Plant functional group classifications and a generalized hierarchical framework of plant functional traits

The plant functional group concept has been proven to be an excellent research framework for investigating the linkages between ecosystem functions and plant biodiversity. The large number of plant functional group classifications however makes it difficult to compare data from different studies and draw general conclusions. In this article, we briefly review the major plant functional group classifications, and then propose a generalized hierarchical framework that incorporates plant functional traits ranging from the molecular to the biospherical level, and operating on varying spatial/temporal/disturbance scales for in-depth studies of the relationship between plant biodiversity and ecosystem characteristics. This framework may help policy makers formulate better ecological conservation and restoration plans.Keywords: Plant functional traits, relationship, biodiversity, plant functional groups, ecosystem proces

Deep Learning for Single Image Super-Resolution: A Brief Review

Single image super-resolution (SISR) is a notoriously challenging ill-posed problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions. To solve the SISR problem, recently powerful deep learning algorithms have been employed and achieved the state-of-the-art performance. In this survey, we review representative deep learning-based SISR methods, and group them into two categories according to their major contributions to two essential aspects of SISR: the exploration of efficient neural network architectures for SISR, and the development of effective optimization objectives for deep SISR learning. For each category, a baseline is firstly established and several critical limitations of the baseline are summarized. Then representative works on overcoming these limitations are presented based on their original contents as well as our critical understandings and analyses, and relevant comparisons are conducted from a variety of perspectives. Finally we conclude this review with some vital current challenges and future trends in SISR leveraging deep learning algorithms.Comment: Accepted by IEEE Transactions on Multimedia (TMM

Patrones de distribución de individuos longevos de plantas relictas en los alrededores de la montana Fanjingshan en China: implicaciones para su conservación in situ

The mountain areas in south-central China are widely recognized as refugia of relict plants during the late Neogene and Quaternary periods. In this paper, we try to explore the distribution patterns of natural habitats and to exactly locate the refugia of relict species around Fanjingshan Mountain using dendrological data of long-lived individuals (≥ 100 years old). Six typical relict plants were found around the mountain, i.e. Cyclocarya paliurus, Ginkgo biloba, Liriodendron chinense, Pinus massoniana, Podocarpus macrophyllus, and Taxus chinensis. The long-lived individuals were divided into three classes according to their ages: Class-I (≥ 500 years), Class-II (300–499 years), and Class-III (100–299 years). Our results showed that the south-west region to the mountain was the main distribution area of Class-I trees of G. biloba and T. chinensis, most of which occurring in the same small village (Yangliu Village of Yinjiang County). The north-east region harboured all the six relict species. Floristic analyses also indicated these two regions were very similar in tree growth as measured by DBH (diameter at breast height of 1.3 m). Thus, these two areas would have provided long-term suitable habitats for relict species. The south-west region, especially the small village Yangliu, should be given highest priority for in situ conservation of relict species and other rare and endangered plants. Attention should also be paid to the north-east region for its very high species diversity of relict species.Las áreas montañosas de la región centro-sur de China están ampliamente reconocidas por su papel como refugio de plantas relictas durante la última etapa del Neógeno y el Cuaternario. En el presente trabajo se intentan explorar los patrones de distribución de los hábitats naturales y la localización exacta de los refugios para especies vegetales relictas en los alrededores de la montaña Fanjinshan, mediante el empleo de datos dendrológicos de individuos longevos (≥ 100 años). En el área de estudio se encontraron seis especies vegetales típicamente relictas: Cyclocarya paliurus, Ginkgo biloba, Liriodendron chinense, Pinus massoniana, Podocarpus macrophyllus y Taxus chinensis. Los individuos longevos se dividieron en tres categorías de acuerdo con su edad estimada: individuos de Clase I (≥ 500 años), de Clase II (300–499 años) y de Clase III (100–299 años). Nuestros resultados muestran que la región situada al suroeste de la montaña se corresponde con la principal área de distribución de los árboles de Clase I de G. biloba y T. chinensis, localizándose la mayor parte de éstos en los alrededores de una pequeña aldea (Yangliu, en el condado de Yinjiang). La región situada al noreste de Fanjinshan alberga, por su parte, las seis especies relictas, y los análisis florísticos muestran una elevada similaridad entre ambas regiones por lo que respecta al crecimiento arbóreo medido como DBH [diámetro a la altura del pecho (1,3 m)]. Por consiguiente, estas dos regiones habrían proporcionado hábitats adecuados para la supervivencia de especies relictas. La región suroeste, y en especial la aldea de Yangliu, deben recibir la máxima prioridad para la conservación in situ de especies relictas (y otras especies raras y amenazadas). La región noreste también debe priorizarse dada su elevada diversidad de especies relictas

On precessing flow in an oblate spheroid of arbitrary eccentricity

This is the author accepted manuscript. The final version is available from Cambridge University Press via the DOI in this record. Copyright © 2014 Cambridge University PressWe consider a homogeneous fluid of viscosity v confined within an oblate spheroidal cavity of arbitrary eccentricity E marked by the equatorial radius d and the polar radius d √1-E2 with 0<E<1. The spheroidal container rotates rapidly with an angular velocity Ω0 about its symmetry axis and precesses slowly with an angular velocity Ωp about an axis that is fixed in space. It is through both topographical and viscous effects that the spheroidal container and the viscous fluid are coupled together, driving precessing flow against viscous dissipation. The precessionally driven flow is characterized by three dimensionless parameters: the shape parameter E , the Ekman number Ek=v /(d2|Ω| 0 and the Poincaré number Po=±|Ωp|/ |Ω0|. We derive a time-dependent asymptotic solution for the weakly precessing flow in the mantle frame of reference satisfying the no-slip boundary condition and valid for a spheroidal cavity of arbitrary eccentricity at Ek≪1. No prior assumptions about the spatialoral structure of the precessing flow are made in the asymptotic analysis. We also carry out direct numerical simulation for both the weakly and the strongly precessing flow in the same frame of reference using a finite-element method that is particularly suitable for non-spherical geometry. A satisfactory agreement between the asymptotic solution and direct numerical simulation is achieved for sufficiently small Ekman and Poincaré numbers. When the nonlinear effect is weak with |Po| ≪ 1, the precessing flow in an oblate spheroid is characterized by an azimuthally travelling wave without having a mean azimuthal flow. Stronger nonlinear effects with increasing |Po| produce a large-amplitude, time-independent mean azimuthal flow that is always westward in the mantle frame of reference. Implications of the precessionally driven flow for the westward motion observed in the Earth's fluid core are also discussed. © 2014 Cambridge University Press.Science & Technology Facilities Council (STFC)NERCHong Kong RGCNSFCChinese Academy of SciencesK.Z. is supported by UK STFC and NERC grants, K.H.C. is supported by Hong Kong RGC grant/700310 and X.L. is supported by NSFC/11133004 and Chinese Academy of Sciences under grant number KZZD-EW-01-3. The numerical computation is supported by Shanghai Supercomputer Cente

Improving Ant Collaborative Filtering on Sparsity via Dimension Reduction

Recommender systems should be able to handle highly sparse training data that continues to change over time. Among the many solutions, Ant Colony Optimization, as a kind of optimization algorithm modeled on the actions of an ant colony, enjoys the favorable characteristic of being optimal, which has not been easily achieved by other kinds of algorithms. A recent work adopting genetic optimization proposes a collaborative filtering scheme: Ant Collaborative Filtering (ACF), which models the pheromone of ants for a recommender system in two ways: (1) use the pheromone exchange to model the ratings given by users with respect to items; (2) use the evaporation of existing pheromone to model the evolution of users’ preference change over time. This mechanism helps to identify the users and the items most related, even in the case of sparsity, and can capture the drift of user preferences over time. However, it reveals that many users share the same preference over items, which means it is not necessary to initialize each user with a unique type of pheromone, as was done with the ACF. Regarding the sparsity problem, this work takes one step further to improve the Ant Collaborative Filtering’s performance by adding a clustering step in the initialization phase to reduce the dimension of the rate matrix, which leads to the results that K<<#users, where K is the number of clusters, which stands for the maximum number of types of pheromone carried by all users. We call this revised version the Improved Ant Collaborative Filtering (IACF). Experiments are conducted on larger datasets, compared with the previous work, based on three typical recommender systems: (1) movie recommendations, (2) music recommendations, and (3) book recommendations. For movie recommendation, a larger dataset, MoviesLens 10M, was used, instead of MoviesLens 1M. For book recommendation and music recommendation, we used a new dataset that has a much larger size of samples from Douban and NetEase. The results illustrate that our IACF algorithm can better deal with practical recommendation scenarios that handle sparse dataset

The cumulative effects of known susceptibility variants to predict primary biliary cirrhosis risk.

Multiple genetic variants influence the risk for development of primary biliary cirrhosis (PBC). To explore the cumulative effects of known susceptibility loci on risk, we utilized a weighted genetic risk score (wGRS) to evaluate whether genetic information can predict susceptibility. The wGRS was created using 26 known susceptibility loci and investigated in 1840 UK PBC and 5164 controls. Our data indicate that the wGRS was significantly different between PBC and controls (P=1.61E-142). Moreover, we assessed predictive performance of wGRS on disease status by calculating the area under the receiver operator characteristic curve. The area under curve for the purely genetic model was 0.72 and for gender plus genetic model was 0.82, with confidence limits substantially above random predictions. The risk of PBC using logistic regression was estimated after dividing individuals into quartiles. Individuals in the highest disclosed risk group demonstrated a substantially increased risk for PBC compared with the lowest risk group (odds ratio: 9.3, P=1.91E-084). Finally, we validated our findings in an analysis of an Italian PBC cohort. Our data suggested that the wGRS, utilizing genetic variants, was significantly associated with increased risk for PBC with consistent discriminant ability. Our study is a first step toward risk prediction for PBC

Optimum sizing of PV/Wind hybrid system (I) CAD method

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe