The use of wood in outdoor applications causes problems such as dimensional change, WEATHERING and biological degradation. In this study, poplar wood was modified by three types of amino resins (melamine, melamine-urea and urea formaldehyde resins) and nano Zinc oxide (0, 0. 5 wt%). Then, the PHYSICAL properties and WEATHERING resistance of modified wood after six months natural WEATHERING were measured. The results showed that the treatment of wood with amino resins reduced water absorption and improved dimensional stability of samples in which melamine formaldehyde resin had the best performance. Moreover, the addition of nano zinc oxide to the amino resins enhanced their performance in improving dimensional stability of samples. The results of the colorimetry and microscopic images indicate that the treating by melamine formaldehyde reduced the color changes and surface morphology of the samples, although the use of nano zinc oxide did not have a positive effect in this regard.

Every year a huge amount of stones and according the investment on them are and wearing out of the building stones in the metropolis of mashhad. Marblite stones and granite has a durable resistance against the WEATHERING among the building stones use for the external walls. The type of WEATHERING in stones facades of the city of mashhad is PHYSICAL (mostly frost action). In other word PHYSICAL WEATHERING surmounts chemical WEATHERING. It has been also cleared that the rate of WEATHERING in building stones used in facades in the city of mashhad facing to the south is more than the other geographical directions.

ABSTRACT Despite a wide range of components and criteria affecting travel behavior presented through empirical research, the results of these studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different PHYSICAL developments affect travel behavior due to the differences in various PHYSICAL developments. The required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan in Tehran, Iran, as the old, conventional, and new neighborhoods, respectively. ANOVA test was exerted to analyze the significant difference between different development patterns in three neighborhoods. Dunnett's T3 was applied to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered that factors such as car ownership, dependence and pro-liking for private cars, density and access to educational centers and parks, access to medical and service centers, and variety and density of retail stores had been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a residence, dependence, and pro-liking for other than a private car, having a license, number of children under five years old, and age have influenced travel behavior regardless of the variation between neighborhoods. Extended Abstract Introduction Finding factors affecting travel behavior has been one of the main concerns of transportation planners. However, in the last two decades, the importance of the influence of the features of the built environment, including land use, along with demographic-economic characteristics, travel behavior, and attitudes of people, has been raised by urban planners. Studies seek to find factors affecting travel behavior, especially land use characteristics. Despite presenting a wide range of components and criteria affecting travel behavior, the results of the studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different PHYSICAL developments affect travel behavior due to the differences in various PHYSICAL developments. In order to do this, it must first be determined whether the study areas/different development patterns have a significant difference in terms of travel behavior or not. In case of a positive answer to the previous question, the following question is which study areas caused this difference. The next question arises: -Which PHYSICAL and non-PHYSICAL characteristics affect travel behavior due to distinctions between different development patterns?   Methodology The present research method is analytical and experimental based on quantitative methods. This research chose the frequency of travel by private car, public transportation, and walking as the travel behavior. According to the research's purpose, indicators and criteria affecting travel behavior were extracted after reviewing the theoretical and experimental literature. Then, the required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan as the old, conventional, and new neighborhoods, respectively. The questionnaire was compiled as a Likert scale in five parts of travel information, demographic-economic characteristics, perceptual characteristics of land use, travel habits, and access preferences of people in choosing their residence. ANOVA test was used to analyze the significant difference between different groups of a characteristic (here, different development patterns or the three case studies). Dunnett T3 was exerted to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered which factors affecting travel behavior were due to the differences in study areas and which factors affect travel behavior regardless of development patterns.   Results and discussion This research aims to identify the factors affecting travel behavior due to the differences in development patterns. In this regard, the findings in line with the first research question show that the frequency of three modes of travel, by private car, transportation, and pedestrian, differ significantly in the three neighborhoods. Furthermore, ANOVA test results depict that there is a significant difference between these three neighborhoods in terms of factors affecting travel behavior, such as perceptually environmental characteristics of the neighborhood, dependence and pro-liking for personal cars, variety and density of retail stores, density and access to educational units and parks, access to medical and service centers, and car ownership. Finally, by comparing the results of the ANOVA test with the regression analysis assessing the relationship between PHYSICAL and non-PHYSICAL factors (the same indicators in the same study areas) with travel behavior, the factors affecting travel behavior owing to different development patterns were identified. Factors such as car ownership, dependence and pro-liking for private cars, density and access to educational units and parks, access to medical and service centers, and variety and density of retail stores have been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a place of residence, dependence, and pro-liking for other than a private car, having a certificate, number of children under five years old, and age have influenced on travel behavior regardless of the variation between neighborhoods (different PHYSICAL development patterns).   Conclusion In In order to discover the factors affecting travel behavior due to the differences in patterns of PHYSICAL development, this research has provided a more detailed analysis of the factors affecting travel behavior. It has achieved more accurate components than previous studies in this regard. Detailed analysis of studies related to travel behavior and finding the main components affecting it, considering the extent of variables and data, can pave the way for professionals in transportation planning and urban planning, in addition to providing detailed methods and criteria in the related literature.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Background: The expansion of the use of audio and video media technology has faced society with many medical, cultural and economic challenges. In the meantime, excessive use of mobile phones can cause many problems. Objective: The aim of this study was to construct and validate a questionnaire on PHYSICAL and psychological injuries of mobile phones. Method: The method of the present study was descriptive-correlational and confirmatory factor analysis. The statistical population of the study consisted of all citizens of Khorramabad with a diploma or higher in 1399, which was selected as a statistical sample by available sampling method of 200 people online and virtual. Results: The results showed that the factorized PHYSICAL and psychological harm questionnaire of cell phone with 42 questions and 10 components (fear of loss, vibration syndrome, duck syndrome, nomophobia, insomnia, hearing problem, eye syndrome, tunnel and neck syndrome SMS) and has good reliability, validity and flexibility in terms of psychometrics. Discussion and Conclusion: The questionnaire of factor analysis of PHYSICAL and psychological injuries of mobile phones can be used to identify and study the PHYSICAL and psychological injuries of mobile phones.

Background and Objectives: Soil and groundwater contamination by petroleum hydrocarbons might cause negative environmental impacts. It may adversely affect soil PHYSICAL conditions and quality such as hydraulic properties via raising soil water repellency. Soil structure is an important PHYSICAL characteristic depending on pore size distribution and continuity, and it can affect several soil PHYSICAL and chemical processes. Soil structure might be affected by PHYSICAL WEATHERING processes such as wetting/drying and freezing/thawing cycles. It is possible to reproduce the natural soil structure in the laboratory by imposing wetting/drying and freezing/thawing cycles on the repacked soil samples. This would minimize the possible changes in soil structure during core sampling from the field. Few studies have been conducted about the interactive effect of oil contamination, soil texture and structure on soil water repellency and hydraulic properties. The present study aims to investigate the interaction effects of crude oil application, soil texture and WEATHERING-induced structure on soil water repellency and hydraulic properties.Methodology: In this study, the effect of crude oil application and PHYSICAL WEATHERING on water repellency and hydraulic properties of two soils (sandy loam and clay loam) was studied in a factorial experiment of completely randomized design with three replicates. Soil samples were collected from 025 cm layer of agricultural lands in Chaharmahal-va-Bakhtiari province, central Iran (sandy loam and clay loam soils were located in 32° 43' N 51° 59' E and 32° 29' N 50° 42' E, respectively). The soil was ground and sieved through a 4-mm mesh to exclude the gravel particles and plant residues. Crude oil was solved in the n-hexane and added to soil with the concentrations of 0.5 and 1 %w/w of total petroleum hydrocarbons (TPHs). Besides, a control without crude oil addition was included in the experiment. The treated soils were then poured into stainless cylinders (height and diameter of 5 cm) and packed to natural bulk density of 1.45 and 1.43 g cm-3 for sandy loam and clay loam soils, respectively. Half of the prepared soil samples were tested immediately and named “repacked” treatment and the rest wetted and dried for five months under normal conditions in the greenhouse and was named “PHYSICAL WEATHERING” treatment. Thus, a total of 36 soil samples were prepared (2 soil types × 3 levels of water repellency × 2 WEATHERING treatments × 3 replicates). Then, water repellency was determined by water drop pentetration time (WDPT) on the treated soil cores. Soil water characteristic curve and saturated hydraulic conductivity (Ks) were measured on the soil cores and modeled by van Genuchten equation. Soil PHYSICAL quality indicators including field capacity (FC), permanent wilting point (PWP), available water colntent (AWC), macroporosity (Macro-P), mesoporosity (Meso-P), microporosity (Micro-P), and Dexter’s index for soil PHYSICAL quality (SDexter) were calculated as well.Findings: The results showed that soil hydraulic properties were significantly affected by the experimental treatments. Water retention was greater in the clay loam soil compared to the sandy loam soil. Oil contamination reduced soil water retention at all matric suctions (0 to 15000 cm) due to oil-induced water repellency and soil resistance against wetting (as observed by an increment in WDPT). The effect of oil contamination on water retention was greated in the sandy loam soil than in the clay loam soil due to lower specific surface area of coarse-textured soils. The Ks, saturated water content (s) and residual water content (r) decreased, and scaling () and shape (n) parameters increased significantly due to oil-induced water repellency. The Ks of 1% TPHs-treated samples (i.e., 5.64 cm h-1) was significantly lower than that of control (i.e., 7.98 cm h-1). The s and r significantly decreased by 1% oil contamination (i.e., 0.457 and 0.112 cm3 cm-3) compared to the control (i.e., 0.547 and 0.122 cm3 cm-3), respectively. However, the parameters  and n were significantly greater in the 1% TPHs-treated samples (i.e., 0.240 cm-1 and 1.56) compared to the control (i.e., 0.130 cm-1 and 1.36), respectively. PHYSICAL WEATHERING significantly increased s. The The Ks and Macro-P were significantly greater in the sandy loam soil whereas the Meso-P and Micro-P were significantly greater in the clay loam soil. The FC, PWP and AWC were significantly greater in the clay loam soil than in the sandy loam soil. The FC, PWP, Meso-P and Micro-P decreased but the Macro-P and SDexter increased in the oil-contaminated soil samples. The AWC significantly decreased from 0.084 (control) to 0.049 cm3 cm-3 due to 1% oil contamination. PHYSICAL WEATHERING intensified the oil-induced water repellency (i.e., an incement in WDPT from 23.9 in repacked soil to 30.2 s in weathered soil), and reduced water retention in the sandy loam soil more than in the clay loam soil. The Ks, Macro-P and Micro-P were significantly greater in the weathered soil samples than in the repacked ones.Conclusion: As coarse-textured soils with low specific surface area are more prone to water repellency compared to fine-textured soils, they became water-repellent quicker upon PHYSICAL WEATHERING. It seems that PHYSICAL WEATHERING stimulated soil structure formation and intensified the oil-induced water repellency. The findings of this study are important for the management of oil contamination in different soil (texture and structure) conditions.

In this study, the effect of propionylation on the WEATHERING resistance of eastern cottonwood was investigated. The samples were propionylated under different reaction temperatures and times, and then the treated samples were exposed to natural WEATHERING for 180 days. The color change of the propionylated wood was evaluated before and after WEATHERING for time interval (40, 80 and 180 days). In addition, the surface roughness of the specimens was measured before and after WEATHERING. The statistical analysis was done using Kruscal Wallis at the confidence level of 95% showed that propionylation reduced significantly the color change (turning grey) due to WEATHERING. The color change reduced when the WPG increased. At the end of the exposure time to WEATHERING, the surface roughness of the treated samples was 16.4% less than that for the control (untreated) samples but the difference was not statistically significant.