A comparison of Landsat 8, RapidEye and Pleiades products for improving empirical predictions of satellite-derived bathymetry

Satellite derived bathymetry (SDB) enables rapid mapping of large coastal areas through measurement of optical penetration of the water column. The resolution of bathymetric mapping and achievable horizontal and vertical accuracies vary but generally, all SDB outputs are constrained by sensor type, water quality and other environmental conditions. Efforts to improve accuracy include physics-based methods (similar to radiative transfer models e.g. for atmospheric/vegetation studies) or detailed in-situ sampling of the seabed and water column, but the spatial component of SDB measurements is often under-utilised in SDB workflows despite promising results suggesting potential to improve accuracy significantly. In this study, a selection of satellite datasets (Landsat 8, RapidEye and Pleiades) at different spatial and spectral resolutions were tested using a log ratio transform to derive bathymetry in an Atlantic coastal embayment. A series of non-spatial and spatial linear analyses were then conducted and their influence on SDB prediction accuracy was assessed in addition to the significance of each model’s parameters. Landsat 8 (30m pixel size) performed relatively weak with the non-spatial model, but showed the best results with the spatial model. However, the highest spatial resolution imagery used – Pleiades (2m pixel size) showed good results across both non-spatial and spatial models which suggests a suitability for SDB prediction at a higher spatial resolution than the others. In all cases, the spatial models were able to constrain the prediction differences at increased water depths

Stable isotope profile (C, N, O, S) of Irish raw milk: Baseline data for authentication

Grass-based milk production is a major contributor to Irish agricultural output. The study characterized the Irish milk pool using stable isotope ratio analysis of carbon, nitrogen, oxygen and sulphur. Authentic raw milk samples were collected from 50 farms on five occasions over 13 months. Mean values of −27.11, 6.79, −3.27 and 6.16‰ were obtained for δ13C, δ15N, δ18O and δ34S, respectively. δ13C values reflected a high level of grass input and values increased with increasing cereal concentrate feed input (P < 0.001). δ18O values were most negative in spring. There was a significant interaction between feed and season for δ13C and δ15N values (P < 0.05), with the impact of concentrate feeding most evident in spring. δ34S values were lowest at the highest level of concentrate input (P < 0.05). The isotopic values reported here describe the Irish milk pool and may offer the potential to discriminate Irish milk and dairy products from similar commodities from other countries

Impurity-Ion pair induced high-temperature ferromagnetism in Co-doped ZnO

Magnetic 3d-ions doped into wide-gap oxides show signatures of room temperature ferromagnetism, although their concentration is two orders of magnitude smaller than that in conventional magnets. The prototype of these exceptional materials is Co-doped ZnO, for which an explanation of the room temperature ferromagnetism is still elusive. Here we demonstrate that magnetism originates from Co2+ oxygen-vacancy pairs with a partially filled level close to the ZnO conduction band minimum. The magnetic interaction between these pairs is sufficiently long-ranged to cause percolation at moderate concentrations. However, magnetically correlated clusters large enough to show hysteresis at room temperature already form below the percolation threshold and explain the current experimental findings. Our work demonstrates that the magnetism in ZnO:Co is entirely governed by intrinsic defects and a phase diagram is presented. This suggests a recipe for tailoring the magnetic properties of spintronics materials by controlling their intrinsic defects

Parental cultural models and resources for understanding mathematical achievement in culturally diverse school settings

This paper proposes that the theoretical concept of cultural models can offer useful insights into parental involvement in their child’s mathematical achievement and the resources they use to go about gaining information in culturally diverse learning settings. This examination takes place within a cultural-developmental framework and draws on the notion of cultural models to explicate parental understandings of their child’s mathematics achievement and what resources are used to make sense of this. Three parental resources are scrutinized: (a) the teacher, (b) examination test results, and (c) constructions of child development. The interviews with 22 parents revealed some ambiguity around the interpretation of these resources by the parent, which was often the result of incongruent cultural models held between the home and the school. The resources mentioned are often perceived as being unambiguous but show themselves instead to be highly interpretive because of the diversity of cultural models in existence in culturally diverse settings. Parents who are in minority or marginalized positions tend to have difficulties in interpreting cultural models held by school, thereby disempowering them to be parentally involved in the way the school would like

Tutor and teacher timescapes : lessons from a home-school partnership

A partnership project was developed in which parents volunteered to support teachersin training years 1-3 children in computer skills at a primary school in a small, lowsocio-economic community. This article identifies the ways teachers and the &lsquo;tutors&rsquo;(as the volunteers were called) understood the value of the project. &lsquo;Being a teacher&rsquo;and &lsquo;being a volunteer&rsquo; were structured by different forms of social engagement,which in turn influenced the ways individuals were able to work with each other incollaborative processes. We argue that the discursive practices encoded in homeschool-community partnership rhetoric represent ruling-class ways of organising andnetworking that may be incompatible with those of people from low socio-economicbackgrounds. When such volunteers work in schools their attendance may be sporadicand short-term whereas teachers would like &lsquo;reliable&rsquo; ongoing commitment. Thismismatch wrought of teachers&rsquo; and volunteers&rsquo; differing everyday realities needs to beunderstood before useful models for partnerships in disadvantaged communities maybe realised.<br /

A Mechanism‐based Pharmacokinetic Model of Remdesivir Leveraging Interspecies Scaling to Simulate COVID‐19 Treatment in Humans

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak initiated the global COVID-19 pandemic resulting in 42.9 million confirmed infections and >1.1 million deaths worldwide as of October 26, 2020. Remdesivir is a broad-spectrum nucleotide prodrug shown to be effective against enzootic coronaviruses. The pharmacokinetics (PK) of remdesivir in plasma have recently been described. However, the distribution of its active metabolite nucleoside triphosphate (NTP) to the site of pulmonary infection is unknown in humans. Our objective was to use existing in vivo mouse PK data for remdesivir and its metabolites to develop a mechanism-based model to allometrically scale and simulate the human PK of remdesivir in plasma and NTP in lung homogenate. Remdesivir and GS-441524 concentrations in plasma and total phosphorylated nucleoside concentrations in lung homogenate from Ces1c-/- mice administered 25 or 50 mg/kg of remdesivir subcutaneously were simultaneously fit to estimate PK parameters. The mouse PK model was allometrically scaled to predict human PK parameters to simulate the clinically recommended 200 mg loading dose followed by 100 mg daily maintenance doses administered as 30-minute intravenous infusions. Simulations of unbound remdesivir concentrations in human plasma were below 2.48 μM, the 90% maximal inhibitory concentration for SARS-CoV-2 inhibition in vitro. Simulations of NTP in lung were below high efficacy in vitro thresholds. We have identified a need for alternative dosing strategies to achieve more efficacious concentrations of NTP in human lung, perhaps by reformulating remdesivir for direct pulmonary delivery

Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients

Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill

"Dreaming in colour’: disabled higher education students’ perspectives on improving design practices that would enable them to benefit from their use of technologies"

The focus of this paper is the design of technology products and services for disabled students in higher education. It analyses the perspectives of disabled students studying in the US, the UK, Germany, Israel and Canada, regarding their experiences of using technologies to support their learning. The students shared how the functionality of the technologies supported them to study and enabled them to achieve their academic potential. Despite these positive outcomes, the students also reported difficulties associated with: i) the design of the technologies, ii) a lack of technology know-how and iii) a lack of social capital. When identifying potential solutions to these difficulties the disabled students imagined both preferable and possible futures where faculty, higher education institutions, researchers and technology companies are challenged to push the boundaries of their current design practices

A Systems-Based Analysis of Mono- and Combination Therapy for Carbapenem-Resistant Klebsiella pneumoniae Bloodstream Infections

Antimicrobial resistance is a global threat. As “proof-of-concept, ” we employed a system-based approach to identify patient, bacterial, and drug variables contributing to mortality in patients with carbapenem-resistant Klebsiella pneumoniae (CRKp) bloodstream infections exposed to colistin (COL) and ceftazidime-avibactam (CAZ/AVI) as mono- or combination therapies. Patients (n = 49) and CRKp isolates (n = 22) were part of the Consortium on Resistance Against Carbapenems in Klebsiella and other Enterobacteriaceae (CRACKLE-1), a multicenter, observational, prospective study of patients with carbapenem-resistant Enterobacterales (CRE) conducted between 2011 and 2016. Pharmacodynamic activity of mono- and combination drug concentrations was evaluated over 24 h using in vitro static time-kill assays. Bacterial growth and killing dynamics were estimated with a mechanism-based model. Random Forest was used to rank variables important for predicting