Degradation of the Tensile Properties of an Au-Coated 316L Stainless Steel Bipolar Plate in a Fuel Cell Stack

Cost reduction for fuel cell stainless steel bipolar plate (BPP)’s Au-coating requires in depth understanding of its corrosion behavior. To this end, this paper explores the degradation of the tensile properties of an Au-coated 316L stainless steel bipolar plate in a real fuel cell stack. 4 BPPs were randomly chosen and removed from a stack that had run for 1600 h and, along with 2 pristine BPPs, were subsequently tested for surface morphology and tensile properties. Results suggest that (1) Pristine BPPs have initial pinhole flaws on the surface, whereas corroded BPPs have punctate (on O₂ side) and continual (on H₂ side) corrosions. (2) The tensile ultimate elongation for a BPP significantly decreases after corrosion on both O₂ and H₂ sides. (3) The degradation of tensile properties is attributed to primary cell effect.

     

In vitro potential of flavonoids from tartary buckwheat on antioxidants activity and starch digestibility

The effects of various flavonoids of Tartary buckwheat (rutin-enhanced flavonoid extract [REFE and quercetin-enhanced flavonoid extract [QEFE]) and individual flavonoids (rutin, quercetin and kaempferol) on the antioxidant activity, inhibition of α-glucosidases and α-amylase and starch digestibility were evaluated. Quercetin possessed the highest antioxidant activity and inhibition of α-glucosidases and α-amylase activity followed by kaempferol and rutin. REFE and QEFE have similar antioxidant and inhibition of α-amylase activities, but QEFE has much higher α-glucosidases inhibition than REFE. Tartary buckwheat flour has the lowest content of rapidly digestible starch and predicted glycaemic index (pGI) compared to maize flour, wheat flour and rice flour. Addition of rutin and quercetin to wheat flour showed a weak or no effect on digestion inhibition, but they inhibited starch digestion under solid complex conditions. Our results may help explain the benefits of supplementing the diet with food rich in flavonoids.     

Efficient key generation leveraging channel reciprocity and balanced gray code

Wireless Networks - Key generation leveraging wireless channel reciprocity can establish secret keys from unauthenticated broadcast channels and thus protect the communication of wireless networks....     

SDN‐based dynamic multipath forwarding for inter–data center networking

Equal‐cost multipath (ECMP)–based traffic engineering (TE) methods are commonly used in intra–data center (DC) networks to improve the transmission performance for east‐west traffic (ie, traffic from server to server within a DC). However, applying ECMP on inter‐DC wide area network (WAN) offers limited performance enhancement as a result of irregular network topology. Since TE can be intelligently and efficiently realized with software‐defined networking (SDN), SDN‐based multipath becomes a popular option. However, SDN suffers from scalability issue caused by limited ternary content‐addressable memory (TCAM) size. In this paper, we propose an SDN‐based TE method called dynamic flow‐entry‐saving multipath (DFSM) for inter‐DC traffic forwarding. DFSM adopts source‐destination–based multipath forwarding and latency‐aware traffic splitting to reduce the consumption of flow entries and achieve load balancing. The evaluation results indicate that DFSM saves 15% to 30% of system flow entries in practical topologies and reduces the standard deviation of path latencies from 10% to 7% than do label‐switched tunneling, and also reduces average latency by 10% to 48% by consuming 6% to 20% more flow entries than do ECMP in less‐interconnected topologies. Note that the performance gain may not always be proportional to flow entry investment, with the interconnectivity between nodes being an important factor. The evaluation also indicates that per‐flow provision consumes several times the flow entries consumed by DFSM but reduces latency by 10% at most. Besides, DFSM reduces the standard deviation of path latencies from 14% to 7% than do even traffic splitting.     

Low complexity carrier phase estimation for m-QAM optical communication systems

Photonic Network Communications - A low complexity carrier phase estimation (CPE) algorithm for M-ary quadrature amplitude modulation (m-QAM) optical communication systems is investigated in this...     

A holographic waveguide based eye tracking device

We demonstrated the feasibility of using a holographic waveguide imager for eye tracking. A holographic waveguide placed in front of the eye was used to capture images of the anterior segment of the eye and to guide the images to a camera distant from the eye. The pupil centre (PC) and corneal reflection (CR) of the eye was used to compute eye position. A custom-built model eye was used to validate the prototype eye tracker. A linear relationship between the angular eye position and the PC/CR vector was found over 60 horizontal degrees and 40 vertical degrees. The tracking accuracy and precision were 0.72 degree and 0.50 degree over these tracking ranges. These results confirmed that holographic waveguide could be a viable platform for developing compact, wearable, see-through eye trackers that can continuously monitor eye movements during real life tasks and thus can facilitate diagnosis of oculomotor disorders.     

Grey filter functions for suppression of grey-scale elements

To solve the problem of the presence of grey-scale material in optimization results and improve convergence efficiency during the optimization procedure caused by those intermediate densities, three kinds of simpler filter functions were proposed for the variable density method according to S-curve models. First, the feasible range for the parameters of the filter functions was determined by studying Messerschmitt–Bölkow–Blohm beam with the solid isotropic micro-structure with the penalization (SIMP) method. Then, the filter functions were applied to three classic examples to verify their validity and feasibility. The results showed that higher convergence efficiency, clearer structure boundaries, and better feasible solutions were obtained compared with that without the filter function. Finally, the filter functions were also compared with one existing method to demonstrate its effectiveness and validity.     

Distant Supervised Relation Extraction with Cost-Sensitive Loss

Recently, many researchers have concentrated on distant supervision relation extraction (DSRE). DSRE has solved the problem of the lack of data for supervised learning, however, the data automatically labeled by DSRE has a serious problem, which is class imbalance. The data from the majority class obviously dominates the dataset, in this case, most neural network classifiers will have a strong bias towards the majority class, so they cannot correctly classify the minority class. Studies have shown that the degree of separability between classes greatly determines the performance of imbalanced data. Therefore, in this paper we propose a novel model, which combines class-to-class separability and cost-sensitive learning to adjust the maximum reachable cost of misclassification, thus improving the performance of imbalanced data sets under distant supervision. Experiments have shown that our method is more effective for DSRE than baseline methods.