A Laboratory Investigation into the Effects of the Aggregated Related Facts of Critical VMA in Asphalt Paving Mixtures, June 2000

This report summarizes research conducted at Iowa State University on behalf of the Iowa Department of Transportation, focusing on the volumetric state of hot-mix asphalt (HMA) mixtures as they transition from stable to unstable configurations. This has raditionally been addressed during mix design by meeting a minimum voids in the mineral aggregate (VMA) requirement, based solely upon the nominal maximum aggregate size without regard to other significant aggregate-related properties. The goal was to expand the current specification to include additional aggregate properties, e.g., fineness modulus, percent crushed fine and coarse aggregate, and their interactions. The work was accomplished in three phases: a literature review, extensive laboratory testing, and statistical analysis of test results. The literature review focused on the history and development of the current specification, laboratory methods of identifying critical mixtures, and the effects of other aggregate-related factors on critical mixtures. The laboratory testing involved three maximum aggregate sizes (19.0, 12.5, and 9.5 millimeters), three gradations (coarse, fine, and dense), and combinations of natural and manufactured coarse and fine aggregates. Specimens were compacted using the Superpave Gyratory Compactor (SGC), conventionally tested for bulk and maximum theoretical specific gravities and physically tested using the Nottingham Asphalt Tester (NAT) under a repeated load confined configuration to identify the transition state from sound to unsound. The statistical analysis involved using ANOVA and linear regression to examine the effects of identified aggregate factors on critical state transitions in asphalt paving mixtures and to develop predictive equations. The results clearly demonstrate that the volumetric conditions of an HMA mixture at the stable unstable threshold are influenced by a composite measure of the maximum aggregate size and gradation and by aggregate shape and texture. The currently defined VMA criterion, while significant, is seen to be insufficient by itself to correctly differentiate sound from unsound mixtures. Under current specifications, many otherwise sound mixtures are subject to rejection solely on the basis of failing to meet the VMA requirement. Based on the laboratory data and statistical analysis, a new paradigm to volumetric mix design is proposed that explicitly accounts for aggregate factors (gradation, shape, and texture).

Beaufils ranges to assess the cotton nutrient status in the southern region of Mato Grosso

The relationships between nutrient contents and indices of the Diagnosis and Recommendation Integrated System (DRIS) are a useful basis to determine appropriate ranges for the interpretation of leaf nutrient contents. The purpose of this study was to establish Beaufils ranges from statistical models of the relationship between foliar concentrations and DRIS indices, generated by two systems of DRIS norms - the F value and natural logarithm transformation - and assess the nutritional status of cotton plants, based on these Beaufils ranges. Yield data from plots (average acreage 100 ha) and foliar concentrations of macro and micronutrients of cotton (Gossypium hirsutum r. latifolium) plants, in the growing season 2004/2005, were stored in a database. The criterion to define the reference population consisted of plots with above-average yields + 0.5 standard deviation (over 4,575 kg ha-1 seed cotton yield). The best-fitting statistical model of the relationship between foliar nutrient concentrations and DRIS indices was linear, with R² > 0.8090, p < 0.01, except for N, with R² = 0.5987, p < 0.01. The two criteria were effective to diagnose the plant nutritional status. The diagnoses were not random, but based on the effectiveness of the chi-square-tested method. The agreement between the methods to assess the nutritional status was 92.59-100 %, except for S, with 74.07 % agreement.

Neurogenic subventricular zone stem/progenitor cells are notch1-dependent in their active but not quiescent state.

The adult mammalian forebrain contains neural stem/progenitor cells (NSCs) that generate neurons throughout life. As in other somatic stem cell systems, NSCs are proposed to be predominantly quiescent and proliferate only sporadically to produce more committed progeny. However, quiescence has recently been shown not to be an essential criterion for stem cells. It is not known whether NSCs show differences in molecular dependence based on their proliferation state. The subventricular zone (SVZ) of the adult mouse brain has a remarkable capacity for repair by activation of NSCs. The molecular interplay controlling adult NSCs during neurogenesis or regeneration is not clear but resolving these interactions is critical in order to understand brain homeostasis and repair. Using conditional genetics and fate mapping, we show that Notch signaling is essential for neurogenesis in the SVZ. By mosaic analysis, we uncovered a surprising difference in Notch dependence between active neurogenic and regenerative NSCs. While both active and regenerative NSCs depend upon canonical Notch signaling, Notch1-deletion results in a selective loss of active NSCs (aNSCs). In sharp contrast, quiescent NSCs (qNSCs) remain after Notch1 ablation until induced during regeneration or aging, whereupon they become Notch1-dependent and fail to fully reinstate neurogenesis. Our results suggest that Notch1 is a key component of the adult SVZ niche, promoting maintenance of aNSCs, and that this function is compensated in qNSCs. Therefore, we confirm the importance of Notch signaling for maintaining NSCs and neurogenesis in the adult SVZ and reveal that NSCs display a selective reliance on Notch1 that may be dictated by mitotic state.

Statistical mechanics in the extended Gaussian ensemble

The extended Gaussian ensemble (EGE) is introduced as a generalization of the canonical ensemble. This ensemble is a further extension of the Gaussian ensemble introduced by Hetherington [J. Low Temp. Phys. 66, 145 (1987)]. The statistical mechanical formalism is derived both from the analysis of the system attached to a finite reservoir and from the maximum statistical entropy principle. The probability of each microstate depends on two parameters ß and ¿ which allow one to fix, independently, the mean energy of the system and the energy fluctuations, respectively. We establish the Legendre transform structure for the generalized thermodynamic potential and propose a stability criterion. We also compare the EGE probability distribution with the q-exponential distribution. As an example, an application to a system with few independent spins is presented.

Comparison of three antigenic extracts of Eurotium amstelodami in serological diagnosis of farmer's lung disease.

In France and Finland, farmer's lung disease (FLD), a hypersensitivity pneumonitis common in agricultural areas, is mainly caused by Eurotium species. The presence of antibodies in patients' serum is an important criterion for diagnosis. Our study aimed to improve the serological diagnosis of FLD by using common fungal particles that pollute the farm environment as antigens. Fungal particles of the Eurotium species were observed in handled hay. A strain of Eurotium amstelodami was grown in vitro using selected culture media; and antigen extracts from sexual (ascospores), asexual (conidia), and vegetative (hyphae) forms were made. Antigens were tested by enzyme-linked immunosorbent assay (ELISA), which was used to test for immunoglobulin G antibodies from the sera of 17 FLD patients, 40 healthy exposed farmers, and 20 nonexposed controls. The antigens were compared by receiver operating characteristic analysis, and a threshold was then established. The ascospores contained in asci enclosed within cleistothecia were present in 38% of the hay blades observed; conidial heads of aspergillus were less prevalent. The same protocol was followed to make the three antigen extracts. A comparison of the results for FLD patients and exposed controls showed the area under the curve to be 0.850 for the ascospore antigen, 0.731 for the conidia, and 0.690 for the hyphae. The cutoffs that we determined, with the standard deviation for measures being taken into account, showed 67% for sensitivity and 92% for specificity with the ascospore antigen. In conclusion, the serological diagnosis of FLD by ELISA was improved by the adjunction of ascospore antigen.

Elasticity and melting of vortex crystals in anisotropic superconductors: Beyond the continuum regime.

The elastic moduli of vortex crystals in anisotropic superconductors are frequently involved in the investigation of their phase diagram and transport properties. We provide a detailed analysis of the harmonic eigenvalues (normal modes) of the vortex lattice for general values of the magnetic field strength, going beyond the elastic continuum regime. The detailed behavior of these wave-vector-dependent eigenvalues within the Brillouin zone (BZ), is compared with several frequently used approximations that we also recalculate. Throughout the BZ, transverse modes are less costly than their longitudinal counterparts, and there is an angular dependence which becomes more marked close to the zone boundary. Based on these results, we propose an analytic correction to the nonlocal continuum formulas which fits quite well the numerical behavior of the eigenvalues in the London regime. We use this approximate expression to calculate thermal fluctuations and the full melting line (according to Lindeman's criterion) for various values of the anisotropy parameter.

Induced quantum metric fluctuations and the validity of semiclassical gravity

We propose a criterion for the validity of semiclassical gravity (SCG) which is based on the stability of the solutions of SCG with respect to quantum metric fluctuations. We pay special attention to the two-point quantum correlation functions for the metric perturbations, which contain both intrinsic and induced fluctuations. These fluctuations can be described by the Einstein-Langevin equation obtained in the framework of stochastic gravity. Specifically, the Einstein-Langevin equation yields stochastic correlation functions for the metric perturbations which agree, to leading order in the large N limit, with the quantum correlation functions of the theory of gravity interacting with N matter fields. The homogeneous solutions of the Einstein-Langevin equation are equivalent to the solutions of the perturbed semiclassical equation, which describe the evolution of the expectation value of the quantum metric perturbations. The information on the intrinsic fluctuations, which are connected to the initial fluctuations of the metric perturbations, can also be retrieved entirely from the homogeneous solutions. However, the induced metric fluctuations proportional to the noise kernel can only be obtained from the Einstein-Langevin equation (the inhomogeneous term). These equations exhibit runaway solutions with exponential instabilities. A detailed discussion about different methods to deal with these instabilities is given. We illustrate our criterion by showing explicitly that flat space is stable and a description based on SCG is a valid approximation in that case.

Risk-benefit balance assessment of SSRI antidepressant use during pregnancy and lactation based on best available evidence.

INTRODUCTION: Psychiatric disorders are among the leading causes of disability in Western societies. Selective serotonin reuptake inhibitors (SSRIs) are the most frequently prescribed antidepressant drugs during pregnancy and the postpartum period. Over the last decade, conflicting findings regarding the safety of SSRI drugs during pregnancy and lactation have questioned whether such treatments should be used during this period. AREAS COVERED: We discuss the main criteria that should be considered in the risk/benefit assessment of SSRI treatment in pregnant and/or breastfeeding patients (i.e., risks associated with SSRI use and with untreated depression as well as therapeutic benefits of SSRI and some alternative treatment strategies). For each criterion, available evidence has been synthesized and stratified by methodological quality as well as discussed for clinical impact. EXPERT OPINION: Currently, it is impossible for most of the evaluated outcomes to distinguish between the effects related to the mother's underlying disease and those inherent to SSRI treatment. In women suffering from major depression and responding to a pharmacological treatment, introduction or continuation of an SSRI should be encouraged in order to prevent maternal complications and to preserve maternal-infant bonding. The choice of the right drug depends above all on individual patient characteristics such as prior treatment response, diagnoses and comorbid conditions.

Stochastic resonance in noisy nondynamical systems

We have analyzed the effects of the addition of external noise to nondynamical systems displaying intrinsic noise, and established general conditions under which stochastic resonance appears. The criterion we have found may be applied to a wide class of nondynamical systems, covering situations of different nature. Some particular examples are discussed in detail.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Noise suppression by noise

We have analyzed the interplay between an externally added noise and the intrinsic noise of systems that relax fast towards a stationary state, and found that increasing the intensity of the external noise can reduce the total noise of the system. We have established a general criterion for the appearance of this phenomenon and discussed two examples in detail.

PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA

Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland) forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2) and Akaike information criterion (AIC) and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.

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.

Diagnosis of the Nutritional Status of Garlic Crops

ABSTRACT Univariate methods for diagnosing nutritional status such as the sufficiency range and the critical level for garlic crops are very susceptible to the effects of dilution and accumulation of nutrients. Therefore, this study aimed to establish bivariate and multivariate norms for this crop using the Diagnosis and Recommendation Integrated System (DRIS) and Nutritional Composition Diagnosis (CND), respectively. The criteria used were nutritional status and the sufficiency range, and then the diagnoses were compared. The study was performed in the region of Alto Paranaíba, MG, Brazil, during the crop seasons 2012 and 2013. Samples comprised 99 commercial fields of garlic, cultivated with the cultivar “Ito” and mostly established in Latossolo Vermelho-Amarelo Distrófico (Oxisol). Copper and K were the nutrients with the highest number of fields diagnosed as limiting by lack (LF) and limiting by excess (LE), respectively. The DRIS method presented greater tendency to diagnose LF, while the CND tended towards LE. The sufficiency range of both methods presented narrow ranges in relation to those suggested by the literature. Moreover, all ranges produced by the CND method provided narrower ranges than the DRIS method. The CND method showed better performance than DRIS in distinguishing crop yield covered by different diagnoses. Turning to the criterion of evaluation, the study found that nutritional status gave a better performance than sufficiency range in terms of distinguishing diagnoses regarding yield.