A Brief Comparison Between Available Bio-printing Methods

The scarcity of organs for transplant has led to large waiting lists of very sick patients. In drug development, the time required for human trials greatly increases the time to market. Drug companies are searching for alternative environments where the in-vivo conditions can be closely replicated. Both these problems could be addressed by manufacturing artificial human tissue. Recently, researchers in tissue engineering have developed tissue generation methods based on 3-D printing to fabricate artificial human tissue. Broadly, these methods could be classified as laser-assisted and laser free. The former have very fine spatial resolutions (10s of $\mu$m) but suffer from slow speed ( $< 10^2$ drops per second). The later have lower spatial resolutions (100s of $\mu$ m) but are very fast (up to $5\times 10^3$ drops per second). In this paper we review state-of-the-art methods in each of these classes and provide a comparison based on reported resolution, printing speed, cell density and cell viability

A Framework for Megascale Agent Based Model Simulations on Graphics Processing Units

Agent-based modeling is a technique for modeling dynamic systems from the bottom up. Individual elements of the system are represented computationally as agents. The system-level behaviors emerge from the micro-level interactions of the agents. Contemporary state-of-the-art agent-based modeling toolkits are essentially discrete-event simulators designed to execute serially on the Central Processing Unit (CPU). They simulate Agent-Based Models (ABMs) by executing agent actions one at a time. In addition to imposing an un-natural execution order, these toolkits have limited scalability. In this article, we investigate data-parallel computer architectures such as Graphics Processing Units (GPUs) to simulate large scale ABMs. We have developed a series of efficient, data parallel algorithms for handling environment updates, various agent interactions, agent death and replication, and gathering statistics. We present three fundamental innovations that provide unprecedented scalability. The first is a novel stochastic memory allocator which enables parallel agent replication in O(1) average time. The second is a technique for resolving precedence constraints for agent actions in parallel. The third is a method that uses specialized graphics hardware, to gather and process statistical measures. These techniques have been implemented on a modern day GPU resulting in a substantial performance increase. We believe that our system is the first ever completely GPU based agent simulation framework. Although GPUs are the focus of our current implementations, our techniques can easily be adapted to other data-parallel architectures. We have benchmarked our framework against contemporary toolkits using two popular ABMs, namely, SugarScape and StupidModel.GPGPU, Agent Based Modeling, Data Parallel Algorithms, Stochastic Simulations

Sparse And Low Rank Decomposition Based Batch Image Alignment for Speckle Reduction of retinal OCT Images

Optical Coherence Tomography (OCT) is an emerging technique in the field of biomedical imaging, with applications in ophthalmology, dermatology, coronary imaging etc. Due to the underlying physics, OCT images usually suffer from a granular pattern, called speckle noise, which restricts the process of interpretation. Here, a sparse and low rank decomposition based method is used for speckle reduction in retinal OCT images. This technique works on input data that consists of several B-scans of the same location. The next step is the batch alignment of the images using a sparse and low-rank decomposition based technique. Finally the denoised image is created by median filtering of the low-rank component of the processed data. Simultaneous decomposition and alignment of the images result in better performance in comparison to simple registration-based methods that are used in the literature for noise reduction of OCT images.Comment: Accepted for presentation at ISBI'1

On signalling over through-silicon via (TSV) interconnects in 3-D integrated circuits.

This paper discusses signal integrity (SI) issues and signalling techniques for Through Silicon Via (TSV) interconnects in 3-D Integrated Circuits (ICs). Field-solver extracted parasitics of TSVs have been employed in Spice simulations to investigate the effect of each parasitic component on performance metrics such as delay and crosstalk and identify a reduced-order electrical model that captures all relevant effects. We show that in dense TSV structures voltage-mode (VM) signalling does not lend itself to achieving high data-rates, and that current-mode (CM) signalling is more effective for high throughput signalling as well as jitter reduction. Data rates, energy consumption and coupled noise for the different signalling modes are extracted

Study of serum magnesium levels in pre-diabetics and its correlation to body mass index

Background: Diabetes is a growing public health burden across the world, particularly in the developing countries. Homeostasis of the trace elements such as magnesium has been found to play an important role in the pathogenesis of diabetes and diabetic complications. Studies had found out an association between serum magnesium and incident diabetes; where diabetes may induce urinary magnesium loss. But in pre-diabetes, serum glucose levels are below the threshold for urinary magnesium wasting and hence unlikely to influence serum magnesium levels. This study was done to assess their serum magnesium levels and find its correlation.Methods: This cross sectional study was done among 120 pre-diabetic subjects. Pre-diabetes was diagnosed as per ADA guidelines and body mass index was calculated according to Asian guidelines of BMI. Serum magnesium levels were done for all of them and statistically analysed to correlate the serum magnesium with body mass.Results: The present study observed that 69 out of 120 pre-diabetics, 57.5% have low magnesium levels. This study showed that 57.5% of pre-diabetics is having normal body mass index, out of which more than half of them are having normal serum magnesium. But out of 12 obese pre-diabetics, 11 were having low serum magnesium 91.6%. (P value 0.026 which is statistically significant).Conclusions: This study observed that serum magnesium levels are low in Pre-diabetics. Significant hyomagnesemia has been seen in pre-diabetics with high BMI compared to those with normal BMI.

Minimal Walking Technicolor: Set Up for Collider Physics

Different theoretical and phenomenological aspects of the Minimal and Nonminimal Walking Technicolor theories have recently been studied. The goal here is to make the models ready for collider phenomenology. We do this by constructing the low energy effective theory containing scalars, pseudoscalars, vector mesons and other fields predicted by the minimal walking theory. We construct their self-interactions and interactions with standard model fields. Using the Weinberg sum rules, opportunely modified to take into account the walking behavior of the underlying gauge theory, we find interesting relations for the spin-one spectrum. We derive the electroweak parameters using the newly constructed effective theory and compare the results with the underlying gauge theory. Our analysis is sufficiently general such that the resulting model can be used to represent a generic walking technicolor theory not at odds with precision data.Comment: 42 pages, 3 figures. RevTex forma

Mass transfer coefficient evaluation for lab scale fermenter using sodium sulphite oxidation method

Oxygen transfer is often the rate-limiting step in the aerobic bioprocess due to the low solubility of oxygen inside the aqueous solution. The rate of reaction is such that as oxygen enters the liquid phase, it is immediately consumed to oxidize the sulfite so that the rate of oxidation is equivalent to the oxygen-transfer rate.  Reaction rate often determined by titration is much faster than oxygen transfer rate so that gas- liquid mass transfer is the rate controlling step. The current study involves using central composite design, a statistical technique to find out the parameter conditions for the optimum volumetric mass transfer coefficient in a lab scale (2L) fermentor. The optimum volumetric mass transfer coefficient was found to lie outside the range of parameters studied and analytical expressions was obtained to predict the volumetric mass transfer coefficients for the parameter ranges studied using response surface methodology.  The analytical expression was found to be significantly valid based on ANOVA results. Keywords: Aerobic bioprocess; Sodium sulphite oxidation process; Mass transfer coefficient; Central composite desig

Shale fracture surface area measured by tracking exchangeable cations

Hydrocarbon production from oil shale and shale gas is increasingly important for securing the energy supply to society. Such shale reservoirs, however, typically have low permeability, and hydraulic fracturing is required to facilitate economic production. Hydraulic fracturing significantly increases fracture-matrix contact areas (through activating pre-existing fractures as well as creating an artificial fracture network), which is of key importance for efficient production. In this context it is vital to estimate this contact area and associated fracture network structures. Conventional techniques, i.e. micro-seismic mapping and pressure transient analysis, however, only deliver limited information. We thus propose here a new experimental technique, which can measure fracture-matrix contact areas; and the accuracy of contact area measurements can be considerably improved. The proposed technique is based on cation exchange processes and chemical tracer measurements. We verified this technique experimentally with laboratory measurements and demonstrated that fracture-matrix areas can be measured with good precision. It is furthermore possible to gather information about the fracture network structure by conducting transient measurements. We conclude that the proposed technique is feasible, and can be combined with conventional techniques to significantly improve measurement accuracy