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AbstractThe human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in “conjunction hubs”—brain regions that selectively integrate sensory, cognitive, and motor activations. We used recent advances in using functional connectivity to map the flow of activity between brain regions to construct a task-performing neural network model from fMRI data during a cognitive control task. We verified the importance of conjunction hubs in cognitive computations by simulating neural activity flow over this empirically-estimated functional connectivity model. These empirically-specified simulations produced above-chance task performance (motor responses) by integrating sensory and task rule activations in conjunction hubs. These findings reveal the role of conjunction hubs in supporting flexible cognitive computations, while demonstrating the feasibility of using empirically-estimated neural network models to gain insight into cognitive computations in the human brain.

Aim: The neurocognitive basis of Developmental Coordination Disorder (DCD; or motor clumsiness) remains an issue of continued debate. This combined systematic review and meta-analysis provides a synthesis of recent experimental studies on the motor control, cognitive, and neural underpinnings of DCD. Methods: The review included all published work conducted since September 2016 and up to April 2021. One-hundred papers with a DCD-Control comparison were included, with 1,374 effect sizes entered into a multi-level meta-analysis. Results: The most profound deficits were shown in: voluntary gaze control during movement; cognitive-motor integration; practice-/context-dependent motor learning; internal modeling; more variable movement kinematics/kinetics; larger safety margins when locomoting, and atypical neural structure and function across sensori-motor and prefrontal regions. Interpretation: Taken together, these results on DCD suggest fundamental deficits in visual-motor mapping and cognitive-motor integration, and abnormal maturation of motor networks, but also areas of pragmatic compensation for motor control deficits. Implications for current theory, future research, and evidence-based practice are discussed. Systematic Review Registration: PROSPERO, identifier: CRD42020185444.

We develop novel numerical schemes for electrostatic field solvers toward the whole-volume gyrokinetic simulation of stellarators. The gyrokinetic Poisson equation should be solved for complicated magnetic fields in the stellarator without assuming nested flux surfaces and toroidal symmetry. The developed schemes enable us to generate suitable unstructured meshes and obtain the solutions within a limited numerical cost for general magnetic field structures. These schemes will be integrated and utilized in X-point Gyrokinetic Code - Stellarator (XGC-S)., source:https://doi.org/10.1585/pfr.16.2403054, identifier:0000-0003-2513-0453

Background: Metronome cueing has been shown to reduce gait variability and thereby potentially reduce falls risk in individuals with Parkinson's disease. It is unclear however, if metronome cueing has a similar effect in healthy older adults with a history of falls. Aim: To investigate whether a traditional and/or an adaptive metronome, based on an individual's gait pattern, were effective in reducing gait variability in older adults with a history of falls. Methods: Twenty older adults (15 women, 71 ± 4.9 years) with a history of falls were included in this cross-over study. Participants received two types of cueing (adaptive and traditional metronome) 1 week apart. The variability of the participants' stride time, stride length, walking speed and duration of double leg support were recorded during three walking conditions (baseline, during feedback and post-feedback gait). Repeated-measures ANOVA was used to assess the possible effects of the two cueing strategies on gait variables. Results: Compared with the baseline condition, participants had significantly increased stride time variability during feedback (F (2) = 9.83, p < 0.001) and decreased double leg support time variability post-feedback (F (2) 3.69, p = 0.034). Increased stride time variability was observed with the adaptive metronome in comparison to the traditional metronome. Conclusion: Metronome cueing strategies may reduce double leg support variability in older adults with a history of falls but seem to increase stride time variability. Further studies are needed to investigate if metronome cueing is more beneficial for individuals with greater baseline gait variability than those included in the current study.

We present initial results in the development of a gyrokinetic particle-in-cell code for the whole-volume modeling of stellarators. This is achieved through two modifications to the X-point Gyrokinetic Code (XGC), originally developed for tokamaks. One is an extension to three-dimensional geometries with an interface to Variational Moments Equilibrium Code (VMEC) data. The other is a connection between core and edge regions that have quite different field-line structures. The VMEC equilibrium is smoothly extended to the edge region by using a virtual casing method. Non-axisymmetric triangular meshes in which triangle nodes follow magnetic field lines in the toroidal direction are generated for field calculation using a finite-element method in the entire region of the extended VMEC equilibrium. These schemes are validated by basic benchmark tests relevant to each part of the calculation cycle, that is, particle push, particle-mesh interpolation, and field solver in a magnetic field equilibrium of Large Helical Device including the edge region. The developed code also demonstrates collisionless damping of geodesic acoustic modes and steady states with residual zonal flow in the core region., source:Plasma 2019, 2(2), 179-200; https://doi.org/10.3390/plasma2020014, source:https://doi.org/10.3390/plasma2020014, identifier:0000-0003-2513-0453

Isotope effects under the influence of a radial electric field are examined in a helical magnetic field configuration. We perform global gyrokinetic simulations with additional poloidal rotations to estimate quasi-linear heat flux due to ion temperature gradient mode under the mixing length model. In single-ion-species plasmas, the mass number dependency of heat flux agrees with gyro-Bohm scaling in the absence of a radial electric field. Favorable mass number dependencies violating gyro-Bohm scaling are observed in the presence of a global radial electric field or a heavy hydrogen component in multi-ion-species plasmas. The radial electric field and the heavy hydrogen component affect the heat flux through an increase of wavelength as well as mode stabilization. Poloidal Mach number characterizes the transition from unfavorable to favorable mass number dependency under radial electric fields. While the heat flux is independent of mass number for a given poloidal Mach number, the heat flux decreases for higher mass numbers in a given radial electric field. The heat flux is also independent of average mass number in multi-ion-species plasmas because the heavy hydrogen component effectively enhances the light hydrogen heat flux. The present results are potentially relevant to the violation of gyro-Bohm scaling observed in the recent deuterium experiments in the Large Helical Device., source:T. Moritaka et al 2022 Nucl. Fusion 62 126059, source:https://doi.org/10.1088/1741-4326/ac95ab, identifier:0000-0003-2513-0453

Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. We have developed "scone"- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through graphical summaries and quantitative reports, scone summarizes trade-offs and ranks large numbers of normalization methods by panel performance. The method is implemented in the open-source Bioconductor R software package scone. We show that top-performing normalization methods lead to better agreement with independent validation data for a collection of scRNA-seq datasets. scone can be downloaded at http://bioconductor.org/packages/scone/.

Copyright: © 2020 Ito et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Many large-scale functional connectivity studies have emphasized the importance of communication through increased inter-region correlations during task states. In contrast, local circuit studies have demonstrated that task states primarily reduce correlations among pairs of neurons, likely enhancing their information coding by suppressing shared spontaneous activity. Here we sought to adjudicate between these conflicting perspectives, assessing whether co-active brain regions during task states tend to increase or decrease their correlations. We found that variability and correlations primarily decrease across a variety of cortical regions in two highly distinct data sets: non-human primate spiking data and human functional magnetic resonance imaging data. Moreover, this observed variability and correlation reduction was accompanied by an overall increase in dimensionality (reflecting less information redundancy) during task states, suggesting that decreased correlations increased information coding capacity. We further found in both spiking and neural mass computational models that task-evoked activity increased the stability around a stable attractor, globally quenching neural variability and correlations. Together, our results provide an integrative mechanistic account that encompasses measures of large-scale neural activity, variability, and correlations during resting and task states.

Computational Medical Extended Reality (CMXR), brings together life sciences and neuroscience with mathematics, engineering and computer science. It unifies computational science (scientific computing) with intelligent extended reality and spatial computing for the medical field. It significantly differs from previous "Clinical XR" or "Medical XR" terms, as it is focusing on how to integrate computational methods from neural simulation to computational geometry, computational vision and computer graphics with deep learning models to solve specific hard problems in medicine and neuroscience: from low/no-code/genAI authoring platforms to deep learning XR systems for training, planning, operative navigation, therapy and rehabilitation.

System identification poses a significant bottleneck to characterizing and controlling complex systems. This challenge is greatest when both the system states and parameters are not directly accessible leading to a dual-estimation problem. Current approaches to such problems are limited in their ability to scale with many-parameter systems as often occurs in networks. In the current work, we present a new, computationally efficient approach to treat large dual-estimation problems. Our approach consists of directly integrating pseudo-optimal state estimation (the Extended Kalman Filter) into a dual-optimization objective, leaving a differentiable cost/error function of only in terms of the unknown system parameters which we solve using numerical gradient/Hessian methods. Intuitively, our approach consists of solving for the parameters that generate the most accurate state estimator (Extended Kalman Filter). We demonstrate that our approach is at least as accurate in state and parameter estimation as joint Kalman Filters (Extended/Unscented), despite lower complexity. We demonstrate the utility of our approach by inverting anatomically-detailed individualized brain models from human magnetoencephalography (MEG) data., Comment: Conference

Single-cell RNA sequencing technologies have evolved rapidly over the past few years, but the newest protocols and platforms are still limited by bias and noise. These technical issues can present serious challenges to downstream data analyses when samples are collected from multiple human donors recruited from multiple sites. My dissertation outlines methods for assessing bias and quantifying reproducibility in single-cell RNA sequencing studies. These tools are applicable to a new class of single-cell studies of human disease that move beyond tissue-level case–control comparisons. I have implemented these methods in two software packages, scone and scRAD, both developed to improve the quality of biological insights derived from single-cell RNA sequencing data.

This study seeks to advance our understanding of the leadership consequences that may ensue when supervisors and their teams have similar versus differing orientations toward the past. Integrating a leader–team fit perspective with functional leadership theory, we cast incongruence between supervisor and team past temporal focus as a key antecedent of supervisors' active (i.e., task-oriented and relationship-oriented) and passive (i.e., laissez-faire) leadership behaviors toward the team. We tested our hypotheses in a team-level study that included a field sample of 84 super-visors and their teams using polynomial regression and response surface analyses.Results illustrated that supervisors demonstrated more task-oriented and relationship-oriented leadership when supervisors' and their team's past temporal focus were incongruent rather than aligned. Furthermore, in situations of supervisor–team congruence, supervisors engaged in less task-oriented and relationship-oriented leadership and more laissez-faire leadership with higher (rather than lower)levels of supervisor and team past temporal focus. In sum, these findings support a complex (mis)fit model such that supervisors' attention to the past may hinder their productive leadership behaviors in some team contexts but not in others. Hence, this research advances a novel, multiple-stakeholder perspective on the role of both supervisors' and their team's past temporal focus for important leadership behavior

Cerebrospinal fluid (CSF) protects the central nervous system (CNS) and analyzing CSF aids the diagnosis of CNS diseases, but our understanding of CSF leukocytes remains superficial. Here, using single cell transcriptomics, we identify a specific location-associated composition and transcriptome of CSF leukocytes. Multiple sclerosis (MS) - an autoimmune disease of the CNS - increases transcriptional diversity in blood, but increases cell type diversity in CSF including a higher abundance of cytotoxic phenotype T helper cells. An analytical approach, named cell set enrichment analysis (CSEA) identifies a cluster-independent increase of follicular (TFH) cells potentially driving the known expansion of B lineage cells in the CSF in MS. In mice, TFH cells accordingly promote B cell infiltration into the CNS and the severity of MS animal models. Immune mechanisms in MS are thus highly compartmentalized and indicate ongoing local T/B cell interaction.

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In this work, a neural network based terramechanics model and terrain estimator are presented with an outlook for optimal control applications such as model predictive control. Recognizing the limitations of the state-of-the-art terramechanics models in terms of operating conditions, computational cost, and continuous differentiability for gradient-based optimization, an efficient and twice continuously differentiable terramechanics model is developed using neural networks for dynamic operations on deformable terrains. It is demonstrated that the neural network terramechanics model is able to predict the lateral tire forces accurately and efficiently compared to the Soil Contact Model as a state-of-the-art model. Furthermore, the neural network terramechanics model is implemented within a terrain estimator and it is shown that using this model the estimator converges within around 2% of the true terrain parameter. Finally, with model predictive control applications in mind, which typically rely on bicycle models for their predictions, it is demonstrated that utilizing the estimated terrain parameter can reduce prediction errors of a bicycle model by orders of magnitude. The result is an efficient, dynamic, twice continuously differentiable terramechanics model and estimator that has inherent advantages for implementation in model predictive control as compared to previously established models.

0000-0003-2513-0453, We present initial results in the development of a gyrokinetic particle-in-cell code for the whole-volume modeling of stellarators. This is achieved through two modifications to the X-point Gyrokinetic Code (XGC), originally developed for tokamaks. One is an extension to three-dimensional geometries with an interface to Variational Moments Equilibrium Code (VMEC) data. The other is a connection between core and edge regions that have quite different field-line structures. The VMEC equilibrium is smoothly extended to the edge region by using a virtual casing method. Non-axisymmetric triangular meshes in which triangle nodes follow magnetic field lines in the toroidal direction are generated for field calculation using a finite-element method in the entire region of the extended VMEC equilibrium. These schemes are validated by basic benchmark tests relevant to each part of the calculation cycle, that is, particle push, particle-mesh interpolation, and field solver in a magnetic field equilibrium of Large Helical Device including the edge region. The developed code also demonstrates collisionless damping of geodesic acoustic modes and steady states with residual zonal flow in the core region.

In this work, a terrain estimation framework is developed for autonomous vehicles operating on deformable terrains. Previous work in this area usually relies on steady state tire operation, linearized classical terramechanics models, or on computationally expensive algorithms that are not suitable for real-time estimation. To address these shortcomings, this work develops a reduced-order nonlinear terramechanics model as a surrogate of the Soil Contact Model (SCM) through extending a state-of-the-art Bekker model to account for additional dynamic effects. It is shown that this reduced-order surrogate model is able to accurately replicate the forces predicted by the SCM while reducing the computation cost by an order of magnitude. This surrogate model is then utilized in a unscented Kalman filter to estimate the sinkage exponent. Simulations suggest this parameter can be estimated within 4% of its true value for clay and sandy loam terrains. It is also shown that utilizing this estimated parameter can reduce the prediction errors of the future vehicle states by orders of magnitude, which could assist with achieving more robust model-predictive autonomous navigation strategies.

Treating patient populations with significant psychiatric and neurocognitive symptomatology can present a unique clinical dilemma: progress in psychotherapy can be significantly fettered by cognitive deficits, whereas neurocognitive rehabilitation efforts can be ineffective because of psychiatric overlay. Application of mindfulness-based interventions to address either cognitive or psychiatric symptoms in isolation appears efficacious in many contexts; however, it remains unclear whether this type of intervention might help address simultaneous neurocognitive and psychiatric symptomatology. In a pre-post mixed methods design pilot study, nine Veterans with post-traumatic stress disorder (PTSD) and a history of mild traumatic brain injury with chronic cognitive complaints participated in Mindfulness-Based Stress Reduction (MBSR). Clinical interview, questionnaires, and attention and PTSD measures were administered immediately before, immediately after, and 3 months after MBSR completion. Qualitative and quantitative findings suggest high levels of safety, feasibility, and acceptability. Measurement of attention revealed significant improvement immediately following MBSR (p < 0.05, d = 0.57) and largely sustained improvement 3 months after completion of MBSR (p < 0.10, d = 0.48). Significant reduction in PTSD symptoms was found immediately after MBSR (p < 0.05, d = -1.56), and was sustained 3 months following MBSR completion (p < 0.05, d = -0.93). These results warrant a randomized controlled trial follow-up. Potential mechanisms for the broad effects observed will be explored.

Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task.

BackgroundHuman immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 infection.ResultsTo overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4+ T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro.ConclusionsOverall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful.

Over the last decade, silica aerogel tracks and aluminum foil craters on the Stardust collector have been studied extensively to determine the nature of captured cometary dust grains. Analysis of particles captured in aerogel has been developed to a fine art, aided by sophisticated preparation techniques, and yielding revolutionary knowledge of comet dust mineralogy. The Stardust foil craters can be interpreted in terms of impacting particle size and structure, but almost all studies of composition for their contents have relied on in situ analysis techniques or relatively destructive extraction of materials. This has limited their examination and interpretation. However, numerous experimental hypervelocity impact studies under Stardust-Wild 2 encounter conditions have shown that abundant dust components are preserved in foil craters of all sizes. Using some of these analogue materials, we have previously shown that modern, nondestructive scanning electron microscope imaging and X-ray microanalysis techniques can document distribution of dust remnants both quickly and thoroughly within foil craters prior to any preparation. Here we present findings from our efforts to quantify the amount of residue and demonstrate a simple method of crater shape modification which can bring material into positions where it is much more accessible for in situ analysis, or safe removal of small subsamples. We report that approximately 50% of silicate-dominated impactors were retained as impact crater residue; however, <3% of organic impactors remained in the craters after impact.

BACKGROUND: Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 infection. RESULTS: To overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4+ T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro. CONCLUSIONS: Overall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful. Keywords: HIV-1; dendritic cell; single-cell; RNA-seq; single-cell genomics; elite controller; adjuvant; reproducibility; differential expression, National Institutes of Health (U.S.) (Grant DP2OD020839), National Institutes of Health (U.S.) (Grant 5U24AI118672), National Institutes of Health (U.S.) (Grant 2U19AI089992), National Institutes of Health (U.S.) (Grant 2R01HL095791), National Institutes of Health (U.S.) (Grant 2RM1HG006193)

Learning a similarity metric has gained much attention recently, where the goal is to learn a function that maps input patterns to a target space while preserving the semantic distance in the input space. While most related work focused on images, we focus instead on learning a similarity metric for neuroimages, such as fMRI and DTI images. We propose an end-to-end similarity learning framework called Higher-order Siamese GCN for multi-subject fMRI data analysis. The proposed framework learns the brain network representations via a supervised metric-based approach with siamese neural networks using two graph convolutional networks as the twin networks. Our proposed framework performs higher-order convolutions by incorporating higher-order proximity in graph convolutional networks to characterize and learn the community structure in brain connectivity networks. To the best of our knowledge, this is the first community-preserving similarity learning framework for multi-subject brain network analysis. Experimental results on four real fMRI datasets demonstrate the potential use cases of the proposed framework for multi-subject brain analysis in health and neuropsychiatric disorders. Our proposed approach achieves an average AUC gain of 75% compared to PCA, an average AUC gain of 65.5% compared to Spectral Embedding, and an average AUC gain of 24.3% compared to S-GCN across the four datasets, indicating promising application in clinical investigation and brain disease diagnosis.

IntroductionMedical decision-making is a cornerstone of clinical care and a key contributor to diagnostic accuracy. Medical decision-making occurs via two primary pathways: System 1, pattern recognition, is fast, intuitive, and heuristically driven and occurs largely unconsciously. System 2, analytic thinking, is slow, deliberate, and under conscious control. Biases are systematic errors that can impact reasoning via either pathway but predominantly affect decisions made by pattern recognition. Debiasing strategies involve the deliberate switching from pattern recognition to analytic thinking triggered by a stimulus. This resource describes a faculty development workshop designed to train emergency medicine educators about common biases and debiasing strategies, to improve teaching of diagnostic reasoning to trainees.MethodsThis workshop was implemented at the 2017 Society for Academic Emergency Medicine Annual Meeting. The workshop consisted of a brief didactic, followed by small-group case-based learning. A retrospective survey and qualitative evaluation were administered to attendees.ResultsThe participants' self-assessment showed significant improvements (p < .001) in their abilities to recognize how pattern recognition can lead to bias, identify common types of bias in the emergency department, teach trainees about common types of bias, and apply cognitive debiasing strategies to improve diagnostic reasoning. Strengths of the workshop included the interactive case-based format, discussions of bias-mitigation strategies, and take-home resources. Suggestions for improvement included lengthening the discussion time and providing more cases.DiscussionCognitive biases can negatively impact patient care. Faculty development is needed to improve instruction about bias and debiasing strategies for all levels of trainees.

ObjectiveTo determine whether differentially methylated CpGs in synovium-derived fibroblast-like synoviocytes (FLS) of patients with rheumatoid arthritis (RA) were also differentially methylated in RA peripheral blood (PB) samples.MethodsFor this study, 371 genome-wide DNA methylation profiles were measured using Illumina HumanMethylation450 BeadChips in PB samples from 63 patients with RA and 31 unaffected control subjects, specifically in the cell subsets of CD14+ monocytes, CD19+ B cells, CD4+ memory T cells, and CD4+ naive T cells.ResultsOf 5,532 hypermethylated FLS candidate CpGs, 1,056 were hypermethylated in CD4+ naive T cells from RA PB compared to control PB. In analyses of a second set of CpG candidates based on single-nucleotide polymorphisms from a genome-wide association study of RA, 1 significantly hypermethylated CpG in CD4+ memory T cells and 18 significant CpGs (6 hypomethylated, 12 hypermethylated) in CD4+ naive T cells were found. A prediction score based on the hypermethylated FLS candidates had an area under the curve of 0.73 for association with RA case status, which compared favorably to the association of RA with the HLA-DRB1 shared epitope risk allele and with a validated RA genetic risk score.ConclusionFLS-representative DNA methylation signatures derived from the PB may prove to be valuable biomarkers for the risk of RA or for disease status.

Metamaterials are subwavelength man-made plasmonic or dielectric structures designed to realize specific effects on the electromagnetic radiation interacting with the material. Here we aim to rotate the polarization of an incident terahertz beam using chiral metamaterials, while suppressing the circular dichroism which induces ellipticity of the output beam. An incident linearly polarized wave can be decomposed into left-circularly and right-circularly polarized waves, and the difference in propagation phase will result in rotation of the plane of polarization. Since chiral structures couple electric and magnetic fields, they are often implemented in complex geometries such as spirals or bi-layered plasmonic structures, which can achieve carefully balanced responses to the two fields. The important feature of the bi-layered plasmonic structure is the cross-coupling between the resonances of the two layers. It is precisely this coupling between the layers that induces currents in the structures that are mutually dependent producing chirality within the structure. By coupling a metallic structure to its complement, we are able to achieve strong transmission in the region of maximum polarization rotation, and relatively low ellipticity of the output state. Three different structures were fabricated for this work that will be referred to as: the plain crosses, crossed arrowheads, and crossed arcs, pictured in the figure below. The terahertz responses of the structures were compared using terahertz time-domain spectroscopy and numerical simulations using CST Microwave Studio software.

We present an experimental study of ultra-thin tunable THz absorbers based on MEMS-driven metamaterials. Using the high mechanical sensitivity of thin subwavelength metamaterial absorbers, we proposed a paradigm to combine meta-atoms and suspended flat membranes to simultaneously maximize the near-field coupling and avoid resonance broadening. We employed a MEMS technology and successfully fabricated THz absorbers based on integration of meta-atoms and MEMS, demonstrating giant tuning of resonant absorption. The devices presented in this paper are among the best-performing tunable THz absorbers achieved to date, particularly in device thickness and tunability characteristics.

Tissue homeostasis and regeneration are mediated by programs of adult stem cell renewal and differentiation. However, the mechanisms that regulate stem cell fates under such widely varying conditions are not fully understood. Using single-cell techniques, we assessed the transcriptional changes associated with stem cell self-renewal and differentiation and followed the maturation of stem cell-derived clones using sparse lineage tracing in the regenerating mouse olfactory epithelium. Following injury, quiescent olfactory stem cells rapidly shift to activated, transient states unique to regeneration and tailored to meet the demands of injury-induced repair, including barrier formation and proliferation. Multiple cell fates, including renewed stem cells and committed differentiating progenitors, are specified during this early window of activation. We further show that Sox2 is essential for cells to transition from the activated to neuronal progenitor states. Our study highlights strategies for stem cell-mediated regeneration that may be conserved in other adult stem cell niches.

A detailed understanding of the paths that stem cells traverse to generate mature progeny is vital for elucidating the mechanisms governing cell fate decisions and tissue homeostasis. Adult stem cells maintain and regenerate multiple mature cell lineages in the olfactory epithelium. Here we integrate single-cell RNA sequencing and robust statistical analyses with in vivo lineage tracing to define a detailed map of the postnatal olfactory epithelium, revealing cell fate potentials and branchpoints in olfactory stem cell lineage trajectories. Olfactory stem cells produce support cells via direct fate conversion in the absence of cell division, and their multipotency at the population level reflects collective unipotent cell fate decisions by single stem cells. We further demonstrate that Wnt signaling regulates stem cell fate by promoting neuronal fate choices. This integrated approach reveals the mechanisms guiding olfactory lineage trajectories and provides a model for deconstructing similar hierarchies in other stem cell niches.

This research study identified and analysed the major national, regional and international factors which influenced Thai drug policy formulation and implementation. A qualitative inductive theoretical process incorporating different sources of data (interrogation of the literature, expert interviews and a survey) is used. Data were examined through political economy analysis and other relevant policy analysis frameworks. The results showed the important role of key institutions and the influence of central paradigms, ideologies and cultural values.

We propose a probabilistic model for interpreting gene expression levels that are observed through single-cell RNA sequencing. In the model, each cell has a low-dimensional latent representation. Additional latent variables account for technical effects that may erroneously set some observations of gene expression levels to zero. Conditional distributions are specified by neural networks, giving the proposed model enough flexibility to fit the data well. We use variational inference and stochastic optimization to approximate the posterior distribution. The inference procedure scales to over one million cells, whereas competing algorithms do not. Even for smaller datasets, for several tasks, the proposed procedure outperforms state-of-the-art methods like ZIFA and ZINB-WaVE. We also extend our framework to account for batch effects and other confounding factors, and propose a Bayesian hypothesis test for differential expression that outperforms DESeq2., Comment: BayLearn2017, NIPS workshop MLCB 2017

We propose a probabilistic model for interpreting gene expression levels that are observed through single-cell RNA sequencing. In the model, each cell has a low-dimensional latent representation. Additional latent variables account for technical effects that may erroneously set some observations of gene expression levels to zero. Conditional distributions are specified by neural networks, giving the proposed model enough flexibility to fit the data well. We use variational inference and stochastic optimization to approximate the posterior distribution. The inference procedure scales to over one million cells, whereas competing algorithms do not. Even for smaller datasets, for several tasks, the proposed procedure outperforms state-of-the-art methods like ZIFA and ZINB-WaVE. We also extend our framework to take into account batch effects and other confounding factors and propose a natural Bayesian hypothesis framework for differential expression that outperforms tradition DESeq2., Comment: Updated a previous submission instead. See arXiv:1709.02082

Augusto Pinochet’s regime permanently altered Chilean politics during his seventeen years as dictator of Chile. By the late 1980s, Pinochet’s hold on power remained unyielding, political reconciliation with the military was unimaginable, and civil war seemed inevitable. Notwithstanding the lack of substantive political change, on March 11, 1990, Pinochet ceremoniously handed the presidential sash to the leader of his legal opposition, Patricio Aylwin, thus initiating a peaceful transition to civilian rule in Chile.My dissertation examines the context and content of the Franja de Propaganda Electoral of 1988. What loosely translates as “official space for electoral propaganda” - was a nationally televised, largely uncensored, 30-minute political program, representing the two sides of the 1988 Plebiscito; the NO campaign in opposition to the military regime, and the pro-Pinochet SÍ campaign.The Franja Electoral became a mediated space of Chilean politics, just beyond the repressive reach of the Pinochetista regime, within which a seemingly impossible transition was not only articulated, but also, through which, a transformation of Chilean political culture was engendered. To help explain this transformation, I draw from a conceptual framework known as mediatization theory, to examine the Franja Electoral as a sample case for the mediatization of Chilean politics. I propose that this case is best understood as an historical, political, and theoretical process, rooted in the cultural assimilation of an imagined political configuration. The mediatization of Chilean politics was a process that would ultimately help reconcile a contradictory relationship between what was politically viable as a social and historical course of action, with what was represented as acceptable in a mediated, televisual space of political culture.Furthermore, this project helps in the recovery of an exceptionally rare, complete collection of the 1988 Franja Electoral, and includes one of only a

Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ER alpha-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ER alpha binding and monoallelic-repression of IGFBP5 following oestrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR = 0.68 95% CI 0.55-0.83, P = 0.0002; replication OR = 0.77 95% CI 0.73-0.82, P = 2.1 x 10 (-19)) and identify 13 additional linked variants (r(2) > 0.8) in the 20Kb linkage block containing the enCNV (P = 3.2 x 10 (-15) - 5.6 x 10 (-17)). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5.

This paper describes studies leading to the development of an acoustic instrument for measuring properties of micrometeoroids and other dust particles in space. The instrument uses a pair of easily penetrated membranes separated by a known distance. Sensors located on these films detect the transient acoustic signals produced by particle impacts. The arrival times of these signals at the sensor locations are used in a simple multilateration calculation to measure the impact coordinates on each film. Particle direction and speed are found using these impact coordinates and the known membrane separations. This ability to determine particle speed, direction, and time of impact provides the information needed to assign the particle’s orbit and identify its likely origin. In many cases additional particle properties can be estimated from the signal amplitudes, including approximate diameter and (for small particles) some indication of composition/morphology. Two versions of this instrument were evaluated in this study. Fiber optic displacement sensors are found advantageous when very thin membranes can be maintained in tension (solar sails, lunar surface). Piezoelectric strain sensors are preferred for thicker films without tension (long duration free flyers). The latter was selected for an upcoming installation on the International Space Station.

In chronic lymphocytic leukemia (CLL), mutation and loss of p53 and ATM abrogate DNA damage signalling and predict poorer response and shorter survival. We hypothesised that poly (ADP-ribose) polymerase (PARP) activity, which is crucial for repair of DNA breaks induced by oxidative stress or chemotherapy, may be an additional predictive biomarker and a target for therapy with PARP inhibitors. We measured PARP activity in 109 patient-derived CLL samples, which varied widely (192 - 190052 pmol PAR/10(6) cells) compared to that seen in healthy volunteer lymphocytes (2451 - 7519 pmol PAR/10(6) cells). PARP activity was associated with PARP1 protein expression and endogenous PAR levels. PARP activity was not associated with p53 or ATM loss, Binet stage, IGHV mutational status or survival, but correlated with Bcl-2 and Rel A (an NF-kB subunit). Levels of 8-hydroxy-2'-deoxyguanosine in DNA (a marker of oxidative damage) were not associated with PAR levels or PARP activity. The potent PARP inhibitor, talazoparib (BMN 673), inhibited CD4OL-stimulated proliferation of CLL cells at nM concentrations, independently of Binet stage or p53/ATM function. PARP activity is highly variable in CLL and correlates with stress-induced proteins. Proliferating CLL cells (including those with p53 or ATM loss) are highly sensitive to the PARP inhibitor talazoparib.

Today educational activities take place not only in school but also in after-school programs, community centers, museums, and online communities and forums. The success and expansion of these out-of-school initiatives depends on our ability to document and assess what works and what doesn’t in informal learning, but learning outcomes in these settings are often unpredictable. Goals are open-ended; participation is voluntary; and relationships, means, and ends are complex. This report charts the state of the art for learning assessment in informal settings, offering an extensive review of the literature, expert discussion on key topics, a suggested model for comprehensive assessment, and recommendations for good assessment practices. Drawing on analysis of the literature and expert opinion, the proposed model, the Outcomes-by-Levels Model for Documentation and Assessment, identifies at least ten types of valued outcomes, to be assessed in terms of learning at the project, group, and individual levels. The cases described in the literature under review, which range from promoting girls’ identification with STEM practices to providing online resources for learning programming and networking, illustrate the usefulness of the assessment model.

The specific aspects of cognition contributing to balance and gait have not been clarified in people with Parkinson’s disease (PD). Twenty PD participants and twenty age- and gender-matched healthy controls were assessed on cognition and clinical mobility tests. General cognition was assessed with the Mini Mental State Exam and the Addenbrooke’s Cognitive Exam. Executive function was evaluated using the Trail Making Tests (TMT-A and TMT-B) and a computerized cognitive battery which included a series of choice reaction time (CRT) tests. Clinical gait and balance measures included the Tinetti, Timed Up & Go, Berg Balance and Functional Reach tests. PD participants performed significantly worse than the controls on the tests of cognitive and executive function, balance and gait. PD participants took longer on Trail Making Tests, CRT-Location and CRT-Colour (inhibition response). Furthermore, executive function, particularly longer times on CRT-Distracter and greater errors on the TMT-B were associated with worse balance and gait performance in the PD group. Measures of general cognition were not associated with balance and gait measures in either group. For PD participants, attention and executive function were impaired. Components of executive function, particularly those involving inhibition response and distracters, were associated with poorer balance and gait performance in PD.

Although accelerometers are extensively used for assessing gait, limited research has evaluated the concurrent validity of these devices on less predictable walking surfaces or the comparability of different methods used for gravitational acceleration compensation. This study evaluated the concurrent validity of trunk accelerations derived from a tri-axial inertial measurement unit while walking on firm, compliant and uneven surfaces and contrasted two methods used to remove gravitational accelerations: i) subtraction of the best linear fit from the data (detrending), and; ii) use of orientation information (quaternions) from the inertial measurement unit. Twelve older and twelve younger adults walked at their preferred speed along firm, compliant and uneven walkways. Accelerations were evaluated for the thoracic spine (T12) using a tri-axial inertial measurement unit and an eleven-camera Vicon system. The findings demonstrated excellent agreement between accelerations derived from the inertial measurement unit and motion analysis system, including while walking on uneven surfaces that better approximate a real-world setting (all differences <0.16 m.s−2). Detrending produced slightly better agreement between the inertial measurement unit and Vicon system on firm surfaces (delta range: −0.05 to 0.06 vs. 0.00 to 0.14 m.s−2), whereas the quaternion method performed better when walking on compliant and uneven walkways (delta range: −0.16 to −0.02 vs. −0.07 to 0.07 m.s−2). The technique used to compensate for gravitational accelerations requires consideration in future research, particularly when walking on compliant and uneven surfaces. These findings demonstrate trunk accelerations can be accurately measured using a wireless inertial measurement unit and are appropriate for research that evaluates healthy populations in complex environments.

The survival of organic molecules in shock impact events has been investigated in the laboratory. A frozen mixture of anthracene and stearic acid, solvated in dimethylsulfoxide (DMSO), was fired in a two-stage light gas gun at speeds of ?2 and ?4?km s?1 at targets that included water ice, water, and sand. This involved shock pressures in the range of 2–12 GPa. It was found that the projectile materials were present in elevated quantities in the targets after impact and in some cases in the crater ejecta as well. For DMSO impacting water at 1.9?km s?1 and 45° incidence, we quantify the surviving fraction after impact as 0.44±0.05. This demonstrates successful transfer of organic compounds from projectile to target in high-speed impacts. The range of impact speeds used covers that involved in impacts of terrestrial meteorites on the Moon, as well as impacts in the outer Solar System on icy bodies such as Pluto. The results provide laboratory evidence that suggests that exogenous delivery of complex organic molecules from icy impactors is a viable source of such material on target bodies.

We demonstrate how the complex integral formula for the Airy functions arises from Penrose's twistor contour integral formula. We then use the Lax formulation of the isomonodromy problem with one irregular singularity of order four to show that the Airy equation arises from the anti-self-duality equations for conformal structures of neutral signature invariant under the isometric action of the Bianchi II group. This conformal structure admits a null-K\"ahler metric in its conformal class which we construct explicitly., Comment: Special Issue of SIGMA on Progress in Twistor Theory

Background Degradation of the somatosensory system has been implicated in postural instability and increased falls risk for older people and Parkinson’s disease (PD) patients. Here we demonstrate that textured insoles provide a passive intervention that is an inexpensive and accessible means to enhance the somatosensory input from the plantar surface of the feet. Methods 20 healthy older adults (controls) and 20 participants with PD were recruited for the study. We evaluated effects of manipulating somatosensory information from the plantar surface of the feet using textured insoles. Participants performed standing tests, on two different surfaces (firm and foam), under three footwear conditions: 1) barefoot; 2) smooth insoles; and 3) textured insoles. Standing balance was evaluated using a force plate yielding data on the range of anterior-posterior and medial-lateral sway, as well as standard deviations for anterior-posterior and medial-lateral sway. Results On the firm surface with eyes open both the smooth and textured insoles reduced medial-lateral sway in the PD group to a similar level as the controls. Only the textured insole decreased medial-lateral sway and medial-lateral sway standard deviation in the PD group on both surfaces, with and without visual input. Greatest benefits were observed in the PD group while wearing the textured insoles, and when standing on the foam surface with eyes closed. Conclusions Data suggested that textured insoles may provide a low-cost means of improving postural stability in high falls-risk groups, such as people with PD.