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Seasonal time-series modeling and forecasting of monthly mean temperature for decision making in the Kurdistan Region of Iraq
A generalized structural time-series modeling framework was used to analyze the monthly records of mean temperature, one of the most important environmental parameters, using classical stochastic processes. In this article we are using the SARIMA BoxâJenkins model and obtain a medium-term (10Â years) forecast of the mean temperature in Erbil. A prediction of the monthly mean temperature during the past 287Â months ((Formula presented.)24Â years) using the SARIMA(0,1,2)(0,1,1)12 model predicts that the average temperature in the governorate of Erbil, Iraq, will be stable for the next 10Â years. The evaluation of prediction accuracy shows that our model performs equally well when applying it to different periods of time for which data is available. The method used here could easily be applied by the decision makers responsible for providing water and electricity in the Kurdistan Region
Optimal Crop Water Allocation Based on Constraint-State Method and Nonnormal Stochastic Variable
Validation of the Short Version (TLS-15) of the Triangular Love Scale (TLS-45) Across 37 Languages
Love is a phenomenon that occurs across the world and affects many aspects of human life, including the choice of, and process of bonding with, a romantic partner. Thus, developing a reliable and valid measure of love experiences is crucial. One of the most popular tools to quantify love is Sternbergâs 45-item Triangular Love Scale (TLS-45), which measures three love components: intimacy, passion, and commitment. However, our literature review reveals that most studies (64%) use a broad variety of shortened versions of the TLS-45. Here, aiming to achieve scientific consensus and improve the reliability, comparability, and generalizability of results across studies, we developed a short version of the scaleâthe TLS-15âcomprised of 15 items with 5-point, rather than 9-point, response scales. In Study 1 (Nâ=â7,332), we re-analyzed secondary data from a large-scale multinational study that validated the original TLS-45 to establish whether the scale could be truncated. In Study 2 (Nâ=â307), we provided evidence for the three-factor structure of the TLS-15 and its reliability. Study 3 (Nâ=â413) confirmed convergent validity and testâretest stability of the TLS-15. Study 4 (Nâ=â60,311) presented a large-scale validation across 37 linguistic versions of the TLS-15 on a cross-cultural sample spanning every continent of the globe. The overall results provide support for the reliability, validity, and cross-cultural invariance of the TLS-15, which can be used as a measure of love componentsâeither separately or jointly as a three-factor measure
Predictors of Enhancing Human Physical Attractiveness: Data from 93 Countries
People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving ones physical attractiveness, are universal. Indeed, 99% of participants reported spending \u3e10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complementary perspectives
AnĂĄlise de risco e otimização de recursos hĂdricos e retorno financeiro em nĂvel de fazenda
Exploring Attitudes Toward âSugar Relationshipsâ Across 87 Countries: A Global Perspective on Exchanges of Resources for Sex and Companionship
The current study investigates attitudes toward one form of sex for resources: the so-called sugar relationships, which often involve exchanges of resources for sex and/or companionship. The present study examined associations among attitudes toward sugar relationships and relevant variables (e.g., sex, sociosexuality, gender inequality, parasitic exposure) in 69,924 participants across 87 countries. Two self-report measures of Acceptance of Sugar Relationships (ASR) developed for younger companion providers (ASR-YWMS) and older resource providers (ASR-OMWS) were translated into 37 languages. We tested cross-sex and cross-linguistic construct equivalence, cross-cultural invariance in sex differences, and the importance of the hypothetical predictors of ASR. Both measures showed adequate psychometric properties in all languages (except the Persian version of ASR-YWMS). Results partially supported our hypotheses and were consistent with previous theoretical considerations and empirical evidence on human mating. For example, at the individual level, sociosexual orientation, traditional gender roles, and pathogen prevalence were significant predictors of both ASR-YWMS and ASR-OMWS. At the country level, gender inequality and parasite stress positively predicted the ASR-YWMS. However, being a woman negatively predicted the ASR-OMWS, but positively predicted the ASR-YWMS. At country-level, ingroup favoritism and parasite stress positively predicted the ASR-OMWS. Furthermore, significant cross-subregional differences were found in the openness to sugar relationships (both ASR-YWMS and ASR-OMWS scores) across subregions. Finally, significant differences were found between ASR-YWMS and ASR-OMWS when compared in each subregion. The ASR-YWMS was significantly higher than the ASR-OMWS in all subregions, except for Northern Africa and Western Asia
Combined Effects of Numerical Method Type and Time Step on Water Stressed Actual Crop ET
Introduction: Actual crop evapotranspiration (Eta) is important in hydrologic modeling and irrigation water management issues. Actual ET depends on an estimation of a water stress index and average soil water at crop root zone, and so depends on a chosen numerical method and adapted time step. During periods with no rainfall and/or irrigation, actual ET can be computed analytically or by using different numerical methods. Overal, there are many factors that influence actual evapotranspiration. These factors are crop potential evapotranspiration, available root zone water content, time step, crop sensitivity, and soil. In this paper different numerical methods are compared for different soil textures and different crops sensitivities.
Materials and Methods: During a specific time step with no rainfall or irrigation, change in soil water content would be equal to evapotranspiration, ET. In this approach, however, deep percolation is generally ignored due to deep water table and negligible unsaturated hydraulic conductivity below rooting depth. This differential equation may be solved analytically or numerically considering different algorithms. We adapted four different numerical methods, as explicit, implicit, and modified Euler, midpoint method, and 3-rd order Heun method to approximate the differential equation. Three general soil types of sand, silt, and clay, and three different crop types of sensitive, moderate, and resistant under Nishaboor plain were used. Standard soil fraction depletion (corresponding to ETc=5 mm.d-1), pstd, below which crop faces water stress is adopted for crop sensitivity. Three values for pstd were considered in this study to cover the common crops in the area, including winter wheat and barley, cotton, alfalfa, sugar beet, saffron, among the others. Based on this parameter, three classes for crop sensitivity was considered, sensitive crops with pstd=0.2, moderate crops with pstd=0.5, and resistive crops with pstd=0.7. Therefore, nine different classes were formed by combination of three crop types and three soil class types. Then, the results of numerical methods were compared to the analytical solution of the soil moisture differential equation as a datum. Three factors (time step, initial soil water content, and maximum evaporation, ETc) were considered as influencing variables.
Results and Discussion: It was clearly shown that as the crops becomes more sensitive, the dependency of Eta to ETc increases. The same is true as the soil becomes fine textured. The results showed that as water stress progress during the time step, relative errors of computed ET by different numerical methods did not depend on initial soil moisture. On overall and irrespective to soil tpe, crop type, and numerical method, relative error increased by increasing time step and/or increasing ETc. On overall, the absolute errors were negative for implicit Euler and third order Heun, while for other methods were positive. There was a systematic trend for relative error, as it increased by sandier soil and/or crop sensitivity. Absolute errors of ET computations decreased with consecutive time steps, which ensures the stability of water balance predictions. It was not possible to prescribe a unique numerical method for considering all variables. For comparing the numerical methods, however, we took the largest relative error corresponding to 10-day time step and ETc equal to 12 mm.d-1, while considered soil and crop types as variable. Explicit Euler was unstable and varied between 40% and 150%. Implicit Euler was robust and its relative error was around 20% for all combinations of soil and crop types. Unstable pattern was governed for modified Euler. The relative error was as low as 10% only for two cases while on overall it ranged between 20% and 100%. Although the relative errors of third order Heun were the smallest among the all methods, its robustness was not as good as implicit Euler method. Excluding one large error of 50%, the average relative errors in this method was less than 10%. However, the ETc is time-dependent and varies from one day to another. So, averaging ETc over a larger time step brings about more error in computations. Accumulated relative error in Eta (ETp=5 mm.d-1, W0=Wj, t=1 d) under medium soil and crop type was decreased as the number of time steps increased, irrespective of the numerical method.
Conclusions: Based on practical considerations, we propose implicit Euler for its robustness, and 3-rd order Heun for its low maximum relative error for all combinations of soil and crop types
Adopting Hierarchial Cluster Analysis to Improve The Performance of K-mean Algorithm
Due to inadequate flood data it is not always possible to fit a frequency analysis to at-site stations. Reliable results are not always guaranteed by a single clustering algorithm, so a combination of methods may be used. In this research, we considered three clustering algorithms: single linkge, complete linkage and Ward (as hierarchial clustering methods), and K-mean (as partitional clustering analysis). Hybrid cluster analysis was tested for up-to-dated of floods data in 68 hydrometric stations in East and NE of Iran. Four cluster validity indices were used to find the optimum number of clusters. Based on the Cophenetic coefficient and average Silhouette width, single linkge, and complete linkage methods were performed well, yet they produced non-consistent clusters (one large and numerous small clusters) which are not amenable for flood frequency analysis. It was shown that hybridization was efficient to form homogeneous regions, however, the usefulness was dependent to the number of classes. Heterogeneity measure of Hosking was negative, due to inter-correlation of floods in the clusters. The hybrid of Ward and K-mean was shown to be the best combination for the region under study. Four homogeneous regions were delineated
Sensitivity Analysis of ETo for Five Current Models Using Monte-Carlo Simulation Case study: Bojnourd Synoptic Station
The objective of this study is to analyze the sensitivity of ETo for five models including FAO-Penman-Monteith, modified Blaney-Criddle, Hargreaves, Hargreaves-Samani and Priestley âTaylor. Daily meteorological data of Bojnourd synoptic station including air temperature, relative humidity, actual duration sunshine and wind velocity were used for sensitivity analysis of five models. In order to produce random data at a specific range, Monte-Carlo simulation was performed. Annual and seasonal were calculated to indicate the sensitivity of ETo in simultaneous variations of meteorological variables in each model.The results obtained in this study showed that the sensitivity of in simultaneous variations of meteorological variables is higher in summer. In all models, the most sensitivity was seen in summer and spring and the least sensitivity was occurred in autumn and winter. Among the studied models, FAO-PM and BC models had the most annual sensitivity and PT model had the least annual sensitivity. All of the models had fairly high correlation coefficient with FAO-PM model but the quantity of and was different in each model. BC model had the most and the least and was seen in and PT. According to the findings in this study, it can be concluded that SH model is fairly suitable for estimation of in synoptic station
A pseudo-continuous neural network approach for developing water retention pedotransfer functions with limited data
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