Just like any other process, vaccine manufacturing procedures are defined as a series of interrelated functions and activities using a variety of specified actions and equipment designed to produce a defined product. To assure the reproducibility and consistency of such processes, they must be carried out using validated equipment and under the established procedures that meet all the acceptance criteria, at least 3 times. In many cases, “worst case” conditions are used for the validation purposes to ensure that the process would be acceptable in extreme cases. Therefore, the validation concept in vaccine production facilities is a key element of the quality assurance goals which may reduce the dependence upon intensive in-process and finished products testing. Nevertheless, the concept of validation has expanded through the years to embrace a wide range of activities such as analytical methods used for quality control of drugs, the computerized systems for the clinical trials, the labeling and the process control. To perform such validation activities properly, the updated knowledge of the current regulations are needed. Therefore, the present article focuses on the recommendations in the related guidelines addressing different aspects of validation procedures related to the vaccine production facilities as a part of the product’s life-cycle.

There are many foundations in the word of the jurists for expert witness validation. Acceptance of them has specific effects, especially on the scope of expert witness validation and its circumstances. In this research, while criticizing the basics of the credibility of the expert evidence, such as accuracy because of witness validation, unique news, obstruction, assurance and judges awareness, prove that the correct basis in the validation of expert witness is wise way.Based on this expert opinion on the external issue of the subject, because of existence wise way, it is an independent reason for proving issues and its not just way for the judge awareness, but in proving crime and citation, according to lack of the same way between the Imams and wise men, in referring to the expert opinion, the wise is not an independent reason but merely a sign of based on suspicion that along with other signs can be a documentary for judges awareness. In matters of judgment – such as determine Arsh- expert evidence is not validation, but it can not described as an argument.

Land surface temperature (LST) is one of the key parameters in a wide range of geosciences and environmental studies. Remote sensing technology, can monitor the space and time variations of this quantity in large areas. But evaluating the accuracy of this parameter is the most challenging issues. On the one hand, rapid changes in temperature occur in space and time and the mismatch between the spatial scale of satellite and ground-based sensors, validation of LST is difficult by ground based temperature data. Validation is a process of independently assessing the uncertainty of the data derived from the system outputs. Without validation, no methods, algorithms, or parameters derived from remotely sensed data can be used with confidence. As the retrieved LSTs from satellite TIR data involve corrections to the satellite-observed radiances to account for atmospheric effects and non-unity LSEs, it is necessary to assess the accuracy of the retrieval to provide potential LST users with reliable information regarding the quality of the LST product. However, validation of satellite-derived products is often a challenge in itself. This is true for the sensors having a coarse resolution and even more with the thermal bands over land. Although many algorithms have been proposed and developed over recent decades to retrieve the LST from satellite TIR data, validation of satellite-derived LSTs remains far behind the development of new LST retrieval algorithms due to the difficulties. The important difficulties including: (i) it is difficult to obtain representative LST data at the scale of a pixel, which usually covers an area of about several square kilometers, due to the spatial variability of landscape and the large spatial–temporal variations in the LST itself. (ii) The other difficulty concerns the temporal sampling. Surface temperature is characterized by a very high temporal frequency. In a matter of seconds, the surface skin temperature may change by several degrees due to wind, shadow, etc. Generally, ground radiometers often integrate the temperature over several minutes, but the sensor onboard the satellite acquires the data in a fraction of a second. (iii) In addition, it is difficult to conduct in situ LST measurements at local scale, because LST, LSE, and the atmospheric and environmental radiances are coupled. Therefore, to obtain LST, one has to measure simultaneously the atmospheric and environmental radiances and the LSE, which is time-consuming and hard to monitor. Although there exist many problems and difficulties in the validation of the LST derived from satellite TIR data, in recent years, many efforts and studies have been performed to validate the derived LSTs from different satellite sensors. The methods utilized to validate LST values retrieved from space may be roughly grouped into four categories: the temperature-based method (T-based), the radiance-based method (R-based), the cross-validation method, and the indirect validation method. Among these methods, due to development of thermal sensors, cross-validation procedure is the most common method to evaluate the accuracy of surface temperature. Due to the large spatial and temporal variations in the LST, geographic coordinate matching, time matching, and view zenith angle matching are basic requirements of the cross-validation. In this paper, an alternative scaling method was proposed for cross-validation between LST product of LDCM and MODIS sensors. Because of the wide coverage and taken LST product twice per day by each of the MODIS sensors (Terra and Aqua), this product was selected as the reference temperature. The LST products of MODIS sensors have been validated with in situ measurements and by various methods in more than 50 clear-sky cases taking into account the higher accuracies within 1 °K for both Terra and Aqua. The results of the proposed method showed that evaluation of LST accuracy in areas with high homogeneity and in the first examined LDCM scene, in terms of mean differences and mean absolute differences measures, is 0.6 °K and 1.63 °K, respectively. For the second examined LDCM scene, the accuracy measures were 0.94 °K and 1.27 °K in the LST, respectively. Generally, the experimental results on two LDCM data demonstrated that the proposed cross-validation method not only is a robust and accurate LST validation approach, but also it is applicable for each thermal sensor and every time and place.

The aim of this study is the calibration and validation of the physical-empirical SLSM model for simulation of the snow depth in the Saghez synoptic station. For this purpose, essential daily meteorological data of the model for the time period of 1992-2014 were prepared from the Iranian Meteorological Organization and by applying the Generalized Likelihood Uncertainty Estimation (GLUE) method, that performed by considering 15 parameters and performing 15000 simulations and using both Coefficient of Determination and Nash-Sutcliffe Efficiency indices for evaluating the accuracy of the model, Calibration and validation of the model were performed for the 1992-2009 and 2010-2014 time periods, respectively. Calibration process of the model was led to extracting 108 behavioral simulations and for performing validation of the model, the median of the 108 behavioral simulations was considered as the final output of the model and compared with the measured snow depth data. The results of the model validation showed that in most of the cases, the calibrated SLSM model has an acceptable efficiency to following the fluctuations of the measured snow depth data but it partly underestimates high values of the snow depth.

Soil and Water Assessment Tool (SWAT) is a continuous and semi-distributive model which can simulate the hydrological processes in basins on daily, monthly and yearly time scales through a wide range of information such as physical data of basins (soil, land use, slope) as well as weather information such as precipitation, temperature, wind, relative humidity, solar radiation and connectivity to geographic information systems (GIS). In this research, the monthly runoff of Ravansar Sanjabi basin (1260 ), in Kermanshah Province of Iran is simulated through SWAT hydrological model. Runoff simulation is done in a period of nine years from 2002 to 2010, where the first seven years of this period (2002-2008) is selected as a calibration period by using 14 various parameters and the two end years (2009 to 2010) as a validation period of model. The results of simulations during the calibration and validation periods are evaluated through two statistical indices namely Nash–Sutcliffe coefficient (NSE) and coefficient of determination (R2). According to compared simulated and observed monthly flow hydrographs and also calculated statistical coefficients, the SWAT model has acceptable results in simulating monthly runoff during both calibration and validation periods, so that the NSE and R2 coefficients are calculated equal to 0.7, 0.8 and 0.81, 0.9 for calibration and validation periods, respectively.

Study of water balance is absolutely important for investigation of the hydrology cycle, and preparation of water balance components in the watersheds requires many spatial data and their analyzing; so new technologies, models and tools such as GIS are needed. In this study, the SWAT model, which is a conceptual and semi-distributed model in the water and sediment balance simulation, was used in Aharchay watershed, Ahar, East Azarbayjan Province. Efficiency of the model in hydrologic simulation for this area is evaluated. Meteorology and hydrometers data of 1979-2010 was selected for this simulation; the average amount of rainfall and evapotranspiration were obtained 559.8 and 299.1 mm respectively. The period of 1982-2002 were used for calibration and 2003-2010 for validation. Calibration and validation processes were performed using SWAT-CUP software and PSO algorithm. Nash-Sutcliffe efficiency coefficients for water simulation were 0.39 for calibration and -6.7 for validation. Results showed that water balance simulation was not performed perfectly. Deficiency of required information and use of different data periods in calibration and validation were some of the effective factors which reduced the efficiency coefficients of the model.

The software implements standard statistical approaches commonly adopted in validation studies to estimate analytical method performance (limits of detection and quantitation, precision and accuracy). This software can also be used for tests to determine the normal distribution of data, to check the homogeneity of variances as well as a choices of method selection according to specific user needs. The importance of validation of analytical methods have been risen. Validated methods for the detection of genetically modified organisms (GMO) are requested by European :::::union::::: (EU) legislation in order to accept GMO crops on the European market. The AMPE software could be used to synchronize and standardize the results of the assessment of GMO in different countries and the competent authorities. In most cases, validation requires the assessment of the performance of the proposed method by means of an inter laboratory studies. This application has been developed based on international protocols ISO, Codex CCMAS and the ISO 5725 (1994). This software has to compare different methods and evaluate their adequacy with respect to specific needs, based on summarized information collected during the validation and recognition GMO crops.

In this paper the daily runoff of Ravansar Sanjabi basin (1260 Km^2), in Kermanshah Province of Iran is simulated through SRM hydrological model. The Snow Cover Area variable which a main and necessary variable in SRM model is calculated from MOD10A2 product of MODIS which separate snow cover maps with 8-day intervals. The runoff is simulated in a period of 2 years from 2002 to 2003, where 2002 (January 1 to December 31, 2002) is selected as a calibration period and 2003 (January 1 to 31 December, 2003) as a validation period of model. The results of simulations during the calibration and validation periods were evaluated through three statistical indices namely Nash–Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and volume difference (Dv). According to compared simulated and observed daily flow hydrographs and also calculated statistical coefficients in 2002 and 2003, the SRM shows appropriate and acceptable results in simulating daily runoff during both calibration and validation periods, so that the NSE coefficients are 0.9 and 0.85 for calibration and validation periods, respectively.

For an economic review of food prices in May 2019 to determine the trend of rising or decreasing prices compared to previous periods, we considered the price of food items at that time. The types of items consumed during specific periods in urban areas and the whole country are selected for our statistical analysis. Among the various methods of modelling and statistical prediction, and in a new approach, we modeled the data using data mining techniques consisting of decision tree methods, associative rules, and Bayesian law. Then, prediction, validation, and standardization of the accuracy of the validation are performed on them. Results of data validation in the urban and national area and the results of the standardization of the accuracy of validation in the urban and national area are presented with the desired accuracy.

High-performance liquid chromatography (HPLC) is recognized as a primary separation technique in modern pharmaceutical and biomedical analyses due to its exceptional efficiency and high sensitivity in detecting the analyte of interest. In the analysis of pharmaceutical samples, it is essential to ensure the reliability of the produced results. Method validation is a critical stage in the development of analytical methods, determining whether these methods are suitable and reliable for their intended purposes. The databases including PubMed, PubMed Central, Google Scholar, and ICHQ2R2 were searched using keywords such as HPLC, Validation, Accuracy, and Precision. To meet the requirements set by Good Manufacturing Practice (GMP) guidelines, pharmaceutical companies must establish a program to monitor and evaluate all their processes. The primary goal of this effort is to standardize all processes involved in the industry, including development, manufacturing, production, and analytical methods. This review article aims to provide insightful guidance on conducting validation for analytical methods that employed in pharmaceutical analysis. Specifically, it focuses on the validation process as per ICH Guidelines, which encompasses a comprehensive evaluation of performance characteristics such as accuracy, precision, specificity, linearity, working range, limit of detection, limit of quantification, robustness.