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.

The characteristics of vertical ground reaction Force (VGRF) gait Patterns in children with autism spectrum disorders (ASD) are poorly understood. The purpose of this study was to identify VGRF gait features that discriminate between children with ASD and the peer control group. The VGRF data were obtained from 30 children with ASD and 30 normal healthy children aged 4 to 12 years. A three-dimensional motion analysis system with eight cameras and two Force plates were used to collect VGRF data while subjects performed self-selected speed of barefoot walking. Parameterization techniques were applied to VGRF waveforms to extract the VGRF gait features. Mean significant differences between the two groups were tested using independent samples t-test and Mann-Whitney U test. Significant group differences were found for four VGRF gait features. Results indicated that children with ASD exhibited a significant reduction of the second peak of VGRF, earlier relative time to the occurrence of the second peak of VGRF, lower push-off rate, and higher peak ratio of the two VGRF peaks during normal speed of walking. These prominent differences showed that children with ASD had difficulties in supporting their body weight during terminal stance phase and these conditions affect the gait instability. The findings of this study develop further understanding of VGRF gait Patterns that significantly differentiate between children with ASD and the peer control groups.

Background and Aim: Superelasticity refers to the same amount of Force exerted by an ideal archwire independent of the degree of activation. Clinical findings show that in most of situations these materials do not fulfill the expected properties. The aim of this study was to evaluate the bending properties of some of these archwires.Materials and Methods: In this experimental research eight specimens of each of the round wires with 0.14, 0.16 and 0.018 inch sizes of Force I, rematitan lite and superelastic G & H types were tested. These wires were subjected to a three point bending test by DARTEC machine. Data were tested by ANOVA and Duncan tests at 0.05 level of significance. Results: All of these materials showed superelastic properties or at least superelastic tendencies. More pronounced superelastic properties were observed in thicker wires. However, their Force level of plateau for 0.014 inch rematitan lite wires the end of the plateau was observed when the wire was displaced at least 0.6 mm.Conclusion: In all of these wires, the Force level of plateau was higher than the optimal Force required for tipping movements.

An injury is defined as illegally caused harm to any person’s body, mind reputation or property. In practice, injuries often consist of combination of several basic injury types and usually classified according the predominant injury type. The wounding process and distribution of injuring Force are governed by equations of motion physics. However, the purpose Legal judgment demands the forensic medical expert, as an independent witness, to explain those complex biophysical remedies in the context of the common legal sense, which can be easily understood by the courts. Therefore, we suggest the following simple biomechanical classification of wounding process that could serve the purpose; light Force, moderately heavy Force and heavy Force injuries.

At first, an embryo has no front or back, head or tail. It’, s a simple sphere of cells. But soon enough, the smooth clump begins to change. Fluid pools in the middle of the sphere. Cells flow like honey to take up their positions in the future body. Sheets of cells fold origami-style, building a heart, a gut, a brain. None of this could happen without Forces that squeeze, bend and tug the growing animal into shape. Even when it reaches adulthood, its cells will continue to respond to pushing and pulling —,by each other and from the environment. Yet the manner in which bodies and tissues take form remains “, one of the most important, and still poorly understood, questions of our time”, , says developmental biologist Amy Shyer, who studies morphogenesis at the Rockefeller University in New York City. For decades, biologists have focused on the ways in which genes and other biomolecules shape bodies, mainly because the tools to analyse these signals are readily available and always improving. Mechanical Forces have received much less attention.

Introduction: In orthodontic treatment a proper bond is essential between the enamel and the bracket. Evaluation of the efficacy of different adhesives for bonding orthodontic brackets to enamel has yielded different results. This study aimed to compare the shear bond strength and adhesive remnant index (ARI) of metal brackets bonded by Transbond XT, Ortho-Force and Resilience composites.Materials& Methods: Sixty extracted intact upper maxillary first premolars were selected for the purpose of this in vitro study. The teeth were randomly divided into three groups (n=20). The teeth were bonded with were bonded with Transbond XT, Resilience and Ortho-Force composites in groups 1, 2 and 3, respectively. After 24 hours, shear bond strength test was conducted at a crosshead speed of 0.05 mm/min. ARI scores were evaluated under a stereomicroscope. The results of shear bond strength test were analyzed with ANOVA and Tukey tests. ARI results were analyzed with chi-squared test (a=0.05).Results: Shear bond strengths were significantly different between the three groups (p value<0.001). Transbond XT composite exhibited the highest bond strength (15.26 MP) and Ortho-Force composite had the lowest bond strength (11.96 MP). There were no statistically significant differences in ARI between the three groups p value=0.561).Conclusion: Although the mean shear bond strength of Ortho-Force composite was less than the two other composites, it is still clinically acceptable.