SPATIAL DEPENDENCE OF ELECTRICAL CONDUCTIVITY AND CHEMICAL PROPERTIES OF THE SOIL BY ELECTROMAGNETIC INDUCTION

Brazilian soils have natural high chemical variability; thus, apparent electrical conductivity (ECa) can assist interpretation of crop yield variations. We aimed to select soil chemical properties with the best linear and spatial correlations to explain ECa variation in the soil using a Profiler sensor (EMP-400). The study was carried out in Sidrolândia, MS, Brazil. We analyzed the following variables: electrical conductivity - EC (2, 7, and 15 kHz), organic matter, available K, base saturation, and cation exchange capacity (CEC). Soil ECa was measured with the aid of an all-terrain vehicle, which crossed the entire area in strips spaced at 0.45 m. Soil samples were collected at the 0-20 cm depth with a total of 36 samples within about 70 ha. Classical descriptive analysis was applied to each property via SAS software, and GS+ for spatial dependence analysis. The equipment was able to simultaneously detect ECa at the different frequencies. It was also possible to establish site-specific management zones through analysis of correlation with chemical properties. We observed that CEC was the property that had the best correlation with ECa at 15 kHz.

Meissner effect and critical fields in an inhomogeneous Ba2HoCu3O7-x high-Tc superconductor

The Meissner and diamagnetic shielding effects and the upper, lower, and thermodynamical critical fields have been studied in a Ba2HoCu3O7-x sample using magnetization measurements in fields up to 55 kOe. The diamagnetic shielding curve shows the existence of a transition at Tc=91.5 K followed by a broad transition extending from 85 to 25 K which may be related to inhomogeneities in the oxygen content of the sample. A rather low flux expulsion (13.5%) is observed which we attribute to flux pinning or trapping. We show that the coexistence of superconducting and nonsuperconducting regions within the sample at temperatures just below Tc leads to strong reductions in the critical magnetic fields.

Molecular Identification of Trichoderma spp. in Garlic and Onion Fields and In Vitro Antagonism Trials on Sclerotium cepivorum

ABSTRACT Trichoderma species are non-pathogenic microorganisms that protect against fungal diseases and contribute to increased crop yields. However, not all Trichoderma species have the same effects on crop or a pathogen, whereby the characterization and identification of strains at the species level is the first step in the use of a microorganism. The aim of this study was the identification – at species level – of five strains of Trichoderma isolated from soil samples obtained from garlic and onion fields located in Costa Rica, through the analysis of the ITS1, 5.8S, and ITS2 ribosomal RNA regions; as well as the determination of their individual antagonistic ability over S. cepivorum Berkeley. In order to distinguish the strains, the amplified products were analyzed using MEGA v6.0 software, calculating the genetic distances through the Tamura-Nei model and building the phylogenetic tree using the Maximum Likelihood method. We established that the evaluated strains belonged to the species T. harzianum and T. asperellum; however it was not possible to identify one of the analyzed strains based on the species criterion. To evaluate their antagonistic ability, the dual culture technique, Bell’s scale, and the percentage inhibition of radial growth (PIRG) were used, evidencing that one of the T. asperellum isolates presented the best yields under standard, solid fermentation conditions.

Investigation of Electromagnetic Gauges for Determining In-Place HMA Density, Final Report, May 2007

Density is an important component of hot-mix asphalt (HMA) pavement quality and long-term performance. Insufficient density of an in-place HMA pavement is the most frequently cited construction-related performance problem. This study evaluated the use of electromagnetic gauges to nondestructively determine densities. Field and laboratory measurements were taken with two electromagnetic gauges—a PaveTracker and a Pavement Quality Indicator (PQI). Test data were collected in the field during and after paving operations and also in a laboratory on field mixes compacted in the lab. This study revealed that several mix- and project-specific factors affect electromagnetic gauge readings. Consequently, the implementation of these gauges will likely need to be done utilizing a test strip on a project- and mix-specific basis to appropriately identify an adjustment factor for the specific electromagnetic gauge being used for quality control and quality assurance (QC/QA) testing. The substantial reduction in testing time that results from employing electromagnetic gauges rather than coring makes it possible for more readings to be used in the QC/QA process with real-time information without increasing the testing costs.

Bilateral Sequential NAION: A Comparison of Visual Outcomes in Fellow Eyes Using Quantitative Analysis of Goldmann Visual Fields

Purpose: Previous studies of the visual outcome in bilateral non-arteritic anterior ischemic optic neuropathy (NAION) have yielded conflicting results, specifically regarding congruity between fellow eyes. Prior studies have used measures of acuity and computerized perimetry but none has compared Goldmann visual field outcomes between fellow eyes. In order to better define the concordance of visual loss in this condition, we reviewed our cases of bilateral sequential NAION, including measures of visual acuity, pupillary function and both pattern and severity of visual field loss.Methods: We performed a retrospective chart review of 102 patients with a diagnosis of bilateral sequential NAION. Of the 102 patients, 86 were included in the study for analysis of final visual outcome between the affected eyes. Visual function was assessed using visual acuity, Goldmann visual fields, color vision and RAPD. A quantitative total visual field score and score per quadrant was analyzed for each eye using the numerical Goldmann visual field scoring method previously described by Esterman and colleagues. Based upon these scores, we calculated the total deviation and pattern deviation between fellow eyes and between eyes of different patients. Statistical significance was determined using nonparametric tests.Results: A statistically significant correlation was found between fellow eyes for multiple parameters, including logMAR visual acuity (P = 0.0101), global visual field (P = 0.0001), superior visual field (P = 0.0001), and inferior visual field (P = 0.0001). In addition, the mean deviation of both total (P = 0.0000000007) and pattern (P = 0.000000004) deviation analyses was significantly less between fellow eyes ("intra"-eyes) than between eyes of different patients ("inter"-eyes).Conclusions: Visual function between fellow eyes showed a fair to moderate correlation that was statistically significant. The pattern of vision loss was also more similar in fellow eyes than between eyes of different patients. These results may help allow better prediction of visual outcome for the second eye in patients with NAION. These findings may also be useful for evaluating efficacy of therapeutic interventions.

Growing The Fields of Opportunity for Children and Adults with Autism in Iowa, 2009-2010

Many would argue that the dramatic rise in autism has reached critical mass, and this council echoes that statement. Iowa, like many states in the nation, is currently ill equipped to handle the large influx of children and adults with autism. When this council was initially formed we were facing diagnosis rates of 1 in 150 and currently the diagnosis rate is 1 in 91. Current resource strains in education, qualified trained professionals, access to care, and financial services are rapidly deteriorating Iowa’s ability to deliver quality services to children, adults, and families affected by autism. If Iowa leadership fails to act quickly the already strained system will face a breaking point in the following areas: financing, coordination of care, educational resources, early identification, adult services, and access to service delivery - just to name a few. This council has taken the past 12 plus months hearing testimony from state officials, providers, and caregivers to ensure that care for those with autism is effective, cost efficient, and accessible. This council will be making recommendations on three major areas; early identification, seamless support/coordination of care, and financing of care. While these areas will be highlighted in this first annual report it in no way minimizes other areas that need to be addressed such as early intervention, special education, training, in-home support services, financing options, and data collection. Implementing the initial recommendations of this council will lay foundational support for the areas mentioned above. Often those in position to help ask what can be done to help families in Iowa. This council has provided a roadmap to help facilitate effective and proven treatments to children and adults with autism.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Deep crustal electromagnetic structure of Bhuj earthquake region (India) and its implications

The existence of fluids and partial melt in the lower crust of the seismically active Kutch rift basin (on the western continental margin of India) owing to underplating has been proposed in previous geological and geophysical studies. This hypothesis is examined using magnetotelluric (MT) data acquired at 23 stations along two profiles across Kutch Mainland Uplift and Wagad Uplift. A detailed upper crustal structure is also presented using twodimensional inversion of MT data in the Bhuj earthquake (2001) area. The prominent boundaries of reflection in the upper crust at 5, 10 and 20 km obtained in previous seismic reflection profiles correlate with conductive structures in our models. The MT study reveals 1-2 km thick Mesozoic sediments under the Deccan trap cover. The Deccan trap thickness in this region varies from a few meters to 1.5 km. The basement is shallow on the northern side compared to the south and is in good agreement with geological models as well as drilling information. The models for these profiles indicate that the thickness of sediments would further increase southwards into the Gulf of Kutch. Significant findings of the present study indicate 1) the hypocentre region of the earthquake is devoid of fluids, 2) absence of melt (that is emplaced during rifting as suggested from the passive seismological studies) in the lower crust and 3) a low resistive zone in the depth range of 5-20 km. The present MT study rules out fluidsand melt (magma) as the causative factors that triggered the Bhuj earthquake. The estimated porosity value of 0.02% will explain 100-500 ohm·m resistivity values observed in the lower crust. Based on the seismic velocities and geochemical studies, presence of garnet is inferred. The lower crust consists of basalts - probably generated by partial melting of metasomatised garnet peridotite at deeper depths in the lithosphere - and their composition might be modified by reaction with the spinel peridotites.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Nutritional status in commercial currant fields

Selostus: Herukkaviljelmien ravinnetila

Radarsat backscattering from an agricultural scene

Orbital remote sensing in the microwave electromagnetic region has been presented as an important tool for agriculture monitoring. The satellite systems in operation have almost all-weather capability and high spatial resolution, which are features appropriated for agriculture. However, for full exploration of these data, an understanding of the relationships between the characteristics of each system and agricultural targets is necessary. This paper describes the behavior of backscattering coefficient (sigma°) derived from calibrated data of Radarsat images from an agricultural area. It is shown that in a dispersion diagram of sigma° there are three main regions in which most of the fields can be classified. The first one is characterized by low backscattering values, with pastures and bare soils; the second one has intermediate backscattering coefficients and comprises well grown crops mainly; and a third one, with high backscattering coefficients, in which there are fields with strong structures causing a kind of double bounce effect. The results of this research indicate that the use of Radarsat images is optimized when a multitemporal analysis is done making the best use of the agricultural calendar and of the dynamics of different cultures.