用低成本非易失可编程器件进行平台管理

在电信基础设施服务器和工业应用中,系统设计人员正在转向使用可鳊程逻辑器件.本文介绍了利用可编程逻辑器件MachXO在这些设计中进行平台管理的应用.     

Integrating carbon market uncertainties into a sustainable manufacturing investment decision: a Bayesian NPV approach

Net present value (NPV) is a widely used technique in capital budgeting. In this paper, we develop a Bayesian NPV framework using a Gibbs sampler. This approach allows decision-makers to integrate their knowledge, past experience, and uncertain and volatile cash flows from carbon emissions credits into decisions dealing with energy efficient, sustainable manufacturing equipment. The results indicate NPV is highly dependent on the nature of volatility and uncertainty of the cash flows. Without inclusion of this information through the Bayesian framework results, NPV becomes overstated, and thus it may provide biased guidance for the investment. The results developed in this paper further show that the frequency of very high and low cash flows and to a lesser degree their variability adversely impacts NPV. The results may also explain reasons for the economic phenomenon known as the energy efficiency gap.     

Sulfonated poly(ether ether ketone) reinforced with polystyrene sulfonic acid functionalized micelle templated mesoporous MCM-41 for direct methanol fuel cells

A composite membrane comprising sulfonated polyether ether ketone (sPEEK) and polystyrene sulfonic acid functionalized micelle templated MCM-41 (PSSA-f-MCM-41) is realized as a potential alternative to the Nafion membrane for direct methanol fuel cells (DMFC). PSSA-f-MCM-41 incorporation in sPEEK leads to improvement in the physio-chemical properties such as ionic conductivity, methanol permeability, tensile strength, water uptake and ion exchange capacity. The methanol permeability of the composite membrane i.e. PSSA-f-MCM-41 (1.5 wt %)-sPEEK is reduced by 60% in comparison to pristine sPEEK. Moreover, the electrochemical selectivity of the aforesaid composite membrane is four times higher than sPEEK. The DMFC performance shows the peak power density of 147 mW cm^?2 for the composite membrane which is higher than the pristine sPEEK and Nafion 117 membranes. Stability test for the composite membranes confirm less degradation in OCV in comparison to pristine sPEEK.     

A New Robust and Efficient Ion‐Tagged Proline Catalyst Carrying an Amide Spacer for the Asymmetric Aldol Reaction

The synthesis of a new, highly efficient cis‐ion‐tagged catalyst ( 8a ), possessing an amide linkage between the imidazolium tag and the proline ring, is described. This new bench‐stable catalyst has been tested in the classic asymmetric aldol condensation between ketones and aldehydes “in the presence” of water, and is proposed as a valuable alternative to the analogous but more sensitive ester cis‐ 2d . Catalyst 8a displayed an excellent efficiency in terms of catalyst loading and stereochemical control.     

Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection

The coronavirus COVID-19 pandemic is today’s major public health crisis, we have faced since the Second World War. The pandemic is spreading around the globe like a wave, and according to the World Health Organization’s recent report, the number of confirmed cases and deaths are rising rapidly. COVID-19 pandemic has created severe social, economic, and political crises, which in turn will leave long-lasting scars. One of the countermeasures against controlling coronavirus outbreak is specific, accurate, reliable, and rapid detection technique to identify infected patients. The availability and affordability of RT-PCR kits remains a major bottleneck in many countries, while handling COVID-19 outbreak effectively. Recent findings indicate that chest radiography anomalies can characterize patients with COVID-19 infection. In this study, Corona-Nidaan, a lightweight deep convolutional neural network (DCNN), is proposed to detect COVID-19, Pneumonia, and Normal cases from chest X-ray image analysis; without any human intervention. We introduce a simple minority class oversampling method for dealing with imbalanced dataset problem. The impact of transfer learning with pre-trained CNNs on chest X-ray based COVID-19 infection detection is also investigated. Experimental analysis shows that Corona-Nidaan model outperforms prior works and other pre-trained CNN based models. The model achieved 95% accuracy for three-class classification with 94% precision and recall for COVID-19 cases. While studying the performance of various pre-trained models, it is also found that VGG19 outperforms other pre-trained CNN models by achieving 93% accuracy with 87% recall and 93% precision for COVID-19 infection detection. The model is evaluated by screening the COVID-19 infected Indian Patient chest X-ray dataset with good accuracy.

     

Synthesis, characterization and thermolysis studies on new derivatives of 2,4,5-trinitroimidazoles: potential insensitive high energy materials

This paper reports the synthesis of three new derivatives of 2,4,5-trinitroimidazole namely, 1-methyl-2,4,5-trinitroimidazole (III), 1-carboethoxy-2,4,5-trinitroimidazole (V) and 1-picryl-2,4,5-trinitroimidazole (VII). The title compounds (III) and (V) were synthesized by the nitration of 1-methyl-/1-carboethoxy-(2,4,5-triiodoimidazole) (II and IV) with fuming nitric acid at 0 degrees C and (VII) was synthesized by condensation of 2,4,5-triiodoimidazole (I) with picryl chloride to obtain 1-picryl-2,4,5-triiodoimidazole (VI) followed by its nitration with fuming nitric acid at 0 degrees C. The synthesized compounds have been characterized by elemental analysis, spectral and thermal techniques. The thermolysis studies using TG-DTA revealed exothermic decomposition of the nitroimidazoles (III, V and VII) with T(max) in the temperature range of 196-225 degrees C. The energy of activation obtained for these compounds was in the range 150-170 kJ/mol. The sensitivity data obtained for the newly synthesized compounds (III, V and VII) indicated their safe nature towards external stimuli (h(50%)>100 cm; friction>36 kg) and could be potential candidates for low vulnerable applications in the futuristic systems. The theoretically predicted performance parameters suggest that 1-methyl-2,4,5-trinitroimidazole (III), exhibits higher velocity of detonation (VOD: 8.8 km/s) compared to compounds V and VII (VOD: 7.6 and 8.41 km/s, respectively).