Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge.

Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is essential for proactive interventions, playing a crucial role in enhancing the management of type 1 diabetes (T1D) and type 2 diabetes (T2D). However, developing a model generalized to a population and subsequently embedding it within a microchip of a wearable device presents significant technical challenges. Furthermore, the domain of BG prediction in T2D remains under-explored in the literature. In light of this, we propose a population-specific BG prediction model, leveraging the capabilities of the temporal fusion Transformer (TFT) to adjust predictions based on personal demographic data. Then the trained model is embedded within a system-on-chip, integral to our low-power and low-cost customized wearable device. This device seamlessly communicates with CGM systems through Bluetooth and provides timely BG predictions using edge computing. When evaluated on two publicly available clinical datasets with a total of 124 participants with T1D or T2D, the embedded TFT model consistently demonstrated superior performance, achieving the lowest prediction errors when compared with a range of machine learning baseline methods. Executing the TFT model on our wearable device requires minimal memory and power consumption, enabling continuous decision support for more than 51 days on a single Li-Poly battery charge. These findings demonstrate the significant potential of the proposed TFT model and wearable device in enhancing the quality of life for people with diabetes and effectively addressing real-world challenges.

A LoC Ion Imaging Platform for Spatio-Temporal Characterisation of Ion-Selective Membranes.

In this paper, a complete Lab-on-Chip (LoC) ion imaging platform for analysing Ion-Selective Membranes (ISM) using CMOS ISFET arrays is presented. An array of 128 × 128 ISFET pixels is employed with each pixel featuring 4 transistors to bias the ISFET to a common drain amplifier. Column-level 2-step readout circuits are designed to compensate for array offset variations in a range of up to ±1 V. The chemical signal associated with a change in ionic concentration is stored and fed back to a programmable gain instrumentation amplifier for compensation and signal amplification through a global system feedback loop. This column-parallel signal pipeline also integrates an 8-bit single slope ADC and an 8-bit R-2R DAC to quantise the processed pixel output. Designed and fabricated in the TSMC 180 nm BCD process, the System-on-Chip (SoC) operates in real time with a maximum frame rate of 1000 fps, whilst occupying a silicon area of 2.3 mm × 4.5 mm. The readout platform features a high-speed digital system to perform system-level feedback compensation with a USB 3.0 interface for data streaming. With this platform we show the first reported analysis and characterisation of ISMs using an ISFETs array through capturing real-time high-speed spatio-temporal information at a resolution of 16 µm in 1000 fps, extracting time-response and sensitivity. This work paves the way of understanding the electrochemical response of ISMs, which are widely used in various biomedical applications.

Silica-Decorated NiAl-Layered Double Oxide for Enhanced CO/CO2 Methanation Performance.

CO/CO2 hydrogenation has attracted much attention as a pathway to achieve carbon neutrality and production of synthetic natural gas (SNG). In this work, two-dimensional NiAl layered double oxide (2D NiAl-LDO) has been successfully decorated by SiO2 nanoparticles derived from SiCl4 and used as CO/CO2 methanation catalysts. The as-obtained H-SiO2-NiAl-LDO exhibited a large specific surface area of 201 m2/g as well as high ratio of metallic Ni0 species and surface adsorption oxygen that were beneficial for low-temperature methanation of CO/CO2. The conversion of CO methanation was 99% at 400 °C, and that of CO2 was 90% at 350 °C. At 250 °C, the CO methanation reached 85% whereas that of CO2 reached 23% at 200 °C. We believe that this provides a simple method to improve the methanation performance of CO and CO2 and a strategy for the modification of other similar catalysts.

An Ultra-High Frame Rate Ion Imaging Platform Using ISFET Arrays With Real-Time Compression.

In this paper, a Lab-on-Chip platform with ultra-high throughput and real-time image compression for high speed ion imaging is presented. The sensing front-end comprises of a CMOS ISFET array with sensors biased in velocity saturation for a linear pH-to-current conversion and high spatial and temporal resolution. An array of 128 × 128 pixels is designed with a pixel size of 13.5 µm × 10.5 µm. In-pixel reset switches are applied for offset compensation, by asynchronously resetting the floating gate of the ISFET to a known fixed potential. Additionally, each row of pixels is processed by a current mode signal pipeline with auto zeroing functionality to remove fixed pattern noise, followed by an on-chip 1 MS/s 8-bit row-parallel single slope ADC. Fabricated in standard TSMC 180 nm BCD process, the entire system-on-chip occupies a silicon area of 2 mm × 2 mm, and achieves a frame rate of 6100 fps (7800 fps from simulation). A high speed 25 ms-latency readout platform based on a USB 3.0 interface and standard JPEG is presented for real-time ion imaging and image compression respectively, while an optimised JPEG algorithm is also designed and verified for a higher compression ratio without sacrificing image quality. We demonstrate real-time ion image visualisation by sensing high speed ion diffusion at 6100 fps, which is more than two times faster than the current state-of-the-art.

A 128 × 128 Current-Mode Ultra-High Frame Rate ISFET Array With In-Pixel Calibration for Real-Time Ion Imaging.

An ultra-high frame rate and high spatial resolution ion-sensing Lab-on-Chip platform using a 128 × 128 CMOS ISFET array is presented. Current mode operation is employed to facilitate high-speed operation, with the ISFET sensors biased in the triode region to provide a linear response. Sensing pixels include a reset switch to allow in-pixel calibration for non-idealities such as offset, trapped charge and drift by periodically resetting the floating gate of the ISFET sensor. Current mode row-parallel signal processing is applied throughout the readout pipeline including auto-zeroing circuits for the removal of fixed pattern noise. The 128 readout signals are multiplexed to eight high-sample-rate on-chip current mode ADCs followed by an off-chip PCIe-based readout system on a FPGA with a latency of 0.15 s. Designed in a 0.35 µm CMOS process, the complete system-on-chip occupies an area of 2.6 × 2.2 [Formula: see text] with a pixel size of 18 × 12.5 µ[Formula: see text] and the whole system achieves a frame rate of 3000 fps which is the highest reported in the literature for ISFET arrays. The platform is demonstrated in the application of real-time ion-imaging through the high-speed visualization of sodium hydroxide (NaOH) diffusion in water at 60 fps on screen in addition to slow-motion playback of ion-dynamics recorded at 3000 fps.

Combustion Products of Calcium Carbide Reused by Cu-Based Catalysts for Acetylene Carbonylation.

Sustainable development is a worldwide concern. This work mainly focuses on the reuse of the combustion products of calcium carbide and the influence of different kinds of copper on the acetylene carbonylation reaction. A series of catalysts were prepared by heating the precursors under various atmospheres (air, hydrogen, and nitrogen). The X-ray diffraction and the X-ray photoelectron spectroscopy have been analyzed regarding copper species composition and content in catalysts. The result of the Cu+-promoted reaction was in good agreement with the conducted density functional theory analysis, and we speculate that Cu+ promotes the transfer of electrons in the reaction. Transmission electron microscopy and elemental mapping evaluation confirmed the difference in Cu dispersion. Characterization of catalysts using temperature programmed desorption and pyridine Fourier-transform infrared revealed differences in their acidity. Acidity was found to be favorable for acetylene carbonylation. Selectivity and yield of the CuAlZn-LDO(N) catalyst at 225 °C were 73 and 70%, respectively, and the catalyst showed good stability over two consecutive cycles of reuse.