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Transformative learning

Katherine C Hall, Sandy K Diffenderfer, April Stidham, Christine M Mullins
In the 1990s, dedicated education units transformed undergraduate preceptorships, but graduate preceptorships remain static. The dyadic nurse practitioner preceptorship model supports an environment where faculty, students, and preceptors may overlook nuances that affect the teaching-learning process. This article describes an innovative clinical education model, Student and Preceptor Advancement in a Dedicated Education Site, designed to improve preceptorships for advanced practice nurses. The focus is on adaptations made to facilitate use in advanced practice nursing programs...
April 19, 2018: Nursing Education Perspectives
Shaowei Jiang, Jun Liao, Zichao Bian, Kaikai Guo, Yongbing Zhang, Guoan Zheng
A whole slide imaging (WSI) system has recently been approved for primary diagnostic use in the US. The image quality and system throughput of WSI is largely determined by the autofocusing process. Traditional approaches acquire multiple images along the optical axis and maximize a figure of merit for autofocusing. Here we explore the use of deep convolution neural networks (CNNs) to predict the focal position of the acquired image without axial scanning. We investigate the autofocusing performance with three illumination settings: incoherent Kohler illumination, partially coherent illumination with two plane waves, and one-plane-wave illumination...
April 1, 2018: Biomedical Optics Express
Pauline Rhenter, Aurélie Tinland, Julien Grard, Christian Laval, Jean Mantovani, Delphine Moreau, Benjamin Vidaud, Tim Greacen, Pascal Auquier, Vincent Girard
BACKGROUND: In 2006, a local collective combating homelessness set up an 'experimental squat' in an abandoned building in Marseille, France's second largest city. They envisioned the squat as an alternative to conventional health and social services for individuals experiencing long-term homelessness and severe psychiatric disorders. Building on what they learned from the squat, some then joined a larger coalition that succeeded in convincing national government decision-makers to develop a scientific, intervention-based programme based on the Housing First model...
April 19, 2018: Health Research Policy and Systems
Guoxian Dai, Jin Xie, Yi Fang
How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape...
July 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Ville Heikkinen
This paper explores hyperspectral reflectance factor estimation using Gaussian process regression with multispectral- and trichromatic measurements. Estimations are performed in visible- (400-700 nm) or visible-near infrared (400-980 nm) wavelength ranges using the learning-based approach, where sensor and light spectral characteristics are not required. We first construct new estimation models via Gaussian processes, show connection to previous kernel-based models, and then evaluate new models by using marginal likelihood optimization within the probabilistic interpretation...
July 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Yanru Zhao, Dongsheng Wang, Jin Tong, Jiyu Sun, Jin Zhang
The structures combining the veins and membranes of membranous wings of the Chinese bee Apis cerana cerana Fabricius into a whole have excellent load-resisting capacity. The membranous wings of Chinese bees were taken as research objects and the mechanical properties of a biomimetic model of membranous wings as targets. In order to understand and learn from the biosystem and then make technical innovation, the membranous wings of Chinese bees were simulated and analysed with reverse engineering and finite element method...
2018: Applied Bionics and Biomechanics
Alice Mizrahi, Tifenn Hirtzlin, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Julie Grollier, Damien Querlioz
In neuroscience, population coding theory demonstrates that neural assemblies can achieve fault-tolerant information processing. Mapped to nanoelectronics, this strategy could allow for reliable computing with scaled-down, noisy, imperfect devices. Doing so requires that the population components form a set of basis functions in terms of their response functions to inputs, offering a physical substrate for computing. Such a population can be implemented with CMOS technology, but the corresponding circuits have high area or energy requirements...
April 18, 2018: Nature Communications
Riccardo Sartori, Arianna Costantini, Andrea Ceschi, Francesco Tommasi
The article aims to be a reflective paper on the interconnected concepts of training, development and innovation and the potential they have in dealing with change in organizations. We call change both the process through which something becomes different and the result of that process. Change management is the expression used to define the complex of activities, functions, and tools (such as training courses) through which an organization deals with the introduction of something new that is relevant for both its survival and growth...
2018: Frontiers in Psychology
David J Herzfeld, Yoshiko Kojima, Robijanto Soetedjo, Reza Shadmehr
The primary output cells of the cerebellar cortex, Purkinje cells, make kinematic predictions about ongoing movements via high-frequency simple spikes, but receive sensory error information about that movement via low-frequency complex spikes (CS). How is the vector space of sensory errors encoded by this low-frequency signal? Here we measured Purkinje cell activity in the oculomotor vermis of animals during saccades, then followed the chain of events from experience of visual error, generation of CS, modulation of simple spikes, and ultimately change in motor output...
April 16, 2018: Nature Neuroscience
Xiaoguang Yang, Shenglan Tang, Gavin Yamey, Xu Qian
China has made impressive achievements in improving maternal and child health (MCH) over the past few decades. This paper uses a policy lens to examine reasons for these achievements as well as barriers to further success. We found that strong governmental commitment and leadership, effective coordination, proactive participation of different stakeholders, and the provision of adequate resources were associated with China's success in improving MCH outcomes. Other low- and middle-income countries can learn valuable lessons from China's experience...
April 15, 2018: Bioscience Trends
Lisa K Kearney, Jeanne A Schaefer, Katherine M Dollar, Gayle Y Iwamasa, Ira Katz, Theresa Schmitz, Mary Schohn, Sandra G Resnick
This column reviews the unique contributions of multiple partners in establishing a standardized site visit process to promote quality improvement in mental health care at the Veterans Health Administration. Working as a team, leaders in policy and operations, staff of research centers, and regional- and facility-level mental health leaders developed a standardized protocol for evaluating mental health services at each site and using the data to help implement policy goals. The authors discuss the challenges experienced and lessons learned in this systemwide process and how this information can be part of a framework for improving mental health services on a national level...
April 16, 2018: Psychiatric Services: a Journal of the American Psychiatric Association
Martin Vogt
Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity...
April 19, 2018: Expert Opinion on Drug Discovery
Elica Inagaki, Alik Farber, Jeffrey J Siracuse, Matthew W Mell, Denis V Rybin, Gheorghe Doros, Jeffrey Kalish
OBJECTIVE: There is a documented learning curve when adopting ultrasound guidance (UG) to aid vascular access. In the Vascular Study Group of New England (VSGNE), routine UG during percutaneous femoral artery access was shown to protect against the complication of groin hematoma. We sought to confirm this finding in the Vascular Quality Initiative (VQI), a dataset with a larger sample size and broader geographic distribution, and evaluate the effects of ultrasound usage and interventionalist volume on hematoma rates following peripheral vascular interventions (PVI)...
April 12, 2018: Annals of Vascular Surgery
Friedemann Zenke, Surya Ganguli
A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns...
April 13, 2018: Neural Computation
Hesham Mostafa, Gert Cauwenberghs
Many recent generative models make use of neural networks to transform the probability distribution of a simple low-dimensional noise process into the complex distribution of the data. This raises the question of whether biological networks operate along similar principles to implement a probabilistic model of the environment through transformations of intrinsic noise processes. The intrinsic neural and synaptic noise processes in biological networks, however, are quite different from the noise processes used in current abstract generative networks...
April 13, 2018: Neural Computation
Brian S Freeman, Graham Taylor, Bahram Gharabaghi, Jesse Thé
Implications Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction...
April 13, 2018: Journal of the Air & Waste Management Association
Tariq Ahmad, Lars H Lund, Pooja Rao, Rohit Ghosh, Prashant Warier, Benjamin Vaccaro, Ulf Dahlström, Christopher M O'Connor, G Michael Felker, Nihar R Desai
BACKGROUND: Whereas heart failure (HF) is a complex clinical syndrome, conventional approaches to its management have treated it as a singular disease, leading to inadequate patient care and inefficient clinical trials. We hypothesized that applying advanced analytics to a large cohort of HF patients would improve prognostication of outcomes, identify distinct patient phenotypes, and detect heterogeneity in treatment response. METHODS AND RESULTS: The Swedish Heart Failure Registry is a nationwide registry collecting detailed demographic, clinical, laboratory, and medication data and linked to databases with outcome information...
April 12, 2018: Journal of the American Heart Association
Yibing Ma, Zhiguo Jiang, Haopeng Zhang, Fengying Xie, Yushan Zheng, Huaqiang Shi, Yu Zhao, Jun Shi
BACKGROUND AND OBJECTIVE: Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels...
June 2018: Computer Methods and Programs in Biomedicine
Mahmoud Ahmed, Huynh Quoc Nguyen, Jin Seok Hwang, Sahib Zada, Trang Huyen Lai, Sang Soo Kang, Deok Ryong Kim
Autophagy contributes to reorganizing intracellular components and forming fat droplets during the adipocyte differentiation. Here, we systematically describe the role of autophagy-related genes and gene sets during the differentiation of adipocytes. We used a public dataset from the European Nucleotide Archive from an RNA-seq experiment in which 3T3-L1 cells were induced by a differentiation induction medium, total RNA was extracted and sequenced at four different time points. Raw reads were aligned to the UCSC mouse reference genome (mm10) using HISAT2, and aligned reads were summarized at the gene or exon level using HTSeq...
March 20, 2018: Oncotarget
Raffaella Nori, Laura Piccardi, Andrea Maialetti, Mirco Goro, Andrea Rossetti, Ornella Argento, Cecilia Guariglia
The present study has two-fold aims: to investigate whether gender differences persist even when more time is given to acquire spatial information; to assess the gender effect when the retrieval phase requires recalling the pathway from the same or a different reference perspective (egocentric or allocentric). Specifically, we analyse the performance of men and women while learning a path from a map or by observing an experimenter in a real environment. We then asked them to reproduce the learned path using the same reference system (map learning vs...
2018: Frontiers in Neuroscience
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