Development of an approximate method for quantum optical models and their pseudo-Hermicity

An approximate method is suggested to obtain analytical expressions for the eigenvalues and eigenfunctions of the some quantum optical models. The method is based on the Lie-type transformation of the Hamiltonians. In a particular case it is demonstrated that $E\times \epsilon$ Jahn-Teller Hamiltonian can easily be solved within the framework of the suggested approximation. The method presented here is conceptually simple and can easily be extended to the other quantum optical models. We also show that for a purely imaginary coupling the $E\times \epsilon$ Hamiltonian becomes non-Hermitian but $P\sigma _{0}$-symmetric. Possible generalization of this approach is outlined.Comment: Paper prepared fo the "3rd International Workshop on Pseudo-Hermitian Hamiltonians in Quantum Physics" June 2005 Istanbul. To be published in Czechoslovak Journal of Physic

Pseudoelasticity at Large Strains in Au Nanocrystals [post-print]

© 2018 American Physical Society. Pseudoelasticity in metals is typically associated with phase transformations (e.g., shape memory alloys) but has recently been observed in sub-10 nm Ag nanocrystals that rapidly recovered their original shape after deformation to large strains. The discovery of pseudoelasticity in nanoscale metals dramatically changes the current understanding of the properties of solids at the smallest length scales, and the motion of atoms at surfaces. Yet, it remains unclear whether pseudoelasticity exists in different metals and nanocrystal sizes. The challenge of observing deformation at atomistic to nanometer length scales has prevented a clear mechanistic understanding of nanoscale pseudoelasticity, although surface diffusion and dislocation-mediated processes have been proposed. We further the understanding of pseudoelasticity in nanoscale metals by using a diamond anvil cell to compress colloidal Au nanocrystals under quasihydrostatic and nonhydrostatic pressure conditions. Nanocrystal structural changes are measured using optical spectroscopy and transmission electron microscopy and modeled using electrodynamic theory. We find that 3.9 nm Au nanocrystals exhibit pseudoelastic shape recovery after deformation to large uniaxial strains of up to 20%, which is equivalent to an ellipsoid with an aspect ratio of 2. Nanocrystal absorbance efficiency does not recover after deformation, which indicates that crystalline defects may be trapped in the nanocrystals after deformation

Low-Dose CT Image Enhancement Using Deep Learning

The application of ionizing radiation for diagnostic imaging is common around the globe. However, the process of imaging, itself, remains to be a relatively hazardous operation. Therefore, it is preferable to use as low a dose of ionizing radiation as possible, particularly in computed tomography (CT) imaging systems, where multiple x-ray operations are performed for the reconstruction of slices of body tissues. A popular method for radiation dose reduction in CT imaging is known as the quarter-dose technique, which reduces the x-ray dose but can cause a loss of image sharpness. Since CT image reconstruction from directional x-rays is a nonlinear process, it is analytically difficult to correct the effect of dose reduction on image quality. Recent and popular deep-learning approaches provide an intriguing possibility of image enhancement for low-dose artifacts. Some recent works propose combinations of multiple deep-learning and classical methods for this purpose, which over-complicate the process. However, it is observed here that the straight utilization of the well-known U-NET provides very successful results for the correction of low-dose artifacts. Blind tests with actual radiologists reveal that the U-NET enhanced quarter-dose CT images not only provide an immense visual improvement over the low-dose versions, but also become diagnostically preferable images, even when compared to their full-dose CT versions

Urban agriculture: a global analysis of the space constraint to meet urban vegetable demand

Urban agriculture (UA) has been drawing a lot of attention recently for several reasons: the majority of the world population has shifted from living in rural to urban areas; the environmental impact of agriculture is a matter of rising concern; and food insecurity, especially the accessibility of food, remains a major challenge. UA has often been proposed as a solution to some of these issues, for example by producing food in places where population density is highest, reducing transportation costs, connecting people directly to food systems and using urban areas efficiently. However, to date no study has examined how much food could actually be produced in urban areas at the global scale. Here we use a simple approach, based on different global-scale datasets, to assess to what extent UA is constrained by the existing amount of urban space. Our results suggest that UA would require roughly one third of the total global urban area to meet the global vegetable consumption of urban dwellers. This estimate does not consider how much urban area may actually be suitable and available for UA, which likely varies substantially around the world and according to the type of UA performed. Further, this global average value masks variations of more than two orders of magnitude among individual countries. The variations in the space required across countries derive mostly from variations in urban population density, and much less from variations in yields or per capita consumption. Overall, the space required is regrettably the highest where UA is most needed, i.e., in more food insecure countries. We also show that smaller urban clusters (i.e., <100 km2 each) together represent about two thirds of the global urban extent; thus UA discourse and policies should not focus on large cities exclusively, but should also target smaller urban areas that offer the greatest potential in terms of physical space

Boron Stress Activates the General Amino Acid Control Mechanism and Inhibits Protein Synthesis

Boron is an essential micronutrient for plants, and it is beneficial for animals. However, at high concentrations boron is toxic to cells although the mechanism of this toxicity is not known. Atr1 has recently been identified as a boron efflux pump whose expression is upregulated in response to boron treatment. Here, we found that the expression of ATR1 is associated with expression of genes involved in amino acid biosynthesis. These mechanisms are strictly controlled by the transcription factor Gcn4 in response to boron treatment. Further analyses have shown that boron impaired protein synthesis by promoting phosphorylation of eIF2α in a Gcn2 kinase dependent manner. The uncharged tRNA binding domain (HisRS) of Gcn2 is necessary for the phosphorylation of eIF2α in the presence of boron. We postulate that boron exerts its toxic effect through activation of the general amino acid control system and inhibition of protein synthesis. Since the general amino acid control pathway is conserved among eukaryotes, this mechanism of boron toxicity may be of general importance

Are Deep Learning Classification Results Obtained on CT Scans Fair and Interpretable?

Following the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications to various automatic diagnosis cases. Unfortunately, most of the deep learning-based classification attempts in the literature solely focus on the aim of extreme accuracy scores, without considering interpretability, or patient-wise separation of training and test data. For example, most lung nodule classification papers using deep learning randomly shuffle data and split it into training, validation, and test sets, causing certain images from the CT scan of a person to be in the training set, while other images of the exact same person to be in the validation or testing image sets. This can result in reporting misleading accuracy rates and the learning of irrelevant features, ultimately reducing the real-life usability of these models. When the deep neural networks trained on the traditional, unfair data shuffling method are challenged with new patient images, it is observed that the trained models perform poorly. In contrast, deep neural networks trained with strict patient-level separation maintain their accuracy rates even when new patient images are tested. Heat-map visualizations of the activations of the deep neural networks trained with strict patient-level separation indicate a higher degree of focus on the relevant nodules. We argue that the research question posed in the title has a positive answer only if the deep neural networks are trained with images of patients that are strictly isolated from the validation and testing patient sets.Comment: This version has been submitted to CAAI Transactions on Intelligence Technology. 202

Nano-scale superhydrophobicity: suppression of protein adsorption and promotion of flow-induced detachment

Wall adsorption is a common problem in microfluidic devices, particularly when proteins are used. Here we show how superhydrophobic surfaces can be used to reduce protein adsorption and to promote desorption. Hydrophobic surfaces, both smooth and having high surface roughness of varying length scales (to generate superhydrophobicity), were incubated in protein solution. The samples were then exposed to flow shear in a device designed to simulate a microfluidic environment. Results show that a similar amount of protein adsorbed onto smooth and nanometer-scale rough surfaces, although a greater amount was found to adsorb onto superhydrophobic surfaces with micrometer scale roughness. Exposure to flow shear removed a considerably larger proportion of adsorbed protein from the superhydrophobic surfaces than from the smooth ones, with almost all of the protein being removed from some nanoscale surfaces. This type of surface may therefore be useful in environments, such as microfluidics, where protein sticking is a problem and fluid flow is present. Possible mechanisms that explain the behaviour are discussed, including decreased contact between protein and surface and greater shear stress due to interfacial slip between the superhydrophobic surface and the liquid

Probiotic yogurt with brazilian red propolis: physicochemical and bioactive properties, stability, and shelf life

This study aimed to evaluate the quality parameters in probiotic yogurt produced with Brazilian red propolis to replace potassium sorbate used in conventional yogurt (CY). Microbiological stability and shelf life, physicochemical properties (pH, acidity, chemical composition, and fatty acids), and bioactive properties (phenolic compounds and antioxidant activity) were evaluated. The addition of red propolis (0.05%) to replace the potassium sorbate did not change the pH, acidity, fatty acid profile, chemical composition, or shelf life. Microbiological stability of at least 28 days was achieved, while a drastic reduction in the lactic acid bacteria content was observed in the CY during refrigeration storage. Phenolic total contents were higher than those of the control, and consequently, yogurt with red propolis showed higher antioxidant activity.We thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazilian government, for scholarship support (Finance Code 001), the Dr Cátia Ionara Santos Lucas (INSECTA laboratory, UFRB, Cruz das Almas, Brazil), and the technical team of the Polytechnic Institute of Bragança laboratory (Bragança, Portugal) for their support during the research.info:eu-repo/semantics/publishedVersio

L2 series solutions of the Dirac equation for power-law potentials at rest mass energy

We obtain solutions of the three dimensional Dirac equation for radial power-law potentials at rest mass energy as an infinite series of square integrable functions. These are written in terms of the confluent hypergeometric function and chosen such that the matrix representation of the Dirac operator is tridiagonal. The "wave equation" results in a three-term recursion relation for the expansion coefficients of the spinor wavefunction which is solved in terms of orthogonal polynomials. These are modified versions of the Meixner-Pollaczek polynomials and of the continuous dual Hahn polynomials. The choice depends on the values of the angular momentum and the power of the potential.Comment: 13 pages, 1 Tabl

Post-transplant cyclophosphamide for graft-versus-host disease prophylaxis in HLA matched sibling or matched unrelated donor transplant for patients with acute leukemia, on behalf of ALWP-EBMT

Background: Experience using post-transplant cyclophosphamide (PT-Cy) as graft-versus-host disease (GVHD) prophylaxis in allogeneic stem cell transplantation (HSCT) from matched sibling donors (MSD) or unrelated donors (UD) is limited and with controversial results. The study aim was to evaluate PT-Cy as GVHD prophylaxis post-HSCT from MSD and UD transplants. We analyzed 423 patients with acute leukemia who received PT-Cy alone or in combination with other immunosuppressive (IS) drugs as GVHD prophylaxis. Seventy-eight patients received PT-Cy alone (group 1); 204 received PT-Cy in combination with one IS drug - cyclosporine-A (CSA) or methotrexate (MTX) or mycophenolate-mofetil (MMF) (group 2), while 141 patients received PT-Cy in combination with two IS drugs - CSA + MTX or CSA + MMF (group 3). Transplants were performed from 2007 to 2015 and median follow-up was 20 months. Results: Probability of overall survival (OS) at 2 years was 50, 52.2, and 62.4%, for the three groups, respectively, p = 0.06. In multivariate analysis, in comparison to PT-Cy alone, the addition of two IS drugs was associated with reduced risk of extensive cGVHD (HR 0.25, p = 0.02). Use of bone marrow (BM) and anti-thymocyte globulin were independently associated with reduced risk of extensive cGVHD. Prognostic factors for non-relapse mortality (NRM) were the addition of two IS drugs to PT-Cy (HR 0.35, p = 0.04), diagnosis of AML, disease status at transplant, and patient CMV serology. Factors associated with increased OS were the use of PT-Cy with two IS drugs (HR 0.49, p = 0.02), AML, and disease status at transplant. Conclusion: For GVHD prophylaxis in MSD and UD HSCT, the addition of IS drugs to PT-Cy enhances its effect and reduces the risk of severe cGVHD, reducing mortality and improving survival