Interpretation of Natural-language Robot Instructions: Probabilistic Knowledge Representation, Learning, and Reasoning

A robot that can be simply told in natural language what to do -- this has been one of the ultimate long-standing goals in both Artificial Intelligence and Robotics research. In near-future applications, robotic assistants and companions will have to understand and perform commands such as set the table for dinner'', make pancakes for breakfast'', or cut the pizza into 8 pieces.'' Although such instructions are only vaguely formulated, complex sequences of sophisticated and accurate manipulation activities need to be carried out in order to accomplish the respective tasks. The acquisition of knowledge about how to perform these activities from huge collections of natural-language instructions from the Internet has garnered a lot of attention within the last decade. However, natural language is typically massively unspecific, incomplete, ambiguous and vague and thus requires powerful means for interpretation. This work presents PRAC -- Probabilistic Action Cores -- an interpreter for natural-language instructions which is able to resolve vagueness and ambiguity in natural language and infer missing information pieces that are required to render an instruction executable by a robot. To this end, PRAC formulates the problem of instruction interpretation as a reasoning problem in first-order probabilistic knowledge bases. In particular, the system uses Markov logic networks as a carrier formalism for encoding uncertain knowledge. A novel framework for reasoning about unmodeled symbolic concepts is introduced, which incorporates ontological knowledge from taxonomies and exploits semantically similar relational structures in a domain of discourse. The resulting reasoning framework thus enables more compact representations of knowledge and exhibits strong generalization performance when being learnt from very sparse data. Furthermore, a novel approach for completing directives is presented, which applies semantic analogical reasoning to transfer knowledge collected from thousands of natural-language instruction sheets to new situations. In addition, a cohesive processing pipeline is described that transforms vague and incomplete task formulations into sequences of formally specified robot plans. The system is connected to a plan executive that is able to execute the computed plans in a simulator. Experiments conducted in a publicly accessible, browser-based web interface showcase that PRAC is capable of closing the loop from natural-language instructions to their execution by a robot

A novel tissue engineered three-dimensional in vitro colorectal cancer model

The interactions of cancer cells within a solid mass with the surrounding reactive stroma are critical for growth and progression. The surrounding vasculature is recruited into the periphery of the growing tumour to supply cancer cells with nutrients and O2. This study focuses on developing a novel three-dimensional (3-D) in vitro biomimetic colorectal cancer model using colorectal cancer cells and connective tissue cells. The 3-D model comprises a dense artificial cancer mass, created by partial plastic compression of collagen type I containing HT29 colorectal cancer cells, nested in a non-dense collagen type I gel populated by fibroblasts and/or endothelial cells. HT29 cells within the dense mass proliferate slower than when cultured in a two-dimensional system. These cells form tumour spheroids which invade the surrounding matrix, away from the hypoxic conditions in the core of the construct, measured using real time O2 probes. This model is also characterized by the release of vascular endothelial growth factor (VEGF) by HT29 cells, mainly at the invading edge of the artificial cancer mass. This characterization is fundamental in establishing a reproducible, complex model that could be used to advance our understanding of cancer pathology and will facilitate therapeutic drug testing

Joint Probability Trees

We introduce Joint Probability Trees (JPT), a novel approach that makes learning of and reasoning about joint probability distributions tractable for practical applications. JPTs support both symbolic and subsymbolic variables in a single hybrid model, and they do not rely on prior knowledge about variable dependencies or families of distributions. JPT representations build on tree structures that partition the problem space into relevant subregions that are elicited from the training data instead of postulating a rigid dependency model prior to learning. Learning and reasoning scale linearly in JPTs, and the tree structure allows white-box reasoning about any posterior probability $P(Q|E)$, such that interpretable explanations can be provided for any inference result. Our experiments showcase the practical applicability of JPTs in high-dimensional heterogeneous probability spaces with millions of training samples, making it a promising alternative to classic probabilistic graphical models

The next level of 3D tumour models: immunocompetence

The complexity of the tumour microenvironment encompasses interactions between cancer and stromal cells. Moving from 2D cell culture methods into 3D models enables more-accurate investigation of those interactions. Current 3D cancer models focus on cancer spheroid interaction with stromal cells, such as fibroblasts. However, over recent years, the cancer immune environment has been shown to have a major role in tumour progression. This review summarises the state-of-art on immunocompetent 3D cancer models that, in addition to cancer cells, also incorporate immune cells, including monocytes, cancer-associated macrophages, dendritic cells, neutrophils and lymphocytes

The anti-angiogenic tyrosine kinase inhibitor Pazopanib kills cancer cells and disrupts endothelial networks in biomimetic 3D renal tumouroids

Pazopanib is a tyrosine kinase inhibitor used to treat renal cell carcinoma. Few in vitro studies investigate its effects towards cancer cells or endothelial cells in the presence of cancer. We tested the effect of Pazopanib on renal cell carcinoma cells (CAKI-2,786-O) in two-dimensional and three-dimensional tumouroids made of dense extracellular matrix, treated in normoxia and hypoxia. Finally, we engineered complex tumouroids with a stromal compartment containing fibroblasts and endothelial cells. Simple CAKI-2 tumouroids were more resistant to Pazopanib than 786-O tumouroids. Under hypoxia, while the more ‘resistant’ CAKI-2 tumouroids showed no decrease in viability, 786-O tumouroids required higher Pazopanib concentrations to induce cell death. In complex tumouroids, Pazopanib exposure led to a reduction in the overall cell viability (p < 0.0001), disruption of endothelial networks and direct killing of renal cell carcinoma cells. We report a biomimetic multicellular tumouroid for drug testing, suitable for agents whose primary target is not confined to cancer cells

Oncogenic Ras deregulates cell-substrate interactions during mitotic rounding and respreading to alter cell division orientation

Oncogenic Ras has been shown to change the way cancer cells divide by increasing the forces generated during mitotic rounding. In this way, RasV12 enables cancer cells to divide across a wider range of mechanical environments than normal cells. Here, we identify a further role for oncogenic Ras-ERK signaling in division by showing that RasV12 expression alters the shape, division orientation, and respreading dynamics of cells as they exit mitosis. Many of these effects appear to result from the impact of RasV12 signaling on actomyosin contractility, because RasV12 induces the severing of retraction fibers that normally guide spindle positioning and provide a memory of the interphase cell shape. In support of this idea, the RasV12 phenotype is reversed by inhibition of actomyosin contractility and can be mimicked by the loss of cell-substrate adhesion during mitosis. Finally, we show that RasV12 activation also perturbs division orientation in cells cultured in 2D epithelial monolayers and 3D spheroids. Thus, the induction of oncogenic Ras-ERK signaling leads to rapid changes in division orientation that, along with the effects of RasV12 on cell growth and cell-cycle progression, are likely to disrupt epithelial tissue organization and contribute to cancer dissemination

Bioelectrical impedance analysis in clinical practice: implications for hepatitis C therapy BIA and hepatitis C

<p>Abstract</p> <p>Background</p> <p>Body composition analysis using phase angle (PA), determined by bioelectrical impedance analysis (BIA), reflects tissue electrical properties and has prognostic value in liver cirrhosis. Objective of this prospective study was to investigate clinical use and prognostic value of BIA-derived phase angle and alterations in body composition for hepatitis C infection (HCV) following antiviral therapy.</p> <p>Methods</p> <p>37 consecutive patients with HCV infection were enrolled, BIA was performed, and PA was calculated from each pair of measurements. 22 HCV genotype 3 patients treated for 24 weeks and 15 genotype 1 patients treated for 48 weeks, were examined before and after antiviral treatment and compared to 10 untreated HCV patients at 0, 24, and 48 weeks. Basic laboratory data were correlated to body composition alterations.</p> <p>Results</p> <p>Significant reduction in body fat (BF: 24.2 ± 6.7 kg vs. 19.9 ± 6.6 kg, genotype1; 15.4 ± 10.9 kg vs. 13.2 ± 12.1 kg, genotype 3) and body cell mass (BCM: 27.3 ± 6.8 kg vs. 24.3 ± 7.2 kg, genotype1; 27.7 ± 8.8 kg vs. 24.6 ± 7.6 kg, genotype 3) was found following treatment. PA in genotype 3 patients was significantly lowered after antiviral treatment compared to initial measurements (5.9 ± 0.7° vs. 5.4 ± 0.8°). Total body water (TBW) was significantly decreased in treated patients with genotype 1 (41.4 ± 7.9 l vs. 40.8 ± 9.5 l). PA reduction was accompanied by flu-like syndromes, whereas TBW decline was more frequently associated with fatigue and cephalgia.</p> <p>Discussion</p> <p>BIA offers a sophisticated analysis of body composition including BF, BCM, and TBW for HCV patients following antiviral regimens. PA reduction was associated with increased adverse effects of the antiviral therapy allowing a more dynamic therapy application.</p

Electrochemical and Spectroelectrochemical Comparative Study of Macrocyclic Thermally Activated Delayed Fluorescent Compounds: Molecular Charge Stability vs OLED EQE Roll-Off

In this work, we present how a small change in molecular structure can affect the electrochemical stability of organic compounds. A new electron donor-acceptor-donor-acceptor (D-A-D-A) macrocyclic π-conjugated compound (tBuMC) comprising of dibenzophenazine as As and N,N’-bis(t-butylphenyl)-p-phenylenediamines as Ds has been synthesized. The photophysical investigation uncovered that tBuMC showed thermally activated delayed fluorescence and that the organic light-emitting diodes (OLEDs) fabricated with tBuMC as the emitter achieved high external quantum efficiency (EQEs) of ca. 10%. However, the OLED with tBuMC showed a slightly lower EQE than that of the OLED with MC (11.6%) and showed greater EQE roll-off. Comparative studies on electrochemical properties of tBuMC, MC, and a linear analogue (Linear) revealed the introduction of t-Bu groups in the D-A-D-A scaffold causes a significant change in redox behavior. Full electrochemical and spectroelectrochemical studies gave clues to understand how the steric hindering group is affecting the charge distribution in the new molecules which results in a significant difference in the OLED roll-off. The electrochemical investigations together with UV-Vis-NIR and EPR analyses supported by quantum chemical theoretical calculations were performed, which provided us insights on the effect of structural modification on the redox properties of the D-A-D-A scaffold.This is the peer reviewed version of the following article: A. Nyga, S. Izumi, H. F. Higginbotham, P. Stachelek, S. Pluczyk, P. de Silva, S. Minakata, Y. Takeda, P. Data, Asian J. Org. Chem. 2020, 9, 2153., which has been published in final form at https://doi.org/10.1002/ajoc.202000475. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving