Evaluation of Reorientation Techniques and Distractors for Walking in Large Virtual Environments

Vir tual Environments (VEs) that use a real-walking locomotion interface have typically been restricted in size to the area of the tracked lab space. Techniques proposed to lift this size constraint, enabling real walking in VEs that are larger than the tracked lab space, all require reorientation techniques (ROTs) in the worst-case situation—when a user is close to walking out of the tracked space. We propose a new ROT using visual and audial distractors—objects in the VE that the user focuses on while the VE rotates—and compare our method to current ROTs through three user studies. ROTs using distractors were preferred and ranked more natural by users. Our findings also suggest that improving visual realism and adding sound increased a user's feeling of presence. Users were also less aware of the rotating VE when ROTs with distractors were used.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.     

The use of acellular matrices for the tissue engineering of cardiac valves

Tissue-engineering approaches to cardiac valve replacement have made considerable advances over recent years and it is likely that this application will realize clinical success in the near future. Research in this area has been driven by the inadequacy of the currently available cardiac valve prostheses for younger patients who require multiple reoperations as they grow and develop. Tissue engineering has the potential to provide a valve capable of the same growth, repair, and regeneration as a natural valve and could improve outcomes for patients of all ages. Owing to the function and physical environment of the cardiac valve, the development of tissue-engineered replacements is unusual in that the biomechanical properties of the construct must dominate the biological properties in order for the valve to be functional at the time of implantation. As a result of this, conventional tissue-engineering scaffolds based on biodegradable polymers or collagen may not at present be suitable in this situation because of their initial limited strength. Research into the use of acellular xenogeneic and allogeneic matrices for tissue-engineered heart valves has consequently become extremely popular since the biomechanical properties of the valve can potentially be preserved with an optimal decellularization technique that removes the cells without damaging the matrix. A number of acellular scaffolds have already been tested clinically both unseeded and preseeded with cells and these have met with variable results. This article reviews the concepts involved and the advantages and disadvantages of the different approaches to tissue engineering a living cardiac valve.     

Photon counting with passively quenched germanium avalanche

We demonstrate photon counting in germanium avalanche photodiodes biased beyond breakdown and quenched with a simple series resistance circuit. The devices show moderate (> 7%) quantum efficiency with limited afterpulsing and dark counts and subnanosecond jitter.     

Approximate regular expression pattern matching with concave gap penalties

Given a sequenceA of lengthM and a regular expressionR of lengthP, an approximate regular expression pattern-matching algorithm computes the score of the optimal alignment betweenA and one of the sequencesB exactly matched byR. An alignment between sequencesA=a₁a₂ ... a_M andB=b₁b₂... b_N is a list of ordered pairs, (i₁,j₁), (i₂j₂), ..., (i_t,j_tt) such that i_k < i_k+1 and j_k < j_k+1. In this case the alignmentaligns symbols a_ik and b_jk, and leaves blocks of unaligned symbols, orgaps, between them. A scoring schemeS associates costs for each aligned symbol pair and each gap. The alignment's score is the sum of the associated costs, and an optimal alignment is one of minimal score. There are a variety of schemes for scoring alignments. In a concave gap penalty scoring schemeS={, w}, a function (a, b) gives the score of each aligned pair of symbolsa andb, and aconcave function w(k) gives the score of a gap of lengthk. A function w is concave if and only if it has the property that, for allk > 1, w(k + 1) –w(k) w(k) –w(k –1). In this paper we present an O(MP(logM + log² P)) algorithm for approximate regular expression matching for an arbitrary and any concavew. This work was supported in part by the National Institute of Health under Grant RO1 LM04960.     

Design and Development of Flexible PDMS Antenna for UWB-WBAN Applications

Wireless Personal Communications - This paper presents the design and development of a flexible Ultra Wide Band (UWB) antenna using polydimethylsiloxane as a substrate. Copper foil having a...     

Mammogram Learning System for Breast Cancer Diagnosis Using Deep Learning SVM

The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces system complexity. The softmax layer in VGG assumes that the training samples belong to exactly only one class, which is not valid in a real situation, such as in medical image diagnosis. To overcome this situation, SVM is employed instead of the softmax layer in VGG. Data augmentation is also employed as DLA usually requires a large number of samples. VGG model with different SVM kernels is built to classify the mammograms. Results show that the VGG-SVM model has good potential for the classification of Mammographic Image Analysis Society (MIAS) database images with an accuracy of 98.67%, sensitivity of 99.32%, and specificity of 98.34%.     

Oxygen saturation-dependent effects on blood transverse relaxation at low fields

Objective

Blood oxygenation can be measured using magnetic resonance using the paramagnetic effect of deoxy-haemoglobin, which decreases the \(\textit{T}_{2}\) relaxation time of blood. This \(\textit{T}_{2}\) contrast has been well characterised at the \(\textit{B}_{{0}}\) fields used in MRI (1.5 T and above). However, few studies have characterised this effect at lower magnetic fields. Here, the feasibility of blood oximetry at low field based on \(\textit{T}_{2}\) changes that are within a physiological relevant range is explored. This study could be used for specifying requirements for construction of a monitoring device based on low field permanent magnet systems.

Methods

A continuous flow circuit was used to control parameters such as oxygen saturation and temperature in a sample of blood. It flowed through a variable field magnet, where CPMG experiments were performed to measure its \(\textit{T}_{2}\). In addition, the oxygen saturation was monitored by an optical sensor for comparison with the \(\textit{T}_{2}\) changes.

Results

These results show that at low \(\textit{B}_{{0}}\) fields, the change in blood \(\textit{T}_{2}\) due to oxygenation is small, but still detectable. The data measured at low fields are also in agreement with theoretical models for the oxy-deoxy \(\textit{T}_{2}\) effect.

Conclusion

\(\textit{T}_{2}\) changes in blood due to oxygenation were observed at fields as low as 0.1 T. These results suggest that low field NMR relaxometry devices around 0.3 T could be designed to detect changes in blood oxygenation.

     

Study of DNA Origami Dimerization and Dimer Dissociation Dynamics and of the Factors that Limit Dimerization

Organizing DNA origami building blocks into higher order structures is essential for fabrication of large structurally and functionally diverse devices and molecular machines. Unfortunately, the yields of origami building block attachment reactions are typically not sufficient to allow programed assembly of DNA devices made from more than a few origami building blocks. To investigate possible reasons for these low yields, a detailed single‐molecule fluorescence study of the dynamics of rectangular origami dimerization and origami dimer dissociation reactions is conducted. Reactions kinetics and yields are investigated at different origami and ion concentrations, for different ion types, for different lengths of bridging strands, and for the “sticky end” and “weaving welding” attachment techniques. Dimerization yields are never higher than 86%, which is typical for such systems. Analysis of the dynamic data shows that the low yield cannot be explained by thermodynamic instability or structural imperfections of the origami constructs. Atomic force microscopy and gel electrophoresis evidence reveal self‐dimerization of the origami monomers, likely via blunt‐end interactions made possible by the presence of bridging strands. It is suggested that this mechanism is the major factor that inhibits correct dimerization and means to overcome it are discussed.     

Microstructural study of Au-Pd-Zn ohmic contacts to p-type InGaAsP-InP

A detailed microstructural study has been done on Au-Pd-Zn ohmic contacts to p-type InGaAsP epitaxially grown on InP. The doping level in the InGaAsP was 1.0 × 10¹⁹ to 1.5 × 10¹⁹ cm^–3 near the surface with the Zn concentration graded to a value of 7 × 10¹⁸ cm^–3 at the InGaAsP-InP interface. Metal layers (10 nm Pd,3 nmZn, 25 nm Pd and 50 nm Au) were deposited sequentially by electron beam evaporation. Contact resistances less than 10^–4 cm² were achieved for all annealing temperatures studied (380–440 C) and a minimum contact resistance of 2 × 10^–6 cm² was obtained for an anneal at 400 C for 20 s. Comparisons were made to similar metallizations on p-type InP. Lower contact resistances were achieved for the quaternary material compared with the binary material, however, contact stability and uniformity were worse.