Intersected EMG heatmaps and deep learning based gesture recognition

Hand gesture recognition in myoelectric based prosthetic devices is a key challenge to offering effective solutions to hand/lower arm amputees. A novel hand gesture recognition methodology that employs the difference of EMG energy heatmaps as the input of a specific designed deep learning neural network is presented. Experimental results using data from real amputees indicate that the proposed design achieves 94.31% as average accuracy with best accuracy rate of 98.96%. A comparison of experimental results between the proposed novel hand gesture recognition methodology and other similar approaches indicates the superior effectiveness of the new design

Recovering 6D Object Pose: A Review and Multi-modal Analysis

A large number of studies analyse object detection and pose estimation at visual level in 2D, discussing the effects of challenges such as occlusion, clutter, texture, etc., on the performances of the methods, which work in the context of RGB modality. Interpreting the depth data, the study in this paper presents thorough multi-modal analyses. It discusses the above-mentioned challenges for full 6D object pose estimation in RGB-D images comparing the performances of several 6D detectors in order to answer the following questions: What is the current position of the computer vision community for maintaining "automation" in robotic manipulation? What next steps should the community take for improving "autonomy" in robotics while handling objects? Our findings include: (i) reasonably accurate results are obtained on textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy existence of occlusion and clutter severely affects the detectors, and similar-looking distractors is the biggest challenge in recovering instances' 6D. (iii) Template-based methods and random forest-based learning algorithms underlie object detection and 6D pose estimation. Recent paradigm is to learn deep discriminative feature representations and to adopt CNNs taking RGB images as input. (iv) Depending on the availability of large-scale 6D annotated depth datasets, feature representations can be learnt on these datasets, and then the learnt representations can be customized for the 6D problem

Interaction imaging with amplitude-dependence force spectroscopy

Knowledge of surface forces is the key to understanding a large number of processes in fields ranging from physics to material science and biology. The most common method to study surfaces is dynamic atomic force microscopy (AFM). Dynamic AFM has been enormously successful in imaging surface topography, even to atomic resolution, but the force between the AFM tip and the surface remains unknown during imaging. Here, we present a new approach that combines high accuracy force measurements and high resolution scanning. The method, called amplitude-dependence force spectroscopy (ADFS) is based on the amplitude-dependence of the cantilever's response near resonance and allows for separate determination of both conservative and dissipative tip-surface interactions. We use ADFS to quantitatively study and map the nano-mechanical interaction between the AFM tip and heterogeneous polymer surfaces. ADFS is compatible with commercial atomic force microscopes and we anticipate its wide-spread use in taking AFM toward quantitative microscopy

The interpretive approach to religious education : challenging Thompson's interpretation

In a recent book chapter, Matthew Thompson makes some criticisms of my work, including the interpretive approach to religious education and the research and activity of Warwick Religions and Education Research Unit. Against the background of a discussion of religious education in the public sphere, my response challenges Thompson’s account, commenting on his own position in relation to dialogical approaches to religious education. The article rehearses my long held view that the ideal form of religious education in fully state funded schools of a liberal democracy should be ‘secular’ but not ‘secularist’; there should be no implication of an axiomatic secular humanist interpretation of religions

Isolation and characterization of stem cells derived from human third molar tooth germs of young adults: Implications in neo-vascularization, osteo-, adipo-and neurogenesis

A number of studies have reported in the last decade that human tooth germs contain multipotent cells that give rise to dental and peri-odontal structures. The dental pulp, third molars in particular, have been shown to be a significant stem cell source. In this study, we isolated and characterized human tooth germ stem cells (hTGSCs) from third molars and assessed the expression of developmentally important transcription factors, such as oct4, sox2, klf4, nanog and c-myc, to determine their pluri-potency. Flow-cytometry analysis revealed that hTGSCs were positive for CD73, CD90, CD105 and CD166, but negative for CD34, CD45 and CD133, suggesting that these cells are mesenchymal-like stem cells. Under specific culture conditions, hTGSCs differentiated into osteogenic, adipogenic and neurogenic cells, as well as formed tube-like structures in Matrigel assay. hTGSCs showed significant levels of expression of sox2 and c-myc messenger RNA (mRNA), and a very high level of expression of klf4 mRNA when compared with human embryonic stem cells. This study reports for the first time that hTGSCs express developmentally important transcription factors that could render hTGSCs an attractive candidate for future somatic cell re-programming studies to differentiate germs into various tissue types, such as neurons and vascular structures. In addition, these multipotential hTGSCs could be important stem cell sources for autologous transplantation. © 2010 Nature Publishing Group All rights reserved

Accuracy of magnetic resonance studies in the detection of chondral and labral lesions in femoroacetabular impingement : systematic review and meta-analysis

Background: Several types of Magnetic resonance imaging (MRI) are commonly used in imaging of femoroacetabular impingement (FAI), however till now there are no clear protocols and recommendations for each type. The aim of this meta-analysis is to detect the accuracy of conventional magnetic resonance imaging (cMRI), direct magnetic resonance arthrography (dMRA) and indirect magnetic resonance arthrography (iMRA) in the diagnosis of chondral and labral lesions in femoroacetabular impingement (FAI). Methods: A literature search was finalized on the 17th of May 2016 to collect all studies identifying the accuracy of cMRI, dMRA and iMRA in diagnosing chondral and labral lesions associated with FAI using surgical results (arthroscopic or open) as a reference test. Pooled sensitivity and specificity with 95% confidence intervals using a random-effects meta-analysis for MRI, dMRA and iMRA were calculated also area under receiver operating characteristic (ROC) curve (AUC) was retrieved whenever possible where AUC is equivocal to diagnostic accuracy. Results: The search yielded 192 publications which were reviewed according inclusion and exclusion criteria then 21 studies fulfilled the eligibility criteria for the qualitative analysis with a total number of 828 cases, lastly 12 studies were included in the quantitative meta-analysis. Meta-analysis showed that as regard labral lesions the pooled sensitivity, specificity and AUC for cMRI were 0.864, 0.833 and 0.88 and for dMRA were 0.91, 0.58 and 0.92. While in chondral lesions the pooled sensitivity, specificity and AUC for cMRI were 0.76, 0.72 and 0.75 and for dMRA were 0.75, 0.79 and 0.83, while for iMRA were sensitivity of 0.722 and specificity of 0.917. Conclusions: The present meta-analysis showed that the diagnostic test accuracy was superior for dMRA when compared with cMRI for detection of labral and chondral lesions. The diagnostic test accuracy was superior for labral lesions when compared with chondral lesions in both cMRI and dMRA. Promising results are obtained concerning iMRA but further studies still needed to fully assess its diagnostic accuracy

Serological identification and expression analysis of gastric cancer-associated genes

Serological identification of tumour antigens by recombinant expression cloning has proved to be an effective strategy for the identification of cancer-associated genes having a relevance to cancer aetiology and progression, and for defining possible targets for immunotherapeutic intervention. In the present study we applied this technique to identify immunogenic proteins for gastric cancer that resulted in isolation of 14 distinct serum-reactive antigens. In order to evaluate their role in tumourigenesis and assess the immunogenicity of the identified antigens, we characterised each cDNA clone by DNA sequence analysis, mRNA tissue distribution, comparison of mRNA levels in cancerous and adjacent non-cancerous tissues and the frequency of antibody responses in allogeneic patient and control sera. Previously unknown splice variants of TACC1 and an uncharacterised gene Ga50 were identified. The expression of a newly identified TACC1 isoform is restricted to brain and gastric cancer tissues. Comparison of mRNA levels by semi-quantitative RT–PCR revealed a relative overexpression of three genes in cancer tissues, including growth factor granulin and Tbdn-1 – an orthologue of the mouse acetyltransferase gene which is associated with blood vessel development. An unusual DNA polymorphism – a three-nucleotide deletion was found in NUCB2 cDNA but its mRNA level was consistently decreased in gastric tumours compared with that in the adjacent non-cancerous tissues. This study has revealed several new gastric cancer candidate genes; additional studies are required to gain a deeper insight into their role in the tumorigenesis and their potential as therapeutic targets