Perceived biodiversity, sound, naturalness and safety enhance the restorative quality and wellbeing benefits of green and blue space in a neotropical city

Urban land cover expansion and human population growth are accelerating worldwide. This is resulting in the loss and degradation of green and blue spaces (e.g. parks, waterways, lakes) in cities, which provide resources to sustain biodiversity and improve human wellbeing. The specific characteristics of these spaces (e.g. sounds, species, safety) that enhance or detract from wellbeing are underexplored, yet this knowledge is needed to inform urban planning, management and policies that will ultimately benefit both people and biodiversity. Research of this kind is rarely conducted in the Global South, where rapid urbanisation threatens biodiversity-rich ecosystems of worldwide significance. Here, we examine how perceptions of green, waterway, and dense urban spaces relate to wellbeing in Georgetown, Guyana. Specifically, we use mediation models to test how perceptions of sound, bird species richness, naturalness, and safety concerns contribute to sites being perceived as restorative which, subsequently, influences wellbeing. We assess the accuracy of these site perceptions with objective measures of sound (using a bioacoustic sound index), bird species richness, and percent coverage of vegetation, water, and impervious surfaces. Results showed that if sites were perceived as species rich, containing natural sounds like birdsong, natural rather than artificial, and safe, they were perceived as more restorative, resulting in improved wellbeing. In general, people’s perceptions were consistent with objective measures. Green, compared with waterway and dense urban sites, contained more biophonic sounds, higher species richness, greater vegetation and water coverage. Although waterways were biodiverse, they were dominated by anthrophonic sounds, so were perceived as artificial and non-restorative. We shed light on how city planners might augment specific characteristics to improve the wellbeing of urban dwellers, with implications for biodiversity conservation. Our findings provide a scientific evidence base for urban design and management plans that could deliver multiple co-benefits, particularly in biodiversity-rich cities in neotropical regions

Roadmap on inorganic perovskites for energy applications

Authors thank EPSRC (EP/P007821/1) and Low Emissions Resources Global for support.Inorganic perovskites exhibit many important physical properties such as ferroelectricity, magnetoresistance and superconductivity as well their importance as Energy Materials. Many of the most important energy materials are inorganic perovskites and find application in batteries, fuel cells, photocatalysts, catalysis, thermoelectrics and solar thermal. In all these applications, perovskite oxides, or their derivatives offer highly competitive performance, often state of the art and so tend to dominate research into energy material. In the following sections, we review these functionalities in turn seeking to facilitate the interchange of ideas between domains. The potential for improvement is explored and we highlight the importance of both detailed modelling and in situ and operando studies in taking these materials forward.Publisher PDFPeer reviewe

Scalable and accurate deep learning for electronic health records

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that discards the vast majority of information in each patient's record. We propose a representation of patients' entire, raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) format. We demonstrate that deep learning methods using this representation are capable of accurately predicting multiple medical events from multiple centers without site-specific data harmonization. We validated our approach using de-identified EHR data from two U.S. academic medical centers with 216,221 adult patients hospitalized for at least 24 hours. In the sequential format we propose, this volume of EHR data unrolled into a total of 46,864,534,945 data points, including clinical notes. Deep learning models achieved high accuracy for tasks such as predicting in-hospital mortality (AUROC across sites 0.93-0.94), 30-day unplanned readmission (AUROC 0.75-0.76), prolonged length of stay (AUROC 0.85-0.86), and all of a patient's final discharge diagnoses (frequency-weighted AUROC 0.90). These models outperformed state-of-the-art traditional predictive models in all cases. We also present a case-study of a neural-network attribution system, which illustrates how clinicians can gain some transparency into the predictions. We believe that this approach can be used to create accurate and scalable predictions for a variety of clinical scenarios, complete with explanations that directly highlight evidence in the patient's chart.Comment: Published version from https://www.nature.com/articles/s41746-018-0029-

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

2021 roadmap for sodium-ion batteries

Abstract: Increasing concerns regarding the sustainability of lithium sources, due to their limited availability and consequent expected price increase, have raised awareness of the importance of developing alternative energy-storage candidates that can sustain the ever-growing energy demand. Furthermore, limitations on the availability of the transition metals used in the manufacturing of cathode materials, together with questionable mining practices, are driving development towards more sustainable elements. Given the uniformly high abundance and cost-effectiveness of sodium, as well as its very suitable redox potential (close to that of lithium), sodium-ion battery technology offers tremendous potential to be a counterpart to lithium-ion batteries (LIBs) in different application scenarios, such as stationary energy storage and low-cost vehicles. This potential is reflected by the major investments that are being made by industry in a wide variety of markets and in diverse material combinations. Despite the associated advantages of being a drop-in replacement for LIBs, there are remarkable differences in the physicochemical properties between sodium and lithium that give rise to different behaviours, for example, different coordination preferences in compounds, desolvation energies, or solubility of the solid–electrolyte interphase inorganic salt components. This demands a more detailed study of the underlying physical and chemical processes occurring in sodium-ion batteries and allows great scope for groundbreaking advances in the field, from lab-scale to scale-up. This roadmap provides an extensive review by experts in academia and industry of the current state of the art in 2021 and the different research directions and strategies currently underway to improve the performance of sodium-ion batteries. The aim is to provide an opinion with respect to the current challenges and opportunities, from the fundamental properties to the practical applications of this technology

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Formulation and delivery strategies of ibuprofen: challenges and opportunities

Ibuprofen, a non-steroidal anti-inflammatory drug (NSAID) is mostly administered orally and topically to relieve acute pain and fever. Due to its mode of action this drug may provide useful in the treatment regimens of other, more chronic conditions, like cystic fibrosis. This drug is poorly soluble in aqueous media and thus the rate of dissolution from the currently available solid dosage forms are limited that leads to poor bioavailability at high dose after oral administration. The poor solubility is a problem for developing injectable solution dosage forms. Because of its poor skin permeability, it is difficult to obtain an effective therapeutic concentration from topical preparations. This review aims to give a brief insight into the status of ibuprofen dosage forms and their limitations, particle/crystallization technologies for improving formulation strategies as well as suggesting its incorporation into the pulmonary drug delivery systems for achieving better therapeutic action at low dose

Large area survey grain size and texture optimization for thin film CdTe solar sells using xenon-plasma focused ion beam (PFIB)

Microstructural analysis of high efficiency thin film CdTe solar cells has been obtained over large areas. Analysis regions are device cross-sections approximately 0.325 mm in length. The samples have been prepared using a xenon-plasma focused ion beam (Xe-PFIB). The detailed images of the microstructure were obtained using backscattered electron imaging and electron backscatter diffraction (EBSD). As deposited devices and those with a low level of cadmium chloride treatment both show strong (111) growth texture. A high density of twins is seen in the columnar grains. Three As doped FTO/CdZnS/CdTe with varying process conditions we devices with 13.1 %, 16.3% and 17% conversion efficiency were investigated. Lowest efficiency device was CdCl2 treated at 420°C for 10 minutes while the 16.3 and 17% devices were both treated at 440°C for 10 minutes. The large area analysis revealed a partial recrystallisation state in the 16.3% efficient device which was induced by an incomplete chloride activation process. The analysis confirms that the efficiency of the devices tends to correlate with grain size. It also showed that a strong correlation exists between device efficiency and the randomization of the texture away from the (111) grain orientation. EBSD can be used to survey large areas and to mark out features for more detailed analysis using transmission electron microscopy (TEM). As an example, we show how using an EBSD scanned cross-sectional area can identify a partially recrystallized region which is then extracted and analyzed in detail using TEM

General Release: Young British Artists Group Exhibition

Commissioner: Andrea Rose (British Council