Climate change is at the forefront of discussions for many companies. Climate change-related disclosures and reporting are important tools and allow stakeholders to understand climate-related risks a company is facing and help various stakeholders to take informed decisions.

The landscape for climate change-related reporting requirements is ever evolving, with a trend from voluntary to mandatory, with many global disclosure standards and requirements influencing local requirements and other related standards.

This paper explores these ideas further, giving a general background to disclosure requirements, discusses greenwashing, details disclosure organisations including TCFD and the ISSB, and provides details on a country level including green taxonomies.

In this work, we study an elliptic problem involving an operator of mixed order with both local and nonlocal aspects, and in either the presence or the absence of a singular nonlinearity. We investigate existence or nonexistence properties, power- and exponential-type Sobolev regularity results, and the boundary behaviour of the weak solution, in the light of the interplay between the summability of the datum and the power exponent in singular nonlinearities.

OBJECTIVES/GOALS: Glioblastomas (GBMs) are heterogeneous, treatment-resistant tumors that are driven by populations of cancer stem cells (CSCs). In this study, we perform an epigenetic-focused functional genomics screen in GBM organoids and identify WDR5 as an essential epigenetic regulator in the SOX2-enriched, therapy resistant cancer stem cell niche. METHODS/STUDY POPULATION: Despite their importance for tumor growth, few molecular mechanisms critical for CSC population maintenance have been exploited for therapeutic development. We developed a spatially resolved loss-of-function screen in GBM patient-derived organoids to identify essential epigenetic regulators in the SOX2-enriched, therapy resistant niche. Our niche-specific screens identified WDR5, an H3K4 histone methyltransferase responsible for activating specific gene expression, as indispensable for GBM CSC growth and survival. RESULTS/ANTICIPATED RESULTS: In GBM CSC models, WDR5 inhibitors blocked WRAD complex assembly and reduced H3K4 trimethylation and expression of genes involved in CSC-relevant oncogenic pathways. H3K4me3 peaks lost with WDR5 inhibitor treatment occurred disproportionally on POU transcription factor motifs, required for stem cell maintenance and including the POU5F1(OCT4)::SOX2 motif. We incorporated a SOX2/OCT4 motif driven GFP reporter system into our CSC cell models and found that WDR5 inhibitor treatment resulted in dose-dependent silencing of stem cell reporter activity. Further, WDR5 inhibitor treatment altered the stem cell state, disrupting CSC in vitro growth and self-renewal as well as in vivo tumor growth. DISCUSSION/SIGNIFICANCE: Our results unveiled the role of WDR5 in maintaining the CSC state in GBM and provide a rationale for therapeutic development of WDR5 inhibitors for GBM and other advanced cancers. This conceptual and experimental framework can be applied to many cancers, and can unmask unique microenvironmental biology and rationally designed combination therapies.

As COVID-19 was declared a health emergency in March 2020, there was immense demand for information about the novel pathogen. This paper examines the clinician-reported impact of Project ECHO COVID-19 Clinical Rounds on clinician learning. Primary sources of study data were Continuing Medical Education (CME) Surveys for each session from the dates of March 24, 2020 to July 30, 2020 and impact surveys conducted in November 2020, which sought to understand participants’ overall assessment of sessions. Quantitative analyses included descriptive statistics and Mann-Whitney testing. Qualitative data were analyzed through inductive thematic analysis. Clinicians rated their knowledge after each session as significantly higher than before that session. 75.8% of clinicians reported they would ‘definitely’ or ‘probably’ use content gleaned from each attended session and clinicians reported specific clinical and operational changes made as a direct result of sessions. 94.6% of respondents reported that COVID-19 Clinical Rounds helped them provide better care to patients. 89% of respondents indicated they ‘strongly agree’ that they would join ECHO calls again.COVID-19 Clinical Rounds offers a promising model for the establishment of dynamic peer-to-peer tele-mentoring communities for low or no-notice response where scientifically tested or clinically verified practice evidence is limited.

Innovation is a key driver for product success. Engineering design and lean start-up are prominent innovation methodologies well accepted and widely used. There is a lack of availability of pragmatic reflections for innovators to put into practice. The paper addresses this need by undertaking a comparative analysis of the two methodologies, using three case studies of medical device innovation. Directions and insights on how innovators may employ one or both approaches at different stages of their innovation are presented.

Case fatality rate (CFR) and doubling time are important characteristics of any epidemic. For coronavirus disease 2019 (COVID-19), wide variations in the CFR and doubling time have been noted among various countries. Early in the epidemic, CFR calculations involving all patients as denominator do not account for the hospitalised patients who are ill and will die in the future. Hence, we calculated cumulative CFR (cCFR) using only patients whose final clinical outcomes were known at a certain time point. We also estimated the daily average doubling time. Calculating CFR using this method leads to temporal stability in the fatality rates, the cCFR stabilises at different values for different countries. The possible reasons for this are an improved outcome rate by the end of the epidemic and a wider testing strategy. The United States, France, Turkey and China had high cCFR at the start due to low outcome rate. By 22 April, Germany, China and South Korea had a low cCFR. China and South Korea controlled the epidemic and achieved high doubling times. The doubling time in Russia did not cross 10 days during the study period.

A principled approach to understand networks is to formulate generative models and infer their parameters from given network data. Due to the scarcity of data in the form of multiple networks that have evolved from the same process, generative models are typically formulated to learn parameters from a single network observation, hence ignoring the natural variability of the “true” process. In this paper, we highlight the importance of variability in evaluating generative models and present two ways of quantifying the variability for a finite set of networks. The first evaluation scheme compares the statistical properties of networks in a dissimilarity space, while the other relies on data-driven entropy measures to compute variability in network populations. Using these measures, we evaluate the ability of four generative models to synthesize networks that capture the variability of the “true” process. Our empirical analysis suggests that generative models fitted for a single network observation fail to capture the variability in the network population. Our work highlights the need for rethinking the way we evaluate the goodness-of-fit of new and existing network models and devising models that are capable of matching the variability of network populations when available.

Evidence suggests that both high and low birth weight children have increased the risk for obesity and the metabolic syndrome in adulthood. Previously we have found altered feeding behaviour and food preferences in pre-school children and adults born with low birth weight. In this study, we investigated if birth weight was associated with different intake of fat, carbohydrate and/or protein at 6–12 years of age. This is a cross-sectional study where 255 guardians answered online and telephone questions including anthropometrics and demographic data, parental family food rules (food control, encouragement and restriction) and a complete web-based FFQ for their children (130 boys and 125 girls). Baseline demographic and parental food rules characteristics did not differ accordingly to sex. Linear regression models were conducted separately for each sex, adjusted for income, age and maternal age. There were no differences in total energy intake, but energy density (ED, energy content/g) was negatively associated with birth weight in boys. Macronutrient analysis showed that ED intake was from a greater intake of fat. Birth weight was not a significant predictor of protein and carbohydrate intake in boys. In girls, we saw a positive correlation between fat intake and cholesterol intake v. birth weight, but no association with ED intake (results did not remain after adjustment). The study shows that low birth weight is associated with altered fat intake in childhood in a sex-specific manner. It is likely that biological factors such as fetal programming of homoeostatic and/or hedonic pathways influencing food preferences are involved in this process.

We estimate spatial gradients in the ionosphere using the Global Positioning System and GLONASS (Russian global navigation system) observations, utilising data from multiple Global Positioning System stations in the vicinity of Murchison Radio-astronomy Observatory. In previous work, the ionosphere was characterised using a single-station to model the ionosphere as a single layer of fixed height and this was compared with ionospheric data derived from radio astronomy observations obtained from the Murchison Widefield Array. Having made improvements to our data quality (via cycle slip detection and repair) and incorporating data from the GLONASS system, we now present a multi-station approach. These two developments significantly improve our modelling of the ionosphere. We also explore the effects of a variable-height model. We conclude that modelling the small-scale features in the ionosphere that have been observed with the MWA will require a much denser network of Global Navigation Satellite System stations than is currently available at the Murchison Radio-astronomy Observatory.

We compare first-order (refractive) ionospheric effects seen by the MWA with the ionosphere as inferred from GPS data. The first-order ionosphere manifests itself as a bulk position shift of the observed sources across an MWA field of view. These effects can be computed from global ionosphere maps provided by GPS analysis centres, namely the CODE. However, for precision radio astronomy applications, data from local GPS networks needs to be incorporated into ionospheric modelling. For GPS observations, the ionospheric parameters are biased by GPS receiver instrument delays, among other effects, also known as receiver DCBs. The receiver DCBs need to be estimated for any non-CODE GPS station used for ionosphere modelling. In this work, single GPS station-based ionospheric modelling is performed at a time resolution of 10 min. Also the receiver DCBs are estimated for selected Geoscience Australia GPS receivers, located at Murchison Radio Observatory, Yarragadee, Mount Magnet and Wiluna. The ionospheric gradients estimated from GPS are compared with that inferred from MWA. The ionospheric gradients at all the GPS stations show a correlation with the gradients observed with the MWA. The ionosphere estimates obtained using GPS measurements show promise in terms of providing calibration information for the MWA.

Ventricular assist devices (VADs) provide long- and short-term support to chronically ill heart disease patients; these devices are expected to match the remarkable functionality of the natural heart, which makes their design a very challenging task. Blood pumps, the principal component of the VADs, must operate over a wide range of flow rates and pressure heads and minimise the damage to blood cells in the process. They should also be small to allow easy implantation in both children and adults. Mathematical methods and computational fluid dynamics (CFD) have recently emerged as powerful design tools in this context; a review of the recent advances in the field is presented here. This review focusses on the CFD-based design strategies applied to blood flow in blood pumps and other blood-handling devices. Both simulation methods for blood flow and blood damage models are reviewed. The literature is put into context with a discussion of the chronological development in the field. The review is illustrated with specific examples drawn from our group's Galerkin/least squares (GLS) finite-element simulations of the basic Newtonian flow problem for the continuous-flow centrifugal GYRO blood pump. The GLS formulation is outlined, and modifications to include models that better represent blood rheology are shown. Haemocompatibility analysis of the pump is reviewed in the context of haemolysis estimations based on different blood damage models. Our strain-based blood damage model that accounts for the viscoleasticity associated with the red blood cells is reviewed in detail. The viability of design improvement based on trial and error and complete simulation-based design optimisation schemes are also discussed.

The problem has been examined using a kinematic model for wall pliability, wherein a kinematic postulation of the wall boundary conditions is made. A form of the normalized wall-displacement and its phase are used as additional parameters in an extended eigenvalue problem. Using this technique the entire gamut of possibilities regarding stability of flow past (normally) pliable walls can be examined, yet without recourse to any specific material properties for the wall. Rather, the results based on the kinematic model can be used to back-calculate the material properties corresponding to any chosen model for the dynamics of the wall. A sample back calculation is discussed herein for the Benjamin–Landahl wall model, and based on this some predictions are made regarding both stabilization of the flow and physical realizability of modes. It is believed that the kinematic model will prove useful in further understanding of the problem, and in the design of stabilizing coatings.

The results show that there are three important ‘mode classes’ (distinct from ‘modes’), namely the Tollmien–Schlichting (TS), resonant (R) and Kelvin–Helmholtz (KH). Whereas the TS and R mode classes broadly agree with modes bearing similar names as found by earlier workers, the present KH mode class is difficult to classify based on earlier work. Moreover, there are also important transitional mode classes in the regions of bifurcations of the regular mode classes.

Two important concepts evolve in connection with the TS and R mode classes, namely the existence of ‘stable pockets’ for the former and ‘unstable pockets’ for the latter. It is also confirmed herein that there are conflicting requirements on the damping d to stabilize TS and R modes. Considering these points it has been suggested that TS and R modes be avoided by keeping soft surfaces as compliant coatings. However, this in turn leads to instabilities from one of the transitional mode classes. It is also seen that a soft surface that is also marginally active (i.e. having a small negative value of d) could render even better stabilization.

In this work, a hydrogen (H2) reduction process has been developed which gives tungsten (W) nucleation on titanium nitride (TiN) adhesion layers with a very short incubation time, eliminating the need for a silane (SiH4reduced seed layer. The nucleation was found to be strongly dependent on the following factors: temperature of the substrate, total pressure in chamber, and gas introduction sequence into the reactor. Theenhanced nucleation rate has been explained based on two competing reactions: dissociation of H2, and formation of titanium subfluorides on the TiN surface.