Technical Approach to Environmentally Sustainable Architecture in Jordan

Sustainable architecture is a major subject in glow of the environmental degradation that the world faces today. This paper disputes that there is a need in Jordan to expand the technical understanding of sustainable architecture to integrate the socio-cultural features in its production. The need appears in which that Jordan architects have failed to distinguish the worth of the social dimension in facilitating the improvement of sustainable trends. One of the end solutions have been urbanized to improve the energy effectiveness regarding to construction that require high initial venture and are based on technical issue. Furthermore, end low cost techniques like old mud architecture were developed which don’t fit in with the goals of the upward movable urban population such as Bedouins. Technical issue is then seen as the only way of addressing environmental poverty. The role of society such as consumers, customers and decision makers for sustainable architecture has been ignored.  The outcomes are important as this issue is of certain relevance for developing countries for instance Jordan that are still in the process of industrializing but are so far to meet the high costs of development. Both urbanization and housing expansion take a heavy charge on the environment and the need of suitable techniques and sustainable construction suggests that the architectural vocation has failed to distinguish the vital need for developing socially suitable sustainable architectural practices for Jordan. Keywords: sustainable architecture, energy efficient constructions, and social sustainability, Jorda

The effectiveness of Guided-Discovery Strategy Supported by the Technology of Augmented Reality on Acquiring Mathematical Concepts for Grade Four Male Students in Jordan.

This research aimed to know the effectiveness of guided discovery supported by augmented reality technology in acquiring mathematical concepts among fourth-grade students in Jordan. The quasi-experimental approach was adobted. To achieve the goal of this research, a teacher’s guide and a mathematical concepts test were developed. The validity and reliability of instruments were confirmed. The research members consist of (40) students in the first semester of 2020/2021, They were distributed equally into two groups: the experimental group studied using the suggested strategy and the control group studied using the usual way .The results showed that there were statistically significant difference at the level of significance (α = 0.05) in the acquisition of mathematical concepts in favor of the experimental group. The research recommended generalizing the experience to different subjects and conducting other new studies on different classes and variables

Digital Models Used in Documenting the Mosaic Areas

Digital models are considered the most important in documenting the mosaic floors tools. So, take advantage of the high capabilities in monitoring and documentation, analysis and manifesting required by the mosaic floors and murals. Also, these digital models dealing with large amounts of spatial and metadata. This means that the use of the large data that is collected from the mosaic floors and electronic transfers, which allows more than one user to access or manage and edit them to give wider dissemination horizon. Consequently, they contribute to the electronic documents for floors mosaic mural. This study shows that the numerical models can be used to perform various analyzes in documenting mosaic flooring. Keywords: Geographic Information System (GIS), spatial support decision-making (SDSS), remote sensing (RS), digital modeling (DM), mosaic floors (MF

Stepwise Relationship of Exercise Frequency with Serum BDNF Level among Adolescents

Introduction: Regular participation in exercise in adolescents is associated with numerous health benefits, including improved CV, metabolic, muscular, respiratory, immune, cognitive, and neurohormonal functions. Brain-derived neutrophic factor (BDNF) is essential for several body functions, particularly the neural and cognitive functions. However, the dose-effect of exercise participation on BDNF is not fully understood among adolescents. The current study examined the relationship of serum BDNF level with moderate/vigorous exercise frequency in 703 adolescents aged 13-17 years old. Methodology: ELISA was used to evaluate serum BDNF. Additionally, the SALSA questionnaire was used to obtain the weekly frequency of moderate/vigorous exercise. Results: The ANOVA revealed differences (p=0.001) in BDNF level according to running frequency. Subsequent posthoc analysis showed that BDNF was greater (p0.05) were found in BDNF between exercising three, four, five, six, and seven days/week. Conclusions: The current data revealed stepwise differences in BDNF between running frequencies, peaking at five days/week. These differences in BDNF seems to plateau when participating more than three days/week. The results confirm the importance of exercise for brain health and are consistent with the current recommendations for moderate/vigorous exercise frequenc

The Clinical and Nonclinical Values of Nonexercise Estimation of Cardiovascular Endurance in Young Asymptomatic Individuals

Exercise testing is associated with barriers prevent using cardiovascular (CV) endurance (CVE) measure frequently. A recent nonexercise model (NM) is alleged to estimate CVE without exercise. This study examined CVE relationships, using the NM model, with measures of obesity, physical fitness (PF), blood glucose and lipid, and circulation in 188 asymptomatic young (18–40 years) adults. Estimated CVE correlated favorably with measures of PF (r = 0.4 − 0.5) including handgrip strength, distance in 6 munities walking test, and shoulder press, and leg extension strengths, obesity (r = 0.2 − 0.7) including % body fat, body water content, fat mass, muscle mass, BMI, waist and hip circumferences and waist/hip ratio, and circulation (r = 0.2 − 0.3) including blood pressures, blood flow, vascular resistance, and blood (r = 0.2 − 0.5) profile including glucose, total cholesterol, LDL-C, HDL-C, and triglycerides. Additionally, differences (P < 0.05) in examined measures were found between the high, average, and low estimated CVE groups. Obviously the majority of these measures are CV disease risk factors and metabolic syndrome components. These results enhance the NM scientific value, and thus, can be further used in clinical and nonclinical settings

Adaptive Localization of Focus Point Regions via Random Patch Probabilistic Density from Whole-Slide, Ki-67-Stained Brain Tumor Tissue

Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved

Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm

Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD) algorithm to solve the initialization problem, detecting irregular circles (cells), selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs