This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compared to traditional regression models: These estimates are robust to outliers and heterogeneous spatial effects and capture fully conditional distributions with respect to mean regression models. The review supports future work toward enhancing estimation approaches and possible SARQR application extensions to other fields. The spatial modeling has applicability in the research, decision-making, and profession formulation because it encourages a broader SARQR application in economic analysis, infrastructure planning, and public health policy. Future research must aim at refining estimation methods and integrating SARQR with other models of analysis to optimize its usefulness in utilizing sophisticated spatial data.
Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how
... Show MoreAny harm done to genetic material, whether directly interacting with DNA or indirectly through biological systems, is referred to as genotoxicity. Such harm poses major risks to the health of people, animals, and plants as it is a primary source of carcinogenesis, mutagenesis, and teratogenesis. Because of their medicinal qualities, alkaloids—a family of naturally occurring phytochemicals made by plants from amino acids—are frequently utilized to treat ailments such newborn apnea, gout, and asthma. Recent research has sparked worries about their possible genotoxic consequences despite their therapeutic advantages. Through a variety of processes, including as the creation of DNA adducts, DNA–DNA cross-links, and DNA–protein c
... Show MoreANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreThe optical absorption data of Hydrogenated Amorphous Silicon was analyzed using a Dunstan model of optical absorption in amorphous semiconductors. This model introduces disorder into the band-band absorption through a linear exponential distribution of local energy gaps, and it accounts for both the Urbach and Tauc regions of the optical absorption edge.Compared to other models of similar bases, such as the O’Leary and Guerra models, it is simpler to understand mathematically and has a physical meaning. The optical absorption data of Jackson et al and Maurer et al were successfully interpreted using Dunstan’s model. Useful physical parameters are extracted especially the band to the band energy gap , which is the energy gap in the a
... Show MoreIt is very well known in the planning publications that when creating spacing development to a region or sub-region, it can be able to make more than an alternative consisting with the strategic directions overtaken from the actual development of region and the situational and developmental objectives needed. However, the difficulty facing the situational planning is in selecting one of these alternatives to be the best in order to make a balanced situational re-structure, and achieving the economic, social and civil objectives. The developmental situation elements in the regions and governorates, including (Karbala) impose themselves as situational power which implies the process of re-structural arrangement where the situational develo
... Show MoreThe unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I
... Show More Aluminum alloys widely use in production of the automobile and the aerospace because
they have low density, attractive mechanical properties with respect to their weight, better
corrosion and wear resistance, low thermal coefficient of expansion comparison with traditional
metals and alloys. Recently, researchers have shifted from single material to composite materials
to reduce weight and cost, improve quality, and high performance in structural materials.
Friction stir processing (FSP) has been successfully researched for manufacturing of metal
matrix composites (MMCs) and functional graded materials (FGMs), find out new possibilities
to chemically change the surfaces. It is shown th
The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreThe research investigates the physical characteristics of the Euphrates River water in the Abu Ghraib district, where the river flows southwest, demarcating it from Anbar Governorate. Geographically, the area lies between latitudes 33°8'40" - 33°15'23" N and longitudes 43°50'21" - 44°1'24" E. The study is based on fieldwork and laboratory analyses aimed at detecting pollution by analysing four physical parameters during summer and winter. These physical properties include water temperature, turbidity, dissolved solids, and electrical conductivity. To elucidate pollution levels, the study area was divided into ten sites along the river. By examining pollution indicators through samples taken from these sites and comparing them to
... Show MoreThis paper deals to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th
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