Meso-scale Finite Element (FE) modelling of biaxial carbon fibre non-crimp-fabric (NCF) based composites under uniaxial tension and in-plane shear

Non-crimp-fabrics (NCF) are promising materials in aerospace applications. The complex internal structure of NCF composites could influence the in-plane performances, which needs to be comprehensively studied. The novel three-dimensional (3D) meso-scale repeated unit cell (RUC) models were proposed for biaxial NCF composites based on the Finite Element (FE) method to conduct a systematic parameter study, including layup sequence, out-of-plane tow waviness, resin-rich areas, transverse tow placements and delamination. The meso RUC model could effectively predict the homogenised uniaxial tensile and in-plane shear properties of biaxial NCF composites based on their meso-scale constituent and material properties. A multiscale framework was also developed for biaxial NCF composites. A micromechanical representative volume element (RVE) model provided homogenised mechanical properties for tows, and a macroscopical FE model validated the test results using the homogenised results obtained from meso RUC models. The numerical results were in good agreement with the experiment results. Therefore, the multiscale framework provides an insight into the critical parameters influencing the in-plane properties of NCF composites and an analysis tool for NCF material design

Prosthesis replacement in Mason III radial head fractures: A meta-analysis

AbstractIntroductionThis present study was to evaluate the clinical efficacy of prosthesis replacement (PR) for patients with Mason III radial head fractures (RHF) compared with open reduction and internal fixation (ORIF).MethodsWe retrieved the relevant trials up to September 2013 from several public databases, mainly including PubMed, Embase, Springer, Elsevier Science Direct, Cochrane Library, Google scholar, CNKI and Wanfang database. Weighted mean difference (WMD) or odds ratio (OR) and their 95% confidence intervals (CI) were calculated to compare the clinical outcomes between PR and ORIF.ResultsA total of 9 studies including 365 patients with Mason III RHF (169 patients treated with PR and 196 patients treated with ORIF) were reanalyzed in the meta-analysis. The results showed that the patients with Mason III RHF receiving PR, compared with the ORIF ones, had a significantly higher percentage of postoperative excellent and good rate (OR=3.48, 95% CI=1.98 to 6.11, P<0.0001), better Broberg and Morrey elbow scores (WMD=9.79, 95% CI=4.22 to 15.36, P=0.0006) and significantly lower postoperative complications (OR=0.33, 95% CI=0.16 to 0.69, P=0.003).ConclusionsAlthough the results of this study supported the use of PR in the treatment of Mason III RHF in Chinese population with short-term outcomes, the evidences are of low quality and further studies were required for confirming these results in the longer term on other populations.Level of evidenceLevel III. Low power meta-analysis

Willingness to Pay for Better Air Quality: The case of China

Air pollution is a big threat to human beings and has attract worldwide attention from governments and scholars. Based on the survey of happiness in China, this paper attempts to analyze the impact of local air quality on the happiness of individuals, and to evaluate the monetary value of mitigating air pollution. Through merging individual happiness data in a nationally representative survey with daily air quality index (AQI) according to the date and location of each respondent, it calculates the marginal rate of substitution (MRS) between air quality and income, and then estimates respondents’ willingness to pay (WTP) for better air quality. Moreover, it has further explored the differences of WTPs among groups. This study reaches the conclusion that happiness is positively associated with income but negatively correlated with air pollution. Besides, individual happiness is heavily influenced by income, age, gender, health condition, marital status and other variables. Furthermore, WTPs differ greatly among groups and the estimated average WTP of whole sample is 549.36RMB(or 0.90% of annual household income) per year per family for one unit reduction in AQI

Ethanol Production from Kitchen Garbage Using Zymomonas mobilis: Optimization of Parameters through Statistical Experimental Designs

Plackett-Burman design was employed to screen 8 parameters for ethanol production from kitchen garbage by Zymomonas mobilis in simultaneous saccharification and fermentation. The parameters were divided into two parts, four kinds of enzymes and supplementation nutrients. The result indicated that the nutrient inside kitchen garbage could meet the requirement of ethanol production without supplementation, only protease and glucoamylase were needed to accelerate the ethanol production. The optimum usages for both enzymes were determined to be A = 100 U g-1 by single factor experiment. Then the parameters including initial pH, time and temperature were optimized during the fermentation by using central composite experimental design (CCD). The results of second-order polynomial model indicated that interactions between the factors showed no crucial effect on ethanol production. The optimum conditions were determined to be initial pH of 4.95, time of t = 30.69 h, temperature of θ = 31.22 ºC, the corresponding maximum ethanol was γ = 53.20 g L-1. Ethanol production from kitchen garbage enjoyed the advantages of simple process, low cost and short fermentation time, which should be further studied to make it applicable

Ethanol Production from Kitchen Garbage Using Zymomonas mobilis: Optimization of Parameters through Statistical Experimental Designs

Plackett-Burman design was employed to screen 8 parameters for ethanol production from kitchen garbage by Zymomonas mobilis in simultaneous saccharification and fermentation. The parameters were divided into two parts, four kinds of enzymes and supplementation nutrients. The result indicated that the nutrient inside kitchen garbage could meet the requirement of ethanol production without supplementation, only protease and glucoamylase were needed to accelerate the ethanol production. The optimum usages for both enzymes were determined to be A = 100 U g-1 by single factor experiment. Then the parameters including initial pH, time and temperature were optimized during the fermentation by using central composite experimental design (CCD). The results of second-order polynomial model indicated that interactions between the factors showed no crucial effect on ethanol production. The optimum conditions were determined to be initial pH of 4.95, time of t = 30.69 h, temperature of θ = 31.22 ºC, the corresponding maximum ethanol was γ = 53.20 g L-1. Ethanol production from kitchen garbage enjoyed the advantages of simple process, low cost and short fermentation time, which should be further studied to make it applicable

Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings

© 1989-2012 IEEE. Learning appropriate metric is critical for effectively capturing complex data characteristics. The metric learning of categorical data with hierarchical coupling relationships and local heterogeneous distributions is very challenging yet rarely explored. This paper proposes a Heterogeneous mEtric Learning with hIerarchical Couplings (HELIC for short) for this type of categorical data. HELIC captures both low-level value-to-attribute and high-level attribute-to-class hierarchical couplings, and reveals the intrinsic heterogeneities embedded in each level of couplings. Theoretical analyses of the effectiveness and generalization error bound verify that HELIC effectively represents the above complexities. Extensive experiments on 30 data sets with diverse characteristics demonstrate that HELIC-enabled classification significantly enhances the accuracy (up to 40.93 percent), compared with five state-of-the-art baselines

Incentivizing High Quality Crowdwork

We study the causal effects of financial incentives on the quality of crowdwork. We focus on performance-based payments (PBPs), bonus payments awarded to workers for producing high quality work. We design and run randomized behavioral experiments on the popular crowdsourcing platform Amazon Mechanical Turk with the goal of understanding when, where, and why PBPs help, identifying properties of the payment, payment structure, and the task itself that make them most effective. We provide examples of tasks for which PBPs do improve quality. For such tasks, the effectiveness of PBPs is not too sensitive to the threshold for quality required to receive the bonus, while the magnitude of the bonus must be large enough to make the reward salient. We also present examples of tasks for which PBPs do not improve quality. Our results suggest that for PBPs to improve quality, the task must be effort-responsive: the task must allow workers to produce higher quality work by exerting more effort. We also give a simple method to determine if a task is effort-responsive a priori. Furthermore, our experiments suggest that all payments on Mechanical Turk are, to some degree, implicitly performance-based in that workers believe their work may be rejected if their performance is sufficiently poor. Finally, we propose a new model of worker behavior that extends the standard principal-agent model from economics to include a worker's subjective beliefs about his likelihood of being paid, and show that the predictions of this model are in line with our experimental findings. This model may be useful as a foundation for theoretical studies of incentives in crowdsourcing markets.Comment: This is a preprint of an Article accepted for publication in WWW \c{opyright} 2015 International World Wide Web Conference Committe