Transparent and Flexible Thin Film Electroluminescent Devices Using HiTUS Deposition and Laser Processing Fabrication

Highly transparent thin film electroluminescent structures offering excellent switch on characteristics, high luminance and large break-down voltages have been deposited onto glass and flexible polymeric materials with no substrate heating using high target utilization sputtering. Deposition of ZnS:Mn as the active light emitting layer and Y2O3,Al2O3,Ta2O5, and HfO2 as dielectric materials arranged in single and multiple layer configurations were investigated. Devices incorporating Al2O3,HfO2 quadruple layers demonstrate the highest attainable luminance at low threshold voltage. Single pulse excimer laser irradiation of the phosphor layer prior to deposition of the top dielectric layer enhanced the luminance of the devices. The devices fabricated on glass and polymeric substrates exhibited a maximum luminance of 500 and 450 cdm−2 when driven at 270 VRMS and 220 VRMS, respectively, with a 1.0 kHz sine wave

Low temperature remote plasma sputtering of indium tin oxide for flexible display applications

Tin doped indium oxide (ITO) has been directly deposited onto a variety of flexible materials by a reactive sputtering technique that utilises a remotely generated, high density plasma. This technique, known as high target utilisation sputtering (HiTUS), allows for the high rate deposition of good quality ITO films onto polymeric materials with no substrate heating or post deposition annealing. Coatings with a resistivity of 3.8 ×10−4 Ωcm and an average visible transmission of greater than 90% have been deposited onto PEN and PET substrate materials at a deposition rate of 70 nm/min. The electrical and optical properties are retained when the coatings are flexed through a 1.0 cm bend radius, making them of interest for flexible display applications

The management of tetanus in adults in an intensive care unit in Southern Vietnam

Background: Tetanus remains common in many low- and middle-income countries (LMICs) yet the evidence base guiding management of this disease is extremely limited, particularly with respect to contemporary management options. Sharing knowledge about practice may facilitate improvement in outcomes elsewhere. Methods: We describe clinical interventions and outcomes of 180 adult patients ≥16 years-old with tetanus enrolled in prospective observational studies at a specialist infectious diseases hospital in Southern Vietnam. Patients were treated according to a holistic management protocol encompassing wound-care, antitoxin, antibiotics, symptom control, airway management, nutrition and de-escalation criteria. Results: Mortality rate in our cohort was 2.8%, with 90 (50%) patients requiring mechanical ventilation for a median 16 [IQR 12-24] days. Median [IQR] duration of ICU stay was 15 [8-23] days. Autonomic nervous system dysfunction occurred in 45 (25%) patients. Hospital acquired infections occurred in 77 (43%) of patients. Conclusion: We report favourable outcomes for patients with tetanus in a single centre LMIC ICU, treated according to a holistic protocol. Nevertheless, many patients required prolonged intensive care support and hospital acquired infections were common

Synthesizing electronic health records for predictive models in low-middle-income countries (LMICs)

The spread of machine learning models, coupled with by the growing adoption of electronic health records (EHRs), has opened the door for developing clinical decision support systems. However, despite the great promise of machine learning for healthcare in low-middle-income countries (LMICs), many data-specific limitations, such as the small size and irregular sampling, hinder the progress in such applications. Recently, deep generative models have been proposed to generate realistic-looking synthetic data, including EHRs, by learning the underlying data distribution without compromising patient privacy. In this study, we first use a deep generative model to generate synthetic data based on a small dataset (364 patients) from a LMIC setting. Next, we use synthetic data to build models that predict the onset of hospital-acquired infections based on minimal information collected at patient ICU admission. The performance of the diagnostic model trained on the synthetic data outperformed models trained on the original and oversampled data using techniques such as SMOTE. We also experiment with varying the size of the synthetic data and observe the impact on the performance and interpretability of the models. Our results show the promise of using deep generative models in enabling healthcare data owners to develop and validate models that serve their needs and applications, despite limitations in dataset size

Evaluation of the MODS Culture Technique for the Diagnosis of Tuberculous Meningitis

Tuberculous meningitis (TBM) is a devastating condition. The rapid instigation of appropraite chemotherapy is vital to reduce morbidity and mortality. However rapid diagnosis remains elusive; smear microscopy has extremely low sensitivity on cerebrospinal fluid (CSF) in most laboratories and PCR requires expertise with advanced infrastructure and has sensitivity of only around 60% under optimal conditions. Neither technique allows for the microbiological isolation of M. tuberculosis and subsequent drug susceptibility testing. We evaluated the recently developed microscopic observation drug susceptibility (MODS) assay format for speed and accuracy in diagnosing TBM.Two hundred and thirty consecutive CSF samples collected from 156 patients clinically suspected of TBM on presentation at a tertiary referal hospital in Vietnam were enrolled into the study over a five month period and tested by Ziehl-Neelsen (ZN) smear, MODS, Mycobacterial growth Indicator tube (MGIT) and Lowenstein-Jensen (LJ) culture. Sixty-one samples were from patients already on TB therapy for >1day and 19 samples were excluded due to untraceable patient records. One hundred and fifty samples from 137 newly presenting patients remained. Forty-two percent (n = 57/137) of patients were deemed to have TBM by clinical diagnostic and microbiological criteria (excluding MODS). Sensitivity by patient against clinical gold standard for ZN smear, MODS MGIT and LJ were 52.6%, 64.9%, 70.2% and 70.2%, respectively. Specificity of all microbiological techniques was 100%. Positive and negative predictive values for MODS were 100% and 78.7%, respectively for HIV infected patients and 100% and 82.1% for HIV negative patients. The median time to positive was 6 days (interquartile range 5-7), significantly faster than MGIT at 15.5 days (interquartile range 12-24), and LJ at 24 days (interquartile range 18-35 days) (P<0.01).We have shown MODS to be a sensitive, rapid technique for the diagnosis of TBM with high sensitivity, ease of performance and low cost (0.53 USD/sample)

Effect of dynamic stall on the aerodynamics of vertical-axis wind turbines

Accurate simulations of the aerodynamic performance of vertical-axis wind turbines pose a significant challenge for computational fluid dynamics methods. The aerodynamic interaction between the blades of the rotor and the wake that is produced by the blades requires a high-fidelity representation of the convection of vorticity within the wake. In addition, the cyclic motion of the blades induces large variations in the angle of attack on the blades that can manifest as dynamic stall. The present paper describes the application of a numerical model that is based on the vorticity transport formulation of the Navier–Stokes equations, to the prediction of the aerodynamics of a verticalaxis wind turbine that consists of three curved rotor blades that are twisted helically around the rotational axis of the rotor. The predicted variation of the power coefficient with tip speed ratio compares very favorably with experimental measurements. It is demonstrated that helical blade twist reduces the oscillation of the power coefficient that is an inherent feature of turbines with non-twisted blade configurations

Improving Access to Psychological Therapies (IAPT) services outcomes for people with learning disabilities: National data 2012-2013 to 2019-2020

Primary care interventions for people with common mental health problems in England are primarily delivered through Improving Access to Psychological Therapies (IAPT) services. One of the priorities for IAPT services is to reduce inequalities in access and outcomes for potentially disadvantaged populations. This paper uses national data from the years 2012-2013 to 2019-2020 to present a comparison of service process and therapy outcomes for people with learning disabilities. Annual data for people with learning disabilities, people with other recorded disabilities and people with no recorded disabilities were extracted from a publicly available, national data source. Data are presented graphically with relative risk calculated for each variable and year, and show a broadly similar pattern of waiting time access for people with learning disabilities and people with no disabilities, and a broadly similar proportion of people with learning disabilities and people with no disabilities who finish treatment. However, people with learning disabilities have poorer clinical outcomes than people with no disabilities. We discuss adaptations to IAPT processes and therapy provision that may further support people with learning disabilities' access to IAPT services. Key learning aims (1) To describe how IAPT services record disabilities, and in particular record whether a person identifies themselves as having a learning disability.1 (2) To explore the differences in processes and therapy outcomes for people with learning disabilities compared with people with no disabilities and people with other disabilities. (3) To understand adaptations to IAPT processes and therapies that may make IAPT services more accessible to people with learning disabilities