Binary Indium–Zinc Oxide Photoanodes for Efficient Dye‐Sensitized Solar Cells

The benefits of incorporating binary metal‐oxide electrodes en route toward efficient dye‐sensitized solar cells (DSSCs) have recently emerged. The current work aims at realizing efficient indium‐doped zinc oxide based DSSCs by means of enhancing charge transport processes and reducing recombination rates. Electrochemical impedance spectroscopic assays corroborate that low amounts of indium reduce charge transport resistances and increase electron recombination resistances. The latter are in concert with a remarkable enhancement of the charge collection efficiency from 33% to 83% for devices with ZnO and In₁₅Zn₈₅O photoanodes, respectively. Going beyond 15 mol% of indium, an effective electron trapping increases the charge transport resistance and, in turn, dramatically reduces charge collection efficiency. Upon implementing In₁₅Zn₈₅O into an electron cascade photoanode architecture featuring an In₁₅Zn₈₅O bottom layer and a ZnO top layer, a device efficiency of 5.77% and a significantly high current density of 20.4 mA cm^?2 in binary ZnO DSSCs are achieved.     

新型喜树碱类抗癌药物的研究进展

喜树碱是1966年由喜树中分离而来的一种五环结构的生物碱,早期对其抗肿瘤活性的发现更是引发了科学家们对此类化合物极大的研究兴趣,现在已经证实喜树碱类化合物主要是通过抑制在DNA代谢过程中发挥重要作用的I型拓扑异构酶。但其自身因水溶性差、毒副作用强,在临床应用上易出现不良反应。半个世纪以来,国内外研究者在对其作用机制及构效关系的研究基础上,开发出了数以百计的喜树碱类衍生物,很多已经进入临床或临床前研究。但目前仅有两种喜树碱类的化合物拓扑替康和依立替康被美国FDA批准应用于临床上肿瘤的治疗。本文就已上市的喜树碱类化合物以及喜树碱类抗肿瘤药物开发的挑战进行了综述。     

Application of clustering techniques for the characterization of macroinvertebrate communities to support river restoration management

The European Water Framework Directive prescribes that the development of a river assessment system should be based on an ecological typology taking the biological reference conditions of each river type as a starting point. Aside from this assessment, water managers responsible for river restoration actions also need to know the steering environmental factors to meet these reference conditions for biological communities in each ecological river type. As such, an ecological typology based on biological communities is a necessity for efficient river management. In this study, different clustering techniques including the Sørensen similarity ratio, ordination analysis and self-organizing maps were applied to come to an ecological classification of a river. For this purpose, a series of sites within the Zwalm river basin (Flanders, Belgium) were monitored. These river sites were then characterized in terms of biotic (macroinvertebrates), physical–chemical and habitat variables. The cluster analysis resulted in a series of characteristic biotic communities that are found under certain environmental conditions, natural as well as human-influenced. The use of multiple clustering techniques can be of advantage to draw more straightforward and robust conclusions with regard to the ecological classification of river sites. The application of the clustering techniques on the Zwalm river basin, allowed for distinguishing five mutually isolated clusters, characterized by their natural typology and their pollution status. On the basis of this study, one may conclude that river management could benefit from the use of clustering methods for the interpretation of large quantities of data. Furthermore, the clustering results might enable the development of a cenotypology useful for efficiently steering river restoration and enabling river managers to meet a good ecological status in most of the rivers as set by the European Water Framework Directive.     

Statistical measures for validating plant genotype similarity assessments following multivariate analysis of metabolome fingerprint data

Metabolome fingerprinting offers opportunities for ‘first pass’ evaluation of compositional similarity between plant genotypes. Compositional “substantial equivalence” testing is a popular concept in the literature in relation to food safety; however reported studies do not provide a systematic and standard approach to quantify similarity in a high dimensional data context. We have undertaken a large scale screen of Arabidopsis genotypes for evidence that individual genetic modifications effect plant phenotype at the level of the metabolome. From this study we propose pragmatic alternative measures that could in the future be used to assess substantial equivalence in GM foods under realistic data paucity constraints and without prior feature selection. Evaluation of classifier accuracy in supervised data mining approaches by bootstrap error estimation provided a robust tool for model validation. Receiver operating characteristics (such as AUC) provide an alternative measure of predictive ability by displaying the relationship between sensitivity and specificity. Additional specific measures based on scatter matrices and sample margins have also been investigated. We illustrate the application of such metrics on a large metabolic profiling data set derived from analysis of 27 genetically distinct Arabidopsis thaliana mutants. We show that agreement exists between model margins, eigenvalue, accuracies and AUC characteristics produced by three different classifiers (Random Forest, Support Vector Machine and Linear Discriminant Analysis). Comparisons between mutants with no observable phenotypic differences to the parent ecotype provided a baseline for model significance metrics; whilst comparison of mutants with increasingly distinct phenotypic alterations generated predictable changes in these measures of similarity.     

Variability of the needle essential oils of Pinus heldreichii from different populations in Montenegro and Serbia

The essential-oil compositions of Pinus heldreichii Christ. from Montenegro and Serbia are reported at the population level. Whitebark pine is a sub-endemic high-mountain Balkan pine relict of an anthropogenically reduced area, with large morphological diversity and insufficiently clear taxonomic position. In the pine-needle terpene profile from three populations from Montenegro, and one from Serbia, 101 compounds were detected, 72 of which could be identified (Table 3). The dominant constituents are limonene (26.3%), alpha-pinene (17.5%), germacrene D (13.5%), and beta-caryophyllene (10.4%), comprising ca. 67.7% of the essential oil. Medium-to-high contents (0.5-10%) of the following 16 additional components were found: beta-pinene, beta-myrcene, alpha-humulene, delta-cadinene, alpha-muurolene, (E)-hex-2-enal, beta-gurjunene, gamma-muurolene, isopimarol, camphene, gamma-cadinene, aromadendrene, beta-bisabolene, trans-beta-farnesene, alpha-cadinene, and (Z)-hex-3-en-1-ol. The similarity of the populations and the within-population variability was visualized by principle-component analysis (PCA) of eleven selected terpenes in 97 tree samples. Cluster and genetic analyses suggest closest connection between the two spatially most-distant populations I (Montenegro) and IV (Serbia). Based on the profile of the main sesquiterpene components, the studied populations from Montenegro and Serbia are more similar to the populations from Greece and the Central Balkan peninsula (Bosnia and Serbia-Kosovo) than to those on the furthest eastern margin of their natural range (Bulgaria).     

The relationship of vegetation to environmental factors in Wangsuk stream and Gwarim reservoir in Korea: II. Soil environments

This paper presents a quantitative account of vegetation–soil environmental factor relationships in the Wangsuk stream (WS) and the Gwarim reservoir (GR) in Korea. Vegetation and the following soil variables were investigated in May, August and October 2004: pH, conductivity, water content, organic matter, total nitrogen content, NH₄–N content, PO₄–P content, total Ca, Mg, K, and Na content, extractable Ca, Mg, K and Na content, soil texture, distance from the channel, and elevation above water level. Species richness, diversity and ratio of hydrophyte occupation in WS were different from those in GR. Species richness was higher in WS, whereas the ratio of hydrophyte occupation was higher in GR. There were large temporal and spatial variations in plant distribution in the riparian and aquatic zones of WS but only slight variations in those of GR. These differences might have arisen from differences in flooding regime, distance from the stream channel related to elevation above water level, and soil properties such as soil texture and available nutrients. The median values of organic matter, total nitrogen, NH₄–N, PO₄–P and extractable Ca, Mg, K and Na contents in the soil were higher in GR than in WS. Sandy loam and loamy sand were common soil types in WS and clay loam and sandy clay loam in GR. Ten vegetation groups in WS and six in GR were identified using TWINSPAN. DCCA indicated that the distance from the stream channel was most strongly related to plant distribution and this reflected the spatial distribution of plant species in WS. In both WS and GR, NH₄–N content in soil and soil texture were important factors for the distribution of species in May, August and October. Spatial and temporal heterogeneity of soil variables were related to species distribution.     

Patient-Specific Epileptic Seizure Prediction in Long-Term Scalp EEG Signal Using Multivariate Statistical Process Control

An accurate epileptic seizure prediction algorithm can alleviate the problem and reduce risks in the life of a patient suffering from epilepsy. The main motive of this work is to propose a model which can predict seizures well in advance of its occurrence. Multivariate statistical process control (MSPC) has been used for seizure predictions in long-term scalp EEG signal. It has been observed that excessive neuronal activity in the preictal period of seizure changes the electrical characteristic from chaotic to rhythmic behavior. These changes have been utilized for prediction. Eight temporal based features are used for predicting the seizures by using multivariate statistical process control, which is widely known as an anomaly monitoring method. 90 seizures from the CHB-MIT EEG data of ten patients are analyzed.ResultThe results of the proposed method demonstrated that 80 seizures out of 90 in preictal period were correctly predicted prior to the seizure onset, thereby giving a sensitivity of 88.89%. The false positive rate is observed to 0.39 per hour.ConclusionThis study proposed a temporal based patient-specific epileptic seizure prediction method using MSPC in long-term scalp EEG signals. It also provides the possibility of realizing an EEG-based epileptic seizure prediction system which requires less computational power.SignificanceThe proposed method does not require preictal data for modeling. The extracted features are computationally easy. The tested result shows good accuracy on the CHB-MIT data base.     

Multivariate Polya and Inverse Polya Distributions of Order k

Multivariate Polya and inverse Polya distributions of order k are derived by means of generalized urn models and by compounding the type II multinomial and multivariate negative binomial distributions of order k of PHILIPPOU , ANTZOULAKOS and TRIPSIANNIS (1990, 1988), respectively, with the Dirichlet distribution. It is noted that the above two distributions include as special cases a multivariate hypergeometric distribution of order k, a negative one, an inverse one, a negative inverse one and a discrete uniform of the same order. The probability generating functions, means, variances and covariances of the new distributions are obtained and five asymptotic results are established relating them to the above-mentioned multinomial and multivariate negative binomial distributions of order k, and to the type II negative binomial and the type I multivariate Poisson distributions of order k of PHILIPPOU (1983), and PHILIPPOU , ANTZOULAKOS and TRIPSIAN-NIS (1988), respectively. Potential applications are also indicated. The present paper extends to the multivariate case the work of PHILIPPOU , TRIPSIANNIS and ANTZOULAKOS (1989) on Polya and inverse Polya distributions of order k..