RETINOBLASTOMA RELATED1 Regulates Asymmetric Cell Divisions in Arabidopsis.

Formative, also called asymmetric, cell divisions produce daughter cells with different identities. Like other divisions, formative divisions rely first of all on the cell cycle machinery with centrally acting cyclin-dependent kinases (CDKs) and their cyclin partners to control progression through the cell cycle. However, it is still largely obscure how developmental cues are translated at the cellular level to promote asymmetric divisions. Here, we show that formative divisions in the shoot and root of the flowering plant Arabidopsis thaliana are controlled by a common mechanism that relies on the activity level of the Cdk1 homolog CDKA;1, with medium levels being sufficient for symmetric divisions but high levels being required for formative divisions. We reveal that the function of CDKA;1 in asymmetric cell divisions operates through a transcriptional regulation system that is mediated by the Arabidopsis Retinoblastoma homolog RBR1. RBR1 regulates not only cell cycle genes, but also, independent of the cell cycle transcription factor E2F, genes required for formative divisions and cell fate acquisition, thus directly linking cell proliferation with differentiation. This mechanism allows the implementation of spatial information, in the form of high kinase activity, with intracellular gating of developmental decisions.

Impact of increasing mean air temperature on the development of rice and red rice

The objective of this study was to assess the development response of cultivated rice and red rice to different increases in minimum and maximum daily air temperatures, in Santa Maria, Rio Grande do Sul State, Brazil. One hundred years climate scenarios of temperatures 0, +1, +2, +3, +4, and +5ºC, with symmetric and asymmetric increases in minimum and maximum daily air temperatures were created, using the LARS-WG Weather Generator, and a 1969-2003 database. Nine cultivated rice genotypes (IRGA 421, IRGA 416, IRGA 417, IRGA 420, BRS 7 TAIM, BR-IRGA 409, EPAGRI 109, EEA 406 and a hybrid), and two red rice biotypes (awned black hull-ABHRR, and awned yellow hull-AYHRR) were used. The dates of panicle differentiation (R1), anthesis (R4), and all grains with brown hulls (R9) were estimated with a nonlinear simulation model. Overall, the duration of the emergence-R1 phase decreased, whereas the duration of the R1-R4 and R4-R9 phases most often increased, as temperature increased in the climate change scenarios. The simulated rice development response to elevated temperature was not the same, when the increase in minimum and maximum temperature was symmetric or asymmetric.

Dispersal and Inbreeding Avoidance.

Using a game-theoretical approach, we investigate the dispersal patterns expected if inbreeding avoidance were the only reason for dispersal. The evolutionary outcome is always complete philopatry by one sex. The rate of dispersal by the other sex depends on patch size and mating system, as well as inbreeding and dispersal costs. If such costs are sex independent, then two stable equilibria coexist (male or female philopatry), with symmetric domains of attraction. Which sex disperses is determined entirely by history, genetic drift, and gene flow. An asymmetry in costs makes one domain of attraction extend at the expense of the other. In such a case, the dispersing sex might also be, paradoxically, the one that incurs the higher dispersal costs. As asymmetry increases, one equilibrium eventually disappears, which may result in a sudden evolutionary shift in the identity of the dispersing sex. Our results underline the necessity to control for phylogenetic relationships (e.g., through the use of independent-comparisons methods) when investigating empirical trends in dispersal. Our model also makes quantitative predictions on the rate of dispersal by the dispersing sex and suggests that inbreeding avoidance may only rarely be the sole reason for dispersal.

Energy balance measurements over a banana orchard in the Semiarid region in the Northeast of Brazil

The objective of this work was to evaluate the reliability of eddy covariance measurements, analyzing the energy balance components, evapotranspiration and energy balance closure in dry and wet growing seasons, in a banana orchard. The experiment was carried out at a farm located within the irrigation district of Quixeré, in the Lower Jaguaribe basin, in Ceará state, Brazil. An eddy covariance system was used to measure the turbulent flux. An automatic weather station was installed in a grass field to obtain the reference evapotranspiration (ET0) from the combined FAO-Penman-Monteith method. Wind speed and vapor pressure deficit are the most important variables on the evaporative process in both growing seasons. In the dry season, the heat fluxes have a similar order of magnitude, and during the wet season the latent heat flux is the largest. The eddy covariance system had acceptable reliability in measuring heat flux, with actual evapotranspiration results comparing well with those obtained by using the water balance method. The energy balance closure had good results for the study area, with mean values of 0.93 and 0.86 for the dry and wet growing seasons respectively.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

Produtividade simulada de tubérculos de batata em cenários de mudanças climáticas

The objective of this study was to simulate potato (Solanum tuberosum) tuber yield in different climate change scenarios of increased carbon dioxide concentration [CO2] and air temperature, considering symmetric and asymmetric increases in minimum and maximum daily air temperatures. Spitters model was used to simulate Asterix cultivar tuber yield considering two growing seasons (spring and fall) recommended for Santa Maria, state of Rio Grande do Sul, Brazil. In each growing season, five planting dates were evaluated in climate scenarios of a hundred years with no increase in [CO2] and temperature (current scenario), and in scenarios with doubling [CO2] and temperature increases of 0, 1, 2, 3, 4, 5 and 6ºC. A symmetric increase of 4ºC and an asymmetric increase of 5ºC in air temperature offset the yield beneficial effect of increasing [CO2] during spring, whereas increase in air temperature does not affect potato tuber yield during fall. Anticipating planting date in spring and delaying it in fall decrease the negative impact of the increasing air temperature on potato tuber yield.

J2 effect and elliptic inclined periodic orbits in the collision three-body problem

The existence of a new class of inclined periodic orbits of the collision restricted three-body problem is shown. The symmetric periodic solutions found are perturbations of elliptic kepler orbits and they exist only for special values of the inclination and are related to the motion of a satellite around an oblate planet

Maize leaf development under climate change scenarios

The objective of this work was to simulate maize leaf development in climate change scenarios at Santa Maria, RS, Brazil, considering symmetric and asymmetric increases in air temperature. The model of Wang & Engel for leaf appearance rate (LAR), with genotype-specific coefficients for the maize variety BRS Missões, was used to simulate tip and expanded leaf accumulated number from emergence to flag leaf appearance and expansion, for nine emergence dates from August 15 to April 15. LAR model was run for each emergence date in 100-year climate scenarios: current climate, and +1, +2, +3, +4 and +5°C increase in mean air temperature, with symmetric and asymmetric increase in daily minimum and maximum air temperature. Maize crop failure due to frost decreased in elevated temperature scenarios, in the very early and very late emergence dates, indicating a lengthening in the maize growing season in warmer climates. The leaf development period in maize was shorter in elevated temperature scenarios, with greater shortening in asymmetric temperature increases, indicating that warmer nights accelerate vegetative development in maize.

A numeric model to simulate solar individual ultraviolet exposure.

Exposure to solar ultraviolet (UV) light is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors. Individual exposure data remain scarce and development of alternative assessment methods is greatly needed. We developed a model simulating human exposure to solar UV. The model predicts the dose and distribution of UV exposure received on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop a rendering engine that estimates the solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by each triangle was calculated, taking into account reflected, direct and diffuse radiation, and shading from other body parts. Dosimetric measurements (n = 54) were conducted in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model provides a tool to assess outdoor occupational and recreational UV exposures, without necessitating time-consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research.

Persistence of cognitive impairment and its negative impact on psychosocial functioning in lithium-treated, euthymic bipolar patients: a 6-year follow-up study.

BACKGROUND: Previous cross-sectional studies report that cognitive impairment is associated with poor psychosocial functioning in euthymic bipolar patients. There is a lack of long-term studies to determine the course of cognitive impairment and its impact on functional outcome. Method A total of 54 subjects were assessed at baseline and 6 years later; 28 had DSM-IV TR bipolar I or II disorder (recruited, at baseline, from a Lithium Clinic Program) and 26 were healthy matched controls. They were all assessed with a cognitive battery tapping into the main cognitive domains (executive function, attention, processing speed, verbal memory and visual memory) twice over a 6-year follow-up period. All patients were euthymic (Hamilton Rating Scale for Depression score lower than 8 and Young mania rating scale score lower than 6) for at least 3 months before both evaluations. At the end of follow-up, psychosocial functioning was also evaluated by means of the Functioning Assessment Short Test. RESULTS: Repeated-measures multivariate analysis of covariance showed that there were main effects of group in the executive domain, in the inhibition domain, in the processing speed domain, and in the verbal memory domain (p<0.04). Among the clinical factors, only longer illness duration was significantly related to slow processing (p=0.01), whereas strong relationships were observed between impoverished cognition along time and poorer psychosocial functioning (p<0.05). CONCLUSIONS: Executive functioning, inhibition, processing speed and verbal memory were impaired in euthymic bipolar out-patients. Although cognitive deficits remained stable on average throughout the follow-up, they had enduring negative effects on psychosocial adaptation of patients.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Inferring ultraviolet anatomical exposure patterns while distinguishing the relative contribution of radiation components

Exposure to solar ultraviolet (UV) radiation is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors, but individual exposure data remain scarce. UV irradiance is monitored via different techniques including ground measurements and satellite observations. However it is difficult to translate such observations into human UV exposure or dose because of confounding factors (shape of the exposed surface, shading, behavior, etc.) A collaboration between public health institutions, a meteorological office and an institute specialized in computing techniques developed a model predicting the dose and distribution of UV exposure on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop this tool, which estimates solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by various body locations is computed for direct, diffuse and reflected radiation separately. The radiation components are deduced from corresponding measurements of UV irradiance, and the related UV dose received by each triangle of the virtual manikin is computed accounting for shading by other body parts and eventual protection measures. The model was verified with dosimetric measurements (n=54) in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model allows assessing outdoor occupational and recreational UV exposures, without necessitating time-consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research. Using this tool, we investigated solar UV exposure patterns with respect to the relative contribution of the direct, diffuse and reflected radiation. We assessed exposure doses for various body parts and exposure scenarios of a standing individual (static and dynamic postures). As input, the model used erythemally-weighted ground irradiance data measured in 2009 at Payerne, Switzerland. A year-round daily exposure (8 am to 5 pm) without protection was assumed. For most anatomical sites, mean daily doses were high (typically 6.2-14.6 SED) and exceeded recommended exposure values. Direct exposure was important during specific periods (e.g. midday during summer), but contributed moderately to the annual dose, ranging from 15 to 24% for vertical and horizontal body parts, respectively. Diffuse irradiation explained about 80% of the cumulative annual exposure dose. Acute diffuse exposures were also obtained for cloudy summer days. The importance of diffuse UV radiation should not be underestimated when advocating preventive measures. Messages focused on avoiding acute direct exposures may be of limited efficiency to prevent skin cancers associated with chronic exposure (e.g., squamous cell carcinomas).

Computational and Energy Costs of Cryptographic Algorithms on Handheld Devices

Networks are evolving toward a ubiquitous model in which heterogeneousdevices are interconnected. Cryptographic algorithms are required for developing securitysolutions that protect network activity. However, the computational and energy limitationsof network devices jeopardize the actual implementation of such mechanisms. In thispaper, we perform a wide analysis on the expenses of launching symmetric and asymmetriccryptographic algorithms, hash chain functions, elliptic curves cryptography and pairingbased cryptography on personal agendas, and compare them with the costs of basic operatingsystem functions. Results show that although cryptographic power costs are high and suchoperations shall be restricted in time, they are not the main limiting factor of the autonomyof a device.

A Secure and Anonymous Cooperative Sensing Protocol for Cognitive Radio Networks

Spectrum is an essential resource for the provision of mobile services. In order to control and delimit its use, governmental agencies set up regulatory policies. Unfortunately, such policies have led to a deficiency of spectrum as only few frequency bands are left unlicensed, and these are used for the majority of new emerging wireless applications. One promising way to alleviate the spectrum shortage problem is adopting a spectrum sharing paradigm in which frequency bands are used opportunistically. Cognitive radio is the key technology to enable this shift of paradigm.Cognitive radio networks are self-organized systems in which devices cooperate to use those spectrum ranges that are not occupied by licensed users. They carry out spectrum sensing in order to detect vacant channels that can be used for communication. Even though spectrum sensing is an active area of research, an important issue remains unsolved: the secure authentication of sensing reports. Not providing security enables the input of false data in the system thus empowering false results. This paper presents a distributed protocol based on wireless physical layer security, symmetric cryptography and one-way functions that allows determining a final sensing decision from multiple sources in a quick and secure way, as well as it preserves users¿ privacy.

ZigBee/ZigBee PRO security assessment based on compromised cryptographic keys

Sensor networks have many applications in monitoring and controlling of environmental properties such as sound, acceleration, vibration and temperature. Due to limitedresources in computation capability, memory and energy, they are vulnerable to many kinds of attacks. The ZigBee specification based on the 802.15.4 standard, defines a set of layers specifically suited to sensor networks. These layers support secure messaging using symmetric cryptographic. This paper presents two different ways for grabbing the cryptographic key in ZigBee: remote attack and physical attack. It also surveys and categorizes some additional attacks which can be performed on ZigBee networks: eavesdropping, spoofing, replay and DoS attacks at different layers. From this analysis, it is shown that some vulnerabilities still in the existing security schema in ZigBee technology.