Selective conversion of propane to propene by the catalytic oxidative dehydrogenation over cobalt and magnesium molybdates

Catalytic performances of various metal molybdates were tested in the oxidative dehydrogenation of propane to propene with molecular oxygen under an atmospheric pressure. Most of the molybdates tested promoted the selective oxidative conversion of propane to propene and among them cobalt and magnesium molybdates were found highest in the activity and selectivity. It was also found that their catalytic activities were highly sensitive to the catalyst composition, and it turned out that Co_0.95MoO _x and Mg_0.95MoO _x catalysts which have slightly excess molybdenum showed the highest activity in the oxidative dehydrogenation of propane. Under the optimized reaction conditions, higher reaction temperatures and lower partial pressures of oxygen, these catalysts gave 60% selectivity to propene at 20% conversion of propane. Since the molybdates having the surface enriched with molybdenum oxide tended to show high activity for the propane oxidation, surface molybdenum oxide clusters supported on metal molybdate matrix seem to be the active sites for the selective oxidative dehydrogenation of propane.     

Effective renaturation of reduced lysozyme by gentle removal of urea

To increase the folding yield of concentrated reduced lysozyme,we developed a renaturation method by means of dialysis fromconcentrated urea with redox agents. After lysozyme was incubatedin the reducing buffer (8 M urea solution) with oxidized glutathione,renaturation of reduced lysozyme was started by dialysis againstthe dialyzing buffer containing 8 M urea with redox agents.The urea concentration of the dialyzing bottle was graduallydiluted with dialyzing buffer without urea at a flow rate of0.1 ml/min by high pressure pump. Using this systematic dialysis,a concentration as high as 5 mg/ml of reduced lysozyme couldbe renaturated in 80% yield, while the folding yield was <5%even at a concentration of 1 mg/ml using a conventional rapiddilution method [Goldberg et al. (1991) Biochemistry, 30, 2790–2797].Therefore, it was concluded that gentle removal of urea fromdenatured proteins, dissolved in concentrated urea solution,by means of dialysis should be useful to renature denaturedproteins effectively.     

Evaluating card-based protocols in terms of execution time

International Journal of Information Security - Card-based cryptography is an attractive and unconventional computation model; it provides secure computing methods using a deck of physical cards....     

Combination of bottleneck feature extraction and dereverberation for distant-talking speech recognition

The performance of speech recognition in distant-talking environments is severely degraded by the reverberation that can occur in enclosed spaces (e.g., meeting rooms). To mitigate this degradation, dereverberation techniques such as network structure-based denoising autoencoders and multi-step linear prediction are used to improve the recognition accuracy of reverberant speech. Regardless of the reverberant conditions, a novel discriminative bottleneck feature extraction approach has been demonstrated to be effective for speech recognition under a range of conditions. As bottleneck feature extraction is not primarily designed for dereverberation, we are interested in whether it can compensate for other carefully designed dereverberation approaches. In this paper, we propose three schemes covering both front-end processing (cascaded combination and parallel combination) and back-end processing (system combination). Each of these schemes integrates bottleneck feature extraction with dereverberation. The effectiveness of these schemes is evaluated via a series of experiments using the REVERB challenge dataset.     

Clinical application of single-shot echo-planar diffusion-weighted imaging with compressed SENSE in prostate MRI at 3T: preliminary experience

Magnetic Resonance Materials in Physics, Biology and Medicine - Image quality (IQ) of diffusion-weighted imaging (DWI) with single-shot echo-planar imaging (ssEPI) suffers from low signal-to-noise...     

The effect of small dose of topiroxostat on serum uric acid in patients receiving hemodialysis

Introduction : Topiroxostat, a recently developed xanthine oxidase inhibitor, is expected to have fewer adverse effects than allopurinol because it has different mechanism of action from alloprinol. However, its dosage, usage and safety have not been established in patients with impaired renal function or those undergoing dialysis at the development since no studies was conducted in these patients. Methods : Cross over clinical trial using 3 months of allopurinol and topiroxostat on 27 maintain Japanese HD patients were carried out. The effects on oxidative stress status of both drugs were also evaluated by measuring oxidation reduction potential. Findings : Twenty‐five of twenty‐seven patients completed study. The mean serum uric acid levels in the topiroxostat‐treated arm was significantly lower than it in the allopurinol‐treated arm time‐dependently (P < 0.0001). Corrected oxidative stress ratio defined as biological antioxidant potential/diacron reactive oxygen metabolites was significantly increased in topiroxostat‐arm (*P = 0.0035), but not in allopurinol‐arm (P = 0.1429). No significant difference was seen in diacron reactive oxygen metabolites, biological antioxidant potential, static oxidation‐reduction potential, and capacity oxidation‐reduction potential between pre and post treatment of both drugs. Discussion : It is suggested that a low dose of topiroxostat decreased serum uric acid sufficiently to maintain it below 7.0 mg/dL in patients receiving hemodialysis.     

LMNtal as a hierarchical logic programming language

LMNtal (pronounced “elemental”) is a simple language model based on hierarchical graph rewriting that uses logical variables to represent connectivity and membranes to represent hierarchy. LMNtal is an outcome of the attempt to unify constraint-based concurrency and Constraint Handling Rules (CHR), the two notable extensions to concurrent logic programming. LMNtal is intended to be a substrate language of various computational models, especially those addressing concurrency, mobility and multiset rewriting. Although the principal objective of LMNtal was to provide a unifying computational model, it is of interest to equip the formalism with a precise logical interpretation. In this paper, we show that it is possible to give LMNtal a simple logical interpretation based on intuitionistic linear logic and a flattening technique. This enables us to call LMNtal a hierarchical, concurrent linear logic language.     

Optimal linear combination of neural networks for improvingclassification performance

This paper presents a new method for linearly combining multiple neural network classifiers based on the statistical pattern recognition theory. In our approach, several neural networks are first selected based on which works best for each class in terms of minimizing classification errors. Then, they are linearly combined to form an ideal classifier that exploits the strengths of the individual classifiers. In this approach, the minimum classification error criterion is utilized to estimate the optimal linear weights. In this formulation, because the classification decision rule is incorporated into the cost function, a more suitable better combination of weights for the classification objective could be obtained. Experimental results using artificial and real data sets show that the proposed method can construct a better combined classifier that outperforms the best single classifier in terms of overall classification errors for test data