Preparation of continually graded barriers of YPrBaCuO for HTS Josephson junctions

We report preparation of a novel barrier structure for high Tc superconducting multilayer Josephson junctions using a simple composite target technique. Such a barrier consists of Yx Pr1-xBa2Cu3Oy with a continually varied concentration of yttrium. In this barrier no lattice mismatch and other incompatibility problems occur between adjacent layers. Thus the formation of interfacial defects and structural strain can be mostly prevented. The Josephson coupling takes place at the electrically formed interfaces rather than the structural interfaces. A particular feature of these junctions is that the effective thickness of the barrier strongly depends on the measuring temperature and the concentration gradient. The absence of the structural interface in the weak link region greatly enhances the reproducibility and the performance of these junctions.published_or_final_versio

Fatty-acid uptake in prostate cancer cells using dynamic microfluidic raman technology

It is known that intake of dietary fatty acid (FA) is strongly correlated with prostate cancer progression but is highly dependent on the type of FAs. High levels of palmitic acid (PA) or arachidonic acid (AA) can stimulate the progression of cancer. In this study, a unique experimental set-up consisting of a Raman microscope, coupled with a commercial shear-flow microfluidic system is used to monitor fatty acid uptake by prostate cancer (PC-3) cells in real-time at the single cell level. Uptake of deuterated PA, deuterated AA, and the omega-3 fatty acids docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) were monitored using this new system, while complementary flow cytometry experiments using Nile red staining, were also conducted for the validation of the cellular lipid uptake. Using this novel experimental system, we show that DHA and EPA have inhibitory effects on the uptake of PA and AA by PC-3 cells

Characterization of soluble microbial products as precursors of disinfection byproducts in drinking water supply

Water pollution by wastewater discharge can cause the problem of disinfection byproducts (DBPs) in drinking water supply. In this study, DBP formation characteristics of soluble microbial products (SMPs) as the main products of wastewater organic biodegradation were investigated. The results show that SMPs can act as DBP precursors in simulated wastewater biodegradation process. Under the experimental conditions, stabilized SMPs had DBPFP (DBP formation potential) yield of around 5.6 mumol mmol(-1)-DOC (dissolved organic carbon) and DBP speciation profile different from that of the conventional precursor, natural organic matter (NOM). SMPs contained polysaccharides, proteins, and humic-like substances, and the latter two groups can act as reactive DBP precursors. SMP fraction with molecular weight of <1 kDa accounted for 85% of the organic carbon and 65% of the DBP formation. As small SMP molecules are more difficult to remove by conventional water treatment processes, more efforts are needed to control wastewater-derived DBP problem in water resource management.postprin

High-Tc ramp-type Josephson junctions with a continually graded Y1–xPrxBa2Cu3Oy barrier

High-Tc Josephson junctions with a graded barrier have been prepared by using a composite target. Such a barrier is synthesized by utilizing Y1–xPrxBa2Cu3Oy with a continually graded concentration of Pr, in which no lattice mismatch and other incompatible problems take place. The structural interfaces are absent in the weak link region and Josephson coupling occurs at the naturally formed superconducting/normal interfaces within the Y1–xPrxBa2Cu3Oy layer. Thus, it can significantly enhance the reproducibilty and performance of these junctions. The temperature dependences of the barrier thickness and Josephson were also studied. © 2001 American Institute of Physics.published_or_final_versio

Fuel consumption and emissions performance under real driving: Comparison between hybrid and conventional vehicles

© 2018 Elsevier B.V. Hybrid electric vehicles (HEVs) are perceived to be more energy efficient and less polluting than conventional internal combustion engine (ICE) vehicles. However, increasing evidence has shown that real-driving emissions (RDE) could be much higher than laboratory type approval limits and the advantages of HEVs over their conventional ICE counterparts under real-driving conditions have not been studied extensively. Therefore, this study was conducted to evaluate the real-driving fuel consumption and pollutant emissions performance of HEVs against their conventional ICE counterparts. Two pairs of hybrid and conventional gasoline vehicles of the same model were tested simultaneously in a novel convoy mode using two portable emission measurement systems (PEMSs), thus eliminating the effect of vehicle configurations, driving behaviour, road conditions and ambient environment on the performance comparison. The results showed that although real-driving fuel consumption for both hybrid and conventional vehicles were 44%–100% and 30%–82% higher than their laboratory results respectively, HEVs saved 23%–49% fuel relative to their conventional ICE counterparts. Pollutant emissions of all the tested vehicles were lower than the regulation limits. However, HEVs showed no reduction in HC emissions and consistently higher CO emissions compared to the conventional ICE vehicles. This could be caused by the frequent stops and restarts of the HEV engines, as well as the lowered exhaust gas temperature and reduced effectiveness of the oxidation catalyst. The findings therefore show that while achieving the fuel reduction target, hybridisation did not bring the expected benefits to urban air quality

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

A review of physical supply and EROI of fossil fuels in China

This paper reviews China’s future fossil fuel supply from the perspectives of physical output and net energy output. Comprehensive analyses of physical output of fossil fuels suggest that China’s total oil production will likely reach its peak, at about 230 Mt/year (or 9.6 EJ/year), in 2018; its total gas production will peak at around 350 Bcm/year (or 13.6 EJ/year) in 2040, while coal production will peak at about 4400 Mt/year (or 91.9 EJ/year) around 2020 or so. In terms of the forecast production of these fuels, there are significant differences among current studies. These differences can be mainly explained by different ultimately recoverable resources assumptions, the nature of the models used, and differences in the historical production data. Due to the future constraints on fossil fuels production, a large gap is projected to grow between domestic supply and demand, which will need to be met by increasing imports. Net energy analyses show that both coal and oil and gas production show a steady declining trend of EROI (energy return on investment) due to the depletion of shallow-buried coal resources and conventional oil and gas resources, which is generally consistent with the approaching peaks of physical production of fossil fuels. The peaks of fossil fuels production, coupled with the decline in EROI ratios, are likely to challenge the sustainable development of Chinese society unless new abundant energy resources with high EROI values can be found

Developing Novel Fabrication and Optimisation Strategies on Aggregation-Induced Emission Nanoprobe/Polyvinyl Alcohol Hydrogels for Bio-Applications.

The current study describes a new technology, effective for readily preparing a fluorescent (FL) nanoprobe-based on hyperbranched polymer (HB) and aggregation-induced emission (AIE) fluorogen with high brightness to ultimately develop FL hydrogels. We prepared the AIE nanoprobe using a microfluidic platform to mix hyperbranched polymers (HB, generations 2, 3, and 4) with AIE (TPE-2BA) under shear stress and different rotation speeds (0-5 K RPM) and explored the FL properties of the AIE nanoprobe. Our results reveal that the use of HB generation 4 exhibits 30-times higher FL intensity compared to the AIE alone and is significantly brighter and more stable compared to those that are prepared using HB generations 3 and 2. In contrast to traditional methods, which are expensive and time-consuming and involve polymerization and post-functionalization to develop FL hyperbranched molecules, our proposed method offers a one-step method to prepare an AIE-HB nanoprobe with excellent FL characteristics. We employed the nanoprobe to fabricate fluorescent injectable bioadhesive gel and a hydrogel microchip based on polyvinyl alcohol (PVA). The addition of borax (50 mM) to the PVA + AIE nanoprobe results in the development of an injectable bioadhesive fluorescent gel with the ability to control AIEgen release for 300 min. When borax concentration increases two times (100 mM), the adhesion stress is more than two times bigger (7.1 mN/mm2) compared to that of gel alone (3.4 mN/mm2). Excellent dimensional stability and cell viability of the fluorescent microchip, along with its enhanced mechanical properties, proposes its potential applications in mechanobiology and understanding the impact of microstructure in cell studies