Ground operation of robotics on Space Station Freedom

This paper reflects work carried out on Ground Operated Telerobotics (GOT) in 1992 to refine further the ideas, procedures, and technologies needed to test the procedures in a high latency environment, and to integrate GOT into Space Station Freedom operations. Space Station Freedom (SSF) will be in operation for 30 years, and will depend on robots to carry out a significant part of the assembly, maintenance, and utilization workload. Current plans call for on-orbit robotics to be operated by on-board crew members. This approach implies that on-orbit robotics operations use up considerable crew time, and that these operations cannot be carried out when SSF is unmanned. GOT will allow robotic operations to be operated from the ground, with on-orbit crew interventions only when absolutely required. The paper reviews how GOT would be implemented, how GOT operations would be planned and supported, and reviews GOT issues, critical success factors, and benefits

Neuropsychological profile of executive functions in autism spectrum disorder and schizophrenia spectrum disorders: a comparative group study in adults

[EN] As assessed by numerous neuropsychological tasks, individuals with autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SSDs) have similar impairments related to executive functions (EFs). The neuropsychological profle of these two conditions was examined using the three-component EFs’ framework of Miyake and Friedman(Cogn Psychol 41(1):49-100, 2000). This approach assesses Inhibition (suppression of unwanted and irrelevant information/responses), Updating (use and control of contents of working memory), and Shifting (disengagement between activities or mental tasks) using nine diferent tasks. In line with previous research, we expected greater performance defcits in ASD in all three components compared to SSD, as well as faster responses for the SSD group. A self-paced task format allowed us to examine whether unlimited time given for a task would lead to better performance. The sample was constituted by the control group (N=25), ASD group (N=24), and SSD group (N=12). Groups did not difer on Inhibition performance. In Updating, individuals with SSD performed poorer than the other groups. As for Shifting, both groups demonstrated poorer performance compared to controls, with the SSD group presenting the greatest difculties. In terms of reaction time (RT), SSD participants’ RT were the slowest on Inhibition and Shifting tasks. There was a positive correlation between performance and time spent on Inhibition and Shifting only for the SSD group, which demonstrates that their performance improves when there are no time constraints. Our work provides a better understanding of spared and impaired EFs, which could be useful for designing strategies aimed at improving specifc EFs in each group.Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE

Using Machine Learning to Predict Unplanned Hospital Utilisation and Chemotherapy Management from Patient-Reported Outcome Measures

Purpose Adverse effects of chemotherapy often require hospital admissions or treatment management. Identifying factors contributing to unplanned hospital utilization may improve health care quality and patients' well-being. This study aimed to assess if patient-reported outcome measures (PROMs) improve performance of machine learning (ML) models predicting hospital admissions, triage events (contacting helpline or attending hospital), and changes to chemotherapy. Materials and Methods Clinical trial data were used and contained responses to three PROMs (European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire [QLQ-C30], EuroQol Five-Dimensional Visual Analogue Scale [EQ-5D], and Functional Assessment of Cancer Therapy-General [FACT-G]) and clinical information on 508 participants undergoing chemotherapy. Six feature sets (with following variables: [1] all available; [2] clinical; [3] PROMs; [4] clinical and QLQ-C30; [5] clinical and EQ-5D; [6] clinical and FACT-G) were applied in six ML models (logistic regression [LR], decision tree, adaptive boosting, random forest [RF], support vector machines [SVMs], and neural network) to predict admissions, triage events, and chemotherapy changes. Results The comprehensive analysis of predictive performances of the six ML models for each feature set in three different methods for handling class imbalance indicated that PROMs improved predictions of all outcomes. RF and SVMs had the highest performance for predicting admissions and changes to chemotherapy in balanced data sets, and LR in imbalanced data set. Balancing data led to the best performance compared with imbalanced data set or data set with balanced train set only. Conclusion These results endorsed the view that ML can be applied on PROM data to predict hospital utilization and chemotherapy management. If further explored, this study may contribute to health care planning and treatment personalization. Rigorous comparison of model performance affected by different imbalanced data handling methods shows best practice in ML research

Fault-Tolerant Exact State Transmission

We show that a category of one-dimensional XY-type models may enable high-fidelity quantum state transmissions, regardless of details of coupling configurations. This observation leads to a fault- tolerant design of a state transmission setup. The setup is fault-tolerant, with specified thresholds, against engineering failures of coupling configurations, fabrication imperfections or defects, and even time-dependent noises. We propose the implementation of the fault-tolerant scheme using hard-core bosons in one-dimensional optical lattices.Comment: 5 pages and 4 figure

Special issue: Research report Recollection in adolescents with Autism Spectrum Disorder

a b s t r a c t Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder primarily affecting social interaction and communication. Recently, there has been interest in whether people with ASD also show memory deficits as a result of abnormal brain development. However, at least in adolescents with ASD, the recollection component of episodic memory has rarely been explored. This paper is an evaluation of recollection in three different experiments in adolescents with ASD, using both objective (source discrimination) and subjective methods (RemembereKnow judgments). Methods: Three experiments were designed to measure different aspects of contextual information: sensory/perceptual information (Experiment 1), temporal information (Experiment 2) and spatial information (Experiment 3). To measure objective and subjective recollection, for all three experiments, all participants were presented with information to learn in a specific context. At the recognition stage, they were asked whether they remembered the information or just knew the information was there (R/K response, subjective method). To assess the quality of these subjective judgments, participants justified their Remember responses using the contextual information. After the recognition task, to assess source memory (objective measure), all items presented at encoding were represented and participants have to recall the source for all these items. Results: All three experiments showed that adolescents with ASD could correctly recall source information. However, in the first experiment adolescents with ASD gave significantly fewer Remember responses than controls. Conclusions: These findings point to a specific and subtle recollection impairment in adolescents with ASD, at least when subjective methods are used. We discuss how these might relate to differences in the self and to the brain abnormalities in ASD.

De novo variants disturbing the transactivation capacity of POU3F3 cause a characteristic neurodevelopmental disorder

POU3F3, also referred to as Brain-1, is a well-known transcription factor involved in the development of the central nervous system, but it has not previously been associated with a neurodevelopmental disorder. Here, we report the identification of 19 individuals with heterozygous POU3F3 disruptions, most of which are de novo variants. All individuals had developmental delays and/or intellectual disability and impairments in speech and language skills. Thirteen individuals had characteristic low-set, prominent, and/or cupped ears. Brain abnormalities were observed in seven of eleven MRI reports. POU3F3 is an intronless gene, insensitive to nonsense-mediated decay, and 13 individuals carried protein-truncating variants. All truncating variants that we tested in cellular models led to aberrant subcellular localization of the encoded protein. Luciferase assays demonstrated negative effects of these alleles on transcriptional activation of a reporter with a FOXP2-derived binding motif. In addition to the loss-of-function variants, five individuals had missense variants that clustered at specific positions within the functional domains, and one small in-frame deletion was identified. Two missense variants showed reduced transactivation capacity in our assays, whereas one variant displayed gain-of-function effects, suggesting a distinct pathophysiological mechanism. In bioluminescence resonance energy transfer (BRET) interaction assays, all the truncated POU3F3 versions that we tested had significantly impaired dimerization capacities, whereas all missense variants showed unaffected dimerization with wild-type POU3F3. Taken together, our identification and functional cell-based analyses of pathogenic variants in POU3F3, coupled with a clinical characterization, implicate disruptions of this gene in a characteristic neurodevelopmental disorder

Fire Ant Alate Wing Motion Data and Numerical Reconstruction

The wing motions of a male and a female fire ant alate, which beat their wings at 108 and 96 Hz, respectively, were captured with a stereo imaging system at a high frame rate of 8,000 frames per second. By processing the high-speed image frames, the three-dimensional wingtip positions and the wing surface orientation angles were determined with a high phase resolution, i.e. 74 and 83 phases per period for the male and the female, respectively. A numerical reconstruction of the stereo wingbeat images demonstrated that the data collected described almost all the details of the wing surface motion, so that further computational fluid dynamic simulations are possible for fire ant alate flight

Label-free cell cycle analysis for high-throughput imaging flow cytometry

Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding effects of fluorescent stains while maximizing available fluorescence channels. The method is effective in cell cycle analysis for mammalian cells, both fixed and live, and accurately assesses the impact of a cell cycle mitotic phase blocking agent. As the same method is effective in predicting the DNA content of fission yeast, it is likely to have a broad application to other cell types