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In this study, the WRF model is used to investigate the role of Central Vietnam terrain on occurrence of the heavy rainfall event in November 1999 over Central Vietnam. Two model experiments with and without terrain were performed to examine the orographic blocking effects during the event. In the terrain experiment, the results from a three-day simulation show that the model reasonably well captures northeast monsoon circulation, tropical cyclones and the occurrence of heavy rainfall in Central Vietnam. The topography causes a high pressure anomaly intensifying northeast monsoon. When the terrain is removed, the three-day accumulated rainfall decreases approximately 75% in comparison with that in the terrain experiment. The terrain blocking and lifting effects in strong wind and moisture laden conditions combined with convergence circulation over open ocean are the main factors for occurrence of the heavy rainfall event.

Background and Objective Surgical skill assessment aims to objectively evaluate and provide constructive feedback for trainee surgeons. Conventional methods require direct observation with assessment from surgical experts which are both unscalable and subjective. The recent involvement of surgical robotic systems in the operating room has facilitated the ability of automated evaluation of the expertise level of trainees for certain representative maneuvers by using machine learning for motion analysis. The features extraction technique plays a critical role in such an automated surgical skill assessment system. Methods We present a direct comparison of nine well-known feature extraction techniques which are statistical features, principal component analysis, discrete Fourier/Cosine transform, codebook, deep learning models and auto-encoder for automated surgical skills evaluation. Towards near real-time evaluation, we also investigate the effect of time interval on the classification accuracy and efficiency. Results We validate the study on the benchmark robotic surgical training JIGSAWS dataset. An accuracy of 95.63, 90.17 and 90.26% by the Principal Component Analysis and 96.84, 92.75 and 95.36% by the deep Convolutional Neural Network for suturing, knot tying and needle passing, respectively, highlighted the effectiveness of these two techniques in extracting the most discriminative features among different surgical skill levels. Conclusions This study contributes toward the development of an online automated and efficient surgical skills assessment technique.

The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project that includes characterization of chemical and physical attributes of aerosols from filter samples collected worldwide. This paper discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in fine particulate matter (PM2.5). Our methods infer the spatial and temporal variability of PM2.5 in a cost-effective manner. Gravimetrically weighed filters represent multi-day averages of PM2.5, with a collocated nephelometer sampling air continuously. SPARTAN instruments are paired with AErosol RObotic NETwork (AERONET) sun photometers to better understand the relationship between ground-level PM2.5 and columnar aerosol optical depth (AOD).We have examined the chemical composition of PM2.5 at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a background comparison. So far, each SPARTAN location has been active between the years 2013 and 2016 over periods of 2–26 months, with an average period of 12 months per site. These sites have collectively gathered over 10 years of quality aerosol data. The major PM2.5 constituents across all sites (relative contribution ± SD) are ammoniated sulfate (20 % ± 11 %), crustal material (13.4 % ± 9.9 %), equivalent black carbon (11.9 % ± 8.4 %), ammonium nitrate (4.7 % ± 3.0 %), sea salt (2.3 % ± 1.6 %), trace element oxides (1.0 % ± 1.1 %), water (7.2 % ± 3.3 %) at 35 % RH, and residual matter (40 % ± 24 %).Analysis of filter samples reveals that several PM2.5 chemical components varied by more than an order of magnitude between sites. Ammoniated sulfate ranges from 1.1 µg m−3 (Buenos Aires, Argentina) to 17 µg m−3 (Kanpur, India in the dry season). Ammonium nitrate ranged from 0.2 µg m−3 (Mammoth Cave, in summer) to 6.8 µg m−3 (Kanpur, dry season). Equivalent black carbon ranged from 0.7 µg m−3 (Mammoth Cave) to over 8 µg m−3 (Dhaka, Bangladesh and Kanpur, India). Comparison of SPARTAN vs. coincident measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network at Mammoth Cave yielded a high degree of consistency for daily PM2.5 (r2 = 0.76, slope = 1.12), daily sulfate (r2 = 0.86, slope = 1.03), and mean fractions of all major PM2.5 components (within 6 %). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 % for 8 out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi, and Dhaka) are apparent from high Zn : Al ratios.The expected water contribution to aerosols is calculated via the hygroscopicity parameter κv for each filter. Mean aggregate values ranged from 0.15 (Ilorin) to 0.28 (Rehovot). The all-site parameter mean is 0.20 ± 0.04. Chemical composition and water retention in each filter measurement allows inference of hourly PM2.5 at 35 % relative humidity by merging with nephelometer measurements. These hourly PM2.5 estimates compare favourably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r2 = 0.67 (n = 3167), compared to r2 = 0.62 when κv was not considered. SPARTAN continues to provide an open-access database of PM2.5 compositional filter information and hourly mass collected from a global federation of instruments.

The development of the scientific, methodological and technical basis for an integrated terrestrial and satellite monitoring of the atmosphere and the Earth's surface over the Eurasian continent is the goal of an international project carried out by the scientific organizations of Belarus, Russia, Mongolia and Vietnam with the support of the Eurasian Association for the Support of Scientific Research (EAPS). The report presents the results of testing the method of coordinated terrestrial and satellite, lidar and radiometric measurements to study altitude profiles of aerosol parameters in the areas of AERONET stations in the countries participating in the project. The data of the satellite lidar CALIOP and the solar radiometer were processed by the algorithms developed in the frame of combined lidar and radiometric sounding technique (LRS). Coordinated multiwavelength lidar measurements were carried out at remote sensing stations in IPNASB (Minsk, Belarus), IAO (Tomsk, Russia) and KRSU (Teplokluchenka, Kyrgyzstan) to validate the results of satellite data processing.

Exposure to ambient fine particulate matter (PM2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM2.5 to interpret globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM2.5 composition varies substantially for secondary inorganic aerosols (2.4–19.7 μg/m3), mineral dust (1.9–14.7 μg/m3), residual/organic matter (2.1–40.2 μg/m3), and black carbon (1.0–7.3 μg/m3). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m3), industry (6.5 μg/m3), and power generation (5.6 μg/m3) are leading sources of outdoor global population-weighted PM2.5 concentrations. Global population-weighted organic mass is driven by the res...

Exposure to ambient fine particulate matter (PM

The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project designed to maximize the chemical and physical information obtained from filter samples collected worldwide. This manuscript discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in aerosols. Our methods infer the spatial and temporal variability of PM2.5 in a cost-effective manner; single filters represent multi-day averaged fine particulate matter (PM2.5), while an adjacent nephelometer samples air continuously. SPARTAN instruments are collocated with AERONET to better understand the relationship between ground-level PM2.5 and columnar aerosol optical depth (AOD). We have examined the chemical composition of PM2.5 at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a baseline comparison. Each SPARTAN location has so far been active between the years 2013 and 2015 over 2 to 22 month periods. These sites have collectively gathered over 10 years of quality aerosol data. The major PM2.5 constituents across all sites (relative contribution ± SD) were ammonium sulfate (20 % ± 10 %), crustal material (12 % ± 6.2 %), black carbon (11 % ± 8.4 %), ammonium nitrate (4.0 % ± 2.8 %), sea salt (2.2 % ± 1.5 %), trace element oxides (0.9 % ± 0.6 %), water (7.2 % ± 3.1 %) and residue materials (43 % ± 25 %). Analysis of filter samples revealed that several PM2.5 chemical components varied by more than an order of magnitude between sites. Ammonium sulfate ranged from 1.1 μg m−3 (Buenos Aires, Argentina) to 17 μg m−3 (Kanpur, India [dry season]). Ammonium nitrate ranged from 0.2 μg m−3 (Mammoth Cave, in summer) to 6.7 μg m−3 (Kanpur, dry season). Equivalent black carbon ranged from 0.7 μg m−3 (Mammoth Cave) to 8 μg m−3 (Dhaka, Bangladesh and Kanpur). Comparison with coincident measurements from the IMPROVE network at Mammoth Cave yielded a high degree of consistency for daily PM2.5 (r2 = 0.76, slope = 1.12), daily sulfate (r2 = 0.86, slope = 1.03) and mean fractions of all major PM2.5 components (within 6 %). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 % for eight out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi and Dhaka) were apparent from high Zn : Al ratios. The expected water contribution to aerosols was calculated via the hygroscopicity parameter κv for each filter. Mean aggregate values ranged from 0.15 (Manila and Ilorin) to 0.31 (Rehovot); with the latter included a major sulfate event. The all-site parameter mean is 0.19. Chemical composition and water retention in each filter measurement allowed inference of hourly PM2.5 at 35 % relative humidity by merging with nephelometer measurements. These hourly PM2.5 estimates compare favorably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation r2 = 0.67 (n = 3167), compared to r2 = 0.62 when κv was not considered. SPARTAN continues to provide an open-access database of PM2.5 compositional filter information and hourly mass collected from a global federation of instruments.

Possibility of using global positioning systems to determine the refraction coefficient of troposphere is considered. Connection between errors of altitude measurements and condition of troposphere is revealed.

A method for estimating the turbulent pulsations of the velocity of air masses in clouds has been proposed. This method is based on the spectra of scattered signals and makes use of the moment characteristics of the scattered signal spectrum and deviations of the characteristics from trend changes for estimating the shear characteristics of the air stream in terms of both the average speed and its spread.

Recommender systems are the capable systems of providing essential information and removing unessential information for Internet users. The recommender systems are built based on two main information filtering techniques: Collaborative filtering and content-based filtering. Each method exploits particular aspects related to content features or product usage habit of users in the past to predict a brief list of the most suitable items with each user. In this paper, we propose a new unify method between collaborative filtering recommendation and content-based filtering recommendation based on graph model. The model allows us to shift hybrid filtering recommender problem to collaborative filtering recommender problem, then build new similarity measures based on graph to determine similarities between two users or two items, these similar measures are used to predict suitable items for users in the system. The experimental results on real data sets show that the proposed methods achieve superior performance compared to baseline methods.

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short-and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency. Fil: Snider, G.. Dalhousie University Halifax; Canadá Fil: Weagle, C. L.. Dalhousie University Halifax; Canadá Fil: Martin, R. V.. Dalhousie University Halifax; Canadá. University of Cambridge; Reino Unido Fil: van Donkelaar, A.. Dalhousie University Halifax; Canadá Fil: Conrad, K.. Dalhousie University Halifax; Canadá Fil: Cunningham, D.. Dalhousie University Halifax; Canadá Fil: Gordon, C.. Dalhousie University Halifax; Canadá Fil: Zwicker, M.. Dalhousie University Halifax; Canadá Fil: Akoshile, C.. University of Ilorin; Nigeria Fil: Artaxo, P.. Governo Do Estado de Sao Paulo; Brasil Fil: Anh, N. X.. Vietnam Academy of Science and Technology. Institute of Geophysics; Vietnam Fil: Brook, J.. University of Toronto; Canadá Fil: Dong, J.. Tsinghua University; China Fil: Garland, R. M.. North-West University; Sudáfrica Fil: Greenwald, R.. Rollins School of Public Health; Estados Unidos Fil: Griffith, D.. Council for Scientific and Industrial Research; Sudáfrica Fil: He, K.. Tsinghua University; China Fil: Holben, B. N.. NASA Goddard Space Flight Center; Estados Unidos Fil: Kahn, R.. NASA Goddard Space Flight Center; Estados Unidos Fil: Koren, I.. Weizmann Institute Of Science Israel; Israel Fil: Lagrosas, N.. Manila Observatory, Ateneo de Manila University campus; Filipinas Fil: Lestari, P.. Institut Teknologi Bandung; Indonesia Fil: Ma, Z.. Rollins School of Public Health; Estados Unidos Fil: Vanderlei Martins, J.. University of Maryland; Estados Unidos Fil: Quel, Eduardo Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rudich, Y.. Weizmann Institute Of Science Israel; Israel Fil: Salam, A.. University Of Dhaka; Bangladesh Fil: Tripathi, S. N.. Indian Institute Of Technology, Kanpur; India Fil: Yu, C.. Rollins School of Public Health; Estados Unidos Fil: Zhang, Q.. Tsinghua University; China Fil: Zhang, Y.. Tsinghua University; China Fil: Brauer, M.. University of British Columbia; Canadá Fil: Cohen, A.. Health Effects Institute; Estados Unidos Fil: Gibson, M. D.. Dalhousie University Halifax; Canadá Fil: Liu, Y.. Rollins School of Public Health; Estados Unidos

It is known the operating efficiency of radio technical systems of different function (navigation, radar, communication), to a great extent depend on condition of propagation of radio-waves is conditioned on atmosphere refraction state. It for one's turn is conditioned on spatial-temporal distribution of refraction coefficient n . And variation of mean refraction and numerous cases of so called anomalous propagation of radio-waves could lead to considerable increasing of signal level over the horizon or signal fading in the radio-optical line of distance and influence on accuracy of radar and navigation measurements. At present for location the systems of global navigation is in wide application. The completely deployed GPS system of USA exists today. Russia realizes intense work on unwrapping of complete constellation of GLONAS satellites. In the Europe the development of Galileo system is finishes. To the utmost the troposphere influences on results of coordinate measurements. Ignoring of this fact leads to error of measuring of pseudo-range from 2,5 m. (in zenith) to 25 m. (while satellite elevation about 5 degrees). The possible way to decreasing of location error is taking into account troposphere influence while processing of information in the Ukrainian system of cosmic navigation provision (USCNP) [1, 2]. There are two main modes of correction: real-time and post session. For real-time processing we propose to use the data of meteorological stations are in the set of controlling-correcting stations (CCS) USCNP. At that have to be provided accuracies of coordinates determination not worth of some meters. While post session processing corrections are forming on the base of phase observations by stations of USCNP net. The obtained errors of measurement are about some centimeters. Troposphere delays in the real-time the meteorological parameters are obtained in series of points of space are used for approximation. The meteorological parameters of functions approximating dependence of temperature, pressure and humidity on latitude and longitude in the range of Ukraine are forming and giving for users on the base of these delays. Besides the parameters of functions approximating dependence of zenith troposphere delay on latitude and longitude in the range of Ukraine are forming and giving for users. Both these approaches are on the base of troposphere delays calculation using data of meteorological stations to the sea level. Truncation error of estimation is about 2.5%. The analyses is carried out [2] and shows the order of approximating model practically not influences on error of troposphere delay measurement and so we conclude about possibility of usage of zero order model, i.e. the mean data for Ukraine. We seem the bases for such conclusion is small accuracies of measurement of meteorological parameters.

This paper describes a research work whose objective is to help students to learn algebra with a computer. Firstly, we summarise the theoretical foundations and we describe a prototype devoted to the factoring problem. With this prototype, the student solves problems without making the calculations. The student can also observe the system solving a problem and providing explanations. Secondly, we summarise several experiments we carried out with students and we describe the results we got. Last, we present our new objective that consists of making a product that will be available for all students and teachers.

Nguyen-Xuan Anh. Le fonctionnement cognitif : Qu'y-a-t-il eu depuis Human problem solving de Newell et Simon?. In: Bulletin de psychologie, tome 32 n°340, 1979. L'intelligence. pp. 625-641.

Nguyen-Xuan Anh. Structure factorielle et théorie psychogénétique de l'intelligence. In: Bulletin de psychologie, tome 30 n°328, 1977. pp. 493-497.

Nguyen-Xuan Anh. Aptitudes définies par les tests et réussites scolaires dans l'enseignement secondaire. In: Bulletin de psychologie, tome 20 n°257, 1967. pp. 834-844.