Nitric Oxide Mediates the Hormonal Control of Crassulacean Acid Metabolism Expression in Young Pineapple Plants

Genotypic, developmental, and environmental factors converge to determine the degree of Crassulacean acid metabolism (CAM) expression. To characterize the signaling events controlling CAM expression in young pineapple (Ananas comosus) plants, this photosynthetic pathway was modulated through manipulations in water availability. Rapid, intense, and completely reversible up-regulation in CAM expression was triggered by water deficit, as indicated by the rise in nocturnal malate accumulation and in the expression and activity of important CAM enzymes. During both up-and down-regulation of CAM, the degree of CAM expression was positively and negatively correlated with the endogenous levels of abscisic acid (ABA) and cytokinins, respectively. When exogenously applied, ABA stimulated and cytokinins repressed the expression of CAM. However, inhibition of water deficit-induced ABA accumulation did not block the up-regulation of CAM, suggesting that a parallel, non-ABA-dependent signaling route was also operating. Moreover, strong evidence revealed that nitric oxide (NO) may fulfill an important role during CAM signaling. Up-regulation of CAM was clearly observed in NO-treated plants, and a conspicuous temporal and spatial correlation was also evident between NO production and CAM expression. Removal of NO from the tissues either by adding NO scavenger or by inhibiting NO production significantly impaired ABA-induced up-regulation of CAM, indicating that NO likely acts as a key downstream component in the ABA-dependent signaling pathway. Finally, tungstate or glutamine inhibition of the NO-generating enzyme nitrate reductase completely blocked NO production during ABA-induced up-regulation of CAM, characterizing this enzyme as responsible for NO synthesis during CAM signaling in pineapple plants.

Patterns of regional differentiation in post-Soviet Russia

This doctoral thesis aims at contributing to the literature on transition economies focusing on the Russian Federations and in particular on regional income convergence and fertility patterns. The first two chapter deal with the issue of income convergence across regions. Chapter 1 provides an historical-institutional analysis of the period between the late years of the Soviet Union and the last decade of economic growth and a presentation of the sample with a description of gross regional product composition, agrarian or industrial vocation, labor. Chapter 2 contributes to the literature on exploratory spatial data analysis with a application to a panel of 77 regions in the period 1994-2008. It provides an analysis of spatial patterns and it extends the theoretical framework of growth regressions controlling for spatial correlation and heterogeneity. Chapter 3 analyses the national demographic patterns since 1960 and provides a review of the policies on maternity leave and family benefits. Data sources are the Statistical Yearbooks of USSR, the Statistical Yearbooks of the Russian Soviet Federative Socialist Republic and the Demographic Yearbooks of Russia. Chapter 4 analyses the demographic patterns in light of the theoretical framework of the Becker model, the Second Demographic Transition and an economic-crisis argument. With national data from 1960, the theoretically issue of the pro or countercyclical relation between income and fertility is graphically analyzed and discussed, together with female employment and education. With regional data after 1994 different panel data models are tested. Individual level data from the Russian Longitudinal Monitoring Survey are employed using the logit model. Chapter 5 employs data from the Generations and Gender Survey by UNECE to focus on postponement and second births intentions. Postponement is studied through cohort analysis of mean maternal age at first birth, while the methodology used for second birth intentions is the ordered logit model.

Impact of irrigation in the Po valley (Italy) on meteorological parameters through numerical simulation

Recent studies found that soil-atmosphere coupling features, through soil moisture, have been crucial to simulate well heat waves amplitude, duration and intensity. Moreover, it was found that soil moisture depletion both in Winter and Spring anticipates strong heat waves during the Summer. Irrigation in geophysical studies can be intended as an anthropogenic forcing to the soil-moisture, besides changes in land proprieties. In this study, the irrigation was add to a LAM hydrostatic model (BOLAM) and coupled with the soil. The response of the model to irrigation perturbation is analyzed during a dry Summer season. To identify a dry Summer, with overall positive temperature anomalies, an extensive climatological characterization of 2015 was done. The method included a statistical validation on the reference period distribution used to calculate the anomalies. Drought conditions were observed during Summer 2015 and previous seasons, both on the analyzed region and the Alps. Moreover July was characterized as an extreme event for the referred distribution. The numerical simulation consisted on the summer season of 2015 and two run: a control run (CTR), with the soil coupling and a perturbed run (IPR). The perturbation consists on a mask of land use created from the Cropland FAO dataset, where an irrigation water flux of 3 mm/day was applied from 6 A.M. to 9 A.M. every day. The results show that differences between CTR and IPR has a strong daily cycle. The main modifications are on the air masses proprieties, not on to the dynamics. However, changes in the circulation at the boundaries of the Po Valley are observed, and a diagnostic spatial correlation of variable differences shows that soil moisture perturbation explains well the variation observed in the 2 meters height temperature and in the latent heat fluxes.On the other hand, does not explain the spatial shift up and downslope observed during different periods of the day. Given the results, irrigation process affects the atmospheric proprieties on a larger scale than the irrigation, therefore it is important in daily forecast, particularly during hot and dry periods.

A Systems-Level Approach to Human Epileptic Seizures

Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ).

The neurovascular unit as a selective barrier to polymorphonuclear granulocyte (PMN) infiltration into the brain after ischemic injury

The migration of polymorphonuclear granulocytes (PMN) into the brain parenchyma and release of their abundant proteases are considered the main causes of neuronal cell death and reperfusion injury following ischemia. Yet, therapies targeting PMN egress have been largely ineffective. To address this discrepancy we investigated the temporo-spatial localization of PMNs early after transient ischemia in a murine transient middle cerebral artery occlusion (tMCAO) model and human stroke specimens. Using specific markers that distinguish PMN (Ly6G) from monocytes/macrophages (Ly6C) and that define the cellular and basement membrane boundaries of the neurovascular unit (NVU), histology and confocal microscopy revealed that virtually no PMNs entered the infarcted CNS parenchyma. Regardless of tMCAO duration, PMNs were mainly restricted to luminal surfaces or perivascular spaces of cerebral vessels. Vascular PMN accumulation showed no spatial correlation with increased vessel permeability, enhanced expression of endothelial cell adhesion molecules, platelet aggregation or release of neutrophil extracellular traps. Live cell imaging studies confirmed that oxygen and glucose deprivation followed by reoxygenation fail to induce PMN migration across a brain endothelial monolayer under flow conditions in vitro. The absence of PMN infiltration in infarcted brain tissues was corroborated in 25 human stroke specimens collected at early time points after infarction. Our observations identify the NVU rather than the brain parenchyma as the site of PMN action after CNS ischemia and suggest reappraisal of targets for therapies to reduce reperfusion injury after stroke.

Semiparametric Normal Transformation Models for Spatially Correlated Survival Data

There is an emerging interest in modeling spatially correlated survival data in biomedical and epidemiological studies. In this paper, we propose a new class of semiparametric normal transformation models for right censored spatially correlated survival data. This class of models assumes that survival outcomes marginally follow a Cox proportional hazard model with unspecified baseline hazard, and their joint distribution is obtained by transforming survival outcomes to normal random variables, whose joint distribution is assumed to be multivariate normal with a spatial correlation structure. A key feature of the class of semiparametric normal transformation models is that it provides a rich class of spatial survival models where regression coefficients have population average interpretation and the spatial dependence of survival times is conveniently modeled using the transformed variables by flexible normal random fields. We study the relationship of the spatial correlation structure of the transformed normal variables and the dependence measures of the original survival times. Direct nonparametric maximum likelihood estimation in such models is practically prohibited due to the high dimensional intractable integration of the likelihood function and the infinite dimensional nuisance baseline hazard parameter. We hence develop a class of spatial semiparametric estimating equations, which conveniently estimate the population-level regression coefficients and the dependence parameters simultaneously. We study the asymptotic properties of the proposed estimators, and show that they are consistent and asymptotically normal. The proposed method is illustrated with an analysis of data from the East Boston Ashma Study and its performance is evaluated using simulations.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

Cold-season temperatures in the European Alps during the past millennium: variability, seasonality and recent trends

This study presents a proxy-based, quantitative reconstruction of cold-season (mean October to May, TOct–May) air temperatures covering nearly the entire last millennium (AD 1060–2003, some hiatuses). The reconstruction was based on subfossil chrysophyte stomatocyst remains in the varved sediments of high-Alpine Lake Silvaplana, eastern Swiss Alps (46°27’N, 9°48′W, 1791 m a.s.l.). Previous studies have demonstrated the reliability of this proxy by comparison to meteorological data. Cold-season air temperatures could therefore be reconstructed quantitatively, at a high resolution (5-yr) and with high chronological accuracy. Spatial correlation analysis suggests that the reconstruction reflects cold season climate variability over the high- Alpine region and substantial parts of central and western Europe. Cold-season temperatures were characterized by a relatively stable first part of the millennium until AD 1440 (2σ of 5-yr mean values = 0.7 °C) and highly variable TOct–May after that (AD 1440–1900, 2σ of 5-yr mean values = 1.3 °C). Recent decades (AD, 1991-present) were unusually warm in the context of the last millennium (exceeding the 2σ-range of the mean decadal TOct–May) but this warmth was not unprecedented. The coolest decades occurred from AD 1510–1520 and AD 1880–1890. The timing of extremely warm and cold decades is generally in good agreement with documentary data representing Switzerland and central European lowlands. The transition from relatively stable to highly variable TOct–May coincided with large changes in atmospheric circulation patterns in the North Atlantic region. Comparison of reconstructed cold season temperatures to the North Atlantic Oscillation index (NAO) during the past 1000 years showed that the relatively stable and warm conditions at the study site until AD 1440 coincided with a persistent positive mode of the NAO. We propose that the transition to large TOct–May variability around AD 1440 was linked to the subsequent absence of this persistent zonal flow pattern, which would allow other climatic drivers to gain importance in the study area. From AD 1440–1900, the similarity of reconstructed TOct–May to reconstructed air pressure in the Siberian High suggests a relatively strong influence of continental anticyclonic systems on Alpine cold season climate parameters during periods when westerly airflow was subdued. A more continental type of atmospheric circulation thus seems to be characteristic for the Little Ice Age in Europe. Comparison of Toct–May to summer temperature reconstructions from the same study site shows that, as expected, summer and cold season temperature trends and variability differed completely throughout nearly the entire last 1000 years. Since AD 1980, however, summer and cold season temperatures show a simultaneous, strong increase, which is unprecedented in the context of the last millennium. We suggest that the most likely explanation for this recent trend is anthropogenic greenhouse gas (GHG) forcing.

Temperature and precipitation signal in two Alpine ice cores over the period 1961-2001

Water stable isotope ratios and net snow accumulation in ice cores are commonly interpreted as temperature or precipitation proxies. However, only in a few cases has a direct calibration with instrumental data been attempted. In this study we took advantage of the dense network of observations in the European Alpine region to rigorously test the relationship of the annual and seasonal resolved proxy data from two highly resolved ice cores with local temperature and precipitation. We focused on the time period 1961–2001 with the highest amount and quality of meteorological data and the minimal uncertainty in ice core dating (±1 year). The two ice cores were retrieved from the Fiescherhorn glacier (northern Alps, 3900 m a.s.l.), and Grenzgletscher (southern Alps, 4200 m a.s.l.). A parallel core from the Fiescherhorn glacier allowed assessing the reproducibility of the ice core proxy data. Due to the orographic barrier, the two flanks of the Alpine chain are affected by distinct patterns of precipitation. The different location of the two glaciers therefore offers a unique opportunity to test whether such a specific setting is reflected in the proxy data. On a seasonal scale a high fraction of δ18O variability was explained by the seasonal cycle of temperature (~60% for the ice cores, ~70% for the nearby stations of the Global Network of Isotopes in Precipitation – GNIP). When the seasonality is removed, the correlations decrease for all sites, indicating that factors other than temperature such as changing moisture sources and/or precipitation regimes affect the isotopic signal on this timescale. Post-depositional phenomena may additionally modify the ice core data. On an annual scale, the δ18O/temperature relationship was significant at the Fiescherhorn, whereas for Grenzgletscher this was the case only when weighting the temperature with precipitation. In both cases the fraction of interannual temperature variability explained was ~20%, comparable to the values obtained from the GNIP stations data. Consistently with previous studies, we found an altitude effect for the δ18O of −0.17‰/100 m for an extended elevation range combining data of the two ice core sites and four GNIP stations. Significant correlations between net accumulation and precipitation were observed for Grenzgletscher during the entire period of investigation, whereas for Fiescherhorn this was the case only for the less recent period (1961–1977). Local phenomena, probably related to wind, seem to partly disturb the Fiescherhorn accumulation record. Spatial correlation analysis shows the two glaciers to be influenced by different precipitation regimes, with the Grenzgletscher reflecting the characteristic precipitation regime south of the Alps and the Fiescherhorn accumulation showing a pattern more closely linked to northern Alpine stations.

Multiple tree-ring proxies (earlywood width, latewood width and δ13C) from pedunculate oak (Quercus robur L.), Hungary

The aim of this study was to analyse the effects of climatic factors (i.e. monthly mean temperature and total precipitation) on radial growth (earlywood width, latewood width, and total ringwidth) and on latewood stable carbon isotope composition in a pedunculate oak (Quercus robur L) stand in northeastern Hungary. Earlywood widths showed the weakest common variance and lack of statistically significant relationship to monthly precipitation and temperature. Latewood width showed the strongest common chronological signal. Correlation analysis with the monthly climate series pointed out the strongest positive/negative correlation with June precipitation for latewood width/stable carbon isotope ratio. These parameters shared the strongest climatic response also for seasonal scale since the highest correlation coefficients, 0.49 and -0.62 for latewood width and stable carbon isotope ratio, respectively, were obtained for both with a 10-month precipitation total (from previous November to current August of the growing season). A combined parameter, derived as difference between latewood width and stable carbon isotope indices showed improved statistical relationship compared to the hydroclimatic calibration target both for local and regional spatial scales. Spatial correlation analysis indicated that the hydroclimatic signal encoded in these moisture sensitive tree-ring parameters from Bakta Forest is expected to be representative for the northeastern Carpathians and for the large part of the Great Hungarian Plain. In addition, the hydroclimatic signal of latewood width chronology was compared to three independent records. Results showed that neither the strength nor the rank of the similarity of the local hydroclimate signals were stable throughout the past two centuries. Future palaeo(hydro)climatological efforts targeting the Carpathian(-Balkan) region are recommended to track carefully the spatial domains for which a given, local, proxy-derived hydroclimate reconstruction might provide useful information.

Establishing the skill of climate field reconstruction techniques for precipitation with pseudoproxy experiments

This study aims at assessing the skill of several climate field reconstruction techniques (CFR) to reconstruct past precipitation over continental Europe and the Mediterranean at seasonal time scales over the last two millennia from proxy records. A number of pseudoproxy experiments are performed within the virtual reality ofa regional paleoclimate simulation at 45 km resolution to analyse different aspects of reconstruction skill. Canonical Correlation Analysis (CCA), two versions of an Analog Method (AM) and Bayesian hierarchical modeling (BHM) are applied to reconstruct precipitation from a synthetic network of pseudoproxies that are contaminated with various types of noise. The skill of the derived reconstructions is assessed through comparison with precipitation simulated by the regional climate model. Unlike BHM, CCA systematically underestimates the variance. The AM can be adjusted to overcome this shortcoming, presenting an intermediate behaviour between the two aforementioned techniques. However, a trade-off between reconstruction-target correlations and reconstructed variance is the drawback of all CFR techniques. CCA (BHM) presents the largest (lowest) skill in preserving the temporal evolution, whereas the AM can be tuned to reproduce better correlation at the expense of losing variance. While BHM has been shown to perform well for temperatures, it relies heavily on prescribed spatial correlation lengths. While this assumption is valid for temperature, it is hardly warranted for precipitation. In general, none of the methods outperforms the other. All experiments agree that a dense and regularly distributed proxy network is required to reconstruct precipitation accurately, reflecting its high spatial and temporal variability. This is especially true in summer, when a specifically short de-correlation distance from the proxy location is caused by localised summertime convective precipitation events.

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.

AMS and EBSD maps of rock salt - lamprophyre dyke contact zone, Loule diapir, Algarve basin, Portugal

A rock salt-lamprophyre dyke contact zone (sub-vertical, NE-SW strike) was investigated for its petrographic, mechanic and physical properties by means of anisotropy of magnetic susceptibility (AMS) and rock magnetic properties, coupled with quantitative microstructural analysis and thermal mathematical modelling. The quantitative microstructural analysis of halite texture and solid inclusions revealed good spatial correlation with AMS and halite fabrics. The fabrics of both lamprophyre and rock salt record the magmatic intrusion, "plastic" flow and regional deformation (characterized by a NW-SE trending steep foliation). AMS and microstructural analysis revealed two deformation fabrics in the rock salt: (1) the deformation fabrics in rock salt on the NW side of the dyke are associated with high temperature and high fluid activity attributed to the dyke emplacement; (2) On the opposite side of the dyke, the emplacement-related fabric is reworked by localized tectonic deformation. The paleomagnetic results suggest significant rotation of the whole dyke, probably during the diapir ascent and/or the regional Tertiary to Quaternary deformation.

Agglomeration versus Fragmentation:A Comparison of East Asia and Europe

Inspired by the observed contrasting patterns of industrial distribution in East Asia and Europe, this paper conducts an empirical clarification of the difference in spatial relationships among countries within a region for the electric machinery industry by use of spatial econometric analysis. The results indicate that, while production in the electric machinery industry in a country is positively correlated with that of neighboring countries in East Asia, there is no significant spatial correlation in Europe. Such a difference in spatial interdependence has important implications for economic development in those regions.

Simulation Model for Sea Clutter in Airborne Radars

This paper presents the architecture and the methods used to dynamically simulate the sea backscatter of an airborne radar operating in a medium repetition frequency mode (MPRF). It offers a method of generating a sea backscatter signal which fulfills the intensity statistics of real clutter in time domain, spatial correlation and local Doppler spectrum of real data. Three antenna channels (sum, guard and difference) and their cross-correlation properties are simulated. The objective of this clutter generator is to serve as the signal source for the simulation of complex airborne pulsed radar signal processors