External stimulus-responsive biomaterials designed for the culture and differentiation of ES,iPS, and adult stem cells

The physical and chemical characteristics of biomaterial surface and hydrogels can be altered by external stimuli, such as light irradiation, temperature changes, pH shifts, shear stress forces, electrical forces, and the addition of small chemical molecules. Such external stimulus-responsive biomaterials represent promising candidates that have been developed for the culture and differentiation of embryonic stem (ES) cells, induced pluripotent stem (iPS) cells, and adult stem cells. Biomaterials that are designed to respond in a reversible manner to specific external signals can be formed on micropatterned or non-micropatterned surface, in hydrogels, or on microcarriers. Stem cells and the cells differentiated from them into specific tissue lineages can be cultured and/or differentiated on dishes with immobilized external stimulus-responsive polymers. Cells can be detached from these dishes without using an enzymatic digestion method or a mechanical method when the appropriate external stimulus is generated on the surface. This review discusses the polymers and polymeric designs employed to produce surface and hydrogels for stem cell culture, differentiation, and/or cell detachment using various external stimuli.     

A conflict-based priority dispatching rule and operation-based approaches to job shops

Job shop scheduling (JSS) problems consist of a set of machines and a collection of jobs to be scheduled. Each job consists of several operations with a specified processing order. In this paper, a job shop model problem is scheduled with the help of the Giffler and Thompson algorithm using a priority dispatching rule (PDR). A conflict based PDR is used to schedule the job shop model by using Genetic Algorithms (GAs). An iterative method is applied to the job model to find the optimal conflict-based PDR order and the operation sequence. The same job shop model is also scheduled based on an operation using simulated annealing (SA) and hybrid simulated annealing (HSA). A makespan of the job model is used as an objective. These four methods are considered as different solutions for each problem. A two-way analysis of variance (ANOVA) is applied to test its significance.     

Assembling nanowires from Mo-S clusters and effects of iodine doping on electronic structure

Using ab initio calculations, we find high stability of octahedral Mo6S8 clusters, which can further be condensed to form Mo3nS3n+2 (n, an integer) nanowires. These linear structures are energetically more favorable compared with other closed-packed polyhedral isomers of Mo-S clusters. The octahedral units in nanowires are stabilized by strong Mo-Mo interactions and p-d hybridization between Mo 4d and S 2p orbitals. There is a free electron-like band that crosses the Fermi energy in infinite nanowires and leads to their metallic character. Iodine doping acts as electron donor and can be used to tailor the electronic conductivity. For Mo12S8I4 nanowires, both electrons and holes are found to contribute to conduction. These nanowires are energetically more favorable than the experimentally obtained Mo12S6I12 nanowires.     

Region based coronary artery segmentation using modified Frangi's vesselness measure

Recent research suggests that the cardiovascular diseases (CVDs), seem to be the foremost cause of mortality among the world populace. Three dimensional (3D) imaging modality such as computed tomography angiography(CTA) is a standard noninvasive imaging modality which has great potentials for the visualization of heart and coronary arteries. This article presents a fully automated method for coronary artery extraction using modified Frangi's vesselness measure and region based segmentation. In this article, grayness and gradient based measures are used while computing Frangi's vesselness measure to improve the extraction of coronary arteries. The obtained vesselness measures are utilized for automatically computing the location of ostia. The locations of ostia are then used as starting seed points in region growing segmentation to extract coronary arteries. Three major coronary arteries, namely the left anterior descending artery (LAD), left circumflex artery (LCX) and right coronary artery (RCA) are segmented using the proposed method and the centerlines are extracted for the main coronary branches. The performance of the proposed method is evaluated using 12 3D CCTA data set. The experimental results reveal that during the calculation of modified Frangi's vesselness measure the proposed method gives improved results. The qualitative results obtained during the segmentation stage are also convincing. The average segmentation accuracy and overlap measure of the proposed method are 97.4% and 77.86%, respectively. Hence, the proposed automated approach can detect and extract coronary arteries in CCTA images with high performance.     

An Efficient Image Analysis Framework for the Classification of Glioma Brain Images Using CNN Approach

The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours. The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work. The non-active cells in brain region are known to be benign and they will never cause the death of the patient. These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels. The Magnetic Resonance (MR) image contrast is improved by the cost map construction technique. The deep learning algorithm for differentiating the normal brain MRI images from glioma cases is implemented in the proposed method. This technique permits to extract the linear features from the brain MR image and glioma tumors are detected based on these extracted features. Using k-mean clustering algorithm the tumor regions in glioma are classified. The proposed algorithm provides high sensitivity, specificity and tumor segmentation accuracy.     

Green synthesis of silver nanoparticles using Zea mays and exploration of its biological applications

The biosynthesis of silver nanoparticles (AgNPs) has been proved to be a cost effective and environmental friendly approach toward chemical and physical methods. In the present study, biosynthesis of AgNPs was carried out using aqueous extract of Zea mays (Zm) husk. The initial colour change from golden yellow to orange was observed between 410 and 450 nm which confirmed the synthesis of AgNPs. Also, dynamic light scattering‐particle size analysis confirmed the average size to be 113 nm and zeta potential value of −28 kV. The morphology of synthesised Zm AgNPs displayed flower‐shaped structure, X‐ray diffraction pattern revealed the strongest peaks at 2θ = 38.6° and 64° which proved that the nanoparticle has the face centred crystalline structure. The Fourier transform infrared spectroscopy results showed strong absorption bands at 1394.53, 2980.02 and 2980.02 cm⁻¹ due to the presence of alkynes, carboxylic acids, alcoholic and phenolic groups. The maximum zone of inhibition was observed against Salmonella typhi (22 mm) and Candida albicans (18 mm). The synthesised nanoparticles exhibited more free radical scavenging activity than the aqueous plant extract. This is the first report on the synthesis of AgNP from Zm husk, delivers the efficient and stable Zm AgNPs through simple feasible approach toward green biotechnology.Inspec keywords: silver, nanoparticles, nanofabrication, light scattering, particle size, X‐ray diffraction, crystal structure, Fourier transform infrared spectra, absorption coefficients, free radicalsOther keywords: green synthesis, silver nanoparticles, biosynthesis, environmental friendly approach, aqueous extract, Zea mays husk, colour change, golden yellow, dynamic light scattering‐particle size analysis, average size, zeta potential value, flower‐shaped structure, X‐ray diffraction pattern, face centred crystalline structure, Fourier transform infrared spectroscopy, absorption bands, alkynes, carboxylic acids, alcoholic groups, phenolic groups, Salmonella typhi, Candida albicans, free radical scavenging activity, aqueous plant extraction, green biotechnology, size 113 nm, wavelength 410 nm to 450 nm     

A coprecipitation technique to prepare Sro.5Bao.5Nb206

An aqueous mixture of ammonium oxalate and ammonium hydroxide was used to coprecipitate barium and strontium ions as oxalates and niobium ions as hydroxide under basic conditions. This precursor on calcining at 750°C yielded Sr_0.5Ba_0.5Nb₂O₆ phase. This is a much lower temperature than that prepared by traditional solid state method (1000°C) as reported for the formation of Sr_0.5Ba_0.5Nb₂0₆ (SBN). Transmission electron microscopic (TEM) investigations revealed that the average particle size was 80 nm for the calcined powders. The room temperature dielectric constant at 1 kHz was found to be 1100. The ferroelectric hysteresis loop parameters of these samples were also studied.     

Influence of transverse load on the high cycle fatigue behaviour of low pressure cast AZ91 magnesium alloy

A new testing procedure, employing transverse load was adopted to investigate the high cycle fatigue behaviour of low pressure cast AZ91 magnesium alloy. The tests were conducted with an electro dynamic shaker system by employing specimens fabricated as per ASTM standard. S–N plot was generated from the test results and compared with that of gravity cast AZ91 alloy tested in identical ambience. The influence of transverse load on the fatigue behaviour of these alloys is discussed. As fatigue cracks were found to have initiated in pores in most of the tested samples, pores were assumed as initial cracks as per linear fracture mechanics and the critical stress intensity amplitude (K_cr) was estimated. Structure–fatigue property correlations are discussed using fractographs. Mean stress effect on the fatigue properties and effects of alloying constituents are also discussed.