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Strain Distribution in Circular Disk of PMMA by Using Reflection Polariscope

Journal of physics: Conference Series 2018年第1期1144卷

作者： Y Manjit A Limpichaipanit A Ngamjarurojana Department of Physics and Materials Science Faculty of Science Chiang Mai University Chiang Mai 50200 Thailand Faculty of Science at Si Racha Kasetsart University Si Racha Campus Chon Buri 20230 Thailand PhD's Degree Program in Applied Physics Faculty of Science Chiang Mai University Chiang Mai 50200 Thailand

The experiment was conducted to study strain distribution in circular disk of PMMA by photoelasticity in reflection polariscope. The strain in circular disk was induced by two point load created by hydraulic system (535.37-994.63 N) with the step increase of 153.21 N. We added the Babinet compensater in basic reflection polariscope to observe the fractional isochromatic fringe order in the first quadrant of disk and we calculated strain by using stressstrain optic laws. The result showed the relation between absolute of different strain in first quadrant of circular disk and the relation of force with absolute of different strain. It was found that maximum different strain produced at contact area of disk decreased along horizontal and vertical direction. The relation of force with different strain was linear.

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News and Commentaries: US Dollar is a “Hidden Variable” in the Sino-US Relations

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China and the World 2021年第1期4卷

作者： Da Hsuan Feng Haiming Liang Da Hsuan Feng is currently the Honorary Dean of Hainan University Belt and Road Research Institute and the Chief Advisor of China Silk Road iValley Research Institute. He grew up in Singapore and received his physics PhD from the University of Minnesota (1972). He was the M Russell Wehr Chair Professor of Drexel University. He also served as the United States National Science Foundation Program Director in Theoretical Physics for two years. Since 2002 Feng had taken roles as the Vice President for Research at the University of Texas at Dallas the Senior Vice President of National Cheng Kung University National Tsing Hua University in Taiwan and Special Advisor to the Rector and Director of Global Strategies of Macau University. Feng is a Fellow of the American Physical Society and had been the honorary professor of fifteen Chinese universities which includes Peking Union Medical College Fudan University Jilin University Huazhong University of Science and Technology and Chinese Academy of Sciences Institute of Applied Physics. Feng was the 2009 Bian-Zhong laureate for individuals with outstanding contributions to Hubei Province (2009). He was also the recipient of “The Light of Civilization the 2017 Chinese Cultural Exchange Award” (2017). Haiming Liang (Hoi Ming Leung) is the Dean of Hainan University Belt and Road Research Institute and Chairman of the China Silk Road iValley Research Institute one of the top three think-tanks of China today (there are now over 600) with offices in Hong Kong Guangzhou and Beijing. Within the Institute there are experts in all areas from economics to culture to technology from within China and foreign countries. Currently he is a Visiting Scholar at Princeton University. Liang is one of the new generation of economists of China today. He was invited by the Chinese Government as one of the few Chinese experts in the Belt and Road Forum for International Cooperation in 2017. He is also a columnist for Financial Times (Chinese edition) and a Financial Commentator of

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The standard genetic code facilitates exploration of the space of functional nucleotide sequences

arXiv

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arXiv 2017年

作者： Tripathi, Shubham Deem, Michael W. PhD Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Center for Theoretical Biological Physics Rice University HoustonTX77005 United States Department of Bioengineering Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States

The standard genetic code is well known to be optimized for minimizing the phenotypic effects of single nucleotide substitutions, a property that was likely selected for during the emergence of a universal code. Given the fitness advantage afforded by high standing genetic diversity in a population in a dynamic environment, it is possible that selection to explore a large fraction of the space of functional proteins also occurred. To determine whether selection for such a property played a role during the emergence of the nearly universal genetic code, we investigated the number of functional variants of the Escherichia coli PhoQ protein explored at different time scales under translation using different genetic codes. We found that the standard genetic code is highly optimal for exploring a large fraction of the space of functional PhoQ variants at intermediate time scales as compared to random codes. Environmental changes, in response to which genetic diversity in a population provides a fitness advantage, are likely to have occurred at these intermediate time scales. Our results indicate that the ability of the standard code to explore a large fraction of the space of functional sequence variants arises from a balance between robustness and flexibility and is largely independent of the property of the standard code to minimize the phenotypic effects of mutations. We propose that selection to explore a large fraction of the functional sequence space while minimizing the phenotypic effects of mutations contributed towards the emergence of the standard code as the universal genetic code. Copyright © 2017, The Authors. All rights reserved.

关键词： Escherichia coli

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Task-driven convolutional recurrent models of the visual system

arXiv

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arXiv 2018年

作者： Nayebi, Aran Bear, Daniel Kubilius, Jonas Kar, Kohitij Ganguli, Surya Sussillo, David DiCarlo, James J. Yamins, Daniel L.K. Neurosciences PhD Program Stanford University StanfordCA94305 United States Department of Psychology Stanford University StanfordCA94305 United States Department of Computer Science Stanford University StanfordCA94305 United States Department of Applied Physics Stanford University StanfordCA94305 United States McGovern Institute for Brain Research MIT CambridgeMA02139 United States Department of Brain and Cognitive Sciences MIT CambridgeMA02139 United States Brain and Cognition KU Leuven Leuven Belgium Google Brain Google Inc. Mountain ViewCA94043 United States Wu Tsai Neurosciences Institute StanfordCA94305 United States

Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of neurons in the primate brain's visual system. However, biological visual systems have two ubiquitous architectural features not shared with typical CNNs: local recurrence within cortical areas, and long-range feedback from downstream areas to upstream areas. Here we explored the role of recurrence in improving classification performance. We found that standard forms of recurrence (vanilla RNNs and LSTMs) do not perform well within deep CNNs on the ImageNet task. In contrast, novel cells that incorporated two structural features, bypassing and gating, were able to boost task accuracy substantially. We extended these design principles in an automated search over thousands of model architectures, which identified novel local recurrent cells and long-range feedback connections useful for object recognition. Moreover, these task-optimized ConvRNNs matched the dynamics of neural activity in the primate visual system better than feedforward networks, suggesting a role for the brain's recurrent connections in performing difficult visual behaviors. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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Task-driven convolutional recurrent models of the visual system 18

Task-driven convolutional recurrent models of the visual sys...

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Proceedings of the 32nd International Conference on Neural Information Processing Systems

作者： Aran Nayebi Daniel Bear Jonas Kubilius Kohitij Kar Surya Ganguli David Sussillo James J. DiCarlo Daniel L. K. Yamins Neurosciences PhD Program Stanford University Stanford CA Department of Psychology Stanford University Stanford CA McGovern Institute for Brain Research MIT Cambridge MA and Brain and Cognition KU Leuven Leuven Belgium McGovern Institute for Brain Research MIT Cambridge MA and Google Brain Google Inc. Mountain View CA Department of Applied Physics Stanford University Stanford CA Google Brain Google Inc. Mountain View CA McGovern Institute for Brain Research MIT Cambridge MA and Department of Brain and Cognitive Sciences MIT Cambridge MA Department of Psychology Stanford University Stanford CA and Department of Computer Science Stanford University Stanford CA and Wu Tsai Neurosciences Institute Stanford CA

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Analysis of hierarchical organization in gene expression networks reveals underlying principles of collective tumor cell dissemination and metastatic aggressiveness of inflammatory breast cancer

arXiv

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arXiv 2017年

作者： Tripathi, Shubham Jolly, Mohit Kumar Woodward, Wendy A. Levine, Herbert Deem, Michael W. PhD Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Center for Theoretical Biological Physics Rice University HoustonTX77005 United States Department of Radiation Oncology University of Texas MD Anderson Cancer Center HoustonTX77030 United States MD Anderson Morgan Welch Inflammatory Breast Cancer Research Program and Clinic University of Texas MD Anderson Cancer Center HoustonTX77030 United States Department of Bioengineering Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States

Background: Clusters of circulating tumor cells (CTCs), despite being rare, may account for more than 95% of metastases. Cells in these clusters do not undergo a complete epithelial-to-mesenchymal transition (EMT) but retain some epithelial traits as compared to individually disseminating tumor cells. Determinants of single cell dissemination versus collective dissemination remain elusive. Inflammatory breast cancer (IBC), a highly aggressive breast cancer subtype that chiefly metastasizes via CTC clusters, is a promising model for studying mechanisms of collective tumor cell dissemination. Previous studies on breast cancer and adult acute myeloid leukemia, motivated by a theory that suggests physical systems with hierarchical organization tend to be more adaptable, have found that the expression of metastasis associated genes is more hierarchically organized in cases of successful metastases. Methods: We used the cophenetic correlation coefficient (CCC) to quantify the hierarchical organization in the expression networks of two distinct gene sets, collective dissemination associated genes and IBC associated genes, in cancer cell lines and in tumor samples from breast cancer patients. Hypothesizing that a higher CCC for collective dissemination associated genes and for IBC associated genes would be associated with a more evident epithelial phenotype and with worse outcomes in breast cancer patients, we evaluated the correlation of CCC with different phenotypic groups. Results: The CCC of both gene networks, the collective dissemination associated gene network and the IBC associated gene network, was higher in (a) epithelial cell lines as compared to mesenchymal cell lines and (b) tumor samples from IBC patients, as compared to samples from non-IBC breast cancer patients. A higher CCC of both networks was also correlated with a higher rate of metastatic relapse in breast cancer patients. Neither the levels of CDH1 gene expression, nor gene set enrichment analysis cou

关键词： Pathology

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Deep Learning Models of the Retinal Response to Natural Scenes 16

Deep Learning Models of the Retinal Response to Natural Scen...

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Annual Conference on Neural Information Processing Systems

作者： Lane T. McIntosh Niru Maheswaranathan Aran Nayebi Surya Ganguli Stephen A. Baccus Neurosciences PhD Program Stanford University Department of Applied Physics Stanford UniversityNeurobiology Department Stanford University Neurobiology Department Stanford University

ISBN: (纸本)9781510838819

A central challenge in sensory neuroscience is to understand neural computations and circuit mechanisms that underlie the encoding of ethologically relevant, natural stimuli. In multilayered neural circuits, nonlinear processes such as synaptic transmission and spiking dynamics present a significant obstacle to the creation of accurate computational models of responses to natural stimuli. Here we demonstrate that deep convolutional neural networks (CNNs) capture retinal responses to natural scenes nearly to within the variability of a cell's response, and are markedly more accurate than linear-nonlinear (LN) models and Generalized Linear Models (GLMs). Moreover, we find two additional surprising properties of CNNs: they are less susceptible to overfitting than their LN counterparts when trained on small amounts of data, and generalize better when tested on stimuli drawn from a different distribution (e.g. between natural scenes and white noise). An examination of the learned CNNs reveals several properties. First, a richer set of feature maps is necessary for predicting the responses to natural scenes compared to white noise. Second, temporally precise responses to slowly varying inputs originate from feedforward inhibition, similar to known retinal mechanisms. Third, the injection of latent noise sources in intermediate layers enables our model to capture the sub-Poisson spiking variability observed in retinal ganglion cells. Fourth, augmenting our CNNs with recurrent lateral connections enables them to capture contrast adaptation as an emergent property of accurately describing retinal responses to natural scenes. These methods can be readily generalized to other sensory modalities and stimulus ensembles. Overall, this work demonstrates that CNNs not only accurately capture sensory circuit responses to natural scenes, but also can yield information about the circuit's internal structure and function.

关键词： natural scenes Stimuli circuit response Retinaldehyde feature map Computational modeling Noise sources

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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EARLY METABOLIC RESPONSE IN FOLLICULAR LYMPHOMA: A SUBSET ANALYSIS OF THE FOLL12 TRIAL BY THE FONDAZIONE ITALIANA LINFOMI (FIL)

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Hematological Oncology 2021年第S2期39卷

作者： S. Luminari L. Guerra R. Durmo S. Chauvie S. Peano A. Franceschetto F. Fallanca V. Tarantino A. Pinto C. Ghiggi A. Pulsoni M. Merli L. Farina M. Tani B. Botto G. Musuraca B. Falini F. Ballerini P. M. Stefani S. Bolis G. Pietrantuono M. Manni L. Marcheselli M. Federico A. Versari Azienda Unità Sanitaria Locale IRCCS Arcispedale Santa Maria Nuova IRCCS Hematology Unit and University of Modena and Reggio Emilia Surgical Medical and Dental Department of Morphological Sciences related to Transplant Oncology and Regenerative Medicine Reggio Emilia Italy S. Gerardo Hospital University of Milano-Bicocca Nuclear Medicine and University of Milano Bicocca School of Medicine and Surgery Monza Italy Azienda USL-IRCCS di Reggio Emilia Nuclear Medicine Reggio Emilia Italy Santa Croce e Carle Hospital Department of Medical Physics Cuneo Italy ASO S. Croce e Carle S.C. Medicina Nucleare Cuneo Italy Modena Cancer Center University of Modena and Reggio Emilia Department of Oncology and Hematology Unit of Nuclear Medicine Modena Italy IRCCS San Raffaele Scientific Institute Nuclear Medicine Unit Milano Italy University of Modena and Reggio Emilia PhD program in Clinical and Experimental Medicine (CEM) Modena Italy National Cancer Institute Fondazione "G. Pascale" IRCCS Hematology-Oncology and Stem Cell Transplantation Unit Napoli Italy IRCCS San Martino Hospital Hematology and Transplant Center Division Genoa Italy Sapienza Università di Roma Dipartimento di Biotecnologie Cellulari ed Ematologia Roma Italy University Hospital Ospedale di Circolo e Fondazione Macchi ASST Settelaghi Varese Italy Fondazione IRCCS Istituto Nazionale dei Tumori di Milano Division of Hematology Milano Italy Ospedale Civile S Maria delle Croci Azienda Unità Sanitaria Locale (AUSL) Ravenna Italy A.O.U. Città della Salute e della Scienza di Torino SC Ematologia Torino Italy IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Department of Hematology Meldola Italy University of Perugia Institute of Hematology and CREO (Center for Hemato-Oncological Research) Ospedale S. Maria della Misericordia Perugia Italy IRCCS Ospedale Policlinico San Martino University of Genoa Clinica Ematologica Genova Italy General Hospital Ca' Foncello Hematology Treviso

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