Low-Power Analog Integrated Architecture of the Voting Classification Algorithm for Diabetes Disease Prediction.

A low-power (∼ 600nW), fully analog integrated architecture for a voting classification algorithm is introduced. It can effectively handle multiple-input features, maintaining exceptional levels of accuracy and with very low power consumption. The proposed architecture is based on a versatile Voting algorithm that selectively incorporates one of three key classification models: Bayes or Centroid, or, the Learning Vector Quantization model; all of which are implemented using Gaussian-likelihood and Euclidean distance function circuits, as well as a current comparison circuit. To evaluate the proposed architecture, a comprehensive comparison with popular analog classifiers is performed, using real-life diabetes dataset. All model architectures were trained using Python and compared with the software-based classifiers. The circuit implementations were performed using the TSMC 90 nm CMOS process technology and the Cadence IC Suite was utilized for the design, schematic and post-layout simulations. The proposed classifiers achieved sensitivity of ≥ 96.7% and specificity of ≥ 89.7%.

Stochastic modelling of intersectional pay gaps in universities.

The gender and ethnicity pay gaps are well publicised for academics. The majority of research relies on observations representing a point in time or uses models to consider a standard academic lifespan. We use a stochastic mathematical model to ask what drives differences in lifetime earnings of university academics and highlight a new question: how best should we quantify a working lifetime? The model observes and accounts for patterns in age when entering and leaving the workforce, and differing salary trajectories during an academic career. It is parameterized with data from a national dataset in Aotearoa New Zealand. We compare the total lifetime earnings of different gender and ethnicity groups with and without accounting for the different lengths of time spent in academia. The lifetime earnings gaps are considerably larger when we account for different hiring and leaving ages. We find that overall, for every ethnicity, women have shorter careers and are more likely to leave academia. All minority ethnic groups-and women-earn considerably less than their male white, European colleagues.

Graphene-based RRAM devices for neural computing.

Resistive random access memory is very well known for its potential application in in-memory and neural computing. However, they often have different types of device-to-device and cycle-to-cycle variability. This makes it harder to build highly accurate crossbar arrays. Traditional RRAM designs make use of various filament-based oxide materials for creating a channel that is sandwiched between two electrodes to form a two-terminal structure. They are often subjected to mechanical and electrical stress over repeated read-and-write cycles. The behavior of these devices often varies in practice across wafer arrays over these stresses when fabricated. The use of emerging 2D materials is explored to improve electrical endurance, long retention time, high switching speed, and fewer power losses. This study provides an in-depth exploration of neuro-memristive computing and its potential applications, focusing specifically on the utilization of graphene and 2D materials in RRAM for neural computing. The study presents a comprehensive analysis of the structural and design aspects of graphene-based RRAM, along with a thorough examination of commercially available RRAM models and their fabrication techniques. Furthermore, the study investigates the diverse range of applications that can benefit from graphene-based RRAM devices.

Anticholinergic exposure and its association with dementia/Alzheimer's disease and mortality in older adults.

BACKGROUND: Use of anticholinergic (ACH) medications is associated with increased risk of cognitive decline in the elderly. However, little is known about this association from a health plan perspective. METHODS: This retrospective cohort study used the Humana Research Database to identify individuals with at least one ACH medication dispensed in 2015. Patients were followed until incidence of dementia/Alzheimer's disease, death, disenrollment or end of December 2019. Multivariate Cox regression models were used to assess the association between ACH exposure and study outcomes, adjusting for demographics and clinical characteristics. RESULTS: A total of 12,209 individuals with no prior ACH use or dementia/Alzheimer's disease diagnosis were included. As ACH polypharmacy increased (i.e., from no ACH exposure, to one, two, three, and four or more ACH medications), there was a stair-step increase in the incidence rate of dementia/Alzheimer's disease (15, 30, 46, 56 and 77 per 1,000 person-years of follow-up) and in the incidence of mortality (19, 37, 80, 115 and 159 per 1,000 person-years of follow-up). After adjusting for confounders, ACH exposure to one, two, three and four or more ACH medications was associated with a 1.6 (95% CI 1.4-1.9), 2.1 (95% CI 1.7-2.8), 2.6 (95% CI 1.5-4.4), and 2.6 (95% CI 1.1-6.3) times, respectively, increased risk of a dementia/Alzheimer's disease diagnosis compared to periods of no ACH exposure. ACH exposure to one, two, three and four or more medications was associated with a 1.4 (95% CI 1.2-1.6), 2.6 (95% CI 2.1-3.3), 3.8 (95% CI 2.6-5.4), and 3.4 (95% CI 1.8-6.4) times, respectively, increased risk of mortality compared to periods of no ACH exposure. CONCLUSIONS: Reducing ACH exposure may potentially minimize long-term adverse effects in older adults. Results suggest populations which may benefit from targeted interventions to reduce ACH polypharmacy.

Factors Associated with Perioperative Transfusions in Veterans.

Background: Private sector literature demonstrates an association between perioperative transfusions and poor clinical outcomes. Hemostatic agents, surgeon training, and patient blood management programs (PBMPs) may mitigate perioperative bleeding. This study attempts to identify preoperative risk factors associated with perioperative transfusions in Veterans. Study Design and Methods: This study is a retrospective review of the prospectively maintained Veterans Affairs Surgical Quality Improvement Project database. Included patients were older than 18 years and underwent noncardiac surgery between April 1, 2016, and March 31, 2021. Data collected included demographics, surgery variables, preoperative clinical variables, postoperative outcomes, and perioperative transfusions. Cohorts were created based on transfusion status. Univariate and multivariate analyses were performed to characterize the similarities, differences, and potential predictors of perioperative transfusion. Results: Of 6108 patients included, 153 patients received perioperative transfusions. The risks for transfusion included older age, male sex, black race, smoking, and low body mass index (BMI). The highest percent of transfused patients underwent vascular (43.4%), orthopedic (22%), and general surgeries (20%). Transfusion increased risk for postoperative cerebral vascular accident (P = .041) and 30-day mortality (P < .001). Multivariate regression analysis revealed American Society of Anesthesiology class, chemotherapy within 30 days, increased age, tobacco smoking, and decreased BMI were predictive of perioperative transfusions. Discussion: Perioperative transfusions are associated with increased morbidity and mortality in the Veteran population. These retrospective data describe the complex relationships between perioperative transfusions and outcomes after noncardiac surgery. These results serve as a foundation to create predictive models and PBMP within the veteran population to decrease transfusion requirements and associated complications.

Brood size in an uncertain world.

Reproduction in an uncertain world is fraught. The consequences of investing in too many offspring in a resource poor season can be disastrous but so too is missing the opportunity of a resource rich year. We consider a simple population and individual growth model and use Lyapunov exponents to find analytical results for the optimum brood size under stochastic environmental conditions. We show that if the environment shows dramatic changes between breeding seasons choosing a smaller brood size is more likely to be successful but the best strategy is to synchronize your reproduction to the food availability. Finally, we show that if the cost of having offspring is high it can be better to live in a highly varying world with a plastic strategy that synchronizes to the environment than to live in a deterministic world with a constant strategy, a finding with implications for invasive species and climate change.

Current state of radiomic research in pancreatic cancer: focusing on study design and reproducibility of findings.

OBJECTIVES: To critically appraise methodology and reproducibility of published studies on CT radiomics of pancreatic ductal adenocarcinoma (PDAC). METHODS: PRISMA literature search of MEDLINE, PubMed, and Scopus databases was conducted from June to August 2022 relating to CT radiomics human research articles pertaining to PDAC diagnosis, treatment, and/ or prognosis, utilising Image Biomarker Standardisation Initiative-compliant (IBSI) radiomic software. Keyword search included [pancreas OR pancreatic] AND [radiomic OR [quantitative AND imaging] OR [texture AND analysis]]. Analysis included cohort size, CT protocol used, radiomic feature (RF) extraction, segmentation, and selection, software used, outcome correlation, and statistical methodology, with focus on reproducibility. RESULTS: Initial search yielded 1112 articles; however, only 12 articles met all inclusion/exclusion criteria. Cohort sizes ranged from 37 to 352 (median = 106, mean = 155.8). CT slice thickness varied among studies (4 using ≤ 1 mm, 5 using > 1 to 3 mm, 2 using > 3 to 5 mm, 1 not specifying). CT protocol varied (5 using a single portal-venous (pv)-phase, 5 using a pancreas protocol, 1 study using a non-contrast protocol). RF extraction and segmentation were heterogeneous (RF extraction: 5 using pv-phase, 2 using late arterial, 4 using multi-phase, 1 using non-contrast phase; RF selection: 3 pre-selected, 9 software-selected). 2D/3D RF segmentation was diverse (2D in 6, 3D in 4, 2D and 3D in 2 studies). Six different radiomics software were used. Research questions and cohort characteristics varied, ultimately leading to non-comparable outcome results. CONCLUSION: The current twelve published IBSI-compliant PDAC radiomic studies show high variability and often incomplete methodology resulting in low robustness and reproducibility. CLINICAL RELEVANCE STATEMENT: Radiomics research requires IBSI compliance, data harmonisation, and reproducible feature extraction methods for non-invasive imaging biomarker discoveries to be valid. This will ensure a successful clinical implementation and ultimately an improvement of patient outcomes as part of precision and personalised medicine. KEY POINTS: • Current state of radiomics research in pancreatic cancer shows low software compliance to the Image Biomarker Standardisation Initiative (IBSI). • IBSI-compliant radiomics studies in pancreatic cancer are heterogeneous and not comparable, and the majority of study designs showed low reproducibility. • Improved methodology and standardisation of practice in the emerging field of radiomics has the potential of this non-invasive imaging biomarker in the management of pancreatic cancer.

Rapid prototyping mixed-signal development kit for tactile neural computing.

Intelligent sensor systems are essential for building modern Internet of Things applications. Embedding intelligence within or near sensors provides a strong case for analog neural computing. However, rapid prototyping of analog or mixed signal spiking neural computing is a non-trivial and time-consuming task. We introduce mixed-mode neural computing arrays for near-sensor-intelligent computing implemented with Field-Programmable Analog Arrays (FPAA) and Field-Programmable Gate Arrays (FPGA). The combinations of FPAA and FPGA pipelines ensure rapid prototyping and design optimization before finalizing the on-chip implementations. The proposed approach architecture ensures a scalable neural network testing framework along with sensor integration. The experimental set up of the proposed tactile sensing system in demonstrated. The initial simulations are carried out in SPICE, and the real-time implementation is validated on FPAA and FPGA hardware.

Targeted design of porous materials without strong, directional interactions.

A porous molecular crystal (TSCl) was found to crystallise from dichloromethane and water during the synthesis of tetrakis(4-sulfophenylmethane). Crystal structure prediction (CSP) rationalises the driving force behind the formation of this porous TSCl phase and the intermolecular interactions that direct its formation. Gas sorption analysis showed that TSCl is permanently porous with selective adsorption of CO2 over N2, H2 and CH4 and a maximum CO2 uptake of 74 cm3 g-1 at 195 K. Calculations revealed that TSCl assembles via a combination of weak hydrogen bonds and strong dispersion interactions. This illustrates that CSP can underpin approaches to crystal engineering that do not involve more intuitive directional interactions, such as hydrogen bonding.

Levers of change: using mathematical models to compare gender equity interventions in universities.

Women are under-represented in academic staff in universities worldwide. Our work builds on other studies of 'demographic inertia'. We find that time will not bridge the gender representation gap in academia, and echo others in saying bold actions are required to reach parity. Our work then uses New Zealand's unique system of scoring individual research performance to test empirically which levers universities should pull, and in which combinations. We combine individual research performance scores with 20 years of data from one university to parametrize a rank-structured mathematical model using Leslie matrices. Our model compares three key levers of change at universities' disposal-hiring, promotion and attrition. We apply the model to a bifurcated population of university staff-those with high research activity, and those who are moderately active-based on their national research quality score. We then test levers in various combinations that management could pull to improve gender representation. We find that the solutions are different for the high versus moderate research performers. For individuals with high research activity, universities should concentrate on equitable hiring practices. For those with more moderate research activity, more equitable promotion practices hold the key.

Predicting elimination of evolving virus variants.

As the SARS-CoV-2 virus spreads around the world new variants are appearing regularly. Although some countries have achieved very swift and successful vaccination campaigns, on a global scale the vast majority of the population is unvaccinated and new variants are proving more resistant to the current set of vaccines. We present a simple model of disease spread, which includes the evolution of new variants of a novel virus and varying vaccine effectiveness to these new strains. We show that rapid vaccine updates to target new strains are more effective than slow updates and containing spread through non-pharmaceutical interventions is vital while these vaccines are delivered. Finally, when measuring the key model inputs, e.g. the rate at which new mutations and variants of concern emerge, is difficult we show how an observable model output, the number of new variants that have been seen, is strongly correlated with the probability the virus is eliminated.

Estimating decay curves of neutralizing antibodies to SARS-CoV-2 infection.

Estimating the longevity of an individual's immune response to the SARS-Cov-2 virus is vital for future planning, particularly of vaccine requirements. Neutralizing antibodies (Nabs) are increasingly being recognized as a correlate of protection and while there are many studies that follow the response of a cohort of people, each study alone is not enough to predict the long-term response. Studies use different assays to measure Nabs, making them hard to combine. We present a modelling method that can combine multiple datasets and can be updated as more detailed data becomes available. Combining data from seven published datasets we predict that the NAb decay has two phases, an initial fast but short-lived decay period followed by a longer term and slower decay period.

Potential reduction in transmission of COVID-19 by digital contact tracing systems: a modelling study.

BACKGROUND: Digital tools are being developed to support contact tracing as part of the global effort to control the spread of COVID-19. These include smartphone apps, Bluetooth-based proximity detection, location tracking and automatic exposure notification features. Evidence on the effectiveness of alternative approaches to digital contact tracing is so far limited. METHODS: We use an age-structured branching process model of the transmission of COVID-19 in different settings to estimate the potential of manual contact tracing and digital tracing systems to help control the epidemic. We investigate the effect of the uptake rate and proportion of contacts recorded by the digital system on key model outputs: the effective reproduction number, the mean outbreak size after 30 days and the probability of elimination. RESULTS: Effective manual contact tracing can reduce the effective reproduction number from 2.4 to around 1.5. The addition of a digital tracing system with a high uptake rate over 75% could further reduce the effective reproduction number to around 1.1. Fully automated digital tracing without manual contact tracing is predicted to be much less effective. CONCLUSIONS: For digital tracing systems to make a significant contribution to the control of COVID-19, they need be designed in close conjunction with public health agencies to support and complement manual contact tracing by trained professionals.

I've Got a Girl Crush: Parents' Responses to Stories about Sexuality in Children's Television.

People harbor unique biases about the relative influence of popular media on themselves compared to others. Broadly, they expect others to experience greater harm from exposure to negative depictions (e.g., violent content) and to derive fewer benefits from exposure to positive depictions (e.g., educational content). The current experiment examined if these biases impact how parents monitor their children's television exposure, specifically programs about same-sex attraction. Parents (N = 702) watched a cartoon about a young girl who expresses romantic interest in another girl. Although biases emerged with regard to parents' beliefs that this content would harm or benefit their own (vs. other) children, these biases did not influence their monitoring intentions. Instead, parents with conservative (vs. liberal) attitudes perceived the show as more threatening and less valuable for all children, which enhanced their desire to criticize, restrict, and censor that content.

Out-of-hospital cardiac arrest due to hanging: a retrospective analysis.

BACKGROUND: There has been little research into the prehospital management of cardiac arrest following hanging despite it being among the most prevalent methods of suicide worldwide. The aim of this study was to report the characteristics, resuscitative treatment and outcomes of patients managed in the prehospital environment for cardiac arrest secondary to hanging and compare these with all-cause out-of-hospital cardiac arrest (OHCA). METHODS: Data from a UK ambulance service cardiac arrest registry were extracted for all cases in which treatment was provided for OHCA due to hanging between 1 January 2013 and 30 June 2018. Cases were linked to outcome data obtained from the Trauma Audit and Research Network. Comparison of the cohort was made to previously published data from a UK study of all-cause OHCA with 95% CIs calculated for the proportional difference between the studies in selected presentation and outcome variables. RESULTS: 189 cases were identified. 95 patients were conveyed to hospital and four of these survived to discharge. 40 patients were conveyed despite absence of a spontaneous circulation and none of these patients survived. While only three patients were initially in a shockable rhythm, DC shocks were administered in 20 cases. There was one case of failed ventilation prompting front-of-neck access for oxygenation. By comparison with all-cause OHCA the proportion of patients with a spontaneous circulation at hospital handover was similar (27.0% vs 27.5%; 0.5% difference, 95% CI -5.9% to 6.8%, p=0.882) but survival to hospital discharge was significantly lower (2.2% vs 8.4%; 6.2% difference, 95% CI 4.1% to 8.3%, p=0.002). CONCLUSION: Clinical outcomes following OHCA due to hanging are poor, particularly when patients are transported while in cardiac arrest. Failure to ventilate was uncommon, and clinicians should be alert to the possibility of shockable rhythms developing during resuscitation.

Early intervention is the key to success in COVID-19 control.

New Zealand responded to the COVID-19 pandemic with a combination of border restrictions and an Alert Level (AL) system that included strict stay-at-home orders. These interventions were successful in containing an outbreak and ultimately eliminating community transmission of COVID-19 in June 2020. The timing of interventions is crucial to their success. Delaying interventions may reduce their effectiveness and mean that they need to be maintained for a longer period. We use a stochastic branching process model of COVID-19 transmission and control to simulate the epidemic trajectory in New Zealand's March-April 2020 outbreak and the effect of its interventions. We calculate key measures, including the number of reported cases and deaths, and the probability of elimination within a specified time frame. By comparing these measures under alternative timings of interventions, we show that changing the timing of AL4 (the strictest level of restrictions) has a far greater impact than the timing of border measures. Delaying AL4 restrictions results in considerably worse outcomes. Implementing border measures alone, without AL4 restrictions, is insufficient to control the outbreak. We conclude that the early introduction of stay-at-home orders was crucial in reducing the number of cases and deaths, enabling elimination.

Generalised Analog LSTMs Recurrent Modules for Neural Computing.

The human brain can be considered as a complex dynamic and recurrent neural network. There are several models for neural networks of the human brain, that cover sensory to cortical information processing. Large majority models include feedback mechanisms that are hard to formalise to realistic applications. Recurrent neural networks and Long short-term memory (LSTM) inspire from the neuronal feedback networks. Long short-term memory (LSTM) prevent vanishing and exploding gradients problems faced by simple recurrent neural networks and has the ability to process order-dependent data. Such recurrent neural units can be replicated in hardware and interfaced with analog sensors for efficient and miniaturised implementation of intelligent processing. Implementation of analog memristive LSTM hardware is an open research problem and can offer the advantages of continuous domain analog computing with relatively low on-chip area compared with a digital-only implementation. Designed for solving time-series prediction problems, overall architectures and circuits were tested with TSMC 0.18 µm CMOS technology and hafnium-oxide (HfO 2) based memristor crossbars. Extensive circuit based SPICE simulations with over 3,500 (inference only) and 300 system-level simulations (training and inference) were performed for benchmarking the system performance of the proposed implementations. The analysis includes Monte Carlo simulations for the variability of memristors' conductance, and crossbar parasitic, where non-idealities of hybrid CMOS-memristor circuits are taken into the account.

Maori and Pacific people in New Zealand have a higher risk of hospitalisation for COVID-19.

AIMS: We aim to quantify differences in clinical outcomes from COVID-19 infection in Aotearoa New Zealand by ethnicity and with a focus on risk of hospitalisation. METHODS: We used data on age, ethnicity, deprivation index, pre-existing health conditions and clinical outcomes on 1,829 COVID-19 cases reported in New Zealand. We used a logistic regression model to calculate odds ratios for the risk of hospitalisation by ethnicity. We also considered length of hospital stay and risk of fatality. RESULTS: After controlling for age and pre-existing conditions, we found that Maori have 2.50 times greater odds of hospitalisation (95% CI 1.39-4.51) than non-Maori non-Pacific people. Pacific people have three times greater odds (95% CI 1.75-5.33). CONCLUSIONS: Structural inequities and systemic racism in the healthcare system mean that Maori and Pacific communities face a much greater health burden from COVID-19. Older people and those with pre-existing health conditions are also at greater risk. This should inform future policy decisions including prioritising groups for vaccination.

Worldwide border interceptions provide a window into human-mediated global insect movement.

As part of national biosecurity programs, cargo imports, passenger baggage, and international mail are inspected at ports of entry to verify compliance with phytosanitary regulations and to intercept potentially damaging nonnative species to prevent their introduction. Detection of organisms during inspections may also provide crucial information about the species composition and relative arrival rates in invasion pathways that can inform the implementation of other biosecurity practices such as quarantines and surveillance. In most regions, insects are the main taxonomic group encountered during inspections. We gathered insect interception data from nine world regions collected from 1995 to 2019 to compare the composition of species arriving at ports in these regions. Collectively, 8,716 insect species were intercepted in these regions over the last 25 yr, with the combined international data set comprising 1,899,573 interception events, of which 863,972 were identified to species level. Rarefaction analysis indicated that interceptions comprise only a small fraction of species present in invasion pathways. Despite differences in inspection methodologies, as well as differences in the composition of import source regions and imported commodities, we found strong positive correlations in species interception frequencies between regions, particularly within the Hemiptera and Thysanoptera. There were also significant differences in species frequencies among insects intercepted in different regions. Nevertheless, integrating interception data among multiple regions would be valuable for estimating invasion risks for insect species with high likelihoods of introduction as well as for identifying rare but potentially damaging species.