Understanding values associated with stormwater remediation options in marine coastal ecosystems: A case study from Auckland, New Zealand

This paper describes the design and implementation of a choice experiment to understand Aucklanders’ preferences for environmental qualities associated with the effects of urban run-off on marine coastal environments. Auckland’s coastal environments are affected by a range of ecological and human factors. While much research has been undertaken in the area of ecology, little is understood of human preferences for coastal environments and their management. An unlabelled choice experiment was developed with three environmental quality attributes specified at three broad coastal categories. The environmental qualities are ecological health, water clarity, and underfoot conditions. Willingness to pay estimates for these attributes indicates that respondents show a strong preference for improved environmental quality at outer coastal beach locations over middle and upper harbour locations. Water quality leads ecological health, then underfoot conditions in importance at beach locations. An application is discussed in which a hypothetical project consisting of policy and engineering components delivers changes in water quality and underfoot conditions in the Auckland upper harbour areas. A 95% confidence estimate of the money value of that change ranges from $783 m. to$ 1,122 b. The key outcome is demonstration of the choice experiment as a statistically robust and flexible approach to making sense of Aucklanders’ complex preferences for coastal ecosystem management.Environmental Economics and Policy, Research Methods/ Statistical Methods,

COVID-19 vaccine effectiveness against symptomatic SARS-CoV-2 infection and severe COVID-19 outcomes from Delta AY.4.2:Cohort and test-negative study of 5.4 million individuals in Scotland

Background: In July 2021, a new variant of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) in the Delta lineage was detected in the United Kingdom (UK), named AY.4.2 or "Delta plus". By October 2021, the AY.4.2 variant accounted for approximately 10-11% of cases in the UK. AY.4.2 was designated as a variant under investigation by the UK Health and Security Agency on 20 October 2021. This study aimed to investigate vaccine effectiveness (VE) against symptomatic COVID-19 (Coronavirus disease 2019) infection and COVID-19 hospitalisation/death for the AY.4.2 variant. Methods: We used the Scotland-wide Early Pandemic Evaluation and Enhanced Surveillance (EAVE-II) platform to estimate the VE of the ChAdOx1, BNT162b2, and mRNA-1273 vaccines against symptomatic infection and severe COVID-19 outcomes in adults. The study was conducted from June 8 to October 25, 2021. We used a test-negative design (TND) to estimate VE against reverse transcriptase polymerase chain reaction (RT-PCR) confirmed symptomatic SARS-CoV-2 infection while adjusting for sex, socioeconomic status, number of coexisting conditions, and splines in time and age. We also performed a cohort study using a Cox proportional hazards model to estimate VE against a composite outcome of COVID-19 hospital admission or death, with the same adjustments. Results: We found an overall VE against symptomatic SARS-CoV-2 infection due to AY.4.2 of 73% (95% confidence interval (CI) = 62-81) for >14 days post-second vaccine dose. Good protection against AY.4.2 symptomatic infection was observed for BNT162b2, ChAdOx1, and mRNA-1273. In unvaccinated individuals, the hazard ratio (HR) for COVID-19 hospital admission or death from AY.4.2 among community detected cases was 1.77 (95% CI = 1.02-3.07) relative to unvaccinated individuals who were infected with Delta, after adjusting for multiple potential confounders. VE against AY.4.2 COVID-19 admissions or deaths was 87% (95% CI = 74-93) >28 days post-second vaccination relative to unvaccinated. Conclusions: We found that AY.4.2 was associated with an increased risk of COVID-19 hospitalisations or deaths in unvaccinated individuals compared with Delta and that vaccination provided substantial protection against symptomatic SARS-CoV-2 and severe COVID-19 outcomes following Delta AY.4.2 infection. High levels of vaccine uptake and protection offered by existing vaccines, as well as the rapid emergence of the Omicron variant may have contributed to the AY.4.2 variant never progressing to a variant of concern

Repetitive Transcranial Magnetic Stimulation (rTMS) for depression : outcomes in a United Kingdom (UK) clinical practice

Objective: The aim of this paper is to present the outcomes data from the largest United Kingdom’s (UK) National Health Service (NHS) clinical rTMS service treating treatment resistant depression (TRD). Methods: The study was a retrospective investigation of routinely collected data on patients receiving rTMS between 2015 and 2017. Measures used were the clinician-rated Clinical Global Impression (CGI) and Hamilton Depression Rating Scale (HAM-D), and patient rated Beck Depression Inventory (BDI). The outcome data of 73 patients with TRD was analysed. The sample included patients with co-morbid psychiatric diagnosis. Results: Response and remission rates respectively were 40.4% and 25.5% for the HAM-D; 35.6% and 20.8% for the BDI; and 51.1% and 52.1% for the CGI. Effect sizes were medium (.54, .52 and .56 respectively). Conclusions: The results show that a UK based clinical service achieves similar results to those published internationally and that clinical rTMS can have significant impact on symptoms of depression in many patients with TRD. Health services are under pressure to make financial savings, investment in rTMS could reduce the long term treatment costs associated with TRD

Repetitive Transcranial Magnetic Stimulation (rTMS) in Treatment Resistant Depression : Retrospective Data Analysis from Clinical Practice

Objective: The aim of this paper is to present the service data results from a clinical repetitive Transcranial Magnetic Stimulation (rTMS) service treating treatment resistant depression (TRD). Methods The study was a retrospective investigation of routinely collected data on patients receiving rTMS between 2015 and 2018. Measures used were the clinician-rated Clinical Global Impression (CGI) and Hamilton Depression Rating Scale (HAM-D), and patient rated Physical Health Questionnaire (PHQ-9) and Generalised Anxiety Disorder 7 (GAD-7). The outcome data of 144 patients with TRD was analysed. The sample included patients with co-morbid psychiatric diagnosis. Results Response and remission rates respectively were 34.6% and 20.6% for the HAM-D; 10% and 28.6% for the PHQ-9; 31% and 31.8% for the CGI; and 24.6% and 28.8% for GAD-7. Effect sizes were mostly medium (0.48, 0.27, 0.51, 0.43 respectively). GAD-7 reliable change improvement was 56.1% and PHQ-9 reliable change improvement was 40%. There was a medium positive correlation between anxiety (GAD-7) and depression recovery (HAM-D), r = .31, n = 46, p = .039, with lower pre-treatment anxiety associated with lower post-treatment HAM-D scores. Conclusions TRD patients with low pre-treatment anxiety levels respond to treatment better than those with high pre-treatment anxiety. The results show that a clinical rTMS service can have a significant impact on symptoms of depression and anxiety in TRD. The findings support wider availability of rTMS as a treatment option for people with TRD

Patients’, Carers’, and the Public’s Perspectives on Electroconvulsive Therapy

Aims and Method: The aim of this study was to present patients’, carers’, and the public’s perspectives on electroconvulsive therapy (ECT) through a narrative review of the literature.Results: People’s perspectives on ECT are often negative due to media and Internet portrayal. Perspectives are influenced by risks, short-term side effects, and the most commonly reported longer-term side effect: memory loss. However, many patients do not report memory loss. Most people who experience ECT and their carers report a positive perspective. In the future, people’s perspectives may become more positive with higher service delivery standards and a more balanced, well-informed view of modern ECT presented by the media. However, ECT has risks and side effects, and negative and critical perspectives on the use and effects of ECT will persist.Clinical Implications: Perspectives on ECT are important because of the impact on stigma, patient treatment choice, patient consent, and provision of and referral for ECT

Open Design & Citizen-Centered Innovation at Tate Exchange 2019

A case study report about the EU Open Design and Manufacturing (OD&M) project at Tate Exchange, in association with the University of the Arts London (UAL) Digital Maker Collective (DMC) and Beta Society. Co-funded by the Erasmus+ Programme of the European Union. Since September 2018 the Digital Maker Collective (DMC), a group of University of the Arts London (UAL) staff, students, alumni, have been developing a project titled ‘Beta Society’. The project aimed to establish an open and collaborative community to raise awareness and support greater diversity and equality of opportunity in technology, education and the arts. Beta Society is a collaboration between the DMC and community/industry partners (see below) that supports projects exploring the impacts of technology on society. Working across public, private and industry sectors, it champions diversity and equality of opportunity in the technology industries, education and the arts. This case study highlights the contribution of the Open Design and Manufacturing Project to the development of Beta Society and the launch event at the Tate Exchange (5-10 March 2019). Beta Society has been developed in collaboration with the project partners

Simulation Theorems via Pseudorandom Properties

We generalize the deterministic simulation theorem of Raz and McKenzie [RM99], to any gadget which satisfies certain hitting property. We prove that inner-product and gap-Hamming satisfy this property, and as a corollary we obtain deterministic simulation theorem for these gadgets, where the gadget's input-size is logarithmic in the input-size of the outer function. This answers an open question posed by G\"{o}\"{o}s, Pitassi and Watson [GPW15]. Our result also implies the previous results for the Indexing gadget, with better parameters than was previously known. A preliminary version of the results obtained in this work appeared in [CKL+17]

Magnetic field generation in finite beam plasma system

For finite systems boundaries can introduce remarkable novel features. A well known example is the Casimir effect [1, 2] that is observed in quantum electrodynamic systems. In classical systems too novel effects associated with finite boundaries have been observed, for example the surface plasmon mode [3] that appears when the plasma has a finite extension. In this work a novel instability associated with the finite transverse size of a beam owing through a plasma system has been shown to exist. This instability leads to distinct characteristic features of the associated magnetic field that gets generated. For example, in contrast to the well known unstable Weibel mode of a beam plasma system which generates magnetic field at the skin depth scale, this instability generates magnetic field at the scales length of the transverse beam dimension [4]. The existence of this new instability is demonstrated by analytical arguments and by simulations conducted with the help of a variety of Particle - In - Cell (PIC) codes (e.g. OSIRIS, EPOCH, PICPSI). Two fluid simulations have also been conducted which confirm the observations. Furthermore, laboratory experiments on laser plasma system also provides evidence of such an instability mechanism at work

Performance Limits of Stochastic Sub-Gradient Learning, Part II: Multi-Agent Case

The analysis in Part I revealed interesting properties for subgradient learning algorithms in the context of stochastic optimization when gradient noise is present. These algorithms are used when the risk functions are non-smooth and involve non-differentiable components. They have been long recognized as being slow converging methods. However, it was revealed in Part I that the rate of convergence becomes linear for stochastic optimization problems, with the error iterate converging at an exponential rate $\alpha^i$ to within an $O(\mu)-$neighborhood of the optimizer, for some $\alpha \in (0,1)$ and small step-size $\mu$. The conclusion was established under weaker assumptions than the prior literature and, moreover, several important problems (such as LASSO, SVM, and Total Variation) were shown to satisfy these weaker assumptions automatically (but not the previously used conditions from the literature). These results revealed that sub-gradient learning methods have more favorable behavior than originally thought when used to enable continuous adaptation and learning. The results of Part I were exclusive to single-agent adaptation. The purpose of the current Part II is to examine the implications of these discoveries when a collection of networked agents employs subgradient learning as their cooperative mechanism. The analysis will show that, despite the coupled dynamics that arises in a networked scenario, the agents are still able to attain linear convergence in the stochastic case; they are also able to reach agreement within $O(\mu)$ of the optimizer