mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Estimating grassland LAI using the Random Forests approach and Landsat imagery in the meadow steppe of Hulunber, China

Leaf area index (LAI) is a key parameter for describing vegetation structures and is closely associated with vegetative photosynthesis and energy balance. The accurate retrieval of LAI is important when modeling biophysical processes of vegetation and the productivity of earth systems. The Random Forests (RF) method aggregates an ensemble of decision trees to improve the prediction accuracy and demonstrates a more robust capacity than other regression methods. This study evaluated the RF method for predicting grassland LAI using ground measurements and remote sensing data. Parameter optimization and variable reduction were conducted before model prediction. Two variable reduction methods were examined: the Variable Importance Value method and the principal component analysis (PCA) method. Finally, the sensitivity of RF to highly correlated variables was tested. The results showed that the RF parameters have a small effect on the performance of RF, and a satisfactory prediction was acquired with a root mean square error (RMSE) of 0.1956. The two variable reduction methods for RF prediction produced different results; variable reduction based on the Variable Importance Value method achieved nearly the same prediction accuracy with no reduced prediction, whereas variable reduction using the PCA method had an obviously degraded result that may have been caused by the loss of subtle variations and the fusion of noise information. After removing highly correlated variables, the relative variable importance remained steady, and the use of variables selected based on the best-performing vegetation indices performed better than the variables with all vegetation indices or those selected based on the most important one. The results in this study demonstrate the practical and powerful ability of the RF method in predicting grassland LAI, which can also be applied to the estimation of other vegetation traits as an alternative to conventional empirical regression models and the selection of relevant variables used in ecological models.
Assessment of the cropland classifications in four global land cover datasets: A case study of Shaanxi Province, China

Accurate and reliable cropland surface information is of vital importance for agricultural planning and food security monitoring. As several global land cover datasets have been independently released, an inter-comparison of these data products on the classification of cropland is highly needed. This paper presents an assessment of cropland classifications in four global land cover datasets, i.e., moderate resolution imaging spectrometer (MODIS) land cover product, global land cover map of 2009 (GlobCover2009), finer resolution observation and monitoring of global cropland (FROM-GC) and 30-m global land cover dataset (GlobeLand30). The temporal coverage of these four datasets are circa 2010. One of the typical agricultural regions of China, Shaanxi Province, was selected as the study area. The assessment proceeded from three aspects: accuracy, spatial agreement and absolute area. In accuracy assessment, 506 validation samples, which consist of 168 cropland samples and 338 non-cropland ones, were automatically and systematically selected, and manually interpreted by referencing high-resolution images dated from 2009 to 2011 on Google Earth. The results show that the overall accuracy(OA) of four datasets ranges from 61.26 to 80.63%. GlobeLand30 dataset, with the highest accuracy, is the most accurate dataset for cropland classification. The cropland spatial agreement (mainly located in the plain ecotope of Shaanxi) and the non-cropland spatial agreement (sparsely distributed in the south and middle of Shaanxi) of the four datasets only makes up 33.96% of the whole province. FROM-GC and GlobeLand30, obtaining the highest spatial agreement index of 62.40%, have the highest degree of spatial consistency. In terms of the absolute area, MODIS underestimates the cropland area, while GlobCover2009 significantly overestimates it. These findings are of value in revealing to which extent and on which aspect that these global land cover datasets may agree with each other at small scale on each ecotope region. The approaches taken in this study could be used to derive a fused cropland classification dataset.
The relationship between international crude oil prices and China's refined oil prices based on a structural VAR model

With the frequent fluctuations of international crude oil prices and China's increasing dependence on foreign oil in recent years, the volatility of international oil prices has significantly influenced China domestic refined oil price. This paper aims to investigate the transmission and feedback mechanism between international crude oil prices and China's refined oil prices for the time span from January 2011 to November 2015 by using the Granger causality test, vector autoregression model, impulse response function and variance decomposition methods. It is demonstrated that variation of international crude oil prices can cause China domestic refined oil price to change with a weak feedback effect. Moreover, international crude oil prices and China domestic refined oil prices are affected by their lag terms in positive and negative directions in different degrees. Besides, an international crude oil price shock has a significant positive impact on domestic refined oil prices while the impulse response of the international crude oil price variable to the domestic refined oil price shock is negatively insignificant. Furthermore, international crude oil prices and domestic refined oil prices have strong historical inheritance. According to the variance decomposition analysis, the international crude oil price is significantly affected by its own disturbance influence, and a domestic refined oil price shock has a slight impact on international crude oil price changes. The domestic refined oil price variance is mainly caused by international crude oil price disturbance, while the domestic refined oil price is slightly affected by its own disturbance. Generally, domestic refined oil prices do not immediately respond to an international crude oil price change, that is, there is a time lag.
Modeling flow in naturally fractured reservoirs: effect of fracture aperture distribution on dominant sub-network for flow

Fracture network connectivity and aperture (or conductivity) distribution are two crucial features controlling flow behavior of naturally fractured reservoirs. The effect of connectivity on flow properties is well documented. In this paper, however, we focus here on the influence of fracture aperture distribution. We model a two-dimensional fractured reservoir in which the matrix is impermeable and the fractures are well connected. The fractures obey a power-law length distribution, as observed in natural fracture networks. For the aperture distribution, since the information from subsurface fracture networks is limited, we test a number of cases: log-normal distributions (from narrow to broad), power-law distributions (from narrow to broad), and one case where the aperture is proportional to the fracture length. We find that even a well-connected fracture network can behave like a much sparser network when the aperture distribution is broad enough (α < 2 for power-law aperture distributions and σ > 0.4 for log-normal aperture distributions). Specifically, most fractures can be eliminated leaving the remaining dominant sub-network with 90% of the permeability of the original fracture network. We determine how broad the aperture distribution must be to approach this behavior and the dependence of the dominant sub-network on the parameters of the aperture distribution. We also explore whether one can identify the dominant sub-network without doing flow calculations.
Zoeppritz-based AVO inversion using an improved Markov chain Monte Carlo method

The conventional Markov chain Monte Carlo (MCMC) method is limited to the selected shape and size of proposal distribution and is not easy to start when the initial proposal distribution is far away from the target distribution. To overcome these drawbacks of the conventional MCMC method, two useful improvements in MCMC method, adaptive Metropolis (AM) algorithm and delayed rejection (DR) algorithm, are attempted to be combined. The AM algorithm aims at adapting the proposal distribution by using the generated estimators, and the DR algorithm aims at enhancing the efficiency of the improved MCMC method. Based on the improved MCMC method, a Bayesian amplitude versus offset (AVO) inversion method on the basis of the exact Zoeppritz equation has been developed, with which the P- and S-wave velocities and the density can be obtained directly, and the uncertainty of AVO inversion results has been estimated as well. The study based on the logging data and the seismic data demonstrates the feasibility and robustness of the method and shows that all three parameters are well retrieved. So the exact Zoeppritz-based nonlinear inversion method by using the improved MCMC is not only suitable for reservoirs with strong-contrast interfaces and long-offset ranges but also it is more stable, accurate and antinoise.
Beat note analysis and spectral modulation of terahertz quantum cascade lasers with radio frequency injection

We demonstrate the electrical beat note analysis and radio frequency (RF) injection locking of a continuous wave (cw) terahertz quantum cascade laser (QCL) emitting around 3 THz (~100 μm). In free running the beat note frequency of the QCL shows a shift of ~180 MHz with increasing drive current. The beat note, modulation response, injection pulling, and terahertz emission spectral characteristics in the different current regimes I, II, and III are investigated. The results show that in the current regime I close to the laser threshold we obtain a narrower beat note and flat response to the RF modulation at the cavity round trip frequency. The pulling effect and spectral modulation measurements verify that in the current regime I the RF injection locking is more efficient and a robust tool to modulate the mode number and mode frequency of terahertz QCLs.
2016年淋巴瘤研究新进展

2016年淋巴瘤领域的新进展,主要是复发难治淋巴瘤的新方案或新药尝试的临床研究,结果逐渐出炉,近2年备受肿瘤领域青睐的细胞治疗也在淋巴瘤治疗中结果不俗。
儿童恶性血液病中心静脉导管相关血流感染研究进展

随着医学的发展, 中心静脉导管(centralvenous catheter,CVC)被广泛应用于危重患者抢救、慢性疾病的长期静脉营养、血液透析及肿瘤化疗等临床治疗。在儿童恶性血液病(包括白血病和恶性肿瘤)中应用不仅能保证化疗及营养支持治疗的顺利进行,且大大降低了化学性静脉炎的发生率。然而,随之而来日益增多的是导管相关并发症,如感染、血栓、堵塞等,其中最常见的是CVC相关血流感染(catheter-related bloodstream infection,CRBSI)。由于自身免疫系统紊乱、化疗以及化疗后骨髓抑制和激素等免疫抑制剂的使用等,使儿童恶性血液病患者更易发生CRBSI,且常缺乏局部或全身感染症状,显著增加住院费用、延长住院时间。Celebi等报道儿童恶性血液病CRBSI发生率约7.4例次/1 000置管天,病死率约为9.6%。2014年美国阿肯色大学、宾夕法尼亚大学分别报道儿童CRBSI约增加住院费用及住院天数为55 646美元和19 d及70 000美元和21 d。儿童恶性血液病具有较高的CRBSI感染率和病死率,并明显增加了治疗相关费用和住院时间。因此,加强对CRBSI的认识,早期预防和干预,有很重要的临床意义。本文就CRBSI的病原学、危险因素,及是否移除导管等方面的近期研究综述如下。
中性粒细胞缺乏合并麻疹孪生球菌血流感染1例

中性粒细胞缺乏并发感染是化疗后常见并发症,若严重感染不能及时被控制,会延长中性粒细胞恢复正常的时间,诱使耐药,合并真菌、病毒感染的概率增加,危及生命,故应选择起效迅速的抗菌药物。与替考拉宁不同,万古霉素的蛋白结合率低,能够迅速达到有效血药浓度。本例患儿在换用万古霉素后体温迅速降至正常,主要考虑与不同药物的药动学有关,亦不排除为前期使用替考拉宁3 d后开始起效。对血流感染、需要迅速控制感染者,万古霉素疗效可能更优于替考拉宁。中性粒细胞缺乏后出现发热、抗生素控制不理想、多次血培养阴性的情况下,应考虑罕见细菌感染,这需要引起广大医师的高度重视。
目标捕获测序技术确诊新生儿阿姆斯特丹侏儒症一例

本例患儿为10日龄,有阿姆斯特丹侏儒症的临床表现,但不能明确其疾病亚型。本研究利用目标捕获测序不仅明确了对阿姆斯特丹侏儒症的基因诊断及分型,而且发现了该患儿存在的NIPBL基因c.7150C>T杂合突变。目标捕获测序技术根据反应信号实时阅读,可检测高达400万条序列,读取1G~14G碱基数,根据特定位点的变异,通过Sanger测序验证,进一步确保突变检测的准确性,不仅可以明确不同类型阿姆斯特丹侏儒症的基因诊断,还利于发现新的位点突变,丰富本病的遗传数据库。
先天性心脏病胎儿和新生儿大脑皮质发育的影像学研究进展

近年来,对CHD胎儿和新生儿脑皮质发育的研究认为CHD患儿存在脑皮质发育异常,表现为脑皮质体积减少、脑沟出现延迟、皮质折叠程度下降和脑岛闭合不全,并且脑皮质发育异常在宫内即已出现,并与CHD结构异常程度和类型有关。而目前对CHD患儿的研究主要是应用MRI技术对CHD新生儿进行颅脑发育观察,对产前CHD胎儿的脑皮质发育研究极少,此外,应用超声检查技术对CHD患儿脑皮质发育的研究鲜见报道。超声检查具有无创、方便、经济、可实时成像等优点,近20年来随着超声仪器性能的提升和人们对胎儿生理及畸形的发生、发展的超声特点进行深入研究,产前超声在降低围产儿死亡率和出生缺陷率方面起到了重要的作用。超声有可能成为宫内实时追踪观察CHD胎儿脑沟回发育的重要影像学方法,这对确定CHD胎儿是否合并脑皮质发育异常具有重大意义。
改良的房水流出通路重建术手术操作规范

对于曾经接受过滤过手术、因滤过通道瘢痕化导致手术失败的患者,其生理学房水流出通路仍然存在再次疏通的可能。选择房水流出通路重建术(reconstruction of aqueous outflow drainage,RAOD),可以获得理想的降眼压效果AOD手术成功,必须使缝线在Schlemm管内360度穿通,且实现环形向心性的张力,从而牵拉Schlemm管内壁及小梁网,产生一系列的改变。因此,对于曾经有滤过手术史患者,如果手术未伤及到Schlemm管,Schlemm管仍然是一个360°贯通的管道,按常规房水流出通路重建术操作规范即可完成手术。如果既往手术已经伤及到Schlemm管,Schlemm管存在瘢痕区域,则按如下规范操作。
Production of neutron-rich exotic nuclei in projectilefragmentation at Fermi energies

Isotopic fragment yields of projectile fragmentation in peripheral collisions of 86Kr on 124;112Sn and the mean neutron-to-proton ratios of the fragments are calculated, theoretically, within the ensemble approach of statistical multifragmentation model. Obtained data are compared to the experimental cross-section measurements for the projectile-like fragmentation in the reaction of 25 MeV/nucleon ~(86)Kr+~(124;112)Sn at Texas A&M University. We show the enhancement in the production of neutronrich isotopes close to the projectile as observed in the experiments. We also demonstrate the universality of the limitation of the excitation energy induced in the projectile residues.
从循证视角探析大数据研究--痛风与高尿酸血症患者多中心网络注册及随访研究

2016年,Ann Intern Med发表了一篇论述大数据(big data)与循证医学(evidence-based medicine,EBM)关系的文章,该文的作者是加州大学旧金山分校的Ida Sim教授,也是最早倡导将循证医学与大数据结合进而为决策提供最佳依据的学者之一。在这篇文章中,Ida Sim教授提出,大数据作为一种全新的产生证据的方式,近年来发展迅速,大数据分析在医疗实践中的应用也越来越广泛。各医疗机构存储的电子健康档案(electronic health record,EHR)数据急剧增多,加之各种移动传感器(如穿戴设备、远程监测设备)收集的实时健康数据(如心率、血压、血糖等信息),以及为获得患者的社会背景开辟了新途径的社交网络和媒体数据,正在成为临床诊疗决策的新来源。如欲了解公众对人类乳头瘤病毒疫苗接种态度,传统做法是通过问卷调查,样本量从几十至上千不等。但在大数据时代,可以通过对1.3亿英语博客的发布者进行分析,从而了解其对该疫苗接种的积极或消极态度。此外,另一项基于210万条微博的分类算法可识别患有抑郁症的微博用户,其准确度为70%,阳性预测值为74%。然而,大数据提供的证据存在一个显著的局限性,即根据某种算法,仅从数据本身来挖掘分析出结果,其真伪很难识别,存在的偏倚也无从得知。循证医学则重视一开始就通过对试验数据进行科学的设计、准确的测量和严格的实施,从而最大程度降低偏倚的影响。现以国家风湿病数据中心(CRDC)的痛风数据为例,探索从循证角度如何提高医学大数据的质量,减少和降低偏倚风险,为临床决策提供最佳依据。
一期翻修术治疗全膝关节置换术后假体周围感染的中长期随访结果

全膝关节置换术(total knee arthroplasty,TKA)后假体周围感染(prosthetic joint infection,PJI)虽然临床上较少见(发生率1%~2%),但对于患者来说却是灾难性的并发症,是导致TKA后失败的最常见原因之一。目前临床上多通过二期翻修术治疗TKA术后慢性PJI,文献报道其感染清除率为82%~92%。但该术式耗时长,费用高,在两期手术间患者膝关节功能受限,且可能增加患者的并发症发生率和病死率。相比之下,一期翻修术在耗时、费用及膝关节功能重建方面较二期翻修术具有优势。因此,我们回顾性研究了我院收治的7例随访6年以上的一期翻修术患者的临床资料,旨在了解一期翻修术感染清除率和中长期随访膝关节功能评分,以为临床提供参考。
Antidepressant Effects of Electroconvulsive Therapy Unrelated to the Brain's Functional Network Connectivity alterations at an Individual Level

Background: Electroconvulsive therapy (ECT) can alleviate the symptoms of treatment-resistant depression (TRD). Functional network connectivity (FNC) is a newly developed method to investigate the brain's functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods: This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis (GIG-ICA) was used to compute subject-specific functional networks (FNs). Grassmann manifold and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks' connectivity patterns (FCP). Pearson's correlation analysis was used to calculate the correlations between the FCP and ECT response. Results: A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ± 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT (the Hamilton scores reduction rate was more than 50%), response rate 51%. 8 FNs (anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network) were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions: The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT's effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging.
Current Clinical Management Status of Pulmonary Embolism in China

Pulmonary embolism (PE) is a potentially life-threatening disease with high morbidity and mortality all over the world. PE and deep vein thrombosis (DVT), as two different forms of venous thromboembolism (VTE) on patients, cannot be separated apart in the management. After years of efforts, the management of PE has been comprehensively promoted in China. Medical authorities and staff have gained more awareness of the disease, standardized diagnosis and treatment has been extended, and varieties of clinical and basic researches have been conducted.
A Review of the Development of Properties and Structures Based on Konjac Glucomannan as Functional Materials

In recent years, konjac glucomannan (KGM) has gained considerable attention due to its non-toxic, harmless, excellent biocompatibility, biodegradability, good water imbibition as well as gel properties. KGM and its derivatives have been widely used in food science, chemical, pharmaceutical, and material areas. In this review, we will focus on the most recent advances in the structures and properties of KGM. We will first describe the influence of different modification methods on the structures and properties of KGM. Then we will review the results obtained with KGM as functional materials in different studies in the fields of hydrogels, aerogels, nanoparticles, membrane materials, microspheres and microcapsule to provide theoretical basis for the further study.
Synthesis, Crystal Structure and Thermal Decomposition of a New Energetic Dipotassium 3,3'-Dinitro-5,5'-bis-1,2,4-triazole-1,1'-diolate

A new energetic dipotassium 3,3' -dinitro-5,5'-bis-1,2,4-triazole-1,1' -diolate [K2(DNOBT)] was synthesized, and structurally characterized by elemental analysis, IR spectra, ~(13)C NMR and single-ciystal X-ray diffraction. K_2(DNOBT).2H_2O crystallizes in monoclinic system, space group P2_1/n with a = 6.0446(10), b = 15.999(3), c = 6.4169(11) A, β = 99.421(2)°,V = 612.21(18) A~3,Z = 4, D_c = 2.009 g·cm~(-3),F(000) = 372,μ = 0.838 mm~(-1), S = 1.012,the final R = 0.0248 and wR(I > 2σ(I)) = 0.0604. Thermal decomposition of the title compound was studied by using DSC and TG-DTG, and there is primarily one exothermic decomposition process at 371.5 ℃.
Spatiotemporal variation of dissolved carbohydrates and amino acids in Jiaozhou Bay, China

Surface seawater samples were collected from Jiaozhou Bay, China, during six cruises (March-May 2010, September-November 2010) to study the distribution of dissolved organic matter including dissolved organic carbon (DOC), total dissolved carbohydrates, namely monosaccharides (MCHO) and polysaccharides (PCHO) and total hydrolysable amino acids. These included dissolved free amino acids (DFAA) and combined amino acids (DCAA). The goal was to investigate possible relationships between these dissolved organic compounds and environmental parameters. During spring, the concentrations of MCHO and PCHO were 9.6 (2.8-22.6) and 11.0 (2.9-42.5) μmol C/L, respectively. In autumn, MCHO and PCHO were 9.1 (2.6-27.0) and 10.8 (2.4-25.6) μmol C/L, respectively. The spring concentrations of DFAA and DCAA were 1.7 (1.1-4.1) and 7.6 (1.1-31.0) μmol C/L, respectively, while in autumn, DFAA and DCAA were 2.3 (1.1-8.0) and 3.3 (0.6-7.2) μmol C/L, respectively. Among these compounds, the concentrations of PCHO were the highest, accounting for nearly a quarter of the DOC, followed by MCHO, DCAA and DFAA. The concentrations of the organic compounds exhibited a decreasing trend from the coastal to the central regions of the bay. A negative correlation between concentrations of DOC and salinity in each cruise suggested that riverine inputs around the bay have an important impact on the distribution of DOC in the surface water. A significant positive correlation was found between DOC and total bacteria count in spring and autumn, suggesting bacteria play an important role in the marine carbon cycle.
Determining oxygen consumption rate and asphyxiation point in Chanodichthys mongolicus using an improved respirometer chamber

Knowledge of oxygen consumption rates and asphyxiation points in fish is important to determine appropriate stocking and water quality management in aquaculture. The oxygen consumption rate and asphyxiation point in Chanodichthys mongolicus were detected under laboratory conditions using an improved respirometer chamber. The results revealed that more accurate estimates can be obtained by adjusting the volume of the respirometer chamber, which may avoid system errors caused by either repeatedly adjusting fish density or selecting different equipment specifications. The oxygen consumption rate and asphyxiation point of C. mongolicus increased with increasing water temperature and decreasing fish size. Changes in the C. mongolicus oxygen consumption rate were divided into three stages at water temperatures of 11-33℃: (1) a low temperature oxygen consumption rate stage when water temperature was 11-19℃, (2) the optimum temperature oxygen consumption rate stage when water temperature was 19-23℃, and (3) a high temperature oxygen consumption rate stage when water temperature was >27℃. The temperature quotients (Q_(10)) obtained suggested that C. mongolicus preferred a temperature range of 19-23℃. At 19℃, C. mongolicus exhibited higher oxygen consumption rates during the day when the maximum values were observed at 10:00 and 14:00 than at night when the minimum occurred at 02:00.
升主动脉瘤合并自发性冠状动脉夹层一例

总之,升主动脉瘤合并SCAD十分罕见,二者的发病机制尚不清楚,治疗上也缺乏指导性建议。因此,对于中青年女性(尤其是妊娠和围产期)的急性心肌梗死或心绞痛,应提高警惕,要考虑到冠状动脉夹层的可能,并要排除其他大血管病变。其治疗策略应个体化,患者出院后应密切随访。
Distribution changes of woody plants in Western Iran as monitored by remote sensing and geographical information system: a case study of Zagros forest

The status of woody plants in dry-land systems is a fundamental determinant of key ecosystem processes. Monitoring of this status plays an important role in understanding the dynamics of woody plants in arid and semi-arid ecosystems. The present study determined the dynamism of the Zagros forests in Iran using Remote Sensing and Geographic Information System techniques and statistical science. The results show that the density of trees varied from 10 to 53 % according to the physiographic and climatic conditions of semi-arid regions. The best and lowest correlation between vegetation indices and forest density were obtained for the global environmental monitoring index (GEMI; R2 = 0.94) and soil adjust vegetation index (R2 = 0.81), respectively. GEMI is used to monitor land use changes over a 10-year period. Results show that 2720 ha2 of forest have been destroyed by human interference and tillage on steep slopes during this period which also resulted in the loss of the fertile soil layer. GEMI determined the areas with a biomass of trees and could normally separate border regions with low biomass density of trees from regions without canopy cover. The results revealed that assessment of forest and vegetation cover in arid and semi-arid arduous forest regions using satellite digital numbers and ordinary sampling is subject to uncertainty. A stratified grouping procedure should be established to increase the accuracy of assessment.