Arch dams are generally built in cantilever monoliths. Vertical contraction joints between monoliths control the stresses due to concrete shrinkage and temperature variations. Past studies in earthquake safety evaluation of the system often show the tensile fracture and local nonlinear deformation of joints. In this paper, some nonlinear joint element constitutive models are presented to examine the tensile and shear fractures of joints. Reservoir hydrodynamic interaction and water compressibility are considered in the finite element analysis of the system. Some primary examples were studied for numerical examination of the models. Also earthquake response of "Morrow Point" arch dam was calculated. Regarding the numerical results, efficiency of the proposed models is promising for safety evaluation of arch dams under static and dynamic loads.  

In this paper, we first introduce semi-parametric heteroscedastic hierarchical models. Then, we define a new version of the empirical likelihood function (Restricted Joint Empirical likelihood) and use it to obtain the shrinkage estimators of the models' parameters in these models. Under different assumptions, a simulation study investigates the better performance of the restricted joint empirical likelihood function in the analysis of semi-parametric heterogeneity hierarchical models. Furthermore, we analyze an actual data set using the RJEL method.

Evaluating the cutting rate (CR) of stones is important in the cost estimation and the planning of the stone processing plants. This research used regression models to estimate the stones’ CR based on their physico-mechanical characteristics. Stone processing factories in Mahallat City (Markazi province, Iran) were visited, and the CR of diamond circular saws was recorded on six different travertine stones. Next, the stone block samples were collected from the quarries for laboratory tests. Stones’ porosity (n), uniaxial compressive strength (UCS), and Schmidt hammer hardness (SH) were determined in the laboratory as their physico-mechanical characteristics. Correlation relationships of CR with physico-mechanical characteristics were evaluated using simple and multiple regression analyses, and estimator models were developed. Results showed that multiple regression models are more reliable than simple regression for estimating the stones’ CR. The validity of the developed multiple regression models was verified with the published data of one researcher. The findings indicated that these models are accurate enough for estimating the CR of stones. Consequently, the multiple regression models provide practical advantages for estimating the CR and save time and cost during the planning and design of the stone processing factories.

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.

Background: One of the major challenges in orthopedic surgery is the prevention of arthrofibrosis, which can be successfully alleviated in its early stages. Many studies suggest the administration of methylene blue (MB) as an accessible and effective agent for the prevention of post-operation adhesions. The purpose of this study was to evaluate the efficacy of MB in the prevention of arthrofibrosis. Methods: This study was conducted on 18 New Zealand white female mature rabbits. The anterior cruciate ligament of the left stifle joint of each animal was cut during aseptic surgery. In the next step, the rabbits were divided into three groups based on their treatments. The rabbits in the first, second, and third groups were subjected to the injection of normal saline, 1% MB solution, and 2% MB solution into their synovial space, respectively. The postoperative stifle range of motion was measured every week. After 4 weeks, the animals were euthanized and all joints were dissected for histopathology. Results: The histopathological evaluation of tissues indicated the presence of fibrotic connective tissue as a sign of fibrosis in all groups. The fibrosis rate, inflammatory rate, tissue disarrangement, fibroblastic cellularity, and granulation tissue formation were at their highest levels in the 1% MB group. The integrity of articular cartilage in the 2% MB group was lower than the other groups. The level of bone degeneration was similar in both MB groups; however, it was more than the control saline group. The range of motion was reduced during the first week, then increased in the second and third weeks, and finally decreased in the fourth week. Conclusion: The MB was not an effective method regarding the prevention or treatment of arthofibrosis and the subsequent osteoarthritis. In contrast with previous studies, fibrosis was lower in the high dose MB group, compared to the low dose MB group. The alterations in the range of motion were related to the reduced movement caused by the pain and stiffness of the operated joints. The current study can be considered as the first report addressing the adverse effect of MB on synovial components.