Search results for: vector density

Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Fang Liu, JunShuai Xue, JiaJia Yao, XueYan Yang, ZuMao Li, GuanLin Wu, HePeng Zhang, ZhiPeng Sun

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III-Nitride resonant tunneling diode (RTD) is one of the most promising candidates for multiple-valued logic (MVL) elements. Here, we report a monolithic integration of GaN resonant tunneling diodes to realize multiple negative differential resistance (NDR) regions for MVL application. GaN RTDs, composed of a 2 nm quantum well embedded in two 1 nm quantum barriers, are grown by plasma-assisted molecular beam epitaxy on free-standing c-plane GaN substrates. Negative differential resistance characteristic with a peak current density of 178 kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed. Statistical properties exhibit high consistency showing a peak current density standard deviation of almost 1%, laying the foundation for the monolithic integration. After complete electrical isolation, two diodes of the designed same area are connected in series. By solving the Poisson equation and Schrodinger equation in one dimension, the energy band structure is calculated to explain the transport mechanism of the differential negative resistance phenomenon. Resonant tunneling events in a sequence of the series-connected RTD pair (SCRTD) form multiple NDR regions with nearly equal peak current, obtaining three stable operating states corresponding to ternary logic. A frequency multiplier circuit achieved using this integration is demonstrated, attesting to the robustness of this multiple peaks feature. This article presents a monolithic integration of SCRTD with multiple NDR regions driven by the resonant tunneling mechanism, which can be applied to a multiple-valued logic field, promising a fast operation speed and a great reduction of circuit complexity and demonstrating a new solution for nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, multiple-valued logic system, frequency multiplier, negative differential resistance, peak-to-valley current ratio

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Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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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: Jiří Barta, Oldřich Svoboda, Jiří F. Urbánek

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In this paper will be discussed two coin´s sides of crisis scenarios dynamics. On the one's side is negative role of subsidiary scenario branches in its compactness weakening by means unduly chaotic atomizing, having many interactive feedbacks cases, increasing a value of a complexity here. This negative role reflects the complexity of use cases, weakening leader compliancy, which brings something as a ´readiness for controlling capabilities provision´. Leader´s dissatisfaction has zero compliancy, but factual it is a ´crossbar´ (interface in fact) between planning and executing use cases. On the other side of this coin, an advantage of rich scenarios embranchment is possible to see in a support of response awareness, readiness, preparedness, adaptability, creativity and flexibility. Here rich scenarios embranchment contributes to the steadiness and resistance of scenario mission actors. These all will be presented in live power-points ´Blazons´, modelled via DYVELOP (Dynamic Vector Logistics of Processes) on the Conference.

Keywords: leadership, controlling, complexity, DYVELOP, scenarios

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Authors: Isao Tomita

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Electrical conduction in a quasi-one-dimensional polycrystalline metallic ring with a long electron phase coherence length realized at low temperature is investigated. In this situation, the wave nature of electrons is important in the ring, where the electrical current I can be induced by a vector potential that arises from a static magnetic field applied perpendicularly to the ring’s area. It is shown that if the average grain size of the polycrystalline ring becomes large (or comparable to the Fermi wavelength), the electrical current I increases to ~I0, where I0 is a current in a disorder-free ring. The cause of this increasing effect is examined, and this takes place if the electron localization length in the polycrystalline potential increases with increasing grain size, which gives rise to coherent connection of tails of a localized electron wave function in the ring and thus provides highly coherent electrical conduction.

Keywords: electrical conduction, electron phase coherence, polycrystalline metal, magnetic field

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Authors: Abdalla Mohamed M. Musbahi

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The study area lies in Al-Falah area on Airport-Tripoli in Zone (16) Where planned establishment of complex multi-floors for residential and commercial, this part was divided into seven subzone. In each sup zone, were collected Orthogonal profiles by using Seismic refraction method. The overall aim with this project is to investigate the applicability of Seismic refraction method is a commonly used traditional geophysical technique to determine depth-to-bedrock, competence of bedrock, depth to the water table, or depth to other seismic velocity boundaries The purpose of the work is to make engineers and decision makers recognize the importance of planning and execution of a pre-investigation program including geophysics and in particular seismic refraction method. The overall aim with this thesis is achieved by evaluation of seismic refraction method in different scales, determine the depth and velocity of the base layer (bed-rock). Calculate the elastic property in each layer in the region by using the Seismic refraction method. The orthogonal profiles was carried out in every subzones of (zone 16). The layout of the seismic refraction set up is schematically, the geophones are placed on the linear imaginary line whit a 5 m spacing, the three shot points (in beginning of layout–mid and end of layout) was used, in order to generate the P and S waves. The 1st and last shot point is placed about 5 meters from the geophones and the middle shot point is put in between 12th to 13th geophone, from time-distance curve the P and S waves was calculated and the thickness was estimated up to three-layers. As we know any change in values of physical properties of medium (shear modulus, bulk modulus, density) leads to change waves velocity which passing through medium where any change in properties of rocks cause change in velocity of waves. because the change in properties of rocks cause change in parameters of medium density (ρ), bulk modulus (κ), shear modulus (μ). Therefore, the velocity of waves which travel in rocks have close relationship with these parameters. Therefore we can estimate theses parameters by knowing primary and secondary velocity (p-wave, s-wave).

Keywords: application of seismic, geotechnical study, physical properties, seismic refraction

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Authors: Sutapa Mondal Roy, Suban K. Sahoo

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The primary aim of this work is to synthesis silver nanoparticles (AgNPs) through environmentally benign routes to avoid any chemical toxicity related undesired side effects. The nanoparticles were stabilized with drug ciprofloxacin (Cp) and were studied for their effectiveness as drug delivery agent. Targeted drug delivery improves the therapeutic potential of drugs at the diseased site as well as lowers the overall dose and undesired side effects. The small size of nanoparticles greatly facilitates the transport of active agents (drugs) across biological membranes and allows them to pass through the smallest capillaries in the body that are 5-6 μm in diameter, and can minimize possible undesired side effects. AgNPs are non-toxic, inert, stable, and has a high binding capacity and thus can be considered as biomaterials. AgNPs were synthesized from the nutrient broth supernatant after the culture of environment-friendly bacteria Bacillus subtilis. The AgNPs were found to show the surface plasmon resonance (SPR) band at 425 nm. The Cp capped Ag nanoparticles formation was complete within 30 minutes, which was confirmed from absorbance spectroscopy. Physico-chemical nature of the AgNPs-Cp system was confirmed by Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM) etc. The AgNPs-Cp system size was found to be in the range of 30-40 nm. To monitor the kinetics of drug release from the surface of nanoparticles, the release of Cp was carried out by careful dialysis keeping AgNPs-Cp system inside the dialysis bag at pH 7.4 over time. The drug release was almost complete after 30 hrs. During the drug delivery process, to understand the AgNPs-Cp system in a better way, the sincere theoretical investigation is been performed employing Density Functional Theory. Electronic charge transfer, electron density, binding energy as well as thermodynamic properties like enthalpy, entropy, Gibbs free energy etc. has been predicted. The electronic and thermodynamic properties, governed by the AgNPs-Cp interactions, indicate that the formation of AgNPs-Cp system is exothermic i.e. thermodynamically favorable process. The binding energy and charge transfer analysis implies the optimum stability of the AgNPs-Cp system. Thus, the synthesized Cp-Ag nanoparticles can be effectively used for biological purposes due to its environmentally benign routes of synthesis procedures, which is clean, biocompatible, non-toxic, safe, cost-effective, sustainable and eco-friendly. The Cp-AgNPs as biomaterials can be successfully used for drug delivery procedures due to slow release of drug from nanoparticles over a considerable period of time. The kinetics of the drug release show that this drug-nanoparticle assembly can be effectively used as potential tools for therapeutic applications. The ease of synthetic procedure, lack of possible chemical toxicity and their biological activity along with excellent application as drug delivery agent will open up vista of using nanoparticles as effective and successful drug delivery agent to be used in modern days.

Keywords: silver nanoparticles, ciprofloxacin, density functional theory, drug delivery

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Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

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Authors: P. Aarumugam, N. Krishnamoorthy, K. Gunasekaran

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The mosquitoes with loss of minimum three legs especially the hind legs have the negative impact on the survival hood of mosquitoes. Three days old unfed adult female laboratory strain was selected in each generation against sublethal dosages (0.004%, 0.005%, 0.007% and 0.01%) of deltamethrin upto 40 generations. Impregnated papers with acetone were used for control. Every fourth generation, survived mosquitoes were observed for functional mortality. Hind legs lost were significantly (P< 0.05) higher in treated than the controls up to generation 24, thereafter no significant lost. In contrary, no significant forelegs lost among exposed mosquitoes. Middle legs lost were also not significant in the exposed mosquitoes except first generation (F1). The field strain (Chennai) did not show any significant loss of legs (fore or mid or hind) compared to the control. The selection pressure on mosquito population influences strong natural selection to develop various adaptive mechanisms.

Keywords: Anopheles stephensi, deltamethrin, functional mortality, synthetic pyrethroids

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Authors: Ira Irawati, Muhammad Rangga Sururi

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The expansion of built-up areas in many cities, particularly, as the consequences of urbanization process, is a common phenomenon in our contemporary world. As happened in many cities in developing world, this horizontal expansion let only a handful size of the area left for green open spaces, creating an extreme unbalance between built-up and green spaces. Combined with the high density and variety of human activities with its transportation modes; a process of urban heat island will occur, resulting in an increase in air temperature. This is one of the indicators of decreasing of the quality of urban microclimate. This paper will explore the effect of several variables of built-up areas and open spaces to the increase of air temperature using multiple linear regression analysis. We selected 11 zones within the radius of 1 km in Inner Bandung city center, and each zones measured within 300 m radius to represent the variety of land use, as well as the composition of buildings and green open spaces. By using a quantitative method which is multiple linear regression analysis, six dependent variables which are a) tree density-x1, b) shade level of tree-x2, c) surface area of buildings’ side which are facing west and east-x3, d) surface area of building side material-x4, e) surface area of pathway material, and f) numbers of motorized vehicles-x6; are calculated to find those influence to the air temperature as an independent variable-y. Finally, the relationship between those variables shows in this equation: y = 30.316 - 3.689 X1 – 6.563 X2 + 0.002 X3 – 2,517E6 X4 + 1.919E-9 X5 + 1.952E-4 X6. It shows that the existence of vegetation has a great impact on lowering temperature. In another way around, built up the area and motorized vehicles would increase the temperature. However, one component of built up area, the surface area of buildings’ sides which are facing west and east, has different result due to the building material is classified in low-middle heat capacity.

Keywords: built-up area, microclimate, vehicles, urban heat island, vegetation

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Authors: Wei Quan, Liu Chao, Mohammed N. Afsar

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The dielectric properties and ionic conductivity of novel "ceramic state" polymer electrolytes for high capacity lithium battery are characterized by radio-frequency and Microwave methods in two broad frequency ranges from 50 Hz to 20 KHz and 4 GHz to 40 GHz. This innovative solid polymer electrolyte which is highly ionic conductive (10-3 S/cm at room temperature) from -40 oC to +150 oC and can be used in any battery application. Such polymer exhibits properties more like a ceramic rather than polymer. The various applied measurement methods produced accurate dielectric results for comprehensive analysis of electrochemical properties and ion transportation mechanism of this newly invented polymer electrolyte. Two techniques and instruments employing air gap measurement by capacitance bridge and inwave guide measurement by vector network analyzer are applied to measure the complex dielectric spectra. The complex dielectric spectra are used to determine the complex alternating current electrical conductivity and thus the ionic conductivity.

Keywords: polymer electrolyte, dielectric permittivity, lithium battery, ionic relaxation, microwave measurement

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Authors: Farhia Hassan Mohamed

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This study examined the macroeconomic factors that affect the inflation Rate in Somalia using quarterly time series data from 1991q1 to 2017q4 retired from World Development Indicators and SESRIC. It employed the vector error correction model (VECM) and Granger Causality method to measure the long-run and short-run causality of the GDP, inflation exchange rate, and unemployment. The study confirmed that there is one cointegration equation between GDP, exchange rate, inflation, and unemployment in Somalia. However, the VECM model's result indicates a long-run relationship among variables. The VEC Granger causality/Block Exogeneity Wald test result confirmed that all covariates are statistically significant at 5% and are Granger's cause of inflation in the short term. Finally, the impulse response result showed that inflation responds negatively to the shocks from the exchange rate and unemployment rate and positively to GDP and itself. Drawing from the empirical findings, the study makes several policy recommendations for both the monetary and Government sides.

Keywords: CPI, OP, exchange rate, inflation ADF, Johansen, PP, VECM, impulse, ECT

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Authors: Mindaye Teshome, Nesibu Yahya, Carlos Moreira Miquelino Eleto Torres, Pedro Manuel Villaa, Mehari Alebachew

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Arbagugu forest is one of the remnant dry Afromontane forests under severe anthropogenic disturbances in central Ethiopia. Despite this fact, up-to-date information is lacking about the status of the forest and its role in climate change mitigation. In this study, we evaluated the woody species composition, structure, biomass, and carbon stock in this forest. We employed a systematic random sampling design and established fifty-three sample plots (20 × 100 m) to collect the vegetation data. A total of 37 woody species belonging to 25 families were recorded. The density of seedlings, saplings, and matured trees were 1174, 101, and 84 stems ha-1, respectively. The total basal area of trees with DBH (diameter at breast height) ≥ 2 cm was 21.3 m2 ha-1. The characteristic trees of dry Afromontane Forest such as Podocarpus falcatus, Juniperus procera, and Olea europaea subsp. cuspidata exhibited a fair regeneration status. On the contrary, the least abundant species Lepidotrichilia volkensii, Canthium oligocarpum, Dovyalis verrucosa, Calpurnia aurea, and Maesa lanceolata exhibited good regeneration status. Some tree species such as Polyscias fulva, Schefflera abyssinica, Erythrina brucei, and Apodytes dimidiata lack regeneration. The total carbon stored in the forest ranged between 6.3 Mg C ha-1 and 835.6 Mg C ha-1. This value is equivalent to 639.6 Mg C ha-1. The forest had a very low number of woody species composition and diversity. The regeneration study also revealed that a significant number of tree species had unsatisfactory regeneration status. Besides, the forest had a lower carbon stock density compared with other dry Afromontane forests. This implies the urgent need for forest conservation and restoration activities by the local government, conservation practitioners, and other concerned bodies to maintain the forest and sustain the various ecosystem goods and services provided by the Arbagugu forest.

Keywords: aboveground biomass, forest regeneration, climate change, biodiversity conservation, restoration

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Authors: Ross Calvert, Colin Whittaker, Alison Raby, Alistair G. L. Borthwick, Ton S. van den Bremer

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Large concentrations of plastic have polluted the seas in the last half century, with harmful effects on marine wildlife and potentially to human health. Plastic pollution will have lasting effects because it is expected to take hundreds or thousands of years for plastic to decay in the ocean. The question arises how waves transport plastic in the ocean. The predominant motion induced by waves creates ellipsoid orbits. However, these orbits do not close, resulting in a drift. This is defined as Stokes drift. If a particle is infinitesimally small and the same density as water, it will behave exactly as the water does, i.e., as a purely Lagrangian tracer. However, as the particle grows in size or changes density, it will behave differently. The particle will then have its own inertia, the fluid will exert drag on the particle, because there is relative velocity, and it will rise or sink depending on the density and whether it is on the free surface. Previously, plastic pollution has all been considered to be purely Lagrangian. However, the steepness of waves in the ocean is small, normally about α = k₀a = 0.1 (where k₀ is the wavenumber and a is the wave amplitude), this means that the mean drift flows are of the order of ten times smaller than the oscillatory velocities (Stokes drift is proportional to steepness squared, whilst the oscillatory velocities are proportional to the steepness). Thus, the particle motion must have the forces of the full motion, oscillatory and mean flow, as well as a dynamic buoyancy term to account for the free surface, to determine whether inertia is important. To track the motion of a floating inertial particle under wave action requires the fluid velocities, which form the forcing, and the full equations of motion of a particle to be solved. Starting with the equation of motion of a sphere in unsteady flow with viscous drag. Terms can added then be added to the equation of motion to better model floating plastic: a dynamic buoyancy to model a particle floating on the free surface, quadratic drag for larger particles and a slope sliding term. Using perturbation methods to order the equation of motion into sequentially solvable parts allows a parametric equation for the transport of inertial finite-sized floating particles to be derived. This parametric equation can then be validated using numerical simulations of the equation of motion and flume experiments. This paper presents a parametric equation for the transport of inertial floating finite-size particles by ocean waves. The equation shows an increase in Stokes drift for larger, less dense particles. The equation has been validated using numerical solutions of the equation of motion and laboratory flume experiments. The difference in the particle transport equation and a purely Lagrangian tracer is illustrated using worlds maps of the induced transport. This parametric transport equation would allow ocean-scale numerical models to include inertial effects of floating plastic when predicting or tracing the transport of pollutants.

Keywords: perturbation methods, plastic pollution transport, Stokes drift, wave flume experiments, wave-induced mean flow

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Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

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In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

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Authors: Aliseydi Bozkurt

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Objectives: Benign prostatic hyperplasia (BPH) is the most common benign disease, and prostate cancer (PC) is malign disease of the prostate gland. Transrectal ultrasound-guided biopsy (TRUS-bx) is one of the most important diagnostic tools in PC diagnosis. Identifying men at increased risk for having a biopsy detectable prostate cancer should consider prostate specific antigen density (PSAD), f/t PSA Ratio, an estimate of prostate volume. Method: We retrospectively studied 269 patients who had a prostate specific antigen (PSA) score of 4 or who had suspected rectal examination at any PSA level and received TRUS-bx between January 2015 and June 2018 in our clinic. TRUS-bx was received by 12 experienced urologists with 12 quadrants. Prostate volume was calculated prior to biopsy together with TRUS. Patients were classified as malignant and benign at the end of pathology. Age, PSA value, prostate volume in transrectal ultrasonography, corpuscle biopsy, biopsy pathology result, the number of cancer core and Gleason score were evaluated in the study. The success rates of PV, PSAD, and f/tPSA were compared in all patients and those with PSA 2.5-10 ng/mL and 10.1-30 ng/mL tp foresee prostate cancer. Result: In the present study, in patients with PSA 2.5-10 ng/ml, PV cut-off value was 43,5 mL (n=42 < 43,5 mL and n=102 > 43,5 mL) while in those with PSA 10.1-30 ng/mL prostate volüme (PV) cut-off value was found 61,5 mL (n=31 < 61,5 mL and n=36 > 61,5 mL). Total PSA values in the group with PSA 2.5-10 ng/ml were found lower (6.0 ± 1.3 vs 6.7 ± 1.7) than that with PV < 43,5 mL, this value was nearly significant (p=0,043). In the group with PSA value 10.1-30 ng/mL, no significant difference was found (p=0,117) in terms of total PSA values between the group with PV < 61,5 mL and that with PV > 61,5 mL. In the group with PSA 2.5-10 ng/ml, in patients with PV < 43,5 mL, f/t PSA value was found significantly lower compared to the group with PV > 43,5 mL (0.21 ± 0.09 vs 0.26 ± 0.09 p < 0.001 ). Similarly, in the group with PSA value of 10.1-30 ng/mL, f/t PSA value was found significantly lower in patients with PV < 61,5 mL (0.16 ± 0.08 vs 0.23 ± 0.10 p=0,003). In the group with PSA 2.5-10 ng/ml, PSAD value in patients with PV < 43,5 mL was found significantly higher compared to those with PV > 43,5 mL (0.17 ± 0.06 vs 0.10 ± 0.03 p < 0.001). Similarly, in the group with PSA value 10.1-30 ng/mL PSAD value was found significantly higher in patients with PV < 61,5 mL (0.47 ± 0.23 vs 0.17 ± 0.08 p < 0.001 ). The biopsy results suggest that in the group with PSA 2.5-10 ng/ml, in 29 of the patients with PV < 43,5 mL (69%) cancer was detected while in 13 patients (31%) no cancer was detected. While in 19 patients with PV > 43,5 mL (18,6%) cancer was found, in 83 patients (81,4%) no cancer was detected (p < 0.001). In the group with PSA value 10.1-30 ng/mL, in 21 patients with PV < 61,5 mL (67.7%) cancer was observed while only in10 patients (32.3%) no cancer was seen. In 5 patients with PV > 61,5 mL (13.9%) cancer was found while in 31 patients (86.1%) no cancer was observed (p < 0.001). Conclusions: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider PSA, f/t PSA Ratio, an estimate of prostate volume. Prostate volume in PC was found lower.

Keywords: prostate cancer, prostate volume, prostate specific antigen, free/total PSA ratio

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Authors: Elena Pello, Martin Bobak, Yuri Nikitin

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In current issue we evaluated integration of magnesium with lipids; the attractive findings were obtained in men and women; the crucial ties of magnesium with total cholesterol in hypertensive men, with total cholesterol in concordance with low-density lipoprotein cholesterol in hypertensive women were disclosed; unanswered questions were trapped, difficulties were surmounted, and magnesium deficiency perseverance in pathogenesis of cardiovascular disease development was expressed; nutrients as well as risk factors may contribute to cardiovascular complications.

Keywords: dietary, magnesium, hypertension, lipids

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Authors: Mohanapriya Subramanian, V. Raj

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Direct methanol fuel cells (DMFCs) are considered to be one of the most promising candidates for portable and stationary applications in the view of their advantages such as high energy density, easy manipulation, high efficiency and they operate with liquid fuel which could be used without requiring any fuel-processing units. Electrolyte membrane of DMFC plays a key role as a proton conductor as well as a separator between electrodes. Increasing concern over environmental protection, biopolymers gain tremendous interest owing to their eco-friendly bio-degradable nature. Pectin is a natural anionic polysaccharide which plays an essential part in regulating mechanical behavior of plant cell wall and it is extracted from outer cells of most of the plants. The aim of this study is to develop and demonstrate pectin based polymer composite membranes as methanol impermeable polymer electrolyte membranes for DMFCs. Pectin based nanocomposites membranes are prepared by solution-casting technique wherein pectin is blended with chitosan followed by the addition of optimal amount of sulphonic acid modified Titanium dioxide nanoparticle (S-TiO2). Nanocomposite membranes are characterized by Fourier Transform-Infra Red spectroscopy, Scanning electron microscopy, and Energy dispersive spectroscopy analyses. Proton conductivity and methanol permeability are determined into order to evaluate their suitability for DMFC application. Pectin-chitosan blends endow with a flexible polymeric network which is appropriate to disperse rigid S-TiO2 nanoparticles. Resulting nanocomposite membranes possess adequate thermo-mechanical stabilities as well as high charge-density per unit volume. Pectin-chitosan natural polymeric nanocomposite comprising optimal S-TiO2 exhibits good electrochemical selectivity and therefore desirable for DMFC application.

Keywords: biopolymers, fuel cells, nanocomposite, methanol crossover

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Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, REVIVE team

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The environment of the mosquitoes complex Culex pipiens sl. in Portugal mainland is evaluated based in its abundance, using a data set georeferenced, collected during seven years (2006-2012) from May to October. The suitability of the different regions can be delineated using the relative abundance areas; the suitablility index is directly proportional to disease transmission risk and allows focusing mitigation measures in order to avoid outbreaks of vector-borne diseases. The interest in the Culex pipiens complex is justified by its medical importance: the females bite all warm-blooded vertebrates and are involved in the circulation of several arbovirus of concern to human health, like West Nile virus, iridoviruses, rheoviruses and parvoviruses. The abundance of Culex pipiens mosquitoes were documented systematically all over the territory by the local health services, in a long duration program running since 2006. The environmental factors used to characterize the vector habitat are land use/land cover, distance to cartographed water bodies, altitude and latitude. Focus will be on the mosquito females, which gonotrophic cycle mate-bloodmeal-oviposition is responsible for the virus transmission; its abundance is the key for the planning of non-aggressive prophylactic countermeasures that may eradicate the transmission risk and simultaneously avoid chemical ambient degradation. Meteorological parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures) and daily total rainfall were gathered from the weather stations network for the same dates and crossed with the standardized females’ abundance in a geographic information system (GIS). Mean capture and percentage of above average captures related to each variable are used as criteria to compute a threshold for each meteorological parameter; the difference of the mean capture above/below the threshold was statistically assessed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the meaningful thresholds for each parameter. The intersection of the maps of all the parameters obtained for each month show the evolution of the suitable meteorological conditions through the mosquito season, considered as May to October, although the first and last month are less relevant. In parallel, mean and above average captures were related to the physiographic parameters – the land use/land cover classes most relevant in each month, the altitudes preferred and the most frequent distance to water bodies, a factor closely related with the mosquito biology. The maps produced with these results were crossed with the meteorological maps previously segmented, in order to get an index of suitability for the complex Culex pipiens evaluated all over the country, and its evolution from the beginning to the end of the mosquitoes season.

Keywords: suitability index, Culex pipiens, habitat evolution, GIS model

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Authors: B. K. Kanungo, Monika Thakur, Minati Baral

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8-hydroxyquinoline, (8HQ), experiences a renaissance due to its utility as a building block in metallosupramolecular chemistry and its versatile use of its derivatives in various fields of analytical chemistry, materials science, and pharmaceutics. It forms stable complexes with a variety of metal ions. Assembly of more than one such unit to form a polydentate chelator enhances its coordinating ability and the related properties due to the chelate effect resulting in high stability constant. Keeping in view the above, a nonadentate chelator N-[3,5-bis(8-hydroxyquinoline-2-amido)cyclohexyl]-8-hydroxyquinoline-2-carboxamide, (TACH2OX), containing a central cis,cis-1,3,5-triaminocyclohexane appended to three 8-hydroxyquinoline at 2-position through amide linkage is developed, and its solution thermodynamics, photophysical and Density Functional Theory (DFT) studies were undertaken. The synthesis of TACH2OX was carried out by condensation of cis,cis-1,3,5-triaminocyclohexane, (TACH) with 8‐hydroxyquinoline‐2‐carboxylic acid. The brown colored solid has been fully characterized through melting point, infrared, nuclear magnetic resonance, electrospray ionization mass and electronic spectroscopy. In solution, TACH2OX forms protonated complexes below pH 3.4, which consecutively deprotonates to generate trinegative ion with the rise of pH. Nine protonation constants for the ligand were obtained that ranges between 2.26 to 7.28. The interaction of the chelator with two trivalent metal ion Fe3+ and Al3+ were studied in aqueous solution at 298 K. The metal-ligand formation constants (ML) obtained by potentiometric and spectrophotometric method agree with each other. The protonated and hydrolyzed species were also detected in the system. The in-silico studies of the ligand, as well as the complexes including their protonated and deprotonated species assessed by density functional theory technique, gave an accurate correlation with each observed properties such as the protonation constants, stability constants, infra-red, nmr, electronic absorption and emission spectral bands. The nature of electronic and emission spectral bands in terms of number and type were ascertained from time-dependent density functional theory study and the natural transition orbitals (NTO). The global reactivity indices parameters were used for comparison of the reactivity of the ligand and the complex molecules. The natural bonding orbital (NBO) analysis could successfully describe the structure and bonding of the metal-ligand complexes specifying the percentage of contribution in atomic orbitals in the creation of molecular orbitals. The obtained high value of metal-ligand formation constants indicates that the newly synthesized chelator is a very powerful synthetic chelator. The minimum energy molecular modeling structure of the ligand suggests that the ligand, TACH2OX, in a tripodal fashion firmly coordinates to the metal ion as hexa-coordinated chelate displaying distorted octahedral geometry by binding through three sets of N, O- donor atoms, present in each pendant arm of the central tris-cyclohexaneamine tripod.

Keywords: complexes, DFT, formation constant, TACH2OX

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Authors: Yuanjin Liu

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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

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Authors: Yanghui Xu, Qin Ou, Xintu Wang, Feng Hou, Peng Li, Jan Peter van der Hoek, Gang Liu

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The level and removal of microplastics (MPs) in wastewater treatment plants (WWTPs) has been well evaluated by the particle number, while the mass concentration of MPs and especially nanoplastics (NPs) remains unclear. In this study, microfiltration, ultrafiltration and hydrogen peroxide digestion were used to extract MPs and NPs with different size ranges (0.01−1, 1−50, and 50−1000 μm) across the whole treatment schemes in two WWTPs. By identifying specific pyrolysis products, pyrolysis gas chromatography−mass spectrometry were used to quantify their mass concentrations of selected six types of polymers (i.e., polymethyl methacrylate (PMMA), polypropylene (PP), polystyrene (PS), polyethylene (PE), polyethylene terephthalate (PET), and polyamide (PA)). The mass concentrations of total MPs and NPs decreased from 26.23 and 11.28 μg/L in the influent to 1.75 and 0.71 μg/L in the effluent, with removal rates of 93.3 and 93.7% in plants A and B, respectively. Among them, PP, PET and PE were the dominant polymer types in wastewater, while PMMA, PS and PA only accounted for a small part. The mass concentrations of NPs (0.01−1 μm) were much lower than those of MPs (>1 μm), accounting for 12.0−17.9 and 5.6− 19.5% of the total MPs and NPs, respectively. Notably, the removal efficiency differed with the polymer type and size range. The low-density MPs (e.g., PP and PE) had lower removal efficiency than high-density PET in both plants. Since particles with smaller size could pass the tertiary sand filter or membrane filter more easily, the removal efficiency of NPs was lower than that of MPs with larger particle size. Based on annual wastewater effluent discharge, it is estimated that about 0.321 and 0.052 tons of MPs and NPs were released into the river each year. Overall, this study investigated the mass concentration of MPs and NPs with a wide size range of 0.01−1000 μm in wastewater, which provided valuable information regarding the pollution level and distribution characteristics of MPs, especially NPs, in WWTPs. However, there are limitations and uncertainties in the current study, especially regarding the sample collection and MP/NP detection. The used plastic items (e.g., sampling buckets, ultrafiltration membranes, centrifugal tubes, and pipette tips) may introduce potential contamination. Additionally, the proposed method caused loss of MPs, especially NPs, which can lead to underestimation of MPs/NPs. Further studies are recommended to address these challenges about MPs/NPs in wastewater.

Keywords: microplastics, nanoplastics, mass concentration, WWTPs, Py-GC/MS

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Eric Beyegue, Boris Azantza, Judith Laure Ngondi, Julius E. Oben

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Background: Insulin resistance (IR) and oxidative stress are associated with obesity, diabetes mellitus, and other cardio metabolic disorders. The aim of this study was to investigate the effect of Coula edulis extracts (CEE) on insulin resistance and oxidative stress markers in high-fat/high sucrose diet-induced insulin resistance in rats. Materials and Methods: Thirty male rats were divided into 6 groups of 5 rats each fed, received daily oral administration of CE extracts for 8 weeks as follows: Group 1 or negative control group, fed with standard diet (SD); Group 2 fed with high-fat/high sucrose diet (HFHS) only; Group3 fed with HFHS + CEAq 200; Group 4 fed with HFHS + CEAq 400; Group 5 fed with HFHS + CEEt 200; Group 6 fed with HFHS + CEEt 400. At the end of the experiment (8 weeks), animals were sacrificed plasma lipid profile, glucose, insulin, oxidative marker and digestive enzyme activities were measured. The homeostasis model assessment for insulin resistance (HOMA-IR) was determined. Results: Feedings with HFHS significantly (p < 0.01) induced plasma hyperglycaemia, hyperinsulinaemia, increased triglyceride, total cholesterol, and low-density lipoprotein levels, decreased high-density lipoprotein levels, alterations of α amylase, and glucose-6-phosphatase activities, and oxidative stress. Daily oral administration with CEE for eight weeks after insulin resistance induction had a hypolipidaemic action, antioxidative activities and modulated metabolic markers. Ethanolic extract at the higher dose had the best effect on body weight gain and insulin resistance, whereas aqueous extract showed the better activity on hyperlipidemia. Conclusion: These results suggest that CEAq and CEEt at 400mg/kg are promising complementary supplements that can be used to protect better from metabolic disorders associated with HFHS.

Keywords: Coula edulis Baill, high-fat / high sucrose diet, insulin resistance, oxidative stress

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Authors: J. K. Chawla, S. K. Jain, M. K. Mishra

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Ion-acoustic double layers have been studied in magnetized plasma. The modified Korteweg-de Vries (m-KdV) equation using reductive perturbation method is derived. It is found that for the selected set of parameters, the system supports rarefactive double layers depending upon the value of nonthermal parameters. It is also found that the magnetization affects only the width of the double layer. For a given set of parameter values, increases in the magnetization and the obliqueness angle (θ) between wave vector and magnetic field, affect the width of the double layers, however the amplitude of the double layers have no effect. An increase in the values of nonthermal parameter decreases the amplitude of the rarefactive double layer. The effect of the ion temperature ratio on the amplitude and width of the double layers are also discussed in detail.

Keywords: ion-acoustic double layers, magnetized electronegative plasma, reductive perturbation method, the modified Korteweg-de Vries (KdV) equation

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

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Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Abidullah, Basharat Hussain, Jong Seok Kim

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Polymer electrolyte membrane fuel cell (PEMFC) is an electrochemical cell, which undergoes an oxygen reduction reaction to produce electrical energy. Platinum (Pt) metal has been used as a catalyst since its inception, but expensiveness is the major obstacle in the commercialization of fuel cells. Herein a non-precious group metal (NPGM) is employed instead of Pt to reduce the cost of PEMFCs. Manganese dioxide impregnated carbon nanotubes (MnO₂-CNTs composite) is a catalyst having excellent electrochemical properties and offers a better alternative to the Platinum-based PEMFC. The catalyst is synthesized by impregnating the transition metal on large surface carbonaceous CNTs by hydrothermal synthesis techniques. To enhance the catalytic activity and increase the volumetric current density, the sample was pyrolyzed at 800ᵒC under a nitrogen atmosphere. During pyrolysis, the nitrogen was doped in the framework of CNTs. Then the material was treated with acid for removing the unreacted metals and adding oxygen functional group to the CNT framework. This process ameliorates the catalytic activity of the manganese-based catalyst. The catalyst has been characterized by scanning electron microscope (SEM), X-ray diffraction (XRD), and the catalyst activity has been examined by rotating disc electrode (RDE) experiment. The catalyst was strong enough to withstand an austere alkaline environment in experimental conditions and had a high electrocatalytic activity for oxygen reduction reaction (ORR). Linear Sweep Voltammetry (LSV) depicts an excellent current density of -4.0 mA/cm² and an overpotential of -0.3V vs. standard calomel electrode (SCE) in 0.1M KOH electrolyte. Rotating disk electrode (RDE) was conducted at 400, 800, 1200, and 1600 rpm. The catalyst exhibited a higher methanol tolerance and long term durability with respect to commercial Pt/C. The results for MnO₂-CNT show that the low-cost catalyst will supplant the expensive Pt/C catalyst in the fuel cell.

Keywords: carbon nanotubes, methanol fuel cell, oxygen reduction reaction, MnO₂-CNTs

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Authors: Raimoana Frogier, Luc Girard, Pierre Bauduin, Diane Rebiscoul, Olivier Diat

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Nano-ions (NIs) are ionic species or clusters of nanometric size. Their low charge density and the delocalization of their charges give special properties to some of NIs belonging to chemical classes of polyoxometalates (POMs) or boron clusters. They have the particularity of interacting non-covalently with neutral hydrated surface or interfaces such as assemblies of surface-active molecules (micelles, vesicles, lyotropic liquid crystals), foam bubbles or emulsion droplets. This makes possible to classify those NIs in the Hofmeister series as superchaotropic ions. The mechanism of adsorption is complex, linked to the simultaneous dehydration of the ion and the molecule or supramolecular assembly with which it can interact, all with an enthalpic gain on the free energy of the system. This interaction process is reversible and is sufficiently pronounced to induce changes in molecular and supramolecular shape or conformation, phase transitions in the liquid phase, all at sub-millimolar ionic concentrations. This new property of some NIs opens up new possibilities for applications in fields as varied as biochemistry for solubilization, recovery of metals of interest by foams in the form of NIs... In order to better understand the physico-chemical mechanisms at the origin of this interaction, we use silicon wafers functionalized by non-ionic oligomers (polyethylene glycol chains or PEG) to study in situ by X-ray reflectivity this interaction of NIs with the grafted chains. This study carried out at ESRF (European Synchrotron Radiation Facility) and has shown that the adsorption of the NIs, such as POMs, has a very fast kinetics. Moreover the distribution of the NIs in the grafted PEG chain layer was quantify. These results are very encouraging and confirm what has been observed on soft interfaces such as micelles or foams. The possibility to play on the density, length and chemical nature of the grafted chains makes this system an ideal tool to provide kinetic and thermodynamic information to decipher the complex mechanisms at the origin of this adsorption.

Keywords: adsorption, nano-ions, solid-liquid interface, superchaotropicity

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Authors: Shripad Kulkarni

Abstract:

Plant disease is an impairment of the normal state of a plant that interrupts or modifies its vital functions. Disease occurs on different parts of plants and cause heavy losses. Diagnosis of Problem is very important before planning any management practice and this can be done based on appearance of the crop, examination of the root and examination of the soil. There are various types of diseases such as biotic (transmissible) which accounts for ~30% whereas , abiotic (not transmissible) diseases are the major one with ~70% incidence. Plant diseases caused by different groups of organism’s belonging fungi, bacteria, viruses, nematodes and few others have remained important in causing significant losses in different crops indicating the urgent need of their integrated management. Various factors favor disease development and different steps and methods are involved in management of diseases under protected condition. Management of diseases through botanicals and bioagents by modifying root and aerial environment, vector management along with care to be taken while managing the disease are analysed.

Keywords: organic production system, diseases, bioagents and polyhouse, agriculture

Procedia PDF Downloads 406