农村生活垃圾全自动全组分分类处理技术与应用

为解决农村生活垃圾的处理难题,研究了一种生活垃圾末端全自动全组分分类处置技术,通过生物酶液化方法能将生活垃圾中的有机成分首先分解、分离,再通过湿式自动分选系统,将混合生活垃圾中的金属、塑料、废纸、竹木、纺织物等全部有效分离,经清洗后可直接循环再利用,实现资源化率90%以上。应用该技术实际建成运营一年的垃圾处理厂的数据显示,处理1 t垃圾平均可得到有机肥65 kg、纸浆105 kg、塑料124 kg、垃圾衍生燃料133 kg、砂石135 kg、沼气55kg和金属11kg;需要成本约180元,产值约325元,投资成本较焚烧节约近40%,污水经处理后各项污染因子去除率平均达到88.76%,供系统循环使用。证明该技术能提高垃圾处置效率,经济效益可观,环境友好,有较高推广价值。

基于物质来源及成因的细粒沉积岩分类方案探讨

细粒沉积岩分类对细粒沉积岩系统深入研究至关重要,分类方案应当反映岩石组分物质来源、沉积作用方式,且具有广泛适用性。细粒沉积岩物质来源多样,包括陆源碎屑来源、盆内化学沉淀来源、生物源、火山碎屑来源。不同盆地细粒沉积岩的物质来源存在巨大差异,同一盆地同种矿物也通常具有成因多样性。细粒沉积岩作为一种特殊岩石类型,综合考虑物质来源和沉积作用方式,笔者提出了细粒沉积岩四组分三端元分类方案,根据有机质含量分为高、中、低3大类,以陆源碎屑物质、内源化学沉淀物质、火山碎屑物质进行三端元划分,分为4类:陆源碎屑细粒岩类、化学细粒岩类、火山碎屑细粒岩类、混合细粒岩类;并根据三级命名原则、合并命名原则、复合命名原则,分为11个亚类,岩石名称可根据岩石组分的相对含量进行命名。

煤岩显微组分自动识别技术现状及关键问题分析

回顾煤岩显微组分自动识别的历史及技术现状,探讨了基于反射率和形态学参数的煤岩组分分类方案及其优缺点,对目前煤岩显微组分形态学参数的研究进行分析,并指出图像法煤岩组分自动识别技术难点,重点探讨了煤中壳质组的准确识别、煤中矿物质对有机显微组分识别的干扰、高变质煤组分各向异性对识别的影响、混煤煤岩组分的准确识别、识别模式和识别流程的建立等问题。主要研究结论如下:利用图像处理技术并结合煤岩显微组分的反射率和形态学参数,此为实现煤岩组分自动识别的发展方向。随着数字图像处理技术的发展,对煤岩组分形态参数的表征可以做到定量化和与位置相关联,目前已具备解决煤岩组分自动识别的外部条件。鉴于目前图像法煤岩组分自动测试存在壳质组难以准确识别等问题,建议今后应结合煤岩组分的反射率和形貌特征建立各显微组分合适的识别流程。

珠三角地区居民家庭生活垃圾分类现状分析及思考

本文以珠三角地区某市5年中心城区6个社区的居民生活垃圾的监测数据为依据,分析珠三角地区居民生活垃圾分类的现状。居民对生活垃圾分类的参与度影响因素很多,政府的法律法规的监督和宣传教育是关键。居民家庭生活垃圾分类投放精准率越高,餐厨垃圾的组分占比就越高。家庭生活垃圾分类中的其他垃圾中高值可回收垃圾还有一定占比,这部分需要通过垃圾分类“变废为宝”。

碳酸盐烃源岩研究新进展

从有机组分分类、有机组分双重属性、有机质丰度、类型、成熟度评价标准和方法、生烃机制与生烃模式、有机质原始状态恢复与丰度下限的确定、孢粉相及有机相、成熟度与生烃历史、有机包裹体研究等几个方面系统论述了碳酸盐烃源岩的研究历史、现状、发展趋势及其意义。

绿泥石菱镁石等混合物矿物相分辨

利用矿物中组分特征和XRD对被测物进行粗筛、高频红外碳硫法和XRF快速测试计算主成分元素定量滑石、绿泥石、菱镁石、石英混合物中各相。主要对分类和定量公式进行了研究,由公式特性导出对鉴别的判断依据,并使用之对试样进行了矿物相分类鉴别和定量。方法简便适用。

Histotype-based prognostic classification of gastric cancer

AIM： To test the efficiency of a recently proposed his- totype-based grading system in a consecutive series of gastric cancers.

The use of ＂really＂ in Chinese tertiary-level EFL learners＇ speech： A corpus-based study

The present research reports a comparative study on the use of ＂really＂ by Chinese EFL learners. Taking the perspectives colligation and collocation, the study mainly yields the following findings： （1） Compared with American native speakers, Chinese EFL learners have different preferences for colligations and collocations of ＂really＂; （2） High achievers and low achievers demonstrate a similar pattern of the ranking order of the colligations, but high achievers are closer to the native speakers in the use of ＂really＂ in terms of collocation; low achievers rely more heavily on ＂very＂ to collocate with adjectives than high achievers.

Lie Group Classifications and Non-differentiable Solutions for Time-Fractional Burgers Equation

Lie group method provides an efficient tool to solve nonlinear partial differential equations. This paper suggests Lie group method for fractional partial differential equations. A time-fractional Burgers equation is used as an example to illustrate the effectiveness of the Lie group method and some classes of exact solutions are obtained.

Observation of Intensity-Modulated Radiotherapy with Different Fractionated Doses Used in 58 Cases with Astrocytoma

OBJECTIVE To analyze the therapeutic effects and side effects of intensity-modulated radiotherapy （IMRT） with different fractionated doses in treating astrocytoma.METHODS During a period from October 2001 to December 2006, 58 patients with astrocytoma were treated using IMRT. Based on the World Health Organization （WHO） classification, 32 of the 58 cases were grade-Ⅱ, 20 grade-Ⅲ and 6 grade-IV （glioblastoma multiforme, GBM）. Thirty-two of the 58 patients （3 with grade IV, 11 with grade Ⅲ, and the other 18 with grade II who were over 40 years） were treated with hyperfractionated IMRT （Hyper Fr IMRT）, and the other 26 patients were treated with standard fractionated IMRT （St Fr IMRT）.RESULTS The 1-, 3- and 5-year overall survival （OS） rates were respectively 86%, 52%, and 45%, and the 1-, 3- and 5-year progression-free survival （PFS） rates were respectively 77%, 38%, and 25%. Using an analytical hierarchy process it was shown that concerning the patients with grade II astrocytoma classified based on WHO grading, the therapeutic effect was much better in the group of Hyper Fr IMRT than in the St Fr IMRT group. There was no statistical significance of the differences in the OS and PFS rates between the 2 groups （P = 0.049 and P = 0.006）. The OS and PFS rates of the patients with grade-III astrocytoma were both higher in the group with Hyper Fr IMRT than in the St Fr IMRT group. However, there was no statistical significance of the differences between the 2 groups. Advanced RTOG grade-Ⅲ（radiation therapy oncology group, RTOG） neurotoxicity occurred only in 1 of the cases.CONCLUSION Compared with the St Fr IMRT, the Hyper Fr IMRT may help to prolong the survival of patients with astrocytoma.

Flow Label-Based TPv6 Packet Classification Algorithm with Dimension Reduction Capability

Traditional packet classification for IPv4 involves examining standard 5-tuple of a packet header, source address, destination address, source port, destination port and protocol. With introduction of IPv6 flow label field which entails labeling the packets belonging to the same flow, packet classification can be resolved based on 3 dimensions： flow label, source address and desti- nation address. In this paper, we propose a novel approach for the 3-tuple packet classification based on flow label. Besides, by introducing a conversion engine to covert the source-destination pairs to the compound address prefixes, we put forward an algorithm called Reducing Dimension （RD） with dimension reduction capability, which combines heuristic tree search with usage of buck- ets. And we also provide an improved version of RD, called Improved RD （IRD）, which uses two mechanisms： path compression and priority tag, to optimize the perforrmnce. To evaluate our algo- rithm, extensive experiraents have been conducted using a number of synthetically generated databas- es. For the memory consumption, the two pro- posed new algorithms only consumes around 3% of the existing algorithms when the number of ill- ters increases to 10 k. And for the average search time, the search time of the two proposed algo- rithms is more than four times faster than others when the number of filters is 10 k. The results show that the proposed algorithm works well and outperforms rmny typical existing algorithms with the dimension reduction capability.

Personalized Metaheuristic Clustering Onto Web Documents

Optimal clustering for the web documents is known to complicated cornbinatorial Optimization problem and it is hard to develop a generally applicable oplimal algorithm. An accelerated simuIated arlneaIing aIgorithm is developed for automatic web document classification. The web document classification problem is addressed as the problem of best describing a match between a web query and a hypothesized web object. The normalized term frequency and inverse document frequency coefficient is used as a measure of the match. Test beds are generated on - line during the search by transforming model web sites. As a result, web sites can be clustered optimally in terms of keyword vectofs of corresponding web documents.

Earnings disaggregation and analysts＇ forecasts

Accounting concepts dictate that separately disclosed components should contain separate useful information. This paper examines the relations between income statement components and analysts＇ earnings forecasts and forecast errors. Regressions explaining earnings forecasts using earnings components provide a better fit than regression using just aggregate income to explain forecasts. We interpret this as consistent with the hypothesis that analysts use incremental information in components not available in aggregate income. However, additional tests based on predictability of forecast errors indicate that analysts do not incorporate all information available in components into earnings forecasts. In addition, this inefficiency appears to increase at longer forecast horizons.

Effect of Heteroscedastic Variance Covariance Matrices on Two Groups Linear Classification Techniques

The authors investigate the comparative classification performance of the two groups linear classification techniques. They compared the Fisher linear classification analysis, its robust version based on the minimum covariance determinant with the Filter linear classification rule and the linear combination linear classification technique. These procedures are investigated using laboratory reared aedes albopictus mosquito data set and simulated data set generated based on heteroscedastic covariance matrices with various proportion of contamination. The evaluation procedure is based on the effect of contamination on the mean probabilities of correct classification obtain for each technique. The comparative analysis revealed that the robust Fisher linear classification rule and the linear combination linear classification rule are robust and comparable than the other procedures.

Studies on Wetland Biodiversity in China

This paper briefly summarizes the history of wetland research, the evolvement of wetland science, and their impacts on the understanding of wetland biodiversity in China. A marsh is the key type and basic component of a wetland. Defining the marsh and wetland plants is the basis for understanding the wetland and its biodiversity. The comprehensive multiple factorial classification principles and the multiple developmental models of the wetland are two innovative feats achieved by Chinese scientists, and their application has further promoted ecological research. The CAS Wetland Research Center has made historic contributions to the study of the wetland and its biodiversity in China. Also, the paper discusses several important tasks of wetland and biodiversity research.

基于高生物利用度的创新组分结构中药制剂技术研究

中药制剂现代化是目前中药发展进程中的主要方向,而中药是一个具有多组分、多途径、多靶点整体作用特点的复杂体系,存在着物质基础尚不明确、作用机制不清晰等问题,这些都制约着中药制剂现代化的发展。加强中药组分的理论探索,提高组分制剂技术水平,促进中药组分制剂的发展,对实现中药现代化具有重要的意义。以"组分结构"理论为指导,从原材料前处理工艺和制剂成型技术2个方面系统阐述,以提出高组分生物利用度为目的,论述创新组分结构中药制剂的研究思路。

Finite p-Groups in Which the Number of Subgroups of Possible Order Is Less Than or Equal to p^3

In this paper, groups of order p^n in which the number of subgroups of possible order is less than or equal to p3 ale classified. It turns out that if p 〉 2, n≥ 5, then the classification of groups of order p^n in which the number of subgroups of possible order is less than or equal to p3 and the classification of groups of order p^n with a cyclic subgroup of index p2 are the same.

Genomic landscape of gastric cancer： molecular classification and potential targets

Gastric cancer imposes a considerable health burden worldwide, and its mortality ranks as the second highest for all types of cancers. The limited knowledge of the molecular mechanisms underlying gastric cancer tumorigenesis hinders the development of therapeutic strategies. However, ongoing collaborative sequencing efforts facilitate molecular classification and unveil the genomic landscape of gastric cancer. Several new drivers and tumorigenic pathways in gastric cancer, including chromatin remodeling genes, Rho A-related pathways, TP53 dysregulation, activation of receptor tyrosine kinases, stem cell pathways and abnormal DNA methylation, have been revealed. These newly identified genomic alterations await translation into clinical diagnosis and targeted therapies. Considering that loss-of-function mutations are intractable, synthetic lethality could be employed when discussing feasible therapeutic strategies. Although many challenges remain to be tackled, we are optimistic regarding improvements in the prognosis and treatment of gastric cancer in the near future.

Nanopore DNA sequencing:Are we there yet?

Nanopores have been studied as a unique DNA sequencing technology that can quickly read long stretched DNA sequences. A DNA molecule could pass through a nanopore in a speed of microsecond per base and even faster. With this speed, a human genome can potentially be sequenced by one nanopore in 〈1 h. In contrast to next- generation DNA sequencing （NGS）, the nanopore sequencing is enzyme free without need of sample amplification due to its single-molecule nature. The nanopore sequencing has been envisioned as a new generation of DNA sequencing technology in the post-NGS era. This progress focuses on status quo of the nanopore DNA sequencing and discusses the opportunities and challenges in this rapidly growing field.

NETWORK ANALYSIS OF TERRORIST ACTIVITIES

This paper uses an extensive network approach to "East Turkistan" activities by building both the one-mode and the bipartite networks for these activities.In the one-mode network,centrality analysis and spectrum analysis are used to describe the importance of each vertex.On this basis,two types of core vertices——The center of communities and the intermediary vertices among communities— are distinguished.The weighted extreme optimization(WEO) algorithm is also applied to detect communities in the one-mode network.In the "terrorist-terrorist organization" bipartite network,the authors adopt centrality analysis as well as clustering analysis based on the original bipartite network in order to calculate the importance of each vertex,and apply the edge clustering coefficient algorithm to detect the communities.The comparative and empirical analysis indicates that this research has been proved to be an effective way to identify the core members,key organizations,and communities in the network of "East Turkistan" terrorist activity.The results can provide a scientific basis for the analysis of "East Turkistan" terrorist activity,and thus provide decision support for the real work of "anti-terrorism".