Mesoporous titanium dioxide nanocatalyst: a recyclable approach for one‐pot synthesis of 5‐hydroxymethylfurfural

The present study deals with the production of 5‐hydroxymethyl furfural (HMF) from fructose by chemo‐conversion method using chemical catalyst, conventionally achieved by microwave‐assisted dehydration process. Five different chemical catalysts, namely oxalic acid, phosphotungstic acid and mesoporous titanium dioxide nanoparticles (TNPs) were compared at constant conditions of which TNPs yielded a maxima of 33.95%. The optimum temperature and catalyst loading were found to be 200°C and 20%, respectively, at a 5% optimum substrate concentration during 15 min optimum reaction time to yield 61.53% HMF. The efficiency of synthesised TNPs was investigated further through reusability studies. TNPs were properly recycled and the catalytic activity recovery was good even after a 14 batch reactions. The specific surface area of the TNP obtained is about 105.46 m² /g and its pore‐volume is about 0.42 cm³ /g according to single point adsorption. A large accessible surface area combined with a minimal pore size (15.92 nm) obtained with mesoporous TNPs is desirable for better catalyst loading, high‐yield HMF, retention and reduced diffusion constraints.Inspec keywords: mesoporous materials, recycling, production management, dissociation, nanoparticles, nanotechnologyOther keywords: mesoporous titanium dioxide nanocatalyst, recyclable approach, one‐pot synthesis, 5‐hydroxymethyl furfural production, HMF, chemo‐conversion method, chemical catalyst, microwave‐assisted dehydration process, oxalic acid, phosphotungstic acid, mesoporous titanium dioxide nanoparticles, TNP     

Lanthanide Doped Near Infrared Active Upconversion Nanophosphors: Fundamental Concepts,Synthesis Strategies,and Technological Applications

Near infrared (NIR) light utilization in a range of current technologies has gained huge significance due to its abundance in nature and nondestructive properties. NIR active lanthanide (Ln) doped upconversion nanomaterials synthesized in controlled shape, size, and surface functionality can be combined with various pertinent materials for extensive applications in diverse fields. Upconversion nanophosphors (UCNP) possess unique abilities, such as deep tissue penetration, enhanced photostability, low toxicity, sharp emission peaks, long anti‐Stokes shift, etc., which have bestowed them with prodigious advantages over other conventional luminescent materials. As new generation fluorophores, UCNP have found a wide range of applications in various fields. In this Review, a comprehensive overview of lanthanide doped NIR active UCNP is provided by discussing the fundamental concepts including the different mechanisms proposed for explaining the upconversion processes, followed by the different strategies employed for the synthesis of these materials, and finally the technological applications of UCNP, mainly in the fields of bioimaging, drug delivery, sensing, and photocatalysis by highlighting the recent works in these areas. In addition, a brief note on the applications of UCNP in other fields is also provided along with the summary and future perspectives of these materials.     

Evaluation of potential anti‐cancer activity of cationic liposomal nanoformulated Lycopodium clavatum in colon cancer cells

Research dealing with early diagnosis and efficient treatment in colon cancer to improve patient''s survival is still under investigation. Chemotherapeutic agent result in high systemic toxicity due to their non‐specific actions on DNA repair and/or cell replication. Traditional medicine such as Lycopodium clavatum (LC) has been claimed to have therapeutic potentials against cancer. The present study focuses on targeted drug delivery of cationic liposomal nanoformulated LC (CL‐LC) in colon cancer cells (HCT15) and comparing the efficacy with an anti‐colon cancer drug, 7‐ethyl‐10‐hydroxy‐camptothecin (SN38) along with its nanoformulated form (CL‐SN38). The colloidal suspension of LC was made using thin film hydration method. The drugs were characterised using ultraviolet, dynamic light scattering, scanning electron microscopy, energy, dispersive X‐ray spectroscopy. In vitro drug release showed kinetics of 49 and 89% of SN38 and LC, whereas CL‐SN38 and CL‐LC showed 73 and 74% of sustained drug release, respectively. Studies on morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis of Bcl‐2, Bax, p53 by real‐time polymerase chain reaction and western blot analysis of Bad and p53 protein were performed. Nanoformulated LC significantly inhibited growth and increased the apoptosis of colon cancer cells indicating its potential anti‐cancer activity against colon cancer cells.Inspec keywords: cancer, biological organs, cellular biophysics, drug delivery systems, drugs, nanomedicine, genetics, DNA, molecular biophysics, biochemistry, lipid bilayers, toxicology, suspensions, colloids, light scattering, X‐ray chemical analysis, solvation, enzymes, nanostructured materialsOther keywords: energy dispersive X‐ray spectroscopy, in vitro drug release, morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis, Bcl‐2, Bax, real‐time polymerase chain reaction, western blot analysis, Bad protein, p53 protein, scanning electron microscopy, dynamic light scattering, ultraviolet scattering, thin film hydration method, colloidal suspension, nanoformulated form CL‐SN38, 7‐ethyl‐10‐hydroxy‐camptothecin, anticolon cancer drug, colon cancer cells HCT15, cationic liposomal nanoformulated LC, targeted drug delivery, therapeutic potentials, Lycopodium clavatum, traditional medicines, cell replication, DNA repair, nonspecific actions, high systemic toxicity, chemotherapeutic agents, patient survival, colon cancer treatment, colon cancer diagnosis, CL‐LC, potential anticancer activity     

Fault diagnosis of spur bevel gear box using discrete wavelet features and Decision Tree classification

The wavelet transform (WT) is used to represent all possible types of transients in vibration signals generated by faults in a gear box. It is shown that the transform provides a powerful tool for condition monitoring and fault diagnosis. The vibration signal of a spur bevel gear box in different conditions is used to demonstrate the application of various wavelets in feature extraction. In present work, a discrete wavelet, Daubechies wavelets (db1–db15) is used for feature extraction and their relative effectiveness in feature extraction is compared. The major steps in pattern classification are feature extraction and classification. This paper investigates the use of discrete wavelets for feature extraction and a Decision Tree for classification. J48 Decision Tree algorithm has been used for feature selection as well as for classification. This paper illustrates the powerfulness and flexibility of the discrete wavelet transform to decompose linear and non-linear processing of vibration signal.     

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing

Microtubules are involved in numerous cellular processes including chromosome segregation during mitosis and, as a result, their constituent protein, tubulin, has become a successful target of several chemotherapeutic drugs. In general, these drugs bind indiscriminately to tubulin within both cancerous and healthy cells, resulting in unwanted side effects. However, differences between beta-tubulin isotypes expressed in a wide range of cell types may aid in the development of anti-tubulin drugs having increased specificity for only certain types of cells. Here, we describe a digital signal processing (DSP) method that is capable of predicting hot spots for the tubulin family of proteins as well as determining relative differences in binding affinities to these hot spots based only on the primary sequence of 10 human tubulin isotypes. Due to the fact that several drug binding sites have already been characterized within beta-tubulin, we are able to correlate hot spots with the binding sites for known chemotherapy drugs. We have also verified the accuracy of this method using the correlation between the binding affinities of characterized drugs and the tubulin isotypes. Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined.     

Human pathogenic streptococcal proteomics and vaccine development

Gram-positive streptococci are non-motile, chain-forming bacteria commonly found in the normal oral and bowel flora of warm-blooded animals. Over the past decade, a proteomic approach combining 2-DE and MS has been used to systematically map the cellular, surface-associated and secreted proteins of human pathogenic streptococcal species. The public availability of complete streptococcal genomic sequences and the amalgamation of proteomic, genomic and bioinformatic technologies have recently facilitated the identification of novel streptococcal vaccine candidate antigens and therapeutic agents. The objective of this review is to examine the constituents of the streptococcal cell wall and secreted proteome, the mechanisms of transport of surface and secreted proteins, and describe the current methodologies employed for the identification of novel surface-displayed proteins and potential vaccine antigens.     

Robust Estimation of GARMA Model Parameters with an Application to Cointegration among Interest Rates of Industrialized Countries

We review the literature on long memory ARFIMA and GARMA models andintroduce a new efficient estimator for GARMA models, which we show to berobust. Next we conduct a Monte Carlo study to demonstate the power of theDickie–Fuller test when the data are generated from a stationary GARMAprocess. We conclude with a brief discussion of cointegration in the contextof GARMA models with an application to international interest rates.     

Probabilistic Belief Contraction

Probabilistic belief contraction has been a much neglected topic in the field of probabilistic reasoning. This is due to the difficulty in establishing a reasonable reversal of the effect of Bayesian conditionalization on a probabilistic distribution. We show that indifferent contraction, a solution proposed by Ramer to this problem through a judicious use of the principle of maximum entropy, is a probabilistic version of a full meet contraction. We then propose variations of indifferent contraction, using both the Shannon entropy measure as well as the Hartley entropy measure, with an aim to avoid excessive loss of beliefs that full meet contraction entails.     

Thermal and structural properties of spray pyrolysed CdS thin film

Using photo acoustic technique, the thermal properties of CdS thin films grown by spray pyrolysis are measured. Thermal diffusivity and conductivity in these films decrease at least two orders compared with bulk. These results are compared with our study on nano CdS and the other available literature. The comparison is good. The dependence of thermal diffusivity on the thickness of the layer or the size of the particles on the glass substrate are analysed from the present measurement and discussed. The dependence of thermal diffusivity on the thickness of the layer on the glass substrate is discussed.     

Toward a more realistic performance evaluation of interconnectionnetworks

lnterconnection network design plays a central role in the design of parallel systems. Most of the previous research has evaluated the performance of interconnection networks in isolation. In this study, we investigate the relationship between application program characteristics and interconnection network performance using an execution driven simulation test bed: the Reconfigurable Architecture Workbench (RAW). We simulate five topological configurations of a k-ary n-cube interconnect and four different network link models for a 4,096 node SIMD machine, and quantify the impact of the network on two application programs. We provide experimental evidence that such “in-context” simulation provides a better view of the impact of network design variables on system performance. We show that recent results, indicating that low-dimensional designs provide better ICN performance, ignore application requirements that may favor high-dimensional designs. Furthermore, applications that would appear to favor low dimensional designs may not, in fact, be significantly impacted by the network's dimensionality. We experimentally test the results of published performance models comparing the use of a synthetic load to that of a load generated by a typical application program