Characterisation of the first authenticated organomercury hydroxide, 4-Me₂NC₆H₄HgOH

4-Me₂NC₆H₄HgOH was prepared from 4-Me₂NC₆H₄HgOAc. Full characterisation showed that it crystallises as discrete molecules, the first example of a true organomercury hydroxide in the solid state. The structures of 4-Me₂NC₆H₄HgOAc and (4-Me₂NC₆H₄)₂Hg are also discussed. 4-Me₂NC₆H₄HgOH has been characterised spectroscopically and crystallographically as a true organomercury hydroxide

No ordinary field trip: a conversation with John Lewis

Eighth grade students from Bank Street School for Children meet Congressman John Lewis in Washington D. C.https://educate.bankstreet.edu/progressive/1003/thumbnail.jp

Programming deliberation strategies in meta-APL

A key advantage of BDI-based agent programming is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages provide flexible support for expressing plans, they are typically limited to a single, hard-coded, deliberation strategy (perhaps with some parameterisation) for all task environments. In this paper, we present an alternative approach. We show how both agent programs and the agent’s deliberation strategy can be encoded in the agent programming language meta-APL. Key steps in the execution cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing BDI deliberation strategies to be programmed with ease. To illustrate the flexibility of meta-APL, we show how three typical BDI deliberation strategies can be programmed using meta-APL rules. We then show how meta-APL can used to program a novel adaptive deliberation strategy that avoids interference between intentions

Chem# - Semantically Enriched Linked Open Chemical Data

The problem: Vast quantities of chemical data (e.g. crystal structures, NMR spectra, experimental reports) are generated every day. The majority of this data is never published, and the data that is published is fragmented,trapped in legacy formats and difficult to discover. The solution: Semantically Enriched Linked Open Chemical Data: browsable, searchable, discoverable and interpretable by humans and machines alike, using standardized extensible data formats (Chemical Markup Language) and technologies (HTTP, RDF).Funded by JISC

Deindividuation of Drivers: Is Everyone Else a Bad Driver?

Deindividuation is a psychological phenomenon that occurs when a given environment reduces the individuality or identifiability of a person. These environments may cause a psychological reduction in self-consciousness, potentially leading to violations of sociocultural norms (Festinger, Pepitone, & Newcomb, 1952; Singer, Brush, & Lublin, 1965). The present research sought to empirically test deindividuation theory among automobile drivers utilizing the anonymizing factor of observation. Participants (N = 31) used a driving simulator and were either in the observed condition or an unobserved condition. Analysis of driving data did not reveal significant results, however self-report data had some interesting trends. Though limited in scope, this research begins to shed light on deindividuation of drivers and may provide a foundation for future research

Challenges in operation of the Abuja water distribution system: headquarters and area office perspectives

Often effective management of a water resource will involve cooperation and understanding between concerned stakeholders. An inquiry into the challenges in operation of the current water distribution system at the Headquarters and Areas Office of the Federal Capital Territory Water Board (FCTWB) showed that reluctance to share information (where present) to maintain a level of control on was routine and often lead to differing views between them on various subjects including non-revenue water and cooperation with the city development agency. It also revealed the need for integration of the operational staff of the area offices in the affairs and decisions of the headquarters in order to ensure practicality of programmes during the planning phase and promote cooperation and initiative in implementation

Operation of adoptive green building assessment tools-case study

Purpose– The rising interest in the use of green building assessment tools (GBATs) as means of promoting sustainable construction has heightened the adoption of some well-established tools for use in other contexts. The role of the adoptive tools in minimising the hassle of developing GBATs in countries that are not able to develop their own cannot be overemphasised. However, more recently, the literature has emerged that offers contradictory findings about the contribution of these adoptive tools in addressing sustainability in the new contexts. However, the research to date has tended to focus on improving the performance rather than the way they are operated. Design/methodology/approach–This paper examines the operating criteria of the Green Star (GS) tool in its original and adoptive countries (Australia and South Africa (SA) respectively to identify any implications caused in the South Africa context. The focus however, is on the facilitation, accreditation and implementation cost criteria based on the online resources. Findings–One of the key findings in this synopsis is that, the GS-SA operating criteria tend to marginalise building projects and practitioners in the informal sector particularly with regard to the accreditation system employed. Originality/value –Besides the recommendations on how to address the issues, the study provides a conceptual framework on which future empirical studies on improving the operating criteria by the GBCSA and its next generation tools, such as the GBC Ghana, could be based

The impact of COVID-19 fiscal spending on climate change adaptation and resilience

Government expenditure and taxation have a significant influence on the long-term adaptation and resilience of societies to climate and other environmental shocks. Unprecedented fiscal spending in the COVID-19 recovery offered an opportunity to systematically enhance adaptation and resilience to future shocks. But did the ‘build back better’ rhetoric manifest in more resilient policy? We develop a dedicated fiscal policy taxonomy for climate change adaptation and resilience (A&R)—the Climate Resilience and Adaptation Financing Taxonomy (CRAFT)—and apply this to analyse ~8,000 government policies across 88 countries. We find that US$279–334 billion (9.7–11.1%) of economic recovery spending potentially had direct A&R benefits. This positive spending is substantial in absolute terms but falls well below adaptation needs. Moreover, a notable portion (27.6–28%) of recovery spending may have had negative impacts on A&R, acting to lock in non-resilient infrastructure. We add a deep learning algorithm to consider A&R themes in associated COVID-19 policy documents. Compared with climate mitigation, A&R received only one-third of the spending and was mentioned only one-seventh as frequently in policy documents. These results suggest that the COVID-19 fiscal response missed many opportunities to advance climate A&R. We draw conclusions for how to better align fiscal policy with A&R

SOS: Selective Objective Switch for Rapid Immunofluorescence Whole Slide Image Classification

The difficulty of processing gigapixel whole slide images (WSIs) in clinical microscopy has been a long-standing barrier to implementing computer aided diagnostic systems. Since modern computing resources are unable to perform computations at this extremely large scale, current state of the art methods utilize patch-based processing to preserve the resolution of WSIs. However, these methods are often resource intensive and make significant compromises on processing time. In this paper, we demonstrate that conventional patch-based processing is redundant for certain WSI classification tasks where high resolution is only required in a minority of cases. This reflects what is observed in clinical practice; where a pathologist may screen slides using a low power objective and only switch to a high power in cases where they are uncertain about their findings. To eliminate these redundancies, we propose a method for the selective use of high resolution processing based on the confidence of predictions on downscaled WSIs --- we call this the Selective Objective Switch (SOS). Our method is validated on a novel dataset of 684 Liver-Kidney-Stomach immunofluorescence WSIs routinely used in the investigation of autoimmune liver disease. By limiting high resolution processing to cases which cannot be classified confidently at low resolution, we maintain the accuracy of patch-level analysis whilst reducing the inference time by a factor of 7.74.Comment: Accepted for publication at CVPR202