Study of thermodegradation and thermostabilization of poly(lactide acid) using subsequent extrusion cycles

The thermomechanical degradation and thermostabilization of poly(lactic acid) (PLA) have been studied using subsequent extrusion cycles under different temperature profiles. Primary and secondary antioxidants were used to avoid degradation process during extrusion. Melt flow index (MFI), size exclusion chromatography (SEC), and infrared spectroscopy (FTIR) analysis were used to evaluate the degradation and stabilization of PLA. The MFI and SEC analysis show that the main thermodegradation mechanism of PLA is governed by scission reactions. FTIR analysis confirmed the SEC results and showed that the synergetic effect between primary and secondary antioxidant is a suitable way to thermostabilize the PLA. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2014 , 131, 40023.     

An economic analysis comparing the cost feasibility of replacing injection molding processes with emerging additive manufacturing techniques

Additive manufacturing (AM) has proliferated in recent years and is displacing traditional manufacturing methods in numerous applications due to improvements in process efficiencies and cost reductions related to the evolving AM processes. This study explores the cost structure and break-even points of AM versus traditional methods. The comparative analysis examined the cost requirements of AM versus injection molding to manufacture various lot sizes of parts. Break-even points based on lot sizes and the relationship to the overall cost structure were also calculated. This research concludes that break-even points may be calculated based on part mass, density, and lot size.     

Efficient Utilization of SIMD Extensions

This paper targets automatic performance tuning of numerical kernels in the presence of multilayered memory hierarchies and single-instruction, multiple-data (SIMD) parallelism. The studied SIMD instruction set extensions include Intel's SSE family, AMD's 3DNow!, Motorola's AltiVec, and IBM's BlueGene/L SIMD instructions. FFTW, ATLAS, and SPIRAL demonstrate that near-optimal performance of numerical kernels across a variety of modern computers featuring deep memory hierarchies can be achieved only by means of automatic performance tuning. These software packages generate and optimize ANSI C code and feed it into the target machine's general-purpose C compiler to maintain portability. The scalar C code produced by performance tuning systems poses a severe challenge for vectorizing compilers. The particular code structure hampers automatic vectorization and, thus, inhibits satisfactory performance on processors featuring short vector extensions. This paper describes special-purpose compiler technology that supports automatic performance tuning on machines with vector instructions. The work described includes: 1) symbolic vectorization of digital signal processing transforms; 2) straight-line code vectorization for numerical kernels; and 3) compiler back ends for straight-line code with vector instructions. Methods from all three areas were combined with FFTW, SPIRAL, and ATLAS to optimize both for memory hierarchy and vector instructions. Experiments show that the presented methods lead to substantial speedups (up to 1.8 for two-way and 3.3 for four-way vector extensions) over the best scalar C codes generated by the original systems as well as roughly matching the performance of hand-tuned vendor libraries.     

Discrete fourier transform on multicore

This article gives an overview on the techniques needed to implement the discrete Fourier transform (DFT) efficiently on current multicore systems. The focus is on Intel-compatible multicores, but we also discuss the IBM Cell and, briefly, graphics processing units (GPUs). The performance optimization is broken down into three key challenges: parallelization, vectorization, and memory hierarchy optimization. In each case, we use the Kronecker product formalism to formally derive the necessary algorithmic transformations based on a few hardware parameters. Further code-level optimizations are discussed. The rigorous nature of this framework enables the complete automation of the implementation task as shown by the program generator, Spiral. Finally, we show and analyze DFT benchmarks of the fastest libraries available for the considered platforms.     

FFTs with Near-Optimal Memory Access Through Block Data Layouts: Algorithm,Architecture and Design Automation

Fast Fourier transform algorithms on large data sets achieve poor performance on various platforms because of the inefficient strided memory access patterns. These inefficient access patterns need to be reshaped to achieve high performance implementations. In this paper we formally restructure 1D, 2D and 3D FFTs targeting a generic machine model with a two-level memory hierarchy requiring block data transfers, and derive memory access pattern efficient algorithms using custom block data layouts. These algorithms need to be carefully mapped to the targeted platform’s architecture, particularly the memory subsystem, to fully utilize performance and energy efficiency potentials. Using the Kronecker product formalism, we integrate our optimizations into Spiral framework and evaluate a family of DRAM-optimized FFT algorithms and their hardware implementation design space via automated techniques. In our evaluations, we demonstrate DRAM-optimized accelerator designs over a large tradeoff space given various problem (single/double precision 1D, 2D and 3D FFTs) and hardware platform (off-chip DRAM, 3D-stacked DRAM, ASIC, FPGA, etc.) parameters. We show that Spiral generated pareto optimal designs can achieve close to theoretical peak performance of the targeted platform offering 6x and 6.5x system performance and power efficiency improvements respectively over conventional row-column FFT algorithms.     

Nonlinear Damping Identification in Precast Prestressed Reinforced Concrete Beams

Abstract:  This article presents a damage detection method for prestressed reinforced concrete (PRC) elements based on free vibration tests and nonlinear damping identification. Integrated static and dynamic experiments were carried out on three precast PRC beam specimens. The static loading induced different levels of damage to the beams. At each damage level, impulsive loading was applied to the beams and the free vibration response was measured. The dynamic response data were processed using different methods including the multi-input multi-output (MIMO) curve fitting and the Hilbert transform techniques. A strong correlation is observed between the level of concrete damage (cracks) and the amount of nonlinear energy dissipation that can be modeled by means of quadratic damping. The nonlinear damping can be extracted from the free vibration response for each vibration mode. The proposed method is suited for quality control when manufacturing precast PRC members, and can be further extended for in situ detection of damage in concrete structures under ambient vibration.     

Wettability of Aqueous Rhamnolipids Solutions Produced by Pseudomonas aeruginosa LBI

The wetting behavior of rhamnolipids produced by Pseudomonas aeruginosa LBI strain grown on waste oil substrate and sodium dodecyl sulfate (SDS) on glass, polyethylene terephthalate (PET), poly(vinyl chloride) (PVC), poly(ε-caprolactone) (PCL) and polymer blend (PVC–PCL) was investigated by the measuring contact angle of sessile drops, to determine the wetting characteristics of rhamnolipids. The comparison of the wetting profiles showed that at low SDS and rhamnolipid concentrations, the contact angle increased and when the concentration of the surfactant increased further, the contact angle decreased. The blend surface (PVC–PCL) showed better wettability than the homopolymers themselves and the blend changed the surface hydrophobicity of the polymer, making it more hydrophilic. The rhamnolipids produced by the LBI strain exhibited superior wetting abilities than the chemical surfactant SDS one. This is the first work that evaluates the wetting properties of rhamnolipids on polymer blends.

Synthesis, structure, and antiproliferative activity of selenophenfurin, an inosine 5'-monophosphate dehydrogenase inhibitor analogue of selenazofurin

The synthesis and biological activity of selenophenfurin (5-beta-D-ribofuranosylselenophene-3-carboxamide, 1), the selenophene analogue of selenazofurin, are described. Glycosylation of ethyl selenophene-3-carboxylate (6) under stannic chloride-catalyzed conditions gave 2- and 5-glycosylated regioisomers, as a mixture of alpha- and beta-anomers, and the beta-2,5-diglycosylated derivative. Deprotected ethyl 5-beta-D-ribofuranosylselenophene-3-carboxylate (12 beta) was converted into selenophenfurin by ammonolysis. The structure of 12 beta was determined by 1H- and 13C-NMR, crystallographic, and computational studies. Selenophenfurin proved to be antiproliferative against a number of leukemia, lymphoma, and solid tumor cell lines at concentrations similar to those of selenazofurin but was more potent than the thiophene and thiazole analogues thiophenfurin and tiazofurin. Incubation of K562 cells with selenophenfurin resulted in inhibition of IMP dehydrogenase (IMPDH) (76%) and an increase in IMP pools (14.5-fold) with a concurrent decrease in GTP levels (58%). The results obtained confirm the hypothesis that the presence of heteroatoms such as S or Se in the heterocycle in position 2 with respect to the glycosidic bond is essential for both cytotoxicity and IMP dehydrogenase inhibitory activity in this type of C-nucleosides.     

SPIRAL: Code Generation for DSP Transforms

Fast changing, increasingly complex, and diverse computing platforms pose central problems in scientific computing: How to achieve, with reasonable effort, portable optimal performance? We present SPIRAL, which considers this problem for the performance-critical domain of linear digital signal processing (DSP) transforms. For a specified transform, SPIRAL automatically generates high-performance code that is tuned to the given platform. SPIRAL formulates the tuning as an optimization problem and exploits the domain-specific mathematical structure of transform algorithms to implement a feedback-driven optimizer. Similar to a human expert, for a specified transform, SPIRAL "intelligently" generates and explores algorithmic and implementation choices to find the best match to the computer's microarchitecture. The "intelligence" is provided by search and learning techniques that exploit the structure of the algorithm and implementation space to guide the exploration and optimization. SPIRAL generates high-performance code for a broad set of DSP transforms, including the discrete Fourier transform, other trigonometric transforms, filter transforms, and discrete wavelet transforms. Experimental results show that the code generated by SPIRAL competes with, and sometimes outperforms, the best available human tuned transform library code.     

Decomposition pathways and in vitro HIV inhibitory effects of isoddA pronucleotides: toward a rational approach for intracellular delivery of nucleoside 5'-monophosphates

The decomposition pathways and kinetics in various biological media and the in vitro anti-HIV-1 and anti-HIV-2 activities of four derivatives of the 5'-mononucleotide of isoddA incorporating carboxylate esterase-labile transient phosphate protecting groups are reported and compared: namely, two mononucleoside aryl phosphoramidate derivatives 1a,b and two mononucleoside phosphotriester derivatives incorporating two S-acyl-2-thioethyl groups 2a,b. All four compounds show better antiviral activity, compared to the parent nucleoside analog isoddA. The results highlight that both types of compounds act as pronucleotides, i.e. they exert their antiviral effect via intracellular delivery of the 5'-mononucleotide of isoddA. The results may give insights for the design of new more efficient pronucleotides.