Chemo,stereo, and regioselective addition of α‐(2‐methoxyaryl)‐N‐aryl nitrones to diarylidineacetone: Synthesis of novel isoxazolidines

A new set of 2,3,4,5‐tetrasubstituted isoxazolidines with an α,β‐unsaturated carbonyl function at position 4 has been synthesized. The multicomponent approach and microwave irradiation protocol have also been investigated for the above synthesis.     

Conformationally locked bridged bicyclic diselenides: synthesis, structure, Se...O interaction, and theoretical studies

A general synthetic methodology has been developed for the synthesis of a conformationally locked, bridged diselena-bicyclo[3.2.1]octane skeleton by regio- and stereospecific tandem nucleophilic ring opening of cis-1,4-aziridino-epoxides with tetraethylammonium tetraselenotungstate [Et4N]2WSe4, 1, in a one-pot synthesis. Some correlations have been made on the physicochemical characteristics of the diselenides with a change in the dihedral angles.     

Regio- and stereospecific synthesis of beta-sulfonamidodisulfides and beta-sulfonamidosulfides from aziridines using tetrathiomolybdate as a sulfur transfer reagent

A comprehensive study of a general and effective one-step procedure for the synthesis of beta-sulfonamidodisulfides directly from N-tosyl aziridines in a regio- and stereospecific manner under neutral conditions without the use of any Lewis acid or base has been reported. This methodology is extended to the synthesis of an optically pure cyclic seven-membered disulfide 29. Synthesis of a variety of beta-sulfonamidosulfides involving tandem, multistep reactions in one pot is also reported.     

Stabilized gold nanoparticles by reduction using 3,4-ethylenedioxythiophene-polystyrenesulfonate in aqueous solutions: nanocomposite formation, stability, and application in catalysis

Herein, we report a one-pot synthesis of highly stable Au nanoparticles (AuNPs) using 3,4-ethylenedioxythiophene (EDOT) as a reductant and polystyrene sulfonate (PSS-) as a dopant for PEDOT and particle stabilizer. The synthesis demonstrated in this work entails the reduction of HAuCl4 using EDOT in the presence of PSS-. The formation of AuNPs with concomitant EDOT oxidation is followed by UV-vis spectroscopy at various time intervals. Absorption at 525 nm is due to the surface plasmon band of AuNPs (violet), and broad absorption above 700 nm is due to oxidized PEDOT that was further characterized to be in its highly oxidized (doped) state, using FT-Raman spectroscopy. Transmission electron microscopy shows a polydisperse nature of the particles, and the selected area electron diffraction pattern reveals the polycrystalline nature of AuNPs. With stabilizers such as sodium dodecylsulfate (SDS) (green) and polyvinylpyrrolidone (PVP) (blue), the absorbance around 525 nm was found to be negligibly small, while PSS- showed high absorbance at 525 nm (violet) and above 700 nm (oxidized PEDOT). PSS- also allows complete oxidation of EDOT and serves as an effective dopant for PEDOT. While AuNPs covered by PEDOT alone cannot be dispersed in aqueous solutions, PSS- renders Au-PEDOT water soluble. The hydrodynamic diameter of the nanocomposite estimated from the dynamic light scattering (DLS) measurements increases in the order Na-PSS < SDS < PVP. Interestingly, the color of the Au(nano)-PEDOT/PSS- aqueous dispersion changed reversibly between violet and blue and vice versa on addition of NaOH and HCl, respectively. This reversible color change appears to be a combination effect of acid/base on the properties of PEDOT, in turn changing the environment around the embedded AuNPs. The nanoparticle dispersion also exhibited very high stability in presence of 3.0 M NaCl. Remarkably, the nanocomposite Au(nano)-PEDOT/PSS- was found to function as an effective catalyst to activate the reduction of 4-nitrophenol to 4-aminophenol in the presence of excess NaBH4, and the calculated apparent rate constant value of 4.39 x 10-2 s-1 is found to be higher than those obtained using other nanocomposites with SDS and PVP and comparable to the values reported in the case of other encapsulants.     

A novel extracellular synthesis of monodisperse gold nanoparticles using marine alga, Sargassum wightii Greville

The process of development of reliable and eco-friendly metallic nanoparticles is an important step in the field of nanotechnology. To achieve this use of natural sources like biological systems becomes essential. In the present, work we have investigated extracellular biosynthesis of gold nanoparticles using Sargassum wightii and have achieved rapid formation of gold nanoparticles in a short duration. The UV-vis spectrum of the aqueous medium containing gold ion showed peak at 527 nm corresponding to the plasmon absorbance of gold nanoparticles. Transmission electron microscopy (TEM) showed formation of well-dispersed gold nanoparticles in the range of 8-12 nm. X-ray diffraction (XRD) spectrum of the gold nanoparticles exhibited Bragg reflections corresponding to gold nanoparticles.     

Cubic potential models for cluster radioactivity

Cluster radioactivity is a process by which nuclei equal and heavier than the α-particle is emitted spontaneously. The clusters usually emitted in this process are the α-particle, carbon, oxygen, neon, magnesium, silicon etc. When the mass of the cluster becomes comparable with the mass of the daughter, symmetric fission takes place. Thus the cluster radioactivity is an intermediate process between the well known α-decay and the spontaneous fission. In earlier years such cluster radioactivity was found mostly in actinide nuclei like radium, uranium etc. Very recently it has been predicted that such decays are possible in a new region around ¹¹¹Ba. There has been an exciting experimental detection of the emission of ¹²C from ¹¹¹Ba leading to ¹⁰²Sn, which is attracting a lot of attention recently. To study the phenomenon of cluster radioactivity there are various theoretical models in vogue. The existing models generally fall under two categories: the unified fission model (UFM) and the preformed cluster model (PCM). The physics of the UFM and the PCM are completely different. The UFM considers cluster radioactivity simply as a barrier penetration phenomenon in between the fission and the α-decay without worrying about the cluster being or not being preformed in the parent nucleus. In the PCM clusters are assumed to be preborn in a parent nucleus before they could penetrate the potential barrier with a given Q-value. The basic assumption of the UFM is that heavy clusters as well as the α-particle have equal probability of being preformed. In PCM, clusters of different sizes have different probabilities of their being preformed in the parent nucleus. We have developed three fission models during the last decade using the cubic potential for the pre-scission region. The use of these models in the study of cluster radioactivity in both the actinide and barium regions will be discussed in this talk in comparison with the other existing theories.     

Poissonian Behavior of Ising Spin Systems in an External Field

We apply the Stein–Chen method for Poisson approximation to spin-half Ising-type models in positive external field which satisfy the FKG inequality. In particular, we show that, provided the density of minus spins is low and can be expanded as a convergent power series in the activity (fugacity) variable, the distribution of minus spins is approximately Poisson. The error of the approximation is inversely proportional to the number of lattice sites (we obtain upper and lower bounds on the total variation distance between the exact distribution and its Poisson approximation). We illustrate these results by application to specific models, including the mean-field and nearest neighbor ferromagnetic Ising models.     

An Adaptive Rank Aggregation-Based Ensemble Multi-Filter Feature Selection Method in Software Defect Prediction

Feature selection is known to be an applicable solution to address the problem of high dimensionality in software defect prediction (SDP). However, choosing an appropriate filter feature selection (FFS) method that will generate and guarantee optimal features in SDP is an open research issue, known as the filter rank selection problem. As a solution, the combination of multiple filter methods can alleviate the filter rank selection problem. In this study, a novel adaptive rank aggregation-based ensemble multi-filter feature selection (AREMFFS) method is proposed to resolve high dimensionality and filter rank selection problems in SDP. Specifically, the proposed AREMFFS method is based on assessing and combining the strengths of individual FFS methods by aggregating multiple rank lists in the generation and subsequent selection of top-ranked features to be used in the SDP process. The efficacy of the proposed AREMFFS method is evaluated with decision tree (DT) and naïve Bayes (NB) models on defect datasets from different repositories with diverse defect granularities. Findings from the experimental results indicated the superiority of AREMFFS over other baseline FFS methods that were evaluated, existing rank aggregation based multi-filter FS methods, and variants of AREMFFS as developed in this study. That is, the proposed AREMFFS method not only had a superior effect on prediction performances of SDP models but also outperformed baseline FS methods and existing rank aggregation based multi-filter FS methods. Therefore, this study recommends the combination of multiple FFS methods to utilize the strength of respective FFS methods and take advantage of filter–filter relationships in selecting optimal features for SDP processes.     

Particle Sizing Using Frequency Domain Photon Migration

The transport properties of particulate process streams and their final product quality, are directly affected by critical parameters of particle size distribution, f(x), and volume, mass, or number density of particles or dispersed phase droplets. A method is proposed for the potential on-line monitoring of particle size distribution and volume fraction in real time, using frequency-domain photon migration measurements (FDPM). Theory, experimental measurements, and results for the determination of particle size distributions for both a polystyrene latex and a titanium dioxide suspension determined using the photon migration technique are presented. The critical issues associated with the application of photon migration to particulate and dispersed phase processes are discussed, including the effects of interparticle interactions on the transport of light.     

Interventional Fairness with Indirect Knowledge of Unobserved Protected Attributes

The deployment of machine learning (ML) systems in applications with societal impact has motivated the study of fairness for marginalized groups. Often, the protected attribute is absent from the training dataset for legal reasons. However, datasets still contain proxy attributes that capture protected information and can inject unfairness in the ML model. Some deployed systems allow auditors, decision makers, or affected users to report issues or seek recourse by flagging individual samples. In this work, we examine such systems and consider a feedback-based framework where the protected attribute is unavailable and the flagged samples are indirect knowledge. The reported samples are used as guidance to identify the proxy attributes that are causally dependent on the (unknown) protected attribute. We work under the causal interventional fairness paradigm. Without requiring the underlying structural causal model a priori, we propose an approach that performs conditional independence tests on observed data to identify such proxy attributes. We theoretically prove the optimality of our algorithm, bound its complexity, and complement it with an empirical evaluation demonstrating its efficacy on various real-world and synthetic datasets.