Evaluating the impacts of the clean cities program

The Department of Energy's Clean Cities program was created in 1993 to reduce petroleum usage in the transportation sector. The program promotes alternative fuels such as biofuels and fuel-saving strategies such as idle reduction and fleet management through coalitions of local government, non-profit, and private actors. Few studies have evaluated the impact of the program because of its complexity that include interrelated strategies of grants, education and training and diversity of participants. This paper uses a Difference-in-Differences (DiD) approach to evaluate the effectiveness of the program between 1990 and 2010. We quantify the effectiveness of the Clean Cities program by focusing on performance measures such as air quality, number of alternative fueling stations, private vehicle occupancy and transit ridership. We find that counties that participate in the program perform better on all these measures compared to counties that did not participate. Compared to the control group, counties in the Clean Cities program experienced a reduction in days with bad air quality (3.7%), a decrease in automobile commuters (2.9%), an overall increase in transit commuters (2.1%) and had greater numbers of new alternative fueling stations (12.9). The results suggest that the program is a qualified success

Improved heat transfer for pyroelectric energy harvesting applications using a thermal conductive network of aluminum nitride in PMN–PMS–PZT ceramics

The harvesting of waste heat is attracting increasing attention, due to its abundance and potential benefits to the environment. However, the need for high heat transfer rates in thermal harvesting systems is a longstanding obstacle for their practical application. In this work, we construct thermally conductive networks in Pb[(MnxNb1−x)1/2(MnxSb1−x)1/2]y(Zr95Ti5)1−yO3 (lead magnesium niobate–lead antimony–manganese–lead zirconate titanate: PMN–PMS–PZT) ceramics to improve heat transfer and enhance their ferroelectric properties by use of a thermally conductive AlN additive dispersed in the ceramic matrix. The ferroelectric properties, pyroelectric coefficient and thermal conductivity of the PMN–PMS–PZT: AlN composite materials are influenced by the AlN content as a result of the formation of random bridges or thermally conductive networks for phonon transfer in the ceramic matrix, thereby leading to high heat transfer. For a PMN–PMS–PZT composite with a 0.2 wt% AlN content, the ferroelectric properties, pyroelectric coefficient and thermal conductivity are shown to be enhanced owing to the improved crystallinity and density, and the relative permittivity is also reduced, which results in optimized pyroelectric figure of merits. This combination of materials property enhancements is shown to be beneficial for high performance pyroelectric materials in devices for energy harvesting applications

Cylindrical Three-Dimensional Millimeter-Wave Imaging via Compressive Sensing

Millimeter-wave (MMW) imaging techniques have been used for the detection of concealed weapons and contraband carried by personnel. However, the future application of the new technology may be limited by its large number of antennas. In order to reduce the complexity of the hardware, a novel MMW imaging method based on compressive sensing (CS) is proposed in this paper. The MMW images can be reconstructed from the significantly undersampled backscattered data via the CS approach. Thus the number of antennas and the cost of system can be further reduced than those based on the traditional imaging methods that obey the Nyquist sampling theorem. The effectiveness of the proposed method is validated by numerical simulations as well as by real measured data of objects

Improved heat transfer for pyroelectric energy harvesting applications using a thermal conductive network of aluminum nitride in PMN–PMS–PZT ceramics

The harvesting of waste heat is attracting increasing attention, due to its abundance and potential benefits to the environment.</p

Effect of Zr/Ti ratio on microstructure and electrical properties of pyroelectric ceramics for energy harvesting applications

In this paper, Pb[(MnxNb1-x)1/2(MnxSb1-x)1/2]y(ZrzTi1-z)1-yO3 (lead magnesium niobate-lead antimony-manganese-lead zirconate titanate: PMnN-PMS-PZT) ceramics with three different Zi/Ti compositions of 95/5 (Zr95), 85/15 (Zr85) and (Zr85 + Zr95) were successfully fabricated and characterized. The effect of Zr/Ti ratio on the microstructure and electric properties were studied in detail. The pyroelectric coefficient of Zr95 ceramic was 5957 μC/m2K which was more than 2–3 times higher than other reported pyroelectric ceramics. The effect on pyroelectric energy harvesting was systemically investigated via a variation of Zr/Ti compositions in the ceramics, which was directly evaluated by the output power acquired from the data acquisition system. The output power was 25.7 μW, 4.8 μW and 14.2 μW at a composition ratio of Zr95, Zr85 and Zr85 + Zr95, respectively under identical conditions. Among the three Zi/Ti compositions, the best pyroelectric and ferroelectric properties were achieved with Zr95, which indicated that the pyroelectric energy harvesting can be efficiently optimized by the appropriate control of phase structure.</p

Characterizing microRNA editing and mutation sites in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder whose pathogenesis is still unclear. MicroRNAs (miRNAs) are a kind of endogenous small non-coding RNAs that play important roles in the post-transcriptional regulation of genes. Recent researches show that miRNAs are edited in multiple ways especially in central nervous systems. A-to-I editing of RNA catalyzed by Adenosine deaminases acting on RNA (ADARs) happens intensively in brain and is also noticed in other organs and tissues. Although miRNAs are widely edited in human brain, miRNA editing in ASD is still largely unexplored. In order to reveal the editing events of miRNAs in ASD, we analyzed 131 miRNA-seq samples from 8 different brain regions of ASD patients and normal controls. We identified 834 editing sites with significant editing levels, of which 70 sites showed significantly different editing levels in the superior frontal gyrus samples of ASD patients (ASD-SFG) when compared with those of control samples. The editing level of an A-to-I editing site in hsa-mir-376a-1 (hsa-mir-376a-1_9_A_g) in ASD-SFG is higher than that of normal controls, and the difference is exaggerated in individuals under 10 years. The increased expression of ADAR1 is consistent with the increased editing level of hsa-mir-376a-1_9_A_g in ASD-SFG samples compared to normal SFG samples. Furthermore, we verify that A-to-I edited hsa-mir-376a-5p directly represses GPR85 and NAPB, which may contribute to the abnormal neuronal development of ASD patients. These results provide new insights into the mechanism of ASD

A de novo Genome of a Chinese Radish Cultivar

AbstractHere, we report a high-quality draft genome of a Chinese radish (Raphanus sativus) cultivar. This draft contains 387.73Mb of assembled scaffolds, 83.93% of the scaffolds were anchored onto nine pseudochromosomes and 95.09% of 43 240 protein-coding genes were functionally annotated. 184.75Mb (47.65%) of repeat sequences was identified in the assembled genome. By comparative analyses of the radish genome against 10 other plant genomes, 2 275 genes in 780 gene families were found unique to R. sativus. This genome is a good reference for genomic study and of great value for genetic improvement of radish

Research on Picking Identification and Positioning System Based on IOT

The key and necessary condition for accurate picking are to identify and locate the target fruit accurately. This paper focuses on the development of picking robot, mainly through two aspects: software and hardware. Moreover, it mainly consists of the binocular vision system and the camera calibration model. Based on these two core components, it can complete the function of identification and positioning. The results show that it can accurately locate the target location in the aspect of recognition function. What is more, its error is no more than 8mm, and its picking rate is over 96%. It shows high precision and efficiency, which plays a decisive role in the realization of picking automation.</p

Research on Picking Identification and Positioning System Based on IOT

The key and necessary condition for accurate picking are to identify and locate the target fruit accurately. This paper focuses on the development of picking robot, mainly through two aspects: software and hardware. Moreover, it mainly consists of the binocular vision system and the camera calibration model. Based on these two core components, it can complete the function of identification and positioning. The results show that it can accurately locate the target location in the aspect of recognition function. What is more, its error is no more than 8mm, and its picking rate is over 96%. It shows high precision and efficiency, which plays a decisive role in the realization of picking automation