Low Temperature Oxidation of Carbon Monoxide over Mesoporous Au-Fe 2

Low temperature active and stable mesoporous Au (0.1, 0.2, 0.5, and 1.0 wt.%) supported α-Fe2O3 catalysts were prepared via deposition-precipitation method. The H2-pretreated catalyst with 0.5 wt.% Au loading offered CO conversion of 100% at 323 K and showed continual activity for at least 120 h. X-ray diffraction and transmission electron microscopy analysis indicate that Au species were highly dispersed as nanoparticles (20–40 nm) on the surface of α-Fe2O3 support even after thermal treatment at 773 K. The N2-physisorption measurements show that the synthesized α-Fe2O3 support and Au-Fe2O3 nanocomposites possessed mesopores with high specific surface area of about 158 m2 g−1. X-ray photoelectron spectroscopy and H2-TPR results reveal that the Au species exist in metallic and partially oxidized state due to strong interaction with the support. Effective Au-Fe2O3 interaction resulted in a high activity for Au nanoparticles, locally generated by the thermal treatment at 773 K in air

Methanol oxidation on transition elements oxides

Methanol oxidation to formaldehyde is one of the most important industries in our lives; the reaction occurs on catalyst surface in heterogeneous catalysis. Iron molybdate is the current selective catalyst. However, molybdenum volatilises during methanol oxidation and leaving the catalyst with a low molybdenum ratio, which deactivates the catalyst, a 2.2 Mo: 1Fe iron molybdate catalyst was used instead the stoichiometric catalyst, while yield of formaldehyde cannot be 100%. The goal of this study is to find more selective and more productive catalyst than iron molybdate catalyst, the first step is to find another transition element as selective as molybdenum, because molybdenum is the selective part, and iron is the active part, the resulting iron molybdate catalyst is a selective catalyst to formaldehyde near molybdenum and active near iron. Experimentally, catalysts were prepared using co-precipitation method, however, some doped catalysts were papered by incipient wetness impregnation, also sol-immobilization was used to prepare nano-gold particles on the surfaces of few supports. Catalysts characterizations were carried out within several techniques for the surface analysis (XPS) and bulk analysis (XRD), also the surface area was measured by BET equipment. Raman too was used in this study, while micro-reactor was the reactor to determine selectivity and activity of each catalyst. When molybdenum replaced by vanadium, the catalyst yielded 100% formaldehyde at 200 oC; moreover, tungsten was selective. Likewise, iron was replaced by other active metals such as manganese, copper and bismuth, which are active. Nano-gold improved activity when doped on molybdenum oxide and iron molybdate supports

Selectivity determinants for dual function catalysts: applied to methanol selective oxidation on iron molybdate

Evolution of the IRAS spectrum with temperature after adsorbing methanol at room temperature. The bands at 2930 and 2820 cm− 1 are due to the methoxy species C–H stretches, while that at 2870 is due to the formate. Here, we report a simple, quantitative model to describe the behaviour of bi-cationic oxide catalysts, in terms of selectivity variation as a function of increased loading of one cation into a sample of the other. We consider its application to a particular catalytic system, namely the selective oxidation of methanol, which proceeds with three main C1 products, namely CO2, CO, and H2CO. The product selectivity varies in this order as Mo is added in increasing amounts to an iron oxide catalyst, and the product selectivity is determined by the distribution of dual sites and single sites of each species

Facile Synthesis of Palladium-Nanoparticle-Embedded N-Doped Carbon Fibers for Electrochemical Sensing

2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. In recent years, there have been many studies on metal/carbon hybrid materials for electrochemical applications. However, reducing the metal content in catalysts is still a challenge. Here, a facile synthesis of palladium (Pd) nanoparticle-embedded N-doped carbon fibers (Pd/N-C) through electropolymerization and reduction methods is demonstrated. The as-prepared Pd/N-C contains only 1.5wt% Pd. Under optimal conditions, bisphenolA is detected by using amperometry in two dynamic ranges from 0.1 to 10μm and from 10 to 200μm, and the obtained correlation coefficients are close to 0.9836 and 0.9987, respectively. The detection limit (DL) for bisphenolA is determined to be 29.44 (±0.77)nm

Facile Synthesis of Palladium-Nanoparticle-Embedded N-Doped Carbon Fibers for Electrochemical Sensing

2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. In recent years, there have been many studies on metal/carbon hybrid materials for electrochemical applications. However, reducing the metal content in catalysts is still a challenge. Here, a facile synthesis of palladium (Pd) nanoparticle-embedded N-doped carbon fibers (Pd/N-C) through electropolymerization and reduction methods is demonstrated. The as-prepared Pd/N-C contains only 1.5wt% Pd. Under optimal conditions, bisphenolA is detected by using amperometry in two dynamic ranges from 0.1 to 10μm and from 10 to 200μm, and the obtained correlation coefficients are close to 0.9836 and 0.9987, respectively. The detection limit (DL) for bisphenolA is determined to be 29.44 (±0.77)nm

Facile Synthesis of Palladium-Nanoparticle-Embedded N-Doped Carbon Fibers for Electrochemical Sensing

2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. In recent years, there have been many studies on metal/carbon hybrid materials for electrochemical applications. However, reducing the metal content in catalysts is still a challenge. Here, a facile synthesis of palladium (Pd) nanoparticle-embedded N-doped carbon fibers (Pd/N-C) through electropolymerization and reduction methods is demonstrated. The as-prepared Pd/N-C contains only 1.5wt% Pd. Under optimal conditions, bisphenolA is detected by using amperometry in two dynamic ranges from 0.1 to 10μm and from 10 to 200μm, and the obtained correlation coefficients are close to 0.9836 and 0.9987, respectively. The detection limit (DL) for bisphenolA is determined to be 29.44 (±0.77)nm

Dermatological Lesions of Cholesterol Embolization Syndrome and Kaposi Sarcoma Mimic Primary Systemic Vasculitis: Case Report Study

Primary systemic vasculitis can present with a wide spectrum of manifestations ranging from systemic non-specific features such as fever, malaise, arthralgia, and myalgia to specific organ damage. We describe two cases of cholesterol embolization syndrome and Kaposi sarcoma mimicking primary systemic vasculitis, both of which were characterized by features such as livedo reticularis, blue toe syndrome, a brown, purpuric skin rash, and positive p-ANCA associated with Kaposi sarcoma. Establishing the right diagnosis was challenging, and thus we aim in this study to highlight the possible ways to distinguish them from primary systemic vasculitis. Keywords: Dermatological lesions, Cholesterol embolization syndrome, Kaposi sarcoma, vasculitis mimic

Soft-templated synthesis of mesoporous nickel oxide using poly(styrene-block-acrylic acid-block-ethylene glycol) block copolymers

In this work, we report the soft-templated preparation of mesoporous nickel oxide using an asymmetric poly(styrene-block-acrylic acid-block-ethylene glycol) (PS-b-PAA-b-PEG) triblock copolymer. This block copolymer forms a micelle consisting of a PS core, a PAA shell and a PEG corona in aqueous solutions, which can serve as a soft template. Specifically, the PS block forms the core of the micelles on the basis of its lower solubility in water. The anionic PAA block interacts with the cationic Ni ions present in the solution to generate the shell. The PEG block forms the corona of the micelles and stabilizes the micelles by preventing secondary aggregation through steric repulsion between the PEG chains. In terms of textural characteristics, the as-synthesized mesoporous NiO exhibits a large average pore size of 35 nm with large specific surface area and pore volume of 97.0 m g and 0.411 cm g, respectively. It is expected that the proposed soft-templated strategy can be expanded to other metal oxides/sulfides in the future for potential applications in gas sensors, catalysis, energy storage and conversion, optoelectronics, and biomedical applications

The need for national medical licensing examination in Saudi Arabia

<p>Abstract</p> <p>Background</p> <p>Medical education in Saudi Arabia is facing multiple challenges, including the rapid increase in the number of medical schools over a short period of time, the influx of foreign medical graduates to work in Saudi Arabia, the award of scholarships to hundreds of students to study medicine in various countries, and the absence of published national guidelines for minimal acceptable competencies of a medical graduate.</p> <p>Discussion</p> <p>We are arguing for the need for a Saudi national medical licensing examination that consists of two parts: Part I (Written) which tests the basic science and clinical knowledge and Part II (Objective Structured Clinical Examination) which tests the clinical skills and attitudes. We propose this examination to be mandated as a licensure requirement for practicing medicine in Saudi Arabia.</p> <p>Conclusion</p> <p>The driving and hindering forces as well as the strengths and weaknesses of implementing the licensing examination are discussed in details in this debate.</p

TF-TDA: A Novel Supervised Term Weighting Scheme for Sentiment Analysis

In text classification tasks, such as sentiment analysis (SA), feature representation and weighting schemes play a crucial role in classification performance. Traditional term weighting schemes depend on the term frequency within the entire document collection; therefore, they are called unsupervised term weighting (UTW) schemes. One of the most popular UTW schemes is term frequency–inverse document frequency (TF-IDF); however, this is not sufficient for SA tasks. Newer weighting schemes have been developed to take advantage of the membership of documents in their categories. These are called supervised term weighting (STW) schemes; however, most of them weigh the extracted features without considering the characteristics of some noisy features and data imbalances. Therefore, in this study, a novel STW approach was proposed, known as term frequency–term discrimination ability (TF-TDA). TF-TDA mainly presents the extracted features with different degrees of discrimination by categorizing them into several groups. Subsequently, each group is weighted based on its contribution. The proposed method was examined over four SA datasets using naive Bayes (NB) and support vector machine (SVM) models. The experimental results proved the superiority of TF-TDA over two baseline term weighting approaches, with improvements ranging from 0.52% to 3.99% in the F1 score. The statistical test results verified the significant improvement obtained by TF-TDA in most cases, where the p-value ranged from 0.0000597 to 0.0455