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Predicting rice diseases using advanced technologies at different scales: present status and future perspectives

aBIOTECH 2023年第4期4卷 359-371页

作者： Ruyue Li Sishi Chen Haruna Matsumoto Mostafa Gouda Yusufjon Gafforov Mengcen Wang Yufei Liu College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310058China College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China State Key Laboratory of Rice Biology and Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and InsectsZhejiang UniversityHangzhou 310058China Department of Nutrition and Food Science National Research CentreGiza 12622Egypt Central Asian Center for Development Studies New Uzbekistan UniversityTashkent 100000Uzbekistan Global Education Program for AgriScience Frontiers Graduate School of AgricultureHokkaido UniversitySapporo 060-8589Japan

The past few years have witnessed significant progress in emerging disease detection techniques foraccurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focuson image processing techniques using machine learning (ML) and deep learning (DL) models related tomulti-scale rice diseases. Furthermore, we summarize applications of different detection techniques,including genomic, physiological, and biochemical approaches. In addition, we also present the state-ofthe-art in contemporary optical sensing applications of pathogen–plant interaction phenotypes. Thisreview serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice cropsthrough ML and DL models.

关键词： Artificial intelligence Rice disease model algorithms Imaging technology Plant-pathogen interactions High-throughput data

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Application of Secondary Development Based on MATLAB in Rubber Life Prediction 8

Application of Secondary Development Based on MATLAB in Rubb...

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8th International Conference on Advances in Machinery, Materials Science and Engineering Application (MMSE)

作者： Huang, Hongning Liu, Shixiang He, Jianxin Li, Zehua Zhao, Fangchao Liu, Xiang Southwest Technol & Engn Res Inst Chongqing 400039 Peoples R China Natl Outdoor Scientificm Observat & Res Jiang Jin Mat Atmospher Corros Stn JiangJin 402200 Peoples R China Natl Outdoor Scientificm Observat & Res Dun Huang Atmospher Stn DunHuang 736200 Peoples R China

ISBN: (纸本)9781643683225;9781643683232

Rubber seals are polymer materials which are widely used in aerospace, weapon equipment technology, electrical and electronics, medical equipment and mechanical manufacture and other fields. Their properties will reduce progressively under the environmental conditions of high temperature, oxygen, and mechanical stress etc, that is so-called "aging". In view of the huge losses and hidden dangers caused by the aging failure of rubber, and various phenomena will seriously affect the accuracy of life prediction and the understanding of rubber aging behavior, therefore, the rapid evaluation mechanism of the existing model established by software is used to evaluate the aging of rubber. In order to quickly calculate the rubber life of different material components, more than 10 classical model algorithms are established through the MATLAB platform in this paper. Users can choose relevant models to complete life prediction. The simulation results are close to the test results. The software improves the accuracy and reliability of life evaluation.

关键词： Rubber MATLAB model algorithms life prediction

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The Development of a Space climatology: 3. models of the Evolution of Distribution of Space Weather Variables With Timescale

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SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 2019年第1期17卷 180-209页

作者： Lockwood, Mike Bentley, Sarah N. Owens, Mathew J. Barnard, Luke A. Scott, Chris J. Watt, Clare E. Allanson, Oliver Freeman, Mervyn P. Univ Reading Dept Meteorol Reading Berks England British Antarctic Survey Cambridge England

We study how the probability distribution functions of power input to the magnetosphere P-alpha and of the geomagnetic ap and Dst indices vary with averaging timescale, tau, between 3 hr and 1 year. From this we develop and present algorithms to empirically model the distributions for a given z and a given annual mean value. We show that lognormal distributions work well for ap, but because of the spread of Dst for low activity conditions, the optimum formulation for Dst leads to distributions better described by something like the Weibull formulation. Annual means can be estimated using telescope observations of sunspots and modeling, and so this allows the distributions to be estimated at any given z between 3 hr and 1 year for any of the past 400 years, which is another important step toward a useful space weather climatology. The algorithms apply to the core of the distributions and can be used to predict the occurrence rate of large events (in the top 5% of activity levels): they may contain some, albeit limited, information relevant to characterizing the much rarer superstorm events with extreme value statistics. The algorithm for the Dst index is the more complex one because, unlike ap, Dst can take on either sign and future improvements to it are suggested. Plain Language Summary;This is the third in a series of three papers aimed at developing a climatology of space weather that applies to all solar conditions between grand solar minimum and grand solar maximum. We generate empirical models to enable us to predict the probability of a given level of space weather disturbance, as quantified by either the ap of the Dst geomagnetic indices, in a year with a given average level of disturbance. The models can be used with averaging/integration times anywhere between 3 hr and 1 year.

关键词： climatology long‐term variations geomagnetic indices probability distribution functions model algorithms large and extreme events

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Controls on carbon export in the subtropical North Atlantic

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PROGRESS IN OCEANOGRAPHY 2020年 187卷 102380-102380页

作者： Yumruktepe, Veli Caglar Salihoglu, Baris Neuer, Susanne Middle East Tech Univ Inst Marine Sci POB 28 TR-33731 Erdemli Mersin Turkey Arizona State Univ Sch Life Sci POB 874501 Tempe AZ USA Nansen Ctr N-5019 Bergen Norway

We present a lower trophic level pelagic ecosystem model that allows the investigation of the role of hydrography, bacterial remineralization and detritus consumption on the strength of carbon export and its attenuation. We apply the model to investigate the controls on the carbon export at the Bermuda Atlantic Time-Series Study site (BATS) and the European Station for Time series in the Ocean, Canary Islands (ESTOC) in the subtropical North Atlantic. In previous field studies, export ratios at 200 m (the ratio between particulate carbon export below the euphoric zone and primary production) were found to be 300-400% smaller at ESTOC compared to BATS. Our model results show that the magnitude and temporal variability of primary productivity and modeled carbon export are modulated by the intensity and duration of vertical mixing events. BATS, with a more dynamic physical environment, has winter mixed-layer depths on average 80 m deeper than ESTOC and is characterized by pulses of enhanced productivity and export. Our model demonstrates the influence of hydrography on export attenuation through (i) more stable water column dynamics at ESTOC that increase particle remineralization time scales and weaken export strength at ESTOC compared to BATS;and (ii) higher water temperatures at BATS in the mesopelagic between 200 and 500 m that increase remineralization rates compared to ESTOC. This results in reduced differences in export ratios within the mesopelagic between both stations that is confirmed by observations. Strengthening remineralization through (i) adding zooplankton feeding on detritus and (ii) increasing bacterial remineralization rates decrease export at all depths at both stations, and increase the modeled difference in 200 m export ratios between BATS and ESTOC from 7% to 17%, a difference that is still much smaller than observed. While we could demonstrate the skill of our model in testing the mechanisms that could lead to differences in regional carbon exp

关键词： Carbon export BATS ESTOC model algorithms Detritus feeding Bacterial remineralization Subtropical gyre

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A Self-Acting Gas Journal Bearing with a Flexibly Supported Foil - Numerical model of Bearing Dynamics

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INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS 2017年第5期17卷 1740012-1740012页

作者： Tkacz, Eliza Kozanecki, Zbigniew Kozanecka, Dorota Lagodzinski, Jakub Lodz Univ Technol Div Automat & Diagnost Turbomachinery Inst Turbomachinery 219-223 Wolczanska St PL-90924 Lodz Poland Lodz Univ Technol Div Automat & Diagnost Turbomachinery 219-223 Wolczanska St PL-90924 Lodz Poland Lodz Univ Technol Div Flow Metrol 219-223 Wolczanska St PL-90924 Lodz Poland

The work is devoted to an analysis of the journal bearing dynamics, while factors related to motion and friction of nonrotating elements of the sleeve are taken into account. Based on the originally established numerical model devoted to bearing static simulations, the thickness of gas film was determined as well as the pressure distribution in the bearing and its lift capacity. Moreover, the numerical program developed for dynamic simulations led to an analysis of forced vibrations of the system under consideration. It was possible to visualize a journal trajectory for the dynamic harmonic input function. The relationship between the frequency of excitation force and bearing stiffness has been identified numerically and compared with the experimental results. The Fast Fourier Transform (FFT) analysis of vibrations was implemented. In the spectrum, only a frequency of the input function was observed, whereas and a lack of subsynchronous frequencies pointed to the stable operation of the bearing. The established numerical model yields the basis for simulations carried out in order to determine correctly dynamic characteristics of an oil-free machine rotating system at the early stage of its design and during its operation.

关键词： Foil bearing dynamics numerical methods model algorithms

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Good-bye to tropical alpine plant giants under warmer climates? Loss of range and genetic diversity in Lobelia rhynchopetalum

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ECOLOGY AND EVOLUTION 2016年第24期6卷 8931-8941页

作者： Chala, Desalegn Brochmann, Christian Psomas, Achilleas Ehrich, Dorothee Gizaw, Abel Masao, Catherine A. Bakkestuen, Vegar Zimmermann, Niklaus E. Univ Oslo Nat Hist Museum Oslo Norway Swiss Fed Res Inst WSL Birmensdorf Switzerland UiT Arctic Univ Norway Dept Arctic & Marine Biol Tromso Norway Univ Dar Es Salaam Inst Resource Assessment Dar Es Salaam Tanzania Norwegian Inst Nat Res Oslo Norway

The main aim of this paper is to address consequences of climate warming on loss of habitat and genetic diversity in the enigmatic tropical alpine giant rosette plants using the Ethiopian endemic Lobelia rhynchopetalum as a model. We modeled the habitat suitability of L. rhynchopetalum and assessed how its range is affected under two climate models and four emission scenarios. We used three statistical algorithms calibrated to represent two different complexity levels of the response. We analyzed genetic diversity using amplified fragment length polymorphisms and assessed the impact of the projected range loss. Under all model and scenario combinations and consistent across algorithms and complexity levels, this afro-alpine flagship species faces massive range reduction. Only 3.4% of its habitat seems to remain suitable on average by 2,080, resulting in loss of 82% (CI 75%-87%) of its genetic diversity. The remaining suitable habitat is projected to be fragmented among and reduced to four mountain peaks, further deteriorating the probability of long-term sustainability of viable populations. Because of the similar morphological and physiological traits developed through convergent evolution by tropical alpine giant rosette plants in response to diurnal freeze-thaw cycles, they most likely respond to climate change in a similar way as our study species. We conclude that specialized high-alpine giant rosette plants, such as L. rhynchopetalum, are likely to face very high risk of extinction following climate warming.

关键词： afro-alpine climate change giant rosette plants Lobelia rhynchopetalum loss of genetic diversity model algorithms model complexity range loss tropical alpine plants

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Using Lagrangian-based process studies to test satellite algorithms of vertical carbon flux in the eastern North Pacific Ocean

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JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 2015年第11期120卷 7208-7222页

作者： Stukel, M. R. Kahru, M. Benitez-Nelson, C. R. Decima, M. Goericke, R. Landry, M. R. Ohman, M. D. Florida State Univ Dept Earth Ocean & Atmospher Sci Tallahassee FL 32306 USA Univ Calif San Diego Scripps Inst Oceanog La Jolla CA 92093 USA Univ S Carolina Marine Sci Program Columbia SC 29208 USA Univ S Carolina Dept Earth & Ocean Sci Columbia SC 29208 USA Natl Inst Water & Atmospher Res Wellington New Zealand

The biological carbon pump is responsible for the transport of similar to 5-20 Pg C yr(-1) from the surface into the deep ocean but its variability is poorly understood due to an incomplete mechanistic understanding of the complex underlying planktonic processes. In fact, algorithms designed to estimate carbon export from satellite products incorporate fundamentally different assumptions about the relationships between plankton biomass, productivity, and export efficiency. To test the alternate formulations of export efficiency in remote-sensing algorithms formulated by Dunne et al. (2005), Laws et al. (2011), Henson et al. (2011), and Siegel et al. (2014), we have compiled in situ measurements (temperature, chlorophyll, primary production, phytoplankton biomass and size structure, grazing rates, net chlorophyll change, and carbon export) made during Lagrangian process studies on seven cruises in the California Current Ecosystem and Costa Rica Dome. A food-web based approach formulated by Siegel et al. (2014) performs as well or better than other empirical formulations, while simultaneously providing reasonable estimates of protozoan and mesozooplankton grazing rates. By tuning the Siegel et al. (2014) algorithm to match in situ grazing rates more accurately, we also obtain better in situ carbon export measurements. Adequate representations of food-web relationships and grazing dynamics are therefore crucial to improving the accuracy of export predictions made from satellite-derived products. Nevertheless, considerable unexplained variance in export remains and must be explored before we can reliably use remote sensing products to assess the impact of climate change on biologically mediated carbon sequestration.

关键词： satellite-derived export carbon export model algorithms mesozooplankton grazing sinking particles gravitational flux

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