studies for a Smart Wheelchair

We build on previous work [12], [14] on the development of a computer controlled wheelchair equipped with a suite of sensors and a novel interface for human-robot interaction. In this paper, we present experimental results and usability studies for the wheelchair. The architecture for human-robot interaction is hierarchical, with the lowest level corresponding to trajectory control, the intermediate level being behavioral and the highest level involving the composition of behaviors and navigation. Our experimental results illustrate the benefits of a shared-control paradigm where the human operator selects the appropriate hehavior(s) or goals while the software is responsible for executing behaviors and generating safe trajectories. Experiments with human users highlight advantages of augmentation in wheelchairs

ACR-ARS Practice Parameter for the Performance of Proton Beam Therapy

PURPOSE: This practice parameter for the performance of proton beam radiation therapy was revised collaboratively by the American College of Radiology (ACR) and the American Radium Society (ARS). This practice parameter was developed to serve as a tool in the appropriate application of proton therapy in the care of cancer patients or other patients with conditions in which radiation therapy is indicated. It addresses clinical implementation of proton radiation therapy, including personnel qualifications, quality assurance (QA) standards, indications, and suggested documentation. MATERIALS AND METHODS: This practice parameter for the performance of proton beam radiation therapy was developed according to the process described under the heading The Process for Developing ACR Practice Parameters and Technical Standards on the ACR website (https://www.acr.org/Clinical-Resources/Practice-Parameters-and-Technical-Standards) by the Committee on Practice Parameters - Radiation Oncology of the ACR Commission on Radiation Oncology in collaboration with the ARS. RESULTS: The qualifications and responsibilities of personnel, such as the proton center Chief Medical Officer or Medical Director, Radiation Oncologist, Radiation Physicist, Dosimetrist and Therapist, are outlined, including the necessity for continuing medical education. Proton therapy standard clinical indications and methodologies of treatment management are outlined by disease site and treatment group (e.g. pediatrics) including documentation and the process of proton therapy workflow and equipment specifications. Additionally, this proton therapy practice parameter updates policies and procedures related to a quality assurance and performance improvement program (QAPI), patient education, infection control, and safety. CONCLUSION: As proton therapy becomes more accessible to cancer patients, policies and procedures as outlined in this practice parameter will help ensure quality and safety programs are effectively implemented to optimize clinical care

A Phase II Trial of the WEE1 Inhibitor Adavosertib in SETD2-Altered Advanced Solid Tumor Malignancies (NCI 10170).

UNLABELLED: We sought to evaluate the efficacy of WEE1 inhibitor adavosertib in patients with solid tumor malignancies (cohort A) and clear cell renal cell carcinoma (ccRCC; cohort B). NCT03284385 was a parallel cohort, Simon two-stage, phase II study of adavosertib (300 mg QDAY by mouth on days 1-5 and 8-12 of each 21-day cycle) in patients with solid tumor malignancies harboring a pathogenic SETD2 mutation. The primary endpoint was the objective response rate. Correlative assays evaluated the loss of H3K36me3 by IHC, a downstream consequence of SETD2 loss, in archival tumor tissue. Eighteen patients were enrolled (9/cohort). The median age was 60 years (range 45-74). The median duration of treatment was 1.28 months (range 0-24+). No objective responses were observed in either cohort; accrual was halted following stage 1. Minor tumor regressions were observed in 4/18 (22%) evaluable patients. Stable disease (SD) was the best overall response in 10/18 (56%) patients, including three patients with SD > 4 months. One patient with ccRCC remains on treatment for >24 months. The most common adverse events of any grade were nausea (59%), anemia (41%), diarrhea (41%), and neutropenia (41%). Nine patients (50%) experienced a Grade ≥3 adverse event. Of eight evaluable archival tissue samples, six (75%) had a loss of H3K36me3 by IHC. Adavosertib failed to exhibit objective responses in SETD2-altered ccRCC and other solid tumor malignancies although prolonged SD was observed in a subset of patients. Combination approaches may yield greater depth of tumor response. SIGNIFICANCE: WEE1 inhibition with adavosertib monotherapy demonstrated limited clinical activity in patients with SETD2-altered solid tumors despite compelling preclinical data indicating a synthetic lethal effect, which did not translate into robust tumor regression. Loss of the H3K36me3 trimethylation mark caused by SETD2-deficiency was confirmed in the majority of evaluable tumors. A subset of patients derived clinical benefit as manifested by minor tumor regressions and prolonged SD

Revolutionizing physics: a comprehensive survey of machine learning applications

In the context of the 21st century and the fourth industrial revolution, the substantial proliferation of data has established it as a valuable resource, fostering enhanced computational capabilities across scientific disciplines, including physics. The integration of Machine Learning stands as a prominent solution to unravel the intricacies inherent to scientific data. While diverse machine learning algorithms find utility in various branches of physics, there exists a need for a systematic framework for the application of Machine Learning to the field. This review offers a comprehensive exploration of the fundamental principles and algorithms of Machine Learning, with a focus on their implementation within distinct domains of physics. The review delves into the contemporary trends of Machine Learning application in condensed matter physics, biophysics, astrophysics, material science, and addresses emerging challenges. The potential for Machine Learning to revolutionize the comprehension of intricate physical phenomena is underscored. Nevertheless, persisting challenges in the form of more efficient and precise algorithm development are acknowledged within this review

The Taming of Closed Time-like Curves

We consider a $R^{1,d}/Z_2$ orbifold, where $Z_2$ acts by time and space reversal, also known as the embedding space of the elliptic de Sitter space. The background has two potentially dangerous problems: time-nonorientability and the existence of closed time-like curves. We first show that closed causal curves disappear after a proper definition of the time function. We then consider the one-loop vacuum expectation value of the stress tensor. A naive QFT analysis yields a divergent result. We then analyze the stress tensor in bosonic string theory, and find the same result as if the target space would be just the Minkowski space $R^{1,d}$, suggesting a zero result for the superstring. This leads us to propose a proper reformulation of QFT, and recalculate the stress tensor. We find almost the same result as in Minkowski space, except for a potential divergence at the initial time slice of the orbifold, analogous to a spacelike Big Bang singularity. Finally, we argue that it is possible to define local S-matrices, even if the spacetime is globally time-nonorientable.Comment: 37 pages, LaTeX2e, uses amssymb, amsmath and epsf macros, 8 eps and 3 ps figures; (v2): Two additional comments + one reference added; (v3): corrections in discussion of CTCs + some clarification

Evidence-based Review on the Use of Proton Therapy in Lymphoma From the Particle Therapy Cooperative Group (PTCOG) Lymphoma Subcommittee.

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