Few-shot hypercolumn-based mitochondria segmentation in cardiac and outer hair cells in focused ion beam-scanning electron microscopy (FIB-SEM) data

We present a novel AI-based approach to the few-shot automated segmentation of mitochondria in large-scale electron microscopy images. Our framework leverages convolutional features from a pre-trained deep multilayer convolutional neural network, such as VGG-16. We then train a binary gradient boosting classifier on the resulting high-dimensional feature hypercolumns. We extract VGG-16 features from the first four convolutional blocks and apply bilinear upsampling to resize the obtained maps to the input image size. This procedure yields a 2688-dimensional feature hypercolumn for each pixel in a 224 x 224 input image. We then apply L1-regularized logistic regression for supervised active feature selection to reduce dependencies among the features, to reduce overfitting, as well as to speed-up gradient boosting-based training. During inference we block process 1728 x 2022 large microscopy images. Our experiments show that in such a formulation of transfer learning our processing pipeline is able to achieve high-accuracy results on very challenging datasets containing a large number of irregularly shaped mitochondria in cardiac and outer hair cells. Our proposed few-shot training approach gives competitive performance with the state-of-the-art using far less training data

Search for gravitational waves associated with the InterPlanetary Network short gamma ray bursts

We outline the scientific motivation behind a search for gravitational waves associated with short gamma ray bursts detected by the InterPlanetary Network (IPN) during LIGO's fifth science run and Virgo's first science run. The IPN localisation of short gamma ray bursts is limited to extended error boxes of different shapes and sizes and a search on these error boxes poses a series of challenges for data analysis. We will discuss these challenges and outline the methods to optimise the search over these error boxes.Comment: Methods paper; Proceedings for Eduardo Amaldi 9 Conference on Gravitational Waves, July 2011, Cardiff, U

Risk of chronic kidney disease after cancer nephrectomy.

The incidence of early stage renal cell carcinoma (RCC) is increasing and observational studies have shown equivalent oncological outcomes of partial versus radical nephrectomy for stage I tumours. Population studies suggest that compared with radical nephrectomy, partial nephrectomy is associated with decreased mortality and a lower rate of postoperative decline in kidney function. However, rates of chronic kidney disease (CKD) in patients who have undergone nephrectomy might be higher than in the general population. The risks of new-onset or accelerated CKD and worsened survival after nephrectomy might be linked, as kidney insufficiency is a risk factor for cardiovascular disease and mortality. Nephron-sparing approaches have, therefore, been proposed as the standard of care for patients with type 1a tumours and as a viable option for those with type 1b tumours. However, prospective data on the incidence of de novo and accelerated CKD after cancer nephrectomy is lacking, and the only randomized trial to date was closed prematurely. Intrinsic abnormalities in non-neoplastic kidney parenchyma and comorbid conditions (including diabetes mellitus and hypertension) might increase the risks of CKD and RCC. More research is needed to better understand the risk of CKD post-nephrectomy, to develop and validate predictive scores for risk-stratification, and to optimize patient management

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

The on-line determination of underground cable conductor temperatures

The criterion determining the maximum load able to be sustained by an underground cable is its maximum allowable conductor temperature. Above this value, degradation of insulation will commence and lead to ultimate failure of the cable. Methods using a digital computer program are available for calculating cable conductor temperature given the thermal characteristics of the cable and its environment and the loads at whlch the cable will be operated. Such methods invariably assume a 24 hourly load cycle to which the cable is subjected continuously and a maximum ground ambient temperature which conservatively occurs at the time of peak load. The thesis describes the development of an electronic device which can be installed in a substation, reading cable loading and ambient temperature in real time, and calculating in an on-line capacity, the cable conductor temperature. The device overcomes the limitations of the use of assumed variables. It calculates cable operating temperature which is continuously updated as loading and ambient conditions change. The algorithm used relies on a modification of the CIGRE Method (circa 1974) and a long term load test on a buried cable installation has confirmed its accuracy. All storage and calculation functions required are processed by a microcomputer developed specifically for the task using a proprietary line 16-bit processor. Software development was aided by the use of a high level language facilitated by the compatibility of the device processor and computer development systems already possessed by SEQEB. The device can be installed in a normal substation environment (5°c - 35°c ambient) without the need for a controlled atmosphere and will operate from normal 240V mains supply. Ten cable groups each consisting of one or two circuits may be processed from the one device and updated temperatures are calculated at hourlyIn the normal mode, continuous conductor temperature monitoring is provided which is able to accommodate any load or ground ambient temperature change. The SEQEB substation automated control system, a microprocessor based supervisory and control facility, can relay conductor temperature information from the device to remote system operators at VDU terminals via normal telecommunication lines. Alarm initiation is incorporated into software for operator attention in the case of conductor temperature exceeding allowable limits. Furthermore, the device may be used to predict conductor temperature response to a contingency situation known in advance. In the event of a power supply failure to the device and consequent memory loss, a cassette drive backup system has been employed. This system re-loads stored data and program instructions into memory upon power restoration and instructs the microcomputer to recommence operation. It is concluded that although devices of this type are new to the electricity supply industry in Australia, they can provide additional benefits for the planning and operation of a supply system. The added economic benefit to the supply authority, and ultimately the consumer, is evident in the more effective utilisation of the system with deferment of capital expenditure on new circuits while the existing system is operated nearer its full capacity. intervals

Fast synthesis of n-type half-heusler TiNiSn thermoelectric material

The n-type half-Heusler TiNiSn is very promising for thermoelectric applications in the medium temperature range. However, the synthesis of TiNiSn often involves long annealing times (up to several weeks) to obtain a single phase, which is a major barrier to scaling-up. In this work, TiNiSn was synthesized by a combination of arc-melting, ball-milling and spark plasma sintering. The obtained samples with diameters up to 30 mm had high-purity, high-density and fine-grains. Without the need for an annealing step, the total synthesis time was significantly shortened. Addition of Cu was used to optimize the thermoelectric properties of TiNiSn, and a maximum figure of merit of 0.6 was achieved at 773 K. The fast and scalable synthesis of TiNiSn with good thermoelectric performance presented in this work opens up the possibility of industrial scaling-up