Search results for: soil texture prediction

Authors: Abhay Asthana, Shally Toshkhani, Gyati Shilakari

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The present research was aimed to develop a biodegradable dermal patch formulation for wound healing in a novel, sustained and systematic manner. The goal is to reduce the frequency of dressings with improved drug delivery and thereby enhance therapeutic performance. In present study optimized formulation was designed using component polymers and excipients (e.g. Hydroxypropyl methyl cellulose, Ethylcellulose, and Gelatin) to impart significant folding endurance, elasticity and strength. Gelatin was used to get a mixture using ethylene glycol. Chitosan dissolved in suitable medium was mixed with stirring to gelatin mixture. With continued stirring to the mixture Curcumin was added in optimized ratio to get homogeneous dispersion. Polymers were dispersed with stirring in final formulation. The mixture was sonicated casted to get the film form. All steps were carried out under under strict aseptic conditions. The final formulation was a thin uniformly smooth textured film with dark brown-yellow color. The film was found to have folding endurance was around 20 to 21 times without a crack in an optimized formulation at RT (23C). The drug content was in range 96 to 102% and it passed the content uniform test. The final moisture content of the optimized formulation film was NMT 9.0%. The films passed stability study conducted at refrigerated conditions (4±0.2C) and at room temperature (23 ± 2C) for 30 days. Further, the drug content and texture remained undisturbed with stability study conducted at RT 23±2C for 45 and 90 days. Percentage cumulative drug release was found to be 80% in 12 h and matched the biodegradation rate as drug release with correlation factor R2 > 0.9. The film based formulation developed shows promising results in terms of stability and release profiles.

Keywords: biodegradable, patch, bioactive, polymer

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Authors: T. Bouchabchoub, A. Bendahmane, A. Haouriqui, N. Attou

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This paper presents simulation results of Forex predicting model equations in order to give approximately a prevision of interest rates. First, Hall-Taylor (HT) equations have been used with Taylor rule (TR) to adapt them to European and American Forex Markets. Indeed, initial Taylor Rule equation is conceived for all Forex transactions in every States: It includes only one equation and six parameters. Here, the model has been used with Hall-Taylor equations, initially including twelve equations which have been reduced to only three equations. Analysis has been developed on the following base macroeconomic variables: Real change rate, investment wages, anticipated inflation, realized inflation, real production, interest rates, gap production and potential production. This model has been used to specifically study the impact of an inflation shock on macroeconomic director interest rates.

Keywords: interest rate, Forex, Taylor rule, production, European Central Bank (ECB), Federal Reserve System (FED).

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Authors: Rino Gubiani, Gianfranco Pergher

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The work focused on the statistical analysis of accidents in the forestry sector (2000-2020) in Friuli-Venezia Giulia region, located in the North-East of Italy. The aim of the work was to analyse the evolution of the casualties throughout time and to evaluate possible improvements in the sector. It was shown that even nowadays the rate of accidents in forestry work is higher compared with all the other sectors, including agriculture; moreover, it was highlighted that some accidents remained present throughout the whole analysed range, such as slipping on the soil, being hit by trees and falling down from the plants. The results showed that an increase in forestry exploitation could even increase the total number of accidents, if advanced technological machines, such as cable cranes, would not implemented, given the fact that there is also a significant number of old people (above 50 years old) working in the sector.

Keywords: safety, forestry work, accidents, risk analysis, casualties, statistical analysis

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Authors: Mutwakil Nafi, Abed Elaziz El Amein, Muna El Dawi, Khalafala Salih, Osma Elbahi, Abed Elhalim Abou

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Recently a large deposit of oolitic iron ore of Late Carboniferous-Permotriassic-Lower Jurassic age was discovered in Wadi Halfa and Argein areas, North Sudan. It seems that the iron ore mineralization exists in the west and east bank of the River Nile of the study area that are found on the Egyptian-Sudanese border. The Carboniferous-Lower Jurassic age strata were covered by 67 sections and each section has been examined and carefully described. The iron-ore in Wadi Halfa occurs as oolitic ironstone and contained two horizons: (A) horizon and (B) horizon. Only horizon (A) was observed in southern Argein area. The texture of the ore is variable depending on the volume of the component. In thin sections the average of the ooids were ranged between 90% - 80%. The matrix varies between 10%-20% by volume and detritus quartz in other component my reach up to 30% by volume in sandy massive ore. Ooids size ranges from 0.2mm-1.00 mm on average in very coarse ooids may attend up to 1 mm in size. The matrix around the ooids is dominated by iron hydroxide, carbonate, fine and amorphous silica. The probable ore reserve estimate of 1.234 billion at a head grade of 41.29% Fe for the Wadi Halfa Oolitic Ironstone Formation. The iron ore shows higher content of phosphorus ranges from 6.15% to 0.16%, with mean 1.45%. The new technology Hatch–Ironstone Chloride Segregation (HICS) can be used to produce commercial-quality of iron and reduce phosphorus and silica to acceptable levels for steel industry. The development of infra structures and presence huge quantity of iron ore would make exploitation of the iron ore economic.

Keywords: HICS, Late Carboniferous age, oolitic iron ore, phosphorus

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: Milind Chaudhari, Suhail Balasinor

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Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

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Authors: Mohamed Bekhit Gad Khalil

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This dam is the oldest dam in history. It was built by the ancient Egyptian around (2650 B.C) control flooding. It is believed to have been built between the third and fourth dynasties .It contains the oldest dam in history. Many studies have been conducted for the dam. This report was prepared under my supervision and in cooperation with the Ministry of Tourism and Antiquities. The dam was re-documented and photographed again. The dam on the northern side Consists of irregularly shaped stones of varying sizes used randomly. Sand and soil fill the gaps between the stones. creating layers to form the body of the dam. The eastern. side of the dam Consists of a series of regular shaped stones that have been cut and constructed into a stepped pyramid-like structure with width of (15,7) meters and height of (10) meters. The surface has significant erosion and wear on the stones due to weather Conditions. which has resulted in deep cavities in most of the stone blocks forming the surface.

Keywords: ministry of tourism and antiquities, excavations, registration, documentation

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Authors: Riccardo Angiuli, Michele Giannuzzi, Rodolfo Franchi, Gabriele Papadia

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Temperature knowledge in machining is fundamental to improve the numerical and FEM models used for the study of some critical process aspects, such as the behavior of the worked material and tool. The extreme conditions in which they operate make it impossible to use traditional measuring instruments; infrared thermography can be used as a valid measuring instrument for temperature measurement during metal cutting. In the study, a large experimental program on superduplex steel (ASTM A995 gr. 5A) cutting was carried out, the relevant cutting temperatures were measured by infrared thermography when certain cutting parameters changed, from traditional values to extreme ones. The values identified were used to calibrate a FEM model for the prediction of residual life of the tools. During the study, the problems related to the detection of cutting temperatures by infrared thermography were analyzed, and a dedicated procedure was developed that could be used during similar processing.

Keywords: machining, infrared thermography, FEM, temperature measurement

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Authors: Djarot B. Darmadi

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The wider growing Finite Element Method (FEM) application is caused by its benefits of cost saving and environment friendly. Also, by using FEM a deep understanding of certain phenomenon can be achieved. This paper observed the role of material properties and volumetric change when Solid State Phase Transformation (SSPT) takes place in residual stress formation due to a welding process of ferritic steels through coupled Thermo-Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by experiment. From parametric study of the FEM model, it can be concluded that the material properties change tend to over-predicts residual stress in the weld center whilst volumetric change tend to underestimates it. The best final result is the compromise of both by incorporates them in the model which has a better result compared to a model without SSPT.

Keywords: residual stress, ferritic steels, SSPT, coupled-TMM

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Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco

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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.

Keywords: forecasting, ordinary differential equations, SARS-COV-2 epidemic, SIR model

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Authors: Meri Khakhutaishvili, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

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Cultivation of blueberry in Georgia started in 21st century. There are more than 20 species of blueberry cultivated in this region from all other the world. The species are mostly planted on acidic soil, previously occupied by tea plantations. Many of the plantations have pretty good yield. It is known that changing the location of a plant to a new soil or climate effects chemical compositions of the plant. However, even though these plants are brought from other countries, no research has been conducted to fully examine the blueberry fruit cultivated in Georgia. Shota Rustaveli National Science Foundation Grant FR/335/10-160/14, gave us an opportunity to continue our previous works and conduct research on several berries, among them of course the chemical composition of stored Blueberry. We were able to conduct the first study that included examining qualitative and quantitative features of bioactive compounds in Georgian Blueberry. This experiments were held in the ‘West Georgia Regional Chromatography center’ (Grant AP/96/13) of our university, that is equipped with modern equipment like HPLC UV-Vis, RI-detector, HPLC-conductivity detector, UPLC-MS-detector. Biochemical analysis was conducted using different physico-chemical and instrumental methods. Separation-identification and quantitative analysis were conducted using UPLC-MS (Waters Acquity QDa detector), HPLC (Waters Brceze 1525, UV-Vis 2489 detectors), pH-meters (Mettler Toledo). Refractrometer -Misco , Spectrometer –Cuvette Changer (Mettler Toledo UV5A), C18 Cartridge Solid Phase Extraction (SPE) Waters Sep-Pak C18 (500 mg), Chemicals – stability radical- 2,2-Diphenil-1-picrilhydrazyl (Aldrich-germany), Acetonitrile, Methanol, Acetic Acid (Merck-Germany), AlCl3, Folin Ciocalteu reagent (preparation), Standarts –Callic acid, Quercetin. Carbohydrate HPLC-RI analysis used systems acetonitrile-water (80-20). UPLC-MS analysis used systems- solvent A- Water +1 % acetic acid და solvent -B Methanol +1% acetic acid). It was concluded that the amount of sugars was in range of 5-9 %, mostly glucose and fructose. Also, the amount of organic acids was 0.2-1.2% most of which was malic and citric acid. Anthocians were also present in the sample 200-550mg/100g. We were able to identify up to 15 different compounds, most of which were products of delphinidine and cyanide. All species have high antioxidant level(DPPH). By rapidly freezing the sample and then keeping it in specific conditions allowed us to keep the sample for 12 months.

Keywords: antioxidants, bioactive, blueberry, storage

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Authors: Arezoo Sadrinezhad, Kallol Sett, S. I. Hariharan

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In this paper, a probabilistic framework based on Fokker-Planck-Kolmogorov (FPK) approach has been applied to simulate triaxial cyclic constitutive behavior of uncertain soils. The framework builds upon previous work of the writers, and it has been extended for cyclic probabilistic simulation of triaxial undrained behavior of soils. von Mises elastic-perfectly plastic material model is considered. It is shown that by using probabilistic framework, some of the most important aspects of soil behavior under cyclic loading can be captured even with a simple elastic-perfectly plastic constitutive model.

Keywords: elasto-plasticity, uncertainty, soils, fokker-planck equation, fourier spectral method, finite difference method

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Mehmet Sinan Erguven

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Modern art is relatively new but a popular area in Turkish art society. Modern art museums are mainly located in big cities like Istanbul and Ankara where cultural life is more dynamic. Odunpazarı Modern Museum (OMM) will open its doors on September 2019 and be the only modern art museum located in a small town in Turkey. OMM executives declare the mission of the museum as; art must go beyond the metropolises of the world, give a new lease of life to cities that make a difference with their cultural texture, and reach a greater audience through that expansion. So OMM will not only serve as a museum but a landmark for regenerating the city brand of Eskişehir like the Guggenheim in Bilbao. OMM is located in the Odunpazarı area, the heart of Eskişehir. Named after the historical timber market it once hosted, Odunpazarı is a nominated site for the UNESCO Intangible Cultural Heritage List, and is Eskişehir’s first area of settlement. This study focuses on the complex nature of opening a modern art museum in a small town. The management and marketing dynamics of OMM are discussed in the study. Content analysis technique is used on local and national news to display the perception differences before and after the opening of OMM. In depth interviews with the executives of the museum are conducted in order to enlighten the insights of opening a modern art museum in a small town. Early findings of the content analysis point out that, the comments on the national press are mostly positive. On the other hand, different views occur on the local press. The location OMM is constructed and grandness of the museum building are criticized by some of the local newspapers. OMM’s potential as a tourist attraction is agreed by most of the media. OMM executives stated the most challenging task as reaching the different target audiences on international, national and local levels. These early findings will be improved and compared shortly before and after the opening of the museum.

Keywords: management, marketing, Odunpazarı modern museum, small town

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Authors: Ruichong Zhang

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This study proposes a recording-based approach to characterize and quantify earthquake-induced site nonlinearity, exemplified as soil nonlinearity and/or liquefaction. Alternative to Fourier spectral analysis (FSA), the paper introduces time-frequency analysis of earthquake ground motion recordings with the aid of so-called Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the nonlinear features shown in the recordings. With the use of the 2001 Nisqually earthquake recordings, this study shows that the proposed approach is effective in characterizing site nonlinearity and quantifying the influences in seismic ground responses.

Keywords: site nonlinearity, site amplification, site damping, Hilbert-Huang Transform (HHT), liquefaction, 2001 Nisqually Earthquake

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Sheikh Samsuzzhan Alam

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The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: G. K. Pandey, D. Ramadasu, I. Banerjee, V. Vinod, G. Padmakumar, V. Prakash, K. K. Rajan

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Detailed thermal hydraulic investigations are very essential for safe and reliable functioning of liquid metal cooled fast breeder reactors. These investigations are further more important for components with complex profile, since there is no direct correlation available in literature to evaluate the hydraulic characteristics of such components directly. In those cases available correlations for similar profile or geometries may lead to significant uncertainty in the outcome. Hence experimental approach can be adopted to evaluate these hydraulic characteristics more precisely for better prediction in reactor core components. Prototype Fast Breeder Reactor (PFBR), a sodium cooled pool type reactor is under advanced stage of construction at Kalpakkam, India. Several components of this reactor core require hydraulic investigation before its usage in the reactor. These hydraulic investigations on full scale models, carried out by experimental approaches using water as simulant fluid are discussed in the paper.

Keywords: fast breeder reactor, cavitation, pressure drop, reactor components

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Authors: Zhaocheng Shang

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In order to study the topic of cities crossing rivers, a Four-Dimensional Analysis Method consisting of timeline, X-axis, Y-axis, and Z-axis is proposed. Policies, plans, and their implications are summarized and researched along with the timeline. The X-axis is the direction which is parallel to the river. The research area was chosen because of its important connection function. It is proposed that more surface water network should be built because of the ecological orientation of the research area. And the analysis of groundwater makes it for sure that the proposal is feasible. After the blue water network is settled, the green landscape network which is surrounded by it could be planned. The direction which is transversal to the river (Y-axis) should run through the transportation axis so that the urban texture could stretch in an ecological way. Therefore, it is suggested that the work of the planning bureau and river bureau should be coordinated. The Z-axis research is on the section view of the river, especially on the Yellow River’s special feature of being a perched river. Based on water control safety demands, river parks could be constructed on the embankment buffer zone, whereas many kinds of ornamental trees could be used to build the buffer zone. City Crossing River is a typical case where we make use of landscaping to build a symbiotic relationship between the urban landscape architecture and the environment. The local environment should be respected in the process of city expansion. The planning order of "Benefit- Flood Control Safety" should be replaced by "Flood Control Safety - Landscape Architecture- People - Benefit".

Keywords: blue-green landscape network, city crossing river, four-dimensional analysis method, planning order

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Authors: Susana P. Dias, Andrea Gomes, Fernanda M. Ferreira, Marta F. Henriques

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Thymus mastichina L. is an endogenous medicinal and aromatic plant of the Mediterranean flora. It has been used empirically over the years as a natural preservative in food. Nowadays, the antimicrobial activity of its bioactive compounds, such as essential oils and extracts, has been well recognized. The main purpose of this study was to evaluate the antimicrobial effect of Thymus mastichina ethanolic and aqueous extracts on pathogens and spoilage microorganisms present in cheese during ripening. The effect that the extract type and its concentration has on the development of Staphylococcus aureus, Escherichia coli, and Yarrowia lipolytica populations during 24 hours, was studied 'in vitro' using appropriate culture media. The results achieved evidenced the antimicrobial activity of T. mastichina extracts against the studied strains, and the concentration of 2 mg/mL (w/v) was selected and used directly on the cheese surface during ripening. In addition to the microbiological evaluation in terms of total aerobic bacteria, Enterobacteriaceae, yeasts (particularly Y. lipolytica) and molds, the treated cheeses physicochemical evaluation (humidity, aw, pH, colour, and texture) was also performed. The results were compared with cheeses with natamicyn (positive control) and without any treatment (negative control). The physicochemical evaluation showed that the cheeses treated with ethanolic extract of Thymus mastichina, except the fact that they lead to a faster water loss during ripening, did not present considerable differences when compared to controls. The study revealed an evident antimicrobial power of the extracts, although less effective than the one shown by the use of natamycin. For this reason, the improvement of the extraction methods and the adjustment of the extract concentrations will contribute to the use of T. mastichina as a healthier and eco-friendly alternative to natamycin, that is also more attractive from an economic point of view.

Keywords: antimicrobial activity, cheese, ethanolic extract, Thymus mastichina

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Authors: Jesus Ruano, Francesc Xavier Trias, Asensi Oliva

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A three-dimensional incompressible Large Eddy Simulation (LES) is performed to compute the hydrodynamic field around a pair of tandem cylinders. Symmetry-preserving schemes will be used during this simulation in conjunction with Finite Volume Method (FVM) to obtain the hydrodynamic field around the selected geometry. A set of results consisting of pressure and velocity and the combination of them will be stored at different surfaces near the cylinders as the initial input for the second part of the study. A post-processing of the obtained results based on Ffowcs-Williams and Hawkings (FWH) equation with a Fourier Transform of the acoustic sources will be used to compute noise at several probes located far away from the region where the hydrodynamics are computed. Directivities as well as spectral profile of the obtained acoustic field will be analyzed.

Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, long-span bodies

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Authors: N. P. Yadav, Deepti Verma

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This paper focuses on the mathematical modeling for solidification of Al alloy in a cube mould cavity to study the solidification behavior of casting process. The parametric investigation of solidification process inside the cavity was performed by using computational solidification/melting model coupled with Volume of fluid (VOF) model. The implicit filling algorithm is used in this study to understand the overall process from the filling stage to solidification in a model metal casting process. The model is validated with past studied at same conditions. The solidification process are analyzed by including the effect of pouring velocity and temperature of liquid metal, effect of wall temperature as well natural convection from the wall and geometry of the cavity. These studies show the possibility of various defects during solidification process.

Keywords: buoyancy driven flow, natural convection driven flow, residual flow, secondary flow, volume of fluid

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Authors: Cinzia Federico, Gaetano Giudice, Salvatore Inguaggiato, Marco Liuzzo, Maria Pedone, Fabio Vita, Christoph Kern, Leonardo La Pica, Giovannella Pecoraino, Lorenzo Calderone, Vincenzo Francofonte

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The periods of increased fumarolic activity at La Fossa volcano have been characterized, since early 80's, by changes in the gas chemistry and in the output rate of fumaroles. Excepting the direct measurements of the steam output from fumaroles performed from 1983 to 1995, the mass output of the single gas species has been recently measured, with various methods, only sporadically or for short periods. Since 2008, a scanning DOAS system is operating in the Palizzi area for the remote measurement of the in-plume SO₂ flux. On these grounds, the need of a cross-comparison of different methods for the in situ measurement of the output rate of different gas species is envisaged. In 2015, two field campaigns have been carried out, aimed at: 1. The mapping of the concentration of CO₂, H₂S and SO₂ in the fumarolic plume at 1 m from the surface, by using specific open-path diode tunable lasers (GasFinder Boreal Europe Ltd.) and an Active DOAS for SO₂, respectively; these measurements, coupled to simultaneous ultrasonic wind speed and meteorological data, have been elaborated to obtain the dispersion map and the output rate of single species in the overall fumarolic field; 2. The mapping of the concentrations of CO₂, H₂S, SO₂, H₂O in the fumarolic plume at 0.5 m from the soil, by using an integrated system, including IR spectrometers and specific electrochemical sensors; this has provided the concentration ratios of the analysed gas species and their distribution in the fumarolic field; 3. The in-fumarole sampling of vapour and measurement of the steam output, to validate the remote measurements. The dispersion map of CO₂, obtained from the tunable laser measurements, shows a maximum CO₂ concentration at 1m from the soil of 1000 ppmv along the rim, and 1800 ppmv in the inner slopes. As observed, the largest contribution derives from a wide fumarole of the inner-slope, despite its present outlet temperature of 230°C, almost 200°C lower than those measured at the rim fumaroles. Actually, fumaroles in the inner slopes are among those emitting the largest amount of magmatic vapour and, during the 1989-1991 crisis, reached the temperature of 690°C. The estimated CO₂ and H₂S fluxes are 400 t/d and 4.4 t/d, respectively. The coeval SO₂ flux, measured by the scanning DOAS system, is 9±1 t/d. The steam output, recomputed from CO₂ flux measurements, is about 2000 t/d. The various direct and remote methods (as described at points 1-3) have produced coherent results, which encourage to the use of daily and automatic DOAS SO₂ data, coupled with periodic in-plume measurements of different acidic gases, to obtain the total mass rates.

Keywords: DOAS, fumaroles, plume, tunable laser

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Authors: Jai Prakash Prasad, Suresh Chandra Mohan

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Modern wireless sensor networks (WSN) consist of small size, low cost devices which are networked through tight wireless communications. WSN fundamentally offers cooperation, coordination among sensor networks. Potential applications of wireless sensor networks are in healthcare, natural disaster prediction, data security, environmental monitoring, home appliances, entertainment etc. The design, development and deployment of WSN based on application requirements. The WSN design performance is optimized to improve network lifetime. The sensor node resources constrain such as energy and bandwidth imposes the limitation on efficient resource utilization and sensor node management. The proposed N-Tier GRID routing protocol focuses on the design of energy efficient large scale wireless sensor network for improved performance than the existing protocol.

Keywords: energy efficient, network lifetime, sensor networks, wireless communication

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Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Milind D. Meshram

Abstract:

Ascarids are the most frequent worm parasite of dogs and cats. There are two species that commonly infect dogs: Toxocara canis and Toxascaris leonina. Adult roundworms live in the stomach and intestines and can grow to 7 inches (18 cm) long. A female may lay 200,000 eggs in a day. The eggs are protected by a hard shell. They are extremely hardy and can live for months or years in the soil. A dog aged about 6 years, from Satara was referred to Teaching Veterinary Clinical Complex (TVCC) with a complaint of abdominal pain, anorexia, loss of condition and dull body coat with mucous pale membrane. The clinical examination revealed Anaemia, palpation of abdomen revealed enlargement of liver, slimy feel of the intestine loop, diarrhea.

Keywords: therapeutic management, Toxocara canis, induced hepatitis, dogs

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Authors: Saddam Hussain, Ghadeer Mohsen Albadrani

Abstract:

Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.

Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain

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