Digital Output Research Articles

Surface acoustic wave platform integrated with ultraviolet activated rGO-SnS2 nanocomposites to achieve ppb-level dimethyl methylphosphonate detection at room-temperature

Dimethyl methylphosphonate (DMMP) is commonly used as an alternative for demonstrating to detect sarin, which is one of the most toxic but odorless chemical nerve agents. Among various types of DMMP sensors, those utilizing surface acoustic wave (SAW) technology provide notable advantages such as wireless/passive monitoring, digital output, and a compact, portable design. However, key challenges for SAW-based DMMP sensors operated at room temperature lies in simultaneous enhancement of sensitivities and reduction of detection limits. In this study, we developed a binary material strategy by combining reduced graphene oxide (rGO) and tin disulfide (SnS2) with (100)-facets orientation as sensing layers of SAW device for DMMP detection utilized at room temperature. Ultraviolet (UV) light was applied to activate the sensitive film and reduce the sensor's response time. The developed SAW DMMP sensor demonstrated a superior sensitivity (−1298.82 Hz/ppm), a low detection limit of 50 ppb, and a hysteresis below 1.5%, along with fast response/recovery time (39.2 s/28.4 s), excellent selectivity, long-term stability and repeatability. The formation of shrub-like rGO-SnS2 heterojunctions with abundant surface defects and large specific surface areas, high-energy (100) crystalline surfaces of SnS2, and photogenerated carriers generated by UV irradiation were pinpointed as the crucial sensing mechanisms. These factors collectively enhanced adsorption and reaction dynamics of DMMP molecules.

Monitoring Gene Sequences of Staphylococcus aureus Using a Love-Mode Surface Acoustic Wave Biosensor Coated with Cellulose Acetate/Polyethylenimine Nanofibers and Au Nanoparticles.

Love-mode surface acoustic wave (SAW) sensors show great promise for biodetection applications owing to their low cost, digital output, and wireless passive capability, but their performance is often restricted by the availability of suitable sensitive membrane layers. Herein, a composite layer of electrospun fibers made from cellulose acetate and polyethylenimine, coated with gold nanoparticles, is proposed as a porous and sensitive membrane coated onto a love-mode SAW biosensor for monitoring gene sequences of Staphylococcus aureus. The results showed that the developed sensor exhibited an impressive sensitivity of 122.56 Hz/(nmol/L) for detecting gene sequences of S. aureus, surpassing the sensitivity of conventional SAW sensors employing a bare Au film as the sensitive layer by 5-fold. The analysis revealed a remarkably linear detection (R2 of 0.97827) of S. aureus gene sequences within the range of 0 to 100 nmol/L. The limit of detection was impressively low at 0.9116 nmol/L. The good stability and specificity of the biosensor in liquid environments were demonstrated for clinical diagnostics.

An Energy‐Efficient Fully On‐Chip CMOS Temperature Sensor for Portable Applications With an RFoM of 2.79 pJ.K2

ABSTRACTThis article describes an energy‐efficient, low‐power CMOS temperature sensor suitable for portable applications. The sensor's front‐end circuitry is designed with a reference voltage (V), complementary to absolute temperature (CTAT) voltage (V), and ramp voltage generators. The ramp voltage (V) is produced by utilizing a current reference circuit. The ramp voltage is compared with independent and temperature‐dependent voltages to perform the voltage‐to‐frequency conversion. Conversion from frequency to digital output is achieved through an asynchronous counter with an on‐chip oscillator. The proposed design is realized in a 0.18‐m CMOS technology and attains a power usage of 604.4 nW at 27°C with an operating voltage of 0.5 V. Furthermore, it obtains an inaccuracy of +0.71/−0.73°C over −40°C to 125°C temperature range with an active area of 0.025 mm2. Moreover, the designed sensor circuit offers a resolution of 0.17°C with an energy conversion of 96.7 pJ.

Design of a Portable Electronic Nose for Identification of Minced Chicken Meat Adulterated With Soybean Protein Isolate

ABSTRACTThe study aimed to develop a portable electronic nose system for detecting adulteration with soybean protein isolate (SPI) in chicken meat. The system mainly consisted of three parts: the gas sensor array, the DSP28335 control board, and the upper computer. The DSP28335 control board, developed using C language, included analog to digital converter (ADC) module, digital output (DO) module, pulse width modulation (PWM) module, controller area network (CAN) module, power module, drive circuit, and so forth. The upper computer, developed using LabVIEW, facilitated user interaction with the user by primarily handling CAN configuration and monitoring, displaying and storing sensor data, temperature and flow data, and sending and monitoring electronic nose commands. The feasibility of the proposed electronic nose for characterizing adulterated chicken meat was tested on six classes of chicken meat that had been adulterated with varied quantities of SPI. The mass fractions of SPI were 0%, 5%, 10%, 15%, 20%, and 25%, respectively. On the basis of odor data from the electronic nose, K‐nearest neighbor (KNN), linear discriminant analysis (LDA), and support vector machine (SVM) were applied to qualitatively distinguish minced chicken meat with different adulteration ratios. The results showed that the SVM model had the best recognition effect. When the best parameters (c, g) were c = 16 and g = 1, the accuracy of SVM model was 97.22% and 93.75% in the training and testing sets, respectively. These results demonstrated that the portable electronic nose designed in this paper effectively identifies minced chicken meat under various adulteration conditions, enabling rapid and nondestructive detection of chicken meat adulteration.

Laboratory systems for detonation research

Decarbonizing global energy systems is among the most pertinent challenges in the climate crisis. Tightly tied to the economic prosperity of a nation and responsible for more than 75% of global emissions, decarbonization of the energy sector will require well-developed solutions. The emergence of detonation engines can reduce emissions in aviation and gas-fired power generation, with theoretical efficiencies 40% lower than conventional engines. These efficiencies have yet to be realized in practice, due to our lack of understanding of detonation propagation and its instabilities. This project aimed to develop the laboratory systems required to study detonations. To this end, a long rectangular channel was manufactured and outfitted with a gas handling system to inject a mixture, an ignition system, pressure transducers to capture the propagation characteristics, and an optical system enabling Schlieren photography. The gas handling system uses sonic nozzles, thus flow rate is a linear function of upstream line pressure. Each line contains a pressure transducer, microcontroller to process signals, LCD for pressure readout, and a regulator for adjustment of the line pressure. The ignition system uses an ignition box that steps up a 12 V supply to 400 V, an ignition coil raising the voltage to 15-40 kV, and a spark plug to ignite the mixture. Ignition, pressure transducer signal acquisition, and Schlieren photography are all synchronized using a NI-6356 DAQ with LabVIEW. The DAQs analog input ports receive readings from the pressure transducers along the channel, the timing of which and known distance between transducers allows for velocity calculations. The schlieren system utilizes the digital output channels to synchronize camera shutter with an LED driver, and parabolic mirrors, positioned to optimize schlieren imaging. The LED driver requires greater current than produced by the DAQ thus a current amplifier circuit is used to bridge the DAQ and driver.

A 3D photon-to-digital converter readout for low-power and large-area applications

A new trend in large area noble liquid experiments is to measure the scintillation light with photodetectors and their electronics inside the active volume. Compared to the typical approach of using silicon photomultipliers (SiPM) with an analog readout chain leading to an analog-to-digital converter, this paper presents a new 3D photon-to-digital converter (PDC) readout that takes advantage of the binary nature of the single-photon avalanche diodes (SPAD). The readout contains 4096 pixels over 25 mm2, each including a 3D bonding pad and a quenching circuit. The readout features three different outputs: a fast flag to get the timestamp of each event from an external time-to-digital converter, a digital sum to retrieve the number of pixels triggered during an event, and an analog monitor to generate an analog SiPM-like output. The analog monitor is also used to validate the two former digital outputs. The readout also includes 61 2D CMOS SPADs for validation purpose prior to the final 3D integration with SPADs custom made according to our design by Teledyne DALSA (Bromont, Canada). As a first system integration toward large-area detector applications, a mini-tile of 2 × 2 readouts has been developed to test all the functionalities. The measured single-photon timing resolution ranges from 72 to 93 ps FWHM across the mini-tile SPAD channels population (i.e. 4 × 61 channels). The flag timing resolution is below 95 ps RMS, which includes the contribution of the optimized flag H-tree but also an additional trigger tree that replaces the 3D SPAD array at this stage of development. Once bonded with the 3D SPADs, the trigger tree won't be required to measure the flag timing resolution. With the removed contribution of the trigger tree, the estimated flag timing resolution should be below 45 ps RMS. The extent of the benefits of the digital sum output depend on the application, and this paper focuses on two cases. First, a low-power coincidence scheme such as required by the nEXO liquid xenon experiment, leading to a power consumption as low as 140 μW per PDC. With a finer sampling of the scintillation light such as required for pulse shape discrimination in liquid argon, the power consumption remains below 100 μW per PDC. Overall, this readout is designed as a replacement for a typical analog SiPM chain, without compromise on the performances.

Photovoltaic-Energy-Powered Temperature-Sensing Chip With Digital Output and Built-in Energy Harvesting Circuit

Photovoltaic-Energy-Powered Temperature-Sensing Chip With Digital Output and Built-in Energy Harvesting Circuit

Sensor-based isometric contraction examination tool after ankle sprain injury and ankle instability

Background. Previous studies have examined the application and benefits of sensors, both in sports and health. Unfortunately, the design of sensor-based isometric contraction examination tools after ankle sprain injuries and ankle instability is still rarely carried out. Purpose. The aim of this research is to design a sensor-based isometric contraction examination tool after ankle sprain injury and ankle instability. Material and Methods. The design used is research and development involving experts, namely instrumentation physics, sports physiology, and physiotherapy to assess the suitability of the tool before field trials. The tool developed is the “Isometric Contractions Test”, which is designed in the form of a box with dimensions of 10 cm (height) x 10 cm (width) x 25 cm (length). Various electronic components are also used, such as Arduino Pro Mini, Flexi Sensors, switch buttons, and OLED LCD as digital reading output. A total of 10 participants aged 18-23 years participated voluntarily for the field trial. Participants were men and women who had experienced sub-acute or chronic ankle sprains and ankle instability. The data obtained were analyzed using the correlation method. Result. The results of this study report that this sensor-based isometric contraction examination tool is valid, reliable, effective, and practical in detecting and treating post-injury healing of ankle sprains and ankle instability. Conclusions. This tool can be used to assist physiotherapists in carrying out observations and evaluations to treat healing quickly and precisely, both in athletes and non-athletes.

Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability

Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activity observed in alpha-EEG recordings. The suggested research provides evidence of the reliability of alpha-EEG rhythm in a Gated-Recurrent-Unit-based deep-learning model for investigating SZ. This study suggests Rudiment Densely-Coupled Convolutional Gated Recurrent Unit (RDCGRU) for the various EEG-rhythm-based (gamma, beta, alpha, theta, and delta) diagnoses of SZ. The model includes multiple 1-D-Convolution (Con-1-D) folds with steps greater than 1, which enables the model to programmatically and effectively learn how to reduce the incoming signal. The Con-1-D layers and numerous Gated Recurrent Unit (GRU) layers comprise the Exponential-Linear-Unit activation function. This powerful activation function facilitates in-deep-network training and improves classification performance. The Densely-Coupled Convolutional Gated Recurrent Unit (DCGRU) layers enable RDCGRU to address the training accuracy loss brought on by vanishing or exploding gradients, and this might make it possible to develop intense, deep versions of RDCGRU for more complex problems. The sigmoid activation function is implemented in the digital (binary) classifier's output nodes. The RDCGRU deep learning model attained the most excellent accuracy, 88.88 %, with alpha-EEG rhythm. The research achievements: The RDCGRU deep learning model's GRU cells responded superiorly to the alpha-EEG rhythm in EEG-based verification of SZ.

Design of an Embedded Test Bench for Organic Photovoltaic Module Testing

In this article, a multipurpose embedded system for testing organic photovoltaic modules is presented. It is designed to include all the features for real-time monitoring, data acquisition, and power conversion based on a Ćuk converter, providing useful data for scientific investigation of the outdoor operation of organic photovoltaic modules. The embedded system allows both the scan of the I–V curve and the continuous operation of the organic photovoltaic module, such as at its maximum power. Voltage and current at the terminals of the organic photovoltaic module under test and up to four temperatures are continuously measured and stored on a Secure Digital card. The communication interface allows the embedded system to connect with other instruments, such as irradiance sensors, with digital serial output. The embedded system is designed both for laboratory and in-the-field use: it can be powered either by the AC electrical grid or a battery, which can also operate as a backup battery. Galvanic isolation divides the embedded system into the field-side and the logic-side functional sections, providing improved noise immunity and safe operation. The main power distribution system within the embedded system is a +9 V bus; ultra-low-noise linear low dropout regulators provide the +3.3 V and +5 V regulated voltages to supply the analog and digital circuits within the logic-side section, and a flyback converter supplies the field-side section of the board. The proposed embedded solution is validated using an experimental setup built at SolarTechLab, Politecnico di Milano. The experimental results report the feasibility of the proposed embedded system.

Achieving new excellence in an augmented reality dental education system

Background/purposeSimEx-Plus (EPED. Inc) was already a mature augmented reality (AR) dental training simulator that allowed students to have a high quality dental education practice. Now the EPCAD software has been further developed into a comprehensive computer-aided design software. It helps relevant professionals learn how to create digital fixed prosthesis in a virtual environment. This study used the newly developed EPCAD software that was integrated within the SimEx-Plus to design dental restorations then digital output milling restorations. We hope that the SimEx-Plus AR dental training simulator can achieve the multi-purpose function in one machine. Materials and methodsA right maxillary central incisor was prepared in the standard dental model. The restorations were designed by EPCAD software integrated with the SimEx-Plus and milled by a 4-axis dental milling machine (N4+, vhf camfacture AG). The internal gap of the restoration was evaluated. ResultsThe internal gaps of the crowns set on the right maxillary central incisor were among 68.27–89.80 μm. The different setting for digital output did not influence the internal gap (P 0.05, One-Way ANOVA). However, the internal gap on the palatal side was larger than that on the labial, mesial, distal, and incisal surfaces (P < 0.05, One-Way ANOVA). ConclusionThe new software EPCAD that was integrated within the SimEx-Plus AR dental training simulator could design restorations, and the designed restorations had good internal gap for clinical use. The professionals can learn tooth preparation and digital restoration fabrication by the SimEx-Plus AR dental training system.

Implementation of a high-resolution micro-grating accelerometer using a subdivision interpolation technique

This paper proposes a subdivision interpolation technique for an optical accelerometer based on diffraction grating interferometry. The diffraction light intensity curve presents a sine shape with the increase of the acceleration. To address the issues of linearization signal processing across the entire range, a subdivision interpolation circuit is employed, in conjunction with a 90° phase shift and high-precision DC bias-voltage techniques, converting an analog signal with sinusoidal characteristics from the photodetector into standard incremental digital signals that vary linearly over the full range. The novel methodology, to the best of our knowledge, ensures that its performance is least affected by the phase imbalance, offset error, and amplitude mismatch induced by fabrication and alignment errors of the grating, achieving high-resolution digital signal output. The experiment results reveal that the optical accelerometer based on grating interferometry achieved a sensitivity of 85.2 V/g, a resolution of 137.6 µg, as well as a subdivision interpolation factor of 45. This work provides a significant guide for the development of high-resolution MOEMS accelerometers in practical applications.

Spatial differentiation and driving factors of scientific and technological innovation efficiency under the background of the digital economy

Scientific and technological innovation (STI) activities are facilitated under the influence of the digital economy and depend on digital elements to support innovation activities. This study measures digital element inputs and outputs using data related to the digital economy and estimates STI efficiency in 29 provincial regions in mainland China from 2010 to 2021 employing the global super-efficiency slacks-based measure (SBM) model. Then, spatial characteristics and driving forces of STI efficiency are quantified using spatial autocorrelation and geographic detectors. The results reveal that STI efficiency exhibits a fluctuating, W-shaped pattern, and the spatial correlation effect shows a gradually declining trend from 2010 to 2021. The findings reveal that the core drivers of STI efficiency are digital financial development, e-commerce development, digital access level, and related factors. Therefore, strengthening inter-regional innovation links, promoting the construction of 5 G mobile internet and accelerating the integration of digital industries into traditional industries are recommended.

Genetic neural network based background calibration method for pipeline ADC

This article presents a pipeline analog-to-digital converter (ADC) background calibration method that combines genetic algorithm (GA) and neural network (NN) algorithm. The proposed method uses ADC outputs or individual stage sub-ADC outputs for NN training, employs GA for global optimization of the NN's initial setup to avoid local optima traps, and utilizes a parallel pipeline architecture to create a high-throughput calibration circuit with optimized multiply-accumulator (MAC) to minimize resource consumption. Through simulation on a 6-stage 14-bit pipelined ADC model, the proposed method demonstrated superiority over traditional calibration techniques and other NN-based calibration strategies. Specifically, after calibration, the signal-to-noise ratio (SNDR), spurious-free dynamic range (SFDR), and effective number of bits (ENOB) are significantly improved from 57.72 dB, 59.77 dB, and 8.79 bits to 104.61 dB, 152.64 dB, and 17.08 bits, respectively.

An Algorithm for Automated Measurement of Kinetic Tremor Magnitude Using Digital Spiral Drawings

Introduction: Essential tremor is a common movement disorder. Numerous validated clinical rating scales exist to quantify essential tremor severity by employing rater-dependent visual observation but have limitations, including the need for trained human raters and the lack of precision and sensitivity compared to technology-based objective measures. Other continuous objective methods to quantify tremor amplitude have been developed, but frequently provide unitless measures (e.g., tremor power), limiting real-world interpretability. We propose a novel algorithm to measure kinetic tremor amplitude using digital spiral drawings, applying the V3 framework (sensor verification, analytical validation, and clinical validation) to establish reliability and clinical utility. Methods: Archimedes spiral drawings were recorded on a digitizing tablet from participants (n = 7) enrolled in a randomized placebo control double-blinded crossover pilot trial evaluating the efficacy of oral cannabinoids in reducing essential tremor. We developed an algorithm to calculate the mean and maximum tremor amplitude derived from the spiral tracings. We compared the digitally measured tremor amplitudes to manual measurement to evaluate sensor reliability, determined the test-retest reliability of the digital output across two short-interval repeated measures, and compared the digital measure to kinetic tremor severity graded using The Essential Tremor Rating Assessment Scale (TETRAS) score for spiral drawings. Results: This algorithm for automated assessment of kinetic tremor amplitude from digital spiral tracings demonstrated a high correlation with manual spot measures of tremor amplitude, excellent test-retest reliability, and a high correlation with human ratings of the TETRAS score for spiral drawing severity when the tremor severity was rated “slight tremor” or worse. Discussion: This digital measure provides a simple and clinically relevant evaluation of kinetic tremor amplitude that shows promise as a potential future endpoint for use in clinical trials of essential tremor.

Intan Technologies integrated circuits can produce analog-to-digital conversion artifacts that affect neural signal acquisition

Objective. Intan Technologies’ integrated circuits (ICs) are valuable tools for neurophysiological data acquisition, providing signal amplification, filtering, and digitization from many channels (up to 64 channels/chip) at high sampling rates (up to 30 kSPS) within a compact package (⩽9× 7 mm). However, we found that the analog-to-digital converters (ADCs) in the Intan RHD2000 series ICs can produce artifacts in recorded signals. Here, we examine the effects of these ADC artifacts on neural signal quality and describe a method to detect them in recorded data. Approach. We identified two types of ADC artifacts produced by Intan ICs: 1) jumps, resulting from missing output codes, and 2) flatlines, resulting from overrepresented output codes. We identified ADC artifacts in neural recordings acquired with Intan RHD2000 ICs and tested the repeated performance of 17 ICs in vitro. With the on-chip digital-signal-processing disabled, we detected the ADC artifacts in each test recording by examining the distribution of unfiltered ADC output codes. Main Results. We found larger ADC artifacts in recordings using the Intan RHX data acquisition software versions 3.0–3.2, which did not run the necessary ADC calibration command when the inputs to the Intan recording controller were rescanned. This has been corrected in the Intan RHX software version 3.3. We found that the ADC calibration routine significantly reduced, but did not fully eliminate, the occurrence and size of ADC artifacts as compared with recordings acquired when the calibration routine was not run (p < 0.0001). When the ADC calibration routine was run, we found that the artifacts produced by each ADC were consistent over time, enabling us to sort ICs by performance. Significance. Our findings call attention to the importance of evaluating signal quality when acquiring electrophysiological data using Intan Technologies ICs and offer a method for detecting ADC artifacts in recorded data.

PLATO’s signal and noise budget

ESA’s PLATO mission aims the detection and characterization of terrestrial planets around solar-type stars as well as the study of host star properties. The noise-to-signal ratio (NSR) is the main performance parameter of the PLATO instrument, which consists of 24 Normal Cameras and 2 Fast Cameras. In order to justify, verify and breakdown NSR-relevant requirements the software simulator PINE was developed. PINE models the signal pathway from a target star to the digital output of a camera based on physical models and considers the major noise contributors. In this paper, the simulator’s coarse mode is introduced which allows fast performance analyses on instrument level. The added value of PINE is illustrated by exemplary applications.

Design of Fluxgate Current Sensor Based on Magnetization Residence Times and Neural Networks.

This study introduces a novel fluxgate current sensor with a compact, ring-shaped configuration that exhibits improved performance through the integration of magnetization residence times and neural networks. The sensor distinguishes itself with a unique magnetization profile, denoted as M waves, which emerge from the interaction between the target signal and ambient magnetic interference, effectively enhancing interference suppression. These M waves highlight the non-linear coupling between the magnetic field and magnetization residence times. Detection of these residence times is accomplished using full-wave rectification circuits and a Schmitt trigger, with a digital output provided by timing sequence detection. A dual-layer feedforward neural network deciphers the target signal, exploiting this non-linear relationship. The sensor achieves a linearity error of 0.054% within a measurement range of 15 A. When juxtaposed with conventional sensors utilizing the residence-time difference strategy, our sensor reduces linearity error by more than 40-fold and extends the effective measurement range by 150%. Furthermore, it demonstrates a significant decrease in ambient magnetic interference.

Unearthing new learning opportunities: adapting and innovating through the 'Antibiotics under our feet' citizen science project in Scotland during COVID-19.

'Antibiotics under our feet' is a Scottish citizen science project that aimed to raise science capital in primary school learners and their teachers through measurement of microbial diversity in urban soil samples in the search for novel antimicrobial compounds. Resistance to antibiotics is rising, posing a global threat to human health. Furthermore, science, technology, engineering and mathematics (STEM) skills are in crisis, jeopardising our capacity to mobilise as a society to fight antimicrobial resistance (AMR). Originally conceived as a response to the AMR and STEM emergencies, our project was hit by the unprecedented challenge of engaging with schools during the COVID-19 pandemic. We describe how we adapted our project to enable remote participation from primary schools and youth groups, utilising COVID-19 response initiatives as opportunities for multi-level co-creation of resources with learners in primary, secondary, and higher education. We produced portable kit boxes for soil sample collection with learning activities and videos linked to the Scottish Curriculum for Excellence. We also addressed glaring project specific content gaps relating to microbiology on English and Simple English Wikipedia. Our hybrid model of working extended our geographical reach and broadened inclusion. We present here the inception, implementation, digital resource outputs, and discussion of pedagogical aspects of 'Antibiotics under our feet'. Our strategies and insights are applicable post-pandemic for educators to develop STEM skills using soil, microbes, and antibiotics as a theme.

Multipurpose error calibration of pipeline analog‐to‐digital converters using decision points of the residue curve in sub‐analog‐to‐digital converters

SummaryA new mechanism of digital background calibration in pipeline analog‐to‐digital converters (ADCs) is expressed. The presented technique calibrates various errors like capacitor mismatch, finite DC gain of the amplifier, third‐order nonlinearity, and fifth‐order nonlinearity, so it is called multipurpose. In this method, the error coefficients are identified by estimation of the output code of the decision points in the voltage transfer characteristic (VTC) of the pipeline stages. To achieve sufficient decision points in the VTCs of the pipeline stages, one threshold level of one comparator of the sub‐ADC is shifted, and then the digital output is calibrated by capturing the error coefficients. The digital logic of this method is simple and does not require special analog circuits. The introduced calibration mechanism is evaluated for the first five stages of a 12‐bit 100 MS/s pipeline ADC. The required time for the calibration is 1.5 ms. By applying this method, the signal‐to‐noise and distortion ratio (SNDR) and spurious‐free dynamic range (SFDR) in order are enhanced from 46.44 and 50.53 dB to 69.92 and 74.04 dB, respectively.