White certificates and white certificate trading schemes as greenhouse gas mitigation policy options for South Africa

A white certificate, which is also referred to as an Energy Saving Certificate (ESC), or an Energy Efficiency Credit (EEC), is an instrument awarded by an authorisation body to guarantee that a specific amount of energy savings has been achieved. Each certificate is a unique and traceable commodity carrying a property right over a certain amount of additional energy savings and certifying that the benefit of these savings has not been accounted for elsewhere (EuroWhiteCert Project, 2006)

Emissions trading as a policy option for greenhouse gas mitigation in South Africa

An emissions trading scheme (ETS) is based on the allocation of allowances to emit pollutants, which in the case of climate change are greenhouse gases. Allowances are allocated to a defined set of emitters, who are required to hold sufficient allowances to cover their emissions at the end of a compliance period, or face penalties. Scarcity is created in the scheme through the allocation of fewer allowances than emissions, resulting in emitters having to choose between reducing their emissions in line with their allowance allocations, or purchasing additional allowances to cover their excess emissions levels

Sequencing a Shrimp Diversity Panel

Eighty-six shrimp (eighty Pacific White, six Tiger shrimp) from ten different geographic regions were sequenced with a twofold goal: first, to better understand and document the genetic makeup of the species, and second, to discover genetic differences between shrimp lines that may facilitate the breeding of shrimp with better performance trait

A Small-scale Procedure for Acid-catalyzed Ketal Formation

A modified procedure for dehydrative ketal protections is disclosed, which serves as an alternative to the classic Dean–Stark protocol. Studies show that this new procedure can outperform the Dean–Stark apparatus on small scales and thus serves as a complementary approach to effect dehydrative ketalizations. A detailed procedure for this apparatus is presented

Geometric instability of graph neural networks on large graphs

We analyse the geometric instability of embeddings produced by graph neural networks (GNNs). Existing methods are only applicable for small graphs and lack context in the graph domain. We propose a simple, efficient and graph-native Graph Gram Index (GGI) to measure such instability which is invariant to permutation, orthogonal transformation, translation and order of evaluation. This allows us to study the varying instability behaviour of GNN embeddings on large graphs for both node classification and link prediction

Using the COVID-19 to influenza ratio to estimate early pandemic spread in Wuhan, China and Seattle, US

Background: Pandemic SARS-CoV-2 was first reported in Wuhan, China on December 31, 2019. Twenty-one days later, the US identified its first case a man who had traveled from Wuhan to the state of Washington. Recent studies in the Wuhan and Seattle metropolitan areas retrospectively tested samples taken from patients with COVID-like symptoms. In the Wuhan study, there were 4 SARS-CoV-2 positives and 7 influenza positives out of 26 adults outpatients who sought care for influenza-like-illness at two central hospitals prior to January 12, 2020. The Seattle study reported 25 SARS-CoV-2 positives and 442 influenza positives out of 2353 children and adults who reported acute respiratory illness prior to March 9, 2020. Here, we use these findings to extrapolate the early prevalence of symptomatic COVID-19 in Wuhan and Seattle. Methods: For each city, we estimate the ratio of COVID-19 to influenza infections from the retrospective testing data and estimate the age-specific prevalence of influenza from surveillance reports during the same time period. Combining these, we approximate the total number of symptomatic COVID-19 infections. Findings: In Wuhan, there were an estimated 1386 [95% CrI: 420 3793] symptomatic cases over 30 of COVID- 19 between December 30, 2019 and January 12, 2020. In Seattle, we estimate that 2268 [95% CrI: 498, 6069] children under 18 and 4367 [95% CrI: 2776, 6526] adults were symptomatically infected between February 24 and March 9, 2020. We also find that the initial pandemic wave in Wuhan likely originated with a single infected case who developed symptoms sometime between October 26 and December 13, 2019; in Seattle, the seeding likely occurred between December 25, 2019 and January 15, 2020. Interpretation: The spread of COVID-19 in Wuhan and Seattle was far more extensive than initially reported. The virus likely spread for months in Wuhan before the lockdown. Given that COVID-19 appears to be overwhelmingly mild in children, our high estimate for symptomatic pediatric cases in Seattle suggests that there may have been thousands more mild cases at the time.We acknowledge support from NIH grant U01 GM087791 and Tito’s Handmade VodkaIntegrative Biolog

Diagnosis-based and external cause-based criteria to identify adverse drug reactions in hospital ICD-coded data: application to an Australia population-based study

Objectives: External cause International Classification of Diseases (ICD) codes are commonly used to ascertain adverse drug reactions (ADRs) related to hospitalisation. We quantified ascertainment of ADR-related hospitalisation using external cause codes and additional ICD-based hospital diagnosis codes. Methods: We reviewed the scientific literature to identify different ICD-based criteria for ADR-related hospitalisations, developed algorithms to capture ADRs based on candidate hospital ICD-10 diagnoses and external cause codes (Y40–Y59), and incorporated previously published causality ratings estimating the probability that a specific diagnosis was ADR related. We applied the algorithms to the NSW Admitted Patient Data Collection records of 45 and Up Study participants (2011–2013). Results: Of 493 442 hospitalisations among 267 153 study participants during 2011–2013, 18.8% (n = 92 953) had hospital diagnosis codes that were potentially ADR related; 1.1% (n = 5305) had high/very high–probability ADR-related diagnosis codes (causality ratings: A1 and A2); and 2.0% (n = 10 039) had ADR-related external cause codes. Overall, 2.2% (n = 11 082) of cases were classified as including an ADR-based hospitalisation on either external cause codes or high/very high–probability ADR-related diagnosis codes. Hence, adding high/very high–probability ADR-related hospitalisation codes to standard external cause codes alone (Y40–Y59) increased the number of hospitalisations classified as having an ADR-related diagnosis by 10.4%. Only 6.7% of cases with high-probability ADR-related mental symptoms were captured by external cause codes. Conclusion: Selective use of high-probability ADR-related hospital diagnosis codes in addition to external cause codes yielded a modest increase in hospitalised ADR incidence, which is of potential clinical significance. Clinically validated combinations of diagnosis codes could potentially further enhance capture