Spatial Regression Modeling for Compositional Data With Many Zeros

Compositional data analysis considers vectors of nonnegative-valued variables subject to a unit-sum constraint. Our interest lies in spatial compositional data, in particular, land use/land cover (LULC) data in the northeastern United States. Here, the observations are vectors providing the proportions of LULC types observed in each 3 km×3 km grid cell, yielding order 10⁴ cells. On the same grid cells, we have an additional compositional dataset supplying forest fragmentation proportions. Potentially useful and available covariates include elevation range, road length, population, median household income, and housing levels. We propose a spatial regression model that is also able to capture flexible dependence among the components of the observation vectors at each location as well as spatial dependence across the locations of the simplex-restricted measurements. A key issue is the high incidence of observed zero proportions for the LULC dataset, requiring incorporation of local point masses at 0. We build a hierarchical model prescribing a power scaling first stage and using latent variables at the second stage with spatial structure for these variables supplied through a multivariate CAR specification. Analyses for the LULC and forest fragmentation data illustrate the interpretation of the regression coefficients and the benefit of incorporating spatial smoothing.     

Electronic correlation effects and superconductivity in doped fullerenes

A theory of the electronic properties of doped fullerenes is proposed in which electronic correlation effects within single fullerene molecules play a central role, and qualitative predictions are made which, if verified, would support this hypothesis. Depending on the effective intrafulllerene electron-electron repulsion and the interfullerene hopping amplitudes (which should depend on the dopant species, among other things), the calculations indicate the possibilities of singlet superconductivity and ferromagnetism.     

A Novel Zero Discharge Intensive Seawater Recirculating System for the Culture of Marine Fish

Results are presented of a zero‐discharge marine recirculating system used for the culture of gilthead seabream Sparus aurata. Operation of the system without any discharge of water and sludge was enabled by recirculation of effluent water through two separate treatment loops, an aerobic trickling filter and a predominantly anoxic sedimentation basin, followed by a fluidized bed reactor. The fish basin was stocked for the first 6 mo with red tilapia Oreochromis niloticus × O. aureus at an initial density of 16 kg/m³. During this period salinity was raised from 0 to 20 parts per thousand. Then, gilthead seabream, stocked at an initial density of 21 kg/m³, replaced tilapia at day 167 and were cultured for an additional 225 d. Non steady‐state inorganic nitrogen transformations occurred as a result of these salinity changes. After day 210, the system operated at all times with those water quality parameters considered critical for successful operation of mariculture systems, within acceptable limits. Thus ammonia, nitrite, and nitrate concentrations did not exceed 1.0‐mg total ammonia‐N/ L, 0.5‐mg NO₂:‐N/L and 50‐mg NO₃‐N/L, respectively. Sulfide levels in the fish basin were below detection limits and oxygen > 6 mg/L after the oxygen generator was added at day 315. Ammonia, produced in the fish basin and to a lesser extent in the sedimentation basin, was converted to nitrate in the aerobic trickling filter. Nitrate removal took place in the sedimentation basin and to a lesser extent in the fluidized bed reactor. Sludge, remaining in the sedimentation basin at the end of the experimental period, accounted for 9.2% of the total feed dry matter addition to the system. The system was disease‐free for the entire year and fish at harvest were of good quality. Water consumption for production of 1 kg of tilapia was 93 L and 214 L for production of 1 kg of gilthead seabream. Additional growth performance data of gilthead seabream cultured in a similar but larger system are presented. During 164 d of operation of the latter system, maximum stocking densities reached 50 kgl M³ and fish biomass production was 27.7 kg/m³. Relatively poor fish survival and growth resulted from occasional technical failures of this pilot system.     

Cell cycle regulation of myosin-V by calcium/calmodulin-dependent protein kinase II

Organelle transport by myosin-V is down-regulated during mitosis, presumably by myosin-V phosphorylation. We used mass spectrometry phosphopeptide mapping to show that the tail of myosin-V was phosphorylated in mitotic Xenopus egg extract on a single serine residue localized in the carboxyl-terminal organelle-binding domain. Phosphorylation resulted in the release of the motor from the organelle. The phosphorylation site matched the consensus sequence of calcium/calmodulin-dependent protein kinase II (CaMKII), and inhibitors of CaMKII prevented myosin-V release. The modulation of cargo binding by phosphorylation is likely to represent a general mechanism regulating organelle transport by myosin-V.     

Recent advances in the polymerase chain reaction

The polymerase chain reaction (PCR) has dramatically altered how molecular studies are conducted as well as what questions can be asked. In addition to simplifying molecular tasks typically carried out with the use of recombinant DNA technology, PCR has allowed a spectrum of advances ranging from the identification of novel genes and pathogens to the quantitation of characterized nucleotide sequences. PCR can provide insights into the intricacies of single cells as well as the evolution of species. Some recent developments in instrumentation, methodology, and applications of the PCR are presented in this review.     

Spatial Regression Using Kernel Averaged Predictors

Traditional spatial linear regression models assume that the mean of the response is a linear combination of predictors measured at the same location as the response. In spatial applications, however, it seems plausible that neighboring predictors can also inform about the response. This article proposes using unobserved kernel averaged predictors in such regressions. The kernels are parametric introducing additional parameters that are estimated with the data. Properties and challenges of using kernel averaged predictors within a regression model are detailed in the simple case of a univariate response and a single predictor. Additionally, extensions to multiple predictors and generalized linear models are discussed. The methods are demonstrated using a data set of dew duration and shrub density. Supplemental materials are available online.     

Continuous Spatial Process Models for Spatial Extreme Values

We propose a hierarchical modeling approach for explaining a collection of point-referenced extreme values. In particular, annual maxima over space and time are assumed to follow generalized extreme value (GEV) distributions, with parameters μ, σ, and ξ specified in the latent stage to reflect underlying spatio-temporal structure. The novelty here is that we relax the conditionally independence assumption in the first stage of the hierarchial model, an assumption which has been adopted in previous work. This assumption implies that realizations of the the surface of spatial maxima will be everywhere discontinuous. For many phenomena including, e.g., temperature and precipitation, this behavior is inappropriate. Instead, we offer a spatial process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters. In this sense, the first stage smoothing is viewed as fine scale or short range smoothing while the larger scale smoothing will be captured in the second stage of the modeling. In addition, as would be desired, we are able to implement spatial interpolation for extreme values based on this model. A simulation study and a study on actual annual maximum rainfall for a region in South Africa are used to illustrate the performance of the model.     

Influence of nitrite accumulation in association with seasonal patterns and mineralization of soil nitrogen in a semi-arid pine forest

To identify factors that influence the relatively high productivity of a semi-arid pine afforestation system in southern Israel, we investigated inorganic nitrogen deposition and mineralization for more than 2 years. To this end, we measured bulk and dry deposition, in situ N-mineralization over the seasonal cycle, and the potential activity of nitrifying microorganisms by soil slurry incubations. There was a small increase in bulk N deposition in the forest, compared with shrubland, but no change in dry deposition. An unexpected rapid increase in nitrite concentration in the forest soil was observed after soil rewetting by the first winter rains, which could not be explained by deposition. This was accompanied by a decrease in ammonium and only a slight increase in nitrate concentrations. Only a small increase in nitrite and a rapid increase in nitrate concentration in the mineral soil were observed in the surrounding shrubland. Soil slurry incubations from the forest sites exhibited significant delay in nitrite, compared with nitrate accumulation (up to 50 h under lab conditions) in samples taken in the dry season, but not in the wet season. This indicated different rates of ammonium and nitrite oxidation that are most likely linked to differential activation of different microbial populations after the summer stress. The initial oxidation process of ammonia to nitrate, upon soil rewetting in semi-arid environments, appears to occur as a partially uncoupled two-step process, as opposed to a rapid continuous one in wetter environments. This may have implications for the synchronization of nitrate availability to plants and therefore for high forest productivity and nitrogen use efficiency. Forest productivity in the semi-arid regions, in turn, is becoming increasingly more important with persistent predictions of warming and drying trends over the entire Mediterranean basin and other regions.