Using an independent cognitive-behavioral therapy (CBT) data set, the authors replicated T. Z. Tang and R. J. DeRubeis' (1999) discovery of sudden gains--sudden and large decreases in depression severity in a single between-session interval. By incorporating therapy session transcripts, the authors of this study improved the reliability of the Patient Cognitive Change Scale to .75 and found that these CBT sudden gains were also preceded by substantial cognitive changes in the pregain sessions.

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The backflow technique allows to accurate the intra-articular placement of the needle for "dry" knee joints injection. This technique can be proposed as a learning tool as well as a daily practice technique to ascertaining intra-articular knee injections without using fluoroscopy with injection of contrast material. Further studies are needed to assess the technique for other joint injections.

In advanced hip OA, the so-called "BME" MR lesion corresponds to a combination of edema, fibrosis, and necrosis at histopathology. When the classical "BME" is more specifically separated into edema-like and necrosis-like MR patterns, MR Imaging and histological findings show substantial agreement, with edema-like MR pattern mainly corresponding to histological edema.

Abstract. This paper aims to predict the trend of land use land cover (LULC) changes in Dak Nong province over time. Data from Landsat images captured in 2009, 2015, and 2018 was employed to analyze and predict the spatial distributions of LULC categories. The Random Forest (RF) was adopted to classify the images into ten different LULC classes. Besides, integration of Multi-Layer Perceptron Markov Neural Network (MLP-NN) with Markov Chain (MC) was applied to predict the future LULC changes in the region based on the change detection over the previous years. For all classified images, overall accuracy (OA) ranged from 77.35% to 84.55% with kappa (K) coefficient index ranging from 0.75 to 0.8. The results revealed that the annual population growth together with social-economic development was regarded as major drives for land conversion in the area. The predicted map showed a significant decrease trend inthe forest classes by 2025, accounting for 23 thousand ha. However, residential areas, rubber, and agricultural land classes are predicted to rise to 460 ha, 3,000 ha, and 20,000 ha, respectively. The simulated model and calibrated area data may be a vital contribution to sustainable development efforts of the local based on the dynamics of LULC and future LULC change scenarios. Overall, ascertaining the complex interface related to changes in land use and its major drivers over time provides useful information predict to explore the future trend of LULC changes, establish alternative land-use schemes and serve as guidelines for urban planning policymakers.