Prediction of peptides binding to MHC class I alleles by partial periodic pattern mining

MHC (Major Histocompatibility Complex) is a key player in the immune response of an organism. It is important to be able to predict which antigenic peptides will bind to a specific MHC allele and which will not, creating possibilities for controlling immune response and for the applications of immunotherapy. However, a problem for MHC class I is the presence of bulges and loops in the peptides, changing the total length. Most machine learning methods in use today require the sequences to be of same length to successfully mine the binding motifs. We propose the use of time-based data mining methods in motif mining to be able to mine motifs position-independently. Also, the information for both binding and non-binding peptides is used on the contrary to the other methods which only rely on binding peptides. The prediction results are between 60-95% for the tested alleles

Prediction of peptides binding to MHC class I alleles by partial periodic pattern mining

MHC (Major Histocompatibility Complex) is a key player in the immune response of an organism. It is important to be able to predict which antigenic peptides will bind to a spe-cific MHC allele and which will not, creating possibilities for controlling immune response and for the applications of immunotherapy. However a problem encountered in the computational binding prediction methods for MHC class I is the presence of bulges and loops in the peptides, changing the total length. Most machine learning methods in use to-day require the sequences to be of same length to success-fully mine the binding motifs. We propose the use of time-based data mining methods in motif mining to be able to mine motifs position-independently. Also, the information for both binding and non-binding peptides are used on the contrary to the other methods which only rely on binding peptides. The prediction results are between 70-80% for the tested alleles

Non-invasive measurement of stress levels in knee implants using a magnetic-based detection method

A knee replacement surgery (arthroplasty) has become prevalent worldwide and has a high success rate over the short to medium term. In some cases, especially over the longer term, implant degradation can develop due to the deterioration of the ultra-high molecular weight polyethylene (UHMWPE) tibial insert. Unfortunately, there are no satisfactory techniques currently available for assessing implant integrity and predicting failure. This paper describes a possible solution to this problem by using a non-invasive, electromagnetic method for monitoring implant integrity. This approach utilizes the magnetoelastic property of amorphous ribbon, which when stressed causes an inductance change in a nearby magnetizing winding. Amorphous ribbons encased in UHMWPE disks, to simulate a knee insert, were subjected to varying tensile stresses under an applied ac magnetic field. A correlation between total circuit impedance and applied stress was observed. The results obtained demonstrate that the proposed sensor has sufficient sensitivity for measuring typical stress levels associated with the axial forces in tibial inserts

Using finite element modelling and experimental methods to investigate planar coil sensor topologies for inductive measurement of displacement

The usage of planar sensors is widespread due to their non-contact nature and small size profiles, however only a few basic design types are generally considered. In order to develop planar coil designs we have performed extensive finite element modelling (FEM) and experimentation to understand the performance of different planar sensor topologies when used in inductive sensing. We have applied this approach to develop a novel displacement sensor. Models of different topologies with varying pitch values have been analysed using the ANSYS Maxwell FEM package, furthermore the models incorporated a movable soft magnetic amorphous ribbon element. The different models used in the FEM were then constructed and experimentally tested with topologies that included mesh, meander, square coil, and circular coil configurations. The sensors were used to detect the displacement of the amorphous ribbon. A LabView program controlled both the displacement stage and the impedance analyser, the latter capturing the varying inductance values with ribbon displacement. There was good correlation between the FEM models and the experimental data confirming that the methodology described here offers an effective way for developing planar coil based sensors with improved performance

Volumetrically scanning the structure of stray-fields above grain-oriented electrical-steel using a variably angled TMR sensor

Abstract—a new versatile scanning hardware based on a Micromagnetics® STJ-020 MgO-based tunnelling magneto-resistance (TMR) sensor has been developed to volumetrically scan the thin boundary layer above a given sample. An (x,y) planar scan of the surface of a 7.5 mm × 7.5 mm sample of grain-oriented (3% Si) electrical steel is presented. Stray fields normal to the surface between -116 and 272 A/m are measured. At 10 μm/pixel domain and micro-domain structures are seen. At 5 μm/pixel the micro-domain structures resolve into clear Lancet domains. The domain images presented have greater qualitative similarity with Kerr effect observations than with Bitter technique results. An (x,z) vertical scan along a 2.35 mm transect reveals the perpendicular extent of the stray fields, with the normal components shown to emanate from the domain bodies and extend approximately 40 - 100 μm from the sample surface. With the aim of investigating how the stray fields close back onto the surface, the (x,z) transect is repeated with the sensor at 5, 10, 15 and 20 degrees from the vertical. For the first time, the stray fields from surface domains viewed by other techniques in only a planar (x,y) projection have been

An optical sensor for tracking hand articulations

Recognizing and tracking articulations of the human hand is key to the development of areas such as robotics, virtual reality systems and physical rehabilitation. Based on the principle of crossed-polarization detection, a novel optical sensor with a hinge configuration, is proposed to monitor finger articulation. Using 3D printing technology, we fabricated a lightweight and compact sensor suited to attaching on fingers. The weighted average method was applied to the sensor's output data to determine angular positions corresponding to finger joint articulations. The experimental results show excellent consistency with theoretical predictions. The sensor features good accuracy (±0.5% of full scale) and repeatability, improved sensitivity, and an improved measuring range of 180°. The performance of the sensor is a promising development for monitoring finger articulation. Future work will focus on integrating multiple sensors as part of an instrumented glove to evaluate the true potential for monitoring hand articulation

Enhanced tracking system based on micro inertial measurements unit to measure sensorimotor responses in pigeons

The ability to orientate and navigate is critically important for the survival of all migratory birds and other animals. Progress in understanding the mechanisms underlying these capabilities and, in particular, the importance of a sensitivity to the Earth’s magnetic field has, thus far, been constrained by the limited number of techniques available for the analysis of often complex behavioural responses. Methods used to track the movements of animals, such as birds, have varied depending on the degree of accuracy required. Most conventional approaches involve the use of a camera for recording and then measuring an animal's head movements in response to a variety of external stimuli, such as changes in magnetic fields. However, video tracking analysis (VTA) will generally only provide a 2D tracking of head angle. Moreover, such a video analysis can only provide information about movements when the head is in view of the camera. In order to overcome these limitations, the novel invention reported here utilises a lightweight (<10g) Inertial Measurement Unit (IMU), positioned on the head of a homing pigeon, which contains a sensor with tri-axial orthogonal accelerometers, gyroscopes, and magnetometers. This highly compact (20.3×12.7×3 mm) system, can be programmed and calibrated to provide measurements of the three rotational angles (roll, pitch and yaw) simultaneously, eliminating any drift, i.e. the movement of the pigeon's head is determined by detecting and estimating the directions of motion at all angles (even those outside the defined areas of tracking). Using an existing VTA approach as a baseline for comparison, it is demonstrated IMU technology can comprehensively track a pigeon’s normal head movements with greater precision and in all 3 axes

Axial magnetic field sensing for pulsed magnetic flux leakage hairline crack detection and quantification

The Magnetic Flux Leakage (MFL) testing method is a well-established branch of electromagnetic non-destructive testing technology extensively used to observe, analyze and estimate the level of imperfections (cracks, corrosions, pits, dents, etc.) affecting the quality of ferromagnetic steel structures. However the conventional MFL (DCMFL) method are not capable of estimating the defect sizes and orientation, hence an additional transducer is required to provide the extra information needed. This paper takes the detection and quantification of tangentially oriented rectangular surface and far-surface hairline cracks as the research objective. It uses an optimized pulsed magnetic flux leakage probe system to establish the location and geometries of such cracks. The results gathered from the approach show that data using the axial (Bx) field component can provide detailed locational information about hairline cracks especially the shape, size and orientation when positioned perpendicular to the applied field

A novel magnetostrictive curvature sensor employing flexible, figure-of-eight sensing coils

The demand for accurate angle measurements in a form that is robust and small is high, due to the advances in virtual reality applications, primarily the virtual reality headsets. The peripheral devices are required to completely immerse the user in a virtual reality setting, and for this purpose, a robust sensor has been developed. The angle measurements can also be used in motion sensing applications for medical purposes, allowing monitoring of a patient’s condition. This paper presents the development of a planar figure-of-eight coil sensor, which has been designed for the purpose of curvature sensing. The copper-plated polyimide material, FR4 FLEX, was used for the fabrication of the planar figure-of-eight coil. A curvature sensor was designed and consists of the figure-of-eight coil along with the magnetostrictive material Metglas 2605SA1. The sensor was incorporated in an oscillator circuit, where curvature-induced stress within the material changes the amplitude and the frequency of the output signal of the circuit

Design and Evaluation of a 3-D Printed Optical Sensor for Monitoring Finger Flexion

The development of techniques for monitoring finger movement is becoming increasingly important in areas, such as robotics, virtual reality, and rehabilitation. To date, various techniques have been proposed for tracking hand movements, but the majority suffer from poor accuracy and repeatability. Inspired by the articulated structure of finger joints, we propose a novel 3-D printed optical sensor with a compact hinged configuration for tracking finger flexion. This sensor exploits Malus' law using the attenuation of light transmitted through crossed polarizers. The sensor consists of a single LED, two pieces of linear polarizing film, and a photodetector that detects the changes in polarized light intensity proportional to the angle of finger flexion. This paper presents the characterization of the proposed optical sensor and compares it with a commonly used commercial bend sensor. Results show that the bend sensor exhibits hysteresis error, low sensitivity at small angles, and significant temporal drift. In contrast, the optical sensor is more accurate (±0.5°) in the measuring range from 0° to 90°, and exhibits high repeatability and stability, as well as a fast dynamic response. Overall, the optical sensor outperforms the commercial bend sensor, and shows excellent potential for monitoring hand movements in real time