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[DISSEMINATED CARCINOMATOSIS OF THE Bone fragments MARROW Together with UROTHELIAL CARCINOMA].
Further investigation of the designated features in terms of their spectral and localization properties revealed task-independent common patterns in the neural mechanisms governing workload. In particular, increased workload was associated with elevated frontal delta and theta power but reduced parietal alpha power, whereas FC exhibited complex frequency- and region-dependent alterations. By implication, the employment of the EEG feature fusion emphasizes their utility in serving as promising indicators for different workload conditions applications.This study investigated the localization ability of an impulse vibration source outside the body in two-dimensional space. We tested whether humans can recognize the direction or distance of an impulse vibration source when using their hand to detect spatiotemporal vibrotactile information provided by the propagated vibrational wave from the source. Specifically, we had users put their hands on a silicone rubber sheet in several postures. We asked users to indicate the position of the vibration source when a location on the sheet was indented. Experimental results suggested that the direction of the impact vibration source can be recognized to some extent, although recognition accuracy depends on hand posture and the position of the vibration source. The best results were achieved when the fingers and palm were grounded and a vibration source was presented around the middle fingertip, and the directional recognition error in this case was 6 degree. In contrast, results suggest it is difficult to accurately recognize the distance of the vibration. The results of this study suggest a new possibility for directional display where vibrotactile actuators are embedded at a distance from the user's hand.In situ fenestration of stent-graft represents a potential option for the treatment of aortic diseases in patients unsuitable for standard endovascular repair. The best fenestration strategy to restore perfusion of collateral vessels after their coverage by an endograft depends mainly on the anatomical area. Several tools are employed as fenestration devices, including needles, radiofrequency probes, and laser systems, used in conjunction with other instrumentation to provide enough support and stability during the procedure. In this systematic review, the approaches to reach the correct fenestration site both in human, animal, and in in vitro environments are described and discussed, highlighting advantages and limitations. SCH 900776 cell line Both commercial and dedicated solutions for the intraoperative modification of the fabric material are reported as well. The clinical interest in this procedure has so far encouraged researchers to develop and refine both methods and tools to solve the current limitations of this technique, intending to extend the indications for endovascular treatment to a broader range of patients.We present here the Arkansas AI-Campus solution method for the 2019 Kidney Tumor Segmentation Challenge (KiTS19). Our Arkansas AI-Campus team participated the KiTS19 Challenge for four months, from March to July of 2019. This paper provides a summary of our methods, training, testing and validation results for this grand challenge in biomedical imaging analysis. Our deep learning model is an ensemble of U-Net models developed after testing many model variations. Our model has consistent performance on the local test dataset and the final competition independent test dataset. The model achieved local test Dice scores of 0.949 for kidney and tumor segmentation, and 0.601 for tumor segmentation, and the final competition test earned Dice scores 0.9470 and 0.6099 respectively. The Arkansas AI-Campus team solution with a composite DICE score of 0.7784 has achieved a final ranking of top fifty worldwide, and top five among the United States teams in the KiTS19 Competition.Malaria is a mosquito-borne disease that results in millions of cases and deaths annually. The development of a fast computational method that identifies secretory proteins of the malaria parasite is important for research on antimalarial drugs and vaccines. Thus, a method was developed to identify the secretory proteins of malaria parasites. In this method, a reduced alphabet was selected to recode the original protein sequence. A feature synthesis method was used to synthesise three different types of feature information. Finally, the random forest method was used as a classifier to identify the secretory proteins. In addition, a web server was developed to share the proposed algorithm. Experiments using the benchmark dataset demonstrated that the overall accuracy achieved by the proposed method was greater than 97.8% using the 10-fold cross-validation method. Furthermore, the reduced schemes and characteristic performance analyses are discussed.Visualization recommendation (VisRec) systems provide users with suggestions for potentially interesting and useful next steps during exploratory data analysis. These recommendations are typically organized into categories based on their analytical actions, i.e., operations employed to transition from the current exploration state to a recommended visualization. However, despite the emergence of a plethora of VisRec systems in recent work, the utility of the categories employed by these systems in analytical workflows has not been systematically investigated. Our paper explores the efficacy of recommendation categories by formalizing a taxonomy of common categories and developing a system, Frontier, that implements these categories. Using Frontier, we evaluate workflow strategies adopted by users and how categories influence those strategies. Participants found recommendations that add attributes to enhance the current visualization and recommendations that filter to sub-populations to be comparatively most useful during data exploration. Our findings pave the way for next-generation VisRec systems that are adaptive and personalized via carefully chosen, effective recommendation categories.During the detailed design phase of an aerospace program, one of the most important consistency checks is to ensure that no two distinct objects occupy the same physical space. Since exact geometrical modeling is usually intractable, geometry models are discretized, which often introduces small interferences not present in the fully detailed model. In this paper, we focus on computing the depth of the interference, so that these false positive interferences can be removed, and attention can be properly focused on the actual design. Specifically, we focus on efficiently computing the penetration depth between two polyhedra, which is a well-studied problem in the computer graphics community. We formulate the problem as a constrained five-variable global optimization problem, and then derive an equivalent unconstrained, 2-variable nonsmooth problem. To solve the optimization problem, we apply a popular stochastic multistart optimization algorithm in a novel way, which exploits the advantages of each problem formulation simultaneously.
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