Learning Robot Control using a Hierarchical SOM-based Encoding

Hierarchical representations and modeling of sensorimotor observations is a fundamental approach for the development of scalable robot control strategies. Previously, we introduced the novel Hierarchical Self-Organizing Map-based Encoding algorithm (HSOME) that is based on a computational model of infant cognition. Each layer is a temporally augmented SOM and every node updates a decaying activation value. The bottom level encodes sensori-motor instances while their temporal associations are hierarchically built on the layers above. In the past, HSOME has shown to support hierarchical encoding of sequential sensor-actuator observations both in abstract domains and real humanoid robots. Two novel features are presented here starting with the novel skill acquisition in the complex domain of learning a double tap tactile gesture between two humanoid robots. During reproduction, the robot can either perform a double tap or prioritize to receive a higher reward by performing a single tap instead. Secondly, HSOME has been extended to recall past observations and reproduce rhythmic patterns in the absence of input relevant to the joints by priming initially the reproduction of specific skills with an input. We also demonstrate in simulation how a complex behavior emerges from the automatic reuse of distinct oscillatory swimming demonstrations of a robotic salamander

Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization

Adversarial self-play in two-player games has delivered impressive results when used with reinforcement learning algorithms that combine deep neural networks and tree search. Algorithms like AlphaZero and Expert Iteration learn tabula-rasa, producing highly informative training data on the fly. However, the self-play training strategy is not directly applicable to single-player games. Recently, several practically important combinatorial optimisation problems, such as the travelling salesman problem and the bin packing problem, have been reformulated as reinforcement learning problems, increasing the importance of enabling the benefits of self-play beyond two-player games. We present the Ranked Reward (R2) algorithm which accomplishes this by ranking the rewards obtained by a single agent over multiple games to create a relative performance metric. Results from applying the R2 algorithm to instances of a two-dimensional and three-dimensional bin packing problems show that it outperforms generic Monte Carlo tree search, heuristic algorithms and integer programming solvers. We also present an analysis of the ranked reward mechanism, in particular, the effects of problem instances with varying difficulty and different ranking thresholds

Tiling Histone H3 Lysine 4 and 27 Methylation in Zebrafish Using High-Density Microarrays

BACKGROUND: Uncovering epigenetic states by chromatin immunoprecipitation and microarray hybridization (ChIP-chip) has significantly contributed to the understanding of gene regulation at the genome-scale level. Many studies have been carried out in mice and humans; however limited high-resolution information exists to date for non-mammalian vertebrate species. PRINCIPAL FINDINGS: We report a 2.1-million feature high-resolution Nimblegen tiling microarray for ChIP-chip interrogations of epigenetic states in zebrafish (Danio rerio). The array covers 251 megabases of the genome at 92 base-pair resolution. It includes ∼15 kb of upstream regulatory sequences encompassing all RefSeq promoters, and over 5 kb in the 5' end of coding regions. We identify with high reproducibility, in a fibroblast cell line, promoters enriched in H3K4me3, H3K27me3 or co-enriched in both modifications. ChIP-qPCR and sequential ChIP experiments validate the ChIP-chip data and support the co-enrichment of trimethylated H3K4 and H3K27 on a subset of genes. H3K4me3- and/or H3K27me3-enriched genes are associated with distinct transcriptional status and are linked to distinct functional categories. CONCLUSIONS: We have designed and validated for the scientific community a comprehensive high-resolution tiling microarray for investigations of epigenetic states in zebrafish, a widely used developmental and disease model organism

Narcissism in patients admitted to psychiatric acute wards: its relation to violence, suicidality and other psychopathology

<p>Abstract</p> <p>Background</p> <p>The objective was to examine various aspects of narcissism in patients admitted to acute psychiatric wards and to compare their level of narcissism to that of an age- and gender-matched sample from the general population (NORM).</p> <p>Methods</p> <p>This cross-sectional study interviewed 186 eligible acute psychiatric patients with the Brief Psychiatric Rating Scale (BPRS) and the Global Assessment of Functioning (GAF). The patients filled in the Narcissistic Personality Inventory-21 item version (NPI-21), The Hospital Anxiety and Depression Scale (HADS) and the Rosenberg Self-Esteem Scale. High and low narcissism was defined by the median of the total NPI-21 score. An age- and gender-matched control sample from the general population also scored the NPI-21 (NORM).</p> <p>Results</p> <p>Being male, involuntary admitted, having diagnosis of schizophrenia, higher self-esteem, and severe violence were significantly associated with high narcissism, and so were also low levels of suicidality, depression, anxiety and GAF scores. Severe violence and high self-esteem were significantly associated with high narcissism in multivariable analyses. The NPI-21 and its subscales showed test-retest correlations ≥0.83, while the BPRS and the HADS showed lower correlations, confirming the trait character of the NPI-21. Depression and suicidality were negatively associated with the NPI-21 total score and all its subscales, while positive association was observed with grandiosity. No significant differences were observed between patients and NORM on the NPI-21 total score or any of the NPI subscales.</p> <p>Conclusion</p> <p>Narcissism in the psychiatric patients was significantly associated with violence, suicidality and other symptoms relevant for management and treatment planning. Due to its trait character, use of the NPI-21 in acute psychiatric patients can give important clinical information. The similar level of narcissism found in patients and NORM is in need of further examination.</p

New Insights into Metabolic Properties of Marine Bacteria Encoding Proteorhodopsins

Proteorhodopsin phototrophy was recently discovered in oceanic surface waters. In an effort to characterize uncultured proteorhodopsin-exploiting bacteria, large-insert bacterial artificial chromosome (BAC) libraries from the Mediterranean Sea and Red Sea were analyzed. Fifty-five BACs carried diverse proteorhodopsin genes, and we confirmed the function of five. We calculate that proteorhodopsin-exploiting bacteria account for 13% of microorganisms in the photic zone. We further show that some proteorhodopsin-containing bacteria possess a retinal biosynthetic pathway and a reverse sulfite reductase operon, employed by prokaryotes oxidizing sulfur compounds. Thus, these novel phototrophs are an unexpectedly large and metabolically diverse component of the marine microbial surface water

Assessment of personal care and medical robots from older adults' perspective

Demographic reports indicate that population of older adults is growing significantly over the world and in particular in developed nations. Consequently, there are a noticeable number of demands for certain services such as health-care systems and assistive medical robots and devices. In today's world, different types of robots play substantial roles specifically in medical sector to facilitate human life, especially older adults. Assistive medical robots and devices are created in various designs to fulfill specific needs of older adults. Though medical robots are utilized widely by senior citizens, it is dramatic to find out into what extent assistive robots satisfy their needs and expectations. This paper reviews various assessments of assistive medical robots from older adults' perspectives with the purpose of identifying senior citizen's needs, expectations, and preferences. On the other hand, these kinds of assessments inform robot designers, developers, and programmers to come up with robots fulfilling elderly's needs while improving their life quality

Exploiting Clinical Trial Data Drastically Narrows the Window of Possible Solutions to the Problem of Clinical Adaptation of a Multiscale Cancer Model

The development of computational models for simulating tumor growth and response to treatment has gained significant momentum during the last few decades. At the dawn of the era of personalized medicine, providing insight into complex mechanisms involved in cancer and contributing to patient-specific therapy optimization constitute particularly inspiring pursuits. The in silico oncology community is facing the great challenge of effectively translating simulation models into clinical practice, which presupposes a thorough sensitivity analysis, adaptation and validation process based on real clinical data. In this paper, the behavior of a clinically-oriented, multiscale model of solid tumor response to chemotherapy is investigated, using the paradigm of nephroblastoma response to preoperative chemotherapy in the context of the SIOP/GPOH clinical trial. A sorting of the model's parameters according to the magnitude of their effect on the output has unveiled the relative importance of the corresponding biological mechanisms; major impact on the result of therapy is credited to the oxygenation and nutrient availability status of the tumor and the balance between the symmetric and asymmetric modes of stem cell division. The effect of a number of parameter combinations on the extent of chemotherapy-induced tumor shrinkage and on the tumor's growth rate are discussed. A real clinical case of nephroblastoma has served as a proof of principle study case, demonstrating the basics of an ongoing clinical adaptation and validation process. By using clinical data in conjunction with plausible values of model parameters, an excellent fit of the model to the available medical data of the selected nephroblastoma case has been achieved, in terms of both volume reduction and histological constitution of the tumor. In this context, the exploitation of multiscale clinical data drastically narrows the window of possible solutions to the clinical adaptation problem