SUPPLY RESPONSE AND IMPACT OF GOVERNMENT-SUPPORTED CROPS ON THE TEXAS VEGETABLE INDUSTRY

Supply functions, elasticity estimates, and nonjointness test results consistently indicated that few commodities compete economically in the production of six major Texas vegetables (cabbage, cantaloupes, carrots, onions, potatoes, and watermelons). Significant bias effects caused by government-supported commodities, fixed inputs, and technological change were observed and measured. Nonnested test results for the hypothesis of sequential decision making by vegetable producers were inconclusive, but they gave greater likelihood support to sequential than to contemporaneous decision making.Demand and Price Analysis,

Field efficacy evaluation and post-treatment contamination risk assessment of an ultraviolet disinfection and safe storage system.

Inconsistent use of household water treatment and safe storage (HWTS) systems reduces their potential health benefits. Ultraviolet (UV) disinfection is more convenient than some existing HWTS systems, but it does not provide post-treatment residual disinfectant, which could leave drinking water vulnerable to recontamination. In this paper, using as-treated analyses, we report on the field efficacy of a UV disinfection system at improving household drinking water quality in rural Mexico. We further assess the risk of post-treatment contamination from the UV system, and develop a process-based model to better understand household risk factors for recontamination. This study was part of a larger cluster-randomized stepped wedge trial, and the results complement previously published population-level results of the intervention on diarrheal prevalence and water quality. Based on the presence of Escherichia coli (proportion of households with ≥ 1 E. coli/100 mL), we estimated a risk difference of -28.0% (95% confidence interval (CI): -33.9%, -22.1%) when comparing intervention to control households; -38.6% (CI: -48.9%, -28.2%) when comparing post- and pre-intervention results; and -37.1% (CI: -45.2%, -28.9%) when comparing UV disinfected water to alternatives within the household. We found substantial increases in post-treatment E. coli contamination when comparing samples from the UV system effluent (5.0%) to samples taken from the storage container (21.1%) and drinking glasses (26.0%). We found that improved household infrastructure, additional extractions from the storage container, additional time from when the storage container was filled, and increased experience of the UV system operator were associated with reductions in post-treatment contamination. Our results suggest that the UV system is efficacious at improving household water quality when used as intended. Promoting safe storage habits is essential for an effective UV system dissemination. The drinking glass appears to represent a small but significant source of recontamination that is likely to impact all HWTS systems

Uncovering distinct protein-network topologies in heterogeneous cell populations

Background: Cell biology research is fundamentally limited by the number of intracellular components, particularly proteins, that can be co-measured in the same cell. Therefore, cell-to-cell heterogeneity in unmeasured proteins can lead to completely different observed relations between the same measured proteins. Attempts to infer such relations in a heterogeneous cell population can yield uninformative average relations if only one underlying biochemical network is assumed. To address this, we developed a method that recursively couples an iterative unmixing process with a Bayesian analysis of each unmixed subpopulation. Results: Our approach enables to identify the number of distinct cell subpopulations, unmix their corresponding observations and resolve the network structure of each subpopulation. Using simulations of the MAPK pathway upon EGF and NGF stimulations we assess the performance of the method. We demonstrate that the presented method can identify better than clustering approaches the number of subpopulations within a mixture of observations, thus resolving correctly the statistical relations between the proteins. Conclusions: Coupling the unmixing of multiplexed observations with the inference of statistical relations between the measured parameters is essential for the success of both of these processes. Here we present a conceptual and algorithmic solution to achieve such coupling and hence to analyze data obtained from a natural mixture of cell populations. As the technologies and necessity for multiplexed measurements are rising in the systems biology era, this work addresses an important current challenge in the analysis of the derived data.Fil: Wieczorek, Jakob. Universitat Dortmund; AlemaniaFil: Malik Sheriff, Rahuman S.. Institut Max Planck fur Molekulare Physiologie; Alemania. Imperial College London; Reino Unido. European Bioinformatics Institute. European Molecular Biology Laboratory; Reino UnidoFil: Fermin, Yessica. Universitat Dortmund; AlemaniaFil: Grecco, Hernan Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Zamir, Eli. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Ickstadt, Katja. Universitat Dortmund; Alemani

Elliptical-P Cells in the Avian Perilymphatic Interface of the Tegmentum Vasculosum

Elliptical cells (E-P) are present at the perilymphatic interface lumen (PIL) of the lagena. The E-P cells often separate from the tegmentum vasculosum (TV) and have touching processes that form a monolayer between the K+ rich perilymph and the Na+ rich endolymph, similar to the mammalian Reissner\u27s membrane. We examined the TV of chicks (Gallus domesticus) and quantitated the expression of anti-S100ααββ and S100β. There was a 30% increase of S100β saturation in the light cells facing the PIL when compared to other TV light cells. We show that: (1) the dimer anti-S100ααββ and the mono-mer anti-S100β are expressed preferentially in the light cells and the E-P cells of TV; (2) expression of S100β is higher in light cells facing the PIL than in adjacent cells; (3) the expression of the dimer S100ααββ and monomer S100β overlaps in most inner ear cell types, including the cells of the TV, most S100ααββ positive cells express S100β, but S100β positive cells do not always express S100ααββ; and (4) the S100β expression in light cells, the abundant Na+-K+ ATPase on dark cells of the TV, and previously demonstrated co-localization of S100β/GABA in sensory cells suggest that S100β could have, in the inner ear, a dual neurotrophic-ionic modulating function

Comparison of DNA Fragmentation and Color Thresholding for Objective Quantitation of Apoptotic Cells

Apoptosis is a process of cell death characterized by distinctive morphological changes and fragmentation of cellular DNA. Using video imaging and color thresholding techniques, we objectively quantitated the number of cultured CD4 + T-lymphoblastoid cells (HUT78 cells, RH9 subclone) displaying morphological signs of apoptosis before and after exposure to γ-irradiation. The numbers of apoptotic cells measured by objective video imaging techniques were compared to numbers of apoptotic cells measured in the same samples by sensitive apoptotic assays that quantitate DNA fragmentation. DNA fragmentation assays gave consistently higher values compared with the video imaging assays that measured morphological changes associated with apoptosis. These results suggest that substantial DNA frag-mentation can precede or occur in the absence of the morphological changes which are associated with apoptosis in γ-irradiated RH9 cells

Electrochemical characterization and regeneration of sulfur poisoned Pt catalysts in aqueous media

Understanding the poisoning and recovery of precious metal catalysts is greatly relevant for the chemical industry dealing with the synthesis of organic compounds. For example, hydrogenation reactions typically use platinum catalysts and sulfuric acid media, leading to poisoning by sulfur-containing species. In this work, we have applied electrochemical methods to understand the status and recovery of Pt catalysts by studying the electro-oxidation of a family of sulfur-containing species adsorbed at several types of Pt electrodes: (i) polycrystalline Pt foil; (ii) Pt single-crystal electrodes; and (iii) Pt nanoparticles supported on Vulcan carbon. The results obtained from polycrystalline Pt electrodes and Pt nanoparticles supported on Vulcan carbon demonstrate that all sulfur-containing species with different oxidation states (2-, 3+ and 4+) lead to the poisoning of Pt active sites. X-ray photoelectron spectroscopy (XPS) analysis was employed to elucidate the chemical state of sulfur species during the recovery process. The degree of poisoning decreased with increased sulfur oxidation state, while the rate of regeneration of the Pt surfaces generally increases with the oxidation state of the sulfur species. Finally, the use of Pt single-crystal electrodes reveals the surface-structure sensitivity of the oxidation of the sulfur species. This information could be useful in designing catalysts that are less susceptible to poisoning and/or more easily regenerated. These studies demonstrate voltammetry to be a powerful method for assessing the status of platinum surfaces and for recovering catalyst activity, such that electrochemical methods could find applications as sensors in catalysis and for catalyst recovery in-situ

oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data

The complexity and high dimensionality of neuroimaging data pose problems for decoding information with machine learning (ML) models because the number of features is often much larger than the number of observations. Feature selection is one of the crucial steps for determining meaningful target features in decoding; however, optimizing the feature selection from such high-dimensional neuroimaging data has been challenging using conventional ML models. Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS) algorithm and hyper-parameter optimization that automatically identifies the best feature pairs for both classification and regression models, where a total of 18 ML models are implemented by default. First, the FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross-validation step that identifies the best subset of features based on a predefined criterion for each model. Next, the hyperparameters of each ML model are optimized at each forward iteration. Final outputs highlight an optimized number of selected features (brain regions of interest) for each model with its accuracy. Furthermore, the toolbox can be executed in a parallel environment for efficient computation on a typical personal computer. With the optimized forward variable selection decoder (oFVSD) pipeline, we verified the effectiveness of decoding sex classification and age range regression on 1,113 structural magnetic resonance imaging (MRI) datasets. Compared to ML models without the FVS algorithm and with the Boruta algorithm as a variable selection counterpart, we demonstrate that the oFVSD significantly outperformed across all of the ML models over the counterpart models without FVS (approximately 0.20 increase in correlation coefficient, r, with regression models and 8% increase in classification models on average) and with Boruta variable selection algorithm (approximately 0.07 improvement in regression and 4% in classification models). Furthermore, we confirmed the use of parallel computation considerably reduced the computational burden for the high-dimensional MRI data. Altogether, the oFVSD toolbox efficiently and effectively improves the performance of both classification and regression ML models, providing a use case example on MRI datasets. With its flexibility, oFVSD has the potential for many other modalities in neuroimaging. This open-source and freely available Python package makes it a valuable toolbox for research communities seeking improved decoding accuracy

Characterization of Electronic Transport through Amorphous TiO_2 Produced by Atomic-Layer Deposition

Electrical transport in amorphous titanium dioxide (a-TiO_2) thin films, deposited by atomic layer deposition (ALD), and across heterojunctions of p+-Si|a-TiO_2|metal substrates that had various top metal contacts has been characterized by ac conductivity, temperature-dependent dc conductivity, space-charge-limited current spectroscopy, electron paramagnetic resonance (EPR) spectroscopy, X-ray photoelectron spectroscopy, and current density versus voltage (J–V) characteristics. Amorphous TiO_2 films were fabricated using either tetrakis(dimethylamido)-titanium with a substrate temperature of 150 °C or TiCl_4 with a substrate temperature of 50, 100, or 150 °C. EPR spectroscopy of the films showed that the Ti^(3+) concentration varied with the deposition conditions and increases in the concentration of Ti^(3+) in the films correlated with increases in film conductivity. Valence band spectra for the a-TiO_2 films exhibited a defect-state peak below the conduction band minimum (CBM) and increases in the intensity of this peak correlated with increases in the Ti^(3+) concentration measured by EPR as well as with increases in film conductivity. The temperature-dependent conduction data showed Arrhenius behavior at room temperature with an activation energy that decreased with decreasing temperature, suggesting that conduction did not occur primarily through either the valence or conduction bands. The data from all of the measurements are consistent with a Ti^(3+) defect-mediated transport mode involving a hopping mechanism with a defect density of 10^(19) cm^(–3), a 0.83 wide defect band centered 1.47 eV below the CBM, and a free-electron concentration of 10^(16) cm^(–3). The data are consistent with substantial room-temperature anodic conductivity resulting from the introduction of defect states during the ALD fabrication process as opposed to charge transport intrinsically associated with the conduction band of TiO_2