Green synthesis and characterization of silver nanoparticles using Juniperus communis leaf extract: Catalytic activity in real-outdoor conditions and electrochemical properties

The present study investigates the green synthesis of stable silver nanoparticles using Juniperus communis leaf aqueous extract at room temperature. Synthesized silver nanoparticles (AgNPs) were characterized with different techniques such as UV–vis spectroscopy, Fourier transforms infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), Scanning electron microscopy (SEM-EDAX) and electrochemical method. Photocatalytic and anti-bacterial activities of synthesized AgNPs are evaluated based on the obtained result showed an efficient inhibition growth for gram negative P. Aeruginosa, E. Coli, and gram positive bacteria S.aureus. The AgNPs exhibited an excellent photocatalytic activity toward the degradation of methylene blue both indoor and outdoor, under sunlight, an efficiency of 95% was achieved. As an easy and environmentally friendly process, AgNPs based on Juniperus communis leaf extract could be applied for the degradation of pollutants and wastewater treatment.     

Large deviation results for the nonparametric regression function estimator on functional data

This paper is devoted to the study of large deviation behavior in the setting of the estimation of the regression function on functional data. A large deviation principle is stated for a process Z _n , defined below, allowing to derive a pointwise large deviation principle for the Nadaraya- Watson-type l-indexed regression function estimator as a by-product. Moreover, a uniform over VC-classes Chernoff type large deviation result is stated for the deviation of the l-indexed regression estimator.     

Computer simulations of ligand–protein binding with ensembles of protein conformations: A Monte Carlo study of HIV‐1 protease binding energy landscapes

We present the results of molecular docking simulations with HIV‐1 protease for the sb203386 and skf107457 inhibitors by Monte Carlo simulated annealing. A simplified piecewise linear energy function, the standard AMBER force field, and the AMBER force field with solvation and a soft‐core smoothing component are employed in simulations with a single‐protein conformation to determine the relationship between docking simulations with a simple energy function and more realistic force fields. The temperature‐dependent binding free energy profiles of the inhibitors interacting with a single protein conformation provide a detailed picture of relative thermodynamic stability and a distribution of ligand binding modes in agreement with experimental crystallographic data. Using the simplified piecewise linear energy function, we also performed Monte Carlo docking simulations with an ensemble of protein conformations employing preferential biased sampling of low‐energy protein conformations, and the results are analyzed in connection with the free energy profiles. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 72: 73–84, 1999     

Scheduling the two-machine open shop problem under resource constraints for setting the jobs

This paper addresses the problem of open shop scheduling on two machines with resources constraints. In the context of our study, in order to be executed, a job requires first, for its preparation for a given period of time, a number of resources which cannot exceed a given resource capacity. Then, it goes onto its execution while the resources allocated to it become available again. We seek a schedule that minimizes the makespan. We first prove the $\mathcal{N}\mathcal{P}$ -hardness of several versions of this problem. Then, we present a well solvable case, lower bounds, and heuristic algorithms along with an experimental study.     

Preparation of doublet, triangular, and tetrahedral colloidal clusters by controlled emulsification

We describe a six-step method for making colloidal clusters of 2, 3, or 4 silica particles with a radius of 1.2 microm. This method, originally described by Manoharan et al. (Manoharan, V. N.; Elsesser, M. T.; Pine, D. J. Science 2003, 301, 483), is based on the encapsulation of silica spheres in emulsion droplets. The originality of our work lies in the preparation of monodisperse emulsions, which allows us to obtain some high yields of small aggregates over a wide range of conditions. Using optical microscopy and disk centrifugation, we show that the relative fractions of 2, 3, and 4 particle aggregates are controlled by the emulsification conditions, particularly the concentration of silica in the dispersed phase. Our best yields are obtained using low to moderate shear rates, a highly viscous continuous phase, and intermediate amounts of silica. The sedimentation of the colloidal solution into a gradient of concentration leads to aqueous suspensions of identical clusters. Since the overall process can easily be scaled up, large quantities of identical clusters may be prepared, which should allow the thermodynamic properties of these new colloidal objects to be measured for the first time. These nonspherical particles could serve as building blocks for more complex assemblies, such as colloidal crystals which could find applications as photonic materials.     

Bounding the optimum for the problem of scheduling the photographs of an Agile Earth Observing Satellite

The problem of managing an Agile Earth Observing Satellite consists of selecting and scheduling a subset of photographs among a set of candidate ones that satisfy imperative constraints and maximize a gain function. We propose a tabu search algorithm to solve this NP-hard problem. This one is formulated as a constrained optimization problem and involves stereoscopic and time window visibility constraints; and a convex evaluation function that increases its hardness. To obtain a wide-ranging and an efficient exploration of the search space, we sample it by consistent and saturated configurations. Our algorithm is also hybridized with a systematic search that uses partial enumerations. To increase the solution quality, we introduce and solve a secondary problem; the minimization of the sum of the transition durations between the acquisitions. Upper bounds are also calculated by a dynamic programming algorithm on a relaxed problem. The obtained results show the efficiency of our approach.     

Two Mercury Chloro Thiocyanate Complexes: NH4[HgCl2(SCN)] and NH4[HgCl(SCN)2]

Single crystals of NH₄[HgCl₂(SCN)] ( 1 ) and NH₄[HgCl(SCN)₂] ( 2 ) are obtained by slow evaporation of ethanol solutions of HgCl₂ and NH₄SCN or Hg(SCN)₂ and NH₄Cl. 1 crystallizes in the monoclinic space group P2₁ (a = 9.297(1), b = 4.171(1), c = 9.198(1)Å, β = 92.827(5)°). The structure consists in HgCl₂(SCN) linear chains, extending along the twofold axis, connected through the ammonium ions. 2 crystallizes in the monoclinic space group C2/c (a = 7.088(1), b = 19.986(2), c = 5.958(1)Å, β = 100.718(5)°). The structure consists of HgCl(SCN)₂ molecules connected through the ammonium ions. The second order non linear optical properties of 1 are discussed.     

Crystal Structure of a Cadmium Iodate Monohydrate: Cd(IO3)2·H2O

Single crystals of Cd(IO₃)₂·H₂O are obtained by slow evaporation of aqueous solutions of CdCl₂ and KIO₃. This compound crystallizes in the triclinic space group P1¯ [a = 7.119(2), b = 7.952(2), c = 6.646(2)Å, α = 102.17(2)°, β = 114.13(2)°, γ = 66.78(4)°]. The structure consists in Cd — (μ2‐O)₂ — Cd dimers with a metal — metal distance of 3.74Å. These dimers are connected through two iodate bridges resulting in layers parallel to the (010) plane. The 3D linkage is ensured by I1 — O1 long bonds (2.775Å).     

Some Functional Large Deviations Principles in?Nonparametric Function Estimation

In this paper, we investigate functional large deviation behaviors of some nonparametric function estimates. As a first step, we define a a vector process W _n and study its large deviation behavior in the space L ₁×L ₁×L ₁ with respect to the weak convergence topology. As by-products, we derive large deviation principles in the L ₁-space equipped with the weak convergence topology simultaneously for several density and regression estimators built up using the delta-sequence estimation method.