Determination of neutron flux parameters in PUSPATI TRIGA Mark II Research Reactor, Malaysia

In standardization NAA, it is necessary to characterize the neutron spectrum parameters such as epithermal neutron flux shape factor (α), thermal to epithermal neutron flux ratio (f), thermal neutron flux (φ _th) and epithermal neutron flux (φ _epi) in the irradiation facility to determine the concentration of an element in the sample using absolute and k ₀ standardization methods. The α and f were determined using Cd-ratio multi monitor method using experimental data obtained in PUSPATI TRIGA Mark II research reactor at four irradiation positions (10, 20, 30 and 40) of the rotary rack. The calculated values of α and f ranged from 0.006 to 0.0281 and 18.56 to 19.12 respectively. The average values of φ _th and φ _epi were found as 2.33 × 10¹² and 1.23 × 10¹¹ n cm^?2 s^?1 respectively. Moreover, a comparison of the neutron flux parameters in the present study shows an acceptable level of consistency with those of previous studies.     

SYNTHESIS OF MONO-AND DIALKYLPHOSPHATES BY THE REACTIONS OF HYDROXYCOMPOUNDS WITH THE PHOSPHORUS PENTAOXIDE UNDER MICROWAVE IRRADIATION

The reactions of phosphorus pentoxide with two alcohols and one phenol were performed in different conditions under microwave irradiation. The products (alkylphosphates and dialkylphosphates) were identical to those formed by classic heating and were obtained with better yields. The speed of the reaction was increased by a factor from 100 to 4000.     

Electrochemical and photochemical approaches for the synthesis of the C28–C38 fragment of okadaic acid

Okadaic acid, a potent and selective inhibitor of Protein Phosphatases 1 and 2A (PP1 and PP2A), is widely used as a probe for various biochemical processes. We describe herein two innovative methods for the synthesis of the terminal C28–C38 fragment of the natural polyether. Suárez photochemical oxidative cyclization and electrochemical oxidation of malonates to their ketals equivalents have been successfully applied for the assembly of the key spiroketal core.     

Development and validation of a RP-HPLC method for Roflumilast and its degradation products

Roflumilast is a phosphodiesterase type 4 inhibitor that is administered orally as a long-term, in the clinical treatment of chronic obstructive pulmonary disease and asthma. Launched in 2010 for the European market, it currently does not have an official monograph. Here, a reproducible gradient RP-HPLC method was developed and validated for the separation and determination of Roflumilast in the presence of its six major degradation products. Separation was performed on a C₁₈ analytical column (250?×?4.6?mm, 5?µm) with a mobile phase-A of ACN and a phase-B of ammonium acetate buffer (5?mM, pH 4.2) containing triethylamine (0.5% v/v). The most effective RP-HPLC gradient program was determined to be 0/80, 35/10, 36/80, 40/80 (time in minutes/% mobile phase-B). The flow rate was 1.0?ml/min and the column temperature was 25°C. The success of separation of the degradation products with different chemical characteristics was obtained by extending the time of the gradient, changing the proportion of the mobile phases and increasing the velocity of the flow. Two detectors were evaluated for the identification of degradation products and Roflumilast: a diode-arrary detector and a charged aerosol detector. The inability of the charged aerosol detector to dectect one of the six degradation products indicated that the method developed with RP-HPLC and the diode-array detector was more suitable for Roflumilast analysis. The method was validated according to specificity, linearity, LOD, LOQ, accuracy, precision and robustness.     

Biosynthesis,characterization, and antimicrobial effect of silver nanoparticles obtained using <Emphasis Type="Italic">Lavandula</Emphasis> × <Emphasis Type="Italic">intermedia</Emphasis>

The use..... of aqueous leaf extract of Lavandula × intermedia for biosynthesis of silver nanoparticles (AgNPs) is presented. The plant extract was obtained by boiling dried leaves and using the obtained filtrate for the synthesis of AgNPs. The study was conducted to investigate an ecofriendly approach to metal nanoparticle synthesis and to evaluate the antimicrobial potential of both the aqueous plant extract and resulting silver nanoparticles against different microbes using the disc diffusion method. The synthesis of silver nanoparticles was monitored using ultraviolet–visible (UV–v is) spectroscopy, which showed a localized surface plasmon resonance band at 411 nm and a shift of the band to higher wavenumber of 422 nm after 90 min of reaction. Powder X-ray diffraction analysis and transmission electron microscopy of the obtained AgNPs revealed their crystalline nature, with average size of 12.6 nm. Presence of elemental silver was further confirmed by energy-dispersive X-ray spectroscopy. Fourier-transform infrared spectroscopy confirmed presence of phytochemicals from Lavandula × intermedia leaf extract on the AgNPs. The AgNPs showed good antimicrobial activity with inhibition zone ranging from 10 to 23 mm; the largest inhibition zone (23 mm) occurred against Escherichia coli. Generally, the AgNPs displayed more antimicrobial activity against all investigated pathogens compared with Lavandula × intermedia leaf extract, and were also more active than streptomycin against Klebsiella oxytoca and E. coli at the same concentration. The silver nanoparticles showed prominent antimicrobial activity with a lowest minimum inhibitory concentration (MIC) value of 15 μg/mL against E. coli, K. oxytoca, and Candida albicans.     

On the Topology of Real Algebraic Plane Curves

We revisit the problem of computing the topology and geometry of a real algebraic plane curve. The topology is of prime interest but geometric information, such as the position of singular and critical points, is also relevant. A challenge is to compute efficiently this information for the given coordinate system even if the curve is not in generic position. Previous methods based on the cylindrical algebraic decomposition use sub-resultant sequences and computations with polynomials with algebraic coefficients. A novelty of our approach is to replace these tools by Gröbner basis computations and isolation with rational univariate representations. This has the advantage of avoiding computations with polynomials with algebraic coefficients, even in non-generic positions. Our algorithm isolates critical points in boxes and computes a decomposition of the plane by rectangular boxes. This decomposition also induces a new approach for computing an arrangement of polylines isotopic to the input curve. We also present an analysis of the complexity of our algorithm. An implementation of our algorithm demonstrates its efficiency, in particular on high-degree non-generic curves.     

Topological representation of posets

There is a canonical imbedding of a poset into a complete Boolean lattice and hence into a Boolean lattice. This gives it a representation as a collection of clopen sets of a Boolean space. There are reflective functions from a category of distributive posets to the subcategories of distributive and Boolean lattices and consequently a topological dual equivalence that extends the Stone duality of Boolean lattices.Presented by B. Jonsson.     

Asymptotic behavior of the distribution of the stock price in models with stochastic volatility: the Hull–White model

In the present Note, we study the asymptotic behavior of the distribution density of the stock price process in the Hull–White model. The leading terms in the asymptotic expansions at zero and infinity are found for such a density and the corresponding error estimates are given. Similar problems are solved for time averages of the volatility process, which are also of interest in the study of Asian options. To cite this article: A. Gulisashvili, E.M. Stein, C. R. Acad. Sci. Paris, Ser. I 343 (2006).     

Group-wise sufficient dimension reduction with principal fitted components

Sufficient dimension reduction methodologies in regressions of Y on a p-variate X aim at obtaining a reduction \(R(X) \in {\mathbb R}^{d}, d \le p\), that retains all the regression information of Y in X. When the predictors fall naturally into a number of known groups or domains, it has been established that exploiting the grouping information often leads to more effective sufficient dimension reduction of the predictors. In this article, we consider group-wise sufficient dimension reduction based on principal fitted components, when the grouping information is unknown. Principal fitted components methodology is coupled with an agglomerative clustering procedure to identify a suitable grouping structure. Simulations and real data analysis demonstrate that the group-wise principal fitted components sufficient dimension reduction is superior to the standard principal fitted components and to general sufficient dimension reduction methods.