High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall s

The use of Near-Surface Mounted (NSM) Carbon-Fiber-Reinforced Polymer (CFRP) strips is an efficient technology for increasing flexural and shear strength or for repairing damaged Reinforced Concrete (RC) members. This strengthening method is a promising technology. However, the thin layer of concrete covering the NSM-CFRP strips is not adequate to resist heat effect when directly exposed to a fire or at a high temperature. There is clear evidence that the strength and stiffness of CFRPs severely deteriorate at high temperatures. Therefore, in terms of fire resistance, the NSM technique has a significant defect. Thus, it is very important to develop a set of efficient fire protection systems to overcome these disadvantages. This pape

Many international studies indicated that the polymorphisms of some genes disturbed the folate homocysteine (Hcy) metabolism and increased the vulnerability to Down syndrome (DS). We aimed to measure the serum levels of folate and Hcy in DS children and compare the levels with age and sex-matched apparently normal healthy children. We also aimed to study the A80G polymorphism of the gene reduced folate carrier (RFC1) in the DS children as a risk factor. Forty children with DS (24 were boys, and 16 were girls) with the age range between 5-13 years, and 26 normal healthy children (16 boys and ten girls) were included in this study. The results show that the highest genotype in the control group was AG (53.85%) followed by AA and GG (30.

The public budget is regarded a main tool for economic and social development. The preparation of the public budget constitute an important stream which enriches the developmental efforts and the definition of its priorities, therefore it is the focus point of many specializations. The public budget has numerous functions. It is a means to precise and to execute the political and economic goals of the executive authority, a mirror of the economic structure which reflects its strength and weakness points, specifies its revenues and others. Since the parliament is the voice of the society which expresses its interests, then, it must monitor the performance of the government so that the participation of the legislative authority in

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Cervical Uterine Cancer is a disease that explains the vulnerability in which women are in terms of reproductive health with an impact on occupational health and public health, even when in Mexico the prevalence rate is lower than the other member countries of the OECD, its impact on Human Development and Local Development shows the importance that the disease have in communities more than in cities where prevention policies through check-ups and medical examinations seem to curb the trend, but show the lack of opportunities and capacities of health centers in rural areas.   To establish the reliability, validity, and correlations between the variables reported in the literature with respect to their weighting in a public hospital. A

Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

The establishment of international funds to compensate for human rights violations represents an important step towards achieving justice and equality between individuals and societies and solidarity among people, whether through providing financial assistance or by assuming legal and moral responsibility towards victims. With the development of international policies in recent decades, it has become necessary for states to assume their responsibilities in accordance with international law, not only in preventing and combating crimes, but also in providing means of redress for victims. Legislation in many countries has demonstrated the importance of fair compensation as part of criminal and social responsibility. Although traditiona

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an