In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Geotechnical characterization of the sites has been investigated with the collection of borehole data from different sources. Using the data, grain size distribution curves have been developed to understand the particle size distribution of the alluvium present. These curves were further used for preliminary assessment of liquefiable areas. From geotechnical characterization, it has been observed that the soil profile in the two sites is dominated by sand and silty sand.Seed and Idriss (1971) approachhas been usedevaluatethe liquefaction potentialbydeterminationof the relation between the maximum ground acceleration (a max/g) valuesdue to an earthquake and the relative density of a sand deposit in the field. The results reveal that

يحتل موضوع الاستهلاك اهمية كبيرة في الدراسات الاقتصادية في حالتي السلم والحرب وذلك لارتباط هذا الموضوع بالانسان والمجتمع ولكونه احد مؤشرات مستوى الرفاهية الاقتصادية والاجتماعية وتزداد اهمية ضبط حركة هذا المتغير السلوكي والكمي في زمن الحرب اكثر مما هو عليه في حالة السلم، في هذا البحث تم استخدام بيانات احصائية عن الانفاق الاستهلاكي الخاص ونصيب الفرد من الدخل القومي اضافة الى الرقم القياسي لاسعار المس

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

Permanent deformation in asphalt concrete pavements is pervasive distress [1], influenced by various factors such as environmental conditions, traffic loading, and mixture properties. A meticulous investigation into these factors has been conducted, yielding a robust dataset from uniaxial repeated load tests on 108 asphalt concrete samples. Each sample underwent systematic evaluation under varied test temperatures, loading conditions, and mixture properties, ensuring the data’s comprehensiveness and reliability. The materials used, sourced locally, were selected to enhance the study ʼs relevance to pavement constructions in hot climate areas, considering different asphalt cement grades and con- tents to understand material variability ef

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi