Lipophilic and hydrophilic quantitative analysis of antioxidant activity in tomatoes and tomato products

The amount of antioxidants present in food varies depending on environmental conditions in which produce was grown and how products were processed prior to consumption. It would, therefore, be useful to quantify antioxidant activities in these foods. This study focused on quantitative analysis of antioxidant activities in commercially produced whole tomatoes and processed tomato products. For commercially processed tomatoes, diced tomatoes had total antioxidant activities (TAA) ranging from 1.243 to 2.243 μmol TE/g fresh weight (fw), juice 1.573 to 6.86 μmol TE/g fw, paste 6.3 to 13.248 μmol TE/g fw, sauce 1.62 to 3.168 μmol TE/g fw, and soup 1.073 to 3.773 μmol TE/g fw. In commercial whole tomatoes, cherry tomatoes had TAA ranging from 2.303 to 3.66 μmol TE/g fw, grape tomatoes 2.443 to 2.825 μmol TE/g fw, roma tomatoes 0.535 to 3.033 μmol TE/g fw, and slicer tomatoes 1.448 to 2.788 μmol TE/g fw. Variations and significant differences were observed in different samples of the same type of tomatoes, between different types of tomatoes, in different batches of the same brand and kind of processed tomatoes, and between different types of processed tomatoes. These variations could be attributed to the different locales tomatoes were grown, type of tomatoes used for processed tomato products, or additives such as herbs and spices used for flavoring. Additionally, the effect of light intensity on antioxidant accumulation in tomatoes was investigated by experimentally growing plants in different light intensities. Data indicated statistical differences between tomatoes grown under the same as well as different light intensities, on a fresh weight basis. Tomatoes grown in 100% light had TAA ranging from 1.898 to 3.565 μmol TE/g fw (7.73 to 13.405 μmol TE/g dw), 2.375 to 2.523 μmol TE/g fw (8.558 to 13.223 μmol TE/g dw) in 50% light, and 1.623 to 1.958 μmol TE/g fw (8.068 to 13.073 μmol TE/g dw) in 25% light. While small differences in data proved to be statistically significant, some of these differences may be too small to be of biological consequence. Data from this study, along with currently available data on antioxidants in foods, can provide useful information to consumers interested in purchasing products that are most beneficial to their health and to dietitians when making dietary recommendations to patient

Synthesis and Characterization of K and Eu Binary Phosphides.

The synthesis, structural characterization, and optical properties of the binary Zintl phases of α-EuP₃, β-EuP₃, EuP₂, and α-K₄P₆ are reported in this study. These crystal structures demonstrate the versatility of P fragments with dimensionality varying from 0D (P₆ rings in α-K₄P₆) to 1D chains (EuP₂) to 2D layers (both EuP₃). EuP₂ is isostructural to previously reported SrP₂ and BaP₂ compounds. The thermal stabilities of the EuP₂ and both EuP₃ phases were determined using differential scanning calorimetry (DSC), with melting temperatures of 1086 K for the diphosphide and 1143 K for the triphosphides. Diffuse reflectance spectroscopy indicated that EuP₂ is an indirect semiconductor with a direct bandgap of 1.12(5) eV and a smaller indirect one, less than 1 eV. Both EuP₃ compounds had bandgaps smaller than 1 eV

Quantum Natural Gradient for Variational Bayes

Variational Bayes (VB) is a critical method in machine learning and statistics, underpinning the recent success of Bayesian deep learning. The natural gradient is an essential component of efficient VB estimation, but it is prohibitively computationally expensive in high dimensions. We propose a hybrid quantum-classical algorithm to improve the scaling properties of natural gradient computation and make VB a truly computationally efficient method for Bayesian inference in highdimensional settings. The algorithm leverages matrix inversion from the linear systems algorithm by Harrow, Hassidim, and Lloyd [Phys. Rev. Lett. 103, 15 (2009)] (HHL). We demonstrate that the matrix to be inverted is sparse and the classical-quantum-classical handoffs are sufficiently economical to preserve computational efficiency, making the problem of natural gradient for VB an ideal application of HHL. We prove that, under standard conditions, the VB algorithm with quantum natural gradient is guaranteed to converge. Our regression-based natural gradient formulation is also highly useful for classical VB

Study of Bs→ℓ+ℓ−γB_s\to\ell^+\ell^-\gamma decays in covariant quark model

We study the rare radiative leptonic decays $B_s\to\ell^+\ell^-\gamma$ ($\ell=e,\mu,\tau$) within the Standard Model, considering both the structure-dependent amplitude and bremsstrahlung. In the framework of the covariant confined quark model developed by us, we calculate the form factors characterizing the $B_s\to\gamma$ transition in the full kinematical region of the dilepton momentum squared and discuss their behavior. We provide the analytic formula for the differential decay distribution and give predictions for the branching fractions in both cases: with and without long-distance contributions. Finally, we compare our results with those obtained in other approaches.Comment: 22 pages, 8 figures, 6 tables, more references and material added, a version to appear on PR

Coxiella burnetii Blocks Intracellular Interleukin-17 Signaling in Macrophages

Coxiella burnetii is an obligate intracellular bacterium and the etiological agent of Q fever. Successful host cell infection requires the Coxiella type IVB secretion system (T4BSS), which translocates bacterial effector proteins across the vacuole membrane into the host cytoplasm, where they manipulate a variety of cell processes. To identify host cell targets of Coxiella T4BSS effector proteins, we determined the transcriptome of murine alveolar macrophages infected with a Coxiella T4BSS effector mutant. We identified a set of inflammatory genes that are significantly upregulated in T4BSS mutant-infected cells compared to mock-infected cells or cells infected with wild-type (WT) bacteria, suggesting that Coxiella T4BSS effector proteins downregulate the expression of these genes. In addition, the interleukin-17 (IL-17) signaling pathway was identified as one of the top pathways affected by the bacteria. While previous studies demonstrated that IL-17 plays a protective role against several pathogens, the role of IL-17 during Coxiella infection is unknown. We found that IL-17 kills intracellular Coxiella in a dose-dependent manner, with the T4BSS mutant exhibiting significantly more sensitivity to IL-17 than WT bacteria. In addition, quantitative PCR confirmed the increased expression of IL-17 downstream signaling genes in T4BSS mutant-infected cells compared to WT- or mock-infected cells, including the proinflammatory cytokine genes Il1a, Il1b, and Tnfa, the chemokine genes Cxcl2 and Ccl5, and the antimicrobial protein gene Lcn2 We further confirmed that the Coxiella T4BSS downregulates macrophage CXCL2/macrophage inflammatory protein 2 and CCL5/RANTES protein levels following IL-17 stimulation. Together, these data suggest that Coxiella downregulates IL-17 signaling in a T4BSS-dependent manner in order to escape the macrophage immune response

No One Walks Alone: Fall Prevention Program

Background: Hospitals strive for patient safety, with fall prevention being a top priority. To improve patient safety outcomes, two local hospitals implemented No One Walks Alone (NOWA), an innovative fall prevention program. Purpose: The purpose of this study was to determine the effectiveness of the NOWA at Hospital A and Hospital B. The study continues to be part of a national system-wide implementation of NOWA. Methods: All staff were trained in the NOWA program. Hospital A implemented the program March 3, 2014 and Hospital B began implementation on two units on March 18, 2014. Data was collected by monitoring fall rates over a one-month trial period. Results: Data showed a decrease in falls at both hospitals after implementation of NOWA. Discussion/Recommendation: The study was limited to one month of data. Long-term data is needed to better evaluate the effectiveness of the program in both hospitals. Topics that need to be discussed and addressed are patient refusal rates and modified plans for specialty units. Further data analysis can help identify the most effective methods in preventing falls. Hospital B should begin implementation hospital-wide

Predicting Agricultural Commodities Prices with Machine Learning: A Review of Current Research

Agricultural price prediction is crucial for farmers, policymakers, and other stakeholders in the agricultural sector. However, it is a challenging task due to the complex and dynamic nature of agricultural markets. Machine learning algorithms have the potential to revolutionize agricultural price prediction by improving accuracy, real-time prediction, customization, and integration. This paper reviews recent research on machine learning algorithms for agricultural price prediction. We discuss the importance of agriculture in developing countries and the problems associated with crop price falls. We then identify the challenges of predicting agricultural prices and highlight how machine learning algorithms can support better prediction. Next, we present a comprehensive analysis of recent research, discussing the strengths and weaknesses of various machine learning techniques. We conclude that machine learning has the potential to revolutionize agricultural price prediction, but further research is essential to address the limitations and challenges associated with this approach

Influence of Evaluation System on Effectiveness of Foreign Students' Mathematical Education

This paper studies the problems of improving the quality of mathematics education of foreign students in Tomsk Polytechnic University. We found out that changes in the evaluation system had provided students progress in studying math. The effectiveness of point rating system introduction is proved according to statistics over the last 5 years. The research involved the application of mathematical statistics, correlation analysis and variance analysis methods. Influence of different evaluation systems on the final grade is shown. We worked out that the studying time started to be used more rationally and the students’ activity increased during the term. Observational results showed a higher level of motivation, orderliness and responsibility. Assessment of the permanent knowledge confirmed the expected results

Design of a static test rig for advanced seals and air bearing testing

International audienceToday's industrial gas turbines are required to cope with strong fluctuations caused by a strongly varying feed of renewable energies into the grid. These transient operating conditions result in high temperature gradients and consequently lead to increased axial and radial displacements of turbine parts. Such flexible operations need to be supported by novel sealing technologies. This paper presents a new test facility for investigating advanced seals under 2D static conditions. It facilitates detailed experimental studies of the static pressure distribution on the seal air bearing faces, measurements on the leakage flow through the seal and measurements on the air bearing force balance. The clearance between the rotor and the seal can be set very accurately and it is furthermore possible to apply a predetermined amount of eccentricity to the seal/rotor combination