Block pavements are widely used in various infrastructures, offering durability and aesthetic appeal. However, assessing their condition through manual methods is resource-intensive and subjective. This study proposes a deep learning approach using the Hybrid TransUNet model to enhance the accuracy and efficiency of detecting block pavement distresses. A dataset of over 10,000 images was used to train and test binary and multiclass segmentation models, significantly improving detection accuracy. The results show that the Hybrid TransUNet model outperforms other models, though challenges in detecting certain distress types like cracks persist.

In order for concrete to have good strength and durability, proper vibration is required. If the concrete does not vibrate completely, honeycomb can form in the concrete, which can reduce the strength and durability of the concrete. Two methods are presented that can be used to check whether a honeycomb is formed depending on whether the concrete is fresh or hardened. For fresh concrete, where a metal ball of the same size as aggregate is placed on a concrete surface and the vibration time is observed until the ball is completely sunk, an impact echo test can be used to check whether a honeycomb is present. Based on concrete surface and strength tests, we showed that this method can be used to detect honeycomb.

PURPOSES : A model for minimizing cutting loss and determining the optimum layout of blocks in pavements was developed in this study. METHODS : Based on literature review, a model which included constraints such as the amount, volume, overlap, and pattern, was developed to minimize the cutting loss in an irregular pavement shape. The Stach bond, stretcher bond, and herringbone patterns were used in this model. The harmony search and particle swarm algorithms were then used to solve this model. RESULTS : Based on the results of the model and algorithms, the harmony search algorithm yielded better results because of its fast computation time. Moreover, compared to the sample pavement area, it reduced the cutting loss by 20.91%. CONCLUSIONS : The model and algorithms successfully optimized the layout of the pavement and they have potential applications in industries, such as tiling, panels, and textiles.

Sarcomatoid carcinoma is rarely diagnosed as gallbladder cancer. Its aggressive nature, due to the characteristics of both sarcoma and carcinoma, results in a poor prognosis. We report a case of gallbladder sarcomatoid carcinoma in an 82-year-old male who was referred to our hospital for evaluation of gallbladder cancer observed on abdominopelvic computed tomography. The characteristics of the cancer were not confirmed after several imaging modalities. The surgically resected tumor was positive for both cytokeratin and vimentin as revealed via immunohistochemical staining, and a sarcomatoid carcinoma was finally diagnosed. The role of chemotherapy has not yet been identified. Therefore, radiation therapy is planned to reduce the risk of recurrence.

PURPOSES : The objective of this study is to understand blow-up distress and causes in concrete pavement. METHODS : Feasible causes of blow-up and existing models were reviewed based on the literature. Three analytical models were adopted to perform a sensitivity analysis. Input parameters reflected the typical concrete pavement of national expressways. Evaluation of blow-up models was based on the amount of temperature increase and zero stress temperature of the concrete pavement. RESULTS : A review of the literature indicated that the five major causes of blow-up were: increase in temperature and solar radiation, alkaliaggregate reaction (AAR), friction characteristics between the concrete slab and subbase, joint closure (incompressible), and joint freezing. The sensitivity analysis revealed that the coefficient of thermal expansion had the greatest influence on the blow-up safety temperature. CONCLUSIONS : From existing blow-up model results, it could be concluded that the construction of concrete pavement during the winter season was not effective at preventing blow-up. In addition, an equivalent coefficient of thermal expansion that considers slab expansion due to AAR was proposed as a model input parameter for concrete pavement sections damaged by AAR.