Preparation and characterization of low-halogen and nonhalgoen fire-resistant low-smoke (FRLS) cable sheathing compound from blends of functionalized polyolefins and PVC

An attempt is made to develop a novel series of cable sheathing compounds with variation in chlorine content and sufficient fire retardance and unique low-smoke characteristics. These are prepared by blending PVC and functionalized polyolefins in different compositions. PE and EPDM have been functionalized by grafting dibutyl maleate (DBM) using DCP as initiator. FRLS compounds made from PVC-functionalized polyolefin blends possess the special characteristics of low-smoke, low-acid-gas generation, increased fire retardance, and improved volume resistivity, which are much better in comparison with a typical PVC sheathing compound. Thermoplastic elastomer (TPE) based nonhalogen FRLS compounds are also reported. The mechanisms for grafting, polymer-polymer and polymer-filler interactions have been presented.     

An International Collaborative Study on Trypsin Inhibitor Assay for Legumes,Cereals, and Related Products

For determining trypsin inhibitor activity (TIA) in soy products, the American Oil Chemists' Society (AOCS) Method Ba 12-75 has been used. It measures differences in absorbance at 410 nm of bovine trypsin activity toward a synthetic substrate (Nα-benzoyl-DL-arginine-p-nitroanilide) in the absence and presence of an inhibitor. Recently, a significantly improved method was developed (JAOCS, 2019, 96:635–645), featuring 5 mL of total assay volume, enzyme-last sequence, and single inhibitor level in duplicate. It is proposed as the AOCS Method Ba 12a-2020. As a part of the AOCS method approval process, a collaborative study involving 12 international laboratories was conducted to evaluate the performance of the proposed method. The study involved measuring TIA in 10 selected test samples plus a blind duplicate. They included soybeans, pulses, cereals, and their processed products (flours, concentrates, and isolates). After rigorous statistical treatment of the data, only three outliers were removed from the data of two samples. Repeatability relative standard deviations (RSDr) for the 11 samples ranged from 0.99% to 5.52%. Reproducibility RSD (RSD_R) ranged from 7.07% to 22.92%, with seven samples having RSD_R around 10% or less. The remaining four samples had very low TIA, and their RSD_R values ranged from 13.34% to 22.92%. The study has demonstrated reliable performance of the proposed AOCS method. Several collaborators carried out additional experiments addressing some aspects of the method, leading to further refinements. The proposed method is undergoing evaluation by the AOCS Uniform Methods Committee for adoption as an Official Method for measuring TIA in various legume and grain products.     

3D computer vision based on machine learning with deep neural networks: A review

Recent advances in the field of computer vision can be attributed to the emergence of deep learning techniques, in particular convolutional neural networks. Neural networks, partially inspired by the brain's visual cortex, enable a computer to “learn” the most important features of the images it is shown in relation to a specific, specified task. Given sufficient data and time, (deep) convolutional neural networks offer more easily designed, more generalizable, and significantly more accurate end‐to‐end systems than is possible with previously employed computer vision techniques. This review paper seeks to provide an overview of deep learning in the field of computer vision with an emphasis on recent progress in tasks involving 3D visual data. Through a backdrop of the mammalian visual processing system, we hope to also provide inspiration for future advances in automated visual processing.     

Lattice Boltzmann method simulation of electroosmotic stirring in a microscale cavity

The suitable surface modification of microfluidic channels can enable a neutral electrolyte solution to develop an electric double layer (EDL). The ions contained within the EDL can be moved by applying an external electric field, inducing electroosmotic flows (EOFs) that results in associated stirring. This provides a solution for the rapid mixing required for many microfluidic applications. We have investigated EOFs generated by applying a steady electric field across a square cavity that has homogenous electric potentials along its walls. The flowfield is simulated using the lattice Boltzmann method. The extent of mixing is characterized for different electrode configurations and electric field strengths. We find that rapid mixing can be achieved by using this simple configuration which increases with increasing electric field strength. The mixing time for water-soluble organic molecules can be decreased by four orders of magnitude by suitable choice of wall zeta potential and electric field. We dedicate this paper to the memory of our colleagues Professors Kevin Granata and Liviu Librescu who fell tragically on April 16, 2007 while answering their call to serve higher education. They continue to inspire us. AM gratefully acknowledges support from Jadavpur University under the World Bank funded Technical Education Quality Improvement Programme of the Government of India and the hospitality of the Virginia Tech ESM Department where he conducted a portion of this work.     

Sensorless current control for active rectifiers

A novel model-based sensorless-input current controller for three-phase active rectifiers is presented. The proposed algorithm is based upon a load-conductance rectifier controller, which was previously implemented using current sensors. The paper presents analytical studies and simulation results and discusses a simple implementation using a low cost integrated microcontroller. Experimental verification utilizes an active input/output insulated gate bipolar transistor (IGBT) converter. Simulation and experimental results for the proposed controller are compared to that of the sensor-based version to validate the efficacy of this novel algorithm     

A general compiler framework for speculative multithreaded processors

Speculative multithreading (SpMT) promises to be an effective mechanism for parallelizing nonnumeric programs, which tend to have irregular and pointer-intensive data structures and complex flows of control. Proper thread formation is crucial for obtaining good speedup in an SpMT system. This paper presents a compiler framework for partitioning a sequential program into multiple threads for parallel execution in an SpMT system. This framework is very general and supports speculative threads, nonspeculative threads, loop-centric threads, and out-of-order thread spawning. It is therefore useful for compiling for a wide variety of SpMT architectures. For effective partitioning of programs, the compiler uses profiling, interprocedural pointer analysis, data dependence information, and control dependence information. The compiler is implemented on the SUIF-MachSUIF platform. A simulation-based evaluation of the generated threads shows that the use of nonspeculative threads and nonloop speculative threads provides a significant increase in speedup for nonnumeric programs.     

Element Level System Identification with Unknown Input with Rayleigh Damping

A novel system identification procedure is proposed for nondestructive damage evaluation of structures. It is a finite element-based time-domain linear system identification technique capable of identifying structures at the element level. The unique features of the algorithm are that it can identify a structure without using any input excitation information and it can consider both viscous and Rayleigh-type proportional damping in the dynamic models. The consideration of proportional damping introduces a source of nonlinearity in the otherwise linear dynamic algorithm. However, it will also reduce the total number of damping coefficients to be identified, reducing the size of the problem. The Taylor series approximation is used to transform a nonlinear set of equations to a linear set of equations. The proposed algorithm, denoted as the modified iterative least square with unknown input algorithm, is verified with several examples considering various types of structures including shear-type building, truss, and beams. The algorithm accurately identified the stiffness of structures at the element level for both viscous (linear) and proportional (nonlinear) damping cases. It is capable of identifying a structure even with noise-contaminated response information. An example shows how the algorithm could be used in detecting the exact location of a defect in a defective element. The algorithm is being developed further and is expected to provide an economical, simple, efficient, and robust system identification technique that can be used as a nondestructive defect detection procedure in the near future.     

Text and non-text separation in offline document images: a survey

International Journal on Document Analysis and Recognition (IJDAR) - Separation of text and non-text is an essential processing step for any document analysis system. Therefore, it is important to...