A Learning-Based Framework for Safe Human-Robot Collaboration with Multiple Backup Control Barrier Functions

Ensuring robot safety in complex environments is a difficult task due to actuation limits, such as torque bounds. This paper presents a safety-critical control framework that leverages learning-based switching between multiple backup controllers to formally guarantee safety under bounded control inputs while satisfying driver intention. By leveraging backup controllers designed to uphold safety and input constraints, backup control barrier functions (BCBFs) construct implicitly defined control invariance sets via a feasible quadratic program (QP). However, BCBF performance largely depends on the design and conservativeness of the chosen backup controller, especially in our setting of human-driven vehicles in complex, e.g, off-road, conditions. While conservativeness can be reduced by using multiple backup controllers, determining when to switch is an open problem. Consequently, we develop a broadcast scheme that estimates driver intention and integrates BCBFs with multiple backup strategies for human-robot interaction. An LSTM classifier uses data inputs from the robot, human, and safety algorithms to continually choose a backup controller in real-time. We demonstrate our method's efficacy on a dual-track robot in obstacle avoidance scenarios. Our framework guarantees robot safety while adhering to driver intention

A regulatory network comprising let-7 miRNA and SMUG1 is associated with good prognosis in ER+ breast tumours

Single-strand selective uracil–DNA glycosylase 1 (SMUG1) initiates base excision repair (BER) of uracil and oxidized pyrimidines. SMUG1 status has been associated with cancer risk and therapeutic response in breast carcinomas and other cancer types. However, SMUG1 is a multifunctional protein involved, not only, in BER but also in RNA quality control, and its function in cancer cells is unclear. Here we identify several novel SMUG1 interaction partners that functions in many biological processes relevant for cancer development and treatment response. Based on this, we hypothesized that the dominating function of SMUG1 in cancer might be ascribed to functions other than BER. We define a bad prognosis signature for SMUG1 by mapping out the SMUG1 interaction network and found that high expression of genes in the bad prognosis network correlated with lower survival probability in ER(+) breast cancer. Interestingly, we identified hsa-let-7b-5p microRNA as an upstream regulator of the SMUG1 interactome. Expression of SMUG1 and hsa-let-7b-5p were negatively correlated in breast cancer and we found an inhibitory auto-regulatory loop between SMUG1 and hsa-let-7b-5p in the MCF7 breast cancer cells. We conclude that SMUG1 functions in a gene regulatory network that influence the survival and treatment response in several cancers

NeBula: Team CoSTAR's robotic autonomy solution that won phase II of DARPA Subterranean Challenge

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR¿s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.The work is partially supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004), and Defense Advanced Research Projects Agency (DARPA)

A review of the potential role of human cytomegalovirus (HCMV) infections in breast cancer carcinogenesis and abnormal immunity

Previously recognized classical human onco-viruses can regulate complex neoplastic events, and are estimated to play a role during carcinogenesis in 15–20% of cancer cases. Although the DNA and gene products of several viruses have been found in breast tumors, none of the classical onco-viruses have definitely been linked to the initiation of breast cancer. However, recent evidence shows that human cytomegalovirus (HCMV) gene products are found in >90% of tumors and metastases of breast cancers, and their increased expression can be correlated to a more aggressive breast cancer phenotype. Supporting the active role of HCMV in breast cancer, a specific HCMV strain, HCMV-DB, was recently shown to exert oncogenic transformational activity in breast epithelial cells in vitro, and to give rise to fast-growing, triple-negative breast tumors when injected into immune deficient mice. The same observation holds true for clinical studies implying increased HCMV protein expression in triple negative breast cancer biopsies. In addition to functionally being able to hijack tumor-promoting cellular events, HCMV is known to exhibit a wide range of immunosuppressive effects, which can have radical impact on the tumor microenvironment. HCMV infected cells can avoid recognition and elimination by the immune system by orchestrating polarization of immunosuppressive type II macrophages, preventing antigen presentation, by expressing T cell inhibitory molecules, and possibly, by the induction of regulatory T (Treg) cell responses. These actions would be especially deleterious for the antigenic activation and proliferation of tumor specific CD8+ cytotoxic T lymphocytes (CTLs), whose effector functions have recently been targeted by successful, experimental immunotherapy protocols. The recognition of alternative causes and drivers of breast cancer is a pivotal research topic for the development of diagnostics and novel, effective preventive and therapeutic strategies targeting both tumor cells and their microenvironments

Inter-rater reliability of risk of bias tools for non-randomized studies

Abstract Purpose There is limited knowledge on the reliability of risk of bias (ROB) tools for assessing internal validity in systematic reviews of exposure and frequency studies. We aimed to identify and then compare the inter-rater reliability (IRR) of six commonly used tools for frequency (Loney scale, Gyorkos checklist, American Academy of Neurology [AAN] tool) and exposure (Newcastle–Ottawa scale, SIGN50 checklist, AAN tool) studies. Methods Six raters independently assessed the ROB of 30 frequency and 30 exposure studies using the three respective ROB tools. Articles were rated as low, intermediate, or high ROB. We calculated an intraclass correlation coefficient (ICC) for each tool and category of ROB tool. We compared the IRR between ROB tools and tool type by inspection of overlapping ICC 95% CIs and by comparing their coefficients after transformation to Fisher’s Z values. We assessed the criterion validity of the AAN ROB tools by calculating an ICC for each rater in comparison with the original ratings from the AAN. Results All individual ROB tools had an IRR in the substantial range or higher (ICC point estimates between 0.61 and 0.80). The IRR was almost perfect (ICC point estimate > 0.80) for the AAN frequency tool and the SIGN50 checklist. All tools were comparable in IRR, except for the AAN frequency tool which had a significantly higher ICC than the Gyorkos checklist (p = 0.021) and trended towards a higher ICC when compared to the Loney scale (p = 0.085). When examined by category of ROB tool, scales, and checklists had a substantial IRR, whereas the AAN tools had an almost perfect IRR. For the criterion validity of the AAN ROB tools, the average agreement between our raters and the original AAN ratings was moderate. Conclusion All tools had substantial IRRs except for the AAN frequency tool and the SIGN50 checklist, which both had an almost perfect IRR. The AAN ROB tools were the only category of ROB tools to demonstrate an almost perfect IRR. This category of ROB tools had fewer and simpler criteria. Overall, parsimonious tools with clear instructions, such as those from the AAN, may provide more reliable ROB assessments

Low Expression of Estrogen Receptor-α and Progesterone Receptor in Human Breast Cancer Tissues Is Associated With High-Grade Human Cytomegalovirus Protein Expression

Background The underlying mechanisms for breast cancer (BC) are largely unknown. We investigated possible correlations between the expression levels of human cytomegalovirus (HCMV) proteins and established histopathological markers of BC, including expression of estrogen receptor (ER)-α, the progesterone receptor (PgR), and HER2. Materials and Methods We retrospectively examined paraffin-embedded biopsy specimens of BC (n = 62), ductal carcinoma in situ (n = 19), and adjacent normal breast tissue (n = 42) for HCMV immediate-early protein (IE), HCMV late antigen, HCMV DNA and RNA, and investigated possible correlations between them and expression of ER-α, PgR, and HER2. Results HCMV DNA and RNA were detected in all examined infiltrating BCs. High-grade positivity for HCMV-IE was detected in 77% of infiltrating BCs, 39% of ductal carcinomas in situ, and 7% of tumor-free breast tissue samples. HCMV expression correlated inversely with ER-α (P = .02) and PgR (P = .003) expression. HER2 expression was also reduced in HCMV-positive samples without reaching a level of statistical significance (P = .09). Conclusion The negative correlation between high-grade expression HCMV-IE and hormone receptor expression suggests a role for HCMV in hormone receptor-negative BC tumors, possibly by forcing BC cells into a more aggressive phenotype. Rahbar, Afsar, et al. "Low Expression of Estrogen Receptor-α and Progesterone Receptor in Human Breast Cancer Tissues Is Associated With High-Grade Human Cytomegalovirus Protein Expression." Clinical breast cancer 17.7 (2017): 526-535. © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license