249 research outputs found
Exploring the geography of China's airport networks: a hybrid complex-network approach
Air networks are normal examples of transportation systems among ubiquitous big data networks in the dynamic nature. This is particularly the case in developing countries with rapid airport network expansions. This paper explores the structure and evolution of the trunk airport network of China (ANC) in major years during 1980s-2000s. We generalise the complex network approach developed in existing studies and further test for statistical properties of weighted network characteristics by using pair-wise traffic flows. The spatiotemporal decomposition of network metric plots and the visualization maps leads to a rich harvest of stylized ANC structures: (i) national hub-and-spoke patterns surrounding mega-cities; (ii) regional broker patterns surrounding Kunming and Urumqi, and (iii) local heterogeneous disparity patterns in isolated geographical cities, such as Lhasa, Lijiang, Huangshan, etc. These findings have important implications towards understanding the geo-political and economic forces at stake in shaping China's urban systems
Hydrogen and nitrogen plasma treated materials with disordered surface layer used for energy storage and conversion devices
Plasma treatment is considered as an easy and effective method for the modification of materialsâ surface of electrodes for electrochemical energy storage and conversion devices to improve the performances. As a result, a disordered surface layer and atom vacancies could be formed after the high-power plasma treatment, which play significant roles on enhancing the performances of energy storage and conversion materials. In this work, hydrogen and nitrogen plasma are used to modify anode materials for lithium and sodium ion batteries (LIBs and SIBs), and electrochemical catalysts for the nitrogen reduction reaction (NRR), and the electrochemical application performances of these materials are tested. Firstly, WS2 nanoparticles are modified through hydrogen plasma treatment at 300 °C for 2 hours, and the hydrogenated WS2 (H-WS2) nanoparticles demonstrate a clearly enhanced electrochemical performance as anode material for both LIBs and SIBs. The TEM investigation shows a disordered surface layer with thickness around 2.5 nm after the treatment, and this is also confirmed by the results of the Raman spectroscopy. The shift in the XPS peaks indicates the structure surface disorders are incorporated in the crystalline structure. The H-WS2 based LIBs and SIBs possess significantly higher specific capacity at different current densities. In addition, the electrochemical impedance spectroscopy (EIS) reveals a drastic decrease of the charge-transfer resistance for both LIB and SIB, which implies the plasma hydrogenated electrode is more favorable for the electron transportation during the electrochemical process. The improved rate performance of H-WS2 in both applications of LIBs and SIBs can be attributed to the largely reduced charge transfer resistivity at the disordered surface layer. Secondly, nitrogen doped TiO2 (N-TiO2) nanoparticles are prepared via nitrogen plasma treatment and investigated as anode material of SIBs. The N-TiO2 nanoparticles demonstrate a much better rate performance, yielding discharge capacities of about 621 mAh·g-1 at 0.1 C and 75 mAh·g-1 at 5 C, as well as a clearly enhanced capacity retention (more than 98% after more than 400 cycles) than the pristine TiO2. Different from the other nitrogen doped TiO2 reported in the literatures, a disordered surface layer with thickness of around 2.5 nm is formed in the N-TiO2 nanoparticles after the N2 plasma treatment. Both the doped nitrogen and the disordered surface layer play significant roles on enhancing the sodium storage performance. Thirdly, we chose the TiO2-Au (P-TiO2-Au, gold nanoclusters supported by P25 TiO2 nanoparticles, Au loading: ~ 2 wt %) as the electrochemical catalysts for the NRR. The material was modified with H2 plasma and then formed a blue-black H-TiO2-Au catalyst, it shown enhanced performance for the nitrogen reduction reaction (NRR) process comparing with the pristine sample. From the TEM investigations we could find some disordered positions on the surface, and also the Raman intensities of H-TiO2-Au is much lower than the pristine material which could be attributed to the disordered surface and the oxygen vacancies formation. Whatâs more, a small peak shift for the XPS could be found after the hydrogen plasma treatment. When the sample was used for the electrochemical NRR, the yield of NH3 of blue-black H-TiO2-Au is around 9.5 times higher than the pristine sample, while the highest faradaic efficiency of 2.7 % is also obtain at the potential of -0.1V. The density functional theory (DFT) calculation results confirm that H-TiO2-Au with oxygen vacancies and disordered surface layer is much preferred for the NRR process. It further proves that the reduction process of H2 plasma treatment makes an important role on the improving of catalystsâ performances. It could be the first time that used the plasma technique to modify catalyst for electrochemical NRR processes.Die Plasmabehandlung gilt als eine einfache und effektive Methode zur Modifikation der MaterialoberflĂ€che von Elektroden fĂŒr elektrochemische Energiespeicher- und Umwandlungs-vorrichtungen, um die Leistungen zu verbessern. Infolgedessen konnten nach der Hochleistungsplasmabehandlung ungeordnete OberflĂ€chenschichten und Atomleerstellen entstehen, die eine wichtige Rolle bei der Leistungssteigerung von Energiespeicher- und Umwandlungsmaterialien spielen. In dieser Arbeit werden Wasserstoff- und Stickstoffplasma verwendet, um Lithium- und Natriumionenbatterien (LIBs und SIBs) Anodenmaterialien und elektrochemische Katalysatoren fĂŒr die Stickstoffreduktionsreaktion (NRR) zu modifizieren, und die elektrochemischen Anwendungsleistungen dieser Materialien zu untersuchen. Erstens, werden WS2-Nanopartikel durch Wasserstoff-Plasma-Behandlung bei 300 °C fĂŒr 2 Stunden modifiziert, und die hydrierten WS2 (H-WS2)-Nanopartikel zeigen eine deutlich verbesserte elektrochemische Leistung als Anodenmaterial fĂŒr Lithium-Ionen-Batterien (LIBs) und Natrium-Ionen-Batterien (SIBs). Die TEM-Untersuchung zeigt eine ungeordnete OberflĂ€chenschicht mit einer Dicke von etwa 2,5 nm nach der Behandlung, was auch durch die Ergebnisse der Raman Spektroskopie bestĂ€tigt wird. Die Verschiebung der XPS-Peaks deutet an, dass die OberflĂ€chenstörungen der Struktur in die kristalline Struktur integriert sind. Die H-WS2-basierten LIBs und SIBs weisen eine deutlich höhere spezifische KapazitĂ€t bei unterschiedlichen Stromdichten auf. DarĂŒber hinaus zeigt die Untersuchung der elektrochemische Impedanzspektroskopie (EIS) eine drastische Verringerung des LadungsĂŒbertragungswiderstands sowohl fĂŒr LIB als auch fĂŒr SIB. Das bedeutet, dass die plasmahydrierte Elektrode fĂŒr den Elektronentransport wĂ€hrend des elektrochemischen Prozesses vorteilhafter ist. Die verbesserte Leistung von H-WS2 in beiden Anwendungen von Li und Na Ionenbatterien ist auf den reduzierten LadungsĂŒbertragungswiderstand an der ungeordneten OberflĂ€chenschicht und die verbesserte elektronische LeitfĂ€higkeit durch die StörungsoberflĂ€che in der kristallinen Struktur zurĂŒckzufĂŒhren. Zweitens, werden stickstoffdotierte TiO2 (N-TiO2)-Nanopartikel durch Stickstoffplasma-Behandlung hergestellt und als Anodenmaterial von Natriumionenbatterien (SIBs) untersucht. Die N-TiO2-Nanopartikel weisen eine wesentlich bessere Ratenleistung auf und liefern EntladekapazitĂ€ten von etwa 621 mAh-g-1 bei 0,1 C und 75 mAh-g-1 bei 5 C sowie eine deutlich verbesserte KapazitĂ€tserhaltung (mehr als 98% nach mehr als 400 Zyklen) als das unbehandelte TiO2. Im Gegensatz zu den anderen stickstoffdotierten TiO2, von denen in der Literatur berichtet werden, bildet sich in den N-TiO2-Nanopartikeln nach der N2-Plasmabehandlung eine ungeordnete OberflĂ€chenschicht mit einer Dicke von etwa 2,5 nm. Sowohl der dotierte Stickstoff als auch die ungeordnete OberflĂ€chenschicht spielen eine wichtige Rolle bei der Verbesserung der Natriumspeicherleistung. Drittens, haben wir das TiO2-Au (P-TiO2-Au, Goldnanocluster, unterstĂŒtzt durch P25 TiO2-Nanopartikel, Au-Belastung: ~ 2 wt%) als elektrochemische Katalysatoren fĂŒr die Stickstoffreduktionsreaktion benutzt. Das Material wurde mit H2-Plasma modifiziert und bildete dann einen blau-schwarzen H-TiO2-Au-Katalysator, der eine verbesserte Leistung fĂŒr den Prozess der Stickstoffreduktionsreaktion (NRR) im Vergleich zur unbehandelten Probe zeigte. Aus den TEM-Untersuchungen konnten wir einige ungeordnete Positionen an der OberflĂ€che finden, und auch die Raman-IntensitĂ€ten von H-TiO2-Au sind viel niedriger als das unbehandelte Material, das auf die ungeordnete OberflĂ€che und die Bildung von Sauerstoffleerstellen zurĂŒckzufĂŒhren ist. DarĂŒber hinaus konnte nach der Wasserstoff-Plasma-Behandlung ein kleiner Peak-Shift im XPS -Spektrum festgestellt werden. Wenn die Probe fĂŒr die elektrochemische NRR verwendet wurde, ist die Ausbeute an NH3 von blau-schwarzem H-TiO2-Au etwa 9,5 mal höher als die unbehandelte Probe, wĂ€hrend die höchste faradaysche Effizienz von 2,7 % auch bei dem Potential von -0,1V erreicht wird. Die Ergebnisse der DFT-Berechnung bestĂ€tigen, dass H-TiO2-Au bei Sauerstoffleerstellen und ungeordneter OberflĂ€chenschicht fĂŒr den NRR-Prozess sehr bevorzugt wird. Es zeigt auĂerdem, dass der Reduktionsprozess der H2-Plasma-Behandlung eine wichtige Rolle bei der Verbesserung der Leistung von Katalysatoren spielt. Es könnte das erste Mal sein, dass die Plasmatechnik zur Modifikation des Katalysators fĂŒr elektrochemische NRR-Prozesse eingesetzt wurde
The Combination of Laser Therapy and Metal Nanoparticles in Cancer Treatment Originated From Epithelial Tissues: A Literature Review
Several methods have been employed for cancer treatment including surgery, chemotherapy and radiation therapy. Today, recent advances in medical science and development of new technologies, have led to the introduction of new methods such as hormone therapy, Photodynamic therapy (PDT), treatments using nanoparticles and eventually combinations of lasers and nanoparticles. The unique features of LASERs such as photo-thermal properties and the particular characteristics of nanoparticles, given their extremely small size, may provide an interesting combined therapeutic effect. The purpose of this study was to review the simultaneous application of lasers and metal nanoparticles for the treatment of cancers with epithelial origin. A comprehensive search in electronic sources including PubMed, Google Scholar and Science Direct was carried out between 2000 and 2013. Among the initial 400 articles, 250 articles applied nanoparticles and lasers in combination, in which more than 50 articles covered the treatment of cancer with epithelial origin. In the future, the combination of laser and nanoparticles may be used as a new or an alternative method for cancer therapy or diagnosis. Obviously, to exclude the effect of laserâs wavelength and nanoparticleâs properties more animal studies and clinical trials are required as a lack of perfect studies
Computer vision system for egg volume prediction using backpropagation neural network
Volume is one of considered aspects in egg sorting process. A rapid and accurate volume measurement method is needed to develop an egg sorting system. Computer vision system (CVS) provides a promising solution for volume measurement problem. Artificial neural network (ANN) has been used to predict the volume of egg in several CVSs. However, volume prediction from ANN could have less accuracy due to inappropriate input features or inappropriate ANN structure. This paper proposes a CVS for predicting the volume of egg using ANN. The CVS acquired an image of egg from top view and then processed the image to extract its 1D and 2 D size features. The features were used as input for ANN in predicting the volume of egg. The experiment results show that the proposed CSV can predict the volume of egg with a good accuracy and less computation time
Web Application for Atmospheric Aerosol Data Management: Software and Case Study in the Spanish Network on Environmental Differential Mobility Analysers
[Abstract] SCALA© (Sampling Campaigns for Aerosols in the Low Atmosphere) is a web-based software system that was developed in a multidisciplinary manner to integrally support the documentation and the management and analysis of atmospheric aerosol data from sampling campaigns. The software development process applied considered the prototyping and the evolutionary approaches. The software product (SCALA©) allows for the comprehensive management of the sampling campaignsâ life cycle (management of the profiles and processes involved in the start-up, development and closure of a campaign) and provides support for both intra- and inter-campaigns data analysis. The pilot deployment of SCALA© considers the Spanish Network on Environmental Differential Mobility Analysers (DMAs) (REDMAAS) and the PROACLIM project. This research project involves, among other objectives, the study of temporal and spatial variations of the atmospheric aerosol through a set of microphysical properties (size distribution, optical properties, hygroscopicity, etc.) measured in several locations in Spain. The main conclusions regarding size distribution are presented in this work. These have been have been extracted through SCALA© from the data collected in the REDMAAS 2015 and 2019 intercomparison campaigns and two years (2015 and 2016) of measurements with two Scanning Mobility Particle Sizers (SMPS) at CIEMAT (Madrid, central Spain) and UDC (A Coruña, NW of Spain) sites.Ministerio de EconomĂa y Competitividad; CGL2014-52877-RMinisterio de EconomĂa y Competitividad; CGL2017-85344-RXunta de Galicia; GRC2013-047Xunta de Galicia; ED431C 2017/28Gobierno Regional de Madrid; Y2018/EMT-517
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Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China â Part 2: Size-resolved aerosol chemical composition, diurnal cycles, and externally mixed weakly CCN-active soot particles
Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC).
The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (Îșa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: Îșa,p=Îșorg·forg + Îșinorg·finorg. The characteristic Îș values of organic and inorganic components were similar to those observed in other continental regions of the world: Îșorgâ0.1 and Îșinorgâ0.6. The campaign average Îșa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg was on average 60% and increased to almost 100% during a biomass burning event.
The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at Sâ€0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around ÎșLVâ0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (Îșt) could be parameterized as a function of Îșa,p and the number fraction of low volatility particles determined by VTDMA (ÏLV): Îșt,p=Îșa,pâÏLV·(Îșa,pâÎșLV).
Based on Îș values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,Sâ102â104 cmâ3 at S = 0.068â0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using Îșt,p, and they increased to ~20% when using only Îșa,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of Îșâ0.3, although the constant Îș value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events).
Overall, the results confirm that on a global and climate modeling scale an average value of Îșâ0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%)
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