Immobilization and the conformational study of phospholipid and phospholipid-protein vesicles

The present work demonstrates the immobilization of phospholipids and phospholipids-protein vesicles on solid substrate by simple drop-cast technique. We have also studied the structural and conformational transition of protein (OVA) molecules when they are loaded in immobilized vesicles of DPPC. High-resolution FE-SEM imaging is used to study the structural aspects of the immobilized vesicles of DPPC and OVA loaded DPPC. FTIR analyses of amide bands are being used to inspect the extent of the conformational transitions of β-sheet to α-helix of OVA in immobilized DPPC vesicles. Immobilized OVA-DPPC vesicles provide the structure of individual OVA molecule attached with DPPC, without aggregation amongst them.     

Effect of geometric and process variables on the performance of inclined plate settlers in treating aquacultural waste

Inclined plate settlers are used in treating wastewater due to their low space requirement and high removal rates. The prediction of sedimentation efficiency of these settlers is essential for their performance evaluation. In the present study, the technique of dimensional analysis was applied to predict the sedimentation efficiency of these inclined plate settlers. The effect of various geometric parameters namely, distance between plates (w(p)), plate angle (alpha), length of plate (l(p)), plate roughness (epsilon(p)), number of plates (n(p)) and particle diameter (d(s)) on the dynamic conditions, influencing the sedimentation process was studied. From the study it was established that neither the Reynolds criterion nor the Froude criterion was singularly valid to simulate the sedimentation efficiency (E) for different values of w(p) and flow velocity (v(f)). Considering the prevalent scale effect, simulation equations were developed to predict E at different dynamic conditions. The optimum dynamic condition producing the maximum E is also discussed.     

Growth and time dependent alignment of KCl crystals in Hemoglobin LB monolayer

Nature and organism often use the biomineralization technique to build up various highly regular structures such as bone, teeth, kidney stone etc., and recently this becomes the strategy to design and synthesis of novel biocomposite materials. We report here the controlled crystallization of KCl in Langmuir and Langmuir Blodgett (LB) monolayer of Hemoglobin (Hb) at ambient condition. The nucleation and growth of KCl crystals in Hb monolayer has temporal and KCl concentration dependency. The growth of KCl crystals in LB film of Hb has distinct behavior in the alignment of crystals from linear to fractal like structures depending on growth time. The crystallographic identity of the biomineralized KCl crystal is confirmed from HR-TEM, XRD, and from powder diffraction simulation. Our results substantiated that the template of Langmuir monolayer of proteins plays a crucial role in biomineralization as well as in designing and synthesizing of novel biocomposite materials.     

A memristor-based long short term memory circuit

Long-short term memory (LSTM) is a cognitive architecture that aims to mimic the sequence temporal memory processes in human brain. The state and time-dependent based processing of events is essential to enable contextual processing in several applications such as natural language processing, speech recognition and machine translations. There are many different variants of LSTM and almost all of them are software based. The hardware implementation of LSTM remains as an open problem. In this work, we propose a hardware implementation of LSTM system using memristors. Memristor has proved to mimic behavior of a biological synapse and has promising properties such as smaller size and absence of current leakage among others, making it a suitable element for designing LSTM functions. Sigmoid and hyperbolic tangent functions hardware realization can be performed by using a CMOS-memristor threshold logic circuit. These ideas can be extended for a practical application of implementing sequence learning in real-time sensory processing data.