Share control of surgery robot master manipulator guiding tool along the standard path

Recently, minimally invasive surgery (MIS) robotics enters the phase of autonomous operation. However, because of the high variability of the environment, conducting a fully autonomous surgery is still extremely difficult. This paper presents a share control system, the objective of which is to suggest the optimum path of tool guidance through the use of force on the master manipulator (hereinafter as master), meaning the surgeon's hand. Owing to this type of control, the surgeon has full control over the position of the tool the entire time and is supported by the system to better and faster guide the tool during surgery. The force should be felt by the surgeon but, simultaneously, must not hinder or impact the surgical process. Furthermore, the share control system presented in the paper can be turned on or off at any moment during surgery.     

基于社会接触网络的大规模人群天花传播并行仿真

天花生物恐怖是世界各国面临的重大潜在威胁.本文利用并行仿真的技术手段,研究天花在大规模城市人群中的传播规律并对环形接种和大规模疫苗接种这两种主要的天花疫苗接种策略进行有效性分析,结果表明环形接种措施能够有效控制天花疫情的扩散,在天花疫苗储备不足的情况下可以优先考虑采用该措施.     

Monkey visual behavior falls into the uncanny valley

Very realistic human-looking robots or computer avatars tend to elicit negative feelings in human observers. This phenomenon is known as the “uncanny valley” response. It is hypothesized that this uncanny feeling is because the realistic synthetic characters elicit the concept of “human,” but fail to live up to it. That is, this failure generates feelings of unease due to character traits falling outside the expected spectrum of everyday social experience. These unsettling emotions are thought to have an evolutionary origin, but tests of this hypothesis have not been forthcoming. To bridge this gap, we presented monkeys with unrealistic and realistic synthetic monkey faces, as well as real monkey faces, and measured whether they preferred looking at one type versus the others (using looking time as a measure of preference). To our surprise, monkey visual behavior fell into the uncanny valley: They looked longer at real faces and unrealistic synthetic faces than at realistic synthetic faces.     

脑卒中患者上肢康复机器人及评价方法综述

利用机器人技术进行上肢康复训练是脑卒中患者进行康复治疗的重要手段之一。本文根据中枢神经系统具有高度的可塑性,分析了机器人辅助康复训练的理论依据。并且依据康复机器人的社会需求和研究意义,归纳总结了5种上肢康复机器人的研究进展和研究成果,其中包括上肢康复机器人、功能性电刺激辅助上肢康复机器人、基于虚拟现实技术的上肢康复机器人、基于sEMG的上肢康复训练机器人、基于BCI上肢康复训练机器人。为完善康复机器人的功能,实现对脑卒中患者上肢运动功能的量化评估,本文还分析了目前临床上常用的几种评价方法,即Brunnstrom等级评价法、Fugl?Meyer量表评价法、上田敏评价法和Bobath评价法。最后分析了上肢康复机器人在机械设计、控制策略和评价方法等方面的发展趋势。     

A human-oriented framework for developing assistive service robots

Purpose: Multipurpose robots that can perform a range of useful tasks have the potential to increase the quality of life for many people living with disabilities. Owing to factors such as high system complexity, as-yet unresolved research questions and current technology limitations, there is a need for effective strategies to coordinate the development process.

Method: Integrating established methodologies based on human-centred design and universal design, a framework was formulated to coordinate the robot design process over successive iterations of prototype development.

Results: An account is given of how the framework was practically applied to the problem of developing a personal service robot. Application of the framework led to the formation of several design goals which addressed a wide range of identified user needs. The resultant prototype solution, which consisted of several component elements, succeeded in demonstrating the performance stipulated by all of the proposed metrics.

Conclusions: Application of the framework resulted in the development of a complex prototype that addressed many aspects of the functional and usability requirements of a personal service robot. Following the process led to several important insights which directly benefit the development of subsequent prototypes.

• Implications for Rehabilitation

• This research shows how universal design might be used to formulate usability requirements for assistive service robots.

• A framework is presented that guides the process of designing service robots in a human-centred way.

• Through practical application of the framework, a prototype robot system that addressed a range of identified user needs was developed.

     

国内首例达芬奇机器人单孔肾上腺肿瘤切除术的护理配合

目的：探讨国内首例行达芬奇机器人单孔肾上腺肿瘤切除术的护理配合方法。方法：总结我院1例达芬奇机器人单孔肾上腺肿瘤切除术患者的手术护理配合方法。结果：患者手术过程顺利,手术成功,于术后10天顺利出院。结论：达芬奇机器人单孔肾上腺肿瘤切除术具有创伤小、出血少、疼痛减轻、术后恢复快等优势,值得推广。     

Extended kinship analysis of historical remains using SNP capture

DNA-assisted identification of historical remains requires the genetic analysis of highly degraded DNA, along with a comparison to DNA from known relatives. This can be achieved by targeting single nucleotide polymorphisms (SNPs) using a hybridization capture and next-generation sequencing approach suitable for degraded skeletal samples. In the present study, two SNP capture panels were designed to target ~ 25,000 (25 K) and ~ 95,000 (95 K) nuclear SNPs, respectively, to enable distant kinship estimation (up to 4th degree relatives). Low-coverage SNP data were successfully recovered from 14 skeletal elements 75 years postmortem using an Illumina MiSeq benchtop sequencer. All samples contained degraded DNA but were of varying quality with mean fragment lengths ranging from 32 bp to 170 bp across the 14 samples. SNP comparison with DNA from known family references was performed in the Parabon Fx Forensic Analysis Platform, which utilizes a likelihood approach for kinship prediction that was optimized for low-coverage sequencing data with cytosine deamination. The 25 K panel produced 15,000 SNPs on average, which allowed for accurate kinship prediction with strong statistical support in 16 of the 21 pairwise comparisons. The 95 K panel increased the average SNPs to 42,000 and resulted in an additional accurate kinship prediction with strong statistical support (17 of 21 pairwise comparisons). This study demonstrates that SNP capture combined with massively parallel sequencing on a benchtop platform can yield sufficient SNP recovery from compromised samples, enabling accurate, extended kinship predictions.     

Optimized variant calling for estimating kinship

One of the fundamental goals of forensic genetics is sample attribution, i.e., whether an item of evidence can be associated with some person or persons. The most common scenario involves a direct comparison, e.g., between DNA profiles from an evidentiary item and a sample collected from a person of interest. Less common is an indirect comparison in which kinship is used to potentially identify the source of the evidence. Because of the sheer amount of information lost in the hereditary process for comparison purposes, sampling a limited set of loci may not provide enough resolution to accurately resolve a relationship. Instead, whole genome techniques can sample the entirety of the genome or a sufficiently large portion of the genome and as such they may effect better relationship determinations. While relatively common in other areas of study, whole genome techniques have only begun to be explored in the forensic sciences. As such, bioinformatic pipelines are introduced for estimating kinship by massively parallel sequencing of whole genomes using approaches adapted from the medical and population genomic literature. The pipelines are designed to characterize a person’s entire genome, not just some set of targeted markers. Two different variant callers are considered, contrasting a classical variant calling algorithm (BCFtools) to a more modern deep convolution neural network (DeepVariant). Two different bioinformatic pipelines specific to each variant caller are introduced and evaluated in a titration series. Filters and thresholds are then optimized specifically for the purposes of estimating kinship as determined by the KING-robust algorithm. With the appropriate filtering and thresholds in place both tools perform similarly, with DeepVariant tending to produce more accurate genotypes, though the resultant types of inaccuracies tended to produce slightly less accurate overall estimates of relatedness     

Massively‐parallel sequencing assists the diagnosis and guided treatment of cancers of unknown primary

The clinical management of patients with cancer of unknown primary (CUP) is hampered by the absence of a definitive site of origin. We explored the utility of massively‐parallel (next‐generation) sequencing for the diagnosis of a primary site of origin and for the identification of novel treatment options. DNA enrichment by hybridization capture of 701 genes of clinical and/or biological importance, followed by massively‐parallel sequencing, was performed on 16 CUP patients who had defied attempts to identify a likely site of origin. We obtained high quality data from both fresh‐frozen and formalin‐fixed, paraffin‐embedded samples, demonstrating accessibility to routine diagnostic material. DNA copy‐number obtained by massively‐parallel sequencing was comparable to that obtained using oligonucleotide microarrays or quantitatively hybridized fluorescently tagged oligonucleotides. Sequencing to an average depth of 458‐fold enabled detection of somatically acquired single nucleotide mutations, insertions, deletions and copy‐number changes, and measurement of allelic frequency. Common cancer‐causing mutations were found in all cancers. Mutation profiling revealed therapeutic gene targets and pathways in 12/16 cases, providing novel treatment options. The presence of driver mutations that are enriched in certain known tumour types, together with mutational signatures indicative of exposure to sunlight or smoking, added to clinical, pathological, and molecular indicators of likely tissue of origin. Massively‐parallel DNA sequencing can therefore provide comprehensive mutation, DNA copy‐number, and mutational signature data that are of significant clinical value for a majority of CUP patients, providing both cumulative evidence for the diagnosis of primary site and options for future treatment. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.