Silver (I) antimicrobial cotton nonwovens and printcloth

In this paper we discuss the preparation and comparative evaluation of silver (I) [Ag(I)] nonwoven and woven antimicrobial barrier fabrics generated from commercial calcium‐sodium alginates and laboratory prepared sodium carboxymethyl (CM) cotton nonwovens and CM‐cotton printcloth for potential use as wound dressings. Degrees of CM substitution (DS) in cotton nonwoven and printcloth samples by titrimetry were 0.38 and 0.10, respectively. Coordination of Ag(I) with carboxylates on fabrics was effected by ion exchange and nitrates were removed by washing to mitigate nitrate ion toxicity issues. Durability of silver coordinated fabrics was tested by soaking them in deionized water with slight agitation at 50°C. Ag(I) alginates and nonwoven Ag(I)‐CM‐cottons lost structural integrity in water. Ag‐CM‐cotton printcloth samples retained structural integrity even after four soak‐and‐dry cycles, were smooth to the touch when dry, and were smoother when moistened. They could be easily peeled from wound surfaces without inducing trauma. Solid‐state carbon‐13 (¹³C) nuclear magnetic resonance (NMR) spectrometry was used to observe changes in carbonyl resonances in Ag(I) alginates and Ag(I)‐CM‐printcloth, and the chemical shift positions of carbonyl resonances of uncoordinated and Ag(I) coordinated fabrics did not change. Inductively coupled plasma‐mass spectrometry (ICP‐MS) was used following fabric digestion to determine the total Ag(I) ion content in fabrics. Ag(I) alginates were found to hold about 10–50 mg Ag(I) per gram fabric; and Ag(I) cotton woven and nonwoven fabrics held about 5–10 mg Ag(I) ions per gram fabric. Kinetic release of Ag(I) after soaking once in physiological saline was studied with ICP‐MS to estimate the availability of Ag(I) upon a single exchange with Na(I) ions on wound surfaces. Alginates released between ～13 and 28% of coordinated Ag(I), and CM‐cotton nonwovens and CM‐cotton printcloth released ～14 and 3% of coordinated Ag(I) ions, respectively. Finally, Ag(I) alginates and Ag(I)‐CM‐cotton printcloth samples were evaluated against Gram‐positive Staphylococcus aureus and Gram‐negative Klebsiella pneumoniae. Ag(I) alginates suppressed 99.95% of bacterial growth in vitro. Even after four soak‐and‐dry cycles in deionized water Ag(I)‐CM‐cotton printcloth suppressed 99.99% of bacterial growth in vitro. Published in 2007 by John Wiley & Sons, Ltd.     

Synthesis,characterization, and application of monodisperse gelatin-stabilized silver nanospheres in reduction of aromatic nitro compounds

Monodisperse colloidal silver nanospheres were synthesized by the reaction of silver nitrate, hydroxylammonium hydrosulphate (NH₂OH)₂ · H₂SO₄ and sodium hydroxide in the presence of gelatin as stabilizer. Colloidal nanospheres were characterized by UV-vis absorption spectroscopy, transmission electron microscopy, X-ray diffraction and dynamic light scattering. X-ray diffraction data confirmed that the silver nanospheres were crystalline with face-centered-cubic structure. Transmission electron microscopy analysis revealed the formation of homogeneously distributed silver nanoparticles of spherical morphology and size of the nanoparticles was in the range of 0.7–5.2 nm. Silver nanospheres were stable for more than two months when stored at ambient temperature. Size and size distribution were studied by varying pH, reaction temperature, silver ion concentration in feed solution, concentration of reducing agent and concentration of the stabilizing agent. Catalytic activity of silver nanospheres was tested for the reduction reaction of nitro compounds in sodium borohydride solution. Monodisperse silver nanospheres showed excellent catalytic activity towards the reduction of aromatic nitro compounds. The reduction rate of aromatic nitro compounds had been observed to follow the sequence 4-nitrophenol > 2-nitrophenol > 3-nitrophenol.     

Dynamic microscopic basis for IBM-2: A new approach

A dynamic approach, based on deformed Hartree-Fock solution of a nucleus, is suggested for obtaining correlated identical nucleon pair wave function for neutrons and protons. Expressions for single pair energies and two pair interaction matrix elements amongst the neutron and proton pairs in the microscopic fermion basis are presented. These matrix elements define the IBM-2 Hamiltonian through Marumori mapping. The entire procedure is illustrated by obtaining the IBM-2 spectra of²⁰Ne,⁴⁴Ti,⁶⁰Zn and⁹⁴Mo and comparing them with shell model (SM) and/or experimental results. The Yrast levels given by our calculations match well with those of the SM and the experimental results for all the four nuclei, while the non-Yrast levels do not barring the case of⁹⁴Mo. This is due to the loss of isospin symmetry for light nuclei in IBM-2. These results are discussed in detail.     

Block splitting for distributed optimization

This paper describes a general purpose method for solving convex optimization problems in a distributed computing environment. In particular, if the problem data includes a large linear operator or matrix $A$ , the method allows for handling each sub-block of $A$ on a separate machine. The approach works as follows. First, we define a canonical problem form called graph form, in which we have two sets of variables related by a linear operator $A$ , such that the objective function is separable across these two sets of variables. Many types of problems are easily expressed in graph form, including cone programs and a wide variety of regularized loss minimization problems from statistics, like logistic regression, the support vector machine, and the lasso. Next, we describe graph projection splitting, a form of Douglas–Rachford splitting or the alternating direction method of multipliers, to solve graph form problems serially. Finally, we derive a distributed block splitting algorithm based on graph projection splitting. In a statistical or machine learning context, this allows for training models exactly with a huge number of both training examples and features, such that each processor handles only a subset of both. To the best of our knowledge, this is the only general purpose method with this property. We present several numerical experiments in both the serial and distributed settings.     

Comparative and Combinatorial Effects of Resveratrol and Sacubitril/Valsartan alongside Valsartan on Cardiac Remodeling and Dysfunction in MI-Induced Rats

The development and progression of heart failure (HF) due to myocardial infarction (MI) is a major concern even with current optimal therapy. Resveratrol is a plant polyphenol with cardioprotective properties. Sacubitril/valsartan is known to be beneficial in chronic HF patients. In this study, we investigated the comparative and combinatorial benefits of resveratrol with sacubitril/valsartan alongside an active comparator valsartan in MI-induced male Sprague Dawley rats. MI-induced and sham-operated animals received vehicle, resveratrol, sacubitril/valsartan, valsartan alone or sacubitril/valsartan + resveratrol for 8 weeks. Echocardiography was performed at the endpoint to assess cardiac structure and function. Cardiac oxidative stress, inflammation, fibrosis, brain natriuretic peptide (BNP), creatinine and neutrophil gelatinase associated lipocalin were measured. Treatment with resveratrol, sacubitril/valsartan, valsartan and sacubitril/valsartan + resveratrol significantly prevented left ventricular (LV) dilatation and improved LV ejection fraction in MI-induced rats. All treatments also significantly reduced myocardial tissue oxidative stress, inflammation and fibrosis, as well as BNP. Treatment with the combination of sacubitril/valsartan and resveratrol did not show additive effects. In conclusion, resveratrol, sacubitril/valsartan, and valsartan significantly prevented cardiac remodeling and dysfunction in MI-induced rats. The reduction in cardiac remodeling and dysfunction in MI-induced rats was mediated by a reduction in cardiac oxidative stress, inflammation and fibrosis.     

Difference in nature of correlation between NASDAQ and BSE indices

We apply a recently developed wavelet based approach to characterize the correlation and scaling properties of non-stationary financial time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The built-in variable windows in wavelet transform makes this procedure well suited for the non-stationary data. We analyze daily price of NASDAQ composite index for a period of 20 years, and BSE sensex index, over a period of 15 years. It is found that the long-range correlation, as well as fractal behavior for both the stock index values differ from each other significantly. Strong non-statistical long-range correlation is observed in BSE index, whose removal revealed a Gaussian random noise character for the corresponding fluctuation. The NASDAQ index, on the other hand, showed a multifractal behavior with long-range statistical correlation.     

Characterizing and modelling cyclic behaviour in non-stationary time series through multi-resolution analysis

A method based on wavelet transform is developed to characterize variations at multiple scales in non-stationary time series. We consider two different financial time series, S&P CNX Nifty closing index of the National Stock Exchange (India) and Dow Jones industrial average closing values. These time series are chosen since they are known to comprise of stochastic fluctuations as well as cyclic variations at different scales. The wavelet transform isolates cyclic variations at higher scales when random fluctuations are averaged out; this corroborates correlated behaviour observed earlier in financial time series through random matrix studies. Analysis is carried out through Haar, Daubechies-4 and continuous Morlet wavelets for studying the character of fluctuations at different scales and show that cyclic variations emerge at intermediate time scales. It is found that Daubechies family of wavelets can be effectively used to capture cyclic variations since these are local in nature. To get an insight into the occurrence of cyclic variations, we then proceed to model these wavelet coefficients using genetic programming (GP) approach and using the standard embedding technique in the reconstructed phase space. It is found that the standard methods (GP as well as artificial neural networks) fail to model these variations because of poor convergence. A novel interpolation approach is developed that overcomes this difficulty. The dynamical model equations have, primarily, linear terms with additive Padé-type terms. It is seen that the emergence of cyclic variations is due to an interplay of a few important terms in the model. Very interestingly GP model captures smooth variations as well as bursty behaviour quite nicely.      

Empirical adjustment for atmospheric transmittances based on calculated and measured radiances

This study summarizes important aspects of transmittance correction for the high-resolution infrared detector aboard the TIROS-N satellite. Accurate transmittances for infrared channels are necessary for the determination of atmospheric temperature profiles based on solution of the radiative transfer equation. The global means of the difference between the observed and calculated radiances for HIRS channels were calculated; the differences between these could not be explained on the basis of channel noise. An empirical correction of the transmittances was determined, and it was found that the optimum correction depended on latitude zones and other factors. In order to find a correction that is valid globally, an attempt was made to relate the correction for a given channel to the temperature of the atmospheric-pressure level at which the channel-weighting function peaks. The results did not indicate a clear correlation, and the scatter of points was beyond acceptable range.     

Random matrix theory and the statistical mechanics of disordered systems

A new method, that systematically combines results of random matrix theory and the usual statistical mechanics, is described to study thermodynamic properties of disordered systems. Two exactly solvable models are examined in this formulation to illustrate the usefulness of this method for systems described by random as well as non-random Hamiltonian.