Learning to Adaptively Scale Recurrent Neural Networks

Recent advancements in recurrent neural network (RNN) research have demonstrated the superiority of utilizing multiscale structures in learning temporal representations of time series. Currently, most of multiscale RNNs use fixed scales, which do not comply with the nature of dynamical temporal patterns among sequences. In this paper, we propose Adaptively Scaled Recurrent Neural Networks (ASRNN), a simple but efficient way to handle this problem. Instead of using predefined scales, ASRNNs are able to learn and adjust scales based on different temporal contexts, making them more flexible in modeling multiscale patterns. Compared with other multiscale RNNs, ASRNNs are bestowed upon dynamical scaling capabilities with much simpler structures, and are easy to be integrated with various RNN cells. The experiments on multiple sequence modeling tasks indicate ASRNNs can efficiently adapt scales based on different sequence contexts and yield better performances than baselines without dynamical scaling abilities

Multi-objective Black Widow Algorithm Guided by Competitive Mechanism and Pheromone Mechanism

Black widow optimization algorithm (BWOA) is a swarm intelligence optimization algorithm, which has the advantages of fast convergence and high precision. However, the update strategy adopted by BWOA is too simple, and it is easy to fall into the local optimal solution. Moreover, the search ability in multi-dimensional space is lacking, the population structure is single, and the convergence and diversity of the algorithm need to be improved.  In order to improve the comprehensive performance of BWOA and make it applicable to multi-objective optimization problems, this paper proposes a multi-objective black widow optimization algorithm (MBWOA) guided by a competition mechanism and an improved pheromone mechanism. MBWOA adopts the method of dynamic allocation of populations, which divides the populations into two in the iterative process and uses different competition mechanisms to enhance the diversity of the populations in the iterative process and improve the convergence of the algorithm. At the same time, it uses the improved pheromone mechanism to guide offspring individuals that have gone through the competition mechanism to optimize in the direction of population gap, improve the distribution of population, and enhance the convergence ability of the algorithm. Using MBWOA and four comparison algorithms to conduct comparative experiments on three indicators of IGD, HV and Spread respectively, the results show that MBWOA has better convergence accuracy, convergence speed and diversity. Finally, the effectiveness of the used mechanism is confirmed by the experiments of MBWOA and the comparison algorithms on three indicators

Bioactivity-based HPLC tandem Q/TOF for alpha-glucosidase inhibitors : Screening, identification, and quantification from actinomycetes

This study was performed to screen α-glucosidase inhibitors from the actinomycete metabolites library by high throughput screening. Twelve strains of actinomycete were considered to be α-glucosidase inhibitors producing strains; then effective inhibitory strain PW409 was fermented and separated by bioactivity based HPLC, two fractions showing remarkable inhibitory activities; the two compounds were identified as 1-deoxynojirimycin (DNJ) and miglitol by mass spectrometry, comparing with authentic standards, and relevant literature. The quantification analysis of DNJ and miglitol by HPLC-MS/MS showed that the average concentrations of DNJ and miglitol in broth of strain PW409 were 11.2 and 95.8 mg/L, respectively. This is the first report about Streptomyces sp. products α-glucosidase inhibitor miglitol. The strain PW409 has potential application in biosynthesis and biotransformation of antidiabetes drug miglitol. The method can be utilized for new α-glucosidase inhibitors discovering and development from other inhibitory activity strains.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Flow-through anastomosis using a T-shaped vascular pedicle for gracilis functioning free muscle transplantation in brachial plexus injury

OBJECTIVE: In gracilis functioning free muscle transplantation, the limited caliber of the dominant vascular pedicle increases the complexity of the anastomosis and the risk of vascular compromise. The purpose of this study was to characterize the results of using a T-shaped vascular pedicle for flow-through anastomosis in gracilis functioning free muscle transplantation for brachial plexus injury. METHODS: The outcomes of patients with brachial plexus injury who received gracilis functioning free muscle transplantation with either conventional end-to-end anastomosis or flow-through anastomosis from 2005 to 2013 were retrospectively compared. In the flow-through group, the pedicle comprised a segment of the profunda femoris and the nutrient artery of the gracilis. The recipient artery was interposed by the T-shaped pedicle. RESULTS: A total of 46 patients received flow-through anastomosis, and 25 patients received conventional end-to-end anastomosis. The surgical time was similar between the groups. The diameter of the arterial anastomosis in the flow-through group was significantly larger than that in the end-to-end group (3.87 mm vs. 2.06 mm, respectively,