Cavity Optomechanical Magnetometer

A cavity optomechanical magnetometer is demonstrated where the magnetic field induced expansion of a magnetostrictive material is transduced onto the physical structure of a highly compliant optical microresonator. The resulting motion is read out optically with ultra-high sensitivity. Detecting the magnetostrictive deformation of Terfenol-D with a toroidal whispering gallery mode (TWGM) resonator a peak sensitivity of 400 nT/Hz^.5 was achieved with theoretical modelling predicting that sensitivities of up to 500 fT/Hz^.5 may be possible. This chip-based magnetometer combines high-sensitivity and large dynamic range with small size and room temperature operation

Signalling product healthiness through symbolic package cues: Effects of package shape and goal congruence on consumer behaviour

Three studies show that product packaging shape serves as a cue that communicates healthiness of food products. Inspired by embodiment accounts, we show that packaging that simulates a slim body shape acts as a symbolic cue for product healthiness (e.g., low in calories), as opposed to packaging that simulates a wide body shape. Furthermore, we show that the effect of slim package shape on consumer behaviour is goal dependent. Whereas simulation of a slim (vs. wide) body shape increases choice likelihood and product attitude when consumers have a health-relevant shopping goal, packaging shape does not affect these outcomes when consumers have a hedonic shopping goal. In Study 3, we adopt a realistic shopping paradigm using a shelf with authentic products, and find that a slim (as opposed to wide) package shape increases on-shelf product recognition and increases product attitude for healthy products. We discuss results and implications regarding product positioning and the packaging design process.Coherent privaatrech

A novel method for determining the Femoral-Tibial Angle of Knee Osteoarthritis on X-ray radiographs:data from the Osteoarthritis Initiative

Femoral-tibial alignment is a prominent risk factor for Knee Osteoarthritis (KOA) incidence and progression. One way of assessing alignment is by determining the Femoral-Tibial Angle (FTA). Several studies have investigated FTA determination; however, methods of assessment of FTA still present challenges. This paper introduces a new method for semi-automatic measurement of FTA as part of KOA research. Our novel approach combines preprocessing of X-ray images and the use of Active Shape Model (ASM) as the femoral and tibial segmentation method, followed by a thinning process. The result of the thinning process is used to predict FTA automatically by measuring the angle between the intersection of the two vectors of branching points on the femoral and tibial areas. The proposed method is trained on 10 x-ray images and tested on 50 different x-ray images of the Osteoarthritis Initiative (OAI) dataset. The outcomes of this approach were compared with manually obtained FTA measurements from the OAI dataset as the ground truth. Based on experiments, the difference in measurement results between the FTA of the OAI and the FTA obtained using our method is quite small, i.e., below 0.81 for the right FTA and below 0.77 for the left FTA with minimal average errors. This result indicates that this method is clinically suitable for semi-automatic measurement of the FTA. Computer science; Medical imaging; Knee osteoarthritis; X-ray; Femoral-tibial angle; Active shape mode

Validation of an AI-based algorithm for measurement of the thoracic aortic diameter in low-dose chest CT

OBJECTIVES: To evaluate the performance of artificial intelligence (AI) software for automatic thoracic aortic diameter assessment in a heterogeneous cohort with low-dose, non-contrast chest computed tomography (CT).MATERIALS AND METHODS: Participants of the Imaging in Lifelines (ImaLife) study who underwent low-dose, non-contrast chest CT (August 2017-May 2022) were included using random samples of 80 participants &lt;50y, ≥80y, and with thoracic aortic diameter ≥40 mm. AI-based aortic diameters at eight guideline compliant positions were compared with manual measurements. In 90 examinations (30 per group) diameters were reassessed for intra- and inter-reader variability, which was compared to discrepancy of the AI system using Bland-Altman analysis, paired samples t-testing and linear mixed models.RESULTS: We analyzed 240 participants (63 ± 16 years; 50 % men). AI evaluation failed in 11 cases due to incorrect segmentation (4.6 %), leaving 229 cases for analysis. No difference was found in aortic diameter between manual and automatic measurements (32.7 ± 6.4 mm vs 32.7 ± 6.0 mm, p = 0.70). Bland-Altman analysis yielded no systematic bias and a repeatability coefficient of 4.0 mm for AI. Mean discrepancy of AI (1.3 ± 1.6 mm) was comparable to inter-reader variability (1.4 ± 1.4 mm); only at the proximal aortic arch showed AI higher discrepancy (2.0 ± 1.8 mm vs 0.9 ± 0.9 mm, p &lt; 0.001). No difference between AI discrepancy and inter-reader variability was found for any subgroup (all: p &gt; 0.05).CONCLUSION: The AI software can accurately measure thoracic aortic diameters, with discrepancy to a human reader similar to inter-reader variability in a range from normal to dilated aortas.</p

Measurement of the 3s3p 3P1 lifetime in magnesium using a magneto-optical trap

We demonstrate an accurate method for measuring the lifetime of long-lived metastable magnetic states using a magneto-optical trap (MOT). Through optical pumping, the metastable (3s3p) (3)P(1) level is populated in a standard MOT. During the optical pumping process, a fraction of the population is captured in the magnetic quadrupole field of the MOT. When the metastable atoms decay to the (3s(2)) (1)S(0) ground state they are recaptured into the MOT. In this system no alternative cascading transition is possible. The lifetime of the metastable level is measured directly as an exponential load time of the MOT. We have experimentally tested our method by measuring the lifetime of the (3s3p) (3)P(1) of (24)Mg. This lifetime has been measured numerous times previously, but with quite different results. Using our method we find the (3s3p) (3)P(1) lifetime to be (4.4 +/- 0.2) ms. Theoretical values point toward a lower value for the lifetime

Spring-Charged Particles Model to Improved Shape Recovery:An Application for X-Ray Spinal Segmentation

Deformable models are widely used in medical image segmentation methods, to find not only single but also multiple objects within an image. They have the ability to follow the contours of an object of interest, define the boundary of ROI (Region Of Interest) and improve shape recovery. However, these methods still have limitations in cases of low image quality or clutter. This paper presents a new deformable model, the Spring-Charged Particles Model (SCPM). It simulates the movement of positively charged particles connected by springs, attracted towards the contour of objects of interest which is charged negatively, according to the gradient-magnitude image. Springs prevent the particles from moving away and keep the particles at appropriate distances without reducing their flexibility. SCPM was tested on simple shape images and on frontal X-ray images of scoliosis patients. Artificial noise was added to the simple images to examine the robustness of the method. Several configurations of springs and positively charged-particles were evaluated by determining the best spinal segmentation result. The performance of SCPM was compared to the Charged Fluid Model (CFM), Active Contours, and a convolutional neural network (CNN) with U-Net architecture to measure its ability for determining the curvature of the spinal column from frontal X-Ray images. The results show that SCPM is better at segmenting the spine and determining its curvature, as indicated by the highest Area Score value of 0.837, and the lowest standard deviation value of 0.028

Brain Tumor Classification in MRI Images Using En-CNN

Brain tumors are among the most common diseases of the central nervous system and are harmful. Early diagnosis is essential for patient proper treatment. Radiologists need an automated system to identify brain tumor images successfully. The identification process is often a tedious and error-prone task. Furthermore, brain tumor binary classification is often characterized by malignant and benign because it involves multi-sequence MRI (T1, T2, T1CE, and FLAIR), making radiologist's work quite challenging. Recently, several classification methods based on deep learning are being used to classify brain tumors. Each model's performance is highly dependent on the CNN architecture used. Due to the complexity of the existing CNN architecture, hyperparameter tuning becomes a problem in its application. We propose a CNN method called en-CNN to overcome this problem. This method is based on VGG-16 that consists of seven convolutional networks, four ReLU, and four max-pooling. The proposed method is used to facilitate the hyperparameter tuning. We also proposed a new approach in which the classification of brain tumors is done directly without priorly doing the segmentation process. The new approach consists of the following stages: preprocessing, image augmentation, and applying the en-CNN method. Our new approach is also doing the classification using four MRI sequences of T1, T1CE, T2, and FLAIR. The proposed method delivers accuracy on the MRI multi-sequence BraTS 2018 dataset with an accuracy of 95.5% for T1, 95.5% for T1CE, 94% for T2, and 97% for FLAIR with mini-batch size 128 and epoch 200 using ADAM optimizer. The accuracy was 4% higher than previous research in the same dataset

Vortex Motion Noise in Micrometre-Sized Thin Films of the Amorphous Nb0.7Ge0.3 Weak-Pinning Superconductor

We report high-resolution measurements of voltage (V) noise in the mixed state of micrometre-sized thin films of amorphous Nb0.7Ge0.3, which is a good representative of weak-pinning superconductors. There is a remarkable difference between the noise below and above the irreversibility field Birr. Below Birr, in the presence of measurable pinning, the noise at small applied currents resembles shot noise, and in the regime of flux flow at larger currents decreases with increasing voltage due to a progressive ordering of the vortex motion. At magnetic fields B between Birr and the upper critical field Bc2 flux flow is present already at vanishingly small currents. In this regime the noise scales with (1-B/Bc2)^2 V^2 and has a frequency (f) spectrum of 1/f type. We interpret this noise in terms of the properties of strongly driven depinned vortex systems at high vortex density.Comment: 8 pages, 5 figures, version accepted for publication in PR

Genetic analysis for physical nut traits in almond

Peer ReviewedPublishe

Towards the genetic architecture of seed lipid biosynthesis and accumulation in Arabidopsis thaliana

We report the quantitative genetic analysis of seed oil quality and quantity in six Arabidopsis thaliana recombinant inbred populations, in which the parent accessions were from diverse geographical origins, and were selected on the basis of variation for seed oil content and lipid composition. Although most of the biochemical steps involved in lipid biosynthesis are known and the key genes have been identified, the regulation of the processes that results in the final oil composition and total amount is not understood. By using physically anchored markers it was possible to compare results across populations. A total of 219 quantitative trait loci (QTLs) were identified, of which 81 were significant at P<0.001. Some of these colocalise with QTLs identified previously, but many novel QTLs were also identified. The results highlight the importance of studying traits in multiple populations, which will lead to a better understanding of the contribution that natural variation makes to the genetic architecture of a phenotype