Isomap nonlinear dimensionality reduction and bimodality of Asian monsoon convection

It is known that the empirical orthogonal function method is unable to detect possible nonlinear structure in climate data. Here, isometric feature mapping (Isomap), as a tool for nonlinear dimensionality reduction, is applied to 1958–2001 ERA-40 sea-level pressure anomalies to study nonlinearity of the Asian summer monsoon intraseasonal variability. Using the leading two Isomap time series, the probability density function is shown to be bimodal. A two-dimensional bivariate Gaussian mixture model is then applied to identify the monsoon phases, the obtained regimes representing enhanced and suppressed phases, respectively. The relationship with the large-scale seasonal mean monsoon indicates that the frequency of monsoon regime occurrence is significantly perturbed in agreement with conceptual ideas, with preference for enhanced convection on intraseasonal time scales during large-scale strong monsoons. Trend analysis suggests a shift in concentration of monsoon convection, with less emphasis on South Asia and more on the East China Sea.

Dimensionality reduction assisted tensor clustering

This paper is concerned with tensor clustering with the assistance of dimensionality reduction approaches. A class of formulation for tensor clustering is introduced based on tensor Tucker decomposition models. In this formulation, an extra tensor mode is formed by a collection of tensors of the same dimensions and then used to assist a Tucker decomposition in order to achieve data dimensionality reduction. We design two types of clustering models for the tensors: PCA Tensor Clustering model and Non-negative Tensor Clustering model, by utilizing different regularizations. The tensor clustering can thus be solved by the optimization method based on the alternative coordinate scheme. Interestingly, our experiments show that the proposed models yield comparable or even better performance compared to most recent clustering algorithms based on matrix factorization.

Gaussian processes autoencoder for dimensionality reduction

Learning low dimensional manifold from highly nonlinear data of high dimensionality has become increasingly important for discovering intrinsic representation that can be utilized for data visualization and preprocessing. The autoencoder is a powerful dimensionality reduction technique based on minimizing reconstruction error, and it has regained popularity because it has been efficiently used for greedy pretraining of deep neural networks. Compared to Neural Network (NN), the superiority of Gaussian Process (GP) has been shown in model inference, optimization and performance. GP has been successfully applied in nonlinear Dimensionality Reduction (DR) algorithms, such as Gaussian Process Latent Variable Model (GPLVM). In this paper we propose the Gaussian Processes Autoencoder Model (GPAM) for dimensionality reduction by extending the classic NN based autoencoder to GP based autoencoder. More interestingly, the novel model can also be viewed as back constrained GPLVM (BC-GPLVM) where the back constraint smooth function is represented by a GP. Experiments verify the performance of the newly proposed model.

Empirical Orthogonal Functions: The Medium is the Message

Empirical orthogonal function (EOF) analysis is a powerful tool for data compression and dimensionality reduction used broadly in meteorology and oceanography. Often in the literature, EOF modes are interpreted individually, independent of other modes. In fact, it can be shown that no such attribution can generally be made. This review demonstrates that in general individual EOF modes (i) will not correspond to individual dynamical modes, (ii) will not correspond to individual kinematic degrees of freedom, (iii) will not be statistically independent of other EOF modes, and (iv) will be strongly influenced by the nonlocal requirement that modes maximize variance over the entire domain. The goal of this review is not to argue against the use of EOF analysis in meteorology and oceanography; rather, it is to demonstrate the care that must be taken in the interpretation of individual modes in order to distinguish the medium from the message.

Effectiveness of landmark analysis for establishing locality in p2p networks

Locality to other nodes on a peer-to-peer overlay network can be established by means of a set of landmarks shared among the participating nodes. Each node independently collects a set of latency measures to landmark nodes, which are used as a multi-dimensional feature vector. Each peer node uses the feature vector to generate a unique scalar index which is correlated to its topological locality. A popular dimensionality reduction technique is the space filling Hilbert’s curve, as it possesses good locality preserving properties. However, there exists little comparison between Hilbert’s curve and other techniques for dimensionality reduction. This work carries out a quantitative analysis of their properties. Linear and non-linear techniques for scaling the landmark vectors to a single dimension are investigated. Hilbert’s curve, Sammon’s mapping and Principal Component Analysis have been used to generate a 1d space with locality preserving properties. This work provides empirical evidence to support the use of Hilbert’s curve in the context of locality preservation when generating peer identifiers by means of landmark vector analysis. A comparative analysis is carried out with an artificial 2d network model and with a realistic network topology model with a typical power-law distribution of node connectivity in the Internet. Nearest neighbour analysis confirms Hilbert’s curve to be very effective in both artificial and realistic network topologies. Nevertheless, the results in the realistic network model show that there is scope for improvements and better techniques to preserve locality information are required.

Interaction between allelic variations in vitamin D receptor and retinoid X receptor genes on metabolic traits

BACKGROUND: Low vitamin D status has been shown to be a risk factor for several metabolic traits such as obesity, diabetes and cardiovascular disease. The biological actions of 1, 25-dihydroxyvitamin D, are mediated through the vitamin D receptor (VDR), which heterodimerizes with retinoid X receptor, gamma (RXRG). Hence, we examined the potential interactions between the tagging polymorphisms in the VDR (22 tag SNPs) and RXRG (23 tag SNPs) genes on metabolic outcomes such as body mass index, waist circumference, waist-hip ratio (WHR), high- and low-density lipoprotein (LDL) cholesterols, serum triglycerides, systolic and diastolic blood pressures and glycated haemoglobin in the 1958 British Birth Cohort (1958BC, up to n = 5,231). We used Multifactor- dimensionality reduction (MDR) program as a non-parametric test to examine for potential interactions between the VDR and RXRG gene polymorphisms in the 1958BC. We used the data from Northern Finland Birth Cohort 1966 (NFBC66, up to n = 5,316) and Twins UK (up to n = 3,943) to replicate our initial findings from 1958BC. RESULTS: After Bonferroni correction, the joint-likelihood ratio test suggested interactions on serum triglycerides (4 SNP - SNP pairs), LDL cholesterol (2 SNP - SNP pairs) and WHR (1 SNP - SNP pair) in the 1958BC. MDR permutation model testing analysis showed one two-way and one three-way interaction to be statistically significant on serum triglycerides in the 1958BC. In meta-analysis of results from two replication cohorts (NFBC66 and Twins UK, total n = 8,183), none of the interactions remained after correction for multiple testing (Pinteraction >0.17). CONCLUSIONS: Our results did not provide strong evidence for interactions between allelic variations in VDR and RXRG genes on metabolic outcomes; however, further replication studies on large samples are needed to confirm our findings.

Crop yield reduction in the tropics under climate change: Processes and uncertainties

Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

Tumour necrosis factor alpha induces rapid reduction in AMPA receptor-mediated calcium entry in motor neurones by increasing cell surface expression of the GluR2 subunit: relevance to neurodegeneration

The AMPA receptor (AMPAR) subunit GluR2, which regulates excitotoxicity and the inflammatory cytokine tumour necrosis factor alpha (TNF alpha) have both been implicated in motor neurone vulnerability in Amyotrophic Lateral Sclerosis/Motor Neurone Disease. TNF alpha has been reported to increase cell surface expression of AMPAR subunits to increase synaptic strength and enhance excitotoxicity, but whether this mechanism occurs in motor neurones is unknown. We used primary cultures of mouse motor neurones and cortical neurones to examine the interaction between TNF alpha receptor activation, GluR2 availability, AMPAR-mediated calcium entry and susceptibility to excitotoxicity. Short exposure to a physiologically relevant concentration of TNFalpha (10 ng/ml, 15 min) caused a marked redistribution of both GluR1 and GluR2 to the cell surface as determined by cell surface biotinylation and immunofluorescence. Using Fura-2 AM microfluorimetry we showed that exposure to TNFalpha caused a rapid reduction in the peak amplitude of AMPA-mediated calcium entry in a PI3-kinase and p38 kinase-dependent manner, consistent with increased insertion of GluR2-containing AMPAR into the plasma membrane. This resulted in a protection of motor neurones against kainate-induced cell death. Our data therefore, suggests that TNF alpha acts primarily as a physiological regulator of synaptic activity in motor neurones rather than a pathological drive in ALS

Reduction of arsenic uptake by lettuce with ferrous sulfate applied to contaminated soil

Soil contamination by arsenic (As) presents a hazard in many countries and there is a need for techniques to minimize As uptake by plants. A proposed in situ remediation method was tested by growing lettuce (Lactuca sativa L. cv. Kermit) in a greenhouse pot experiment on soil that contained 577 mg As kg(-1), taken from a former As smelter site. All combinations of iron (Fe) oxides, at concentrations of 0.00, 0.22, 0.54, and 1.09% (w/w), and lime, at concentrations of 0.00, 0.27, 0.68, and 1.36% (w/w), were tested in a factorial design. To create the treatments, field-moist soil, commercial-grade FeSO4, and ground agricultural lime were mixed and stored for one week, allowing Fe oxides to precipitate. Iron oxides gave highly significant (P < 0.001) reductions in lettuce As concentrations, down to 11% of the lettuce As concentration for untreated soil. For the Fe oxides and lime treatment combinations where soil pH was maintained nearly constant, the lettuce As concentration declined in an exponential relationship with increasing FeSO4 application rate and lettuce yield was almost unchanged. Iron oxides applied at a concentration of 1.09% did not give significantly lower lettuce As concentrations than the 0.54% treatment. Simultaneous addition of lime with FeSO4 was essential. Ferrous sulfate with insufficient lime lowered soil pH and caused mobilization of Al, Ba, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, and Zn. At the highest Fe oxide to lime ratios, Mn toxicity caused severe yield loss.

Microbial perchlorate reduction: A precise laboratory determination of the chlorine isotope fractionation and its possible biochemical basis

Perchlorate-reducing bacteria fractionate chlorine stable isotopes giving a powerful approach to monitor the extent of microbial consumption of perchlorate in contaminated sites undergoing remediation or natural perchlorate containing sites. This study reports the full experimental data and methodology used to re-evaluate the chlorine isotope fractionation of perchlorate reduction in duplicate culture experiments of Azospira suillum strain PS at 37 degrees C (Delta Cl-37(Cr)--ClO4-) previously reported, without a supporting data set by Coleman et al. [Coleman, M.L., Ader, M., Chaudhuri, S., Coates,J.D., 2003. Microbial Isotopic Fractionation of Perchlorate Chlorine. Appl. Environ. Microbiol. 69, 4997-5000] in a reconnaissance study, with the goal of increasing the accuracy and precision of the isotopic fractionation determination. The method fully described here for the first time, allows the determination of a higher precision Delta Cl-37(Cl)--ClO4- value, either from accumulated chloride content and isotopic composition or from the residual perchlorate content and isotopic composition. The result sets agree perfectly, within error, giving average Delta Cl-37(Cl)--ClO4- = -14.94 +/- 0.15%omicron. Complementary use of chloride and perchlorate data allowed the identification and rejection of poor quality data by applying mass and isotopic balance checks. This precise Delta Cl-37(Cl)--ClO4-, value can serve as a reference point for comparison with future in situ or microcosm studies but we also note its similarity to the theoretical equilibrium isotopic fractionation between a hypothetical chlorine species of redox state +6 and perchlorate at 37 degrees C and suggest that the first electron transfer during perchlorate reduction may occur at isotopic equilibrium between art enzyme-bound chlorine and perchlorate. (C) 2008 Elsevier B.V. All rights reserved.

Reduction of arsenic uptake by lettuce with ferrous sulfate applied to contaminated soil

Soil contamination by arsenic (As) presents a hazard in many countries and there is a need for techniques to minimize As uptake by plants. A proposed in situ remediation method was tested by growing lettuce (Lactuca sativa L. cv. Kermit) in a greenhouse pot experiment on soil that contained 577 mg As kg(-1), taken from a former As smelter site. All combinations of iron (Fe) oxides, at concentrations of 0.00, 0.22, 0.54, and 1.09% (w/w), and lime, at concentrations of 0.00, 0.27, 0.68, and 1.36% (w/w), were tested in a factorial design. To create the treatments, field-moist soil, commercial-grade FeSO4, and ground agricultural lime were mixed and stored for one week, allowing Fe oxides to precipitate. Iron oxides gave highly significant (P < 0.001) reductions in lettuce As concentrations, down to 11% of the lettuce As concentration for untreated soil. For the Fe oxides and lime treatment combinations where soil pH was maintained nearly constant, the lettuce As concentration declined in an exponential relationship with increasing FeSO4 application rate and lettuce yield was almost unchanged. Iron oxides applied at a concentration of 1.09% did not give significantly lower lettuce As concentrations than the 0.54% treatment. Simultaneous addition of lime with FeSO4 was essential. Ferrous sulfate with insufficient lime lowered soil pH and caused mobilization of Al, Ba, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, and Zn. At the highest Fe oxide to lime ratios, Mn toxicity caused severe yield loss.

Carbon dioxide induced stomatal closure increases radiative forcing of climate via a rapid reduction in low cloud

We performed an ensemble of twelve five-year experiments using a coupled climate-carbon-cycle model with scenarios of prescribed atmospheric carbon dioxide concentration; CO2 was instantaneously doubled or quadrupled at the start of the experiments. Within these five years, climate feedback is not significantly influenced by the effects of climate change on the carbon system. However, rapid changes take place, within much less than a year, due to the physiological effect of CO2 on plant stomatal conductance, leading to adjustment in the shortwave cloud radiative effect over land, due to a reduction in low cloud cover. This causes a 10% enhancement to the radiative forcing due to CO2, which leads to an increase in the equilibrium warming of 0.4 and 0.7 K for doubling and quadrupling. The implications for calibration of energy-balance models are discussed.