An overview of the communications technology satellite project: Executive summary

An overview of the Communications Technology Satellite (CTS) project, a joint venture between NASA and the Canadian Department of Communications is given. A brief technical description of the CTS spacecraft and its cognate hardware and operations, a history of the CTS project, and a list of the CTS experiments and demonstrations conducted during the course of the project are given

Mapping dynamic environments using Markov random field models

This paper focuses on dynamic environments for mobile robots and proposes a new mapping method combining hidden Markov models (HMMs) and Markov random fields (MRFs). Grid cells are used to represent the dynamic environment. The state change of every grid cell is modelled by an HMM with an unknown transition matrix. MRFs are applied to consider the dependence between different transition matrices. The unknown parameters are learnt from not only the corresponding observations but also its neighbours. Given the dependence, parameter maps are smooth. Expectation maximization (EM) is applied to obtain the best parameters from observations. Finally, a simulation is done to evaluate the proposed method

Novel detection and risk assessment of contaminants of emerging concern in a range of aquatic matrices in Ireland

Water pollution is one of the biggest concerns as a potential hazard for the environment and consequently for human health. Contaminants of emerging concern (CECs) are increasingly being shown to occur in water samples across the world, present at ng/L to μg/L concentrations, and their risks require further investigation. The breadth of such compounds is increasing and therefore there is a constant need for reliable analytical methods for identification and their determination in order to detect them due to their presence at low levels. Limited previous studies have explored the spatial occurrence and relative distribution of pharmaceutical residues in the Irish environment and demonstrated their presence, however, Irish studies evaluating more comprehensively these pollutants and matrices are required. In this study a broad range of CECs including pharmaceuticals, pesticides, and personal care products were detected, monitored and risk assessed in the environment from a rural and an urban influenced area in Ireland for surface waters and wastewater samples (both influent and effluent). Quantitative analysis has been carried out for target compounds; this will allow contaminants which are not efficiently removed during treatment to be highlighted and provide critical information for tools to evaluate their potential risks to human health. Occurrence frequency was established and interpreted to inform prioritisation of these compounds. This will support wastewater treatment plants to develop and optimise strategies for the efficient removal of identified CECs and to minimise the potential risk posed by them. Additionally, an international case study has been carried out comparing occurrence in Irish, UK and Spanish rivers. The monitoring data collected is used to demonstrate the application of a decision support system for monitoring these pollutants as a risk assessment tool for Irish water catchments. This research provides comprehensive insight into the occurrence, fate and impact of CECs in Irish waters

A year-long study of the occurrence and risk of over 140 contaminants of emerging concern in wastewater influent, effluent and receiving waters in the Republic of Ireland

Despite being a developed country in the European Union (EU), knowledge of the nature and extent of contamination of water bodies with contaminants of emerging concern (CECs) in Ireland is limited. In this study, >140 CECs including pharmaceuticals, pesticides and personal care products were monitored in monthly samples of wastewater treatment plant (WWTP) influent, effluent and receiving surface waters at both an urban and a rural location (72 samples in total) in Ireland over a 12-month period in 2018-2019. In total, 58 CECs were detected, including several EU Water Framework Directive Watch List compounds. Of all classes, the highest concentrations were measured for pharmaceuticals across all media, i.e., propranolol in surface waters (134 ng·L-1), hydrochlorothiazide in effluent (1067 ng·L-1) and venlafaxine in influent wastewater (8273 ng·L-1). Overall, high wastewater treatment removal was observed and a further reduction in CEC occurrence and concentration was measured via dilution in the receiving river environment. Lastly, an environmental risk assessment (ERA) was performed using risk quotients (RQ), which revealed that in surface waters, total RQ for all CECs was an order of magnitude lower than in effluents. The majority of CECs in surface waters posed a lower risk except E2 and EE2 which presented a medium risk (RQs of 3.5 and 1.1, respectively) in the rural area. This work represents the most comprehensive CEC monitoring dataset to date for Ireland which allowed for an ERA prioritisation to be performed for the first time

A One-Health environmental risk assessment of contaminants of emerging concern in London’s waterways throughout the SARS-CoV-2 pandemic

The SARS-CoV-2 pandemic had huge impacts on global urban populations, activity and health, yet little is known about attendant consequences for urban river ecosystems. We detected significant changes in occurrence and risks from contaminants of emerging concern (CECs) in waterways across Greater London (UK) during the pandemic. We were able to rapidly identify and monitor large numbers of CECs in n=390 samples across 2019–2021 using novel direct-injection liquid chromatography-mass spectrometry methods for scalable targeted analysis, suspect screening and prioritisation of CEC risks. At total of 10,029 measured environmental concentrations (MECs) were obtained for 66 unique CECs. Pharmaceutical MECs decreased during lockdown in 2020 in the R. Thames (p≤0.001), but then increased significantly in 2021 (p ≤0.01). For the tributary rivers, the R. Lee, Beverley Brook, R. Wandle and R. Hogsmill were the most impacted primarily via wastewater treatment plant effluent and combined sewer overflows. For the R. Hosgmill in particular, pharmaceutical MEC trends were generally correlated with NHS prescription statistics, likely reflecting limited wastewater dilution. Suspect screening of ∼1,200 compounds tentatively identified 25 additional CECs at the five impacted sites, including metabolites such as O-desmethylvenlafaxine, an EU Watch List compound. Lastly, risk quotients (RQs) ≥0.1 were calculated for 21 compounds across the whole Greater London freshwater catchment, of which 7 were of medium risk (RQ ≥1.0) and three were in the high-risk category (RQ ≥10), including imidacloprid (RQ=19.6), azithromycin (15.7) and diclofenac (10.5). This is the largest spatiotemporal dataset of its kind for any major capital city globally and the first for Greater London, representing ∼16 % of the population of England, and delivering a foundational One Health case study in the third largest city in Europe across a global pandemic

Psychometric evaluation of the Questionnaire about the Process of Recovery (QPR)

Background: Supporting recovery is the aim of national mental health policy in many countries, including England. There is a need for standardised measures of recovery, to assess policy implementation and inform clinical practice. Only one measure of recovery has been developed in England: the Questionnaire about the Process of Recovery (QPR) which measures recovery from the perspective of adult mental health service users with a psychosis diagnosis. Aims: To independently evaluate the psychometric properties of the 15-item and 22-item versions of QPR. Method: Two samples were used: Dataset 1 (n=88) involved assessment of QPR at baseline, two weeks and three months. Dataset 2 (n=399; ISRCTN02507940) involved assessment of QPR at baseline and one year. Results: For the 15-item version, internal consistency was 0.89, convergent validity was 0.73, test-retest reliability was 0.74 and sensitivity to change was 0.40. Confirmatory factor analysis showed the 15-item version offered a good fit. For the 22 item version comprising two sub-scales, the Interpersonal sub-scale was found to under-perform and the Intrapersonal sub-scale overlaps substantially with the 15 item version. Conclusions: Both the 15-item and the Intrapersonal sub-scale of the 22-item versions of the QPR demonstrated satisfactory psychometric properties. The 15-item version is slightly more robust and also less burdensome, so it can be recommended for use in research and clinical practice. Declaration of interest: None

Incremental embodied chaotic exploration of self-organized motor behaviors with proprioceptor adaptation

This paper presents a general and fully dynamic embodied artificial neural system, which incrementally explores and learns motor behaviors through an integrated combination of chaotic search and reflex learning. The former uses adaptive bifurcation to exploit the intrinsic chaotic dynamics arising from neuro-body-environment interactions, while the latter is based around proprioceptor adaptation. The overall iterative search process formed from this combination is shown to have a close relationship to evolutionary methods. The architecture developed here allows realtime goal-directed exploration and learning of the possible motor patterns (e.g., for locomotion) of embodied systems of arbitrary morphology. Examples of its successful application to a simple biomechanical model, a simulated swimming robot, and a simulated quadruped robot are given. The tractability of the biomechanical systems allows detailed analysis of the overall dynamics of the search process. This analysis sheds light on the strong parallels with evolutionary search

Nonlinear analysis of EEG signals at different mental states

BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat