Boron Removal of Wastewater via Coagulation Sedimentation with Ettringite: an Experimental and Mechanism Study

Yuyu Liu,Toshihiko Takaya,Azuma Ohuchi 대한환경공학회 2015 대한환경공학회 학술발표논문집 Vol.2015 No.10

Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework

Zhou, Yuyu,Clarke, Leon,Eom, Jiyong,Kyle, Page,Patel, Pralit,Kim, Son H.,Dirks, James,Jensen, Erik,Liu, Ying,Rice, Jennie,Schmidt, Laurel,Seiple, Timothy Elsevier 2014 APPLIED ENERGY Vol.113 No.-

<P><B>Abstract</B></P> <P><B>Objective</B></P> <P>Because long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate change impact on buildings energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning.</P> <P><B>Methods</B></P> <P>In this study, we present a detailed buildings energy model with U.S. state-level representation, nested in an integrated assessment framework of the Global Change Assessment Model (GCAM). We project state-level buildings energy demand and its spatial pattern through the end of the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data.</P> <P><B>Results</B></P> <P>The results indicate that climate change has a large impact on heating and cooling buildings energy and fuel use at the state level and that the 48 U.S. contiguous states exhibit a large spatial heterogeneity (ranges from −10% to+10% for total, −10% to+20% for electricity use and −20% to −5% for oil and gas use in the A2 scenario). Sensitivity analysis explores the potential implications of multiple driving forces, including climate action that would both change the price of energy and reduce climate change, the choice of climate models, and population and GDP growth. In addition, the 50-state building model is compared to a comparable version of the model which represents the entire United States as one region.</P> <P><B>Conclusions</B></P> <P>The study clearly demonstrates the spatially varying nature of fuel consumption changes that might occur from a changing climate. Although the study illustrates the importance of incorporating climate change into infrastructure-planning exercises, it also demonstrates that uncertainties about underlying drivers still must weigh heavily on these planning decisions. Finally, the study demonstrates that the 50-state building model provides both insights at the regional level and potentially better national-level estimates.</P> <P><B>Practice implication</B></P> <P>The findings from this study will help the climate-based policy decision and energy system, especially utility planning related to the buildings sector at the U.S. state and regional level facing the potential climate change.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Climate change has spatially heterogeneous impact on heating and cooling energy and fuel uses in building sector. </LI> <LI> Building energy and fuel uses are sensitive to other factors such as climate policy as well as climate change. </LI> <LI> The 50-state building model provides both insights at the regional level and potentially better national-level estimates. </LI> <LI> Climate change impact on building electricity use is critical, and needs to be incorporated in infrastructure planning. </LI> </UL> </P>

Synthesis and adsorption properties of H4Ti5O12@CNT ion sieves

Gao Yuyu,Chen Jin,Chu Suihong,Yang Bo,Zheng Lu,Liu Min 대한화학회 2023 Bulletin of the Korean Chemical Society Vol.44 No.11

In this study, H4Ti5O12@CNT ion sieves with an encapsulated structure were fabricated by combining pretreated carbon nanotubes (CNTs) as a template and carbon source, C16H36O4Ti as a titanium source, and CH3COOLi as a lithium source. By characterizing and analyzing the pretreated and untreated CNTs, numerous COOH and OH functional groups were introduced into the pretreated CNTs, which improved their dispersion in aqueous solutions and ethanol and facilitated the adsorption of lithium ions. The ion sieves prepared with the precursor roasted at 700 °C showed the best adsorption performance. Moreover, the structural integrity of the ion sieves was not affected by acid washing. For the first adsorption cycle, the ion sieves had a lithium-ion saturated adsorption capacity of 32.32 mg/g. After five adsorption–desorption cycles, the adsorption capacity only decreased by 5.1% to 30.68 mg/g, which shows that they had good cycling stability.

A Study of Active Contour Segmentation Models based on Automatic Initial Contour

Caibo,Zhigui Liu,Junbo Wang,Yuyu Zhu 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.4

Image segmentation is a fundamental and challenging problem in image processing and often a vital step for high level analysis. Due to the active contour model (ACM) need to choose the initial contour for the following evolution, it limited the utilities of this kind of segmentation to a large extent. For the purpose of avoiding the processing of human choosing initial contour, in this paper, we proposed an automatic initial contour choosing algorithm of the input image information. Based on the chosen initial contour, the iterative efficient and the accuracy of segmentation have been improved when the initial contour is incorporated into the local based segmentation framework. Extensive experiments on synthetic and real images are provided to evaluate our method, showing significant improvements on the segmentation accuracy and stability, comparing to the human chosen initial contour, such as LBF and LGIF.

Expression profiles of microRNAs in skeletal muscle of sheep by deep sequencing

Zhi-Jin Liu,Cun-Yuan Li,Xiao-Yue Li,Yang Yao,Wei Ni,Xiang-Yu Zhang,Yang Cao,Wureli Hazi,Dawei Wang,Renzhe Quan,Shuting Yu,Yuyu Wu,Songmin Niu,Yulong Cui,Yaseen Khan,Shengwei Hu 아세아·태평양축산학회 2019 Animal Bioscience Vol.32 No.6

Objective: MicroRNAs are a class of endogenous small regulatory RNAs that regulate cell proliferation, differentiation and apoptosis. Recent studies on miRNAs are mainly focused on mice, human and pig. However, the studies on miRNAs in skeletal muscle of sheep are not comprehensive. Methods: RNA-seq technology was used to perform genomic analysis of miRNAs in prenatal and postnatal skeletal muscle of sheep. Targeted genes were predicted using miRanda software and miRNA-mRNA interactions were verified by quantitative real-time polymerase chain reaction. To further investigate the function of miRNAs, candidate targeted genes were enriched for analysis using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment. Results: The results showed total of 1,086 known miRNAs and 40 new candidate miRNAs were detected in prenatal and postnatal skeletal muscle of sheep. In addition, 345 miRNAs (151 up-regulated, 94 down-regulated) were differentially expressed. Moreover, miRanda software was performed to predict targeted genes of miRNAs, resulting in a total of 2,833 predicted targets, especially miR-381 which targeted multiple muscle-related mRNAs. Furthermore, GO and KEGG pathway analysis confirmed that targeted genes of miRNAs were involved in development of skeletal muscles. Conclusion: This study supplements the miRNA database of sheep, which provides valuable information for further study of the biological function of miRNAs in sheep skeletal muscle.

A New Stable and Accurate Algorithm of Large Image Mosaic

Bo Cai,Zhigui Liu,Junbo Wang,Yuyu Zhu 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.6

Due to the overlapped region and image size of the input image pair is unpredictable, it makes the matching procedure more difficult and unstable. For the purpose of finding out the stable and accurate matching algorithm of large images, we give an analysis of different kinds of characters, such as, scale invariant feature transform (SIFT), local maximum gradient descriptor, Harris corners, and the maximum curvature points of the image edges, etc. Based on the experiments of different images, a new stable matching algorithm is proposed in this paper. In our model, the matching procedure is divided into two stages, the rough and accurate matching procedures. To evaluate the matching result, the edge information is combined with the local maximum gradient of the input images as the constraint of our matching algorithm. After the extraction of the local maximum gradient character points, we use the edge information to divide these points into different classes. Then, the searching of the stable and accurate matching problem becomes to find out the best matching results which agree to the edge constraints. The experimental results show that the proposed algorithm is more efficient and stable than the other kinds of matching algorithms especially in the proposing of large size images.

A New Stable and Accurate Algorithm of Concrete Crack Image Mosaic

Bo Cai,Zhigui Liu,Junbo Wang,Yuyu Zhu 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.8

Due to the concrete crack images are self-similarity in the contents, it makes the matching procedure more difficult and unstable than the others. For the purpose of finding out the stable and accurate matching algorithm of concrete crack images, we give an analysis of different kinds of characters, such as, scale invariant feature transform (SIFT), local maximum gradient descriptor, Harris corners, and the maximum curvature points of the image edges, etc. Based on the experiments of different concrete crack images, a new stable matching algorithm is proposed in this paper. In our model, the edge information is combined with the local maximum gradient of the input matching images. After the extraction of the local maximum gradient character points, we use the edge information to divide these points into different classes. Then, the searching of the stable and accurate matching problem becomes to find out the best matching results which agree to the edge constraints. The experimental results show that the proposed algorithm is more consistence and stable than the other kinds of matching algorithms especially in the proposing of sequential concrete crack images.

A New Inspection Method for Bridge Deformation

Bo Cai,Zhigui Liu,Junbo Wang,Yuyu Zhu 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.7

The deformation of the location of structural systems is an important step to predict the performance of the system under different conditions. In bridges, the plastic deformations generally occur over a long-span beam after years of service. To improve the detection accuracy and stability of bridge deformation, in this paper, we proposed a new deformation inspecting framework. The total procedure of our algorithm may be concluded as the following three aspects. Firstly, because of the beams of bridges are very long, to improve the resolution of images, we divided the acquiring of the bridge beam image into a sequential images. Secondly, the sequential images are proposed with character point extraction, image stitching, image segmentation, and the calculation of the bridge deformation. Finally, the calculated deformation was compared with the experimental results. According to the experiments on the real bridges and the simulating model, the results indicated that our algorithm may improve the detection accurate to a large extent. At the same time, the proposed algorithm is more flexible than the former proposed algorithms.

Graphene/Carbon Nanotubes Hybrid Electrode Materials for High Performance Supercapacitor

Yongzhen Wang,Yong Wang,Yuyu Liu,Azuma Ohuchi,Xiaomin Wang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2015 NANO Vol.10 No.5

A graphene (GN)/carbon nanotubes (CNTs) nanocomposite electrode material were prepared via reduction of exfoliated graphite oxides in the presence of CNTs pretreated by mixed acid. The GN/CNTs nanocomposite characterized by X-ray diffraction (XRD), Raman spectrum (Raman) and scanning electron microscope (SEM) has a layered structure with CNTs uniformly sandwiched between the GN sheets, which efficiently decreased the agglomeration GN sheets. Electrochemical data demonstrate that the GN/CNT exhibited higher specific capacitance than that of graphene.

Image Segmentation Framework Using Gradient Guided Active Contours

Bo Cai,Zhigui Liu,Junbo Wang,Yuyu Zhu 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.7

Image segmentation is a fundamental and challenging problem in image processing and often a vital step for high level analysis. Considering of the inefficient curve evolution against weak boundary and intensity heterogeneous images, an improved level set segmentation framework guided by the image gradient function is proposed. In this framework, the edges and regions of the image are roughly divided by using the image gradient sample function. Compare to the Local Binary Fitting (LBF) model, local and global intensity fitting (LGIF) model, and Edge-flow based active contour model, this algorithm may improve efficient of curve evolution in a large extent. After that, we compare this algorithm with the other active contour model to show that segmenting the noisy blurry boundary and intensity heterogeneous images can be achieved, and still go on an in-depth comparison of these models. Finally, we show the results on challenging images to illustrate the accurate segmentations.