The heterogeneous impact of population mobility on the influent characteristics of wastewater treatment facilities.

Improving the resilience of wastewater treatment facilities (WWTFs) has never been more important with rising risks of disasters under climate change. Beyond physical damages, non-physical shocks induced by disasters warrant attention. Human mobility is a vital mediator in transferring the stresses from extreme events into tangible challenges for urban sewage systems by reshaping influent characteristics. However, the impact path remains inadequately explored. Leveraging the stay-at-home orders during the COVID-19 pandemic as a natural experiment, this study aims to quantify and interpret the heterogeneous impacts of mobility reduction on the influent characteristics of WWTFs with different socio-economic, infrastructural, and climatic conditions. To achieve this goal, we developed a research framework integrating causal inference and interpretable machine learning techniques. Based on the empirical data from China, we find that 79.1% of the studied WWTFs, typically located in cities with well-developed drainage infrastructures and low per capita water usage, exhibited resilience against drastic mobility reduction. In contrast, 20.9% of the studied WWTFs displayed significant variations in influent characteristics. Large-capacity WWTFs in subtropical regions encountered challenges with low-load operations, and small-capacity facilities in suburban areas grappled with nutrient imbalances. This study provides valuable insights to equip WWTFs in anticipating and adapting potential variations in influent characteristics triggered by mobility reduction.

Cortical signatures of auditory looming bias show cue-specific adaptation between newborns and young adults.

Adaptive biases in favor of approaching, or "looming", sounds have been found across ages and species, thereby implicating the potential of their evolutionary origin and universal basis. The human auditory system is well-developed at birth, yet spatial hearing abilities further develop with age. To disentangle the speculated inborn, evolutionary component of the auditory looming bias from its learned counterpart, we collected high-density electroencephalographic data across human adults and newborns. As distance-motion cues we manipulated either the sound's intensity or spectral shape, which is pinna-induced and thus prenatally inaccessible. Through cortical source localisation we demonstrated the emergence of the bias in both age groups at the level of Heschl's gyrus. Adults exhibited the bias in both attentive and inattentive states; yet differences in amplitude and latency appeared based on attention and cue type. Contrary to the adults, in newborns the bias was elicited only through manipulations of intensity and not spectral cues. We conclude that the looming bias comprises innate components while flexibly incorporating the spatial cues acquired through lifelong exposure.

Multifaceted consequences of visual distraction during natural behaviour.

Visual distraction is a ubiquitous aspect of everyday life. Studying the consequences of distraction during temporally extended tasks, however, is not tractable with traditional methods. Here we developed a virtual reality approach that segments complex behaviour into cognitive subcomponents, including encoding, visual search, working memory usage, and decision-making. Participants copied a model display by selecting objects from a resource pool and placing them into a workspace. By manipulating the distractibility of objects in the resource pool, we discovered interfering effects of distraction across the different cognitive subcomponents. We successfully traced the consequences of distraction all the way from overall task performance to the decision-making processes that gate memory usage. Distraction slowed down behaviour and increased costly body movements. Critically, distraction increased encoding demands, slowed visual search, and decreased reliance on working memory. Our findings illustrate that the effects of visual distraction during natural behaviour can be rather focal but nevertheless have cascading consequences.

Loneliness corresponds with neural representations and language use that deviate from shared cultural perceptions.

The word zeitgeist refers to common perceptions shared in a given culture. Meanwhile, a defining feature of loneliness is feeling that one's views are not shared with others. Does loneliness correspond with deviating from the zeitgeist? Across two independent brain imaging datasets, lonely participants' neural representations of well-known celebrities strayed from group-consensus neural representations in the medial prefrontal cortex-a region that encodes and retrieves social knowledge (Studies 1 A/1B: N = 40 each). Because communication fosters social connection by creating shared reality, we next asked whether lonelier participants' communication about well-known celebrities also deviates from the zeitgeist. Indeed, when a strong group consensus exists, lonelier individuals use idiosyncratic language to describe well-known celebrities (Study 2: N = 923). Collectively, results support lonely individuals' feeling that their views are not shared. This suggests loneliness may not only reflect impoverished relationships with specific individuals, but also feelings of disconnection from prevalently shared views of contemporary culture.

Social environment-based opportunity costs dictate when people leave social interactions.

There is an ever-increasing understanding of the cognitive mechanisms underlying how we process others' behaviours during social interactions. However, little is known about how people decide when to leave an interaction. Are these decisions shaped by alternatives in the environment - the opportunity-costs of connecting to other people? Here, participants chose when to leave partners who treated them with varying degrees of fairness, and connect to others, in social environments with different opportunity-costs. Across four studies we find people leave partners more quickly when opportunity-costs are high, both the average fairness of people in the environment and the effort required to connect to another partner. People's leaving times were accounted for by a fairness-adapted evidence accumulation model, and modulated by depression and loneliness scores. These findings demonstrate the computational processes underlying decisions to leave, and highlight atypical social time allocations as a marker of poor mental health.

Distractor inhibition by alpha oscillations is controlled by an indirect mechanism governed by goal-relevant information.

The role of alpha oscillations (8-13 Hz) in cognition is intensively investigated. While intracranial animal recordings demonstrate that alpha oscillations are associated with decreased neuronal excitability, it is been questioned whether alpha oscillations are under direct control from frontoparietal areas to suppress visual distractors. We here point to a revised mechanism in which alpha oscillations are controlled by an indirect mechanism governed by the load of goal-relevant information - a view compatible with perceptual load theory. We will outline how this framework can be further tested and discuss the consequences for network dynamics and resource allocation in the working brain.

Examining the effects of voluntary avoidance behaviour and policy-mediated behaviour change on the dynamics of SARS-CoV-2: A mathematical model.

Background: Throughout the SARS-CoV-2 pandemic, policymakers have had to navigate between recommending voluntary behaviour change and policy-driven behaviour change to mitigate the impact of the virus. While individuals will voluntarily engage in self-protective behaviour when there is an increasing infectious disease risk, the extent to which this occurs and its impact on an epidemic is not known. Methods: This paper describes a deterministic disease transmission model exploring the impact of individual avoidance behaviour and policy-mediated avoidance behaviour on epidemic outcomes during the second wave of SARS-CoV-2 infections in Ontario, Canada (September 1, 2020 to February 28, 2021). The model incorporates an information feedback function based on empirically derived behaviour data describing the degree to which avoidance behaviour changed in response to the number of new daily cases COVID-19. Results: Voluntary avoidance behaviour alone was estimated to reduce the final attack rate by 23.1%, the total number of hospitalizations by 26.2%, and cumulative deaths by 27.5% over 6 months compared to a counterfactual scenario in which there were no interventions or avoidance behaviour. A provincial shutdown order issued on December 26, 2020 was estimated to reduce the final attack rate by 66.7%, the total number of hospitalizations by 66.8%, and the total number of deaths by 67.2% compared to the counterfactual scenario. Conclusion: Given the dynamics of SARS-CoV-2 in a pre-vaccine era, individual avoidance behaviour in the absence of government action would have resulted in a moderate reduction in disease however, it would not have been sufficient to entirely mitigate transmission and the associated risk to the population in Ontario. Government action during the second wave of the COVID-19 pandemic in Ontario reduced infections, protected hospital capacity, and saved lives.

Connecting human behaviour, meaning and nature.

Much of the discourse around climate change and the situation of diverse human societies and cultures in the Anthropocene focuses on responding to scientific understanding of the dynamics of the biosphere by adjusting existing institutional and organizational structures. Our emerging scientific understanding of human behaviour and the mechanisms that enable groups to achieve large-scale coordination and cooperation suggests that incrementally adjusting existing institutions and organizations will not be sufficient to confront current global-scale challenges. Specifically, the transaction costs of operating institutions to induce selfish rational actors to consider social welfare in their decision-making are too high. Rather, we highlight the importance of networks of shared stories that become real-imagined orders-that create context, meaning and shared purpose for framing decisions and guiding action. We explore imagined orders that have contributed to bringing global societies to where they are and propose elements of a science-informed imagined order essential to enabling societies to flourish in the Anthropocene biosphere. This article is part of the theme issue 'Bringing nature into decision-making'.

CUSCO: An Unobtrusive Custom Secure Audio-Visual Recording System for Ambient Assisted Living.

The ubiquity of digital technology has facilitated detailed recording of human behaviour. Ambient technology has been used to capture behaviours in a broad range of applications ranging from healthcare and monitoring to assessment of cooperative work. However, existing systems often face challenges in terms of autonomy, usability, and privacy. This paper presents a portable, easy-to-use and privacy-preserving system for capturing behavioural signals unobtrusively in home or in office settings. The system focuses on the capture of audio, video, and depth imaging. It is based on a device built on a small-factor platform that incorporates ambient sensors which can be integrated with the audio and depth video hardware for multimodal behaviour tracking. The system can be accessed remotely and integrated into a network of sensors. Data are encrypted in real time to ensure safety and privacy. We illustrate uses of the device in two different settings, namely, a healthy-ageing IoT application, where the device is used in conjunction with a range of IoT sensors to monitor an older person's mental well-being at home, and a healthcare communication quality assessment application, where the device is used to capture a patient-clinician interaction for consultation quality appraisal. CUSCO can automatically detect active speakers, extract acoustic features, record video and depth streams, and recognise emotions and cognitive impairment with promising accuracy.

Applying the Non-adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework to evaluate automated evidence synthesis in health behaviour change.

Automated tools to speed up the process of evidence synthesis are increasingly apparent within health behaviour research. This brief review explores the potential of the Non-adoption, Abandonment, Scale-up, Spread and Sustainability framework for supporting automated evidence synthesis in health behaviour change by applying it to the ongoing Human Behaviour-Change Project, which aims to revolutionize evidence synthesis within behaviour change intervention research. To increase the relevance of NASSS for health behaviour change, we recommend i) terminology changes ('condition' to 'behaviour' and 'patient' to 'end user') and ii) that it is used prospectively address complexities iteratively. We draw conclusions about i) the need to specify the organizations that will use the technology, ii) identifying what to do if interdependencies fail and iii) even though we have focused on automated evidence synthesis, NASSS would arguably be beneficial for technology developments in health behaviour change more generally, particularly for invention development.