Numerical Simulation of a Multi-Output Radar Orthogonal Waveform Based on a Chaos Optimization Algorithm

Russian Physics Journal - Aiming at problems of low probability of interception and poor anti-jamming performance of the multi-output radar, the numerical simulation based on a chaos optimization...     

Synthesis and characterization of cellulose acetate from cellophane industry residues. Application as acetaminophen controlled-release membranes

Journal of Thermal Analysis and Calorimetry - Cellophane film production generates cellulosic residues from scraps, edges, and low-quality films. In this work, cellophane was used as a raw material...     

Stability conditions in families

Publications mathématiques de l'IHÉS - We develop a theory of Bridgeland stability conditions and moduli spaces of semistable objects for a family of varieties. Our approach is based...     

Contingent derivatives and regularization for noncoercive inverse problems

Abstract

We study the inverse problem of parameter identification in noncoercive variational problems that commonly appear in applied models. We examine the differentiability of the set-valued parameter-to-solution map using the first-order and the second-order contingent derivatives. We explore the inverse problem using the output least-squares and the modified output least-squares objectives. By regularizing the noncoercive variational problem, we obtain a single-valued regularized parameter-to-solution map and investigate its smoothness and boundedness. We also consider optimization problems using the output least-squares and the modified output least-squares objectives for the regularized variational problem. We give a complete convergence analysis showing that for the output least-squares and the modified output least-squares, the regularized minimization problems approximate the original optimization problems suitably. We also provide the first-order and the second-order adjoint method for the computation of the first-order and the second-order derivatives of the output least-squares objective. We provide discrete formulas for the gradient and the Hessian calculation and present numerical results.     

On cardinal characteristics of Yorioka ideals

Yorioka introduced a class of ideals (parametrized by reals) on the Cantor space to prove that the relation between the size of the continuum and the cofinality of the strong measure zero ideal on the real line cannot be decided in . We construct a matrix iteration of c.c.c. posets to force that, for many ideals in that class, their associated cardinal invariants (i.e., additivity, covering, uniformity and cofinality) are pairwise different. In addition, we show that, consistently, the additivity and cofinality of Yorioka ideals does not coincide with the additivity and cofinality (respectively) of the ideal of Lebesgue measure zero subsets of the real line.     

Synthesis of Highly Functionalized N,N-Diarylamides by an Anodic C,N-Coupling Reaction

We report an innovative, sustainable and straightforward protocol for the synthesis of N,N-diarylamides equipped with nonprotected hydroxyl groups by using electrosynthesis. The concept allows the application of various substrates furnishing diarylamides with yields up to 57 % within a single and direct electrolytic protocol. The method is thereby easy to conduct in an undivided cell with constant current conditions offering a versatile and short-cut alternative to conventional pathways.     

Code2vect: An efficient heterogenous data classifier and nonlinear regression technique

The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: qualitative or quantitative and continuous or discrete. Contrary to other artificial intelligence techniques based on the “Big-Data,” this new approach will enable working with a reduced amount of data, within the so-called “Smart Data” paradigm. Moreover, the main purpose of this algorithm is to enable the representation of high-dimensional data and more specifically grouping and visualizing this data according to a given target. For that purpose, the data will be projected into a vectorial space equipped with an appropriate metric, able to group data according to their affinity (with respect to a given output of interest). Furthermore, another application of this algorithm lies on its prediction capability. As it occurs with most common data-mining techniques such as regression trees, by giving an input the output will be inferred, in this case considering the nature of the data formerly described. In order to illustrate its potentialities, two different applications will be addressed, one concerning the representation of high-dimensional and categorical data and another featuring the prediction capabilities of the algorithm.     

Temperature-Controlled Stereodivergent Synthesis of 2,2′-Biflavanones Promoted by Samarium Diiodide

In this work, the first example of a radical stereodivergent reaction directed towards the stereoselective synthesis of both (R*,R*)- and (R*,S*)-2,2′-biflavanones promoted by samarium diiodide is reported. Control experiments showed that the selectivity of this reaction was exclusively controlled by the temperature. It was possible to generate a variety of 2,2′-biflavanones bearing different substitution patterns at the aromatic ring in good-to-quantitative yields, being both stereoisomers of the desired compounds obtained with total or high control of selectivity. A mechanism that explains both the generation of the corresponding 2,2′-biflavanones and the selectivity is also discussed. The structure and stereochemistry determination of each isomer was unequivocally elucidated by single-crystal X-ray diffraction experiments.     

Janus Gold Nanostars–Mesoporous Silica Nanoparticles for NIR-Light-Triggered Drug Delivery

Janus gold nanostar–mesoporous silica nanoparticle ( AuNSt–MSNP ) nanodevices able to release an entrapped payload upon irradiation with near infrared (NIR) light were prepared and characterized. The AuNSt surface was functionalized with a thiolated photolabile molecule ( 5 ), whereas the mesoporous silica face was loaded with a model drug (doxorubicin) and capped with proton-responsive benzimidazole-β-cyclodextrin supramolecular gatekeepers ( N 1 ). Upon irradiation with NIR-light, the photolabile compound 5 photodissociated, resulting in the formation of succinic acid, which induced the opening of the gatekeeper and cargo delivery. In the overall mechanism, the gold surface acts as a photochemical transducer capable of transforming the NIR-light input into a chemical messenger (succinic acid) that opens the supramolecular nanovalve. The prepared hybrid nanoparticles were non-cytotoxic to HeLa cells, until they were irradiated with a NIR laser, which led to intracellular doxorubicin release and hyperthermia. This induced a remarkable reduction in HeLa cells viability.