University of Essex

Looking at caregivers’ faces is important for early social development, and there is a concomitant increase in neural correlates of attention to familiar versus novel faces in the first 6 months. However, by 12 months of age brain responses may not differentiate between familiar and unfamiliar faces. Traditional group‐based analyses do not examine whether these ‘null’ findings stem from a true lack of preference within individual infants, or whether groups of infants show individually strong but heterogeneous preferences for familiar versus unfamiliar faces. In a preregistered proof‐of‐principle study, we applied Neuroadaptive Bayesian Optimisation (NBO) to test how individual infants’ neural responses vary across faces differing in familiarity. Sixty‐one 5–12‐month‐olds viewed faces resulting from gradually morphing a familiar (primary caregiver) into an unfamiliar face. Electroencephalography (EEG) data from fronto‐central channels were analysed in real‐time. After the presentation of each face, the Negative central (Nc) event‐related potential (ERP) amplitude was calculated. A Bayesian Optimisation algorithm iteratively selected the next stimulus until it identified the stimulus eliciting the strongest Nc for that infant. Attrition (15%) was lower than in traditional studies (22%). Although there was no group‐level Nc‐difference between familiar versus unfamiliar faces, an optimum was predicted in 85% of the children, indicating individual‐level attentional preferences. Traditional analyses based on infants’ predicted optimum confirmed NBO can identify subgroups based on brain activation. Optima were not related to age and social behaviour. NBO suggests the lack of overall familiar/unfamiliar‐face attentional preference in middle infancy is explained by heterogeneous preferences, rather than a lack of preference within individual infants.

Previous studies have investigated the effect of target prevalence in combination with the effect of explicit target value on human visual foraging strategies, though the conclusions have been mixed. Some find that individuals have a bias towards high-value targets even when these targets are scarcer, while other studies find that this bias disappears when those targets are scarcer. In this study, we tested for a bias for scarce targets using standard feature versus conjunction visual foraging tasks, without an explicit value being given. Based on the idea of commodity theory and implicit value, we hypothesized that participants would show a scarcity bias. The bias was investigated using a Bayesian statistical model which has been developed for predicting target-by-target foraging behaviours. However, we found no evidence of a scarcity bias in our experiment, suggesting that participants did not inherently find rarer targets more rewarding.

The present paper investigates whether school-aged French-English bilingual children’s implicit and explicit knowledge of article use is affected by cross-linguistic influence (CLI) during online and offline sentence comprehension. The studies focus on the encoding of plural and mass nouns in specific and generic contexts. We also explore whether individual measures of oral proficiency, language exposure and age play a role in the children’s performance. Forty-three 8-to-10-year-old French-English bilingual children took part in a Self-Paced Reading task, a Grammaticality Judgement task and a Cloze test in their two languages. Overall, CLI was observed across tasks in English and French. These findings suggest that CLI can be bi-directional and tap into school-aged bilinguals’ implicit and explicit representations during sentence comprehension and production. The data also makes a new contribution to our understanding of the relative amount of language exposure, oral proficiency and age on CLI.

Semantic communication holds promise for integration into future wireless networks, offering a potential enhancement in network spectrum efficiency. However, implementing semantic communication in aerial-aided edge networks (AENs) introduces unique challenges. Within AENs, semantic communication strategically substitutes part of the communication load with the computation load, aiming to boost spectrum efficiency. This departure from traditional communication paradigms introduces novel challenges, particularly in terms of energy efficiency. Furthermore, by adding complexity, the use of a semantic coder based on machine learning (ML) in AENs encounters real-time updating challenges, further amplifying energy costs in these complex and energy-limited environments. To address these challenges, we propose an energy-efficient semantic communication system tailored for AENs. Our approach includes a mathematical analysis of semantic communication energy consumption within AENs. To enhance energy efficiency, we introduce an energy-efficient game-theoretic incentive mechanism (EGTIM) designed to optimize semantic transmission within AENs. Moreover, considering the accurate and energy-efficient updating of semantic coders in AENs, we present a game-theoretic efficient distributed learning (GEDL) framework, building upon the foundations of the renewed EGTIM. Simulation results validate the effectiveness of our proposed EGTIM in improving energy efficiency. Additionally, the presented GEDL framework exhibits remarkable performance by increasing model training accuracy and concurrently decreasing training energy consumption.

This article presents a novel shared-control teleoperation framework that integrates imitation learning and bilateral control to achieve system stability based on a new dynamic movement primitives (DMPs) observer. First, a DMPs-based observer is first created to capture human operational skills through offline human demonstrations. The learning results are then used to predict human action intention in teleoperation. Compared with other observers, the DMPs-based observer incorporates human operational features and can predict long-term actions with minor errors. A high-gain observer is established to monitor the robot’s status in real time on the leader side. Subsequently, two controllers on both the follower and leader sides are constructed based on the outputs of the observers. The follower controller shares control authorities to address accidents in real-time and correct prediction errors of the observation using delayed leader commands. The leader controller minimizes position-tracking errors through force feedback. The convergence of the predictions of the DMPs-based observer under the time delays and teleoperation system stability are proved by building two Lyapunov functions. Finally, two groups of comparative experiments are conducted to verify the advantages over other methods and the effectiveness of the proposed framework in motion prediction with time delays and obstacle avoidance.

Real-time semantic segmentation (SS) is a major task for various vision-based applications such as self-driving. Due to the limited computing resources and stringent performance requirements, streaming videos from camera-embedded mobile devices to edge servers for SS is a promising approach. While there are increasing efforts on task-oriented video compression, most SS-applicable algorithms apply more uniform compression, as the sensitive regions are less obvious and concentrated. Such processing results in low compression performance and significantly limits the capacity of edge servers supporting real-time SS. In this paper, we propose STAC, a novel task-oriented DNN-driven video compressive streaming algorithm tailed for SS, to strike accuracy-bitrate balance and adapt to time-varying bandwidth. It exploits DNN's gradients as sensitivity metrics for fine-grained spatial adaptive compression and includes a temporal adaptive scheme that integrates spatial adaptation with predictive coding. Furthermore, we design a new bandwidth-aware neural network, serving as a compatible configuration tuner to fit time-varying bandwidth and content. STAC is evaluated in a system with a commodity mobile device and an edge server with real-world network traces. Experiments show that STAC can save up to 63.7-75.2% of bandwidth or improve accuracy by 3.1-9.5% compared to state-of-the-art algorithms, while capable of adapting to time-varying bandwidth

In dynamic and time-varying vehicular networks, existing vehicular communication systems cannot guarantee ultra-reliable and low latency communication (uRLLC). To address this, we propose a novel deep reinforcement learning-based vehicular optical camera communication (OCC) system with an aim to maximize the throughput and ensure uRLLC. To achieve this, our scheme chooses the optimal code rate, modulation scheme and speed of vehicles for multiple vehicular links. We use OCC, which offers interference-free communication as an alternative to radio frequency systems. Moreover, we employ 5G New Radio low-density parity-check codes and an adaptive modulation scheme to support variable rates and ultra-reliability. The proposed large-scale and continuous problem is solved through an actor-critic algorithm based on Wolpertinger architecture. We extendedly evaluate the system performance and compare it with several other schemes from the literature as well as with variants of our scheme. We observe from the results that the proposed method achieves higher average throughput and lower latency than all the other schemes under comparison. Further, the proposed scheme can meet the uRLLC constraints, whereas other schemes under comparison fail to respect these constraints most of the time.

Rising environmental interests have prompted the international community to actively use the tool of Marine Protected Areas (MPAs) for the protection of the marine environment. In particular, States and international organisations are now adopting international MPAs, which involve more than one State and cover multiple jurisdictions. More MPAs are now being designated in areas beyond national jurisdiction such as the high seas and the deep seabed. Moreover, MPAs are one of the four pillars of an international legally binding instrument under the United Nations Convention on the Law of the Sea on the conservation and sustainable use of marine biological diversity of areas beyond national jurisdiction. Notwithstanding this trend, active international cooperation over international MPAs is seldom observed in Asia. This chapter provides an overview of the development of international MPAs and reflections on such development in Asia. It first illustrates the range and trend in the use of international MPAs as a tool to protect the marine environment. It then turns the focus to Asia. Unlike other regions such as the North-East Atlantic, the Mediterranean Sea or the Baltic Sea, Asia has seldom witnessed regional cooperation for the protection of the marine environment. There are Areas of Particular Environmental Interest situated in the deep seabed area of the Central Pacific, but they are not established by Asian States but rather by the International Seabed Authority. In light of the international community’s ongoing calling for more MPAs, the chapter then explores past discussions on MPAs in the South China Sea. Based on these historical examples, it follows with the prospects of MPAs in Asia, in light of the recent adoption of the BBNJ Agreement.

This article intervenes in contemporary critical scholarship on the ethics of chemsex and other so-called ‘risky’ gay male sexual practices through a careful appraisal of psychoanalytic theory on subjectivity and sexuality. I argue that the emerging field of critical chemsex studies prioritises contemporary approaches to ‘bodies and pleasures’ at the expense of subjectivity, leading to an inability to adequately theorise some participants’ avowed experiences of suffering from problematic chemsex use. Drawing critically on previous psychoanalytic scholarship on barebacking, I argue that, contrary to stereotypical depictions, chemsex may be motivated not by a self-destructive death drive, but rather a paradoxical attempt to shelter oneself from this drive. This idea may helpfully counter the psychoanalytic tendency to exceptionalise or pathologise gay male sexual practices, while also questioning the ethical valence attributed to chemsex. I conclude with an exploration of Lacanian ethics and the implications this may hold for critical chemsex studies and public health.

Device–to–device (D2D) communications are based on direct signaling and data transmission within wireless devices. Furthermore, it facilitates mission-critical services for public safety (PS), vehicle–to–vehicle (V2V) or drones. These D2D applications need nationwide coverage across multiple operators. The existing roaming system, however, does not provide sufficient trust for D2D roaming scenarios since the direct link between devices is difficult to monitor in the core network side. Therefore, a novel framework to support D2D roaming is proposed inspired by blockchain–based trust systems. The framework consists of an authentication for D2D user equipment (UE) access, authorization to configure D2D service, and resource pool selection. Also, a dynamic D2D resource pool selection enabled by D2D class awareness is supported. Analytical results show that the proposed dynamic resource pool selection scheme improves capacity in the form of decoding performance.

When the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM‐5) was published in 2013, there was a firestorm of controversy about the elimination of the bereavement exclusion. Proponents of this change and of the proposed “complicated grief” designation believed that this change would help clinicians recognise major depression in the context of recent bereavement. Other researchers and clinicians have raised concerns about medicalising grief. In 2022 “prolonged grief disorder” (PGD) was officially included in the DSM‐5‐TR in the trauma‐ and stressor‐related disorders section. Not surprisingly, there has been a push to identify biomarkers and to use neuroimaging to identify the neurobiological basis of PGD. Some researchers have even suggested that PGD is a ‘reward circuit disorder’ akin to addiction and that naltrexone, an opioid antagonist, may be a promising treatment. The purpose of this paper is to show how medicalising grief reinforces a research agenda dedicated to the search for pharmaceutical and psychological ‘magic bullets.’ Following George and Whitehouse (2021), we propose that an ecopsychosocial approach—one that incorporates environmental and contextual factors—is needed.

Previous studies suggest that social learning in bumblebees can occur through second-order conditioning, with conspecifics functioning as first-order reinforcers. However, the behavioural mechanisms underlying bumblebees’ acquisition of socially learned associations remain largely unexplored. Investigating these mechanisms requires detailed quantification and analysis of the observation process. Here we designed a new 2D paradigm suitable for simple top-down high-speed video recording and analysed bumblebees’ observational learning process using a deep-learning-based pose-estimation framework. Two groups of bumblebees observed live conspecifics foraging from either blue or yellow flowers during a single foraging bout, and were subsequently tested for their socially learned colour preferences. Both groups successfully learned the colour indicated by the demonstrators and spent more time facing rewarding flowers—whether occupied by demonstrators or not—compared to non-rewarding flowers. While both groups showed a negative correlation between time spent facing non-rewarding flowers and learning outcomes, the observer bees in the blue group benefited from time spent facing occupied rewarding flowers, whereas the yellow group showed that time facing unoccupied rewarding flowers by the observer bees positively correlated with their learning outcomes. These results suggest that socially influenced colour preferences are shaped by the interplay of different types of observations rather than merely by observing a conspecific at a single colour. Together, these findings provide direct evidence of the dynamical viewing process of observer bees during social observation, opening up new opportunities for exploring the details of more complex social learning in bumblebees and other insects.

Background Breastmilk is widely regarded as the healthiest choice for both infants and mothers due to its numerous advantages over formula, such as higher concentrations of essential nutrients and antibodies, easier digestion, and superior taste. The World Health Organization International Code of Marketing of Breast-milk Substitutes was adopted over 40 years ago to mitigate the effects of infant formula marketing on a woman’s decision to breastfeed. Yet, the commercial formula milk industry has continued to market their products aggressively and through an increasing variety of social media channels. This study examines the impact of formula milk marketing on specific components of the health system to understand how systems that are built to support and sustain breastfeeding may have been captured and repurposed by industry practices. Methods As part of A Multi-country Study of Early Infant Feeding Decisions, this qualitative study was conducted in two representative cities in China, Beijing and Jinan, in 2020. The participants were recruited through convenience sampling and snowballing sampling methods. Data were collected through 40 in-depth interviews and 10 focus group discussions with health professionals, pregnant women, and formula milk marketing executives. A thematic analytical method was used to analyze the main themes and sub-themes that detail the characteristics of formula milk marketing and its impact on the health system in China. Results Our results identified the most common practices used by the formula milk industry to reach health workers as well as mothers and their families through health systems. Such practices include (1) provider/facility-based marketing to sponsor academic activities (e.g., seminars, conferences, and research projects) and promote specialized infant formula that targets health care providers and facilities, which influence the health consultations and recommendations provided by health professionals to mothers and families; and (2) receiver-based marketing that targets Chinese women and increases marketing exposure through lectures provided by maternity schools at health facilities during the antenatal period and health promotion activities organized by formula milk companies outside of facilities during the postnatal care period. Conclusions Formula milk marketing aims to influence the practices and services within the health system in China, both directly through health professionals and facilities, and also indirectly by targeting mothers. These marketing strategies have impacted the perceptions of providers on formula milk, and strategies targeting consumers have aimed to further influence and undermine mothers’ intentions to continue breastfeeding. Stricter regulation of industry marketing practices is needed to create a supportive environment for mothers to breastfeed.

Multicopper oxidases use Cu ions as cofactors to oxidize various substrates. High reduction potential at Type 1 Cu is considered as crucial for effective catalysis. Previous studies have shown that replacing the axial methionine ligand of the Type 1 Cu with leucine or phenylalanine leads to an increased reduction potential, but not always to higher enzyme activity. Here we present a study on six variants of the small laccase Ssl1 from Streptomyces sviceus, where the axial methionine ligand was substituted, and the effect of the axial ligand on reduction potential, activity, spectral properties and structure was investigated. Absorption, electronic circular dichroism and EPR spectra revealed the presence of a stronger coordinating axial ligand like oxygen, which influences the electronic and catalytic properties more than the nature of the amino acid side chain. The crystal structures of the Ssl1 variants were solved, which show that none of the amino acid side chains coordinate to the Cu. Instead, a water molecule is found in the axial coordination site, which support the spectroscopic data. Our findings highlight the importance of combining structural and spectroscopic methods to investigate the effect of amino acid exchange on multicopper oxidases.

In this work, we present a new and efficient algorithm to perform a short-term market trend forecast, based on the Artificial Organic Networks (AON) metaheuristic machine learning framework. Regarding this goal, we present the concept of Artificial Halocarbon Compounds (AHC) or AHC-algorithm as a bio-inspired supervised machine learning algorithm based on the AON framework. Through our research, we contrast the forecast acquired with the proposed AHC model, to previously reported outcomes using the Artificial Hydrocarbon Networks (AHN) in similar tasks. The AHN algorithm is the first formally defined topology based on the AON, making the AHN algorithm a vital benchmark to contemplate. After comparing the AHC-algorithm to the original AHN-algorithm, we found out that due to the high computational complexity of the latter, the new topology is more convenient when modeling more complex systems; being this characteristic the main contribution of the AHC-algorithm, allowing it to be a more adaptable, dynamic, and reconfigurable topology. Likewise, we compared the results of the AHC-algorithm against the outcomes derived from an ARIMA model; we also made a cross-reference contrast against results concerning the prediction of other stock market indices using former state-of-the-art machine learning methods. The proficiency of the AHC-algorithm is assessed by doing a forecast of the IPC Mexico index obtaining good results, achieving a computed R-square of 0.9919, and an $8\times 10^{-4}$ mean relative error for the forecast.

Background Gesture and speech collaborate in conveying meaning, and gesture is often leveraged by people with neurogenic communication disorders, such as aphasia, cognitive‐communicative impairments and primary progressive aphasia, when words fail them. Because gesture is imagistic, transitory and holistic, there are inherent challenges when assessing and treating it. Aims The survey had three primary research questions: (1) what gesture assessment practices, and (2) what gesture treatment practices, are employed by speech and language therapists (SLTs) internationally; and (3) what are the factors that influence these practices? Methods and Procedures An online survey of practice using Qualtrics was piloted and then disseminated to practising SLTs working with people with neurogenic communication disorders. In addition to descriptive statistics summarising across the three research questions, statistical comparisons were made for two independent groups: primary work setting (research versus clinical), and primary work setting considering years of experience specific to neurogenic communication disorders (research, high; research, low; clinical, high; and clinical, low). Outcomes and Results A total of 130 international SLTs completed the first two parts of the survey. A total of 107 completed all four sections of the survey. Fifty percent of respondents reported assessing gesture sometimes/for some clients, with only 5% reporting that they never assessed gesture. Nearly 70% of respondents reported never using a published test to evaluate gesture, with qualitative results suggesting a lack of formal assessments. This was further highlighted by the most prominent barrier being a lack of published tests (50% of respondents said this). The primary reason for evaluating gesture was to assess nonverbal communication. There was no significant difference in gesture assessment practices across comparison groups. The research group, and those within the research group with most years of experience, tended to target gestures during treatment and write treatment goals containing gesture more than other respondents. The most common facilitator to assessing or treating gesture was that the family or individual prioritised gesture for enhancing communication (53.1% of respondents). No group differences were identified for barriers/facilitators. Conclusions and Implications Findings indicate that whilst gesture is a critical nonverbal communicative behaviour, there is an unmet need for empirical and standardised methods for assessing gesture in speech and language clinical practice and there is a lack of gesture‐specific treatment resources. SLTs working in research settings may feel more able, or have more resources, to include gesture during treatment. Essential next steps include creating empirical and standardised methods for assessing gesture in speech and language clinical practice. WHAT THIS PAPER ADDS What is already known on the subject Gesture is a complex and crucial aspect of communication. It is a key part of the role of speech and language therapists (SLTs), as described in clinical guidelines, to assess people with aphasia's use of gesture and consider whether it could be enhanced through treatment. What this study adds to existing knowledge This is the first international survey of practice focusing on gesture assessment and treatment. It highlights the variety of methods used by SLTs to assess and treat gesture, the importance they attach to this area and the need for standardised assessment tools and treatment resources. What are the clinical implications of this work? This study provides a comprehensive overview of practices for assessing and treating gesture in neurogenic communication disorders, as well as a list of gesture resources being actively used by clinicians and researchers. These may be useful for clinicians looking to expand their understanding of approaches and resources for assessment and treatment in this domain. The study also reports on the reasons clinicians assess gesture and the barriers and facilitators they encounter which may inform clinical practice in this area.