Development of Fault Diagnosis System for Spacecraft Based on Fault Tree and G2

Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.

Effect of water stress on N_2O emission rate of 5 tree species

The N2O emission rates, photosynthesis, respiration and stomatal conductance of the dominant tree species from broadleaf/Korean pine forest in Changbai Mountain were measured by simulated water stress with the closed bag-gas chromatography. A total of five species seedlings were involved in this study, i.e.,Pinus koraiensis Sieb. et Zucc,Fraxinus mandshurica Rupr,Juglans mandshurica Maxim,Tilia amurensis Rupr, andQuercus mongolica Fisch. ex Turcz.. The results showed that the stomatal conductance, net photosynthetic rate and N2O emission of leaves were significantly reduced under the water stress. The stoma in the leaves of trees is the main pathway of N2O emission. N2O emission in the trees mainly occurred during daytime. N2O emission rates were different in various tree specie seedlings at the same water status. In the same tree species, N2O emission rates decreased as the reduction of soil water contents. At different soil water contents (MW, LW) the N2O emission rates ofPinus koraiensis decreased by 34.43% and 100.6% of those in normal water condition, respectively. In broadleaf arbor decreased by 31.93% and 86.35%, respectively. Under different water stresses N2O emission rates in five tree species such asPinus koraiensis, Fraxinus mandshurica, Juglans mandshurica, Tilia amurensis, andQuercus mongolica were 38.22, 14.44, 33.02, 16.48 and 32.33 ngN2O·g?1DW·h?1, respectively. Keywords Trees - N2O emission rate - Soil water stress - broadleaf/Korean pine forest - Changbai Mountain CLC number S718.55 Document code A Foundation item: This project was supported by the National Natural Science Foundation of China (No. 30271068), the grant of the Knowledge Innovation Program of Chinese Academy of Sciences (KZ-CX-SW-01-01B-10), and the Special Funds for Major State Basic Research Program of China (No. G1999043407)Biography: Wang Miao (1964-), male, associate professor in Institute of Applied Ecology, Chinese Academy of Science, Shenyang 110016, P. R. China.Responsible editor: Song Funan

基于Sentinel-2的青铜峡灌区水稻和玉米种植分布早期识别

及时准确地掌握灌区内作物种植分布对于灌溉水资源高效配置、农田精准管理具有重要指导意义。以宁夏青铜峡灌区为研究对象,利用多时相Sentinel-2卫星数据,通过水稻和玉米早期特征分析,提取关键的“水淹”信号和“植被”信号,构建时序归一化差异水体指数(MNDWI)和归一化植被指数(NDVI)特征值数据集,并通过样本分析关键特征阈值,构建水稻和玉米早期种植分布决策树模型,提取2022年宁夏青铜峡灌区水稻和玉米种植的空间分布。结果表明(:1)玉米和水稻苗期的后半段5月15—31日,水淹信号和植被信号是区分二者关键时期。(2)基于早期作物物候特征的方法,在5月16—31日获取的水稻和玉米图像制图精度高于90%,用户精度超过91%,总体精度超过90%,Kappa系数高于0.88,明显高于同时期随机森林方法的分类精度。(3)本研究提出的方法在早期水稻和玉米种植分布提取方面具有较强的适用性,并且能够在时空尺度上以较少的实地样本进行延展,同时在时间上也更有优势。因此,该方法为青铜峡灌区水稻和玉米种植分布早期调查提供了重要的方法支撑。

2-median location improvement problems under weighted l_1 norm and l_∞ norm on trees

This paper focuses on the 2-median location improvement problem on tree networks and the problem is to modify the weights of edges at the minimum cost such that the overall sum of the weighted distance of the vertices to the respective closest one of two prescribed vertices in the modified network is upper bounded by a given value.l1 norm and l∞norm are used to measure the total modification cost. These two problems have a strong practical application background and important theoretical research value. It is shown that such problems can be transformed into a series of sum-type and bottleneck-type continuous knapsack problems respectively.Based on the property of the optimal solution two O n2 algorithms for solving the two problems are proposed where n is the number of vertices on the tree.

概率网络中星形2-hub放置问题的边扰动算法

在交通运输、邮政和电信网络中,hub作为特殊的设备起着交换、转载和整理的重要作用。该文研究概率网络中的星形2-hub放置问题,网络中的每条边上都有独立的工作概率,给出基于最大概率路图的边扰动算法并在多项式时间内获得最优2-hub树。

星形2-hub选址问题的多项式时间算法

Hub作为特殊的设备在交通运输、邮政和电信网络中承担着交换、转载和整理的重要角色。研究一般网络中最小费用星形2-hub选址问题和最小时延星形2-hub选址问题,分别给出多项式时间算法,计算出2个hub的最佳位置。

Effects of elevated CO_2 on net photosynthetic rate of trees in Changbai Mountain

Net photosynthetic rates (NPRs) of four species seedlings, Pinus koraiensis, Ptrius Syvestriformis,Fraxinus mandshuthe and Phellodendron amurense, were measured at different CO2 concentrations and time respectively in Changbai Mountain during the growing season in 1999. The seedlings were cultivated in open-top chambers (OTCs), located outdoors and exposed to natural sunlight. The experimental objects were divided into four groups by tree species. CO2 concentrations in chambers were kept at 500 μL-L-1 and 700 μL-L-1 and contrast chamber and contrast field were set. The results showed that the effects of elevated CO2 on NPR of the trees strongly depended on tree species and time. NPRs of Pin us koreaipsis and Pinus syvestriformis seedfings increased with the rising of CO2 concentration, while that of Phellodron amurense and haus mandshurica increased at some time and decreased at another time.

Using a Tree Ring δ^(13)C Annual Series to Reconstruct Atmospheric CO_2 Concentration over the Past 300 Years

The annual series of δ13C were measured in tree rings of three Cryptomeria fortunei disks （OF-1, OF-2, and OF- 3） collected from West Tianmu Mountain, Zhejiang Province, China, according to cross-dating tree ring ages. There was no obvious decreasing trend of the δ13C annual time series of CF-2 before 1835. However, from 1835 to 1982 the three tree ring δ13C annual series exhibited similar decreasing trends that were significantly （P ≤ 0.001） correlated. The distribution characteristics of a scatter diagram between estimated δ13C series of CF-2 from modeling and the atmospheric CO2 concentration extracted from the Law Dome ice core from 1840 to 1978 were analyzed and a curvilinear regression equation for reconstructing atmospheric CO2 concentration was established with R2 = 0.98. Also, a test of independent samples indicated that between 1685 and 1839 the reconstructed atmospheric CO2 concentration .using the δ13C series of CF-2 had a close relationship with the Law Dome and Siple ice cores, with a standard deviation of 1.98. The general increasing trend of the reconstructed atmospheric CO2 concentration closely reflected the 10ng-term variation of atmospheric CO2 concentration recorded both before and after the Industrial Revolution. Between 1685 and 1840 the evaluated atmospheric CO2 concentration was stable, but after 1840 it exhibited a rapid increase. Given a longer δ13C annual time series of tree rings, it was feasible to rebuild a representative time series to describe the atmospheric CO2 concentration for an earlier period and for years that were not in the ice core record.

Assessing Landsat-8 and Sentinel-2 spectral-temporal features for mapping tree species of northern plantation forests in Heilongjiang Province,China

Background:Accurate mapping of tree species is highly desired in the management and research of plantation forests,whose ecosystem services are currently under threats.Time-series multispectral satellite images,e.g.,from Landsat-8(L8)and Sentinel-2(S2),have been proven useful in mapping general forest types,yet we do not know quantitatively how their spectral features(e.g.,red-edge)and temporal frequency of data acquisitions(e.g.,16-day vs.5-day)contribute to plantation forest mapping to the species level.Moreover,it is unclear to what extent the fusion of L8 and S2 will result in improvements in tree species mapping of northern plantation forests in China.Methods:We designed three sets of classification experiments(i.e.,single-date,multi-date,and spectral-temporal)to evaluate the performances of L8 and S2 data for mapping keystone timber tree species in northern China.We first used seven pairs of L8 and S2 images to evaluate the performances of L8 and S2 key spectral features for separating these tree species across key growing stages.Then we extracted the spectral-temporal features from all available images of different temporal frequency of data acquisition(i.e.,L8 time series,S2 time series,and fusion of L8 and S2)to assess the contribution of image temporal frequency on the accuracy of tree species mapping in the study area.Results:1)S2 outperformed L8 images in all classification experiments,with or without the red edge bands(0.4%–3.4%and 0.2%–4.4%higher for overall accuracy and macro-F1,respectively);2)NDTI(the ratio of SWIR1 minus SWIR2 to SWIR1 plus SWIR2)and Tasseled Cap coefficients were most important features in all the classifications,and for time-series experiments,the spectral-temporal features of red band-related vegetation indices were most useful;3)increasing the temporal frequency of data acquisition can improve overall accuracy of tree species mapping for up to 3.2%(from 90.1%using single-date imagery to 93.3%using S2 time-series),yet similar overall accuracies were achieved using S2 time-series(93.3%)and the fusion of S2 and L8(93.2%).Conclusions:This study quantifies the contributions of L8 and S2 spectral and temporal features in mapping keystone tree species of northern plantation forests in China and suggests that for mapping tree species in China's northern plantation forests,the effects of increasing the temporal frequency of data acquisition could saturate quickly after using only two images from key phenological stages.

基于注意力机制的Tree2Seq代码注释自动生成

代码注释可以帮助开发人员快速理解代码,降低代码维护成本。为了保留代码的结构信息,针对经典的Seq2Seq模型将代码的结构信息压缩为序列,导致结构信息丢失的问题,提出使用Tree-LSTM编码器直接将代码转化成抽象语法树进行编码,使注释生成模型能有效获取代码的结构信息,提升注释生成效果。采用基于注意力机制的Tree2Seq模型实现代码注释生成任务,避免了编码器端将所有输入信息压缩为固定向量,导致部分信息丢失的情况。通过在Java和Python 2种编程语言的数据集上进行实验,使用3种机器翻译常用的自动评测指标进行评估验证,并选取一部分测试数据进行了人工评估。实验结果表明,基于注意力机制的Tree2Seq模型能为解码器提供更全面且丰富的语义结构信息,为后续实验分析和改进提供指导。

Effect of elevated CO_(2) concentration on growth course of tree seedlings in Changbai Mountain

One-year-old seedlings of Pinus koraiensis, Pinus sylvestriformis, Phellodendron amurense were grown in open-top chambers (OTCs) with 700 and 500 (mol/mol CO2 concentrations, control chamber and on open site (ambient CO2, about 350 (mol/mol CO2) respectively at the Open Research Station of Changbai Mountain Forest Ecosystems, Chinese Academy of Sciences, and the growth course responses of three species to elevated CO2 and temperature during one growing season was studied from May to Oct. 1999. The results showed that increase in CO2 concentration enhanced the growth of seedlings and the effect of 700 (mol/mol CO2 was more remarkable than 500 (mol/mol CO2 on seedling growth. Under the condition of doubly elevated CO2 concentration, the biomass increased by 38% in average for coniferous seedlings and 60% for broad-leaved seedlings. With continuous treatment of high CO2 concentration, the monthly-accumulated biomass of shade-tolerant Pinus koraiensis seedlings was bigger in July than in August and September, while those of Pinus sylvestriformis and Phellodendron amurense seedlings showed an increase in July and August, or did not decrese until September. During the hot August, high CO2 concentration enhanced the growth of Pinus koraiensis seedlings by increasing temperature, but it did not show dominance in other two species.

Clinical study of different prediction models in predicting diabetic nephropathy in patients with type 2 diabetes mellitus

BACKGROUND Among older adults,type 2 diabetes mellitus(T2DM)is widely recognized as one of the most prevalent diseases.Diabetic nephropathy(DN)is a frequent com-plication of DM,mainly characterized by renal microvascular damage.Early detection,aggressive prevention,and cure of DN are key to improving prognosis.Establishing a diagnostic and predictive model for DN is crucial in auxiliary diagnosis.AIM To investigate the factors that impact T2DM complicated with DN and utilize this information to develop a predictive model.METHODS The clinical data of 210 patients diagnosed with T2DM and admitted to the First People’s Hospital of Wenling between August 2019 and August 2022 were retrospectively analyzed.According to whether the patients had DN,they were divided into the DN group(complicated with DN)and the non-DN group(without DN).Multivariate logistic regression analysis was used to explore factors affecting DN in patients with T2DM.The data were randomly split into a training set(n=147)and a test set(n=63)in a 7:3 ratio using a random function.The training set was used to construct the nomogram,decision tree,and random forest models,and the test set was used to evaluate the prediction performance of the model by comparing the sensitivity,specificity,accuracy,recall,precision,and area under the receiver operating characteristic curve.RESULTS Among the 210 patients with T2DM,74(35.34%)had DN.The validation dataset showed that the accuracies of the nomogram,decision tree,and random forest models in predicting DN in patients with T2DM were 0.746,0.714,and 0.730,respectively.The sensitivities were 0.710,0.710,and 0.806,respectively;the specificities were 0.844,0.875,and 0.844,respectively;the area under the receiver operating characteristic curve(AUC)of the patients were 0.811,0.735,and 0.850,respectively.The Delong test results revealed that the AUC values of the decision tree model were lower than those of the random forest and nomogram models(P<0.05),whereas the difference in AUC values of the random forest and column-line graph models was not statistically significant(P>0.05).CONCLUSION Among the three prediction models,random forest performs best and can help identify patients with T2DM at high risk of DN.

HitPeers:A P2P File Sharing System with Category Tree

HitPeers conotitute a scalable and highly efficient P2P file sharing system in which all the data file can be shared. The center of HitPeers is the Category Tree (CT). CT collects the published information with category. It is flexible enough to let users customize their own local CT. Its hierarchy helps users to find the information they desire most conveniently. To increase the robustness and retain the efficiency, HitPeers will divide the tree into disjoint parts. Every part is a subtree. Some special nodes named Onodes will take charge of the subtree and play the role of a service provider. HitPeers produce more and more Onodes to meet the service demands in the internet scale distributed environment. This paper will show the profile of the whole system.

Long-Term H2O and CO2 Trends in Conifer Disc Tree Rings and Meteorological Parameters

Results of investigations into the CO2 content in tree disc rings by the method proposed here have shown that a considerable part of CO2 generated under cell respiration is found in tree stems. Besides, annual CO2 distribution in tree rings exhibits a well-defined cyclicity. Results obtained from investigations into long-term CO2 and H2O variations in tree discs performed by different methods are presented. Wavelet and spectral analyses of the relationship between CO2 and H2O variations in a Siberian stone pine disc and meteorological parameters were made. The CO2 annual distributions of seven spruce tree discs were examined by the Caterpiller-SSA method. Wood samples of Siberian stone pine and spruce trees were taken from the same site in Tomsk region （Siberia, Russia） that characterized by an optimum growth habitat. Conclusions are made regarding the response of the annual CO2 and H2O conifer disc tree ring distributions to different climatic factors.

Biosorption Isotherms and Kinetics Studies for the Removal of 2,6-Dichlorophenolindophenol Using Palm Tree Trunk (<em>Elaeis guineensis</em>)

In this work, the potential of natural and pretreated palm tree trunk (PTT) as agents for adsorption of an organic dye, 2,6-dichlorophenolindophenol (2,6-DCPIP) from aqueous solutions was probed. Natural and acetic acid treated PTT were characterized by Fourier transform infrared (FT-IR) spectroscopy and by the point of zero charge (pzc). The biosorption of 2,6-DCPIP was investigated in batch mode using natural and treated PTT. This study was achieved by highlighting several parameters such as the contact time, biosorbents dosage, the initial concentration of 2,6-DCPIP, the pH of the solution, the ionic strength and the interfering ions. The results showed that 2,6-DCPIP was successfully adsorbed from aqueous solutions by natural and treated PTT. The equilibrium was attained after 40 minutes for treated PTT and 20 minutes for natural PTT. The maximum capacity of adsorption was obtained at pH = 2. The adsorption isotherms were investigated and it was found that the experimental data were best described by the Dubinin-Radushkevich isotherm for the natural PTT (R2 = 0.979) and by the Temkin isotherm for the treated PTT (R2 = 0.976). The maximum adsorption capacities determined by Langmuir isotherm were found as 108.932 and 157.233 μmol&middot;g&ndash;1 for natural and treated PTT, respectively. The adsorption kinetics was analyzed and was best described by the pseudo-second order model (R2 ≥ 0.998). The diffusion mechanism was studied and the result showed that external mass transfer is the main rate controlling step. The desorption of 2,6-DCPIP is favorable in alkaline medium.

基于Sentinel-2数据提取江汉平原虾稻田分布方法

以江汉平原为研究区,基于AI Earth阿里云平台提供的Sentinel-2 MSI L2数据,在实地采样样本和目视解译样本的基础上,通过分析遥感影像中虾稻田的时序变化规律,总结出区分虾稻田与其他地物类型的关键时间以及指数阈值,从而构建虾稻田提取的决策树模型,最终提取出江汉平原2022—2023年虾稻田的空间分布。最后,基于样本数据评估了该方法的精度,总体精度达93.25%,Kappa系数为0.8429,结果表明该方法具有较好的提取结果。

Parallelized Hashing via <i>j</i>-Lanes and <i>j</i>-Pointers Tree Modes, with Applications to SHA-256

j-lanes tree hashing is a tree mode that splits an input message into?j?slices, computes?j?independent digests of each slice, and outputs the hash value of their concatenation.?j-pointers tree hashing is a similar tree mode that receives, as input,?j?pointers to?j?messages (or slices of a single message), computes their digests and outputs the hash value of their concatenation. Such modes expose parallelization opportunities in a hashing process that is otherwise serial by nature. As a result, they have a performance advantage on modern processor architectures. This paper provides precise specifications for these hashing modes, proposes appropriate IVs, and demonstrates their performance on the latest processors. Our hope is that it would be useful for standardization of these modes.

A <i>j</i>-Lanes Tree Hashing Mode and <i>j</i>-Lanes SHA-256

j-lanes hashing is a tree mode that splits an input message to j slices, computes j independent digests of each slice, and outputs the hash value of their concatenation. We demonstrate the performance advantage of j-lanes hashing on SIMD architectures, by coding a 4-lanes-SHA-256 implementation and measuring its performance on the latest 3rd Generation IntelR CoreTM. For messages whose lengths range from 2 KB to 132 KB, we show that the 4-lanes SHA-256 is between 1.5 to 1.97 times faster than the fastest publicly available implementation that we are aware of, and between ~2 to ~2.5 times faster than the OpenSSL 1.0.1c implementation. For long messages, there is no significant performance difference between different choices of j. We show that the 4-lanes SHA-256 is faster than the two SHA3 finalists (BLAKE and Keccak) that have a published tree mode implementation. Finally, we explain why j-lanes hashing will be faster on the coming AVX2 architecture that facilitates using 256 bits registers. These results suggest that standardizing a tree mode for hash functions (SHA-256 in particular) could be useful for performance hungry applications.

N_2浮选法在Lone Tree矿山的应用

过去几年里 ,Newmont金矿公司开发了一种处理难选含金硫化矿的新工艺 ,即N2 浮选工艺。 1997年 4月 ,第一个应用N2 浮选工艺的工业选矿厂在美国内华达州LoneTree矿山成功投产。该浮选厂设计能力为 40 85t/d矿石 ,或 494t/d硫化矿精矿。一部分浮选精矿与给矿合并给入LoneTree高压氧化厂 ,因而限制了现有高压氧化厂处理能力的提高。剩余的精矿卖给TwinCreeks高压氧化厂或Carlin焙烧厂 ,在这些厂中先氧化再回收金。本文讨论了N2 浮选工艺扩大试验厂试验和工业选矿厂生产结果 ,以及工程设计模拟结果。同时还提出了N2 浮选工艺的基本投资和生产费用数据。

Retrieval of Antarctic sea ice freeboard and thickness from HY-2B satellite altimeter data

Antarctic sea ice is an important part of the Earth’s atmospheric system,and satellite remote sensing is an important technology for observing Antarctic sea ice.Whether Chinese Haiyang-2B(HY-2B)satellite altimeter data could be used to estimate sea ice freeboard and provide alternative Antarctic sea ice thickness information with a high precision and long time series,as other radar altimetry satellites can,needs further investigation.This paper proposed an algorithm to discriminate leads and then retrieve sea ice freeboard and thickness from HY-2B radar altimeter data.We first collected the Moderate-resolution Imaging Spectroradiometer ice surface temperature(IST)product from the National Aeronautics and Space Administration to extract leads from the Antarctic waters and verified their accuracy through Sentinel-1 Synthetic Aperture Radar images.Second,a surface classification decision tree was generated for HY-2B satellite altimeter measurements of the Antarctic waters to extract leads and calculate local sea surface heights.We then estimated the Antarctic sea ice freeboard and thickness based on local sea surface heights and the static equilibrium equation.Finally,the retrieved HY-2B Antarctic sea ice thickness was compared with the CryoSat-2 sea ice thickness and the Antarctic Sea Ice Processes and Climate(ASPeCt)ship-based observed sea ice thickness.The results indicate that our classification decision tree constructed for HY-2B satellite altimeter measurements was reasonable,and the root mean square error of the obtained sea ice thickness compared to the ship measurements was 0.62 m.The proposed sea ice thickness algorithm for the HY-2B radar satellite fills a gap in this application domain for the HY-series satellites and can be a complement to existing Antarctic sea ice thickness products;this algorithm could provide long-time-series and large-scale sea ice thickness data that contribute to research on global climate change.