Access Road Construction of the Larsi Building Using Reinforced Earth Walls

Mountainous road construction is one of the most difficult and challenging problems in geotechnical engineering. Geometrical complexities and geotechnical conditions make them different from many other urban projects. Retaining wall system is a principal part of these projects. Reinforced Earth Wall system can be considered as an appropriate option for mountainous road construction. In this case history, access road construction of the LARSI building (Shemshak-Iran) is discussed. Shemshak is a tourist town which is located in southern hillsides of the Alborz Mountains. Therefore, the access road is an essential component particularly in cold seasons. Nine terraced levels of the reinforced earth wall were designed according to the geometrical considerations. The walls’ reinforcements were evaluated by TALREN 4 V.2.0.3. There had been some limitations, etc. which resulted in many challenges during the construction. This project was constructed in six months

Lung infection segmentation for COVID-19 pneumonia based on a cascade convolutional network from CT images

The COVID-19 pandemic is a global, national, and local public health which causing a significant outbreak in all countries and regions for both males and females around the world. Automated detection of lung infections and their boundaries from medical images offers a great potential to augment the patient treatment healthcare strategies for tackling COVID-19 and its impacts. Detecting this disease from lung CT scan images is perhaps one of the fastest ways to diagnose the patients. However, finding the presence of infected tissues and segment them from CT slices faces numerous challenges, including similar adjacent tissues, vague boundary, and erratic infections. To overcome the mentioned problems, we propose a two-route convolutional neural network (CNN) by extracting global and local features for detecting and classifying COVID-19 infection from CT images. Each pixel from the image is classified into normal and infected tissue. For improving the classification accuracy, we used two different strategies including Fuzzy c-mean clustering and local directional pattern (LDN) encoding methods to represent the input image differently. This allows us to find a more complex pattern from the image. To overcome the overfitting problems due to small samples, an augmentation approach is utilized. The results demonstrated that the proposed framework achieved Precision 96%, Recall 97%, F-score, average surface distance (ASD) of 2.8\pm0.3\ mm and volume overlap error (VOE) of 5.6\pm1.2%

The Effect of IT Alignment on Business and Manufacturing Organization Approaching the Balanced Score Card IT

The alignment of IT and Business is one of the major issues for the Information Technology Managers and the senior managers in organizations. This article which is to study the rate of alignment of IT among the managers and engineers in manufacturing sections has been done in one of the biggest industrial districts in Iran, industrial district of Semnan. With the regard to the goal, this is an applicable study, and it is considered as a descriptive survey study regarding the data gathering. The statistics' samples were done by sampling randomly among a class, including 300 managers and engineers of manufacturing section. To gather the data, a self – made method, including 35 questions of 4 basic dimensions has been used.  The reliability of tools through analyzing the discovering factor as KMO indicator can be used, that is 0.827 and 0.000 for Bartlett's Test emphasizing the test reliability.  For stability, both Cronbach's Alpha was used that is 0.90 and for analyzing the data, the software of LISREL 8.80 structural model – finding was used. The results show that the most effective factor among the four basic components is the indicator of collaboration and contribution to business, and the least effect is on foresight. Moreover, among the sub variable realizing the capabilities and producing the opportunity is the most effective one

Clinical Evaluation of the Diagnostic Role of MicroRNA-155 in Breast Cancer

Aim. Biochemical markers, including microRNAs (miRs), may facilitate the diagnosis and prognosis of breast cancer. This study was aimed at assessing serum miR-155 expression in patients with breast cancer and receptors. Methods. This case-control study was conducted on 36 patients with breast cancer and 36 healthy individuals. After RNA extraction from the patient’s serum, cDNA was synthesized. The expression of miR-155 was measured using RT-qPCR. Demographic and histochemical data were extracted from patient documents. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) software. Results. The mean age of subjects in breast cancer and control groups was 47.64±8.19 and 47.36±7.52 years, respectively. The serum miR-155 expression was higher in the cancer group (1.68±0.66) compared to the control group (p<0.0001). There was a significant relationship between serum miR-155 expression and the tumor grade (p<0.001), tumor stage (p<0.001), and tumor size (p<0.001) of the patients. However, no relationship between miR-155 expression and the presence of lymph node involvement (p=0.15), HER2 (p=0.79), Ki-67 (p=0.9), progesterone receptor (p=0.54), and estrogen receptors (p=0.84) was found. The ROC curve analysis showed that the AUC was 0.89 (77.78% sensitivity and 88.89% specificity), and the cutoff was 1.4 (Youden index: 0.6667) for detecting breast cancer. Conclusion. The findings of this study revealed that serum miR-155 may serve as a potential noninvasive molecular biomarker for breast cancer diagnosis and can help predict the grade of the disease

Osteolysis: a literature review of basic science and potential computer-based Image processing detection methods

Osteolysis is one of the most prominent reasons of revision surgeries in total joint arthroplasty. is biological phenomenon is induced by wear particles and corrosion products that stimulate inflammatory biological response of surrounding tissues. e eventual responses of osteolysis are the activation of macrophages leading to bone resorption and prosthesis failure. Various factors are involved in the initiation of osteolysis from biological issues, design, material specifications, and model of the prosthesis to the health condition of the patient. Nevertheless, the factors leading to osteolysis are sometimes preventable. Changes in implant design and polyethylene manufacturing are striving to improve overall wear. Osteolysisis clinically asymptomatic and can be diagnosed and analyzed during follow-up sessions through various imaging modalities and methods, such as serial radiographic, CT scan, MRI, and image processing-based methods, especially with the use of artificial neural network algorithms. Deep learning algorithms with a variety of neural network structures such as CNN, U-Net, and Seg-UNet have proved to be efficient algorithms for medical image processing specifically in the field of orthopedics for the detection and segmentation of tumors. ese deep learning algorithms can effectively detect and analyze osteolytic lesions well in advance during follow-up sessions in order to administer proper treatments before reaching a critical point. Osteolysis can be treated surgically or nonsurgically with medications. However, revision surgeries are the only solution for the progressive osteolysis. In this literature review, the underlying causes, mechanisms, and treatments of osteolysis are discussed with the main focus on the possible computer-based methods and algorithms that can be effectively employed for the detection of osteolysis