Unipolar potentiation and depression in memristive devices utilising the subthreshold regime

We present a resistance switching device that exhibits analogue potentiation and depression of conductance under the same voltage polarity. This contrasts with previously studied devices that potentiate and depress under opposite polarities. We refer to this mode of operation as the subthreshold regime due to it occurring at voltage or current biases that are insufficient to produce discrete or non-volatile switching. This behaviour has the potential to reduce the complexity of neuronal and synaptic circuitry in neuromorphic computing by removing the need for voltage pulses of both positive and negative polarities. The characteristically long timescales may also help replicate bio-realistic timings. In this paper, we detail how to induce this unique behaviour, how to tune its properties to a desired response, and finally, we demonstrate one potential application

Memristors -- from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing

Machine learning, particularly in the form of deep learning, has driven most of the recent fundamental developments in artificial intelligence. Deep learning is based on computational models that are, to a certain extent, bio-inspired, as they rely on networks of connected simple computing units operating in parallel. Deep learning has been successfully applied in areas such as object/pattern recognition, speech and natural language processing, self-driving vehicles, intelligent self-diagnostics tools, autonomous robots, knowledgeable personal assistants, and monitoring. These successes have been mostly supported by three factors: availability of vast amounts of data, continuous growth in computing power, and algorithmic innovations. The approaching demise of Moore's law, and the consequent expected modest improvements in computing power that can be achieved by scaling, raise the question of whether the described progress will be slowed or halted due to hardware limitations. This paper reviews the case for a novel beyond CMOS hardware technology, memristors, as a potential solution for the implementation of power-efficient in-memory computing, deep learning accelerators, and spiking neural networks. Central themes are the reliance on non-von-Neumann computing architectures and the need for developing tailored learning and inference algorithms. To argue that lessons from biology can be useful in providing directions for further progress in artificial intelligence, we briefly discuss an example based reservoir computing. We conclude the review by speculating on the big picture view of future neuromorphic and brain-inspired computing systems.Comment: Keywords: memristor, neuromorphic, AI, deep learning, spiking neural networks, in-memory computin

Towards population inversion of electrically pumped Er ions sensitized by Si nanoclusters

This study reports the estimation of the inverted Er fraction in a system of Er doped silicon oxide sensitized by Si nanoclusters, made by magnetron sputtering. Electroluminescence was obtained from the sensitized erbium, with a power efficiency of 10¿2 %. By estimating the density of Er ions that are in the first excited state, we find that up to 20% of the total Er concentration is inverted in the best device, which is one order of magnitude higher than that achieved by optical pumping of similar materials

Nonideality‐Aware Training for Accurate and Robust Low‐Power Memristive Neural Networks

Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever-increasing computing requirements of these structures have contributed to a desire for novel technologies and paradigms, including memristor-based hardware accelerators. Solutions based on memristive crossbars and analog data processing promise to improve the overall energy efficiency. However, memristor nonidealities can lead to the degradation of neural network accuracy, while the attempts to mitigate these negative effects often introduce design trade-offs, such as those between power and reliability. In this work, we design nonideality-aware training of memristor-based neural networks capable of dealing with the most common device nonidealities. We demonstrate the feasibility of using high-resistance devices that exhibit high $I$-$V$ nonlinearity -- by analyzing experimental data and employing nonideality-aware training, we estimate that the energy efficiency of memristive vector-matrix multipliers is improved by three orders of magnitude ($0.715\ \mathrm{TOPs}^{-1}\mathrm{W}^{-1}$ to $381\ \mathrm{TOPs}^{-1}\mathrm{W}^{-1}$) while maintaining similar accuracy. We show that associating the parameters of neural networks with individual memristors allows to bias these devices towards less conductive states through regularization of the corresponding optimization problem, while modifying the validation procedure leads to more reliable estimates of performance. We demonstrate the universality and robustness of our approach when dealing with a wide range of nonidealities

Ovarian leydig cell hyperplasia: an unusual case of virilization in a postmenopausal woman.

Objective. To report an unusual case of ovarian Leydig cell hyperplasia resulting in virilization in a postmenopausal woman. Methods. Patient\u27s medical history and pertinent literature were reviewed. Results. A 64-year-old woman presented with virilization with worsening hirsutism, deepening of her voice, male musculature, and male pattern alopecia. Her pertinent past medical history included type 1 diabetes, hyperlipidemia, and hypertension. Her pertinent past surgical history included hysterectomy due to fibroids. On further work-up, her serum total testosterone was 506 ng/dL (nl range: 2-45) and free testosterone was 40 pg/mL (nl range: 0.1-6.4). After ruling out adrenal causes, the patient underwent an empiric bilateral oophorectomy that showed Leydig cell hyperplasia on pathology. Six weeks postoperatively, serum testosterone was undetectable with significant clinical improvement. Conclusion. Postmenopausal hyperandrogenism can be the result of numerous etiologies ranging from normal physiologic changes to ovarian or rarely adrenal tumors. Our patient was found to have Leydig cell hyperplasia of her ovaries, a rarely reported cause of virilization

Sensing and discrimination of explosives at variable concentration with a large-pore MOF as part of a luminescent array

Metal–organic frameworks (MOFs) have shown great promise for sensing of dangerous chemicals, including environmental toxins, nerve agents, and explosives. However, challenges remain, such as the sensing of larger analytes and the discrimination between similar analytes at different concentrations. Herein, we present the synthesis and development of a new, large-pore MOF for explosives sensing and demonstrate its excellent sensitivity against a range of relevant explosive compounds including trinitrotoluene and pentaerythritol tetranitrate. We have developed an improved, thorough methodology to eliminate common sources of error in our sensing protocol. We then combine this new MOF with two others as part of a three-MOF array for luminescent sensing and discrimination of five explosives. This sensor works at part-per-million concentrations and, importantly, can discriminate explosives with high accuracy without reference to their concentration

Peripheral mechanisms contributing to the glucocorticoid hypersensitivity in proopiomelanocortin null mice treated with corticosterone.

Proopiomelanocortin (POMC) deficiency causes severe obesity through hyperphagia of hypothalamic origin. However, low glucocorticoid levels caused by adrenal insufficiency mitigate against insulin resistance, hyperphagia and fat accretion in Pomc-/- mice. Upon exogenous glucocorticoid replacement, corticosterone-supplemented (CORT) Pomc-/- mice show exaggerated responses, including excessive fat accumulation, hyperleptinaemia and insulin resistance. To investigate the peripheral mechanisms underlying this glucocorticoid hypersensitivity, we examined the expression levels of key determinants and targets of glucocorticoid action in adipose tissue and liver. Despite lower basal expression of 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1), which generates active glucocorticoids within cells, CORT-mediated induction of 11beta-HSD1 mRNA levels was more pronounced in adipose tissues of Pomc-/- mice. Similarly, CORT treatment increased lipoprotein lipase mRNA levels in all fat depots in Pomc-/- mice, consistent with exaggerated fat accumulation. Glucocorticoid receptor (GR) mRNA levels were selectively elevated in liver and retroperitoneal fat of Pomc-/- mice but were corrected by CORT in the latter depot. In liver, CORT increased phosphoenolpyruvate carboxykinase mRNA levels specifically in Pomc-/- mice, consistent with their insulin-resistant phenotype. Furthermore, CORT induced hypertension in Pomc-/- mice, independently of adipose or liver renin-angiotensin system activation. These data suggest that CORT-inducible 11beta-HSD1 expression in fat contributes to the adverse cardiometabolic effects of CORT in POMC deficiency, whereas higher GR levels may be more important in liver

Progress in marine geoconservation in Scotland’s seas : assessment of key interests and their contribution to Marine Protected Area network planning

This study was part-funded by Marine Scotland and was undertaken as part of the Scottish Marine Protected Areas (MPA) Programme, a joint initiative between Marine Scotland, Historic Scotland, Scottish Natural Heritage (SNH) and the Joint Nature Conservation Committee (JNCC).Geoconservation in the marine environment has been largely overlooked, despite a wealth of accumulated information on marine geology and geomorphology and clear links between many terrestrial and marine features. As part of the wider characterisation of Scotland’s seas, this study developed criteria and a methodology that follow the established principles of the terrestrial, Great Britain-wide geoconservation audit, the Geological Conservation Review, to assess geodiversity key areas on the seabed. Using an expert judgement approach, eight geodiversity feature categories were identified to represent the geological and geomorphological processes that have influenced the evolution and present-day morphology of the Scottish seabed: Quaternary of Scotland; Submarine Mass Movement; Marine Geomorphology of the Scottish Deep-Ocean Seabed; Seabed Fluid and Gas Seep; Cenozoic Structures of the Atlantic Margin; Marine Geomorphology of the Scottish Shelf Seabed; Coastal Geomorphology of Scotland; and Biogenic Structures of the Scottish Seabed. Within these categories, 35 key areas were prioritised for their scientific value. Specific interests range from large-scale landforms (e.g. submarine landslides, sea-mounts and trenches) to fine-scale dynamic features (e.g. sand waves). Although these geodiversity interests provided supporting evidence for the identification and selection of a suite of Nature Conservation Marine Protected Areas (MPAs) containing important marine natural features, they are only partially represented in these MPAs and existing protected areas. Nevertheless, a pragmatic approach is emerging to integrate as far as possible the conservation management of marine geodiversity with that of biodiversity and based on evidence of the sensitivity and vulnerability geological and geomorphological features on the seabed.PostprintPeer reviewe

CMOS and memristive hardware for neuromorphic computing

The ever-increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing, which takes inspiration from the highly parallel, low power, high speed, and noise-tolerant computing capabilities of the brain, may provide such a shift. To that end, various aspects of the brain, from its basic building blocks, such as neurons and synapses, to its massively parallel in-memory computing networks have been being studied by the huge neuroscience community. Concurrently, many researchers from across academia and industry have been studying materials, devices, circuits, and systems, to implement some of the functions of networks of neurons and synapses to develop bio-inspired (neuromorphic) computing platforms

Enhanced X-ray variability from V1647 Ori, the young star in outburst illuminating McNeil's Nebula

We report a ~38 ks X-ray observation of McNeil's Nebula obtained with XMM on 2004 April 4. V1647 Ori, the young star in outburst illuminating McNeil's Nebula, is detected with XMM and appears variable in X-rays. We investigate the hardness ratio variability and time variations of the event energy distribution with quantile analysis, and show that the large increase of the count rate from V1647 Ori observed during the second half of the observation is not associated with any large plasma temperature variations as for typical X-ray flares from young low-mass stars. X-ray spectral fitting shows that the bulk (~75%) of the intrinsic X-ray emission in the 0.5-8 keV energy band comes from a soft plasma component (0.9 keV) reminiscent of the X-ray spectrum of the classical T Tauri star TW Hya, for which X-ray emission is believed to be generated by an accretion shock onto the photosphere of a low-mass star. The hard plasma component (4.2 keV) contributes ~25% of the total X-ray emission, and can be understood only in the framework of plasma heating sustained by magnetic reconnection events. We find a hydrogen column density of NH=4.1E22 cm-2, which points out a significant excess of hydrogen column density compared to the value derived from optical/IR observations, consistent with the picture of the rise of a wind/jet unveiled from ground optical spectroscopy. The X-ray flux observed with XMM ranges from roughly the flux observed by Chandra on 2004 March 22 (~10 times greater than the pre-outburst X-ray flux) to a value two times greater than that caught by Chandra on 2004 March 7 (~200 times greater than the pre-outburst X-ray flux). We have investigated the possibility that V1647 Ori displays a periodic variation in X-ray brightness as suggested by the combined Chandra+XMM data set (abridged).Comment: 11 pages and 8 Figures. Accepted for publication by Astronomy & Astrophysic