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.

Report on a special investigation of the Mills County Treasurer’s Office for the period January 1, 2005 through March 31, 2011

Report on a special investigation of the Mills County Treasurer’s Office for the period January 1, 2005 through March 31, 2011

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.

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.

Audit report on Mills County, Iowa for the year ended June 30, 2012

Audit report on Mills County, Iowa for the year ended June 30, 2012

Audit report on Mills County, Iowa for the year ended June 30, 2004

Audit report on Mills County, Iowa for the year ended June 30, 2012

Audit report on Mills County, Iowa for the year ended June 30, 2005

Audit report on Mills County, Iowa for the year ended June 30, 2012

Audit report on Mills County, Iowa for the year ended June 30, 2007

Audit report on Mills County, Iowa for the year ended June 30, 2007

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.

Iowa Development of Rubblized Concrete Pavement Base - Mills County, HR-315, 1995

Iowa counties have tried to rehabilitate deteriorating portland cement concrete (PCC) pavements with standard overlays, placement of engineering fabric, rock, open graded bituminous mixes and cracking and seating. While these methods prolong the life of the road, the cracks in the old pavement have eventually reflected to the surface. One possible alternative for rehabilitating severely deteriorated roads and preventing reflective cracking is the rubblization process. The objective of this research project was to rehabilitate and evaluate a severely deteriorated PCC roadway using a rubblization process. A 3.0 km (1.9 mi) section of L63 in Mills County was selected for this research. The road was divided into 16 sections. A resonate frequency vibration pavement breaker was used to rubblize the existing pavement. The variables of rubblization, drainage, and ACC overlay depths of 75 mm (3 in.), 100 mm (4 in.), and 125 mm (5 in.) were evaluated. The research on rubblized concrete pavement bases support the following conclusions: (1) The rubblization process prevents reflective cracking; (2) Edge drains improved the structural rating of the rubblized roadway; (3) An ACC overlay of 125 mm (5 in.) on a rubblized base provided an excellent roadway regardless of soil and drainage conditions; (4) An ACC overlay of 75 mm (3 in.) on a rubblized base can provide a good roadway if the soil structure below the rubblized base is stable and well drained; and (5) The Road Rater structural ratings of the rubblized test sections for this project are comparable to the nonrubblized test sections.

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.