Programmable Optical Synaptic Linking of Neuromorphic Photonic-Electronic RTD Spiking Circuits.

Interconnectivity between functional building blocks (such as neurons and synapses) represents a fundamental functionality for realizing neuromorphic systems. However, in the domain of neuromorphic photonics, synaptic interlinking and cascadability of spiking optical artificial neurons remains challenging and mostly unexplored in experiments. In this work, we report an optical synaptic link between optoelectronic spiking artificial neurons based upon resonant tunneling diodes (RTDs) that allows for cascadable spike propagation.

Systems Modeling of the Water-Energy-Food-Ecosystems Nexus: Insights from a Region Facing Structural Water Scarcity in Southern Spain.

The complex relationship between water, energy, food, and ecological systems, known as the WEFE nexus, has emerged as a major topic in the debate about sustainable economic development and resource management. This subject is of special interest in Mediterranean coastal areas as rapid economic expansion driven by population growth, higher influx of tourists, and intensification of agriculture is leading to structural water scarcity conditions. However, addressing the diverse range of issues associated with the nexus is a difficult task due to the existence of intricate interconnections, interdependencies, and nonlinearities within and across its various components.

The paradox of success: Water resources closure in Axarquia (southern Spain).

Axarquia is a semi-arid region in southern Spain that in the past 25 years has experienced significant population growth, along with an economic boom driven by an increasing influx of tourists to Costa del Sol and the expansion of irrigated export-oriented subtropical crops. The combination of these factors has led to a chronic structural scarcity condition that has been intensified by the occurrence of a long and extreme drought. As a result, its only reservoir has reached historically low levels and the piezometric levels in its main aquifer have decreased significantly, suggesting that groundwater reserves are being overexploited.

Global and single-nucleotide resolution detection of 7-methylguanosine in RNA.

RNA modifications, including -7-methylguanosine (mG), are pivotal in governing RNA stability and gene expression regulation. The accurate detection of internal mG modifications is of paramount significance, given recent associations between altered mG deposition and elevated expression of the methyltransferase METTL1 in various human cancers. The development of robust mG detection techniques has posed a significant challenge in the field of epitranscriptomics.

Acute and chronic risk assessment of BTEX in the return water of hydraulic fracturing operations in Marcellus Shale.

Environmental pollution caused by human activities is a pressing issue in developed countries. In this context, it is vital to establish methodologies for the early and reliable estimation of the health risks posed by potential pollutants. Flowback and produced water (return water) from shale gas operations can contain toxic compounds, of which BTEX (benzene, toluene, ethylbenzene, and xylenes) are of concern due to their toxicity and frequent presence above regulatory limits.

Artificial optoelectronic spiking neuron based on a resonant tunnelling diode coupled to a vertical cavity surface emitting laser.

Excitable optoelectronic devices represent one of the key building blocks for implementation of artificial spiking neurons in neuromorphic (brain-inspired) photonic systems. This work introduces and experimentally investigates an opto-electro-optical (O/E/O) artificial neuron built with a resonant tunnelling diode (RTD) coupled to a photodetector as a receiver and a vertical cavity surface emitting laser as a transmitter. We demonstrate a well-defined excitability threshold, above which the neuron produces optical spiking responses with characteristic neural-like refractory period.

Training deep neural networks with noisy clinical labels: toward accurate detection of prostate cancer in US data.

Purpose: Ultrasound is the standard-of-care to guide the systematic biopsy of the prostate. During the biopsy procedure, up to 12 biopsy cores are randomly sampled from six zones within the prostate, where the histopathology of those cores is used to determine the presence and grade of the cancer. Histopathology reports only provide statistical information on the presence of cancer and do not normally contain fine-grain information of cancer distribution within each core.

Coarse label refinement for improving prostate cancer detection in ultrasound imaging.

Purpose: Ultrasound-guided biopsy plays a major role in prostate cancer (PCa) detection, yet is limited by a high rate of false negatives and low diagnostic yield of the current systematic, non-targeted approaches. Developing machine learning models for accurately identifying cancerous tissue in ultrasound would help sample tissues from regions with higher cancer likelihood. A plausible approach for this purpose is to use individual ultrasound signals corresponding to a core as inputs and consider the histopathology diagnosis for the entire core as labels.

Ultrafast neuromorphic photonic image processing with a VCSEL neuron.

The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these, approaches based upon vertical cavity surface emitting lasers (VCSELs) are attracting interest given their favourable attributes and mature technology.

Exposure risk assessment to organic compounds based on their concentrations in return water from shale gas developments.

Because of shale gas operations, significant amounts of return water from hydraulic fracturing are stored in tanks and/or ponds on the surface. These waters contain varying concentrations of toxic organic compounds; hence, there is reasonable concern about the occurrence of hypothetical leakages, which would cause adverse environmental effects and pose a risk to human health. In this study, the chronic and acute carcinogenic and non-carcinogenic risks from exposure to these pollutants by inhalation, ingestion and dermal contact have been assessed for an affected area.

Towards targeted ultrasound-guided prostate biopsy by incorporating model and label uncertainty in cancer detection.

Purpose: Systematic prostate biopsy is widely used for cancer diagnosis. The procedure is blind to underlying prostate tissue micro-structure; hence, it can lead to a high rate of false negatives. Development of a machine-learning model that can reliably identify suspicious cancer regions is highly desirable.

Image edge detection with a photonic spiking VCSEL-neuron.

We report both experimentally and in theory on the detection of edge features in digital images with an artificial optical spiking neuron based on a vertical-cavity surface-emitting laser (VCSEL). The latter delivers fast (< 100 ps) neuron-like optical spikes in response to optical inputs pre-processed using convolution techniques; hence representing image feature information with a spiking data output directly in the optical domain. The proposed technique is able to detect target edges of different directionalities in digital images by applying individual kernel operators and can achieve complete image edge detection using gradient magnitude.

Automated Nanoscale Absolute Accuracy Alignment System for Transfer Printing.

The heterogeneous integration of micro- and nanoscale devices with on-chip circuits and waveguide platforms is a key enabling technology, with wide-ranging applications in areas including telecommunications, quantum information processing, and sensing. Pick and place integration with absolute positional accuracy at the nanoscale has been previously demonstrated for single proof-of-principle devices. However, to enable scaling of this technology for realization of multielement systems or high throughput manufacturing, the integration process must be compatible with automation while retaining nanoscale accuracy.

High-Throughput Electrical Characterization of Nanomaterials from Room to Cryogenic Temperatures.

We present multiplexer methodology and hardware for nanoelectronic device characterization. This high-throughput and scalable approach to testing large arrays of nanodevices operates from room temperature to milli-Kelvin temperatures and is universally compatible with different materials and integration techniques. We demonstrate the applicability of our approach on two archetypal nanomaterials-graphene and semiconductor nanowires-integrated with a GaAs-based multiplexer using wet or dry transfer methods.

Multiple instance learning combined with label invariant synthetic data for guiding systematic prostate biopsy: a feasibility study.

Purpose: Ultrasound imaging is routinely used in prostate biopsy, which involves obtaining prostate tissue samples using a systematic, yet, non-targeted approach. This approach is blinded to individual patient intraprostatic pathology, and unfortunately, has a high rate of false negatives.

Methods: In this paper, we propose a deep network for improved detection of prostate cancer in systematic biopsy.

Three-dimensional cross-nanowire networks recover full terahertz state.

Terahertz radiation encompasses a wide band of the electromagnetic spectrum, spanning from microwaves to infrared light, and is a particularly powerful tool for both fundamental scientific research and applications such as security screening, communications, quality control, and medical imaging. Considerable information can be conveyed by the full polarization state of terahertz light, yet to date, most time-domain terahertz detectors are sensitive to just one polarization component. Here we demonstrate a nanotechnology-based semiconductor detector using cross-nanowire networks that records the full polarization state of terahertz pulses.

Ultrafast optical integration and pattern classification for neuromorphic photonics based on spiking VCSEL neurons.

In today's data-driven world, the ability to process large data volumes is crucial. Key tasks, such as pattern recognition and image classification, are well suited for artificial neural networks (ANNs) inspired by the brain. Neuromorphic computing approaches aimed towards physical realizations of ANNs have been traditionally supported by micro-electronic platforms, but recently, photonic techniques for neuronal emulation have emerged given their unique properties (e.

Characterization, Selection, and Microassembly of Nanowire Laser Systems.

Semiconductor nanowire (NW) lasers are a promising technology for the realization of coherent optical sources with ultrasmall footprint. To fully realize their potential in on-chip photonic systems, scalable methods are required for dealing with large populations of inhomogeneous devices that are typically randomly distributed on host substrates. In this work two complementary, high-throughput techniques are combined: the characterization of nanowire laser populations using automated optical microscopy, and a high-accuracy transfer-printing process with automatic device spatial registration and transfer.

Forecasting concentrations of organic chemicals in the vadose zone caused by spills of hydraulic fracturing wastewater.

The return water from hydraulic fracturing operations is characterised by high concentrations of salts and toxic organic compounds. This water is stored on the surface in storage tanks and/or ponds. Wastewater spills caused by inappropriate storage can lead to the contamination of various environmental compartments, thus posing a risk to human health.

Externally-Triggered Activation and Inhibition of Optical Pulsating Regimes in Quantum-Dot Mode-locked Lasers.

Controlled generation and inhibition of externally-triggered picosecond optical pulsating regimes are demonstrated experimentally in a quantum dot mode locked laser (QDMLL) subject to external injection of an amplitude modulated optical signal. This approach also allows full control and repeatability of the time windows of generated picosecond optical pulses; hence permitting to define precisely their temporal duration (from <1 ns spans) and repetition frequency (from sub-Hz to at least hundreds of MHz). The use of a monolithic QDMLL, operating at 1300 nm, provides a system with a very small footprint that is fully compatible with optical telecommunication networks.

A model for predicting organic compounds concentration change in water associated with horizontal hydraulic fracturing.

Horizontal drilling and hydraulic fracturing are technologies designed to increase natural gas flow and to improve productivity in low permeability formations. During this drilling operation, tons of flowback and produced water, which contain several organic compounds, return to the surface with a potential risk of influencing the surrounding environment and human health. In order to conduct predictive risk assessments a mathematical model is needed to evaluate organic compound behaviour along the water transportation process as well as concentration changes over time throughout the operational life cycle.

Vertically Emitting Indium Phosphide Nanowire Lasers.

Semiconductor nanowire (NW) lasers have attracted considerable research effort given their excellent promise for nanoscale photonic sources. However, NW lasers currently exhibit poor directionality and high threshold gain, issues critically limiting their prospects for on-chip light sources with extremely reduced footprint and efficient power consumption. Here, we propose a new design and experimentally demonstrate a vertically emitting indium phosphide (InP) NW laser structure showing high emission directionality and reduced energy requirements for operation.

Integration of Semiconductor Nanowire Lasers with Polymeric Waveguide Devices on a Mechanically Flexible Substrate.

Nanowire lasers are integrated with planar waveguide devices using a high positional accuracy microtransfer printing technique. Direct nanowire to waveguide coupling is demonstrated, with coupling losses as low as -17 dB, dominated by mode mismatch between the structures. Coupling is achieved using both end-fire coupling into a waveguide facet, and from nanowire lasers printed directly onto the top surface of the waveguide.

Controlled inhibition of spiking dynamics in VCSELs for neuromorphic photonics: theory and experiments.

We report experimentally and theoretically on the controllable inhibition of spiking regimes in a 1300 nm wavelength vertical-cavity surface-emitting laser. Reproducible suppression of spiking dynamics is demonstrated at fast operation speeds (up to sub-ns rates) and with total control on the temporal duration of the spiking inhibition windows. This Letter opens new paths toward a photonic inhibitory neuronal model system for use in future neuromorphic photonic information processing modules and which are able to operate at speeds up to 8 orders of magnitude faster than biological neurons.

A risk assessment tool applied to the study of shale gas resources.

The implementation of a risk assessment tool with the capacity to evaluate the risks for health, safety and the environment (HSE) from extraction of non-conventional fossil fuel resources by the hydraulic fracturing (fracking) technique can be a useful tool to boost development and progress of the technology and winning public trust and acceptance of this. At the early project stages, the lack of data related the selection of non-conventional gas deposits makes it difficult the use of existing approaches to risk assessment of fluids injected into geologic formations. The qualitative risk assessment tool developed in this work is based on the approach that shale gas exploitation risk is dependent on both the geologic site and the technological aspects.