A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

Herbicide distribution in soils of a riparian forest and neighboring sugar cane field

Riparian forests are protected by Brazilian law to preserve rivers and their margins. A sugar cane field adjacent to a strip of young riparian forest bordering an older riparian forest along a stream was used to study the riparian forest as a buffer zone to prevent pesticides pollution. Concentrations of the herbicides diuron, hexazinone and tebuthiuron were determined in different soil layers of a Red Yellow Oxisol during 2003 and 2004. The determination was done by High Performance Liquid Chromatography with reverse phase C-18 column, through two mobile phases. Diuron and hexazinone concentration diminished between the sugar cane and riparian forest as buffer strip demonstrating a protective effect. However, tebuthiuron had about four times higher concentrations in the old riparian forest compared to the other areas. Concentrations were higher in the surface and decreased in deeper soil layers in the old riparian forest suggesting that this herbicide probably was introduced by air pollution. This pesticide concentrated in the canopy could be washed by rain to the soil adjacent to the stream. Our data suggest that climate conditions were responsible for enhanced volatilization exposing the old riparian forest to more air pollution that was captured by the higher canopy. (C) 2010 Elsevier B.V. All rights reserved.

Time stability of soil water storage measured by neutron probe and the effects of calibration procedures in a small watershed

The knowledge of soil water storage (SWS) of soil profiles is crucial for the adoption of vegetation restoration practices. With the aim of identifying representative sites to obtain the mean SWS of a watershed, a time stability analysis of neutron probe evaluations of SWS was performed by the means of relative differences and Spearman rank correlation coefficients. At the same time, the effects of different neutron probe calibration procedures were explored on time stability analysis. mean SWS estimation. and preservation of the spatial variability of SWS. The selected watershed, with deep gullies and undulating slopes which cover an area of 20 ha, is characterized by an Ust-Sandiic Entisol and an Aeolian sandy soil. The dominant vegetation species are bunge needlegrass (Stipa bungeana Trim) and korshinsk peashrub (Carugano Korshinskii kom.). From June 11, 2007 to July 23,2008, SWS of the top1 m soil layer was evaluated for 20 dates, based on neutron probe data of 12 sampling sites. Three calibration procedures were employed: type 1, most complete, with each site having its own linear calibration equation (TrE); type II. with TrE equations extended over the whole field: and type III, with one single linear calibration curve for the whole field (UnE) and also correcting its intercept based on site specific relative difference analysis (RdE) and on linear fitting of data (RcE), both maintaining the same slope. A strong time stability of SWS estimated by TrE equations was identified. Soil particle size and soil organic matter content were recognized as the influencing factors for spatial variability of SWS. Land use influenced neither the spatial variability nor the time stability of SWS. Time stability analysis identified one site to represent the mean SWS of the whole watershed with mean absolute percentage errors of less than 10%, therefore. this site can be used as a predictor for the mean SWS of the watershed. Some equations of type II were found to be unsatisfactory to yield reliable mean SWS values or in preserving the associated soil spatial variability. Hence, it is recommended to be cautious in extending calibration equations to other sites since they might not consider the field variability. For the equations with corrected intercept (type III), which consider the spatial variability of calibration in a different way in relation to TrE, it was found that they can yield satisfactory means and standard deviation of SWS, except for the RdE equations, which largely leveled off the SWS values in the watershed. Correlation analysis showed that the neutron probe calibration was linked to soil bulk density and to organic matter content. Therefore, spatial variability of soil properties should be taken into account during the process of neutron probe calibration. This study provides useful information on the mean SWS observation with a time stable site and on distinct neutron probe calibration procedures, and it should be extended to soil water management studies with neutron probes, e.g., the process of vegetation restoration in wider area and soil types of the Loess Plateau in China. (C) 2009 Elsevier B.V. All rights reserved.

Spatio-temporal variability behavior of land surface soil water content in shrub- and grass-land

The knowledge of the relationship between spatial variability of the surface soil water content (theta) and its mean across a spatial domain (theta(m)) is crucial for hydrological modeling and understanding soil water dynamics at different scales. With the aim to compare the soil moisture dynamics and variability between the two land uses and to explore the relationship between the spatial variability of theta and theta(m), this study analyzed sets of surface theta measurements performed with an impedance soil moisture probe, collected 136 times during a period of one year in two transects covering different land uses, i.e., korshinsk peashrub transect (KPT) and bunge needlegrass transect (BNT), in a watershed of the Loess Plateau, China. Results showed that the temporal pattern of theta behaved similarly for the two land uses, with both relative wetter soils during wet period and relative drier soils during dry period recognized in BNT. Soil moisture tended to be temporally stable among different dates, and more stable patterns could be observed for dates with more similar soil water conditions. The magnitude of the spatial variation of theta in KPT was greater than that in ENT. For both land uses, the standard deviation (SD) of theta in general increased as theta(m) increased, a behavior that could be well described with a natural logarithmic function. Convex relationship of CV and theta(m) and the maximum CV for both land uses (43.5% in KPT and 41.0% in BNT) can, therefore, be ascertained. Geostatistical analysis showed that the range in KPT (9.1 m) was shorter than that in BNT (15.1 m). The nugget effects, the structured variability, hence the total variability increased as theta(m) increased. For both land uses, the spatial dependency in general increased with increasing theta(m). 2011 Elsevier B.V. All rights reserved.

Performance of a multi-level TDR system exposed to tropical field conditions - A time-space comparison with tensiometry

Time-domain reflectometry (TDR) is an important technique to obtain series of soil water content measurements in the field. Diode-segmented probes represent an improvement in TDR applicability, allowing measurements of the soil water content profile with a single probe. In this paper we explore an extensive soil water content dataset obtained by tensiometry and TDR from internal drainage experiments in two consecutive years in a tropical soil in Brazil. Comparisons between the variation patterns of the water content estimated by both methods exhibited evidences of deterioration of the TDR system during this two year period at field conditions. The results showed consistency in the variation pattern for the tensiometry data, whereas TDR estimates were inconsistent, with sensitivity decreasing over time. This suggests that difficulties may arise for the long-term use of this TDR system under tropical field conditions. (c) 2008 Elsevier B.V. All rights reserved.

Estimating hourly net radiation for leaf wetness duration using the Penman-Monteith equation

Leaf wetness duration (LWD) is related to plant disease occurrence and is therefore a key parameter in agrometeorology. As LWD is seldom measured at standard weather stations, it must be estimated in order to ensure the effectiveness of warning systems and the scheduling of chemical disease control. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results for operational use. However, the requirement of net radiation (Rn) is a disadvantage foroperational physical models, since this variable is usually not measured over crops or even at standard weather stations. With the objective of proposing a solution for this problem, this study has evaluated the ability of four models to estimate hourly Rn and their impact on LWD estimates using a Penman-Monteith approach. A field experiment was carried out in Elora, Ontario, Canada, with measurements of LWD, Rn and other meteorological variables over mowed turfgrass for a 58 day period during the growing season of 2003. Four models for estimating hourly Rn based on different combinations of incoming solar radiation (Rg), airtemperature (T), relative humidity (RH), cloud cover (CC) and cloud height (CH), were evaluated. Measured and estimated hourly Rn values were applied in a Penman-Monteith model to estimate LWD. Correlating measured and estimated Rn, we observed that all models performed well in terms of estimating hourly Rn. However, when cloud data were used the models overestimated positive Rn and underestimated negative Rn. When only Rg and T were used to estimate hourly Rn, the model underestimated positive Rn and no tendency was observed for negative Rn. The best performance was obtained with Model I, which presented, in general, the smallest mean absolute error (MAE) and the highest C-index. When measured LWD was compared to the Penman-Monteith LWD, calculated with measured and estimated Rn, few differences were observed. Both precision and accuracy were high, with the slopes of the relationships ranging from 0.96 to 1.02 and R-2 from 0.85 to 0.92, resulting in C-indices between 0.87 and 0.93. The LWD mean absolute errors associated with Rn estimates were between 1.0 and 1.5h, which is sufficient for use in plant disease management schemes.

Genetic variability in S(1) families from different maize populations.

Genetic variability in S(1) families from different maize populations. The objectives of the present work were directed towards the study of genetic: variablilty In seven maize populations with a broad genetic base, as a guide for population improvement. The field evaluation was conducted in completely randomized blocks, at one location (Anhembi, Sao Paulo state) with different groups, of S(1) families Obtained from seven populations (GO-D: dent type, GO-F: flint type, GO-L: long car, GO-G: thick Car; and composites G3, G4 and GO-S). Estimates were obtained for genetic variance (progeny mean basis), phenotypic variance of families means, and coefficient of heritability (broad sense) for progeny means. Estimates of heritability were high for Car weight (0,89 to 0.94), car length (0.77 to 0.88) and car diameter (0.77 to 0.92); and lower for plant height (0.58 to 0.80) and Car height (0.54 to 0.84), thus showing the high Potential of the populations for recurrent selection based oil S, families. Ear yield in the base populations used as controls varied front 11,200 kg ha(-1) (GO-D) to 12,800 kg ha(-1) (G3). The means of S(1) families varied from 6,070 kg ha(-1) (GO-F) to 7,380 kg ha(-1) (G4); the Inbreeding depression in S(1) Families varied front 37.5% (G4) to 48.0% (G3) relative to the non-inbred population.

Development of Ramulosis Disease of Cotton Under Controlled Environment and Field Conditions

Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis disease of cotton, is widespread in Brazil and can cause severe yield loss. Because weather conditions greatly affect disease development, the objective of this work was to develop weather-based models to assess disease favorability. Latent period, incidence, and severity of ramulosis symptoms were evaluated in controlled environment experiments using factorial combinations of temperature (15, 20, 25, 30, and 35 degrees C) and leaf wetness duration (0, 4, 8, 16, 32, and 64 h after inoculation). Severity was modeled as an exponential function of leaf wetness duration and temperature. At the optimum temperature of disease development, 27 degrees C, average latent period was 10 days. Maximum ramulosis severity occurred from 20 to 30 degrees C, with sharp decreases at lower and higher temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. In field experiments at Piracicaba, Sao Paulo State, Brazil, cotton plots were inoculated (10(5) conidia ml(-1)) and ramulosis severity was evaluated weekly. The model obtained from the controlled environment study was used to generate a disease favorability index for comparison with disease progress rate in the field. Hourly measurements of solar radiation, temperature, relative humidity, leaf wetness duration, rainfall, and wind speed were also evaluated as possible explanatory variables. Both the disease favorability model and a model based on rainfall explained ramulosis growth rate well, with R(2) of 0.89 and 0.91, respectively. They are proposed as models of ramulosis development rate on cotton in Brazil, and weather-disease relationships revealed by this work can form the basis of a warning system for ramulosis development.

Bacterial soil community in a Brazilian sugarcane field

The assessment of bacterial communities in soil gives insight into microbial behavior under prevailing environmental conditions. In this context, we assessed the composition of soil bacterial communities in a Brazilian sugarcane experimental field. The experimental design encompassed plots containing common sugarcane (variety SP80-1842) and its transgenic form (IMI-1 - imazapyr herbicide resistant). Plants were grown in such field plots in a completely randomized design with three treatments, which addressed the factors transgene and imazapyr herbicide application. Soil samples were taken at three developmental stages during plant growth and analyzed using 16S ribosomal RNA (rRNA)-based PCR-denaturing gradient gel electrophoresis (PCR-DGGE) and clone libraries. PCR-DGGE fingerprints obtained for the total bacterial community and specific bacterial groups - Actinobacteria, Alphaproteobacteria and Betaproteobacteria - revealed that the structure of these assemblages did not differ over time and among treatments. Nevertheless, slight differences among 16S rRNA gene clone libraries constructed from each treatment could be observed at particular cut-off levels. Altogether, the libraries encompassed a total of eleven bacterial phyla and the candidate divisions TM7 and OP10. Clone sequences affiliated with the Proteobacteria, Actinobacteria, Firmicutes and Acidobacteria were, in this order, most abundant. Accurate phylogenetic analyses were performed for the phyla Acidobacteria and Verrucomicrobia, revealing the structures of these groups, which are still poorly understood as to their importance for soil functioning and sustainability under agricultural practices.

Soil CO(2) emission estimated by different interpolation techniques

Soil CO(2) emissions are highly variable, both spatially and across time, with significant changes even during a one-day period. The objective of this study was to compare predictions of the diurnal soil CO(2) emissions in an agricultural field when estimated by ordinary kriging and sequential Gaussian simulation. The dataset consisted of 64 measurements taken in the morning and in the afternoon on bare soil in southern Brazil. The mean soil CO(2) emissions were significantly different between the morning (4.54 mu mol m(-2) s(-1)) and afternoon (6.24 mu mol m(-2) s(-1)) measurements. However, the spatial variability structures were similar, as the models were spherical and had close range values of 40.1 and 40.0 m for the morning and afternoon semivariograms. In both periods, the sequential Gaussian simulation maps were more efficient for the estimations of emission than ordinary kriging. We believe that sequential Gaussian simulation can improve estimations of soil CO(2) emissions in the field, as this property is usually highly non-Gaussian distributed.

Adapting the CROPGRO perennial forage model to predict growth of Brachiaria brizantha

Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass (Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha(-1), with a RMSE of 538 kg DM ha(-1) (D-Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth. (C) 2010 Elsevier B.V. All rights reserved.

Molecular dynamics, density functional, ADMET predictions, virtual screening, and molecular interaction field studies for identification and evaluation of novel potential CDK2 inhibitors in cancer therapy

In this work, we have used molecular dynamics, density functional theory, virtual screening, ADMET predictions, and molecular interaction field studies to design and propose eight novel potential inhibitors of CDK2. The eight molecules proposed showed interesting structural characteristics that are required for inhibiting the CDK2 activity and show potential as drug candidates for the treatment of cancer. The parameters related to the Rule of Five were calculated, and only one of the molecules violated more than one parameter. One of the proposals and one of the drug-like compounds selected by virtual screening indicated to be promising candidates for CDK2-based cancer therapy.

Molecular dynamics, flexible docking, virtual screening, ADMET predictions, and molecular interaction field studies to design novel potential MAO-B inhibitors

Monoamine oxidase is a flavoenzyme bound to the mitochondrial outer membranes of the cells, which is responsible for the oxidative deamination of neurotransmitter and dietary amines. It has two distinct isozymic forms, designated MAO-A and MAO-B, each displaying different substrate and inhibitor specificities. They are the well-known targets for antidepressant, Parkinson`s disease, and neuroprotective drugs. Elucidation of the x-ray crystallographic structure of MAO-B has opened the way for the molecular modeling studies. In this work we have used molecular modeling, density functional theory with correlation, virtual screening, flexible docking, molecular dynamics, ADMET predictions, and molecular interaction field studies in order to design new molecules with potential higher selectivity and enzymatic inhibitory activity over MAO-B.

The use of transcriptional profiles to predict adult mosquito age under field conditions

Age is a critical determinant of an adult female mosquito's ability to transmit a range of human pathogens. Despite its central importance, relatively few methods exist with which to accurately determine chronological age of field-caught mosquitoes. This fact is a major constraint on our ability to fully understand the relative importance of vector longevity to disease transmission in different ecological contexts. It also limits our ability to evaluate novel disease control strategies that specifically target mosquito longevity. We report the development of a transcriptional profiling approach to determine age of adult female Aedes aegypti under field conditions. We demonstrate that this approach surpasses current cuticular hydrocarbon methods for both accuracy of predicted age as well as the upper limits at which age can be reliably predicted. The method is based on genes that display age-dependent expression in a range of dipteran insects and, as such, is likely to be broadly applicable to other disease vectors.

Reliability and validity of physical fitness field tests for adults aged 55 to 70 years

The aim of this study was to examine the reliability and validity of field tests for assessing physical function in mid-aged and young-old people (55–70 y). Tests were selected that required minimal space and equipment and could be implemented in multiple field settings such as a general practitioner's office. Nineteen participants completed 2 field and 1 laboratory testing sessions. Intra-class correlations showed good reliability for the tests of upper body strength (lift and reach, R= .66), lower body strength (sit to stand, R= .80) and functional capacity (Canadian Step Test, R= .92), but not for leg power (single timed chair rise, R= .28). There was also good reliability for the balance test during 3 stances: parallel (94.7% agreement), semi-tandem (73.7%), and tandem (52.6%). Comparison of field test results with objective laboratory measures found good validity for the sit to stand (cf 1RM leg press, Pearson r= .68, p< .05), and for the step test (cf PWC140, r= −.60, p< .001), but not for the lift and reach (cf 1RM bench press, r= .43, p> .05), balance (r= −.13, −.18, .23) and rate of force development tests (r= −.28). It was concluded that the lower body strength and cardiovascular function tests were appropriate for use in field settings with mid-aged and young-old adults.