Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Characteristics of the Active Layers on Fildes Peninsula of King George Island, Antarctica

From the data of the pitting, geoelectrical prospecting, temperature measurement, salt content analysis and detection by layering frost-heaving instruments, the authors discuss firstly the structural features of sediments in the active layers in this region, and proves the presence of the bowl-shaped frost table in the stone-circles area, and then analyse the regularities of temperature distribution in the active layer, effect of salt content on electric resistivity, thaw-settlement and frost-heaving, and their control on periglacial landform development. It suggests that the five layers should exist in the subsurface structure, namely, active layer, frost sand and gravel layer, frost volcanic rock permeated by sea water, frost volcanic rock unpermeated by the sea water, and unfrost ancient continental baement. Finally, the permafrost table and its vertical gradient are deduced

Study on the Effect of Fractional Derivative on the Hyperspectral Data of Soil Organic Matter Content in Arid Region

Discussion on the application of fractional derivative algorithm in monitoring organic matter content in field soil is scarce. This study is aimed at improving the accuracy of soil organic matter (SOM) content estimation in arid region, and the undesirable model precision caused by the missing information associated with the larger discrepancy between conventional integer-order, i.e., first order and second order, derivative, and raw spectral data. We utilized fractional derivative (of zeroth order to second order in 0.2-order interval) processing on the field spectral reflectance (R) of the salinized soil sample from Fukang, Xinjiang, and its square root-transformed (R), log-transformed (lgR), inverse-transformed (1/R), and inverse log-transformed (1/lgR) values. The correlation coefficient of each fractional derivative of transformed value with SOM content was calculated. The simulation showed the derivative reflectance value approximates zero. When increasing from zeroth order to first order, the derivative curve gradually aligns to the first-order curve, and the destination alignment was also seen while increasing from first order to second order. The significance test of 0.05 showed initial increase and later decay of bands in the five spectral transformations as the order increases. For specific bands, the derivative algorithm clearly justifies the correlation between soil spectra and organic matter content, and all of the absolute highest correlation coefficient values were obtained at fractional orders. When compared with integer-order derivative, fractional derivative is significantly better in improving correlation, showing overall superiority. The result supports the application of fractional derivative in the hyperspectral remote monitor of SOM in arid zone, which may in turn realize the timely and accurate SOM monitor in arid zone, and provides the basis for ecological restoration

基于小波分析的土壤碱解氮含量高光谱反演/The Inversion of Soil Alkaline Hydrolysis Nutrient Content with Hyperspectral Reflectance Based on Wavelet Analysis[J]

选取新疆奇台县的134个土壤样本,利用土壤反射率对数的一阶导数光谱分别对四种小波函数进行多层离散分解,采用PLSR方法分别建立了土壤碱解氮含量的反演模型,并对其精度值进行检验.结果表明:小波分解获得的各层低频系数以1～3层较高,而其佘各层则较低.所有函数分解的6层中,均以第2层低频系数建模的精度最高,随着分解层数的增加,其精度值和显著性明显降低.相同尺度下,采用四种小波函数的低频系数构建的反演模型的精度差异较小,而Bior1.3为最优函数；基于Bior1.3分解的ca2低频系数建模的R2达0.977,RMSE仅为7.51 mg·kg-1,且为极显著,为最佳反演模型,经检验,可用以快速、准确估算土壤高光谱碱解氮含量

干旱区农田土壤水分地温变化规律及其相互关系/The variation rule and interrelationship of farmland soil moisture content and ground temperature in arid areas[J]

以干旱区农田灌溉后土壤水分、地温实测数据为基础,研究了其土壤水分、地温各自的变化规律及两者的相互关系.结果表明,各层含水量之间具有高相关性,基本达到了极显著的水平.这与土壤水分灌溉时由上而下的逐渐下渗,以及蒸发时由下而上的逐层上升有密切的关系.各层地温间的相关性大,除地面温度外,其余各层地温间的相关水平为显著或极显著水平,且相邻土层地温间均呈极显著相关.土壤水分及地温剖面垂直变化特征明显,并具有动态性.土壤水分含量大时,两者的垂直变异系数小,反之变异系数大.0～20 cm、地面(0 cm)分别为剖面含水量及地温变异强度的最大层,属中等变异强度.土壤水分及温度之间的负相关性明显.地面温度是预测表层、底层土壤水分的良好指标,利用回归分析法建立的土壤水分与地温间的函数关系可为推测土壤水分提供依据

基于不同模型的土壤有机质含量高光谱反演比较分析/Comparative Analysis of Soil Organic Matter Content Based on Different Hyperspectral Inversion Models[J]

以新疆奇台县为研究区域,选取该县40个土壤样本,采用多元线性逐步回归法和人工神经网络法两种方法分别建立了土壤有机质含量的反演模型,并对模型进行了检验.结果发现:不同模型的精度值各异,其拟合效果从高到低依次为人工神经网络(ANNs)集成模型＞单个人工神经网络(ANNs)模型＞多元逐步回归(MLSR)模型.人工神经网络的线性和非线性逼近能力较强,而其集成模型作为提高反演模型精度的重要手段,相关系数高达0.938,均方根误差和总均方根误差最小,分别仅为2.13和1.404,对土壤有机质含量的预测能力与实测光谱非常接近,分析结果达到了较实用的预测精度,为最优拟合模型

青岛国际旅游市场时空变动特征分析——基于亲景度与竞争态模型/Research on Temporal-spatial Dynamic Changes of Qingdao International Tourist Market——Based on Models of Preference Scale and Competition State[J]

利用地理集中指数、年际集中指数、亲景度、竞争态等研究方法,对1995-2011年青岛国际入境旅游客源国市场的时空变化特征进行了分析.研究表明:①青岛国际客源国的G值平均为55.39,空间分布相对集中,市场结构相对单一;②各客源国年际集中指数差异性大,时间变化不尽相同;③亲景度差异显著,国际游客对青岛的偏爱度各具特点;④青岛客源国的整体市场竞争态的年际差异大,由“瘦狗市场”向“明星市场”演变