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High-performance miniature surgical instruments play an important role in complicated minimally invasive surgery (MIS). Based on in-depth analysis of the requirements of MIS and the characteristics of the existing minimally invasive surgical instruments, a multiple degrees of freedom (DOF) robotic surgical instrument with decoupled pose was proposed. Firstly, the design concept of the pose decoupling instrument was described in detail, and its physical structure, transmission structure, and mechanical properties were designed and analyzed. A surgical instrument control algorithm based on the master-slave mode was established. Finally, a physical prototype was developed, and its motion ranges of joints, load capacity, and suture operation performance were comprehensively evaluated, which confirmed the effectiveness of the proposed minimally invasive robotic surgical instrument.
Assuntos
Desenho de Equipamento , Procedimentos Cirúrgicos Minimamente Invasivos , Procedimentos Cirúrgicos Robóticos , Procedimentos Cirúrgicos Robóticos/métodos , Procedimentos Cirúrgicos Robóticos/instrumentação , Procedimentos Cirúrgicos Minimamente Invasivos/instrumentação , Procedimentos Cirúrgicos Minimamente Invasivos/métodos , Humanos , Algoritmos , Instrumentos CirúrgicosRESUMO
The concise concept and good optimization performance are the advantages of particle swarm optimization algorithm (PSO), which makes it widely used in many fields. However, when solving complex multimodal optimization problems, it is easy to fall into early convergence. The rapid loss of population diversity is one of the important reasons why the PSO algorithm falls into early convergence. For this reason, this paper attempts to combine the PSO algorithm with wavelet theory and levy flight theory to propose a new hybrid algorithm called PSOLFWM. It applies the random wandering of levy flight and the mutation operation of wavelet theory to enhance the population diversity and seeking performance of the PSO to make it search more efficiently in the solution space to obtain higher quality solutions. A series of classical test functions and 19 optimization algorithms proposed in recent years are used to evaluate the optimization performance accuracy of the proposed method. The experimental results show that the proposed algorithm is superior to the comparison method in terms of convergence speed and convergence accuracy. The success of the high-dimensional function test and dynamic shift performance test further verifies that the proposed algorithm has higher search stability and anti-interference performance than the comparison algorithm. More importantly, both t-Test and Wilcoxon's rank sum test statistical analyses were carried out. The results show that there are significant differences between the proposed algorithm and other comparison algorithms at the significance level α = 0.05, and the performance is better than other comparison algorithms.
Assuntos
Algoritmos , MutaçãoRESUMO
BACKGROUND: Anaplastic large cell lymphoma (ALCL) is a rare and heterogeneous malignant tumor, which is classiï¬ed as anaplastic lymphoma kinase (ALK)positive ALCL and ALK- ALCL. Many patients are diagnosed with ALCL at the stage of bone marrow involvement. However, ALCL patients with clinical manifestations consistent with acute leukemia are relatively rare. CASE SUMMARY: In this report, the patient did not receive appropriate diagnosis and treatment despite a two-year history of lymph node enlargement. Hereafter, she was admitted for B symptoms and was diagnosed as ALK-ALCL by lymph node biopsy. Then, the disease progressed to leukemia without any treatment after 2 mo. The proportion of lymphoma cells in bone marrow was as high as 96%, and the proportion of peripheral blood was 84%. She also had clinical manifestations similar to acute leukemia. After completion of chemotherapy, she developed granulocytopenia and fever and died from septicemia. CONCLUSION: ALCL with leukemic presentation is a late manifestation of lymphoma with low chemotherapy tolerance and poor prognosis.
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BACKGROUND/AIMS: Vibrio vulnificus (V. vulnificus) is a Gram-negative marine bacterium that can cause life-threatening primary septicemia, especially in the innate immune system. But how V. vulnificus affects and acts on dendritic cells (DC) is not well understood. The aim of the present study is to investigate [Ca2+]i change and the expression of the mTor-STAT3-Bcl-2 signaling pathway in V. vulnificus B2-induced DC apoptosis, and explore the protective effect of ethylenediaminetetraacetic acid (EDTA) against DC apoptosis in a V. vulnificus B2 and DC2.4 cell coculture infection model, using EDTA as an intervenient. METHODS: The apoptosis rate, [Ca2+]i, and the expression of STAT3, m-Tor and Bcl-2 were detected by cytometry, Fluo-8-AM and Western blotting respectively. RESULTS: The results demonstrated that EDTA inhibited the increase of [Ca2+]i, upregulated the expression of m-Tor-STAT3-Bcl-2 signaling pathway, and protected DC against V. vulnificus B2-induced apoptosis. CONCLUSIONS: EDTA inhibits V. Vulnificus-induced DC apoptosis by lowering [Ca2+]i via m-Tor-STAT3-Bcl-2 signaling pathway.
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BACKGROUND: In typical stereo display systems, the reproduced 3D scene is distorted when the observer moves. Motion parallax is an important depth cue that has the ability to correct this distortion. More importantly, motion parallax enables the observer to look around objects to provide a better view. METHODS: A robotically assisted laparoscope prototype was designed to provide motion parallax. A study to adjust the camera-head mapping ratio (gain of motion parallax) was performed. A series of phantom tests was conducted to test the effectiveness of motion parallax. RESULTS: The experimental results showed that the motion parallax was effective, and the gain of motion parallax was subjective. For a regular laparoscope view distance, larger image zooming rates required smaller gain; for the same equivalent image size, further observer distance decreased the optimal gain. CONCLUSIONS: Motion parallax could be used for improved visualization in laparoscopic surgery. Copyright © 2015 John Wiley & Sons, Ltd.
Assuntos
Laparoscopia/métodos , Procedimentos Cirúrgicos Robóticos/métodos , Humanos , Laparoscopia/instrumentação , Movimento (Física) , Procedimentos Cirúrgicos Robóticos/instrumentaçãoRESUMO
Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.