Path optimization advisory and analytical tools for directional drilling

In directional drilling, well positioning and drilling instructions are planned based on human experiences and may require excessive computation and drilling times. Directional drilling process nowadays lacks optimization and automation to improve performance and efficiency. A path optimization advisor is developed with novel cost analysis, to support real-time directional drilling decisions. Spline in tension is used to simulated drilling path in the path optimization algorithms; more accurate and convenient for optimization purposes than commonly used survey calculation methods. The best valued path is solved using multi-loop optimization process, by determining the path with the lowest accumulated cost. Costs specified for each section are formulated and transformed into equal units. Actual drilling instruction is fitted to the optimal path with consideration of motor tendency and capabilities. The advisor developed using Matlab is validated that such a system can be used in real time directional drilling environments, to provide suggestions. Test cases using simulated drilling situation and historical data are tested for resulting instruction validation. Produced instruction and path results proved to be realistic and optimized based on specified cost functions. Comparing the optimized path with actual drilling instruction and survey drilled in historical cases, plan suggested by the path optimization advisor provides a better valued correction path.Petroleum and Geosystems Engineerin

Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future.

Treatment planning is an essential step of the radiotherapy workflow. It has become more sophisticated over the past couple of decades with the help of computer science, enabling planners to design highly complex radiotherapy plans to minimize the normal tissue damage while persevering sufficient tumor control. As a result, treatment planning has become more labor intensive, requiring hours or even days of planner effort to optimize an individual patient case in a trial-and-error fashion. More recently, artificial intelligence has been utilized to automate and improve various aspects of medical science. For radiotherapy treatment planning, many algorithms have been developed to better support planners. These algorithms focus on automating the planning process and/or optimizing dosimetric trade-offs, and they have already made great impact on improving treatment planning efficiency and plan quality consistency. In this review, the smart planning tools in current clinical use are summarized in 3 main categories: automated rule implementation and reasoning, modeling of prior knowledge in clinical practice, and multicriteria optimization. Novel artificial intelligence-based treatment planning applications, such as deep learning-based algorithms and emerging research directions, are also reviewed. Finally, the challenges of artificial intelligence-based treatment planning are discussed for future works

Research on Marine Pollution Problems and Solutions in China from the Perspective of Marine Tourism

Based on the perspective of marine tourism, this paper integrates various types of marine pollution, and puts forward high-quality development solutions and future extension direction of marine tourism. Through the research, it is found that the main culprits of marine pollution mainly include the following seven points: human activities produce garbage; white pollution; ship pollution; exploration of marine oil and gas resources and mineral pollution; land reclamation; pollution in mariculture industry and new estrogen pollution. The causes of marine pollution and countermeasures are discussed

The Development Prospect of Chinese Rehabilitation Specialist Nurses under the Background of Aging

Objective: To explore the correlation between the supply-demand contradiction and development of rehabilitation nursing talents in China through the analysis of China's aging population. It provides ideas for the increasingly professional and regularization of rehabilitation nursing in China, and provides evidence-based suggestions for the employment of rehabilitation specialist nurses. Design: Review Article. Methods: Literature review. Finding: Due to the traditional concept of Chinese society and the low recognition of rehabilitation specialist nurses, the training institutions for rehabilitation specialist nurses are not perfect, and the education level of rehabilitation specialist nurses is uneven, making it difficult to meet the needs of Chinese rehabilitation nurses. Conclusion: Call on more nursing talents to participate in the construction of rehabilitation nursing in China.Explore the prospects for the development of rehabilitation specialist nurses around the world, take China as an example, and provide evidence-based advice for the employment of rehabilitation specialist nurses

Assessing the Therapeutic Effect of 630 nm Light-emitting Diodes Irradiation on the Recovery of Exercise-induced Hand Muscle Fatigue with Surface Electromyogram

This paper aims to investigate the effect of light emitting diode therapy (LEDT) on exercise-induced hand muscle fatigue by measuring the surface electromyography (sEMG) of flexor digitorum superficialis. Ten healthy volunteers were randomly placed in the equal sized LEDT group and control group. All subjects performed a sustained fatiguing isometric contraction with the combination of four fingertips except thumb at 30% of maximal voluntary contraction (MVC) until exhaustion. The active LEDT or an identical passive rest therapy was then applied to flexor digitorum superficialis. Each subject was required to perform a re-fatigue task immediately after therapy which was the same as the pre-fatigue task. Average rectified value (ARV) and fractal dimension (FD) of sEMG were calculated. ARV and FD were significantly different between active LEDT and passive rest groups at 20%–50%, 70%–80%, and 100% of normalized contraction time (P \u3c 0.05 ). Compared to passive rest, active LEDT induced significantly smaller increase in ARV values and decrease in FD values, which shows that LEDT is effective on the recovery of muscle fatigue. Our preliminary results also suggest that ARV and FD are potential replacements of biochemical markers to assess the effects of LEDT on muscle fatigue

Conformational B-Cell Epitope Prediction on Antigen Protein Structures: A Review of Current Algorithms and Comparison with Common Binding Site Prediction Methods

Accurate prediction of B-cell antigenic epitopes is important for immunologic research and medical applications, but compared with other bioinformatic problems, antigenic epitope prediction is more challenging because of the extreme variability of antigenic epitopes, where the paratope on the antibody binds specifically to a given epitope with high precision. In spite of the continuing efforts in the past decade, the problem remains unsolved and therefore still attracts a lot of attention from bioinformaticists. Recently, several discontinuous epitope prediction servers became available, and it is intriguing to review all existing methods and evaluate their performances on the same benchmark. In addition, these methods are also compared against common binding site prediction algorithms, since they have been frequently used as substitutes in the absence of good epitope prediction methods