Quantitative Analysis of Seeing with Height and Time at Muztagh-Ata Site Based on ERA5 Database

Seeing is an important index to evaluate the quality of an astronomical site.To estimate seeing at the Muztagh-Ata site with height and time quantitatively,the European Centre for Medium-Range Weather Forecasts reanalysis database(ERA5)is used.Seeing calculated from ERA5 is compared consistently with the Differential Image Motion Monitor seeing at the height of 12 m.Results show that seeing decays exponentially with height at the Muztagh-Ata site.Seeing decays the fastest in fall in 2021 and most slowly with height in summer.The seeing condition is better in fall than in summer.The median value of seeing at 12 m is 0.89 arcsec,the maximum value is1.21 arcsec in August and the minimum is 0.66 arcsec in October.The median value of seeing at 12 m is 0.72arcsec in the nighttime and 1.08 arcsec in the daytime.Seeing is a combination of annual and about biannual variations with the same phase as temperature and wind speed indicating that seeing variation with time is influenced by temperature and wind speed.The Richardson number Ri is used to analyze the atmospheric stability and the variations of seeing are consistent with Ri between layers.These quantitative results can provide an important reference for a telescopic observation strategy.

黄河流域煤炭-煤电-煤化工场地特征精准智能识别方法及应用

黄河流域是“能源流域”,兼具生态环境治理和经济社会发展的重任,涉煤产业场地类型、数量及特征的精准智能识别是流域能源资源-低碳发展-生态保护的关键基础问题。研究融合多源数据与深度学习算法,从流域-基地-场地尺度对黄河流域13个大型煤电基地的煤基场地特征精准解析,获得煤电基地高精度、高质量的本底信息,提出一种实时实景智能识别涉煤产业空间特征的新方法。(1)筛选Google image、GF-6影像、Sentinel-2影像等多源数据,采集13个大型煤电基地煤基场地样本,构建煤炭场地(露天)、煤炭场地(井工)、煤电场地、煤化工场地4类数据集,涵盖21种样本类型。按照每种样本六面体设定6×10个样本,共计1 260个场地样本,分析得出最适样本数量-最高识别效率-最优识别模型的置信区间为80%~86%。(2)建立了煤基场地类型量化模型(Coal-based Site Classification Quantitative Model, CSCQM)和煤基场地范围特征模型(Coalbased Site Range Characteristic Model, CSRCM),模型平均精准度为0.837。明析了黄河流域涉煤产业场地本底信息,提出Google image底图叠加场地智能识别模型解算结果的高精度场地智能识别方法。(3)解析了流域神东煤炭-煤电产业集聚区精准本底数据,依据遥感生态指数(Remote Sensing Based Ecological Index,IRSE)分析,煤基场地分布2 km核心区地表生态质量受煤炭、煤电产业影响明显,5 km缓冲区则影响不明显,而8 km控制区基本不受煤炭、煤电产业影响,从而给出了“动态修复”与分区域、分阶段重点治理等低碳路径。(4)解析了流域宁东煤炭-煤电-煤化工产业集聚区精准本底数据,2022年煤炭场地17.81 km^(2)、占比34.1%,煤化工场地22.3 km^(2)、占比42.6%,煤电场地12.2 km^(2)、占比23.3%,煤化工场地>煤炭场地>煤电场地。进而采用PSR(Pressure-State-Response)模型得到风险管控综合得分53.93分,较2003年提高了27.2%。划分生态维护区、生产监测预警区、损毁修复重建区、其他调控区的分区管控模式。研究为涉煤产业煤基场地潜在污染控制、场地治理及区域生态修复提供技术方法与实践支撑。

A Data-Semantic-Conflict-Based Multi-Truth Discovery Algorithm for a Programming Site

With the extensive application of software collaborative development technology,the processing of code data generated in programming scenes has become a research hotspot.In the collaborative programming process,different users can submit code in a distributed way.The consistency of code grammar can be achieved by syntax constraints.However,when different users work on the same code in semantic development programming practices,the development factors of different users will inevitably lead to the problem of data semantic conflict.In this paper,the characteristics of code segment data in a programming scene are considered.The code sequence can be obtained by disassembling the code segment using lexical analysis technology.Combined with a traditional solution of a data conflict problem,the code sequence can be taken as the declared value object in the data conflict resolution problem.Through the similarity analysis of code sequence objects,the concept of the deviation degree between the declared value object and the truth value object is proposed.A multi-truth discovery algorithm,called the multiple truth discovery algorithm based on deviation(MTDD),is proposed.The basic methods,such as Conflict Resolution on Heterogeneous Data,Voting-K,and MTRuths_Greedy,are compared to verify the performance and precision of the proposed MTDD algorithm.

基于Mask R-CNN的试管-支架系统Data Matrix码识别方法

在试管-支架自动化系统的输入图像中,Data Matrix(DM)码呈现为多个小目标,图像存在成像模糊、边缘干扰严重等问题,使得传统方法难以达到良好的识别效果。为此,提出一种基于深度学习的Data Matrix码识别方法DeepDMCode,以Mask R-CNN模型为基础,通过内容差异化数据合成和同步自动化标注,实现训练数据的增强,提升模型的学习能力。在模型分割结果的基础上,提出一种旋转校正方法,确保可用标准解码库实现DM码的解码。以分辨率为1600×1200、支架容量为96的数据实验表明,由于该方法在前期码定位阶段最大程度地还原码边界信息,准确度可达0.92(mIoU),完成单张图像中所有DM识别的平均速度为5.2 s,优于YOLO、SegNet、CenterNet等主流工业基准算法。

基于自编码器的PCA-SOM公共服务资源配置评价与选址优化决策方法

当前城市规划和公共服务资源配置存在分配不均和选址效率低下的问题。将公共服务资源的电力消耗数据与其资源数量、区域人口数量相结合,基于主成分分析(principal component analysis,PCA)评估各区域公共服务资源的配置状况,并以兰州市为案例,运用自组织映射(self-organizingmapping,SOM)算法进行教育资源的优化选址。研究发现,电力数据能有效指示资源配置的不足,并为优化分配提供精确的指导。尤其在兰州市,SOM算法的应用不仅提高了教育资源选址的效率,还促进了资源的公平分配。不仅为甘肃省提供了公共服务资源配置的科学决策依据,也为其他地区在相似领域的研究提供了参考。

FCF-LDH/BiVO_(4)with synergistic effect of physical enrichment and chemical adsorption for efficient reduction of nitrate

Photoelectrochemical NO_(3)^(-)reduction(PEC NITRR)not only provides a promising solution for promoting the global nitrogen cycle,but also converts NO_(3)^(-)to the important chemicals(NH_(3)).However,it is still a great challenge to prepare catalysts with excellent NO_(3)^(-)adsorption/activation capacity to achieve high NITRR.Herein,we designed a novel Fe^(2+)~Cu^(2+)Fe^(3+)LDH/BiVO_(4)(FCF-LDH/BVO)catalyst with synergistic effect of chemical adsorption and physical enrichment.Fe^(2+)in FCF-LDH/BVO provides the rich Lewis acid sites for the adsorption of NO_(3)^(-),and the appropriate layer spacing of FCF-LDH further promotes the physical enrichment of NO_(3)^(-)in its interior,thus realizing the effective contact between NO_(3)^(-)and active sites(Fe^(2+)).FCF-LDH/BVO showed excellent NH_(3)production performance(FE_(NH_(3))=66.1%,r_(NH_(3))=13.8μg h^(-1)cm^(-2))and selectivity(FE_(NO_(2)^(-))=2.5%,r_(NO_(2)^(-))=4.9μg h^(-1)cm^(-2))in 0.5 mol L^(-1)Na_(2)SO_(4)electrolyte.In addition,FCF-LDH/BVO maintains the desirable PEC stability for six cycle experiments,showing great potential for practical application.The^(14)NO_(3)^(-)and^(15)NO_(3)^(-)isotope test provides strong evidence for further verification of the origin of N in the generated NH_(3).This LDH catalyst has a great potential in PEC removal of NO_(3)^(-)from groundwater.

基于大数据BI技术的智慧工地数据可视化平台的设计与研究--以某大型建筑工程集团为例

大数据BI(Business Intelligence)技术在数据挖掘、数据分析、数据可视化等方面的功能实现较成熟,已广泛应用在制造业、零售业等行业。将大数据BI技术融入智慧工地,建立数据可视化平台,可以解决智慧工地存在的局部“数据孤岛”等问题,让智慧工地的海量数据得到最大价值体现。文章以某大型市政特级资质建筑工程集团为例,采用基于Hadoop+Spark的技术架构,以在建的大型地铁市政工程项目为实践,主要论述数据可视化平台架构选型、建立数据仓库、数据ETL、数据可视、Spark引擎框架与MapReduce在数据处理性能方面的对比等。构建基于大数据BI技术的智慧工地可视化数据平台,能有效推进智慧工地的开展,提升对工程项目在质量安全、绿色施工、成本管控等方面的管理。

基于混合深度学习的蛋白质-多肽结合位点识别研究

蛋白质和多肽间的相互作用机制非常重要,且使用计算方法预测蛋白质-多肽相互作用位点能快速定位并有效降低研发成本。然而,现有模型预测两者结合位点的准确率不高,并且难以处理数据不平衡问题。基于此,本文提出了一个基于混合深度学习策略的预测方法——ResPep。在数据集处理层面上,用K-means聚类算法对数据集中多数类样本下采样以平衡数据样本;在算法处理层面上,用残差网络、一维卷积神经网络和多头注意力网络来建立轻量级的混合深度学习模型,同时模型学习融入代价敏感性。结果表明,与多个现有方法相比,ResPep在公共测试数据集TS125上拥有更好的泛化性能。

Deep-sea Pollen Record during 3.0-2.0 Ma B.P. from ODP Site 1143 and Its Response to Global Climate Changes

In order to study vegetation evolution and environmental changes around 2.5 Ma B.P., a total of 146 pollen samples with an average time resolution of 7 000 years were analyzed in the deep-sea record at the depth of 135 - 95 m （in composition depth） from ODP Site 1143 （9° 22＇ N, 113° 17＇ E） in the southern South China Sea. The results show that the pollen influx has a distinct change. During 2.6 - 2.0 Ma B.P., the average value of pollen influx increased evidently compared with that of 3.0 - 2.6 Ma B.P. It shows that the sea level of SCS dropped dramatically around 2.6 Ma B.P., corresponding to the formation of the Northern Hemisphere ice-sheets and the enhancement of the East Asian Monsoon. The pollen influx variations reflect the glacial-interglacial cycles corresponding with the deep-sea oxygen isotope curve and indicate that the sea level of SCS rose and dropped many times after 2.6 Ma B.P. The spectrum analysis results of pollen influx show that there are cycles at 0.1Ma （eccentricity） and 46.9 ka （obliquity） during 3.0 - 2.0 Ma B.P.

A method to obtain the wind field characteristics of super-large aperture radio telescope site based on single-point wind tower and numerical simulation

The influence of wind on the pointing accuracy of large aperture radio telescopes is becoming increasingly serious, especially at high observing frequency. Obtaining the wind field characteristics efficiently is very important to reduce the wind disturbance on antenna structure. In this paper, an error evaluation of numerical simulation method is established based on the measured data of single point wind tower, and the wind field characteristics are obtained from the evaluated numerical simulation results combined with the measured data for the 110 m aperture Qi Tai radio Telescope(QTT) site. According to the simulation results, compared with the measured data, the root mean square error(RMSE) of wind speed is less than 1 m s^-1, and the minimum wind speed RMSE is 0.2 m s^-1. An analysis of the wind field characteristics of the QTT site suggests that the active wind resistance design of the antenna periphery should focus on the SSW(south-south-west) direction.

Probabilistic outlier detection for sparse multivariate geotechnical site investigation data using Bayesian learning

Various uncertainties arising during acquisition process of geoscience data may result in anomalous data instances(i.e.,outliers)that do not conform with the expected pattern of regular data instances.With sparse multivariate data obtained from geotechnical site investigation,it is impossible to identify outliers with certainty due to the distortion of statistics of geotechnical parameters caused by outliers and their associated statistical uncertainty resulted from data sparsity.This paper develops a probabilistic outlier detection method for sparse multivariate data obtained from geotechnical site investigation.The proposed approach quantifies the outlying probability of each data instance based on Mahalanobis distance and determines outliers as those data instances with outlying probabilities greater than 0.5.It tackles the distortion issue of statistics estimated from the dataset with outliers by a re-sampling technique and accounts,rationally,for the statistical uncertainty by Bayesian machine learning.Moreover,the proposed approach also suggests an exclusive method to determine outlying components of each outlier.The proposed approach is illustrated and verified using simulated and real-life dataset.It showed that the proposed approach properly identifies outliers among sparse multivariate data and their corresponding outlying components in a probabilistic manner.It can significantly reduce the masking effect(i.e.,missing some actual outliers due to the distortion of statistics by the outliers and statistical uncertainty).It also found that outliers among sparse multivariate data instances affect significantly the construction of multivariate distribution of geotechnical parameters for uncertainty quantification.This emphasizes the necessity of data cleaning process(e.g.,outlier detection)for uncertainty quantification based on geoscience data.

Environmental archaeology on Longshan Culture （4500-4000 aBP） at Yuhuicun Site in Bengbu, Anhui Province

Based on the samples collected from the west wall of the ABYT2004 at Yuhuicun Site in Bengbu, Anhui Province, the multi-environmental substitute indexes such as the grain-size, Rb/Sr, zircon crystal morphology and magnetic susceptibility were analyzed. The age of archaeological strata was determined by AMS^14C dating. According to the results, combined with the information of the ancient human activities and the cultural heritage data obtained from the Longshan cultural archaeological strata, it can be concluded that （1） Before 4500 aBP, the climate was humid and water level was high in the Huaihe River and its tributaries, the drainage basin and its surrounding areas were even flooded, so the site area was submerged and there were no human activities around the site. （2） About 4500 aBP, the climate began to become drier and water level of the Huaihe River and its tributaries began to decline, thus floodplain gradually appeared, Yuhuicun Site and Longshan Culture began to appear. （3） Around 4100 aBP, the climate was humid and rainfall was abundant, which resulted in frequent flood disasters in the whole Huaihe River Basin. （4） After 4100 aBP, the climate gradually transited to be cold and dry, agricultural production was constrained to reduce the food source, Yuhuicun Site was almost abandoned. （5） The environmental information in sedimentary strata and historical records based on ancient books agree with each other. In addition, Yuhuicun Site was related to Dayu Zhishui （Yu the Great in taming the floods） in ancient books.

mLysPTMpred: Multiple Lysine PTM Site Prediction Using Combination of SVM with Resolving Data Imbalance Issue

Post-translational modification (PTM) increases the functional diversity of proteins by introducing new functional groups to the side chain of amino acid of a protein. Among all amino acid residues, the side chain of lysine (K) can undergo many types of PTM, called K-PTM, such as “acetylation”, “crotonylation”, “methylation” and “succinylation” and also responsible for occurring multiple PTM in the same lysine of a protein which leads to the requirement of multi-label PTM site identification. However, most of the existing computational methods have been established to predict various single-label PTM sites and a very few have been developed to solve multi-label issue which needs further improvement. Here, we have developed a computational tool termed mLysPTMpred to predict multi-label lysine PTM sites by 1) incorporating the sequence-coupled information into the general pseudo amino acid composition, 2) balancing the effect of skewed training dataset by Different Error Cost method, and 3) constructing a multi-label predictor using a combination of support vector machine (SVM). This predictor achieved 83.73% accuracy in predicting the multi-label PTM site of K-PTM types. Moreover, all the experimental results along with accuracy outperformed than the existing predictor iPTM-mLys. A user-friendly web server of mLysPTMpred is available at http://research.ru.ac.bd/mLysPTMpred/.

Real-time crash prediction on freeways using data mining and emerging techniques

Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.

Quantifying urbanization levels on the Tibetan Plateau with high-resolution nighttime light data

The Tibetan Plateau(TP)is undergoing rapid urbanization.To improve urban sustainability and construct eco-logical security barriers,it is essential to quantify the spatial patterns of urbanization level on the TP,but the existing studies on the topic have been limited by the lack of socioeconomic data.This study aims to quantify the urbanization level on the TP in 2018 with Luojia1-01(LJ1-01)high-resolution nighttime light(NTL)data.Specifically,the compounded night light index is used to quantify spatial patterns of urbanization level at mul-tiple scales.The results showed that the TP had a low overall urbanization level with a large internal difference.The urbanization level in the northeast,southeast and south of the TP was relatively high,forming three hotspots centered in Xining City,Lhasa City and Shangri-La City,while the urbanization level in the central and western regions was relatively low.The analysis of influencing factors,based on the random forest model,showed that transportation and topography were the main factors affecting the TP’s spatial patterns of urbanization level.The comparison analysis with socioeconomic statistics and traditional NTL data showed that LJ1-01 NTL data can be used to more effectively quantify the urbanization level since it is more advantageous for reflecting the spatial extent of urban land and describing the spatial structure of socioeconomic activities within urban areas.These advantages are attributed to the high spatial resolution of the data,appropriate imaging time and unaf-fected by saturation phenomena.Thus,the proposed LJ1-01 NTL-based urbanization level measurement method has the potential for wide applications around the world,especially in less-developed regions lacking statistical data.Using this method,we refined the measurement of the TP’s urbanization level in 2018 for multiple scales including the region,basin,prefecture and county levels,which provides basic information for the further urban sustainability research on the TP.

High-speed broadband data acquisition system based on FPGA

A field-programmable gate array(FPGA)based high-speed broadband data acquisition system is designed.The system has a dual channel simultaneous acquisition function.The maximum sampling rate is 500 MSa/s and bandwidth is200 MHz,which solves the large bandwidth,high-speed signal acquisition and processing problems.At present,the data acquisition system is successfully used in broadband receiver test systems.

An Approach of Tropospheric Correction for VLBI Phase-Referencing using GPS Data

The dominant source of error in VLBI phase-referencing is the troposphere at observing frequencies above 5 GHz. We compare the tropospheric zenith delays derived from VLBI and GPS data at VLBA stations collocated with GPS antennas. The systematic biases and standard deviations both are at the level of sub-centimeter. Based on this agreement, we suggest a new method of tropospheric correction in phase-referencing using combined VLBI and GPS data.

A Comparative Study of Acute Hemodynamic Effects of Multi -site Cardiac Pacing in patients with cardiac function NYHA class ⅠtoⅡ without bundle branch block

Objective To compare the acute hemodynamic effects of five different pacing modes in patients with cardiac function NYHA class Ⅰ to Ⅱ without bundle branch block (BBB). Methods This study included 12 patients (SSS 7, Ⅲ°AVB 5) undergoing pacemaker implantation. Right ventricular apex (RVA), right ventricular outflow tract (RVOT), right ventricular bifocal (RV-Bi), left ventricular base (LVB) and bi -ventricular (Bi-Ⅴ) pacing at 60 -80 ppm were done in VVI mode prior to implantation of DDD pacemaker. The cardiac index (CI), mean pulmonary artery pressure (mPAP) and pulmonary capillary wedge pressure (PCWP) were measured with Swan - Ganz thermodilution catheter after 5 minutes of each pacing mode. Results (1) Comparing to pacing at RVA (CI: 2. 41± 0. 38 L/min per m2, PCWP: 16. 7 ±3.3 mmHg), the CI increased and the PCWP decreased significantly in pacing at RVOT(CI: 2. 63 ± 0.46, PCWP: 13. 8±2. 3), LVB(CI: 2. 78±0.52, PCWP: 14. 4±3.1), RV-Bi(CI: 2. 83±0.57, PCWP: 12. 8± 2. 5) and Bi -Ⅴ pacing (CI: 2. 94± 0.60, PCWP: 12. 7±2. 5), P < 0. 01, respectively. (2) The CI of RV-Bi and Bi-Ⅴ pacing was higher than that of RVOT and LVB pacing, the PCWP was lower, P < 0. 05, respectively. (3) There was no significant difference between RV - Bi pacing and Bi-Ⅴ pacing in CI and PCWP. Conclusion There is no significant difference between RV - Bi pacing and Bi -V pacing in the acute hemodynamic effects; however,dual - site pacing is much better than single site pacing in that aspect for patients with cardiac function NYHA class Ⅰ to Ⅱ without BBB. Among single site pacing, the RVOT and LVB pacing is better than RVA pacing in cardiac function.

A Lightweight Data Aggregation Protocol in Wireless Sensor Networks for the Protection of Ancient Sites

In the application of large-scale ancient site protection, it is necessary to continuously monitor the ambient light, temperature, humidity and so on. However, it is impractical to frequently replace the nodes’ battery in the protected areas. So, the key methods to prolong the network lifetime are to aggregate the collected data and reduce the number of transferring messages. In this paper a Lightweight Data Aggregation Protocol (LDAP) based on the characteristics of the environmental changes in ancient sites is proposed. It has been implemented in the Lab with a dozen of MICAz motes and deployed in the real ancient sites. The result shows that LDAP is effective in reducing the number of transferring packets and satisfies the real application requirements.

Optimal site selection for an optical-astronomical observatory in Pakistan using Multicriteria Decision Analysis

An astronomical observatory is the core component of any astronomical research facility that connects astronomers with their lab: the Cosmos. The research quality of an astronomical facility is rooted in the precision of data, collected by its observatory. For optimal performance, an observatory is sited while considering certain astronomical, environmental, geological and social parameters. This study aims to identify the potential sites in Pakistan for locating an optical-astronomical observatory using the Multicriteria Decision Analysis(MCDA) technique. The study uses the Analytic Hierarchy Process(AHP) for deriving the influence weights of nine evaluation criteria: Photometric Night Fraction;Night-time Sky Brightness;Sky Transparency;Aerosol Concentration;Altitude;Terrain Slope;Accessibility;Seismic Vulnerability;and Landuse/Land Cover. On the basis of experts’ opinions and previous studies, the evaluation criteria have been ordered in two possible preference sequences for identifying their influence weights with respect to each other for taking part in MCDA. Consequently, the process of MCDA identified certain areas with respect to each preference sequence, whereas some areas were found to be suitable according to both preference sequences. The study synchronizes the required eclectic data into an evaluation matrix that augments the process of astronomical site selection. In the future, this study will be useful for astronomical societies and for furthering astronomical research in the country.