Controlled Morphological Structure of Ceria Nanoparticles Prepared by Spray Pyrolysis

AbstractCeria based materials have been widely used as catalyst supporters and electrolytes. Different applications require different morphologies, and the microstructural control during the synthesis is crucial. In the study, ceria particles were prepared from various precursors using a spray pyrolysis (SP). Comparing to the hollow and porous particles, the formation mechanism with solid spherical structure is not clarified readily. The ceria particles were characterized by transmission electron microscopy, thermogravimetry analysis and X-ray photoelectron spectroscopy. This experimental result suggests that the morphology is controlled by the precursors and could be related to their decomposed behavior during the heating process in SP

Correlation of Morphology and In-Vitro Degradation Behavior of Spray Pyrolyzed Bioactive Glasses

Bioactive glass (BG) is considered to be one of the Most remarkable Materials in the field of bone tissue regeneration due to its superior bioactivity. In this study, both un-treated and polyethylene glycols (PEG)-treated BG particles were prepared using a spray pyrolysis process to study the correlation between particle Morphology and degradation behavior. The phase compositions, surface Morphologies, inner structures, and specific surface areas of all BG specimens were examined by X-ray diffraction, scanning electron Microscopy, transmission electron Microscopy, and nitrogen adsorption/desorption, respectively. Simulated body fluid (SBF) immersion evaluated the assessments of bioactivity and degradation behavior. The results demonstrate three particle Morphologies of solid, porous, and hollow factors. The correlation between porosity, bioactivity, and degradation behavior was discussed

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.</p

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.</p

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.</p

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma

SummaryWe describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

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