In this research, hydroxyapatite composite with two reinforcements alumina and zirconia has been used as a Coating on titanium dental implants for the first time. Two kinds of titanium implants with different percentages of impurities were chosen and after cleaning, they were coated with hydroxyapatite alumina-zirconia sol. The method of Coating was sol-gel that coated implants by dip-Coating and spin-Coating. The use of sol-gel method was for the reason that it is a cheap Coating method and it can coat all samples. By comparing the samples, it was found that in dip-Coating method, cracks are less and the morphology is more homogeneous. Although spin-coated samples were homogeneous too, but they had more cracks. Coating processes were done in three stages and between these stages, in second stage, Coatings were the best in having less cracks and the best homogeneity. It was found that implants with less impurity had more homogeneous Coatings. Increasing aging and calcination temperature of Coatings had a great effect on the quality of Coatings. The aim of this research was to investigate these Coatings for Coating titanium dental implants. Because implantation is an expensive operation, we used cheap raw materials for the Coating of implants.

The cement industry is one of the major industries in every country. This industry is the driving force behind the development of a nation. The heart of this industry is the rotary kiln. One of the significant concerns about a rotary kiln is forming a cover of molten materials on the kiln's inner wall called Coating. The low thickness of this Coating cause burns to the wall refractory bricks and heavy damage to the kiln, while its high thickness reduces the production volume and quality of products. Currently, the kilns are checked by experienced technicians for empirical Coating estimation. This paper aims to identify the thickness of the Coating for the automatic control purpose of the kiln. The identification problem of Coating thickness is based on thermal resistances in different layers of the kiln and heat transfer equations between these layers. For this purpose, linear and nonlinear identification methods such as Ordinary Least Squares (OLS), Recursive Least Squares (RLS), global search methods, and genetic algorithms are used. The Coating can be identified in the proposed identification approach by having the kiln's ambient and internal solid temperature profiles. The raw data for the identification process has been extracted by Finite Element Analysis (FEA) for a given solid temperature profile along with the kiln and different kiln Coating thicknesses. The modeling and simulations carried out in this paper show that the identification methods were able to determine the amount of Coating with acceptable errors depending on the method.

In this paper, an alternative approach in operational modal analysis is presented, utilizing image processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

Identifying the constraining factors of production and yield gap is very important. Therefore; this research was performed to identify the production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

According to classical texts, Dara stands out as a significant city from the early Parthian era, situated on the eastern fringes of the Parthian Empire. Classical sources have documented this region under various names such as Apavortene, Zapaortenon, Partauticena, and Apauarcticena. Since the latter half of the nineteenth century, Iranologists have engaged in speculation about the location of Dara, drawing insights from descriptions provided by Justin and Pliny, as well as references to its whereabouts in classical texts. This research endeavors to offer relative conjectures concerning the location of Dara and Shahr-Tepe, a potential site representing it, through an evaluation of archaeological data alongside classical and Islamic texts. To achieve the research objectives using a descriptive-analytical approach, the study employs the library research method and incorporates archaeological data. In alignment with classical texts, the research suggests that the province of Apavortene is situated in Eastern Iran, and there exists a likelihood that the Islamic-period Abivard is a transformed manifestation of this Parthian-period province. Aditionally, a comparative examination of Dara in classical texts with present-day Shahr-Tepe in Dargaz reveals congruence, aligning with the descriptions provided by Justin and Pliny. Shahr-Tepe, located on the opposite side of Hezar Masjed Mountains between Nisa and Abivard, exhibits a singular historical period. Surrounded by Hezar Masjed Mountains, the region boasts an abundance of rivers and springs, expansive meadows, and remnants of forests within Tandooreh National Park and Tivan region. These characteristics confirm the general depiction of Apavortene and Dara found in classical sources. Collectively, these findings suggest that Shahr-Tepe, covering an area of approximately 70 hectares, could indeed represent the prominent city of the early Parthian period

Fingerprint identification or dactyloscopy is a method for human identification. The impressions left by a human finger on surfaces are not visible to naked eyes (latent fingerprint); therefore, they require revelation to become visible and identified. Within the last century, several fingerprint revelation techniques such as optical, physical, and chemical were studied. These traditional methods have some shortcomings including hurting and destroying finger prints, long time of the revelation process and toxicity. Therefore, utilizing fluorescent quantum dot nanoparticles is under study due to their unique optical and chemical properties in fingerprint identification. In this article, the synthesis of cadmium telluride quantum dots is discussed, as they have a wide absorption spectrum, proper optical stability, greater radiation intensity, as well as high quantum efficiency, and their radiation is adjustable by composition and the size of the particles. The aim is to identify the effect of latent fingerprint on a variety of porous surfaces such as fabrics and papers or non-porous surfaces such as ceramics, glass and metals, with rapid detection with high contrast, sensitivity and selectivity and low toxicity. The synthesis method consists of using aqueous solution with Cadmium chloride and Tellurium dioxide with an alkaline pH solution. Studying photoluminescence in 540 nanometer wavelength, showed that the maximum radiation intensity is about 751, for 15 min. synthesis time. To modify and decrease toxicity a biocompatible Coating (TEOS) was applied using the Stober method. Essentially, a silica layer reduced the photoluminescence by about 25%.

Background: Studying protein-protein and protein-DNA interactions are prerequisites for the identification of function and mechanistic role of various proteins in the cell. Protocols for analyzing DNA-based Protein-Protein and Protein-DNA interactions are complicated and need to be simplified for efficient tracking of binding capabilities of various proteins to specific DNA molecules. Here, we demonstrated a simple yet efficient protocol for the identification of DNA Coating-based Protein-DNA interaction using antibodymediated immunodetection. Methods: Briefly, we have coated specific DNA in the microtiter plate followed by incubating with protein lysate. Specific protein-DNA and/or protein-protein bind with DNA interactions are identified using specific fluorophore-conjugated antibodies. Antibodies are used to detect a protein that is bound to the DNA. Results: Fluorescent-based detection identifies the specific interaction between Protein-DNA with respect to coated DNA fragments. The protocol uses indirect conjugated antibodies and hence the technique is sensitive for effective identification of Protein-DNA interactions. Conclusions: Based on the results we conclude that the demonstrated protocol is simple, efficient and sensitive for identification of Protein-DNA interactions.

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.