Search results for: Chen-Fu Wang
688 Effect of Chemical Concentration on the Rheology of Inks for Inkjet Printing
Authors: M. G. Tadesse, J. Yu, Y. Chen, L. Wang, V. Nierstrasz, C. Loghin
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Viscosity and surface tension are the fundamental rheological property of an ink for inkjet printing. In this work, we optimized the viscosity and surface tension of inkjet inks by varying the concentration of glycerol with water, PEDOT:PSS with glycerol and water, finally by adding the surfactant. The surface resistance of the sample was characterized by four-probe measurement principle. The change in volume of PEDOT:PSS in water, as well as the change in weight of glycerol in water has got a great influence on the viscosity on both temperature dependence and shear dependence behavior of the ink solution. The surface tension of the solution changed from 37 to 28 mN/m due to the addition of Triton. Varying the volume of PEDOT:PSS and the volume of glycerol in water has a great influence on the viscosity of the ink solution for inkjet printing. Viscosity drops from 12.5 to 9.5 mPa s with the addition of Triton at 25 oC. The PEDOT:PSS solution was found to be temperature dependence but not shear dependence as it is a Newtonian fluid. The sample was used to connect the light emitting diode (LED), and hence the electrical conductivity, with a surface resistance of 0.158 KΩ/square, was sufficient enough to give transfer current for LED lamp. The rheology of the inkjet ink is very critical for the successful droplet formation of the inkjet printing.Keywords: shear rate, surface tension, surfactant, viscosity
Procedia PDF Downloads 164687 Inhibitory Effects of PPARγ Ligand, KR-62980, on Collagen-Stimulated Platelet Activation
Authors: Su Bin Wang, Jin Hee Ahn, Tong-Shin Chang
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The peroxisome proliferator-activated receptors (PPARs) are member of nuclear receptor superfamily that act as a ligand-activated transcription factors. Although platelets lack a nucleus, previous studies have shown that PPARγ agonists, rosiglitazone, inhibited platelet activation induced by collagen. In this study, we investigated the inhibitory effects of KR-62980, a newly synthesized PPARγ agonist, on collagen receptor-stimulated platelet activation. The specific tyrosine phosphorylations of key components (Syk, Vav1, Btk and PLCγ2) for collagen receptor signaling pathways were suppressed by KR-62980. KR-62980 also attenuated downstream responses including cytosolic calcium elevation, P-selectin surface exposure, and integrin αIIbβ3 activation. PPARγ was found to associate with multiple proteins within the LAT signaling complex in collagen-stimulated platelets. This association was prevented by KR-62980, indicating a potential mechanism for PPARγ function in collagen-stimulated platelet activation. Furthermore, KR-62980 inhibited platelet aggregation and adhesion in response to collagen in vitro and prolonged in vivo thrombotic response in carotid arteries of mice. Collectively, these data suggest that KR-62980 inhibits collagen-stimulated platelet activation and thrombus formation through modulating the collagen receptor signaling pathways.Keywords: KR-62980, PPARγ, antiplatelet, thrombosis
Procedia PDF Downloads 328686 Hsa-miR-326 Functions as a Tumor Suppressor in Non-Small Cell Lung Cancer through Targeting CCND1
Authors: Cheng-Cao Sun, Shu-Jun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, De-Jia Li
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Hsa-miRNA-326 (miR-326) has recently been discovered having anticancer efficacy in different organs. However, the role of miR-326 on non-small cell lung cancer (NSCLC) is still ambiguous. In this study, we investigated the role of miR-326 on the development of NSCLC. The results indicated that miR-326 was significantly down-regulated in primary tumor tissues and very low levels were found in NSCLC cell lines. Ectopic expression of miR-326 in NSCLC cell lines significantly suppressed cell growth as evidenced by cell viability assay, colony formation assay and BrdU staining, through inhibition of cyclin D1, cyclin D2, CDK4, and up-regulation of p57(Kip2) and p21(Waf1/Cip1). In addition, miR-326 induced apoptosis, as indicated by concomitantly with up-regulation of key apoptosis protein cleaved caspase-3, and down-regulation of anti-apoptosis protein Bcl2. Moreover, miR-326 inhibited cellular migration and invasiveness through inhibition of matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene CCND1 was revealed to be a putative target of miR-326, which was inversely correlated with miR-326 expression in NSCLC. Taken together, our results demonstrated that miR-326 played a pivotal role on NSCLC through inhibiting cell proliferation, migration, invasion, and promoting apoptosis by targeting oncogenic CCND1.Keywords: hsa-miRNA-326 (miR-326), cyclin D1, non-small cell lung cancer (NSCLC), proliferation, apoptosis
Procedia PDF Downloads 296685 Evaluation of Collagen Synthesis in Macrophages/Fibroblasts Co-Culture Using Polylactic Acid Particles as Stimulants
Authors: Feng Ju Chuang, Yu Wen Wang, Tai Jung Hsieh, Shyh Ming Kuo
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Polylactic acid is a synthetic polymer with good biocompatibility and degradability, is widely used in clinical applications. In this study, we utilized Polylactic acid particles as stimulants for macrophages and the collagen synthesis of co-cultured fibroblasts was evaluated. The results indicated that Polylactic acid particles were nontoxic to cells from 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide. No obvious inflammation effect was observed (under the PLLA concentration of 1 mg/mL) after 24-h co-culture of Raw264.7 and NIH3T3 cells (from TNF-α assay). The addition of PLLA particles to the Raw264.7 and NIH3T3 co-cultures increased the synthesis of collagen, the highest collagen synthesis from the fibroblast was the 0.2 mg/mL (approximately 60% increased as compared with without addition Polylactic acid particles). Moreover, a co-axial atomization delivery device was used to percutaneously introduce Polylactic acid particles into the dermis layer and stimulating macrophages to secrete growth factors promoting fibroblasts to produce collagen. The preliminary results demonstrated the synthesis of collagen was increased mildly after the introduction of Polylactic acid particles for 28-d post implantation. The Polylactic acid particles could be successfully introduced into the dermis layer from H&E staining examination, however, the optimum concentration of Polylactic acid particles and the time-period for collagen synthesis still need to be evaluated.Keywords: collagen synthesis, macrophage, NIH3T3 cells, polylactic acid particles
Procedia PDF Downloads 99684 A Graph-Based Retrieval Model for Passage Search
Authors: Junjie Zhong, Kai Hong, Lei Wang
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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model
Procedia PDF Downloads 123683 Application of a Generalized Additive Model to Reveal the Relations between the Density of Zooplankton with Other Variables in the West Daya Bay, China
Authors: Weiwen Li, Hao Huang, Chengmao You, Jianji Liao, Lei Wang, Lina An
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Zooplankton are a central issue in the ecology which makes a great contribution to maintaining the balance of an ecosystem. It is critical in promoting the material cycle and energy flow within the ecosystems. A generalized additive model (GAM) was applied to analyze the relationships between the density (individuals per m³) of zooplankton and other variables in West Daya Bay. All data used in this analysis (the survey month, survey station (longitude and latitude), the depth of the water column, the superficial concentration of chlorophyll a, the benthonic concentration of chlorophyll a, the number of zooplankton species and the number of zooplankton species) were collected through monthly scientific surveys during January to December 2016. GLM model (generalized linear model) was used to choose the significant variables’ impact on the density of zooplankton, and the GAM was employed to analyze the relationship between the density of zooplankton and the significant variables. The results showed that the density of zooplankton increased with an increase of the benthonic concentration of chlorophyll a, but decreased with a decrease in the depth of the water column. Both high numbers of zooplankton species and the overall total number of zooplankton individuals led to a higher density of zooplankton.Keywords: density, generalized linear model, generalized additive model, the West Daya Bay, zooplankton
Procedia PDF Downloads 143682 Displaying of GnRH Peptides on Bacteriophage T7 and Its Immunogenicity in Mice Model
Authors: Hai Xu, Yiwei Wang, Xi Bao, Bihua Deng, Pengcheng Li, Yu Lu
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T7 phage could be used as a perfect vector for peptides expression and haptens presentation. T7-3GnRH recombinant phage was constructed by inserting three copies of Gonadotrophin Releasing Hormone (GnRH) gene into the multiple cloning site of T7 Select 415-1b phage genome. The positive T7-3GnRH phage was selected by using polymerase chain reaction amplification, and the p10B-3GnRH fusion protein was verified by SDS-PAGE and Western-blotting assay. T7-3GnRH vaccine was made and immunized with 1010 pfu in 0.2 ml per dose in mice. Blood samples were collected at an interval in weeks, and anti-GnRH antibody and testosterone concentrations were detected by ELISA and radioimmunoassay, respectively. The results show that T7-3GnRH phage particles confer a high immunogenicity to the GnRH-derived epitope. Moreover, the T7-3GnRH vaccine induced higher level of anti-GnRH antibody than ImproVac®. However, the testosterone concentrations in both immunized groups were at a similar level, and the testis developments were significantly inhibited compared to controls. These findings demonstrated that the anti-GnRH antibody could neutralize the endogenous GnRH to down regulate testosterone level and limit testis development, highlighting the potential value of T7-3GnRH in the immunocastration vaccine research.Keywords: Gonadotrophin Releasing Hormone (GnRH), Immunocastration, T7 phage, Phage vaccine
Procedia PDF Downloads 273681 Development of Rh/Ce-Zr-La/Al2O3 TWCs’ Wash Coat: Effect of Reactor on Catalytic and Thermal Stability
Authors: Su-Ning Wang, Yao-Qiang Chen
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The CeO2-ZrO2-La2O3-Al2O3 composite oxides are synthesized using co-precipitation method by two different reactors (i.e. continuous stirred-tank reactor and batch reactor), and the corresponding Rh-only three-way catalysts are obtained by wet-impregnation approach. The textural, structural, morphology and redox properties of the support materials, as well as the catalytic performance of the Rh-only catalyst are investigated systematically. The results reveal that the materials (CZLA-C) synthesized by continuous stirred-tank reactor have a better physic-chemical properties than the counterpart material (CZLA-B) prepared by batch reactor. After aging treatment at 1000 ℃ for 5 h, the BET surface area and pore volume of S1 reach up to 76 m2 g-1 and 0.36 mL/g, respectively, which is higher than that of S2. The XRD and Raman results demonstrate that a high structural stability is obtained by S1 because of the negligible lattice variation and the slight grain growth after aging treatment. The SEM and TEM images display that the morphology of S1 is assembled by many homogeneous primary nanoparticles (about 6.12 nm) that are connected to form mesoporous structure The TPR measurement shows that S1 possesses a higher reduction ability than S2. Compared with the catalyst supported on the CZLA-B, the as-prepared CZLA-C demonstrates an improved three-way catalytic activity both before and after aging treatment.Keywords: composite oxides, reactor, catalysis, catalytic performance
Procedia PDF Downloads 286680 Prevalence of Menopausal Women with Clinical Symptoms of Allergy and Evaluation the Effect of Sex Hormone Combined with Anti-Allergy Treatment
Authors: Yang Wei, Xueyan Wang, Hui Zou
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Objective: Investigation the prevalence of menopausal symptoms in patients with allergic symptoms, evaluation of the effect of sex hormones combined with anti-allergic therapy in these patients. Method: Age of 45-65 years old women with allergic symptoms at the same time in gynecological-endocrinology clinic in our hospital were selected from Feb 1 to May 31, 2010, randomly. The patients were given oral estradiol valerate plus progestin pills combined with anti-allergy treatment and then evaluated twice a week and one month later. Evaluation criterion: Menopause Rating Scale (MRS) and the degree of clinical symptoms were used to evaluate menopause and allergy separately. Results: 1) There were 195 cases of patients with menopausal symptoms at the age. Their MRS were all over 15. 2) Among them 45 patients were with allergic symptom accounted for 23% which were diagnosed by allergic department. 3) Evaluated after one week: the menopausal symptoms were improved and MRS were less than or equal to 5 in all these patients; the skin symptom of allergic symptoms vanished completely. 4) Evaluated after one month: Menopause symptoms were improved steadily; other clinical symptoms of allergy were also improved or without recurrence. Conclusion: The incidence rate of menopausal women with clinical symptoms of allergic diseases is high and it needs attention. The effect of sex hormones combined with anti-allergic therapy is obvious.Keywords: menopausal, allergy, sex hormone, anti-allergy treatment
Procedia PDF Downloads 265679 An Alternative Framework of Multi-Resolution Nested Weighted Essentially Non-Oscillatory Schemes for Solving Euler Equations with Adaptive Order
Authors: Zhenming Wang, Jun Zhu, Yuchen Yang, Ning Zhao
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In the present paper, an alternative framework is proposed to construct a class of finite difference multi-resolution nested weighted essentially non-oscillatory (WENO) schemes with an increasingly higher order of accuracy for solving inviscid Euler equations. These WENO schemes firstly obtain a set of reconstruction polynomials by a hierarchy of nested central spatial stencils, and then recursively achieve a higher order approximation through the lower-order precision WENO schemes. The linear weights of such WENO schemes can be set as any positive numbers with a requirement that their sum equals one and they will not pollute the optimal order of accuracy in smooth regions and could simultaneously suppress spurious oscillations near discontinuities. Numerical results obtained indicate that these alternative finite-difference multi-resolution nested WENO schemes with different accuracies are very robust with low dissipation and use as few reconstruction stencils as possible while maintaining the same efficiency, achieving the high-resolution property without any equivalent multi-resolution representation. Besides, its finite volume form is easier to implement in unstructured grids.Keywords: finite-difference, WENO schemes, high order, inviscid Euler equations, multi-resolution
Procedia PDF Downloads 134678 NaOH/Pumice and LiOH/Pumice as Heterogeneous Solid Base Catalysts for Biodiesel Production from Soybean Oil: An Optimization Study
Authors: Joy Marie Mora, Mark Daniel De Luna, Tsair-Wang Chung
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Transesterification reaction of soybean oil with methanol was carried out to produce fatty acid methyl esters (FAME) using calcined alkali metal (Na and Li) supported by pumice silica as the solid base catalyst. Pumice silica catalyst was activated by loading alkali metal ions to its surface via an ion-exchange method. Response surface methodology (RSM) in combination with Box-Behnken design (BBD) was used to optimize the operating parameters in biodiesel production, namely: reaction temperature, methanol to oil molar ratio, reaction time, and catalyst concentration. Using the optimized sets of parameters, FAME yields using sodium and lithium silicate catalysts were 98.80% and 98.77%, respectively. A pseudo-first order kinetic equation was applied to evaluate the kinetic parameters of the reaction. The prepared catalysts were characterized by several techniques such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET) sorptometer, and scanning electron microscopy (SEM). In addition, the reusability of the catalysts was successfully tested in two subsequent cycles.Keywords: alkali metal, biodiesel, Box-Behnken design, heterogeneous catalyst, kinetics, optimization, pumice, transesterification
Procedia PDF Downloads 290677 Frequency Analysis Using Multiple Parameter Probability Distributions for Rainfall to Determine Suitable Probability Distribution in Pakistan
Authors: Tasir Khan, Yejuan Wang
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The study of extreme rainfall events is very important for flood management in river basins and the design of water conservancy infrastructure. Evaluation of quantiles of annual maximum rainfall (AMRF) is required in different environmental fields, agriculture operations, renewable energy sources, climatology, and the design of different structures. Therefore, the annual maximum rainfall (AMRF) was performed at different stations in Pakistan. Multiple probability distributions, log normal (LN), generalized extreme value (GEV), Gumbel (max), and Pearson type3 (P3) were used to find out the most appropriate distributions in different stations. The L moments method was used to evaluate the distribution parameters. Anderson darling test, Kolmogorov- Smirnov test, and chi-square test showed that two distributions, namely GUM (max) and LN, were the best appropriate distributions. The quantile estimate of a multi-parameter PD offers extreme rainfall through a specific location and is therefore important for decision-makers and planners who design and construct different structures. This result provides an indication of these multi-parameter distribution consequences for the study of sites and peak flow prediction and the design of hydrological maps. Therefore, this discovery can support hydraulic structure and flood management.Keywords: RAMSE, multiple frequency analysis, annual maximum rainfall, L-moments
Procedia PDF Downloads 76676 Discovery of Two-dimensional Hexagonal MBene HfBO
Authors: Nanxi Miao, Junjie Wang
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The discovery of 2D materials with distinct compositions and properties has been a research aim since the report of graphene. One of the latest members of the 2D material family is MXene, which is produced from the topochemical deintercalation of the A layer from a laminate MAX phase. Recently, analogous 2D MBenes (transitional metal borides) have been predicted by theoretical calculations as excellent alternatives in applications such as metal-ion batteries, magnetic devices, and catalysts. However, the practical applications of two-dimensional (2D) transition-metal borides (MBenes) have been severely hindered by the lack of accessible MBenes because of the difficulties in the selective etching of traditional ternary MAB phases with orthorhombic symmetry (ort-MAB). Here, we discover a family of ternary hexagonal MAB (h-MAB) phases and 2D hexagonal MBenes (h-MBenes) by ab initio predictions and experiments. Calculations suggest that the ternary h-MAB phases are more suitable precursors for MBenes than the ort-MAB phases. Based on the prediction, we report the experimental synthesis of h-MBene HfBO by selective removal of in from h-MAB Hf2InB2. The synthesized 2D HfBO delivered a specific capacity of 420 mAh g-1 as an anode material in lithium-ion batteries, demonstrating the potential for energy-storage applications. The discovery of this h-MBene HfBO added a new member to the growing family of 2D materials and provided opportunities for a wide range of novel applications.Keywords: 2D materials, DFT calculations, high-throughput screening, lithium-ion batteries
Procedia PDF Downloads 55675 Mental Health Diagnosis through Machine Learning Approaches
Authors: Md Rafiqul Islam, Ashir Ahmed, Anwaar Ulhaq, Abu Raihan M. Kamal, Yuan Miao, Hua Wang
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Mental health of people is equally important as of their physical health. Mental health and well-being are influenced not only by individual attributes but also by the social circumstances in which people find themselves and the environment in which they live. Like physical health, there is a number of internal and external factors such as biological, social and occupational factors that could influence the mental health of people. People living in poverty, suffering from chronic health conditions, minority groups, and those who exposed to/or displaced by war or conflict are generally more likely to develop mental health conditions. However, to authors’ best knowledge, there is dearth of knowledge on the impact of workplace (especially the highly stressed IT/Tech workplace) on the mental health of its workers. This study attempts to examine the factors influencing the mental health of tech workers. A publicly available dataset containing more than 65,000 cells and 100 attributes is examined for this purpose. Number of machine learning techniques such as ‘Decision Tree’, ‘K nearest neighbor’ ‘Support Vector Machine’ and ‘Ensemble’, are then applied to the selected dataset to draw the findings. It is anticipated that the analysis reported in this study would contribute in presenting useful insights on the attributes contributing in the mental health of tech workers using relevant machine learning techniques.Keywords: mental disorder, diagnosis, occupational stress, IT workplace
Procedia PDF Downloads 279674 Surface Enhanced Raman Substrate Detection on the Structure of γ-Aminobutyric Acid(GABA) Connected with Modified Gold-Chitosan Nanoparticles by Mercaptopropionic Acid (MPA)
Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang
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A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). As for the gold-chitosan nanoshell, it is made by using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) for the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. When the system formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced Raman scattering
Procedia PDF Downloads 254673 Synthesis of Rare-Earth Pyrazolate Compounds
Authors: Nazli Eslamirad, Peter C. Junk, Jun Wang, Glen B. Deacon
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Since coordination behavior of pyrazoles and pyrazolate ions are widely versatile towards a great range of metals such as d-block, f-block as well as main group elements; they attract interest as ligands for preparing compounds. A variety of rare-earth pyrazolate complexes have been synthesized by redox transmetalation/protolysis (RTP) previously, therefore, a variety of rare-earth pyrazolate complexes using two pyrazoles, 3,5-dimethylpyrazole (Me₂pzH) and 3,5-di-tert -butylpyrazolate (t-Bu₂pzH), in which the structures span the whole La-Lu array beside Sc and Y has been synthesized by RTP reaction. There have been further developments in this study: Synthesizing structure of [Tb(Me₂pz)₃(thf)]₂ which is isomorphous with those of the previously reported [Dy(Me₂pz)₃(thf)]₂ and [Lu(Me₂pz)₃(thf)]₂ analogous that has two µ-1(N):2(Nʹ)-Me2pz ligands (the most common pyrazolate ligation for non-rare-earth complexes). Previously most of the reported compounds using t-Bu2pzH were monomeric compounds however the lanthanum derivative [La(Me₂pz)₃thf₂] ,which has been reported previously without crystal structure, has now been structurally characterized, along with cerium and lutetium analogue. Also a polymeric structure with samarium has now been synthesized which the neodymium analogue has been reported previously and comparing these polymeric structures can support the idea that the geometry of Sm(tBu₂pz)₃ affect the coordination of the solvent. Also, by using 1,2-dimethoxyethane (DME) instead of tetrahydrofuran (THF) new [Er(tBu₂pz)₃ (dme)₂] has now been reported.Keywords: lanthanoid complexes, pyrazolate, redox transmetalation/protolysis, x-ray crystal structures
Procedia PDF Downloads 205672 Investigation of the Effects of Biodiesel Blend on Particulate-Phase Exhaust Emissions from a Light Duty Diesel Vehicle
Authors: B. Wang, W. H. Or, S.C. Lee, Y.C. Leung, B. Organ
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This study presents an investigation of diesel vehicle particulate-phase emissions with neat ultralow sulphur diesel (B0, ULSD) and 5% waste cooking oil-based biodiesel blend (B5) in Hong Kong. A Euro VI light duty diesel vehicle was tested under transient (New European Driving Cycle (NEDC)), steady-state and idling on a chassis dynamometer. Chemical analyses including organic carbon (OC), elemental carbon (EC), as well as 30 polycyclic aromatic hydrocarbons (PAHs) and 10 oxygenated PAHs (oxy-PAHs) were conducted. The OC fuel-based emission factors (EFs) for B0 ranged from 2.86 ± 0.33 to 7.19 ± 1.51 mg/kg, and those for B5 ranged from 4.31 ± 0.64 to 15.36 ± 3.77 mg/kg, respectively. The EFs of EC were low for both fuel blends (0.25 mg/kg or below). With B5, the EFs of total PAHs were decreased as compared to B0. Specifically, B5 reduced total PAH emissions by 50.2%, 30.7%, and 15.2% over NEDC, steady-state and idling, respectively. It was found that when B5 was used, PAHs and oxy-PAHs with lower molecular weight (2 to 3 rings) were reduced whereas PAHs/oxy-PAHs with medium or high molecular weight (4 to 7 rings) were increased. Our study suggests the necessity of taking atmospheric and health factors into account for biodiesel application as an alternative motor fuel.Keywords: biodiesel, OC/EC, PAHs, vehicular emission
Procedia PDF Downloads 160671 LncRNA NEAT1 Promotes NSCLC Progression through Acting as a ceRNA of miR-377-3p
Authors: Chengcao Sun, Shujun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, Dejia Li
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Recently, the long non-coding RNA (lncRNA) NEAT1 has been identified as an oncogenic gene in multiple cancer types and elevated expression of NEAT1 was tightly linked to tumorigenesis and cancer progression. However, the molecular basis for this observation has not been characterized in progression of non-small cell lung cancer (NSCLC). In our studies, we identified NEAT1 was highly expressed in NSCLC patients and was a novel regulator of NSCLC progression. Patients whose tumors had high NEAT1 expression had a shorter overall survival than patients whose tumors had low NEAT1 expression. Further, NEAT1 significantly accelerates NSCLC cell growth and metastasis in vitro and tumor growth in vivo. Additionally, by using bioinformatics study and RNA pull down combined with luciferase reporter assays, we demonstrated that NEAT1 functioned as a competing endogenous RNA (ceRNA) for has-miR-377-3p, antagonized its functions and led to the de-repression of its endogenous targets E2F3, which was a core oncogene in promoting NSCLC progression. Taken together, these observations imply that the NEAT1 modulated the expression of E2F3 gene by acting as a competing endogenous RNA, which may build up the missing link between the regulatory miRNA network and NSCLC progression.Keywords: long non-coding RNA NEAT1, hsa-miRNA-377-3p, E2F3, non-small cell lung cancer, tumorigenesis
Procedia PDF Downloads 366670 Effect of Fluidized Granular Activated Carbon for the Mitigation of Membrane Fouling in Wastewater Treatment
Authors: Jingwei Wang, Anthony G. Fane, Jia Wei Chew
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The use of fluidized Granular Activated Carbon (GAC) as a means of mitigation membrane fouling in membrane bioreactors (MBRs) has received much attention in recent years, especially in anaerobic fluidized bed membrane bioreactors (AFMBRs). It has been affirmed that the unsteady-state tangential shear conferred by GAC fluidization on membrane surface suppressed the extent of membrane fouling with energy consumption much lower than that of bubbling (i.e., air sparging). In a previous work, the hydrodynamics of the fluidized GAC particles were correlated with membrane fouling mitigation effectiveness. Results verified that the momentum transfer from particle to membrane held a key in fouling mitigation. The goal of the current work is to understand the effect of fluidized GAC on membrane critical flux. Membrane critical flux values were measured by a vertical Direct Observation Through the Membrane (DOTM) setup. The polystyrene particles (known as latex particles) with the particle size of 5 µm were used as model foulant thus to give the number of the foulant on the membrane surface. Our results shed light on the positive effect of fluidized GAC enhancing the critical membrane flux by an order-of-magnitude as compared to that of liquid shear alone. Membrane fouling mitigation was benefitted by the increasing of power input.Keywords: membrane fouling mitigation, liquid-solid fluidization, critical flux, energy input
Procedia PDF Downloads 397669 Optimization of Double-Layered Microchannel Heat Sinks
Authors: Tu-Chieh Hung, Wei-Mon Yan, Xiao-Dong Wang, Yu-Xian Huang
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This work employs a combined optimization procedure including a simplified conjugate-gradient method and a three-dimensional fluid flow and heat transfer model to study the optimal geometric parameter design of double-layered microchannel heat sinks. The overall thermal resistance RT is the objective function to be minimized with number of channels, N, the channel width ratio, β, the bottom channel aspect ratio, αb, and upper channel aspect ratio, αu, as the search variables. It is shown that, for the given bottom area (10 mm×10 mm) and heat flux (100 W cm-2), the optimal (minimum) thermal resistance of double-layered microchannel heat sinks is about RT=0.12 ℃/m2W with the corresponding optimal geometric parameters N=73, β=0.50, αb=3.52, and, αu= 7.21 under a constant pumping power of 0.05 W. The optimization process produces a maximum reduction by 52.8% in the overall thermal resistance compared with an initial guess (N=112, β=0.37, αb=10.32 and, αu=10.93). The results also show that the optimal thermal resistance decreases rapidly with the pumping power and tends to be a saturated value afterward. The corresponding optimal values of parameters N, αb, and αu increase while that of β decrease as the pumping power increases. However, further increasing pumping power is not always cost-effective for the application of heat sink designs.Keywords: optimization, double-layered microchannel heat sink, simplified conjugate-gradient method, thermal resistance
Procedia PDF Downloads 485668 Regulation of SHP-2 Activity by Small Molecules for the Treatment of T Cell-Mediated Diseases
Authors: Qiang Xu, Xingxin Wu, Wenjie Guo, Xingqi Wang, Yang Sun, Renxiang Tan
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The phosphatase SHP-2 is known to exert regulatory activities on cytokine receptor signaling and the dysregulation of SHP-2 has been implicated in the pathogenesis of a variety of diseases. Here we report several small molecule regulators of SHP-2 for the treatment of T cell-mediated diseases. The new cyclodepsipeptide trichomides A, isolated from the fermentation products of Trichothecium roseum, increased the phosphorylation of SHP-2 in activated T cells, and ameliorated contact dermatitis in mice. The trichomides A’s effects were significantly reversed by using the SHP-2-specific inhibitor PHPS1 or T cell-conditional SHP-2 knockout mice. Another compound is a cerebroside Fusaruside isolated from the endophytic fungus Fusarium sp. IFB-121. Fusaruside also triggered the tyrosine phosphorylation of SHP-2, which provided a possible mean of selectively targeting STAT1 for the treatment of Th1 cell-mediated inflammation and led to the discovery of the non-phosphatase-like function of SHP-2. Namely, the Fusaruside-activated pY-SHP-2 selectively sequestrated the cytosolic STAT1 to prevent its recruitment to IFN-R, which contributed to the improvement of experimental colitis in mice. Blocking the pY-SHP-2-STAT1 interaction, with SHP-2 inhibitor NSC-87877 or using T cells from conditional SHP-2 knockout mice, reversed the effects of fusaruside. Furthermore, the fusaruside’s effect is independent of the phosphatase activity of SHP-2, demonstrating a novel role for SHP-2 in regulating STAT1 signaling and Th1-type immune responses.Keywords: SHP-2, small molecules, T cell, T cell-mediated diseases
Procedia PDF Downloads 302667 Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment
Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang
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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks
Procedia PDF Downloads 198666 Predicting Relative Performance of Sector Exchange Traded Funds Using Machine Learning
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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.Keywords: machine learning, ETF prediction, dynamic trading, asset allocation
Procedia PDF Downloads 82665 Comparison of Breast Surface Doses for Full-Field Digital Mammography and Digital Breast Tomosynthesis Using Breast Phantoms
Authors: Chia-Hui Chen, Chien-Kuo Wang
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Background: Full field digital mammography (FFDM) is widely used in diagnosis of breast cancer. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Hence, the radiation dose delivered to the patients involved in an imaging protocol is of utmost concern. Aim: To compare the surface radiation dose (ESD) of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) by using breast phantoms. Method: We analyzed the average entrance surface dose (ESD) of FFDM and DBT by using breast phantoms. Optically Stimulated luminescent Dosimeters (OSLD) were placed in a tissue-equivalent Breast phantom at difference sites of interest. Absorbed dose measurements were obtained after digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) exposures. Results: An automatic exposure control (AEC) is proposed for surface dose measurement during DBT and FFDM. The mean ESD values for DBT and FFDM were 6.37 mGy and 3.51mGy, respectively. Using of OSLD measured for surface dose during DBT and FFDM. There were 19.87 mGy and 11.36 mGy, respectively. The surface exposure dose of DBT could possibly be increased by two times with FFDM. Conclusion: The radiation dose from DBT was higher than that of FFDM and the difference in dose between AEC and OSLD measurements at phantom surface.Keywords: full-field digital mammography, digital breast tomosynthesis, optically stimulated luminescent dosimeters, surface dose
Procedia PDF Downloads 410664 On-Chip Sensor Ellipse Distribution Method and Equivalent Mapping Technique for Real-Time Hardware Trojan Detection and Location
Authors: Longfei Wang, Selçuk Köse
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Hardware Trojan becomes great concern as integrated circuit (IC) technology advances and not all manufacturing steps of an IC are accomplished within one company. Real-time hardware Trojan detection is proven to be a feasible way to detect randomly activated Trojans that cannot be detected at testing stage. On-chip sensors serve as a great candidate to implement real-time hardware Trojan detection, however, the optimization of on-chip sensors has not been thoroughly investigated and the location of Trojan has not been carefully explored. On-chip sensor ellipse distribution method and equivalent mapping technique are proposed based on the characteristics of on-chip power delivery network in this paper to address the optimization and distribution of on-chip sensors for real-time hardware Trojan detection as well as to estimate the location and current consumption of hardware Trojan. Simulation results verify that hardware Trojan activation can be effectively detected and the location of a hardware Trojan can be efficiently estimated with less than 5% error for a realistic power grid using our proposed methods. The proposed techniques therefore lay a solid foundation for isolation and even deactivation of hardware Trojans through accurate location of Trojans.Keywords: hardware trojan, on-chip sensor, power distribution network, power/ground noise
Procedia PDF Downloads 381663 The Mitigation Strategy Analysis of Kuosheng Nuclear Power Plant Spent Fuel Pool Using MELCOR2.1/SNAP
Authors: Y. Chiang, J. R. Wang, J. H. Yang, Y. S. Tseng, C. Shih, S. W. Chen
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Kuosheng nuclear power plant (NPP) is a BWR/6 plant in Taiwan. There is more concern for the safety of Spent Fuel Pools (SFPs) in Taiwan after Fukushima event. In order to estimate the safety of Kuosheng NPP SFP, by using MELCOR2.1 and SNAP, the safety analysis of Kuosheng NPP SFP was performed combined with the mitigation strategy of NEI 06-12 report. There were several steps in this research. First, the Kuosheng NPP SFP models were established by MELCOR2.1/SNAP. Second, the Station Blackout (SBO) analysis of Kuosheng SFP was done by TRACE and MELCOR under the cooling system failure condition. The results showed that the calculations of MELCOR and TRACE were very similar in this case. Second, the mitigation strategy analysis was done with the MELCOR model by following the NEI 06-12 report. The results showed the effectiveness of NEI 06-12 strategy in Kuosheng NPP SFP. Finally, a sensitivity study of SFP quenching was done to check the differences of different water injection time and the phenomena during the quenching. The results showed that if the cladding temperature was over 1600 K, the water injection may have chance to cause the accident more severe with more hydrogen generation. It was because of the oxidation heat and the “Breakaway” effect of the zirconium-water reaction. An animation model built by SNAP was also shown in this study.Keywords: MELCOR, SNAP, spent fuel pool, quenching
Procedia PDF Downloads 350662 Effects of Excess-Iron Stress on Symbiotic Nitrogen Fixation Efficiency of Yardlong-Bean Plants
Authors: Hong Li, Tingxian Li, Xudong Wang, Qinghuo Lin
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Excess-iron (Fe) stresses involved in legume symbiotic nitrogen fixation are not understood. Our objectives were to investigate the tolerance of yardlong-bean plants to soil excess-Fe stress and antagonistic effects of organic amendments and rhizobial inoculants on plant root nodulation and stem ureide formation. The study was conducted in the tropical Hainan Island during 2012-2013. The soil was strongly acidic (pH 5.3±0.4) and highly variable in Fe concentrations(596±79 mg/kg). The treatments were arranged in a split-plot design with three blocks. The treatment effects were significant on root nodulation, stem ureide, amino acids, plant N/Fe accumulation and bean yields (P<0.05). The yardlong-bean stem allantoin, amino acids and nitrate concentrations and relative ureide % declined with high soil Fe concentrations (>300 mg/kg). It was concluded that the co-variance of excess Fe stress could inhibit legume symbiotic N fixation efficiency. Organic amendments and rhizobial inoculants could help improve crop tolerance to excess Fe stress.Keywords: atmospheric N fixation, root nodulation, soil Fe co-variance, stem ureide, yardlong-bean plants
Procedia PDF Downloads 272661 Mapping QTLs Associated with Salinity Tolerance in Maize at Seedling Stage
Authors: Mohammad Muhebbullah Ibne Hoque, Zheng Jun, Wang Guoying
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Salinity stress is one of the most important abiotic factors contributing to crop growth and yield loss. Exploring the genetic basis is necessary to develop maize varieties with salinity tolerance. In order to discover the inherent basis for salinity tolerance traits in maize, 121 polymorphic SSR markers were used to analyze 163 F2 individuals derived from a single cross of inbred line B73 (a salt susceptible inbred line) and CZ-7 (a salt tolerant inbred line). A linkage map was constructed and the map covered 1195.2 cM of maize genome with an average distance of 9.88 cM between marker loci. Ten salt tolerance traits at seedling stage were evaluated for QTL analysis in maize seedlings. A total of 41 QTLs associated with seedling shoot and root traits were detected, with 16 and 25 QTLs under non-salinity and salinity condition, respectively. And only 4 major stable QTLs were detected in two environments. The detected QTLs were distributed on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, and chromosome 10. Phenotypic variability for the identified QTLs for all the traits was in the range from 6.27 to 21.97%. Fourteen QTLs with more than 10% contributions were observed. Our results and the markers associated with the major QTL detected in this study have the potential application for genetic improvement of salt tolerance in maize through marker-assisted selection.Keywords: salt tolerance, seedling stage, root shoot traits, quantitative trait loci, simple sequence repeat, maize
Procedia PDF Downloads 304660 Metabolomics Profile Recognition for Cancer Diagnostics
Authors: Valentina L. Kouznetsova, Jonathan W. Wang, Igor F. Tsigelny
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Metabolomics has become a rising field of research for various diseases, particularly cancer. Increases or decreases in metabolite concentrations in the human body are indicative of various cancers. Further elucidation of metabolic pathways and their significance in cancer research may greatly spur medicinal discovery. We analyzed the metabolomics profiles of lung cancer. Thirty-three metabolites were selected as significant. These metabolites are involved in 37 metabolic pathways delivered by MetaboAnalyst software. The top pathways are glyoxylate and dicarboxylate pathway (its hubs are formic acid and glyoxylic acid) along with Citrate cycle pathway followed by Taurine and hypotaurine pathway (the hubs in the latter are taurine and sulfoacetaldehyde) and Glycine, serine, and threonine pathway (the hubs are glycine and L-serine). We studied interactions of the metabolites with the proteins involved in cancer-related signaling networks, and developed an approach to metabolomics biomarker use in cancer diagnostics. Our analysis showed that a significant part of lung-cancer-related metabolites interacts with main cancer-related signaling pathways present in this network: PI3K–mTOR–AKT pathway, RAS–RAF–ERK1/2 pathway, and NFKB pathway. These results can be employed for use of metabolomics profiles in elucidation of the related cancer proteins signaling networks.Keywords: cancer, metabolites, metabolic pathway, signaling pathway
Procedia PDF Downloads 390659 Relevance Feedback within CBIR Systems
Authors: Mawloud Mosbah, Bachir Boucheham
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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN
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