A translator system for the MATLAB language

A whole‐program MATLAB to C translation system is presented. The paper outlines the motivation for the problem, discusses the system's architecture, its features and limitations. The translator's operation is explained using an example input program. Details are given on how the system implements and specializes some of the language's built‐in primitives. Finally, the paper reports measurements evaluating the execution time and memory usage of the translated sources, and the compilation time required for the translations. Copyright © 2006 John Wiley & Sons, Ltd.     

Solvothermal synthesis and characterization of acicular α-Fe2O3 nanoparticles

Nanometer-sized α-Fe₂O₃ particles have been prepared by a simple solvothermal method using ferric acetylacetonate as a precursor. The products were characterized by X-ray diffraction (XRD), energy dispersive X-ray microanalysis (EDAX), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), transition electron microscopy (TEM), infrared spectroscopy (IR) and thermal analysis (TG-DTA). XRD indicates that the product is single-phase α-Fe₂O₃ with rhombohedral structure. Bundles of acicular shaped nanoparticles are seen in TEM images with an aspect ratio ～ 12; typically 8–12 nm wide and over 150 nm long. The α-Fe₂O₃ nanoparticles posses a high thermal stability, as observed on thermal analysis traces.     

Classification of Hydrogels Based on Their Source: A Review and Application in Stem Cell Regulation

Stem cells are recognized by their self-renewal ability and can give rise to specialized progeny. Hydrogels are an established class of biomaterials with the ability to control stem cell fate via mechanotransduction. They can mimic various physiological conditions to influence the fate of stem cells and are an ideal platform to support stem cell regulation. This review article provides a summary of recent advances in the application of different classes of hydrogels based on their source (e.g., natural, synthetic, or hybrid). This classification is important because the chemistry of substrate affects stem cell differentiation and proliferation. Natural and synthetic hydrogels have been widely used in stem cell regulation. Nevertheless, they have limitations that necessitate a new class of material. Hybrid hydrogels obtained by manipulation of the natural and synthetic ones can potentially overcome these limitations and shape the future of research in application of hydrogels in stem cell regulation.     

Binary Galois field based asynchronous scheduling protocol for delay tolerant networks

Wireless Networks - Neighbour discovery plays a crucial role for communication in sparsely dense mobile networks, especially in delay tolerant networks, where neighbour discovery latency is...     

Optimizations for Efficient Array Redistribution on Distributed Memory Multicomputers

Appropriate data distribution has been found to be critical for obtaining good performance on distributed memory multicomputers such as the Thinking Machines CM-5, Intel Paragon, and IBM SP-1/SP-2. It has also been found that some programs need to change their distributions during execution for better performance (redistribution). This work focuses on automatically generating efficient routines for redistribution. We present a new mathematical representation for regular distributions called FALLS and then discuss algorithms for redistribution based on this representation. One of the significant contributions of this work is being able to handle arbitrary source and target processor sets while performing redistribution. Another important contribution is the ability to handle an arbitrary number of dimensions for the array involved in the redistribution in a scalable manner. Our implementation of these techniques is based on the MPI communication library. The results presented show the efficiency and scalability of our redistribution algorithm.     

CD73 and PD-L1 as Potential Therapeutic Targets in Gallbladder Cancer

Gallbladder cancer (GBC) is one of the most common and aggressive biliary tract cancers with a dismal prognosis. Ongoing clinical trials are evaluating a few selected immune checkpoint inhibitors (ICIs) as monotherapy for the treatment of GBC patients. However, only a subset of patients benefits from these treatments. To improve ICI therapy response, molecular mechanisms that confer resistance to immune checkpoint (IC) blockade needs to be explored. Epithelial-to-mesenchymal transition (EMT) program and cancer stem cells (CSCs) have been implicated as key processes that confer ICI treatment resistance. However, in GBC the EMT-CSC-IC axis has not yet been clearly elucidated. This study aims to examine the aberrant expression of ICs associated with CSC and EMT. We successfully enriched CSCs by utilizing a 3-dimensional culture system and established a reversible EMT model with human GBC NOZ cell line. Notably, ICs CD73 and PD-L1 were closely associated with both CSC and EMT phenotypes. Knockdown of CD73 or PD-L1 reduced the proliferative and motile abilities of both adherent monolayers and anchorage-free spheroids. In conclusion, blocking CD73 and PD-L1 offer a promising therapeutic strategy for targeting highly aggressive populations with CSC and EMT phenotype to improve GBC patient prognosis.     

Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

We have designed efficient quantum circuits for the three-qubit Toffoli (controlled–controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the “Luck-Choose” mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.