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.

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.

Sound measured at various points around the environment can be evaluated by a series of multi-pole sources and their acoustic strength can be acquired. In this numerical study، a method، called the inverse method، was examined to achieve this goal. A variety of arrangements of different sources were considered and the acoustic strength of these sources was acquired. Through the application of the mismatch criterion، good conformity was observed between these sound models and the original sound. Furthermore، with regard to results، sound was generated via different source arrangements which showed acceptable agreement with the original sound. Finally، an arrangement named ‘ sources vertical arrangement’ was selected as the best approach.

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

Plant development can be defined as a programmed qualitative change in plant form, which leads plant to maturity, and researchers call it as phasic development or phenology. Recognizing the timing of occurring each development stage is necessary for managing system in order to yield increment. The timing of occurring development stages depend on climate, genotype specifications and sowing date then determination of these times in different regions is difficult and it is only possible through the using of crop simulation models which can predict the timing of occurrence each development stage by integrating effective factors. The model was constructed based on linear equation of plant temperature response. In order to model evaluation two experiments were carried out in agricultural and natural resources research center of Khuzistan in 2003-2004 and 2004-2005 cropping years. Wheat development stages were determined based on Kirby and Appleyard’s scale by stereoscopic microscope and required GDD for each development stage as well. The constructed model was calibrated and run for simulation. Comparison of simulated and observed data showed that the model can strongly predict wheat development stages.

Since system identification of a tumor model is a primary need for controlling tumor model system, accessing suitable and applicable identification methods is a necessary object. In this paper, firstly, for estimating controlled auto-regressive moving average (CARMA) systems, two  identification methods, namely generalized projection algorithm (GPA) and two-stage GPA (2S-GPA), are introduced and presented in order to estimate unknown parameters of a specific and vital tumor model. Furthermore, effectiveness of such methods, like convergence rate and estimation error, are discussed and considered. The introduced algorithms are simulated to prove these methods effectiveness, and data derived from the simulations are depicted through tables and figures.

Today, one of the most widely used natural language representation methods is meaning representation for text processing in different systems. Meaning representation methods have had many applications in the field of natural language processing in recent years, including automatic text summarization systems and question and answer systems, etc. Many text expressions may be different in terms of grammatical structure, but they are the same in terms of meaning, so how to apply a single and uniform meaning to them is one of the challenges of text processing. The main goal of this paper is to design an Integrated Semantic Representation (ISR) model for natural language. The proposed model, while maintaining its simplicity in annotation and understanding, does not depend on specific natural language features or on syntactic and lexical structure. In this regard, several examples in both English and Persian language, which have different in terms of written and grammatical structure, are presented in this paper. Moreover, by using the proposed model, the same representation is provided for texts with the same meaning and different grammatical structure. The proposed model is designed in graph and list format is recommended to annotate its corpuses. One of the main features of this model is that it can represent semantic relations at both sentence-level and document-level and is able to represent complex and important linguistic phenomena such as aspect, tense, and quantification. The simplicity of the proposed model helps to avoid making language processing slow or complicated in various applications, and the preparation of structures based on this model for different natural languages will not be too complicated, so that it can be used both for natural languages with low resources and for those with various resources. Further, features of the proposed model are compared with one of the most important related works.