Chemical simulation of greywater

Sustainable water resources management attracts considerable attention in today’s world. Recycling and reuse of both wastewater and greywater are becoming more attractive. The strategy is to protect ecosystem services by balancing the withdrawal of water and the disposal of wastewater. In the present study, a timely and novel synthetic greywater composition has been proposed with respect of the composition of heavy metals, nutrients and organic matter. The change in water quality of the synthetic greywater due to increasing storage time was monitored to evaluate the stability of the proposed chemical formula. The new greywater is prepared artificially using analytical grade chemicals to simulate either low (LC) or high (HC) pollutant concentrations. The characteristics of the synthetic greywater were tested (just before starting the experiment, after two days and a week of storage under real weather conditions) and compared to those reported for real greywater. Test results for both synthetic greywater types showed great similarities with the physiochemical properties of published findings concerning real greywater. Furthermore, the synthetic greywater is relatively stable in terms of its characteristics for different storage periods. However, there was a significant (p<0.05) reduction in 5-day biochemical oxygen demand (BOD5) for both low (LC) and high (HC) concentrations of greywater after two days of storage with reductions of 62% and 55%, respectively. A significant (p<0.05) change was also noted for the reduction (70%) of nitrate‒nitrogen (NO3‒N) concerning HC greywater after seven days of storage

Greywater recycling: Treatment options and applications

Wastewater is an immense resource that could find significant applications in regions of water scarcity. Greywater has particular advantages in that it is a large source with a low organic content. Through critical analysis of data from existing greywater recycling applications, this paper presents a review of existing technologies and applications by collating a disparate information base and comparing/contrasting the strengths and weaknesses of different approaches. Simple technologies and sand filters have been shown to have a limited effect on greywater; membranes are reported to provide good solids removal but cannot efficiently tackle the organic fraction. Alternatively, biological and extensive schemes achieve a good general treatment of greywater with particularly effective removal of organics. The best overall performances were observed within schemes that combine different types of methods to ensure effective treatment of all the fractions

Software requirements validation via task analysis

As a baseline for software development, a correct and complete requirements definition is one foundation of software quality.Previously, a novel approach to static testing of software requirements was proposed in which requirements definitions are tested on a set of task scenarios by examining software behaviour in each scenario described by an activity list. Such descriptions of software behaviour can be generated automatically from requirements models. This paper investigates various testing methods for selectingtest scenarios. Data flow, state transition and entity testing methods are studied. A variety of test adequacy criteria and their combinations are formally defined and the subsume relations between the criteria are proved. Empirical studies of the testing methods and the construction of a prototype testing tool are reported

Paramedic utility in screening patients who present to Emergency Medical Services and who may benefit from an Advance Care Plan: A mixed methods study with explanatory sequential design

We used a two phased mixed methods study with an explanatory sequential design to understand how frequently paramedics attend patients who, on paramedic assessment with the Gold Standards Framework Proactive Identification Guidance, are end-of-life and have advance care planning. We subsequently explored paramedic views on paramedic screening of patients to assess if they are end-of-life and onward referral to their General Practitioner for advance care planning.Paramedics screened and recorded 14.9% of patients as end-of-life and 44.3% of these patients were assessed to have no advance care plan in place. Where paramedics screened patients and they did have an advance care plan in place, 36.8% had only a Do Not Attempt Cardiopulmonary Resuscitation. Paramedics found using the Gold Standards Framework Proactive Identification Guidance to screen patients for end-of-life status useful and straightforward and considered themselves well placed to complete this task. Future research is required to address the practicalities of implementing a paramedic screening and referral tool for end of life care that results in the intended outcome of supporting effective advance care planning

A Televised, Web-Based Randomised Trial of an Herbal Remedy (Valerian) for Insomnia

BACKGROUND: This trial was conducted as part of a project that aims to enhance public understanding and use of research in decisions about healthcare by enabling viewers to participate in research and to follow the process, through television reports and on the web. Valerian is an herbal over-the-counter drug that is widely used for insomnia. Systematic reviews have found inconsistent and inconclusive results about its effects. METHODS: Participants were recruited through a weekly nationally televised health program in Norway. Enrolment and data collection were over the Internet. 405 participants who were 18 to 75 years old and had insomnia completed a two week diary-keeping run-in period without treatment and were randomised and mailed valerian or placebo tablets for two weeks. All participants and investigators were blind to treatment until after the analysis was completed. FINDINGS: For the primary outcome of a minimally important improvement in self-reported sleep quality (> or = 0.5 units on a 7 point scale), the difference between the valerian group (29%) and the placebo group (21%) was not statistically significant (difference 7.5%; 95% CI-0.9 to 15.9; p = 0.08). On the global self-assessment question at the end of the treatment period 5.5% (95% CI 0.2 to 10.8) more participants in the valerian group perceived their sleep as better or much better (p = 0.04). There were similar trends favouring the valerian group for night awakenings (difference = 6.0%, 95% CI-0.5 to 12.5) and sleep duration (difference = 7.5%, 95% CI-1.0 to 16.1). There were no serious adverse events and no important or statistically significant differences in minor adverse events. INTERPRETATION: Based on this and previous studies, valerian appears to be safe, but with modest beneficial effects at most on insomnia compared to placebo. The combined use of television and the Internet in randomised trials offers opportunities to answer questions about the effects of health care interventions and to improve public understanding and use of randomised trials. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN72748991

Scenario-based requirements elicitation for user-centric explainable AI

Explainable Artificial Intelligence (XAI) develops technical explanation methods and enable interpretability for human stakeholders on why Artificial Intelligence (AI) and machine learning (ML) models provide certain predictions. However, the trust of those stakeholders into AI models and explanations is still an issue, especially domain experts, who are knowledgeable about their domain but not AI inner workings. Social and user-centric XAI research states it is essential to understand the stakeholder’s requirements to provide explanations tailored to their needs, and enhance their trust in working with AI models. Scenario-based design and requirements elicitation can help bridge the gap between social and operational aspects of a stakeholder early before the adoption of information systems and identify its real problem and practices generating user requirements. Nevertheless, it is still rarely explored the adoption of scenarios in XAI, especially in the domain of fraud detection to supporting experts who are about to work with AI models. We demonstrate the usage of scenario-based requirements elicitation for XAI in a fraud detection context, and develop scenarios derived with experts in banking fraud. We discuss how those scenarios can be adopted to identify user or expert requirements for appropriate explanations in his daily operations and to make decisions on reviewing fraudulent cases in banking. The generalizability of the scenarios for further adoption is validated through a systematic literature review in domains of XAI and visual analytics for fraud detection