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1
Hossain, SK Safdar, Bamidele Victor Ayodele, and Abdulrahman Almithn. "Predictive Modeling of Bioenergy Production from Fountain Grass Using Gaussian Process Regression: Effect of Kernel Functions." Energies 15, no. 15 (July 31, 2022): 5570. http://dx.doi.org/10.3390/en15155570.
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Experimental studies have shown that bioethanol production from biomass sources has been reported to be influenced by several process parameters. It is not entirely known, however, how the interaction of these factors affects the concentration of bioethanol production. In this study, the use of Gaussian Process Regression (GPR) in predictive modeling of bioethanol production from fountain grass has been investigated. Parametric analysis showing the interaction effect of time, pH, temperature, and yeast extract on the bioethanol production was examined. The effect of kernel functions on the performance of the GPR in modeling the prediction of bioenergy output was also examined. The study shows that the kernel function, namely, rotational quadratic (RQGPR), squared exponential (SEGPR), Matern 5/2 (MGPR), exponential (EGPR), and the optimizable (Opt.GPR.), had varying effects on the performance of the GPR. Coefficients of determination (R2) of 0.648, 0.670, 0.667, 0.762, and 0.993 were obtained for the RQGPR, SEGPR, MGPR, EGPR, OptGPR, respectively. The OptGPR with R2 of 0.993 and RMSE of 45.13 displayed the best performance. The input parameters analysis revealed that the pH of the fermentation medium significantly influences bioethanol production. A proper understanding of how the various process variables affect bioethanol production will help in the real-time optimization of the process in the eventuality of scale-up.
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Ekanayake, Piyal, Lasini Wickramasinghe, and Jeevani W. Jayasinghe. "Development of Crop-Weather Models Using Gaussian Process Regression for the Prediction of Paddy Yield in Sri Lanka." International Journal of Intelligent Systems and Applications 14, no. 4 (August 8, 2022): 52–665. http://dx.doi.org/10.5815/ijisa.2022.04.05.
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This research introduces machine learning models using the Gaussian Process Regression (GPR) depicting the association between paddy yield and weather in Sri Lanka. All major regions in the island with most contribution to the total paddy production were considered in this research. The climatic factors of rainfall, relative humidity, minimum temperature, maximum temperature, average wind speed, evaporation, and sunshine hours were considered as input (independent) variables, while the paddy yield was the output (dependent) variable. The collinearity within each pair of independent and dependent variables was determined using Spearman’s and Pearson’s correlation coefficients. Data sets corresponding to the two main annual paddy cultivation seasons since 2009 were trained in MATLAB to develop crop-weather models. The most appropriate Kernel function was chosen from among four types of Kernels viz. Rational Quadratic, Exponential, Squared Exponential, and Matern 5/2 based on their degree of coherence in modeling. This approach exploits the full potential of GPR in developing highly accurate crop-weather models. The performance of the crop-weather models was measured by the Correlation Coefficient, Mean Absolute Percentage Error, Mean Squared Error, Root Mean Squared Error Ratio, Nash Number and the BIAS. All the GPR-based models proposed in this paper are highly accurate in terms of the aforementioned evaluation metrics. Accordingly, when the climatic data are known or projected, the paddy yield and thereby the harvest of Sri Lanka can be predicted precisely by using the proposed crop-weather models.
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Adebayo, Segun, Francis O. Aweda, Isaac A. Ojedokun, and James A. Agbolade. "Meteorological data prediction over selected stations in Sub-Sahara Africa: Leveraging on Machine Learning Algorithm." Ruhuna Journal of Science 13, no. 2 (December 31, 2022): 129–40. http://dx.doi.org/10.4038/rjs.v13i2.120.
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This study investigated selected meteorological data prediction leveraging on a Machine Learning Algorithm Approach over five selected stations in Nigeria. The algorithm of Machine Learning was explored using weather parameters such as temperature, wind speed, wind direction and relative humidity to predict the rainfall rate. In the results, five Gaussian models (i.e., Rational Quadratic, Squared Exponential, Matern 5/2, Exponential and Optimized GPR) revealed different Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE) with prediction speeds ranging from 15000 to 26000 and the training time included 7.936, 1.8923, 2.3701, 3.267 and 282.19, respectively. The predicted response as against the true response for the two models shows a linear graph passing through the origin which confirmed a perfect regression model, where all the points lie on a diagonal line. Therefore, the relationship between MSE, MAE and RMSE for different models revealed that the optimized GPR has a better performance as compared to others. More so, visualizing the relationship between the output variable (rainfall) and each input variable reveals that some input variables (relative humidity, rainfall, pressure, wind speed and direction) have a strong correlation with the output variable (rainfall), with others having a noisy relationship which is not very clear.
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Pustokhina, Inna, Amir Seraj, Hafsan Hafsan, Seyed Mojtaba Mostafavi, and S. M. Alizadeh. "Developing a Robust Model Based on the Gaussian Process Regression Approach to Predict Biodiesel Properties." International Journal of Chemical Engineering 2021 (June 4, 2021): 1–12. http://dx.doi.org/10.1155/2021/5650499.
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Biodiesel is assumed a renewable and environmentally friendly fuel that possesses the potential to substitute petroleum diesel. The basic purpose of the present study is to design a precise algorithm based on Gaussian Process Regression (GPR) model with several kernel functions, i.e., Rational Quadratic, Squared Exponential, Matern, and Exponential, to estimate biodiesel properties. These properties include kinematic viscosity (KV), pour point (PP), iodine value (IV), and cloud point (CP) as a function of fatty acid composition. In order to develop this model, some variables are assumed, such as molecular weight, carbon number, double bond numbers, monounsaturated fatty acids, polyunsaturated fatty acid, weight percent of saturated acid, and temperature. The performance and efficiency of the GPR model are measured through several statistical criteria and the results are summarized in root mean square error (RMSE) and coefficients of determination ( R 2 ). R 2 and RMSE are sorted as 0.992 & 0.15697, 0.998 & 0.96580, 0.966 & 1.38659, and 0.968 & 1.56068 for four properties such as KV, IV, CP, and PP, respectively. It is worth to mention this point that the kernel function Squared Exponential shows a great performance for IV and PP and kernel functions Exponential and Matern indicate appropriate efficiency for CP and KV properties, respectively. On the other hand, the results of the offered GPR models are compared with those of the previous models, LSSVM-PSO and ANFIS. The outcomes proved the superiority of this model over two former models in point of estimating the biodiesel properties.
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Wang, Shicheng, Wei Li, and Issam Alruyemi. "On the Investigation of Effective Factors on Higher Heating Value of Biodiesel: Robust Modeling and Data Assessments." BioMed Research International 2021 (July 12, 2021): 1–9. http://dx.doi.org/10.1155/2021/4814888.
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Higher heating value (HHV) is one of the properties of biomass fuels which is essential in investigating their special characteristics and potentialities. In this paper, various techniques based on Gaussian process regression (GPR) were utilized to assess this value for biomass fuels, including several kernel functions, i.e., exponential, Matern, rational quadratic, and squared exponential. An extensive databank was collected from literature. The findings were compared, and the results indicated that Exponential-based model was more accurate, with the coefficient of regression ( R 2 ) of 0.961 and the mean relative error (% MRE) of 3.11 for total data. Compared to former models presented by previous researchers, the model proposed in this study showed a higher ability to predict output values. With various analyses, it can be concluded that the proposed method has a high rate of efficiency in assessing the HHV of various biomass.
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Elbeltagi, Ahmed, Nikul Kumari, Jaydeo Dharpure, Ali Mokhtar, Karam Alsafadi, Manish Kumar, Behrouz Mehdinejadiani, et al. "Prediction of Combined Terrestrial Evapotranspiration Index (CTEI) over Large River Basin Based on Machine Learning Approaches." Water 13, no. 4 (February 20, 2021): 547. http://dx.doi.org/10.3390/w13040547.
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Drought is a fundamental physical feature of the climate pattern worldwide. Over the past few decades, a natural disaster has accelerated its occurrence, which has significantly impacted agricultural systems, economies, environments, water resources, and supplies. Therefore, it is essential to develop new techniques that enable comprehensive determination and observations of droughts over large areas with satisfactory spatial and temporal resolution. This study modeled a new drought index called the Combined Terrestrial Evapotranspiration Index (CTEI), developed in the Ganga river basin. For this, five Machine Learning (ML) techniques, derived from artificial intelligence theories, were applied: the Support Vector Machine (SVM) algorithm, decision trees, Matern 5/2 Gaussian process regression, boosted trees, and bagged trees. These techniques were driven by twelve different models generated from input combinations of satellite data and hydrometeorological parameters. The results indicated that the eighth model performed best and was superior among all the models, with the SVM algorithm resulting in an R2 value of 0.82 and the lowest errors in terms of the Root Mean Squared Error (RMSE) (0.33) and Mean Absolute Error (MAE) (0.20), followed by the Matern 5/2 Gaussian model with an R2 value of 0.75 and RMSE and MAE of 0.39 and 0.21 mm/day, respectively. Moreover, among all the five methods, the SVM and Matern 5/2 Gaussian methods were the best-performing ML algorithms in our study of CTEI predictions for the Ganga basin.
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Krueger, Lori E., Jui-Ching Wu, Meng-Fu Bryan Tsou, and Lesilee S. Rose. "LET-99 inhibits lateral posterior pulling forces during asymmetric spindle elongation in C. elegans embryos." Journal of Cell Biology 189, no. 3 (April 26, 2010): 481–95. http://dx.doi.org/10.1083/jcb.201001115.
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Cortical pulling on astral microtubules positions the mitotic spindle in response to PAR polarity cues and G protein signaling in many systems. In Caenorhabditis elegans single-cell embryos, posterior spindle displacement depends on Gα and its regulators GPR-1/2 and LIN-5. GPR-1/2 and LIN-5 are necessary for cortical pulling forces and become enriched at the posterior cortex, which suggests that higher forces act on the posterior spindle pole compared with the anterior pole. However, the precise distribution of cortical forces and how they are regulated remains to be determined. Using spindle severing, single centrosome assays, and centrosome fragmentation, we show that both the anterior and posterior cortices generate more pulling force than the lateral–posterior region. Lateral inhibition depends on LET-99, which inhibits GPR-1/2 localization to produce a bipolar GPR-1/2 pattern. Thus, rather than two domains of cortical force, there are three. We propose that the attenuation of lateral forces prevents counterproductive pulling, resulting in a higher net force toward the posterior that contributes to spindle elongation and displacement.
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Kiehn, O., and R. M. Harris-Warrick. "Serotonergic stretch receptors induce plateau properties in a crustacean motor neuron by a dual-conductance mechanism." Journal of Neurophysiology 68, no. 2 (August 1, 1992): 485–95. http://dx.doi.org/10.1152/jn.1992.68.2.485.
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1. The mechanisms for induction of bistable plateau potential properties by a set of serotonergic/cholinergic peripheral stretch receptor cells [gastropyloric receptor (GPR) cells] were examined in the crab stomatogastric ganglion (STG) with the use of intracellular recording techniques. 2. GPR cell stimulation evoked nicotinic excitatory postsynaptic potentials (EPSPs) and induced plateau potential capability in the dorsal gastric (DG) motor neuron. The plateau potential could be triggered during a GPR train either by the summating nicotinic EPSPs or by brief intracellular current injection. After pharmacological blockade of nicotinic and muscarinic receptors, a slow depolarization in response to GPR stimulation was revealed. Prolonged plateau potentials could still be evoked after this treatment. Local application of serotonin (5-HT; 10 microM to 1 mM) mimicked the noncholinergic plateau inducing effects of GPR stimulation in the DG motor neuron. 3. The synergistic action of acetylcholine (ACh) and 5-HT was examined by stimulating the GPR cells at different frequencies (1-20 Hz). The plateau induction was present down to 2 Hz. The time to onset for triggering a plateau during a GPR train was determined by the co-released ACh. 4. The 5-HT-evoked slow depolarization persisted in tetrodotoxin (TTX; 0.1-1 microM), and the DG motor neuron could still produce a plateau potential on brief depolarization in the absence of the spike-generating mechanism. 5. In normal TTX-containing saline, the 5-HT-evoked depolarization was accompanied by a weak and variable decrease in apparent input conductance. After substituting one-half of the extracellular sodium with either Trisma-HCl or choline, the decrease in apparent input conductance became more pronounced. This decrease was converted to an increase in apparent input conductance when extracellular Ca2+ was replaced with Mg2+. 6. Under voltage-clamp conditions, local application of 5-HT caused a slow inward current of prolonged duration in DG. The current versus voltage relationship had an inverted U-shape with no apparent reversal potential in the entire voltage range investigated (-90 to -5 mV). The 5-HT-induced changes in input conductance showed a complex voltage dependence, with a conductance decrease from moderately depolarized voltages. 7. Extracellular Cs+ (2-4 mM) caused the DG to hyperpolarize 2-4 mV from rest, whereas lowering extracellular Ca2+ caused it to depolarize 7-15 mV. The combined action of low extracellular Ca2+ and 2-4 mM Cs+ caused an almost complete block of the slow 5-HT-evoked depolarization.(ABSTRACT TRUNCATED AT 400 WORDS)
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Zhang, B., and R. M. Harris-Warrick. "Multiple receptors mediate the modulatory effects of serotonergic neurons in a small neural network." Journal of Experimental Biology 190, no. 1 (May 1, 1994): 55–77. http://dx.doi.org/10.1242/jeb.190.1.55.
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The gastropyloric receptor (GPR) cells are a set of cholinergic/serotonergic mechanosensory neurons that modulate the activity of neural networks in the crab stomatogastric ganglion (STG). Stimulation of these cells evokes a variety of slow modulatory responses in different STG neurons that are mimicked by exogenously applied serotonin (5-HT); these responses include tonic inhibition, tonic excitation and induction of rhythmic bursting. We used pharmacological agonists and antagonists to show that these three classes of modulatory response in the STG neurons are mediated by distinct 5-HT receptor subtypes. GPR stimulation or application of 5-HT or 2-me-5HT (a vertebrate 5-HT3 agonist) inhibited the pyloric constrictor (PY) neurons; these actions were selectively antagonized by gramine. GPR stimulation or application of 5-HT induced rhythmic bursting in the electrically coupled anterior burster (AB) and pyloric dilator (PD) neurons; these effects were antagonized by the 5-HT1c/2 antagonist cinanserin and by atropine at concentrations that do not block muscarinic cholinergic receptors in the crab STG. The 5-HT agonists 5-CT (5-HT1) and alpha-me-5HT (5-HT2) also induced AB/PD bursting, which was blocked by cinanserin, but not by atropine. GPR stimulation or application of 5-HT and 5-CT evoked tonic excitation of the lateral pyloric (LP) neuron. These effects were blocked by cinanserin. Several other 5-HT agonists and nearly all the vertebrate 5-HT antagonists we tested had little or no effect on the crab pyloric 5-HT receptors. These results provide further evidence that the modulatory sensory GPR neuron uses serotonin to evoke multiple modulatory responses via multiple 5-HT receptors. However, the 5-HT receptors in the crab STG neurons are not pharmacologically similar to vertebrate 5-HT receptors.
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Nugroho, Untoro, and Norick Cahya Jonathan Susanto. "Comparison of GPR (Ground Penetrating Radar) Penetration Results Using the GCB-400 Antenna on Flexible and Rigid Pavement." IOP Conference Series: Earth and Environmental Science 1203, no. 1 (June 1, 2023): 012022. http://dx.doi.org/10.1088/1755-1315/1203/1/012022.
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Abstract GPR (Ground Penetrating Radar) has been known as a tool used in non-destructive testing or in other words GPR can find out the conditions below the surface without damaging the layer above it. The GPR method is generally applied to roads namely flexible pavements and rigid pavements. This method has non-destructive properties because it utilizes electromagnetic waves in its operation, such as detecting the presence of objects or constituent layers at a certain depth. The penetration depth that can be achieved by GPR is influenced by three physical parameters, namely conductivity, relative dielectric permittivity (RDP), and magnetic permeability. In this study, GPR used the GCB-400 antenna model produced by the Swedish company Geoscanners. The research was conducted on roads with 2 different types of materials, namely asphalt (flexible pavement) and concrete (rigid pavement). Asphalt and concrete have different relative dielectric permittivity (RDP), where asphalt has an RDP of 5 and concrete has an RDP of 5.5. The results showed that there were significant differences between roads with asphalt and roads with concrete materials. On roads with asphalt material, GPR can reach a depth of more than 3 meters. On roads with concrete materials, GPR can only reach a depth of less than 2 meters.
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Leucci, G., and L. De Giorgi. "Integrated geophysical surveys to assess the structural conditions of a karstic cave of archaeological importance." Natural Hazards and Earth System Sciences 5, no. 1 (January 3, 2005): 17–22. http://dx.doi.org/10.5194/nhess-5-17-2005.
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Abstract. An integrated geophysical survey using both the electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) methods was undertaken over a cave of great archaeological interest in southern Italy. The survey was performed to assess the stability of the carbonate rock roof of the cave. A geophysical survey was preferred to boreholes and geotechnical tests, in order to avoid the risk of mass movements. The interpretation of integrated data from ERT and GPR resulted in an evaluation of some of the electromagnetic (EM) characteristics (such as the EM wave velocity) and the detection of discontinuities (fractures) in the carbonate rock. It is well known that rock fractures constitute a serious problem in cave maintenance, and progressive cracking within the bed rock is considered to be one of the main causes of collapse. An analysis of the back-scattered energy was also required for the GPR data interpretation. Cracks within the bedrock were detected to a depth of about 2 m by using GPR, which allowed for the identification of the loosened zone around the cave.
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Mangel, Adam R., Stephen M. J. Moysey, and John Bradford. "Reflection tomography of time-lapse GPR data for studying dynamic unsaturated flow phenomena." Hydrology and Earth System Sciences 24, no. 1 (January 14, 2020): 159–67. http://dx.doi.org/10.5194/hess-24-159-2020.
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Abstract. Ground-penetrating radar (GPR) reflection tomography algorithms allow non-invasive monitoring of water content changes resulting from flow in the vadose zone. The approach requires multi-offset GPR data that are traditionally slow to collect. We automate GPR data collection to reduce the survey time significantly, thereby making this approach to hydrologic monitoring feasible. The method was evaluated using numerical simulations and laboratory experiments that suggest reflection tomography can provide water content estimates to within 5 % vol vol−1–10 % vol vol−1 for the synthetic studies, whereas the empirical estimates were typically within 5 %–15 % of measurements from in situ probes. Both studies show larger observed errors in water content near the periphery of the wetting front, beyond which additional reflectors were not present to provide data coverage. Overall, coupling automated GPR data collection with reflection tomography provides a new method for informing models of subsurface hydrologic processes and a new method for determining transient 2-D soil moisture distributions.
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Katz, P. S., and R. M. Harris-Warrick. "Serotonergic/cholinergic muscle receptor cells in the crab stomatogastric nervous system. II. Rapid nicotinic and prolonged modulatory effects on neurons in the stomatogastric ganglion." Journal of Neurophysiology 62, no. 2 (August 1, 1989): 571–81. http://dx.doi.org/10.1152/jn.1989.62.2.571.
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1. The gastropyloric receptor (GPR) cells, which are described in the preceding paper, are a set of proprioceptive cells in the crabs Cancer borealis and Cancer irroratus that contain serotonin (5-hydroxytryptamine, 5-HT) and choline acetyltransferase. These cells have a variety of synaptic effects on cells in the stomatogastric ganglion (STG). We used pharmacologic methods to distinguish the effects that were due to acetylcholine (ACh) from those that could be due to serotonin. 2. The GPR cells evoke excitatory postsynaptic potentials (EPSPs) in two gastric mill motor neurons [lateral and dorsal gastric (LG and DG)] in the stomatogastric ganglion. The EPSPs exhibit nicotinic pharmacology, indicating that they may be due to the release of ACh from the GPR cells. 3. A train of GPR action potentials induces plateau potential properties in the DG motor neuron. This plateau potential induction is not blocked by nicotinic or muscarinic antagonists, suggesting it might be due to serotonin released from the GPR cells. Bath-applied serotonin induces a tonic depolarization of DG with high-intensity spiking. 4. In the accompanying paper, it is shown that DG-evoked muscle contraction leads to the excitation of GPR2 through mechanical coupling of the muscles. Because GPR2 also excites DG, a positive feedback loop exists between GPR2 and DG. This reflex loop may be involved in the control of the medial tooth of the gastric mill. 5. GPR stimulation initiates or enhances rhythmic pyloric cycling. This is due at least in part to a direct enhancement of bursting in the pyloric dilator/anterior burster (PD/AB) pacemaker cell group and can outlast the period of GPR stimulation by up to 1 min. GPR-induced PD burst enhancement continues in the presence of nicotinic and muscarinic antagonists, indicating that the effect is probably not due to the release of ACh. Bath application of serotonin mimicks the neuromodulatory effect of GPR stimulation on the PD/AB group by inducing or enhancing bursting. 6. Thus the GPR cells elicit at least three different synaptic actions in the stomatogastric ganglion: 1) classical, fast nicotinic cholinergic EPSPs that may be important for reflex functions in the gastric mill; 2) noncholinergic, cycle-by-cycle plateau potential induction that might be critical for the timing and operation of the gastric mill, and 3) prolonged, noncholinergic burst enhancement in pyloric neurons that is mimicked by serotonin, lasts many cycles, and may act to assure that the pyloric central pattern generator (CPG) is activated and cycling strongly.
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De Benedetto, Daniela, Francesco Montemurro, and Mariangela Diacono. "Mapping an Agricultural Field Experiment by Electromagnetic Induction and Ground Penetrating Radar to Improve Soil Water Content Estimation." Agronomy 9, no. 10 (October 15, 2019): 638. http://dx.doi.org/10.3390/agronomy9100638.
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A growing interest in proximal sensing technologies for estimating soil water content (SWC) will be highlighted. On this matter the objectives of this study were: (1) to use both the combined electromagnetic induction (EMI) sensor and Ground Penetrating Radar (GPR) to characterize an innovative field experiment located in southern Italy, in which different agricultural practices are tested, including a soil hydraulic arrangement; (2) to implement a geostatistical approach in order to merge different geophysical sensor data as auxiliary variables for SWC estimation. The multi-sensor recorded data were: (1) SWC data measured by gravimetric method; (2) Differential Global Positioning System height; (3) apparent electrical conductivity measured by an EMI sensor; (4) depths of soil discontinuities individuated by GPR radargrams interpretation; and (5) amplitude of GPR signal data at two different frequencies. Geostatistical techniques were used both to map all variables and improve the SWC estimation. The findings of this research indicate that: (1) the GPR radargrams identified four reflection events as a consequence of interfaces; (2) the EMI and GPR mapping provided identification of areas with high potential for water stagnation; and (3) the outputs of geophysical sensors can be effectively used as auxiliary tools to supplement the sampling of the target variable and to improve water content estimation.
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Zaki, Ahmad, Megat Azmi Megat Johari, Wan Muhd Aminuddin Wan Hussin, and Yessi Jusman. "Experimental Assessment of Rebar Corrosion in Concrete Slab Using Ground Penetrating Radar (GPR)." International Journal of Corrosion 2018 (November 21, 2018): 1–10. http://dx.doi.org/10.1155/2018/5389829.
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Corrosion of steel reinforcement is a major cause of structural damage that requires repair or replacement. Early detection of steel corrosion can limit the extent of necessary repairs or replacements and costs associated with the rehabilitation works. The ground penetrating radar (GPR) method has been found to be a useful method for evaluating reinforcement corrosion in existing concrete structures. In this paper, GPR was utilized to assess corrosion of steel reinforcement in a concrete slab. A technique for accelerating reinforcement bar corrosion using direct current (DC) power supply with 5% sodium chloride (NaCl) solution was used to induce corrosion to embedded reinforcement bars (rebars) in this concrete slab. A 2 GHz GPR was used to assess the corrosion of the rebars. The analysis of the results of the GPR data obtained shows that corrosion of the rebars could be effectively localized and assessed.
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Zhu, Shuang, Xiangang Luo, Zhanya Xu, and Lei Ye. "Seasonal streamflow forecasts using mixture-kernel GPR and advanced methods of input variable selection." Hydrology Research 50, no. 1 (June 8, 2018): 200–214. http://dx.doi.org/10.2166/nh.2018.023.
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Abstract Gaussian Process Regression (GPR) is a new machine-learning method based on Bayesian theory and statistical learning theory. It provides a flexible framework for probabilistic regression and uncertainty estimation. The main effort in GPR modelling is determining the structure of the kernel function. As streamflow is composed of trend, period and random components. In this study, we constructed a mixture-kernel composed of squared exponential kernel, periodic kernel and a rational quadratic term to reflect different properties of streamflow time series to make streamflow forecasts. A relevant feature-selection wrapper algorithm was used, with a top-down search for relevant features by Random Forest, to offer a systematic factors analysis that can potentially affect basin streamflow predictability. Streamflow prediction is evaluated by putting emphasis on the degree of coincidence, the deviation on low flows, high flows and the error level. The objective of this study is to construct a seasonal streamflow forecasts model using mixture-kernel GPR and the advanced input variable selection method. Results show that the mixture-kernel GPR has good forecasting quality, and top importance predictors are streamflow at 12, 6, 5, 1, 11, 7, 8, 4 months ahead, Nino 1 + 2 at 11, 5, 12, 10 months ahead.
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Li, Chunjiang, Zhijun Li, Wenfeng Huang, Baosen Zhang, Yu Deng, and Guoyu Li. "Morphology Dynamics of Ice Cover in a River Bend Revealed by the UAV-GPR and Sentinel-2." Remote Sensing 15, no. 12 (June 19, 2023): 3180. http://dx.doi.org/10.3390/rs15123180.
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After the formation of the bend ice cover, the ice thickness of the bend is not uniformly distributed, and an open-water area is usually formed downstream of the bend. The spatial and temporal variation of the ice thickness in seven cross sections was determined via Unmanned Aerial Vehicle Ground Penetrating Radar (UAV-GPR) technology and traditional borehole measurements. The plane morphology change of the open water was observed by Sentinel-2. The results show that the average dielectric permittivity of GPR was 3.231, 3.249, and 3.317 on three surveys (5 January 2022, 16 February 2022, and 25 February 2022) of the Yellow River ice growing period, respectively. The average ice thickness of the three surveys was 0.402 m, 0.509 m, and 0.633 m, respectively. The ice thickness of the concave bank was larger than that of the convex bank. The plane morphology of the open water first shrinks rapidly longitudinally and then shrinks slowly transversely. The vertical boundary of the open water was composed of two arcs, in which the slope of Arc I (close to the water surface) was steeper than that of Arc II, and the hazardous distance of the open-water boundary was 10.3 m. The increased flow mostly affected the slope change of Arc I. Finally, we discuss the variation of hummocky ice and flat ice in GPR images and the physical factors affecting GPR detection accuracy, as well as the ice-thickness variation of concave and convex banks in relation to channel curvature.
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Aslam, Huda, Md Maruf Mortula, Sherif Yehia, Tarig Ali, and Manreet Kaur. "Evaluation of the Factors Impacting the Water Pipe Leak Detection Ability of GPR, Infrared Cameras, and Spectrometers under Controlled Conditions." Applied Sciences 12, no. 3 (February 6, 2022): 1683. http://dx.doi.org/10.3390/app12031683.
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Leakages from water distribution infrastructures are responsible for a considerable amount of water losses. Consequently, innovative, non-destructive techniques (NDT) of leakage detection for early recognition is vital. In this study, the leak detection abilities of Ground Penetration Radar (GPR), spectrometers, and infrared (IR) cameras were investigated, and the factors affecting the leak detection response were assessed. Three experimental setups were constructed to simulate underground pipes in dune sand. Three different pipe materials (PVC, PPR, and PE) were investigated under three levels of moisture content (MC; 2%, 5%, and 10%) and three types of leaks (hole, crack, and faulty joint). The IR camera was the most effective among the different NDTs used in this study. The IR camera detected all types of leaks at 2% and 5% MC but was inconclusive at 10% MC. Similarly, the GPR detected the leaks at 2% and 5% MC successfully but was inconclusive at 10% MC. Lastly, the spectrometer was the least reliable NDT to detect leaks. Results suggest that IR cameras and spectrometers that operate in the mid-IR range (5–25 µm) can detect leaks.
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Fischer, Andrea. "Calculation of glacier volume from sparse ice-thickness data, applied to Schaufelferner, Austria." Journal of Glaciology 55, no. 191 (2009): 453–60. http://dx.doi.org/10.3189/002214309788816740.
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AbstractIn order to develop and evaluate a method for the determination of glacier volume from ice-thickness data, the volume of Schaufelferner, Austria, is calculated (1) by manual interpolation of ground-penetrating radar (GPR) data based on measurements at 36 locations in 1995, (2) by manual interpolation of 144 GPR measurements acquired for a higher-resolution estimate in 2003 and 2006, (3) by multiplying the mean of the measured ice-thickness data by the glacier area, (4) by automatic kriging of the 1995 GPR data and (5) by application of area/volume scaling algorithms to the Austrian glacier inventory data of 1969, 1997 and 2006. The so determined glacier volumes are compared with the ice-volume changes calculated from digital elevation models (DEMs) of the Austrian glacier inventories. The manually interpolated volumes based on the 1995 and 2003/06 GPR data yielded a volume loss only slightly different from volume loss calculated from the glacier inventories of 1997 and 2007. Other methods were not able to reproduce the volume losses of the glacier inventory DEMs. To assess the accuracy of deriving ice-thickness changes with GPR, repeated ice-thickness measurements at the same locations were carried out between 2005 and 2008.
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Katz, P. S., and R. M. Harris-Warrick. "Recruitment of crab gastric mill neurons into the pyloric motor pattern by mechanosensory afferent stimulation." Journal of Neurophysiology 65, no. 6 (June 1, 1991): 1442–51. http://dx.doi.org/10.1152/jn.1991.65.6.1442.
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1. The gastropyloric receptor (GPR) cells are stretch-sensitive muscle receptors in the crab stomatogastric nervous system that use both 5-hydroxytryptamine (serotonin) and acetylcholine as cotransmitters. Brief stimulation of these afferent neurons causes two gastric mill neurons to be recruited into the pyloric motor pattern. 2. The GPR cells evoke complex synaptic potentials in the lateral gastric (LG) and medial gastric (MG) motor neurons, two component neurons of the gastric mill central pattern generator. When the gastric mill is quiescent (as often happens in vivo), GPR stimulation transiently inhibits LG and MG. After this transient inhibition, these cells undergo a prolonged excitation during which they fire bursts of action potentials at a constant phase relation to the pyloric motor pattern. 3. To determine the causes for this effect, we examined the effects of GPR stimulation on these two cells and on the inferior cardiac motor neuron, which is electrically coupled to them. When GPR is stimulated, all three cells receive rapid biphasic synaptic potentials that are blocked by nicotinic antagonists, followed by a slow, prolonged depolarizing potential. 4. The slow, prolonged depolarizing potential is not blocked by nicotinic or muscarinic cholinergic antagonists but is mimicked and occluded by exogenously applied serotonin. 5. The prolonged excitation, mediated at least in part by serotonin, may be responsible for the recruitment of the gastric mill neurons into the pyloric motor pattern. Thus sensory input can directly exert prolonged modulatory effects that change the functional cellular composition of pattern-generating circuits.
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Katz, P. S., M. H. Eigg, and R. M. Harris-Warrick. "Serotonergic/cholinergic muscle receptor cells in the crab stomatogastric nervous system. I. Identification and characterization of the gastropyloric receptor cells." Journal of Neurophysiology 62, no. 2 (August 1, 1989): 558–70. http://dx.doi.org/10.1152/jn.1989.62.2.558.
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1. Serotonin (5-hydroxytryptamine) immunohistochemistry was used to locate and anatomically describe a set of four muscle receptor cells in the stomatogastric nervous system of the crabs Cancer borealis and Cancer irroratus. We found that these sensory cells, which we named gastropyloric receptor (GPR) cells, are the sole source of serotonergic inputs to the stomatogastric ganglion (STG) in these species. Thus any endogenous serotonergic modulation of the central pattern generators (CPGs) in the STG must be afferent and not descending from other ganglia. 2. There are two bilateral pairs of GPR cells. Each pair consists of two cell types (GPR1 and GPR2) based on differences in muscle innervation and physiological response characteristics. GPR2 responds in a mostly tonic fashion to increases in muscle tension caused by passive stretch or motor neuron-evoked contraction, whereas GPR1 responds more phasically and adapts more rapidly. Both GPR cell types project to the midline STG and terminate in each of the bilaterally paired commissural ganglia (COGs). 3. The GPR cells have sensory endings unlike any described for other muscle receptor cells: the terminals enter invaginations of the muscle surface and end near the z-bands of the muscle. These novel structures may be involved in the sensory transduction process. 4. The GPR cells may contain acetylcholine in addition to serotonin, as indicated by the presence of choline acetyltransferase (ChAT) in GPR2 (Table 1) and probably GPR1 as well. 5. The GPR cells have no direct effect on muscle properties or neuromuscular transmission: excitatory junctional potential (EJP) amplitude and motor neuron-evoked tension are unaffected by GPR stimulation. However, very low concentrations of exogenously applied serotonin do cause an increase in motor neuron-evoked muscle tension, probably reflecting a hormonal action of the amine. 6. The activity of GPR2 was monitored in a semi-intact preparation. GPR2 is active in phase with normal movements of the gastric mill. GPR2 is also capable of endogenous rhythmic activity. This indicates that even in the absence of mechanical stimulation, the GPR cells may still provide patterned input to the CPGs in the STG. 7. The GPR cells are proprioceptive cells that use serotonin and acetylcholine as cotransmitters. It is important to characterize these cells to understand the role of serotonergic modulation in the production of motor programs by stomatogastric CPGs.
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Minah, Sitti, Agus Haryono, and Saalon Sinaga. "Pengembangan Perangkat Pembelajaran Materi Arthropoda Berbasis Student Centered Learning Untuk Meningkatkan Keterampilan Berpikir Kritis Mahasiswa Di Masa Pandemi." Jurnal Penelitian Sains dan Pendidikan (JPSP) 2, no. 1 (April 27, 2022): 69–77. http://dx.doi.org/10.23971/jpsp.v2i1.3586.
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Penelitian ini bertujuan untuk menghasilkan perangkat pembelajaran materi Arthropoda untuk meningkatkan kemandirian mahasiswa dan meningkatkan CTS dengan menggunakakan pendekatan Studen-Centered Learning. Pengembangan perangkat menggunakan pengembangan model ADDIE, perangkat pembelajaran yang dikembangkan terdiri dari 1) RPS 2) Bahan Ajar 3) Lembar kerja mahasiswa 4) Evaluasi hots. Pengembangan perangkat mengunakan hasil validasi ahli dan uji terbatas. Hasil pengembangan berupa 1) Pengembangan perangkat perangkat dengan kategori valid dan layak digunakan 2) Hasil keterlaksanaan RPS menggunakan pendekatan SCL dengan kategori cukup baik dan respon mahasiswa terhadap langkah-langkah RPS positif dan mengacu pada keterampilan berpikir kritis dengan kategori N-gain 0,73 dengan nilai tinggi. 3)Pengembangan pada Bahan Ajar dengan kategori baik, 4) LKM didesain sederhana untuk meningkatkan keterrampilan berpikir kritis, 5) Alat evaluasi mengacu pada soal hots. Pelaksanaan penelitian secara hybrid learning dengan memadukan kegiatan online dan offline, kegiatan, perkuliahan secara online menggunakan Whatsapp, GcR dan Zoom, dan kegiatan perkuliahan secara offline dilaksanakan mahasiswa dengan mengakses bahan ajar dan instruksional yang ada di dalam GcR secara mandiri. Perangkat pembelajaran materi Arthropoda berbasis Student-Centered Learning dapat digunakan di masa pandemi untuk meningkatkan keterampilan berpikir kritis mahasiswa.
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Anschütz, Helgard, Daniel Steinhage, Olaf Eisen, Hans Oerter, Martin Horwath, and Urs Ruth. "Small-scale spatio-temporal characteristics of accumulation rates in western Dronning Maud Land, Antarctica." Journal of Glaciology 54, no. 185 (2008): 315–23. http://dx.doi.org/10.3189/002214308784886243.
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AbstractSpatio-temporal variations of the recently determined accumulation rate are investigated using ground-penetrating radar (GPR) measurements and firn-core studies. The study area is located on Ritscherflya in western Dronning Maud Land, Antarctica, at an elevation range 1400–1560 m. Accumulation rates are derived from internal reflection horizons (IRHs), tracked with GPR, which are connected to a dated firn core. GPR-derived internal layer depths show small relief along a 22 km profile on an ice flowline. Average accumulation rates are about 190 kg m−2 a−1 (1980–2005) with spatial variability (1σ) of 5% along the GPR profile. The interannual variability obtained from four dated firn cores is one order of magnitude higher, showing 1σ standard deviations around 30%. Mean temporal variations of GPRderived accumulation rates are of the same magnitude or even higher than spatial variations. Temporal differences between 1980–90 and 1990–2005, obtained from two dated IRHs along the GPR profile, indicate temporally non-stationary processes, linked to spatial variations. Comparison with similarly obtained accumulation data from another coastal area in central Dronning Maud Land confirms this observation. Our results contribute to understanding spatio-temporal variations of the accumulation processes, necessary for the validation of satellite data (e.g. altimetry studies and gravity missions such as Gravity Recovery and Climate Experiment (GRACE)).
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de Sá, Nuno César, Mitra Baratchi, Leon T. Hauser, and Peter van Bodegom. "Exploring the Impact of Noise on Hybrid Inversion of PROSAIL RTM on Sentinel-2 Data." Remote Sensing 13, no. 4 (February 11, 2021): 648. http://dx.doi.org/10.3390/rs13040648.
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Remote sensing (RS) of biophysical variables plays a vital role in providing the information necessary for understanding spatio-temporal dynamics in ecosystems. The hybrid approach to retrieve biophysical variables from RS by combining Machine Learning (ML) algorithms with surrogate data generated by Radiative Transfer Models (RTM). The susceptibility of the ill-posed solutions to noise currently constrains further application of hybrid approaches. Here, we explored how noise affects the performance of ML algorithms for biophysical trait retrieval. We focused on synthetic Sentinel-2 (S2) data generated using the PROSAIL RTM and four commonly applied ML algorithms: Gaussian Processes (GPR), Random Forests (RFR), and Artificial Neural Networks (ANN) and Multi-task Neural Networks (MTN). After identifying which biophysical variables can be retrieved from S2 using a Global Sensitivity Analysis, we evaluated the performance loss of each algorithm using the Mean Absolute Percentage Error (MAPE) with increasing noise levels. We found that, for S2 data, Carotenoid concentrations are uniquely dependent on band 2, Chlorophyll is almost exclusively dependent on the visible ranges, and Leaf Area Index, water, and dry matter contents are mostly dependent on infrared bands. Without added noise, GPR was the best algorithm (<0.05%), followed by the MTN (<3%) and ANN (<5%), with the RFR performing very poorly (<50%). The addition of noise critically affected the performance of all algorithms (>20%) even at low levels of added noise (≈5%). Overall, both neural networks performed significantly better than GPR and RFR when noise was added with the MTN being slightly better when compared to the ANN. Our results imply that the performance of the commonly used algorithms in hybrid-RTM inversion are pervasively sensitive to noise. The implication is that more advanced models or approaches are necessary to minimize the impact of noise to improve near real-time and accurate RS monitoring of biophysical trait retrieval.
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Cai, Jun, and George A. McMechan. "Ray‐based synthesis of bistatic ground‐penetrating radar profiles." GEOPHYSICS 60, no. 1 (January 1995): 87–96. http://dx.doi.org/10.1190/1.1443766.
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An algorithm has been developed to numerically synthesize 2-D bistatic (common‐offset), ground‐penetrating radar (GPR) profiles using the principles of geometrical ray theory. By assuming nondispersive propagation, kinematic properties of electromagnetic waves are simulated by ray tracing. Dynamic properties are simulated by computing transmitter and receiver directivities, reflection and transmission coefficients, geometrical spreading, and attenuation coefficients. The main limitations are that wave effects, such as diffractions, and offline (3-D) effects are not included. The algorithm is applied to iterative modeling of multioffset, multifrequency GPR data acquired over an outcrop of fractured Austin Chalk in Dallas County in northeast Texas. Modeling is able to simulate realistically the main time and amplitude behaviors observed in GPR reflections at 50, 100, and 200 MHz at each of 1, 3, and 5 meter antenna separations from a single model. Detailed modeling produces quantitative estimates of the spatial distributions of electrical properties that are consistent with the geologic environment.
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Ojo, Olabanji Adeolu, Victor Adejumo, and Obaromi Olubunmi. "An Integrated Approach in Geophysical Investigation of Road Failure in Crystalline Basement Area of Nigeria." Journal of Geoscience, Engineering, Environment, and Technology 4, no. 4 (December 30, 2019): 248–56. http://dx.doi.org/10.25299/jgeet.2019.4.4.2590.
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The result of the geophysical investigation carried out to access the cause of road failure and remediation measures along Ilesha-Osogbo expressway, Osun State, South-western Nigeria is presented. The study involved integrating the dipole-dipole technique of electrical resistivity method with the ground penetrating radar (GPR) method. Two dipole-dipole traverses, one long and 20 short GPR profiles were established across the failed section of the road. The dipole-dipole data were interpreted using the Diprowin software to produce the pseudo-section while the GPR data were interpreted using the RadProwin to produce the radargram. The result revealed that the failed road exhibit incompetent layer of resistivity values ranging between 17 Ωm to 171 Ωm lying between two competent layers of resistivity values greater than 200 Ωm. A combination of the dipole-dipole technique and the GPR techniques revealed the depth extend to failure to about 4.5 meters to 5 meters deep which overlie a basement rock of undifferentiated gneiss, a rock that is easily prone to weathering. The water level was observed to occur at shallow depth of about 2 meters and infiltrates the entire weathered layer. The shallow groundwater level coupled with the water-logged clayey layer derived from the weathered materials from basement rock were found responsible for the failure of this section of the road. The study recommends the excavation of the waterlogged clayey layer to a depth of about 5 to 6 meters deep into the subsurface and replacement first with heavy boulders of granitic materials and later overlaid with a thick layer of highly resistive landfill materials such as laterite. The result of the two techniques used in this work have proved to be supportive due to the integration of the double dipole technique with the GPR technique, a relatively new technique recently being introduced into road failure mapping.
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Kruetzmann, N. C., W. Rack, A. J. McDonald, and S. E. George. "Snow accumulation and compaction derived from GPR data near Ross Island, Antarctica." Cryosphere 5, no. 2 (May 18, 2011): 391–404. http://dx.doi.org/10.5194/tc-5-391-2011.
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Abstract. We present an improved method for estimating accumulation and compaction rates of dry snow in Antarctica with ground penetrating radar (GPR). Using an estimate of the emitted waveform from direct measurements, we apply deterministic deconvolution via the Fourier domain to GPR data with a nominal frequency of 500 MHz. This reveals unambiguous reflection horizons which can be observed in repeat measurements made one year apart. At two measurement sites near Scott Base, Antarctica, we extrapolate point measurements of average accumulation from snow pits and firn cores to a larger area by identifying a dateable dust layer horizon in the radargrams. Over an 800 m × 800 m area on the McMurdo Ice Shelf (77°45´ S, 167°17´ E) the average accumulation is found to be 269 ± 9 kg m−2 a−1. The accumulation over an area of 400 m × 400 m on Ross Island (77°40´ S, 167°11´ E, 350 m a.s.l.) is found to be higher (404 ± 22 kg m−2 a−1) and shows increased variability related to undulating terrain. Compaction of snow between 2 m and 13 m depth is estimated at both sites by tracking several internal reflection horizons along the radar profiles and calculating the average change in separation of horizon pairs from one year to the next. The derived compaction rates range from 7 cm m−1 at a depth of 2 m, down to no measurable compaction at 13 m depth, and are similar to published values from point measurements.
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Faria, Sandro Henrique de, Dalto Domingos Rodrigues, Nilcilene das Graças Medeiros, and Paulo Roberto Antunes Aranha. "AVALIAÇÃO DE RADARGRAMAS BATIMÉTRICOS PARA CÁLCULO DE VOLUME DE REPRESA EMPREGANDO O CLASSIFICADOR “FCLASS2”." Boletim de Ciências Geodésicas 23, no. 2 (June 2017): 234–51. http://dx.doi.org/10.1590/s1982-21702017000200015.
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Este trabalho tem como objetivos avaliar o desempenho do GPR (Ground Penetrating RADAR) para aplicações batimétricas e o desenvolvimento de um classificador para análises de radargramas. O estudo foi realizado em uma represa situada no campus da Universidade Federal de Viçosa (UFV), na qual foi, previamente, realizado levantamento batimétrico empregando o ecobatímetro monofeixe. Foram gerados Modelos Digitais de Elevação (MDE), empregando três interpoladores diferentes e observações do ecobatímetro e GPR. Estes MDEs foram comparados aos pares, para cada interpolador, aplicando o teste t pareado. Também foram realizadas comparações com base nos volumes gerados a partir destes MDEs. Os resultados do teste t para os três MDEs mostraram que não há diferenças estatísticas, a um nível de significância de 5%, entre os modelos gerados com dados do ecobatímetro e do GPR. A maior diferença volumétrica encontrada foi de 98m³ em 75.000m³, para a função Griddata com o interpolador v4. Considerando todos os MDEs gerados, a maior diferença entre os volumes foi de 2%, cerca de 1900m³. Verificou-se que o GPR, utilizando uma antena de 100MHz, pode ser empregado em levantamentos batimétricos de represas de até 4,5m e o classificador fclass2 propiciou uma boa separação entre as camadas de água e sedimentos
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Razali, Maryanti, Ariffuddin Joret, Muhammad Suhaimi Sulong, Mohammad Faiz Liew Abdullah, Elfarizanis Baharudin, Che Ku Nor Azie Hailma Che Ku Melor, Nur Izzati Zulkefli, and Noor Azwan Shairi. "Embedded iron object detection using asynchronous full wave envelope detector technique in ground penetrating radar system." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 6187. http://dx.doi.org/10.11591/ijece.v12i6.pp6187-6195.
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<span lang="EN-US">The use of a ground penetrating radar (GPR) system that operates at low frequencies allows the detection of embedded objects underground from the earth’s surface deeper than high frequency. However, the output signal generated from the system using <a name="_Hlk111888456"></a>pulse modulation (PM) technique and high-frequency carrier, has many high ripple signals consequently resulting in a blurry image. Nevertheless, this ripple signal can be minimized by reprocessing the signal using an envelope detector method. In this study, an envelope detection technique called ArJED<sup>©</sup> asynchronous full-wave (AFW) was used in the GPR system and was tested at a frequency range from 0.06 to 0.08 GHz. A dipole antenna has been used as an embedded object detection sensor of the GPR system. The detection system of embedded objects involves four depths starting with 2 cm depth, 5 cm, 7 cm, and 20 cm. A comparison of embedded object images before and after the application of the envelope detection technique was done and proved that the proposed envelope detection technique has produced a clearer radargram image of the GPR system.</span>
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Brandt, Ola, Jack Kohler, and Mikael Lüthje. "Spatial mapping of multi-year superimposed ice on the glacier Kongsvegen, Svalbard." Journal of Glaciology 54, no. 184 (2008): 73–80. http://dx.doi.org/10.3189/002214308784409080.
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AbstractGround-penetrating radar (GPR) and satellite ERS-2 synthetic aperture radar (SAR) are used to map the thickness and extent of the superimposed ice (SI) zone on the surge-type glacier Kongsvegen, Svalbard. GPR imagery shows sub-horizontal SI layers lying unconformably above a discrete boundary. Below this boundary, the ice has a GPR signature similar to that of ice further down-glacier in the ablation zone. This boundary is posited to represent the closing of crevasses that were created during the last surge of Kongsvegen in ∼1948. Open crevasses would have interrupted the formation of sheet layers of SI due to efficient vertical drainage of the snowpack. Aerial photographs suggest that the crevasses closed sometime in the period 1956–66. A classified SAR image from 2003 is used to delineate the extent of the SI zone. The SI extent in the SAR image agrees well with the SI zone mapped by GPR. Using the SI spatial depth distribution, we estimate the mean annual accumulation of superimposed ice to be 0.16 ± 0.06 m w.e. a−1 (locally up to 0.43 m a−1 w.e.). This corresponds to ∼15–33% of the local winter balance and ∼5–10% of the total winter balance measured since 1987.
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Mangel, A. R., S. M. J. Moysey, J. C. Ryan, and J. A. Tarbutton. "Multi-offset ground-penetrating radar imaging of a lab-scale infiltration test." Hydrology and Earth System Sciences Discussions 8, no. 6 (November 15, 2011): 10095–123. http://dx.doi.org/10.5194/hessd-8-10095-2011.
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Abstract. A lab scale infiltration experiment was conducted to evaluate the use of transient multi-offset ground-penetrating radar (GPR) data for characterizing dynamic hydrologic events in the vadose zone. A unique GPR data acquisition setup allowed sets of 21 traces at different offsets to be recorded every 30 s during a 3 h infiltration experiment. The result is a rich GPR data cube that can be viewed as multi-offset gathers at discrete moments in time or as common offset images that track changes in the GPR arrivals over the course of the experiment. These data allows us to continuously resolve the depth to soil boundaries while simultaneously tracking changes in wave velocity, which are strongly associated with soil water content variations. During the experiment the average volumetric water content estimated in the tank ranged between 10–30% with discrepancies between the GPR results, moisture probe data, and 1-D numerical modeling on the order of 3–5% (vol vol−1), though the patterns of the estimated water content over time were consistent for both wetting and drying cycles. Relative errors in the estimated depth to a soil boundary located 60 cm from the surface of the tank were typically on the order of 2% over the course of the experiment. During the period when a wetting front migrated downward through the tank, however, errors in the estimated depth of this boundary were as high as 25%, primarily as a result of wave interference between arrivals associated with the wetting front and soil boundary. Given that our analysis assumed one-dimensional, vertical infiltration, this high error could also suggest that more exhaustive GPR data and comprehensive analysis methods are needed to accurately image non-uniform flow produced during periods of intense infiltration. Regardless, we were able to track the movement of the wetting front through the tank and found a reasonably good correlation with in-situ water content measurements. We conclude that transient multi-offset GPR data are capable of quantitatively monitoring dynamic soil hydrologic processes.
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Minet, J., N. E. C. Verhoest, S. Lambot, and M. Vanclooster. "Temporal stability of soil moisture patterns measured by proximal ground-penetrating radar." Hydrology and Earth System Sciences Discussions 10, no. 4 (April 3, 2013): 4063–97. http://dx.doi.org/10.5194/hessd-10-4063-2013.
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Abstract. We analyzed the temporal stability of soil moisture patterns acquired using a proximal ground-penetrating radar (GPR) in a 2.5 ha agricultural field at five different dates over three weeks. The GPR system was mounted on a mobile platform, allowing for real-time mapping of soil moisture with a high spatial resolution (2–5 m). The spatio-temporal soil moisture patterns were in accordance with the meteorological data and with soil moisture measurements from soil core sampling. Time-stable areas showing the field-average moisture could be revealed by two methods: (1) by the computation of temporal stability indicators based on relative differences of soil moisture to the field-average and (2) by the spatial intersection of the areas showing the field-average. Locations where the mean relative difference was below 0.02 m3 m−3 extended up to 10% of the field area whereas the intersection of areas showing the field-average within a tolerance of 0.02 m3 m−3 covered 5% of the field area. Compared to most of the previous studies about temporal stability of soil moisture, time-stable areas and their spatial patterns could be revealed instead of single point locations, owing to the advanced GPR method for real-time mapping. It is believed that determining spatially coherent time-stable areas is more informative rather than determining time-stable points. Other acquisitions over larger time periods would be necessary to assert the robustness of the time-stable areas.
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Kruetzmann, N. C., W. Rack, A. J. McDonald, and S. E. George. "Snow accumulation and compaction derived from GPR data near Ross Island, Antarctica." Cryosphere Discussions 5, no. 1 (January 5, 2011): 1–39. http://dx.doi.org/10.5194/tcd-5-1-2011.
Full textAbstract:
Abstract. We present a new method of using ground penetrating radar (GPR) for estimating snow accumulation and compaction rates in Antarctica. We process 500 MHz data to produce radargrams with unambiguous reflection horizons that can be observed and tracked in repeat GPR measurements made one year apart. Our processing methodology is a deterministic deconvolution via the Fourier domain using an estimate of the emitted waveform from direct measurement. At two measurement sites near Scott Base, Antarctica, point measurements of average accumulation from snow pits and firn cores are extrapolated to a larger area by identifying a dateable dust layer in the radargrams. Over an 800 m×800 m area on the McMurdo Ice Shelf (77°45´ S, 167°17´ E) the average accumulation is found to be 269 ± 9 kg m−2 a−1. The accumulation over an area of 400 m×400 m in the dry snow zone on Ross Island (77°40´ S, 167°11´ E, 350 m a.s.l.) is found to be higher (404 ± 22 kg m−2 a−1) and shows increased variability related to undulating terrain. Compaction of snow between 2 m and 13 m depth is estimated at both sites by tracking several internal reflection horizons along the radar profiles and calculating the average change in separation of horizon pairs from one year to the next. The derived compaction rates range from 7 cm m−1 at a depth of two metres, down to no measurable compaction at 13 m depth, and are similar to published values from point measurements.
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Giertzuch, Peter-Lasse, Joseph Doetsch, Mohammadreza Jalali, Alexis Shakas, Cédric Schmelzbach, and Hansruedi Maurer. "Time-lapse ground penetrating radar difference reflection imaging of saline tracer flow in fractured rock." GEOPHYSICS 85, no. 3 (April 28, 2020): H25—H37. http://dx.doi.org/10.1190/geo2019-0481.1.
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The characterization of flow and transport processes in fractured rock is challenging because they cannot be observed directly and hydrologic tests can only provide sparse and local data. Time-lapse ground penetrating radar (GPR) can be a valuable tool to monitor such processes in the subsurface, but it requires highly reproducible data. As part of a tracer injection experiment at the Grimsel Test Site (GTS) in Switzerland, borehole reflection GPR data were acquired in a time-lapse survey to monitor saline tracer flow through a fracture network in crystalline rock. Because the reflections from the tracer in the sub-mm fractures appear extremely weak, a differencing approach has been necessary to identify the tracer signal. Furthermore, several processing steps and corrections had to be applied to meet the reproducibility requirements. These steps include (1) single-trace preprocessing, (2) temporal trace alignment, (3) correction of sampling rate fluctuations, (4) spatial trace alignment, (5) spike removal, and (6) postprocessing procedures applied to the difference images. This allowed successful tracer propagation monitoring with a clear signal that revealed two separate tracer flow paths. The GPR results are confirmed by conductivity meters that were placed in boreholes in the GTS. If sufficient data processing is applied, GPR is shown to be capable of resolving tracer flow through sub-mm aperture fractures by difference reflection imaging even in challenging surroundings where many reflectors are present.
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Peterson, Curt D., and Sarah R. Doliber. "Groundwater Surface (GWS) Mapping by Ground Penetrating Radar (GPR) For Use in Protecting Freshwater Habitats, Water Quality, and Active Dune Landscapes, In the Florence Coastal Dune Sheet, Oregon, USA." Journal of Geography and Geology 11, no. 1 (February 26, 2019): 13. http://dx.doi.org/10.5539/jgg.v11n1p13.
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Ground penetrating radar (GPR) profiling was performed in the Florence (FLOR) coastal dune sheet to test relations between remotely-sensed groundwater surface (GWS) trends, measured groundwater phreatic surfaces, and overlying freshwater features/habitats. Following preliminary GPR testing, the GWS trend mapping was employed in the north FLOR dune aquifer (17 km in length and 5 km in width), in anticipation of increasing development pressures on aquifer groundwater withdrawal by the City of Florence, Oregon. Several available technologies, including continuously-towed GPR profiling (5-8 km/hr), real-time GPS positioning (±2 m horizontal), Lidar elevation control (±0.5 m NAVD88), and GIS mapping/surface trend analyses permitted upscaling to the large management area (40 km2) in the north FlOR dune aquifer. Totals of 95 km of GPR track-line, including 943 averaged shot points at 100 m track-line intervals (total ~100,000 shot points), were collected during a three-week field effort. The remotely sensed GWS, ranging from 1 to 14 m depth subsurface and 0 to 57 m elevation NAVD88, was ground-truthed in ponds, gaining-stream reaches, and monitored water wells. An area wide groundwater surface map confirmed a modeled dune-ramp aquifer, sloping (0.5-2.0 % gradients) to the Pacific Ocean shoreline and the dividing Siuslaw River valley. The continuous GPR profiles connected large dune barrage lakes, interdune valley window lakes, anadromous fish passage streams, and sensitive bog habitats to the locally-variable GWS (0.98 R2 correlation coefficient). These elevated freshwater features were shown not to be developed on perched dune soil aquitards or lake bottom mud seals, but rather they are directly dependent on the mounded, variably sloping, and very-shallow GWS in the regional dune aquifer. Shallow GWS depths also promote colonization of active dune surfaces by non-native invasive dune grasses. The freshwater lakes and ponds were shown to be susceptible to contaminant transport by down-gradient GWS flows from surrounding residential and resort development.
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Berends, Christian W. H., Javier Muñoz, Vincent Portegijs, Ruben Schmidt, Ilya Grigoriev, Mike Boxem, Anna Akhmanova, Albert J. R. Heck, and Sander van den Heuvel. "F-actin asymmetry and the endoplasmic reticulum–associated TCC-1 protein contribute to stereotypic spindle movements in the Caenorhabditis elegans embryo." Molecular Biology of the Cell 24, no. 14 (July 15, 2013): 2201–15. http://dx.doi.org/10.1091/mbc.e13-02-0076.
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The microtubule spindle apparatus dictates the plane of cell cleavage in animal cells. During development, dividing cells control the position of the spindle to determine the size, location, and fate of daughter cells. Spindle positioning depends on pulling forces that act between the cell periphery and astral microtubules. This involves dynein recruitment to the cell cortex by a heterotrimeric G-protein α subunit in complex with a TPR-GoLoco motif protein (GPR-1/2, Pins, LGN) and coiled-coil protein (LIN-5, Mud, NuMA). In this study, we searched for additional factors that contribute to spindle positioning in the one-cell Caenorhabditis elegans embryo. We show that cortical actin is not needed for Gα–GPR–LIN-5 localization and pulling force generation. Instead, actin accumulation in the anterior actually reduces pulling forces, possibly by increasing cortical rigidity. Examining membrane-associated proteins that copurified with GOA-1 Gα, we found that the transmembrane and coiled-coil domain protein 1 (TCC-1) contributes to proper spindle movements. TCC-1 localizes to the endoplasmic reticulum membrane and interacts with UNC-116 kinesin-1 heavy chain in yeast two-hybrid assays. RNA interference of tcc-1 and unc-116 causes similar defects in meiotic spindle positioning, supporting the concept of TCC-1 acting with kinesin-1 in vivo. These results emphasize the contribution of membrane-associated and cortical proteins other than Gα–GPR–LIN-5 in balancing the pulling forces that position the spindle during asymmetric cell division.
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Bashkuev, Yuri, Valery Khaptanov, and Mikhail Dembelov. "Determination of Forest Environment Density by Georadar “OKO-2”." Infocommunications and Radio Technologies 5, no. 4 (October 21, 2022): 429–35. http://dx.doi.org/10.29039/2587-9936.2022.05.4.31.
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A radar method for surveying forests based on GPR technology is proposed, which allows measuring the density of the forest environment with an error of ±5%. The forest is irradiated by a georadar installed on a car. Counting the number of reflections from tree trunks (hyperbolas) in a given area allows you to quickly and reliably determine the number of trees per unit area (ar) and recalculate into forest density. A clearer radargram of reflections from tree trunks was obtained with vertical polarization, i.e. the signal reflected from the tree trunk is higher when the polarization of the probing electromagnetic pulse is parallel to the trunk.
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Revill, Andrew, Anna Florence, Alasdair MacArthur, Stephen Hoad, Robert Rees, and Mathew Williams. "The Value of Sentinel-2 Spectral Bands for the Assessment of Winter Wheat Growth and Development." Remote Sensing 11, no. 17 (August 31, 2019): 2050. http://dx.doi.org/10.3390/rs11172050.
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Leaf Area Index (LAI) and chlorophyll content are strongly related to plant development and productivity. Spatial and temporal estimates of these variables are essential for efficient and precise crop management. The availability of open-access data from the European Space Agency’s (ESA) Sentinel-2 satellite—delivering global coverage with an average 5-day revisit frequency at a spatial resolution of up to 10 metres—could provide estimates of these variables at unprecedented (i.e., sub-field) resolution. Using synthetic data, past research has demonstrated the potential of Sentinel-2 for estimating crop variables. Nonetheless, research involving a robust analysis of the Sentinel-2 bands for supporting agricultural applications is limited. We evaluated the potential of Sentinel-2 data for retrieving winter wheat LAI, leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC). In coordination with destructive and non-destructive ground measurements, we acquired multispectral data from an Unmanned Aerial Vehicle (UAV)-mounted sensor measuring key Sentinel-2 spectral bands (443 to 865 nm). We applied Gaussian processes regression (GPR) machine learning to determine the most informative Sentinel-2 bands for retrieving each of the variables. We further evaluated the GPR model performance when propagating observation uncertainty. When applying the best-performing GPR models without propagating uncertainty, the retrievals had a high agreement with ground measurements—the mean R2 and normalised root-mean-square error (NRMSE) were 0.89 and 8.8%, respectively. When propagating uncertainty, the mean R2 and NRMSE were 0.82 and 11.9%, respectively. When accounting for measurement uncertainty in the estimation of LAI and CCC, the number of most informative Sentinel-2 bands was reduced from four to only two—the red-edge (705 nm) and near-infrared (865 nm) bands. This research demonstrates the value of the Sentinel-2 spectral characteristics for retrieving critical variables that can support more sustainable crop management practices.
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Ariska, Nabilla Putri, and Dharu Arseno. "ANALISIS EKSPERIMEN DETEKSI STRUKTUR RONGGA DI BAWAH PERMUKAAN TANAH DENGAN GPR." TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika 6, no. 1 (July 21, 2022): 21. http://dx.doi.org/10.25124/tektrika.v6i1.4033.
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Peningkatan jumlah penduduk di Indonesia mempengaruhi kebutuhan perluasan wilayah dan pembangunan infrastruktur. Proses pembangunan infrastruktur perlu melalui banyak tahapan, terutama bagi wilayah yang tidak adanya pendataan dengan baik sebelumnya. Banyak sekali kasus penanaman saluran gas PGN, jaringan kabel PLN, dan gorong-gorong yang tidak sesuai dengan standar yang telah ditetapkan. Untuk mencegah terjadinya kerusakan saluran pada proses pembangunan dapat disiasati dengan mengidentifikasi infrastruktur wilayah. Diharapkan dengan adanya proses identifikasi infrastruktur wilayah dapat membantu pihak terkait agar menjalankan pembangunan lebih efektif. Proses identifikasi dapat dibantu menggunakan Ground Penetrating Radar (GPR) yang dapat mendeteksi objek di bawah permukaan tanah.Pada eksperimen ini akan dilakukan analisis eksperimen dengan memodelkan kondisi yang menyerupai situasi di lapangan. Pengambilan data akan menerapkan frekuensi Ultra Wideband (UWB) yang memungkinkan pengukuran jarak secara presisi dan hasil citra dengan resolusi tinggi. GPR akan dimodelkan dengan sebuah alat yaitu Vector Network Analyzer (VNA) yang berfungsi untuk memancarkan serta mengolah sinyal yang ditransmisikan. Metode A-scan digunakan untuk mendeteksi saluran dengan rongga sebesar 5 cm dan 15 cm. Pada metode A-scan, kedua pemodelan dapat terdeteksi sesuai dengan ukuran saluran yang dimodelkan. Metode B-scan yang digunakan dapat memperlihatkan batas penampang secara citra 2 dimensi.Kata Kunci: GPR, UWB, VNA, Saluran Berongga.
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Soupios, P., N. Papadopoulos, and A. Sarris. "Reconstructing concealed cultural remains through integrated geophysical tomographic methods." Bulletin of the Geological Society of Greece 47, no. 3 (December 21, 2016): 1260. http://dx.doi.org/10.12681/bgsg.10900.
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The purpose of this work was to compare the mapping of shallow subsurface archaeological structures through Seismic Refraction Tomography (SRT), Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) methods. For achieving the goals of the project, a specific section of the archaeological site in Delphi has been surveyed through the employment of the above techniques. For the SRT survey, twenty four P-wave geophones were installed randomly in a 50 by 40 m area. Totally seventy three (73) shots were made by striking a metal plate with a sledgehammer to collect about 1752 travel-times. The pole-dipole array was employed to capture the ERT data along twenty densely spaced parallel profiles. The GPR data were collected along parallel sections with a resolution of 50 cm between the lines. The SRT and ERT field data were processed with modern tomographic inversion algorithms for the reconstruction of the 3-D velocity and resistivity models describing the buried archaeological remains and the subsurface matrix up to the depth of 5 meters below the ground surface. GPR signals were enhanced with specific filters signifying the shallow structures up to 2 meters below the ground surface. The integrated processing results indicate the existence of walls buried in a relatively uniform background soil. The outcome of this approach signifies that SRT, ERT and GPR methods can be used as a validation tool in any archaeological investigation by providing accurate tomographic subsurface models and contribute in cultural resources management.
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Park, Dae Hwi, and Lesilee S. Rose. "Dynamic localization of LIN-5 and GPR-1/2 to cortical force generation domains during spindle positioning." Developmental Biology 315, no. 1 (March 2008): 42–54. http://dx.doi.org/10.1016/j.ydbio.2007.11.037.
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Oladunjoye, M. A., K. O. Adejato, and A. O. Ogunkoya. "Geophysical investigation of foundation failure at Medina Estate, Lagos, Southwestern Nigeria." Global Journal of Geological Sciences 18 (June 25, 2020): 35–47. http://dx.doi.org/10.4314/gjgs.v18i1.4.
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Integrated geophysical investigation involving Ground Penetrating Radar (GPR) and Electrical Resistivity methods were carried out at Medina Estate, Lagos southwestern Nigeria to map the subsurface lithology in order to delineate its peat stratigraphy that has been causing foundation failure in the area. Twenty-one traverses (varying from 35-880 m in length) of Ground Penetrating Radar (GPR) survey were conducted along the streets of Medina trending NE-SW and NW-SE directions using the Mala 250 MHZ bi-static shielded antenna. Thirty-six Vertical Electrical Soundings (VES) were carried out using Schlumberger electrode array at some selected points along the established traverses within the area. The GPR data were processed into radar section using Rad Explorer software. The VES data were interpreted quantitatively using the partial curve matching method and 1-D forward modeling with Win Resist Software. Available litho-logs from boreholes drilled within the area were compared with the geophysical results. Results of the GPR survey delineated three geologic layers which include the topsoil with high amplitude, parallel to sub parallel, horizontal reflections, with thickness varying from 1 to 2 m across the entire profiles and composed of lateritic clay; peat layer with low amplitude, parallel sinuous/wavy reflections with depth of occurrence ranging from 2.0 to 8 m and clay with low amplitude, planar, horizontal, sub-parallel reflections underlying the peat layer. Vertical Electrical Sounding results revealed the presence of three geological layers which are the topsoil, peat and clay and sandy clay with layer resistivity values ranging from 20- 225 Ωm, 5 – 90 Ωm and 36 to 366 Ωm and thickness values ranging from 0.5 – 2 m, 4.0-29.0 m and infinity respectively. Borehole information confirms the occurrence of shallow peat with depth ranging from 1.5 to 9 m and clay layer with depth ranging from 9 to 21 m beneath the area. The GPR survey results correlates with the well logs acquired in the study area. Based on the correlation of the geophysical results with the well logs, the GPR gives better information about the peat layer compared to the Electrical ResistivityMethod. The information obtained from this study shows that the soils at shallow depth are organic soils which are difficult foundation materials because they exhibit very high compressibility, as such making shallow foundation impossible except some form of soil improvement is carried out. The alternative approach is the adoption of deep foundations in form of piles.
Keywords: Foundation Failure, Geophysical Investigation, Ground Penetrating Radar, Vertical Electrical Sounding, Peat.
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Riche, Soizic, Melissa Zouak, Françoise Argoul, Alain Arneodo, Jacques Pecreaux, and Marie Delattre. "Evolutionary comparisons reveal a positional switch for spindle pole oscillations in Caenorhabditis embryos." Journal of Cell Biology 201, no. 5 (May 20, 2013): 653–62. http://dx.doi.org/10.1083/jcb.201210110.
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During the first embryonic division in Caenorhabditis elegans, the mitotic spindle is pulled toward the posterior pole of the cell and undergoes vigorous transverse oscillations. We identified variations in spindle trajectories by analyzing the outwardly similar one-cell stage embryo of its close relative Caenorhabditis briggsae. Compared with C. elegans, C. briggsae embryos exhibit an anterior shifting of nuclei in prophase and reduced anaphase spindle oscillations. By combining physical perturbations and mutant analysis in both species, we show that differences can be explained by interspecies changes in the regulation of the cortical Gα–GPR–LIN-5 complex. However, we found that in both species (1) a conserved positional switch controls the onset of spindle oscillations, (2) GPR posterior localization may set this positional switch, and (3) the maximum amplitude of spindle oscillations is determined by the time spent in the oscillating phase. By investigating microevolution of a subcellular process, we identify new mechanisms that are instrumental to decipher spindle positioning.
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Hermawan, Willy, and Acep Ruchimat. "PEMODELAN GROUND PENETRATING RADAR MENGGUNAKAN SPLIT STEP DAN FREQUENCY DOMAIN TIME DOMAIN (FDTD) MODELLING PADA SALURAN AIR SUNGAI CIKAPAYANG." Jurnal Lingkungan dan Bencana Geologi 10, no. 1 (June 14, 2019): 29. http://dx.doi.org/10.34126/jlbg.v10i1.231.
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Pemodelan kedepan Ground Penetrating Radar (GPR) diperlukan untuk membantu saat interpretasi data dari profil GPR. Pemodelan ini bertujuan untuk melihat respon GPR dan penjalaran gelombang medan listrik ketika menjalar pada saluran air dan melihat pengaruh keberadaan air dan tidak ada air dari saluran air. Pemodelan ini menggunakan software MATGPR buatan Tzanis dengan berbasis matlab. Pada penelitian ini dilakukan pemodelan berdasarkan algoritma metode split step modelling (Bitri dan Grandjean, 1998) dan Frequency Domain Time Domain (FDTD) modelling. (Irving dan knight, 2006). Pemodelan kedepan menggunakan 2 model kasus yaitu saluran air berisi air dan saluran air tidak berisi air. Pengukuran data dilaksanakan pada tanggal 16 Februari 2014. Lokasi pengukuran dilakukan di bagian barat komplek gedung perkantoran Pusat Sumber Daya Air Tanah dan Geologi Lingkungan (PAG) - Badan Geologi, Bandung Jawa Barat. Pada lokasi tersebut tersingkap saluran air sungai Cikapayang yang tersingkap akibat amblesan tanah. Dari hasil pemodelan dengan menggunakan algoritma split step modelling dapat memperlihatkan pola refleksi hiperbola dari batas atas dan batas bawah saluran air masing – masing pada waktu t= 20 ns dan t = 50 ns dan keberadaan air ditunjukan dengan perlambatan waktu sebesar 5 ns sedangkan pada pemodelan algoritma FDTD dari Irving dan Knight dapat memperlihatkan batas-batas saluran air dari medan listrik Ey yang menjalar di dalam saluran air. Selain itu keberadaan air dapat dibedakan dengan melihat penurunan amplitudo medan listrik.
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Firdaus, M. A., Widodo, and Fatkhan. "River sedimentation modeling using ground-penetrating radar." IOP Conference Series: Earth and Environmental Science 873, no. 1 (October 1, 2021): 012041. http://dx.doi.org/10.1088/1755-1315/873/1/012041.
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Abstract In recent years, siltation has become quite a problem. It has been the main cause of flooding and a rapid decline in water quality. It is usually caused by a high river sedimentation rate and/or uncontrolled waste disposal. The increased rate of erosion also means that river sedimentation occurs faster than normal and could lead to environmental hazards, wildlife deaths, and the disruption of food and drinking water supply among other things. The question is how to monitor the sedimentation process of rivers without damaging the river itself. The suitable geophysical method is GPR. GPR is an active, non-intrusive geophysical method in which electromagnetic radiation and the reflected signals in the form of radar pulses are used for subsurface imaging. The objective is to investigate river sedimentation using GPR, we created the synthetic models based on geological models of rivers with different depths to create their 2-D radargrams to predict the actual model. We set up the first model RSM-I as control which consists of a layer of freshwater with ρ = 16 Ωm, k = 81 and μ r = 1 of depth 5 m, two layers of sandstone with ρ = 850 Ωm, k = 2.5 and μ r = 1 of total depth 4 m, and a layer of claystone with ρ = 120 Ωm, k = 11 and μ r = 1 of depth 1 m. RSM-II and III are added with a buildup of saturated sediment with ρ = 30 Ωm, k = 15, and μ r = 1 of depth 2.5 and 4 m, respectively. The radargrams’ reflector for each model shows a two-way travel time of 300-350, 150-200, and 60-90 ns in their respective order. GPR models can differentiate between the saturated sediment and freshwater, it shows good results regarding sediment investigation in rivers.
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Sellmann, Schirin, Mark Quigley, Brendan Duffy, and Ian Moffat. "Ground Penetrating Radar of Neotectonic Folds and Faults in South-Central Australia: Evolution of the Shallow Geophysical Structure of Fault-Propagation Folds with Increasing Strain." Geosciences 12, no. 11 (October 26, 2022): 395. http://dx.doi.org/10.3390/geosciences12110395.
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Using ground penetrating radar (GPR) we investigate the near surface (~0–10 m depth) geophysical structure of neotectonic fault-propagation folds and thrust faults in south-central Australia in varying stages of fold and fault growth. Variations in neotectonic fold scarp heights are interpreted to reflect variations in accumulated slip on the underlying reverse faults. Fold scarps on the Nullarbor and Roe Plains are characterized by broad, asymmetric morphologies with vertical displacements of ~5 to ~40 m distributed over 1 to 2 km widths (~0.5 to ~4 m per 100 m). Within increasing scarp height there is an increase in the frequency and spatial density of strong reflector packages in the hanging wall that are attributed to material contrasts imposed by co-seismic fracturing and associated lithological and weathering variations. No evidence for discrete faulting is found at scarp heights up to 40 m (maximum relief of 4 m per 100 m). Where the principal slip zone of a fault ruptures to the surface, scarp morphologies are characterized by steep gradients (ca. 10 m per 100 m). Discrete faulting is imaged in GPR as structural lineaments, abrupt changes in the thickness of reflector packages with variations of amplitude, and/or hyperbolic diffraction packages indicative of the disturbance of reflector packages. Geophysical imaging of subtle changes in the shallow geological structure during growth of fault-propagation folds can be conducted using GPR informing the identification of locations for invasive investigations (e.g., trenching).
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van Eenige, E. N., R. J. Wijngaarden, H. Hemmes, J. J. Scholtz, J. J. de Kleuver, and R. Griessen. "Electrical properties and T c of Bi 2 CaSr 2 Cu 2 O 8 up to pressures of 15 GPA." Physica C: Superconductivity and its Applications 162-164 (December 1989): 737–38. http://dx.doi.org/10.1016/0921-4534(89)91235-5.
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Dutta, Arin, Silvia Rahman, Turja Nandy, and Zahid Hasan Mahmood. "Simulation Study on Quantum Capacitances of Graphene Nanoribbon VLSI Interconnects." International Journal of Nanoscience 15, no. 03 (May 10, 2016): 1640006. http://dx.doi.org/10.1142/s0219581x16400068.
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In this paper, study on the capacitive effects of Graphene nanoribbon (GNR) in VLSI interconnect has been studied as a function of GNR width, Fermi function and gate voltage. The quantum capacitance of GNR has been simulated in terms of Fermi function for three different values of insulator thickness — 1.5[Formula: see text]nm, 2[Formula: see text]nm and 2.5[Formula: see text]nm. After that, quantum capacitance is studied in both degenerate and nondegenerate region with respect to Fermi function and gate voltage of range 1–5[Formula: see text]V. Then, the total capacitance of GNR is studied as a function of gate voltage of [Formula: see text][Formula: see text]–5[Formula: see text]V range at degenerate and nondegenerate regions, where width of GNR is considered 4[Formula: see text]nm. Finally, the total capacitance of GNR is studied in both regions with varying GNR width, considering fixed gate voltage of 3[Formula: see text]V. After analyzing these simulations, it has been found that GNR in degenerate region shows nearly steady capacitance under a certain applied gate voltage.
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Sirojuddin, Mochamad Jauhar Nur Ainul, Nurhayati Nurhayati, Raden Roro Hapsari Peni Agustin Tjahyaningtijas, and Farid Baskoro. "Antena Monopole Ultra Wide Band (UWB) untuk Aplikasi Ground Penetrating Radar (GPR)." JURNAL TEKNIK ELEKTRO 11, no. 1 (July 6, 2022): 88–98. http://dx.doi.org/10.26740/jte.v11n1.p88-98.
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Pada penelitian ini menjelaskan antena monopole dengan frekuensi UWB untuk digunakan pada pencitraan Radar Gelombang mikro yang disebut dengan GPR (Ground Penetrating Radar). Pada penelitian ini antena monopole digunakan untuk mendeteksi tiga jenis objek dibawah tanah yaitu plat besi, tutup panci dan kaleng. Metode deteksi dilakukan dengan cara menghubungkan antena dengan VNA (Vector Network Analyzer) portabel sehingga sinyal yang dipancarkan antena bila mengenai objek akan memiliki parameter S21 (karakteristik parameter scatering port 1 terhadap port 2) yang berbeda di antena penerima bila dibandingkan dengan kondisi tanpa adanya target. Data S21 yang didapatkan akan diolah menggunakan metode C-Scan sehingga lokasi objek/target dapat ditentukan. Dimensi antenna yang digunakan memiliki besar yaitu sebesar 200 mm x 200 mm x 0.035 mm yang dibekerja pada frekuensi 500 MHz – 3 GHz dengan bahan copper pada bagian patch dan ground plane setebal 0.035 mm, dan substrat menggunakan FR-4 Lossy dengan ketebalan1.6 mm. Dari hasil pendeteksian didapatkan bahwa bila objek berada sedalam 5 cm di bawah tanah dan posisi antena diatas tanah 20 cm dengan jarak antara antena 1 dan 2 sebesar 10 cm maka ketiga objek dapat dideteksi lokasinya dan objek besi menunjukan hasil pendeteksian dengan resolusi yang paling bagus dibandingkan dengan objek yang lainya.Kata Kunci: Wideband antenna, Monopole antenna, Pencitraan GPR, Metode C-Scan.
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Elbeltagi, Ahmed, Aman Srivastava, Nand Lal Kushwaha, Csaba Juhász, János Tamás, and Attila Nagy. "Meteorological Data Fusion Approach for Modeling Crop Water Productivity Based on Ensemble Machine Learning." Water 15, no. 1 (December 22, 2022): 30. http://dx.doi.org/10.3390/w15010030.
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Crop water productivity modeling is an increasingly popular rapid decision making tool to optimize water resource management in agriculture for the decision makers. This work aimed to model, predict, and simulate the crop water productivity (CWP) for grain yields of both wheat and maize. Climate datasets were collected over the period from 1969 to 2019, including: mean temperature (Tmean), maximum temperature (Tmax), minimum temperature (Tmin), relative humidity (H), solar radiation (SR), sunshine hours (Ssh), wind speed (WS), and day length (DL). Five machine learning (ML) methods were applied, including random forest (RF), support vector regression (SVM), bagged trees (BT), boosted trees (BoT), and matern 5/2 Gaussian process (MG). Models implemented by MG, including Tmean, SR, WS, and DL (Model 3); Tmax, Tmin, Tmean, SR, Ssh, WS, H, and DL (Model 8); Tmean, and SR (Model 9), were found optimal (r2 = 0.85) for forecasting CWP for wheat. Moreover, results of CWP for maize showed that the BT model, a combination of SR, WS, H, and Tmin data, achieved a high correlation coefficient of 0.82 compared to others. The outcomes demonstrated several high performance ML-based alternative CWP estimation methods in case of limited climatic data supporting decision making for designers, developers, and managers of water resources.