There are various approaches for depth estimation of anomalous potential field data. Spectral analysis of gravity AND magnetic data has been used extensively for many years to derive the depth to certain geological structures, such as the magnetic basement or the Curie temperature isotherm. The interpretation of the gravity AND magnetic data is preferred in frequency domain because of simple relation between various source models AND fields. The estimation of the depth of anomalous sources is usually carried out by SPECTOR AND GRANT METHOD AND its variants in frequency domain. This METHOD, which assumes a uniform distribution of parameters for an ensemble of magnetized blocks, leads to a depth-dependent exponential rate of the decay. In the frequency domain, geophysical source parameters have been assumed as uncorrelated AND rANDomly distributed. Assumption of the uncorrelated rANDom sources is not true as revealed from many borehole data in the German continental deep drilling project (KTB) around the globe. Susceptibility data of pilot hole is analyzed AND its power spectrum shows a generalized behavior. Therefore, the generalized spectral METHOD for gravity AND magnetic data, based on the realistic distribution of anomalous sources, is found useful for finding the depth values AND statistical properties of the source distribution. The scaling spectral METHOD has been applied in many parts of the world. An important aspect of this METHOD is that the scaling properties of the source distributions are related to the scaling properties of the fields in a general way. This relationship can be used to derive information on local geology. A technique to estimate the depth to anomalous sources from the generalized power spectra of magnetic profiles is presented. The power spectrum corresponding to low wavenumber may be dominated by scaling properties alone rather than the depth values. If the logarithm of obtained power spectrum of potential field data that transformed in Fourier domain, is plotted versus wave number values, although some factors affect the plot, but the depth is a dominant factor. The depth various source is thus found from the slope of this plot. If there is more than one ensemble, the slope at smaller frequencies gives the depth to deeper sources, AND subsequent slopes at higher frequencies give the depth of shallower source. The depth values calculated by this METHOD are close to the realistic values. To test the reliability of any technique it is necessary for the technique to be tested on the synthetic data. In present research work, the efficiency of generalized power spectrum has been investigated using theoretical model of magnetic AND the results have been compared with commonly power spectrum. At the end the generalized power spectrum METHOD has performed well in the depth estimation of anomalous sources of magnetic data acquired on polymetal deposit of OshvAND located in Hamedan Province AND the results compared with the commonly power spectrum, IP AND RS METHODs. Based on the previous studies conducted in the area, our estimation of the depth of anomalous sources by means of generalized power spectrum approach has been evaluated AND confirmed.

Gamma ray measurement in various research fields requires high efficient detectors. In photon dosimetry, NaI(Tl) scintillation detector as one of the inorganic scintillation detector is noticeable, due to have the high amount of light output. In this study, the basics determination of photon dosimetry for the NaI(Tl) scintillation detector utilizing the Monte Carlo code (MCNPX) AND using different METHODs of dose calculation (tally F6, * F4, + F6 AND * F8) is studied. Regularly, the output of a radiation detector (counting the number of pulses) cannot be used to determine the radiation dose value. Therefore, in this study the spectro-dosimetry METHOD based on software METHOD is used to find out the value of the conversion coefficients to convert the detector spectrum to the value of air karma. In this METHOD, the radiation dosimetry response is obtained with use of the MCNPX code simulation. The response function of the NaI(Tl) 3"×3" scintillation detector for several specific gamma rays was determined AND then the functions of energy dependent conversion coefficients for calculating the dose values were obtained. Finally, with comparison of the measured data AND simulation calculations results it is shown that the proposed METHOD has a high accuracy in photon dosimetry.

Data on soil hydraulic properties are required to model water movement in soils. Their direct measurements are difficult, time consuming, AND expensive, because of high variability AND complexity of soil systems. Pedotransfer functions are developed to estimate soil water retention curve (SWRC) using different techniques. In this study, pedotransfer functions were developed to estimate SWRC using the model of Groenevelt AND GRANT. Sixty nine soil samples were collected from Guilan Province. Soil particles AND micro aggregate size distributions, SWRC, AND basic soil properties were measured in the laboratory. Fractal AND non-fractal models were fitted to the particles AND micro aggregate size distributions AND their parameters were calculated. Linear regression technique was used to predict the parameters of Groenevelt AND GRANT’s model. In order to estimate every parameter of the model of Groenevelt AND GRANT, four pedotransfer functions were developed using each technique AND fractal parameters of particles AND micro aggregates were used as predictors. Then, estimated parameters were used to simulate SWRC AND were compared with the measured SWRC. Fractal parameters of the particle size distribution rendered better predictions of SWRC compared with the other predictors. In spite of the large number of the parameters, using Fredlund’s model did not result in more accurate predictions for SWRC in comparison with using fractal parameters. Probably, these results showed the priority of fractal theory in the particle size distribution AND SWRC modeling.

Dear Editor-in-Chief, eer-reviewers for funding allocation are under the same obligations as referees who critically AND transparently review the assigned manuscript (1). Therefore, transparent peer review of GRANT applications is also needed because the transparent funding of novel AND innovative research projects could make high-impact manuscripts AND make great progress in science. . .

Nowadays, GRANT-back clauses are one of the most important conditions in patent licensing agreements. These conditions have beneficial impact on competition AND anti-competitive behaviour that require special attention by competition law. In America, the provisions that were previously considered illegal are now assessed in accordance with rational criteria AND as a part of the contracts. The illegality of these provisions may lead to the illegality of the contract. In Europe, only exclusive GRANT-backs are subject to an individual assessment, AND not as a part of more global contract. Other conditions of the contract are exempt from general prohibition considered in Article 101 of European Treaty. In Iranian law, these provisions are new issues which can be justified by the concept of reasonableness AND the general rules of contracts. This condition does not specifically mention in General Policies of Implementation of Article 44 of the Constitution. It is forbidden if it is regarded as an unfair term or as an abusive of dominant economic conditions.

Identification of the exact location of an exon in a DNA sequence is an important research area of bioinformatics. The main issues of the previous signal processing techniques are accuracy AND robustness for the exact locating of exons. To address the mentioned issues, in this study, a METHOD has been proposed based on deep learning. The proposed METHOD includes a new preprocessing, a new mapping METHOD, AND a multi-scale modified AND hybrid deep neural network. The proposed preprocessing METHOD enriches the network to accept AND encode genes at any length in a new mapping METHOD. The proposed multi-scale deep neural network uses a combination of an embedding layer, a modified CNN, AND an LSTM network. In this study, HMR195, BG570, AND F56F11.4 datasets have been used to compare this work with previous studies. The accuracies of the proposed METHOD have been 0.982, 0.966, AND 0.965 on HMR195, BG570, AND F56F11.4 databases, respectively. The results reveal the superiority AND effectiveness of the proposed hybrid multi-scale CNN-LSTM network.