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AimsTo assess the level of transesophageal echocardiography (TOE) knowledge and skills of young cardiologists.Methods and resultsA European Association of Cardiovascular Imaging (EACVI) online study using the first fully virtual simulation-based software was conducted in two periods (9–12 December 2021 and 10–13 April 2022). All young cardiologists eligible to participate (ConclusionOnline evaluation of young cardiologists around the world showed a relatively low level of TOE skills and knowledge. Prior participation to a TOE simulation-based training session, a higher number of TOE exams performed per week, and the EACVI certification for TOE were independently associated with a higher global score.

The tutorial provides a practical introduction to Transkribus, a comprehensive platform for the digitisation, AI-powered text recognition, transcription and searching of historical documents. The participants will learn how to run the layout analysis (also for tables and complex layouts) and train and apply Handwritten Text Recognition AI-models to automatically generate machine-readable transcriptions of images of text. In the end, they will have a general understanding of the potential of Handwritten Text Recognition to open new research questions and how Transkribus can be used to collaborate, involve volunteers and teach in DH and History classes.

In an earlier work, we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of a quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical simulation of a calorimeter response with a reduced problem size. This paper explores the dual- PQC GAN for a more practical usage by testing its performance in the presence of different types of quantum noise, which are the major obstacles to overcome for successful deployment using near-term quantum devices. The results propose the possibility of running the model on current real hardware, but improvements are still required in some areas., Comment: 6 pages, 5 figures, Proceedings of the 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)

N, N-Dimethylformamide (DMF) can cause liver damage in occupationally exposed workers, but the molecular mechanism of DMF-induced liver damage has not been fully elucidated. Researches have proved that lncRNA plays a major function in chemical-induced liver toxicity and can be used as a biomarker and therapeutic target for liver injury. In order to verify that lncRNA also participates in DMF-induced liver damage, we treated HL-7702 cells with 75 or 150 mM DMF, and obtained lncRNA expression profiles through high-throughput sequencing. Among the differentially expressed lncRNAs, lncRNA SNHG12 was proved to be significantly downregulated in DMF-treated HL-7702 cells and participate in DMF-mediated apoptosis, even under long-term low-dose DMF exposure (5–10 mM, 8 weeks). In addition, according to bioinformatics analysis, miR-218-5p is expected to be a potential target of SNHG12, which was verified by the dual luciferase reporter assay in HEK293FT cells. MiR-218-5p mimic can induce apoptosis in HL-7702 cells. Among the predicted targets of miR-218-5p, protein kinase C epsilon (PRKCE) was reported to be involved in apoptosis, and was indeed downregulated by miR-218-5p mimic in our study. Further experiments showed that changes of the expression of SNHG12 can affect the expression of PRKCE. In the epidemiological study of occupational population, we also found that SNHG12 was downregulated in the serum exosomes of workers exposed to DMF. These results indicated that SNHG12 can mediate DMF-induced apoptosis of HL-7702 cells through miR-218-5p/PRKCE pathway.

Objectives: Survey studies are a commonly used method for data collection in surgical education research. Nevertheless, studies investigating survey design and response rates in surgical education research are lacking. The aim of this study was to gain an insight into survey response rates among surgical residents and medical students, and provide an initial reporting guideline for future survey studies in this field. Design: PubMed (MEDLINE) was systematically searched for survey studies in surgical education from January 2007 until February 2020, according to the PRISMA statements checklist. Study selection was conducted by 2 authors, independently. Surveys directed at surgical residents and/or medical students were included if data on response rates was available. Studies reporting solely from nonsurgical fields of medicine, paramedicine, or nursing were excluded. Subgroup analyses were performed, comparing response rates for varying modes of survey, per country, and for the 10 journals with the most identified surveys. Results: From the 5,693 records screened for a larger surgical survey database, a total of 312 surveys were included; 173 studies focused on surgical residents and 139 on medical students. The mean (SD) response rate was 55.7% (24.7%) for surgical residents and 69.0% (20.8%) for medical students. The number of published surveys increased yearly, mostly driven by an increase in surgical resident surveys. Although most surveys were Web-based (n = 166, 53.2%), this survey mode resulted in the lowest response rates (mean 52.6%). The highest response rates, with a mean of 79.8% (13.1%), were seen in in-person surveys (n = 89, 28.5%). Wide variations in response rates were seen between different countries and journals. Conclusions: Web-based surveys are gaining popularity for medical research in general and for surgical education specifically; however, this mode results in lower response rates than those of in-person surveys. The response rate of in-person surveys is especially high when focusing on medical students. To improve reporting of survey studies, we present the first step towards a reporting guideline.

Objectives: Survey studies are a commonly used method for data collection in surgical education research. Nevertheless, studies investigating survey design and response rates in surgical education research are lacking. The aim of this study was to gain an insight into survey response rates among surgical residents and medical students, and provide an initial reporting guideline for future survey studies in this field.Design: PubMed (MEDLINE) was systematically searched for survey studies in surgical education from January 2007 until February 2020, according to the PRISMA statements checklist. Study selection was conducted by 2 authors, independently. Surveys directed at surgical residents and/or medical students were included if data on response rates was available. Studies reporting solely from nonsurgical fields of medicine, paramedicine, or nursing were excluded. Subgroup analyses were performed, comparing response rates for varying modes of survey, per country, and for the 10 journals with the most identified surveys.Results: From the 5,693 records screened for a larger surgical survey database, a total of 312 surveys were included; 173 studies focused on surgical residents and 139 on medical students. The mean (SD) response rate was 55.7% (24.7%) for surgical residents and 69.0% (20.8%) for medical students. The number of published surveys increased yearly, mostly driven by an increase in surgical resident surveys. Although most surveys were Web-based (n = 166, 53.2%), this survey mode resulted in the lowest response rates (mean 52.6%). The highest response rates, with a mean of 79.8% (13.1%), were seen in in-person surveys (n = 89, 28.5%). Wide variations in response rates were seen between different countries and journals.Conclusions: Web-based surveys are gaining popularity for medical research in general and for surgical education specifically; however, this mode results in lower response rates than those of in-person surveys. The response rate of in-person surveys is especially high when focusing on medical students. To improve reporting of survey studies, we present the first step towards a reporting guideline.

The cytotoxicity and DNA damage of titanium dioxide and zinc oxide nanoparticles (TiO2 and ZnO NPs) have been studied in a human lung carcinoma cell line (A549) after 24 h exposure. TiO2 and ZnO NPs had mean diameters of 12.9 ± 2.8 and 24.1 ± 8.0 nm, respectively. ZnO NPs reduced cell viability from 250 μg/mL, increasing reactive oxygen species (ROS) and decreased GSH/GSSG ratio. The comet assay detected DNA damage from 50 μg/mL. TiO2 NPs induced cytotoxicity and DNA damage from 50 to 100 μg/mL, respectively, along with a decrease of the GSH/GSSG ratio. Both particles were found inside the cells, within membrane-bound vesicles. The internalization mechanism is promoted partially by caveolae-mediated endocytosis and, in the case of TiO2 NPs, also by macropinocytosis.

Objectives To estimate the frequency, clinical approaches and risk factors of hypoadrenocorticism in dogs under UK primary veterinary care. Materials and methods Dogs diagnosed with hypoadrenocorticism were identified from the UK VetCompass™ programme by searching anonymised electronic patient records. Pre-existing and newly diagnosed cases of disease during 2016 were included. Cases were further sub-categorised as having a laboratory-confirmed or presumed diagnosis of hypoadrenocorticism based on the information recorded in the electronic patient records. Descriptive data were manually extracted. Multivariable logistic regression methods were used to identify demographic risk factors. Results There were 177 hypoadrenocorticism cases identified from 905,543 dogs in 2016; 72 laboratory-confirmed and 105 presumed. The 1-year period prevalence for hypoadrenocorticism in all dogs was 0.06% (95% confidence interval: 0.05-0.07%). The most common presenting clinical signs in laboratory-confirmed dogs were lethargy (51/66, 77.3%), anorexia (48/66, 66.7%) and vomiting (48/66, 66.7%). Hyperkalaemia was reported in 47 of 53 (88.7%), hyponatraemia in 46 of 53 (86.8%). Median sodium: potassium ratio was 19.00 (interquartile range: 16.20-20.60). Breed, age, neuter status and insurance status were associated with a laboratory-confirmed diagnosis of hypoadrenocorticism. No sex association with hypoadrenocorticism was observed in the multivariable model. The standard poodle had 51.38 times the odds (95% CI: 14.49-182.18) of hypoadrenocorticism compared with crossbreeds. The labradoodle and West Highland white terrier also had increased odds. Clinical significance This is the first epidemiological study to report on hypoadrenocorticism in dogs within the UK primary-care population. These results provide benchmark data of current veterinary activity relating to hypoadrenocorticism in primary-care practices.

The use of Ring Imaging Cherenkov detectors (RICH) offers a powerful technique for identifying the particle species in particle physics. These detectors produce 2D images formed by rings of individual photons superimposed on a background of photon rings from other particles. The RICH particle identification (PID) is essential to the LHCb experiment at CERN. While the current PID algorithm has performed well during LHC data-taking periods between 2010 to 2018, its complexity poses a challenge for LHCb computing infrastructure upgrades towards multi-core architectures. The high particle multiplicity environment of future LHC runs strongly motivates shifting towards high-throughput computing for the online event reconstruction. In this contribution, we introduce a convolutional neural network (CNN) approach to particle identification in LHCb RICH. The CNN takes binary input images from the two RICH detectors to classify particle species. The input images are polar-transformed sub-sections of the RICH photon-detection planes. The model is hyperparameter-optimised and trained on classification accuracy with simulated collision data for the upcoming LHC operation starting in 2022. The PID performance of the CNN is comparable to the conventional algorithm, and its simplicity renders it suitable for fast online reconstruction through parallel processing. We show that under conditions of reduced combinatorial background, as expected from the introduction of timing resolution to the RICH detectors in future upgrades, the network achieves a particle identification performance close to 100 %, with simultaneous misclassification of the most prevalent particle species approaching 0 %.

BackgroundDepression is associated with lower educational attainment, but there has been little investigation of long-term educational trajectories in large cohorts with diagnosed depression.AimsTo describe the educational attainment trajectories of children with a depression diagnosis in secondary care, and to investigate whether these trajectories vary by sociodemographic characteristics.MethodWe identified new referrals to South London and Maudsley's NHS Foundation Trust between 2007 and 2013 who received a depression diagnosis at under 18 years old. Linking their health records to the National Pupil Database, we standardised their performance on three assessments (typically undertaken at ages 6–7 years (school Year 2), 10–11 (Year 6) and 15–16 (Year 11)) relative to the local reference population in each academic year. We used mixed models for repeated measures to estimate attainment trajectories.ResultsIn our sample of 1492 children, the median age at depression diagnosis was 15 years (interquartile range = 14–16). Their attainment showed a decline between school Years 6 and 11. Attainment was consistently lower among males and those eligible for free school meals. Black ethnic groups also showed lower attainment than White ethnic groups between Years 2 and 6, but showed a less pronounced drop in attainment at Year 11.ConclusionsThose who receive a depression diagnosis during their school career show a drop in attainment in Year 11. Although this pattern was seen among multiple sociodemographic groups, gender, ethnicity and socioeconomic status predict more vulnerable subgroups within this clinical population who might benefit from additional educational support or more intensive treatment.

Active control of chirality in the terahertz frequency range is of great importance in many scientific areas, which include research into fundamental optical phenomena, investigation of novel materials, spectroscopy, imaging, wireless communications and chemistry. The lack of efficient, integrated and fast-reconfigurable polarization modulators has hindered, so far, the full exploitation of applications in all the aforementioned fields. Metamaterials are artificial resonant elements possessing unique remarkable properties such as high efficiency and miniaturization capability. The interplay of metallic metamaterial arrays with electrostatically tunable monolayer graphene has been demonstrated to be a valid approach for the realization of a novel class of THz devices. In this work, the realization of active chiral graphene/metamaterial modulator is presented. The versatility of this experimental approach allowed the device integration with broadband sources such as terahertz time domain spectrometers as well as with quantum cascade lasers. A continuous rotation of the polarization plane > 30° has been reported with a reconfiguration speed > 5 MHz. These results pave the way to the integration of fast terahertz polarization modulators in all the applications where these devices are in great demand.

We have performed numerical simulations of the electromagnetic hoop stress, ���� , in a REBaCuO disk bulk reinforced by a metal ring during pulsed-field magnetization (PFM) using a solenoid coil, in which the superconducting characteristics of the bulk material were assumed to have realistic J c-B-T ones. The compressive and tensile ���� stresses were applied in the bulk during the ascending and descending stages of PFM, respectively. The time and position dependences of the mechanical stresses were estimated. The possibility of mechanical fracture due to these hoop stresses and the effect of the metal ring reinforcement were discussed., Japan Society for the Promotion of Science (JSPS) KAKENHI Grant No. 15K04646

Objective Patients with cancer are at high risk of depression. However, the risk of major depressive disorder (MDD) after cancer diagnosis has not been studied in a population setting in Japan. This cohort study used a Japanese medical claims database to examine time to MDD in cancer patients and the risk of MDD (hazard ratio; HR) compared with matched cancer‐free controls. Methods Primary endpoint was time to MDD (starting 6 months before cancer diagnosis) in adult (18–74 years) cancer patients; secondary endpoint was time to MDD (6 months before to 12 months after cancer diagnosis) in a matched cohort of cancer patients and cancer‐free controls. Multivariate analyses were performed to determine HRs for all cancers and for each cancer site. Results Of 35 008 cancer patients (mean age, 53.3 years), 2201 (6.3%) were diagnosed with MDD within 66 months. Matched cancer patients (n = 30 372) had an elevated risk of MDD compared with cancer‐free controls (n = 303 720; HR [95% confidence interval] 2.96 [2.77–3.16]). MDD risk was highest in patients with multiple cancers, pancreatic cancer, and brain cancer. Compared with middle‐aged patients, risk was higher in patients

BackgroundClozapine, an antipsychotic with unique efficacy in treatment-resistant psychosis, is associated with increased susceptibility to infection, including pneumonia.AimsTo investigate associations between clozapine treatment and increased risk of COVID-19 infection in patients with schizophrenia-spectrum disorders who are receiving antipsychotic medications in a geographically defined population in London, UK.MethodUsing information from South London and Maudsley NHS Foundation Trust (SLAM) clinical records, via the Clinical Record Interactive Search system, we identified 6309 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders and were taking antipsychotics at the time of the COVID-19 pandemic onset in the UK. People who were on clozapine treatment were compared with those on any other antipsychotic treatment for risk of contracting COVID-19 between 1 March and 18 May 2020. We tested associations between clozapine treatment and COVID-19 infection, adjusting for gender, age, ethnicity, body mass index (BMI), smoking status and SLAM service use.ResultsOf 6309 participants, 102 tested positive for COVID-19. Individuals who were on clozapine had increased risk of COVID-19 infection compared with those who were on other antipsychotic medication (unadjusted hazard ratio HR = 2.62, 95% CI 1.73–3.96), which was attenuated after adjusting for potential confounders, including clinical contact (adjusted HR = 1.76, 95% CI 1.14–2.72).ConclusionsThese findings provide support for the hypothesis that clozapine treatment is associated with an increased risk of COVID-19 infection. Further research will be needed in other samples to confirm this association. Potential clinical implications are discussed.

Improvements have been made in identifying the prevalence of risk factors/indicators for violent extremism. A consistent problem is the lack of base rates. How to develop base rates is of equal concern. This study has two aims: (i) compare two methods for developing base rates; the Unmatched Count Technique (UCT) and direct questioning, (ii) generate base rates in a general population sample and compare these to a sample of lone‐actor terrorists (n = 125). We surveyed 2108 subjects from the general population. Participants were recruited from an online access panel and randomly assigned to one of three conditions; direct survey, control, or UCT. Survey items were based on a lone‐actor terrorist codebook developed from the wider literature. Direct questioning was more suitable under our study conditions where UCT resulted in deflation effects. Comparing the base rates identified a number of significant differences: (i) lone‐actor terrorists demonstrated propensity indicators related to a cognitive susceptibility, and a crime‐ and/or violence‐supportive morality more often; the general sample demonstrated protective factors more often, (ii) lone‐actor terrorists demonstrated situational indicators related to a crime‐ and/or violence‐supportive morality more often, whereas the general sample experienced situational stressors more often, (iii) lone‐actor terrorists demonstrated indicators related to exposure to extremism more often. Results suggest there are measurable differences in the prevalence of risk factors between lone‐actor terrorists and the general population. However, no single factor “predicts” violent extremism. This bears implications for our understanding of the interrelation of risk and protective factors, and for the risk assessment of violent extremism.

Objective \ud Depression and anxiety lead to reduced treatment adherence, poorer quality of life, and increased care costs amongst cancer patients. Mindfulness‐based cognitive therapy (MBCT) is an effective treatment, but dropout reduces potential benefits. Smart‐message reminders can prevent dropout and improve effectiveness. However, smart‐messaging is untested for MBCT in cancer. This study evaluates smart‐messaging to reduce dropout and improve effectiveness in MBCT for cancer patients with depression or anxiety.MethodsFifty‐one cancer patients attending MBCT in a psycho‐oncology service were offered a smart‐messaging intervention, which reminded them of prescribed between‐session activities. Thirty patients accepted smart‐messaging and 21 did not. Assessments of depression and anxiety were taken at baseline, session‐by‐session, and one‐month follow‐up. Logistic regression and multilevel modelling compared the groups on treatment completion and clinical effectiveness. Fifteen post‐treatment patient interviews explored smart‐messaging use.ResultsThe odds of programme completion were eight times greater for patients using smart‐messaging compared with non‐users, controlling for age, gender, baseline depression, and baseline anxiety (OR = 7.79, 95% CI 1.75 to 34.58, p = .007). Smart‐messaging users also reported greater improvement in depression over the programme (B = ‐2.33, SEB = .78, p = .004) when controlling for baseline severity, change over time, age, and number of sessions attended. There was no difference between groups in anxiety improvement (B = ‐1.46, SEB = .86, p = .097). In interviews, smart‐messaging was described as a motivating reminder and source of personal connection. ConclusionsSmart‐messaging may be an easily integrated telehealth intervention to improve MBCT for cancer patients.

Trapped-flux magnets comprising stacked superconducting tape constitute a promising development to increase the power density of electrical machines, whilst at the same time keeping the complexity required in their construction in manageable levels that allow their use in applications such as aircraft propulsion. However, the conditions in which superconducting stacks operate inside an electrical motor differ quite significantly from the materials characterization experiments commonly developed to model their behaviour. This work presents the results of studying the applicability of these devices as magnetic flux source in the rotor of synchronous machines considering the influence of whole magnetic circuit. Several aspects are assessed, such as flux harmonics, magnetization, losses and demagnetization. Analytical expressions, which provide limited accuracy but allow fast calculations, are used for this purpose. The results illustrate the different trade-offs that arise during the design of a synchronous electric motor using trapped-flux magnets.

This paper presents an analysis of the power loss of the upstream turbine for yaw misalignment depending on the inflow condition. High-quality experimental field data, obtained from a lidar wind profiler, met mast, GPS based yaw sensor, turbine data, and load data is used. To reduce the spreading of the power loss during yaw misalignment, the rotor effective wind speed is estimated using load data. Furthermore, the so-called power loss coefficient currently used in most engineering models, for yaw misalignment, is assessed at various inflow conditions. As main finding, the power loss coefficient increases for stronger vertical wind shear. In addition, there is an asymmetry with respect to the direction of the yaw misalignment that is enhanced by the wind shear exponent and the wind veer. Neglecting these two effects could result in in-conservative wake-steering decisions at stable stratification

Injection of cryogenic propellants (e.g. liquid oxygen) into low-pressure environment (e.g. upper-stage rocket engine) may trigger flashing phenomenon, which severely affects the propellants’ mixing and combustion. In order to unveil the characteristics of flashing sprays, numerical models of flashing sprays were developed and validated. First, a developed model based on Adachi-correlation was employed for the flashing spray simulation. The results show good agreements with the experiments, both for the flashing spray morphology and temperature distribution. In the near-injector region, the flashing evaporation dominates the spray vaporization with the evaporation mass flow rate of about 2 orders of magnitude higher than that by the other heat transfers, whereas downstream the injector, the external heat transfer (i.e. heat conduction and convection) does. Furthermore, a new flashing spray model based on the nucleate boiling theory was proposed, which shows an improved agreement of the droplet temperature between the simulation and test data.

This study explores the effect of different technology choices on the life cycle Greenhouse Gases (GHG) emissions of wind turbines. It aims at identifying possible improvement pathways and quantifying potential benefits. First, an automated Life Cycle Assessment (LCA) model is developed and validated against other studies. The breakdown of the resulting Impact Of Energy (IOE) by life stages, components and materials is presented for a selected reference turbine. Sensitivity analyses are conducted on the different hypotheses to model the turbine life cycle. The model is then applied to analyze the potential effect of turbine size, foundation type, tower type, drivetrain technology, carbon-fiber blades and thermoplastic polymer resin for the blades. The tower type (especially wooden tower) and the thermoplastics (allowing to recover materials at the end-of-life) are identified to have the biggest potential to reduce the life cycle environmental impact of wind energy.

Future wind energy control applications require surrogate flow models that can capture processes on short time scales. Dynamic extensions of wake models might be a useful low cost solution. So far, studies have tested the proposals mostly in LES or LIDAR campaigns. At the same time, readily obtainable turbine SCADA measurements are increasingly being used directly for model input or validation. Newly available high resolution recordings allow for the study of processes on shorter time scales. The present study examines the modelling capabilities of a dynamic wake model by utilizing high frequency SCADA data. Therefore, the data is first analyzed for cross-correlation and time delays. Secondly, the dynamic wake model, initialized with SCADA measurements, is used to predict a two turbine wake interaction. An offline tuning algorithm is used to adapt the model for the shorter time scales.

In this work, a novel rotor rebalancing algorithm is tested in a simulation environment to evaluate its performance when facing both aerodynamic and inertial imbalances. The algorithm, starting from a generic measurement collected on the wind turbine fixed frame, is capable of remotely minimizing once per revolution vibrations, avoiding the need for on-site inspections, and without requiring detailed information about the machine. Indeed, once access to the pitch system is granted, this algorithm simply iteratively computes the pitch angle that needs to be applied to each individual blade in order to rebalance the rotor. Several turbulent time histories, with changing mean inflows, were simulated with the goal of testing the proposed method in realistic field conditions. Overall, the algorithm proved capable of significantly reducing the desired once per revolution vibrations in 3 to 4 iterations, irrespective of the imbalance root cause, its severity and its location. The method also appeared quite robust, showing that the found rebalanced configurations guarantee reduced vibrations no matter the machine operating point.

In the recent years machine learning techniques have attracted the attention of wind energy community to make use of the large amount of available data produced from the running wind turbines. These modern wind turbines are typically equipped with measurement systems and sensors that can provide a wealth of information about the operating conditions of the machine. Nevertheless, not all the acquired raw data can be used effectively to enhance the operation of a turbine. This work addresses the question of estimating the damage equivalent loads (DEL) of different components of a drivetrain. The estimation is based on low frequency sampled typically available SCADA measurements. Typical SCADA measurements that are used as input for the estimation model are generator rotational speed, low speed shaft torque and generator torque as well as, wind speed and direction. Several machine learning methods as random forests (RF), support vector machines (SVM), linear regression (LR), decision trees and neural networks (NN) were developed, exhibiting different behavior for each approach. The qualitative and quantitative performance of each algorithm are evaluated and compared against each other. Furthermore, analysis of importance of the input features is presented.

Significance: Peripheral pitting edema is a clinician-administered measure for grading edema. Peripheral edema is graded 0, 1 + , 2 + , 3 + , or 4 + , but subjectivity is a major limitation of this technique. A pilot clinical study for short-wave infrared (SWIR) molecular chemical imaging (MCI) effectiveness as an objective, non-contact quantitative peripheral edema measure is underway. Aim: We explore if SWIR MCI can differentiate populations with and without peripheral edema. Further, we evaluate the technology for correctly stratifying subjects with peripheral edema. Approach: SWIR MCI of shins from healthy subjects and heart failure (HF) patients was performed. Partial least squares discriminant analysis (PLS-DA) was used to discriminate the two populations. PLS regression (PLSR) was applied to assess the ability of MCI to grade edema. Results: Average spectra from edema exhibited higher water absorption than non-edema spectra. SWIR MCI differentiated healthy volunteers from a population representing all pitting edema grades with 97.1% accuracy (N = 103 shins). Additionally, SWIR MCI correctly classified shin pitting edema levels in patients with 81.6% accuracy. Conclusions: Our study successfully achieved the two primary endpoints. Application of SWIR MCI to monitor patients while actively receiving HF treatment is necessary to validate SWIR MCI as an HF monitoring technology.

Significance: Early detection of oral cancer is vital for high-risk patients, and machine learning-based automatic classification is ideal for disease screening. However, current datasets collected from high-risk populations are unbalanced and often have detrimental effects on the performance of classification. Aim: To reduce the class bias caused by data imbalance. Approach: We collected 3851 polarized white light cheek mucosa images using our customized oral cancer screening device. We use weight balancing, data augmentation, undersampling, focal loss, and ensemble methods to improve the neural network performance of oral cancer image classification with the imbalanced multi-class datasets captured from high-risk populations during oral cancer screening in low-resource settings. Results: By applying both data-level and algorithm-level approaches to the deep learning training process, the performance of the minority classes, which were difficult to distinguish at the beginning, has been improved. The accuracy of “premalignancy” class is also increased, which is ideal for screening applications. Conclusions: Experimental results show that the class bias induced by imbalanced oral cancer image datasets could be reduced using both data- and algorithm-level methods. Our study may provide an important basis for helping understand the influence of unbalanced datasets on oral cancer deep learning classifiers and how to mitigate.

International audience; Mini-EUSO is a high sensitivity imaging telescope that observes the Earth from the ISS in the ultraviolet band (2904÷430 nm), through the UV-transparent window in the Russian Zvezda module. The instrument, launched in 2019 as part of the ESA mission Beyond, has a field of view of 44°, a spatial resolution on the Earth surface of 6.3 km and a temporal resolution of 2.5 microseconds. The telescope detects UV emissions of cosmic, atmospheric and terrestrial origin on different time scales, from a few microseconds upwards. Mini-EUSO main detector optics is composed of two Fresnel lenses focusing light onto an array of 36 Hamamatsu multi-anode photomultiplier tubes, for a total of 2304 pixels. The telescope also contains: two ancillary cameras to complement measurements in the near infrared and visible ranges, an array of Silicon-PhotoMultipliers and UV sensors to manage night-day transitions. In this work we will describe the in-flight operations and performances of the various instruments in the first months after launch.

BackgroundMental health policy makers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable.AimsTo develop and validate a population-level prediction model for need for early intervention in psychosis (EIP) care for first-episode psychosis (FEP) in England up to 2025, based on epidemiological evidence and demographic projections.MethodWe used Bayesian Poisson regression to model small-area-level variation in FEP incidence for people aged 16–64 years. We compared six candidate models, validated against observed National Health Service FEP data in 2017. Our best-fitting model predicted annual incidence case-loads for EIP services in England up to 2025, for probable FEP, treatment in EIP services, initial assessment by EIP services and referral to EIP services for ‘suspected psychosis’. Forecasts were stratified by gender, age and ethnicity, at national and Clinical Commissioning Group levels.ResultsA model with age, gender, ethnicity, small-area-level deprivation, social fragmentation and regional cannabis use provided best fit to observed new FEP cases at national and Clinical Commissioning Group levels in 2017 (predicted 8112, 95% CI 7623–8597; observed 8038, difference of 74 [0.92%]). By 2025, the model forecasted 11 067 new treated cases per annum (95% CI 10 383–11 740). For every 10 new treated cases, 21 and 23 people would be assessed by and referred to EIP services for suspected psychosis, respectively.ConclusionsOur evidence-based methodology provides an accurate, validated tool to inform clinical provision of EIP services about future population need for care, based on local variation of major social determinants of psychosis.

Significance: Diffuse light is ubiquitous in biomedical optics and imaging. Understanding the process of migration of an initial photon population entering tissue to a completely randomized, diffusely scattered population provides valuable insight to the interpretation and design of optical measurements. Aim: The goal of this perspective is to present a brief, unifying analytical framework to describe how properties of light transition from an initial state to a distributed state as light diffusion occurs. Approach: First, measurement parameters of light are introduced, and Monte Carlo simulations along with a simple analytical expression are used to explore how these individual parameters might exhibit diffusive behavior. Second, techniques to perform optical measurements are considered, highlighting how various measurement parameters can be leveraged to subsample photon populations. Results: Simulation results reinforce the fact that light undergoes a transition from a non-diffuse population to one that is first subdiffuse and then fully diffuse. Myriad experimental methods exist to isolate subpopulations of photons, which can be broadly categorized as source- and/or detector-encoded techniques, as well as methods of tagging the tissue of interest. Conclusions: Characteristic properties of light progressing to diffusion can be described by some form of Gaussian distribution that grows in space, time, angle, wavelength, polarization, and coherence. In some cases, these features can be approximated by simpler exponential behavior. Experimental methods to subsample features of the photon distribution can be achieved or theoretical methods can be used to better interpret the data with this framework.

The first two years of human life are characterized by the most dynamic growth in brain structures1–5 and remarkable cognitive and behavioral changes.6,7 Functional near-infrared spectroscopy (fNIRS; a list of abbreviations is provided in Table S1 in the Supplementary Material for the convenience of the reader) is an irreplaceable neuroimaging tool for studying early brain functional development, providing unprecedented opportunities for recording the hemodynamic response in awake, behaving infants because of its balanced temporal-spatial resolution and resilience to movement.8–11 Notably, although the Centers for Disease Control and Prevention defines 0- to 1-year-olds (yo) and 2- to 3-yo children as infants and toddlers, respectively, we have described 0- to 2-yo children as infants in this study for readability. Despite the suitability of fNIRS in infant studies, a major limitation of this technique is the inability of fNIRS data to provide structural information of the head tissue. In fNIRS measurements, a source–detector (SD) pair positioned on the scalp surface measures local concentration changes in oxygenated and deoxygenated hemoglobin caused by neural activity.12–15 On the other hand, while neural activity tied to a specific human function originates in local brain regions. The absence of structural information in the fNIRS signal makes it impossible to correlate the signal response with the anatomical brain regions. Therefore, in fNIRS studies, the scalp location where the SD pair is attached to its underlying brain region where the fNIRS signal originates should be mapped. We call this mapping the scalp-cortex correlation (SCC). Several methods for obtaining SCC have been proposed for studies on adults; however, only a few studies have provided SCC for the infant population. Similar to adults, infant SCC is mostly based on a simple geometrical technique, i.e., correlating the location of the SD pair on the scalp, typically, the midpoint of the SD pair, with cortical regions in a simple point-to-point geometrical manner. For instance, researchers often referred to the international 10-20 or 10-10 system16 when attaching SD pairs on the scalp and then inferred the anatomical locations17–19 according to the geometrical SCC of the adult head20,21 or infant head.22–25 Notably, by linearly reducing the size of the adult heads, the virtual registration method26 has also been employed to estimate SCC in infant studies.27–29 As described above, the point-to-point geometrical SCC provides a tolerable estimation of the underlying brain regions for the absorption change acquired by the SD pair. Nevertheless, the geometrical SCC is based on the assumption that the absorption change occurs at the cortical projection point below the midpoint between the SD pair, and light scattering in the head tissue is not considered. Mounting evidence from light propagation analysis in the adult head revealed light scattering in the head tissue could have a considerable influence on the partial pathlength (PPL) in the brain and the spatial sensitivity profile (SSP).30–34 Notably, a few studies have already demonstrated that light propagation in the infant heads is distinct from that in adults owing to structural differences.35,36 Furthermore, very recent studies on adults have started considering light propagation in turbid media when calculating the SCC.37,38 However, to date, no light propagation analysis-based SCC data are available for 0- to 2-yo infants. In addition to age, SD distance must have a significant influence on optics-based SCC during early development. Only a few studies have examined the effect of SD distance on fNIRS sensitivity in infant brain tissue.35,39 For example, Fukui et al.35 found that fNIRS sensitivity to gray matter (GM) and white matter (WM) of neonates was modulated by the SD distance. These threads of evidence revealed that it remains largely unknown how age and SD distance affect optics-based SCC in 0- to 2-yo infants and how to choose an appropriate SD distance to ensure both the sensitivity to cerebral hemodynamics and the selectivity of signals from a specific brain region of interest. To address these issues, the current study aimed to create a precise optics-based SCC between SD pairs on the scalp fiducial point and brain regions defined by a macro-anatomical atlas by considering the light scattering in 0-, 1-, and 2-yo infant heads. In addition, we quantitatively characterized the changes in SCC with age and SD distance and evaluated the suitable SD distances for each age. The optics-based SCC was obtained for each SD pair by solving the diffusion equation.

This report provides perspectives concerning dual roles of serum ferritin as a measure of both iron status and of inflammation. We suggest benefits of a lower range of serum ferritin as has occurred for total serum cholesterol and fasting blood glucose levels. Observations during a prospective randomized study using phlebotomy in patients with peripheral arterial disease (PAD) offered unique insights into dual roles of serum ferritin both as an iron status marker and acute phase reactant. Robust positive associations between serum ferritin, interleukin 6 [IL-6], tissue necrosis factor-alpha (TNF-a), and high sensitivity C-reactive protein (hsCRP) were discovered. Elevated serum ferritin and IL-6 levels associated with increased mortality and with reduced mortality at ferritin levels < 100 ng/mL. Epidemiologic studies demonstrate similar outcomes. Extremely elevated ferritin and IL-6 levels also occur in individuals with high mortality due to SARS-CoV-2 infection. Disordered iron metabolism reflected by a high range of serum ferritin level signals disease severity and outcomes. Based upon experimental and epidemiologic data, we suggest testing the hypotheses that optimal ferritin levels for cardiovascular mortality reduction range from 20—100 ng/mL with % transferrin levels from 20–50%, to ensure adequate iron status and that ferritin levels above 194 ng/mL associate with all-cause mortality in population cohorts., Graphical Abstract Graphical Abstract

Reducing radiation-induced side effects is one of the most important challenges in paediatric cancer treatment. Recently, there has been growing interest in using spatial normalisation to enable voxel-based analysis of radiation-induced toxicities in a variety of patient groups. The need to consider three-dimensional distribution of doses, rather than dose-volume histograms, is desirable but not yet explored in paediatric populations. In this paper, we investigate the feasibility of atlas construction and spatial normalisation in paediatric radiotherapy. We used planning computed tomography (CT) scans from twenty paediatric patients historically treated with craniospinal irradiation to generate a template CT that is suitable for spatial normalisation. This childhood cancer population representative template was constructed using groupwise image registration. An independent set of 53 subjects from a variety of childhood malignancies was then used to assess the quality of the propagation of new subjects to this common reference space using deformable image registration (i.e. spatial normalisation). The method was evaluated in terms of overall image similarity metrics, contour similarity and preservation of dose-volume properties. After spatial normalisation, we report a dice similarity coefficient of 0.95 ± 0.05, 0.85 ± 0.04, 0.96 ± 0.01, 0.91 ± 0.03, 0.83 ± 0.06 and 0.65 ± 0.16 for brain and spinal canal, ocular globes, lungs, liver, kidneys and bladder. We then demonstrated the potential advantages of an atlas-based approach to study the risk of second malignant neoplasms after radiotherapy. Our findings indicate satisfactory mapping between a heterogeneous group of patients and the template CT. The poorest performance was for organs in the abdominal and pelvic region, likely due to respiratory and physiological motion and to the highly deformable nature of abdominal organs. More specialised algorithms should be explored in the future to improve mapping in these regions. This study is the first step toward voxel-based analysis in radiation-induced toxicities following paediatric radiotherapy.

Micro-photoluminescence maps reveal micron-scale spatial variation in intensity, peak emission energy and bandwidth across InGaN/GaN quantum wells. To investigate the effect of this spatial variation on measurements of the dependence of emission efficiency on carrier density, excitation power-dependent emission was collected from a bright and dark region on each of blue-and green emitting samples. The onset of efficiency droop was found to occur at a greater carrier density in the dark regions than in the bright, by factors of 1.2 and 1.8 in the blue and green-emitting samples, respectively. By spatially integrating the emission from progressively larger areas, it is also shown that collection areas greater than ∼50 μm in diameter are required to reduce the intensity variation to less than 10%.

International audience; Mosquito control is implemented when arboviruses are detected in patients or in field-collected mosquitoes. However, mass screening of mosquitoes is usually laborious and expensive, requiring specialized expertise and equipment. Detection of virus in mosquito saliva using honey-impregnated filter papers seems to be a promising method as it is non-destructive and allows monitoring the viral excretion dynamics over time from the same mosquito. Here we test the use of filter papers to detect chikungunya virus in mosquito saliva in laboratory conditions, before proposing this method in large-scale mosquito surveillance programs. We found that 0.9 cm 2 cards impregnated with a 50% honey solution could replace the forced salivation technique as they offered a viral RNA detection until 7 days after oral infection of Aedes aegypti and Aedes albopictus mosquitoes with CHIKV.

Objective The incidence of lung cancer is four times higher in people with chronic obstructive pulmonary disease (COPD) compared with the general population. Promotion of a shorter time from symptom onset to presentation is one potential strategy for earlier lung cancer diagnosis, but distinguishing respiratory symptoms can be difficult. We investigated how the experience of COPD influences symptom appraisal and help seeking for potential lung cancer symptoms. Methods We conducted qualitative interviews with men (n = 17) and women (n = 23) aged 40 to 83 years with COPD. Topic guides drew on the integrated symptom‐response framework and covered symptom experience, interpretation, action, recognition, help seeking, evaluation, and reevaluation. We used the framework method to analyse the data. Results Participants said that they attributed chest symptoms to their COPD; no other cause was considered. Participants said that family/friends noticed changes in their symptoms and encouraged help seeking. Others felt isolated by their COPD because they could not get out, were fatigued, or were embarrassed. Participants visited health professionals frequently, but increased risk of lung cancer was not discussed. Conclusions Our study provides insight into different levels of influence on symptom appraisal and targets for intervention. Greater awareness of increased lung cancer risk and support to act on symptom changes is essential and could be achieved through a concerted information campaign. Health professionals working with people with COPD could also optimise appointments to support symptom appraisal of potential lung cancer symptoms.

Objective To describe health‐care personnel's (HCP's) perceptions of the ethical climate at their workplace in paediatric oncology. Methods A cross‐sectional survey was conducted using the Swedish version of the shortened Hospital Ethical Climate Survey (HECS‐S). HCP at all six paediatric oncology centres (POCs) in Sweden were invited to participate. Analysis included descriptive statistics, the Mann‐Whitney U test (differences between groups) and Spearman's rank correlation. Informed consent was assumed when the respondents returned the survey. Results A high response rate was achieved as 278 HCP answered the questionnaire. Medical doctors perceived the ethical climate to be more positive than registered nurses and nursing assistants. At the POC with the significantly lowest values concerning immediate manager, no significant correlation with the other items was found. At the POC with the poorest ethical climate, HCP also had the lowest perception of the possibility of practicing ethically good care. Conclusions Differences between centres and professional groups have been demonstrated. A negative perception of the immediate manager does not necessarily mean that the ethical climate is poor, but the manager's ability to provide the conditions for an open dialogue within the health‐care team is key to achieving an ethical climate.

Diagnostic Exome Sequencing in 100 Consecutive Patients With Both Epilepsy and Intellectual Disability Snoeijen-Schouwenaars FM, van Ool JS, Verhoeven JS, et al. Epilepsia. 2019;60(1):155-164. doi:10.1111/epi.14618. Epub December 7, 2018. PMID: 30525188.Objective:Epilepsy is highly prevalent among patients with intellectual disability (ID), and seizure control is often difficult. Identification of the underlying etiology in this patient group is important for daily clinical care. We assessed the diagnostic yield of whole-exome sequencing (WES). In addition, we evaluated which clinical characteristics influence the likelihood of identifying a genetic cause and we assessed the potential impact of the genetic diagnosis on (antiepileptic) treatment strategy.Methods:One hundred patients with both unexplained epilepsy and (borderline) ID (intelligence quotient ≤85) were included. All patients were evaluated by a clinical geneticist, a (pediatric) neurologist, and/or a specialist ID physician. Whole-exome sequencing analysis was performed in 2 steps. In step 1, analysis was restricted to the latest versions of ID and/or epilepsy gene panels. In step 2, exome analysis was extended to all genes (so-called full exome analysis). The results were classified according to the American College of Medical Genetics and Genomics guidelines. Results: In 58 patients, the diagnostic WES analysis reported one or more variant(s). In 25 of the 100 patients, these were classified as (likely) pathogenic, in 24 patients as variants of uncertain significance, and in the remaining patients the variant was most likely not related to the phenotype. In 10 (40%) of 25 patients with a (likely) pathogenic variant, the genetic diagnosis might have an impact on the treatment strategy in the future.Significance:This study illustrates the clinical diagnostic relevance of WES for patients with both epilepsy and ID. It also demonstrates that implementing WES diagnostics might have impact on the (antiepileptic) treatment strategy in this population. Confirmation of variants of uncertain significance in (candidate) genes may further increase the yield. Diagnostic Yield of Genetic Tests in Epilepsy: A Meta-Analysis and Cost-Effectiveness Study Sánchez Fernández I, Loddenkemper T, Gaínza-Lein M, Sheidley BR, Poduri A. Neurology. 2019. Epub ahead of print. pii: 10.1212/WNL.0000000000006850. doi:10.1212/WNL.0000000000006850. PMID: 30610098 Objective:To compare the cost-effectiveness of genetic testing strategies in patients with epilepsy of unknown etiology.Methods:This meta-analysis and cost-effectiveness study compared strategies involving 3 genetic tests: chromosomal microarray (CMA), epilepsy panel (EP) with deletion/duplication testing, and whole-exome sequencing (WES) in a cost-effectiveness model, using “no genetic testing”“ as a point of comparison.Results:Twenty studies provided information on the diagnostic yield of CMA (8 studies), EP (9 studies), and WES (6 studies). The diagnostic yield was highest for WES: 0.45 (95% confidence interval [CI]: 0.33-0.57; 0.32 [95% CI: 0.22-0.44] adjusting for potential publication bias), followed by EP: 0.23 (95% CI: 0.18-0.29) and CMA: 0.08 (95% CI: 0.06-0.12). The most cost-effective test was WES with an incremental cost-effectiveness ratio (ICER) of US$15 000/diagnosis. However, after adjusting for potential publication bias, the most cost-effective test was EP (ICER: US$15 848/diagnosis) followed by WES (ICER: US$34 500/diagnosis). Among combination strategies, the most cost-effective strategy was WES, then if nondiagnostic, EP, then if nondiagnostic, CMA (ICER: US$15 336/diagnosis); although adjusting for potential publication bias, the most cost-effective strategy was EP ± CMA ± WES (ICER: US$18 385/diagnosis). Although the cost-effectiveness of individual tests and testing strategies overlapped, CMA was consistently less cost-effective than WES and EP.Conclusion:Whole-exome sequencing and EP are the most cost-effective genetic tests for epilepsy. Our analyses support for a broad population of patients with unexplained epilepsy, starting with these tests. Although less expensive, CMA has lower yield, and its use as the first-tier test is thus not supported from a cost-effectiveness perspective.

Bisphenol A (BPA), a well-known endocrine disruptor, is used as a color developer in thermal paper. More recently, some emerging structural analogues have been introduced to replace BPA due to the strengthened regulations concerning thermal paper. Nevertheless, very limited data are available regarding their occurrence and potential health risks. Here, thirteen potentially toxic compounds were investigated in paper products (120 thermal papers and 81 nonthermal papers) collected in Beijing, China. The results indicated that the replacement of BPA by alternatives such as Bisphenol S (BPS), Bis(2-chloroethyl)ether-4,4″-dihydroxydiphenyl sulfone copolymer (D-90), 4-hydroxyphenyl 4-isoprooxyphenylsulfone (D-8), Bis(4-hydroxyphenyl)sulfonylphenyl (BPS-MAE) and Bis-(3-allyl-4-hydroxyphenyl) sulfone (TGSA) has been significantly advanced in several types of thermal paper (i.e., market weight stickers, train tickets, express labels, air boarding passes and lottery tickets). The mean value for the total analyte concentrations in thermal paper was 6.06 mg/g, and the highest level found was 26.0 mg/g. In addition, the frequent detection of these chemicals in nonthermal paper (>80%, n = 81) demonstrated that the contamination in thermal paper can be spread into other recycled paper, such as corrugated boxes, newspapers, food contact papers, etc. The estimated daily intake of BPA and its alternatives through the handling of thermal paper was 0.025 μg/kg bw/day for the general population. This is the first report on the occurrence of various new BPA alternatives in paper products from China, which will be helpful for further risk assessment and making responsible replacement decisions.

High-fidelity simulations of actual wind farms with the Actuator Line Model, in a Large Eddy Simulation framework, have been performed in the past years, for both onshore and offshore sites. It has become the state of the art to simulate the wind flow through wind turbines and wind farms and it could be a powerful tool to assess the operation of actual wind farms and potential improvements. The objective of the present paper is two-fold: develop a high-fidelity numerical model of an onshore wind farm to be used to assess the influence of different environmental and aerodynamic conditions in its power performance and analyze, as case study, the effect of the topography in the wind flow and power production.

This paper compares the accuracy of four different FLORIS model implementations characterized by increasing levels of accounted physics. The predictions of each model were tested against experimental observations obtained from wind tunnel tests of a cluster of three scaled wind turbines. The experiments were conducted for a wide range of environmental conditions, and mainly with yawed turbines. The results showed a significant improvement in the accuracy of the base model by adding more details to the physical effects of the simulation, such as secondary steering and a heterogeneous flow field. It is also interesting to note that the FLORIS predictions become particularly accurate when considering inflow-dependent power losses in yaw-misaligned conditions.

In this study a new yaw mechanism for a small existing wind turbine model is designed and tested. The special requirement for this yaw device is its compact design due to the small length scaling factor of the model turbine. Such a dense design is crucial in order for the wake of the model turbine not to be influenced by the yaw mechanism. Furthermore, it has to have a fast system response and high accuracy to take into account the time scaling. Different concepts are investigated and a design located at the tower base is realized. To limit its drag, the structure is being concealed in an aerodynamically shaped cover. Wind tunnel measurements confirmed that the wake of the turbine is not influenced by the structure. A system analysis, using a Simulink model of the turbine helps finding the right motor and shows that the device has a fast system response with high accuracy. Consequently, the designed yaw mechanism is suited for the small wind turbine model, which can be used for experimental wake and wind farm control studies in the future.

Significance: Surgical simulators, both virtual and physical, are increasingly used as training tools for teaching and assessing surgical technical skills. However, the metrics used for assessment in these simulation environments are often subjective and inconsistent. Aim: We propose functional activation metrics, derived from brain imaging measurements, to objectively assess the correspondence between brain activation with surgical motor skills for subjects with varying degrees of surgical skill. Approach: Cortical activation based on changes in the oxygenated hemoglobin (HbO) of 36 subjects was measured using functional near-infrared spectroscopy at the prefrontal cortex (PFC), primary motor cortex, and supplementary motor area (SMA) due to their association with motor skill learning. Inter-regional functional connectivity metrics, namely, wavelet coherence (WCO) and wavelet phase coherence were derived from HbO changes to correlate brain activity to surgical motor skill levels objectively. Results: One-way multivariate analysis of variance found a statistically significant difference in the inter-regional WCO metrics for physical simulator based on Wilk’s Λ for expert versus novice, F ( 10,1 ) = 7495.5, p

Antisnake venom (ASV) is the only specific and standard treatment for snakebite envenoming worldwide. The knowledge of antivenom dosage, mode of administration, availability, and logistics is essential to the healthcare practitioners (HCPs) in the management of snakebites. It is vital for the HCPs involved in the handling of ASVs to have its basic knowledge. The ASV contains proteins and can, therefore, easily get denatured if not handled appropriately, leading to poor therapeutic outcome. It is also essential for clinicians to be aware of the tendency of ASV to cause a severe life-threatening hypersensitivity reaction. There is currently no validated tool for assessing the knowledge of ASV among HCPs. Therefore, we developed and validated a tool for evaluating the HCPs knowledge of ASV. The items included in the tool were first generated from a comprehensive literature review. Face validity were conducted by presenting the drafted tool to ten experts on the subject matter. A validation study was conducted among doctors, pharmacists, nurses, pharmacy technicians, and the general public. The objectives of the study were to test the tool for content validity using the content validity index (CVI), construct validity using contrast group approach, difficulty index, readability, and reliability test using the test-retest method. We developed and validated a final tool containing thirty-three items. The tool was valid for face validity and had a scale-level (average) content validity (S-CVI/Ave) of 0.91. The ASV knowledge of pharmacists was higher than that of doctors, pharmacy technicians, nurses, and the general public (p, Highlights • A tool for assessing knowledge of anti-snake venom was developed and validated. • Psychometrics approach was used in validating the knowledge assessment tool. • The tool is reliable with a Simple Measure of Gobbledygook grade level 7. • The tool can measure anti-snake venom knowledge among healthcare practitioners.

The goal of this research is to develop ecologically and economically optimized implementation strategies for social housing. Therefore, a case study is analysed over its life cycle using life cycle assessments (LCA) and life cycle costs (LCC) regarding the global warming potential (GWP) and its environmental impact costs (cost per ton of CO2). The case study is optimized regarding the embodied emissions of construction and energy demand during its use stage. Considering the cost ceiling for social housing, it is evident, that an implementation of renewable materials and energies is mandatory in order to prevent the risk of a project failure due to excessive environmental impact costs.

This paper explores the trade-off between redeveloping an urban site with higher density and maintaining solar access for the surrounding context in the hot and dry climate of Tel Aviv. Such trade-offs are important for future urban development in the Middle East, where densification is a demographic and environmental need. We explore this trade-off with multi-objective optimization (MOO). Specifically, we benchmark seven MOO algorithms on two test problems with different, parametric typologies: courtyard and high-rise. For both problems, we aim to maximize Floor Area Ratio and the simulation-based Context Exposure Index, a novel metric based on the Israeli green building code. The high-rise emerges as the better performing typology, and HypE, SPEA2, and RBFMOpt as the most efficient and robust MOO algorithms.