Computational experiments in the optimal slewing of flexible structures

Numerical experiments on the problem of moving a flexible beam are discussed. An optimal control problem is formulated and transcribed into a form which can be solved using semi-infinite optimization techniques. All experiments were carried out on a SUN 3 microcomputer

But Did You Not Read My Title? The Pastoral Purpose of Joseph Butler\u27s Fifteen Sermons

Bearing in mind Butler’s own council that we are not to “look for any particular reason for the choice of the greatest part [of the sermons]” nor expect “any other connection between them, than the uniformity of thought and design, which will always be found in the writings of the same person, when he writes with simplicity and in earnest” (Preface 15), I contend that a peculiar attention applied to Butler’s sermons reveals a striking unity: namely, a unity of pastoral purpose. Butler’s chief task in Fifteen Sermons is to exhort his audience to cultivate virtue and avoid vice in their actual lives, not merely to present a novel moral theory or make clever psychological observations. With this view in mind, even the most theoretical portions of the sermons are clearly animated by an earnest pastoral concern that shouldn’t be ignored. I argue that, as readers of Butler\u27s sermons, we would do well to recognize his purpose in writing and do so with attention to our own cultivation of virtue

High-Throughput Nonlinear Optical Microscopy

High-resolution microscopy methods based on different nonlinear optical (NLO) contrast mechanisms are finding numerous applications in biology and medicine. While the basic implementations of these microscopy methods are relatively mature, an important direction of continuing technological innovation lies in improving the throughput of these systems. Throughput improvement is expected to be important for studying fast kinetic processes, for enabling clinical diagnosis and treatment, and for extending the field of image informatics. This review will provide an overview of the fundamental limitations on NLO microscopy throughput. We will further cover several important classes of high-throughput NLO microscope designs with discussions on their strengths and weaknesses and their key biomedical applications. Finally, this review will close with a perspective of potential future technological improvements in this field.National Institutes of Health (U.S.) (9P41EB015871-26A1)National Institutes of Health (U.S.) (R01-EX017656)National Institutes of Health (U.S.) (5 R01 NS051320)National Institutes of Health (U.S.) (4R44EB012415-02)National Science Foundation (U.S.) (CBET-0939511)Singapore-MIT AllianceSkolkovo Institute of Science and TechnologySingapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology)Wellcome Trust (London, England) (Massachusetts Institute of Technology. Postdoctoral Fellowship 093831/Z/10/Z

Availability of Buprenorphine Treatment in Kentucky

Drug overdose and substance use treatment admissions data indicate that opioid use is problematic in Kentucky, but little information exists about the geographic availability of buprenorphine treatment across the state. Furthermore, there is even less information about the characteristics of the physicians prescribing buprenorphine. This report describes the availability of buprenorphine treatment in Kentucky

Casting Light Upon The Great Endarkenment

While the Enlightenment promoted thinking for oneself independent of religious authority, the ‘Endarkenment’ (Millgram 2015) concerns deference to a new authority: the specialist, a hyperspecializer. Non-specialists need to defer to such authorities as they are unable to understand their reasoning. Millgram describes how humans are capable of being serial hyperspecializers, able to move from one specialism to another. We support the basic thrust of Millgram’s position, and seek to articulate how the core idea is deployed in very different ways in relation to extremely different philosophical areas. We attend to the issue of the degree of isolation of different specialists and we urge greater emphasis on parallel hyperspecialization, which describes how different specialisms can be embodied in one person at one time

Sampling binary sparse coding QUBO models using a spiking neuromorphic processor

We consider the problem of computing a sparse binary representation of an image. To be precise, given an image and an overcomplete, non-orthonormal basis, we aim to find a sparse binary vector indicating the minimal set of basis vectors that when added together best reconstruct the given input. We formulate this problem with an $L_2$ loss on the reconstruction error, and an $L_0$ (or, equivalently, an $L_1$) loss on the binary vector enforcing sparsity. This yields a so-called Quadratic Unconstrained Binary Optimization (QUBO) problem, whose solution is generally NP-hard to find. The contribution of this work is twofold. First, the method of unsupervised and unnormalized dictionary feature learning for a desired sparsity level to best match the data is presented. Second, the binary sparse coding problem is then solved on the Loihi 1 neuromorphic chip by the use of stochastic networks of neurons to traverse the non-convex energy landscape. The solutions are benchmarked against the classical heuristic simulated annealing. We demonstrate neuromorphic computing is suitable for sampling low energy solutions of binary sparse coding QUBO models, and although Loihi 1 is capable of sampling very sparse solutions of the QUBO models, there needs to be improvement in the implementation in order to be competitive with simulated annealing

The segregated connectome of late-life depression: a combined cortical thickness and structural covariance analysis.

Late-life depression (LLD) has been associated with both generalized and focal neuroanatomical changes including gray matter atrophy and white matter abnormalities. However, previous literature has not been consistent and, in particular, its impact on the topology organization of brain networks remains to be established. In this multimodal study, we first examined cortical thickness, and applied graph theory to investigate structural covariance networks in LLD. Thirty-three subjects with LLD and 25 controls underwent T1-weighted, fluid-attenuated inversion recovery and clinical assessments. Freesurfer was used to perform vertex-wise comparisons of cortical thickness, whereas the Graph Analysis Toolbox (GAT) was implemented to construct and analyze the structural covariance networks. LLD showed a trend of lower thickness in the left insular region (p < 0.001 uncorrected). In addition, the structural network of LLD was characterized by greater segregation, particularly showing higher transitivity (i.e., measure of clustering) and modularity (i.e., tendency for a network to be organized into subnetworks). It was also less robust against random failure and targeted attacks. Despite relative cortical preservation, the topology of the LLD network showed significant changes particularly in segregation. These findings demonstrate the potential for graph theoretical approaches to complement conventional structural imaging analyses and provide novel insights into the heterogeneous etiology and pathogenesis of LLD.This work was supported by the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge, and the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Newcastle upon Tyne Hospitals NHS Foundation Trust and the Newcastle University. Elijah Mak was in receipt of a Gates Cambridge, PhD studentship.This is the author accepted manuscript. It first appeared from Elsevier at http://dx.doi.org/10.1016/j.neurobiolaging.2016.08.013

Neuroimaging correlates of cognitive impairment and dementia in Parkinson's disease.

There has been a gradual shift in the definition of Parkinson's disease, from a movement disorder to a neurodegenerative condition affecting multiple cognitive domains. Mild cognitive impairment (PD-MCI) is a frequent comorbidity in PD that is associated with progression to dementia (PDD) and debilitating consequences for patients and caregivers. At present, the pathophysiology underpinning cognitive impairment in PD is not established, although emerging evidence has suggested that multi-modal imaging biomarkers could be useful in the early diagnosis of PD-MCI and PDD, thereby identifying at-risk patients to enable treatment at the earliest stage possible. Structural MRI studies have revealed prominent grey matter atrophy and disruptions of white matter tracts in PDD, although findings in non-demented PD have been more variable. There is a need for further longitudinal studies to clarify the spatial and temporal progression of morphological changes in PD, as well as to assess their underlying involvement in the evolution of cognitive deficits. In this review, we discuss the aetiology and neuropsychological profiles of PD-MCI and PDD, summarize the putative imaging substrates in light of evidence from multi-modal neuroimaging studies, highlight limitations in the present literature, and suggest recommendations for future research.This work was supported by the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge, and the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Newcastle upon Tyne Hospitals NHS Foundation Trust and the Newcastle University. Elijah Mak was in receipt of a Gates Cambridge PhD studentship.This is the accepted manuscript. The final version is available at http://www.sciencedirect.com/science/article/pii/S1353802015002151

Parallel super-resolution imaging

Massive parallelization of scanning-based super-resolution imaging allows fast imaging of large fields of view