Breaking the ESG rating divergence: an open geospatial framework for environmental scores

Information about a company's environmental, social and governance (ESG) performance has become increasingly important in the decision-making process of financial institutions. The financial implications of environmental challenges (e.g. water stress), negative social impacts (e.g. health impacts in local communities) or poor corporate governance (e.g. breaching legislation) all continue to increase. Accordingly, there is a need for financial institutions to incorporate information on ESG risks, opportunities and impacts in decisions that relate to risk management, investments, credit, strategy, and reporting. ESG information is typically disseminated through ESG ratings, which combine the three constituents into a single rating, or ascribe them separate scores. The compilation of ESG ratings and the identification of appropriate data sources is an inherently complex process; as such, there is no single standard for data collection or reporting. This has led to a divergence in the underlying data sources used by different rating providers, as well as in the determination of factors that are deemed worthy of measurement in the first place. For example, when assessing a company's environmental impact, one rating provider may rely on company-provided data, while another may incorporate independent third-party assessments. Unfortunately, there is currently no clear mechanism for effectively resolving such disagreements to establish a standardised approach to ESG rating assessments. However, geospatial data and analyses offer several key advantages for ESG assessments, including consistency, the potential for enhanced accuracy, and the ability to identify and assess environmental impacts at a detailed physical asset level, in addition to evaluating the broader spatial context. By incorporating geospatial information (obtained through manually processing remotely sensed data, or by using existing products) rating methodologies can be improved, and disparities can be addressed more effectively. This would enable a more comprehensive understanding of the environmental considerations of ESG assessments, promoting a more informed and precise decision-making process. Within this context, a few institutions (e.g. the University of Oxford, the WWF, and a few others) are pioneering thought leadership around spatial finance, including the assessment of ESG issues utilising geospatial intelligence, but there are no consistent frameworks for incorporating geospatial data into ESG ratings and analysis. This paper explores the opportunity for such a geospatial environmental scoring framework, defining a variety of methods in which open data with broad geographic coverage could be incorporated into ESG analysis, generalisable to a range of assets and sectors. The proposed framework is organised into two categories: localised effects, which directly impact the immediate vicinity of an asset, and delocalised effects, which contribute to global climate change and atmospheric pollution. Sub-scores are defined within these categories, which capture both the localised effects on land use, biodiversity, soils, and hydrology, and the global impacts resulting from atmospheric emissions. The approaches for handling geospatial data to generate both these sub-scores and the final E-score are presented, including a test case, and the complete methodology is made available in open repositories

An iterative algorithm for parametrization of shortest length shift registers over finite rings

The construction of shortest feedback shift registers for a finite sequence S_1,...,S_N is considered over the finite ring Z_{p^r}. A novel algorithm is presented that yields a parametrization of all shortest feedback shift registers for the sequence of numbers S_1,...,S_N, thus solving an open problem in the literature. The algorithm iteratively processes each number, starting with S_1, and constructs at each step a particular type of minimal Gr\"obner basis. The construction involves a simple update rule at each step which leads to computational efficiency. It is shown that the algorithm simultaneously computes a similar parametrization for the reciprocal sequence S_N,...,S_1.Comment: Submitte

Genetic susceptibility, elevated blood pressure, and risk of atrial fibrillation: a Mendelian randomization study

BACKGROUND: Whether elevated blood pressure (BP) is a modifiable risk factor for atrial fibrillation (AF) is not established. We tested (1) whether the association between BP and risk of AF is causal, (2) whether it varies according to individual’s genetic susceptibility for AF, and (3) the extent to which specific BP-lowering drugs are expected to reduce this risk. METHODS: First, causality of association was assessed through two-sample Mendelian randomization, using data from two independent genome-wide association studies that included a population of one million Europeans in total. Second, the UK Biobank data of 329,237 participants at baseline was used to study the effect of BP on AF according to genetic susceptibility of developing AF. Third, a possible treatment effect with major BP-lowering drug classes on AF risk was predicted through genetic variants in genes encode the therapeutic targets of each drug class. Estimated drug effects were compared with effects on incident coronary heart disease, for which direct trial evidence exists. RESULTS: The two-sample Mendelian randomization analysis indicated that, on average, exposure to a higher systolic BP increased the risk of AF by 19% (odds ratio per each 10-mmHg [OR] 1.19 [1.12 to 1.27]). This association was replicated in the UK biobank using individual participant data. However, in a further genetic risk-stratified analysis, there was evidence for a linear gradient in the relative effects of systolic BP on AF; while there was no conclusive evidence of an effect in those with low genetic risk, a strong effect was observed among those with high genetic susceptibility for AF. The comparison of predicted treatment effects using genetic proxies for three main drug classes (angiotensin-converting enzyme inhibitors, beta-blockers, and calcium channel blockers) suggested similar average effects for the prevention of atrial fibrillation and coronary heart disease. CONCLUSIONS: The effect of elevated BP on the risk of AF is likely to be causal, suggesting that BP-lowering treatment may be effective in AF prevention. However, average effects masked clinically important variations, with a more pronounced effect in individuals with high genetic susceptibility risk for AF

Blood pressure lowering and risk of new-onset type 2 diabetes: an individual participant data meta-analysis

Background: Blood pressure lowering is an established strategy for preventing microvascular and macrovascular complications of diabetes, but its role in the prevention of diabetes itself is unclear. We aimed to examine this question using individual participant data from major randomised controlled trials. Methods: We performed a one-stage individual participant data meta-analysis, in which data were pooled to investigate the effect of blood pressure lowering per se on the risk of new-onset type 2 diabetes. An individual participant data network meta-analysis was used to investigate the differential effects of five major classes of antihypertensive drugs on the risk of new-onset type 2 diabetes. Overall, data from 22 studies conducted between 1973 and 2008, were obtained by the Blood Pressure Lowering Treatment Trialists’ Collaboration (Oxford University, Oxford, UK). We included all primary and secondary prevention trials that used a specific class or classes of antihypertensive drugs versus placebo or other classes of blood pressure lowering medications that had at least 1000 persons-years of follow-up in each randomly allocated arm. Participants with a known diagnosis of diabetes at baseline and trials conducted in patients with prevalent diabetes were excluded. For the one-stage individual participant data meta-analysis we used stratified Cox proportional hazards model and for the individual participant data network meta-analysis we used logistic regression models to calculate the relative risk (RR) for drug class comparisons. Findings: 145 939 participants (88 500 [60·6%] men and 57 429 [39·4%] women) from 19 randomised controlled trials were included in the one-stage individual participant data meta-analysis. 22 trials were included in the individual participant data network meta-analysis. After a median follow-up of 4·5 years (IQR 2·0), 9883 participants were diagnosed with new-onset type 2 diabetes. Systolic blood pressure reduction by 5 mm Hg reduced the risk of type 2 diabetes across all trials by 11% (hazard ratio 0·89 [95% CI 0·84–0·95]). Investigation of the effects of five major classes of antihypertensive drugs showed that in comparison to placebo, angiotensin-converting enzyme inhibitors (RR 0·84 [95% 0·76–0·93]) and angiotensin II receptor blockers (RR 0·84 [0·76–0·92]) reduced the risk of new-onset type 2 diabetes; however, the use of β blockers (RR 1·48 [1·27–1·72]) and thiazide diuretics (RR 1·20 [1·07–1·35]) increased this risk, and no material effect was found for calcium channel blockers (RR 1·02 [0·92–1·13]). Interpretation: Blood pressure lowering is an effective strategy for the prevention of new-onset type 2 diabetes. Established pharmacological interventions, however, have qualitatively and quantitively different effects on diabetes, likely due to their differing off-target effects, with angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers having the most favourable outcomes. This evidence supports the indication for selected classes of antihypertensive drugs for the prevention of diabetes, which could further refine the selection of drug choice according to an individual's clinical risk of diabetes. Funding: British Heart Foundation, National Institute for Health Research, and Oxford Martin School

Applicability of an abbreviated version of the Child-OIDP inventory among primary schoolchildren in Tanzania

Background: There is a need for studies evaluating oral health related quality of life (OHRQoL) of children in developing countries. Aim: to assess the psychometric properties, prevalence and perceived causes of the child version of oral impact on daily performance inventory (Child- OIDP) among school children in two socio-demographically different districts of Tanzania. Socio-behavioral and clinical correlates of children's OHRQoL were also investigated.Method: One thousand six hundred and one children ( mean age 13 yr, 60.5% girls) attending 16 ( urban and rural) primary schools in Kinondoni and Temeke districts completed a survey instrument in face to face interviews and participated in a full mouth clinical examination. The survey instrument was designed to measure a Kiswahili translated and culturally adapted Child-OIDP frequency score, global oral health indicators and socio-demographic factors. Results: The Kiswahili version of the Child- OIDP inventory preserved the overall concept of the original English version and revealed good reliability in terms of Cronbach's alpha coefficient of 0.77 ( Kinondoni: 0.62, Temeke: 0.76). Weighted Kappa scores from a test-retest were 1.0 and 0.8 in Kinondoni and Temeke, respectively. Validity was supported in that the OIDP scores varied systematically and in the expected direction with self-reported oral health measures and socio-behavioral indicators. Confirmatory factor analyses, CFA, confirmed three dimensions identified initially by Principle Component Analysis within the OIDP item pool. A total of 28.6% of the participants had at least one oral impact. The area specific rates for Kinondoni and Temeke were 18.5% and 45.5%. The most frequently reported impacts were problems eating and cleaning teeth, and the most frequently reported cause of impacts were toothache, ulcer in mouth and position of teeth. Conclusion: This study showed that the Kiswahili version of the Child- OIDP was applicable for use among schoolchildren in Tanzania

Consumers as tutors – legitimate teachers?

BACKGROUND: The aim of this study was to research the feasibility of training mental health consumers as tutors for 4(th )year medical students in psychiatry. METHODS: A partnership between a consumer network and an academic unit in Psychological Medicine was formed to jointly develop a training package for consumer tutors and a curriculum in interviewing skills for medical students. Student attitudes to mental health consumers were measured pre and post the program. All tutorial evaluation data was analysed using univariate statistics. Both tutors and students evaluated the teaching program using a 4 point rating scale. The mean scores for teaching and content for both students and tutors were compared using an independent samples t-test. RESULTS: Consumer tutors were successfully trained and accredited as tutors and able to sustain delivery of tutorials over a 4 year period. The study found that whilst the medical students started with positive attitudes towards consumers prior to the program, there was a general trend towards improved attitude across all measures. Other outcomes for tutors and students (both positive and negative) are described. CONCLUSIONS: Consumer tutors along with professional tutors have a place in the education of medical students, are an untapped resource and deliver largely positive outcomes for students and themselves. Further possible developments are described

The relationships between problem characteristics, achievement-related behaviors, and academic achievement in problem-based learning

This study investigated the influence of five problem characteristics on students' achievement-related classroom behaviors and academic achievement. Data from 5,949 polytechnic students in PBL curricula across 170 courses were analyzed by means of path analysis. The five problem characteristics were: (1) problem clarity, (2) problem familiarity, (3) the extent to which the problem stimulated group discussion, (4) self-study, and (5) identification of learning goals. The results showed that problem clarity led to more group discussion, identification of learning goals, and self-study than problem familiarity. On the other hand, problem familiarity had a stronger and direct impact on academic achievement

Lobe Specific Ca2+-Calmodulin Nano-Domain in Neuronal Spines: A Single Molecule Level Analysis

Calmodulin (CaM) is a ubiquitous Ca2+ buffer and second messenger that affects cellular function as diverse as cardiac excitability, synaptic plasticity, and gene transcription. In CA1 pyramidal neurons, CaM regulates two opposing Ca2+-dependent processes that underlie memory formation: long-term potentiation (LTP) and long-term depression (LTD). Induction of LTP and LTD require activation of Ca2+-CaM-dependent enzymes: Ca2+/CaM-dependent kinase II (CaMKII) and calcineurin, respectively. Yet, it remains unclear as to how Ca2+ and CaM produce these two opposing effects, LTP and LTD. CaM binds 4 Ca2+ ions: two in its N-terminal lobe and two in its C-terminal lobe. Experimental studies have shown that the N- and C-terminal lobes of CaM have different binding kinetics toward Ca2+ and its downstream targets. This may suggest that each lobe of CaM differentially responds to Ca2+ signal patterns. Here, we use a novel event-driven particle-based Monte Carlo simulation and statistical point pattern analysis to explore the spatial and temporal dynamics of lobe-specific Ca2+-CaM interaction at the single molecule level. We show that the N-lobe of CaM, but not the C-lobe, exhibits a nano-scale domain of activation that is highly sensitive to the location of Ca2+ channels, and to the microscopic injection rate of Ca2+ ions. We also demonstrate that Ca2+ saturation takes place via two different pathways depending on the Ca2+ injection rate, one dominated by the N-terminal lobe, and the other one by the C-terminal lobe. Taken together, these results suggest that the two lobes of CaM function as distinct Ca2+ sensors that can differentially transduce Ca2+ influx to downstream targets. We discuss a possible role of the N-terminal lobe-specific Ca2+-CaM nano-domain in CaMKII activation required for the induction of synaptic plasticity