Exploring social cues and engagement in humanoid robots : a Robosen K1 case study

With the increase adoption of humanoid robots in today's world, the need to understand the ways through which these robots communicate social cues has become indispensable for effective human-robot interaction (HRI) in everyday life. The focus of this study is on the examination of the influence of non-verbal behaviour of Robosen K1 (a humanoid robots) on human perceptions and emotional responses. K1 was programmed to perform expressive full-body movements, due its lack of facial expressions, such as dancing, push-ups, and standing on its head. The research design was a mixed-method approach, which combined behavioural observations from live interactions with data from an online survey. Findings from the study revealed positive emotional reactions from participants, most of which described the robot as " impressive, " " curious, " and " amusing. " Also, results indicated that 89.8% of participants were favourably disposed to engaging with similar robots in the future. Finally, it was found that the robot's gestures, being highly expressive, contributed to perceived personality traits such as " playful " and " friendly. " The study, therefore, concluded that a well-designed non-verbal cues would play critical role in enhancing emotional connection, engagement, and trust in humanoid robots, hence, their importance for successful HRI design

A Critical Literature Review of Social Mobility in Britain's Further Education Sector

This article critically reviews the relationship between social mobility and Britain's Further Education (FE) sector, tracing the concept's evolution and the dominance of intergenerational measures in research and policy. It argues that this focus obscures the short-and medium-term impacts of FE, which are better captured through intragenerational approaches. Frameworks such as Bourdieu's forms of capital are noted for their frequent but partial use, often serving as categorisation tools rather than fully applied analytical models. The review highlights structural and policy constraints—including the hierarchy of qualifications, narrowing vocational pathways, and the limitations of proxies such as Free School Meal (FSM) eligibility—that undermine FE's capacity to promote upward mobility for disadvantaged learners. It concludes that persistent data limitations and policy biases towards Higher Education (HE) obscure FE's distinct role, calling for standardised intragenerational measurement frameworks, improved high-frequency longitudinal datasets, and rigorous evaluation of qualification reforms to better understand and enhance FE's contribution to social mobility

Predicting job risk from artificial intelligence in London using supervised machine learning models

This study investigates the risk of job automation in London due to artificial intelligence (AI), applying supervised machine learning techniques to identify occupations most at risk. Leveraging a dataset encompassing job-specific features such as primary tasks, industry domains, and associated AI models, the research develops two predictive models. A Random Forest Classifier is used to categorize jobs as low, medium, or high automation risk, while a Linear Regression model estimates the proportion of each occupation's workload likely to be automated. The Random Forest model achieved a high accuracy rate of 97 % in classifying job risk, indicating strong predictive capability. Meanwhile, the regression model explained 85 % of the variance in the AI workload ratio, highlighting a significant relationship between job attributes and automation potential. These results suggest that job characteristics are reliable indicators of AI impact, particularly in routine, repetitive, and low-skilled roles that are more easily codified and replicated by algorithms. The findings align with broader economic theories such as creative destruction and technological waves, suggesting that AI not only displaces certain roles but also drives structural transformation within the labor market. By focusing on London, this study provides a localized understanding of how AI is reshaping employment patterns. It underscores the growing urgency for strategic workforce re-skilling and adaptive policy frameworks to mitigate negative outcomes and maximize opportunities presented by AI. Ultimately, this research contributes valuable insights into the interaction between AI technologies and employment, helping policymakers, employers, and educators anticipate change and prepare for a more resilient, inclusive labor market

Graphene oxide–based wireless sensor in fibre–reinforced hybrid composites for incipient fire detection

Fire sensors offer an effective strategy for mitigating fire hazards. This work reports the development of self-sensing glass fibre–reinforced composites (GFRCs) by incorporating a graphene oxide (GO)–aramid sensing layer into their structure. Two sensor configurations were explored: GO–coated aramid webs (GO–AW) and GO–aramid nanofibre films (GO–ANF). These sensors function via the thermal reduction of GO to conductive reduced graphene oxide (rGO) under heat or flame, enabling rapid (<1 s) fire detection and real-time wireless alerts via an IoT–enabled system. The GO–AW web strip, patterned with conductive ink electrodes and embedded in a GFRC laminate, effectively responded to both conductive (direct contact) and radiative (external heat flux) heat, acting as a robust pre–fire sensing material. Integration with an ESP32 microcontroller enabled wireless, real–time monitoring and instant alerts, ensuring practical applicability in fire–safety–critical environments. Furthermore, the incorporation of GO–AW enhanced the thermal and mechanical properties of the composite, with the flexural modulus increasing from 3.1 to 6.5 GPa and the glass transition temperature from 86 °C to 94 °C. The presence of GO–AW in the GFRC also reduced flammability of the composite, indicated by reduction in the peak and total heat release rate by 22 and 45 %, respectively in cone calorimetric experiments. Overall, the integration of GO–AW not only imparted fire-sensing functionality but also improved the composite's structural integrity and flame retardancy, demonstrating broad potential for structural and industrial applications

Identification of volatiles during thermal degradation of epoxy resins for detection of incipient fire conditions in composites

This work reports the qualitative and quantitative identification of volatile products from thermal and thermo-oxidative decompositions of different epoxy resins to allow selection of the particular chemical species most likely to be detectable in situ by infrared and chemical sensors. Thermogravimetry coupled with Fourier transform infrared analysis (TGA-FTIR) has been carried out on three resins at heating rates ranging from 20 to 70 °C/min in increments of 10 °C/min to understand the effects of the severities of different heating environments. Pyrolysis-FTIR has been conducted to complement the TGA-FTIR study under static atmospheric conditions hence revealing the volatile production under oxidative conditions. While the evolution of water, CO2, phenolic, carbonyl, aliphatic, aromatic and N-containing species could be observed in all resin types, the intensities and times of evolution of different components varied. Higher heating rates resulted in the evolution of volatiles occurring earlier and at greater intensities, but with a lower total amount of each product being evolved. From detection of CO, CO2 and aliphatic hydrocarbons in early stages of resin decomposition, i.e., prior to ignition, it can be inferred that sensors detecting these gases could be deployed in composites to provide a warning of any potential fires

Supplementary Materials referenced in the 'Playful Citizen Discussion Space to Help Steer Society Towards Water Security' paper

This file contains the supplementary material referenced in the 'Playful Citizen Discussion Space to Help Steer Society Towards Water Security' paper. It contains further details on water use survey design, calculations used to define water use, graphs presented for data exploration survey, screenshots and information of the playful dilemma: Save the City, reflective survey questions, and additional follow up questions

Multifunctional Smart Grid Control based on Power Electronic Systems

There is a worldwide switch to electricity generation plants based on renewable energy sources(RES) to decarbonise electricity generation. In contrast to the fossil fuel based traditionalpower plants, power plants based on RES are widely distributed and often connected to thedistribution system operator (DSO) grid level, which leads to a structural change of theelectricity network. The rising numbers of installed RES and the high fluctuation of powergeneration increase the stress on this grid level. To improve the stability, reliability andefficiency of the DSO grid level, it is necessary to transfer and adapt ancillary service functionsknown from the transmission system operator (TSO) to the DSO grid level.To provide ancillary services at the DSO grid level under high fluctuations, unbalanced gridconditions and harmonic distortions, a new Multifunctional Energy and Power Server (MEPS)based on modern power electronic is introduced in this research. The system topology consistsof a series- and a parallel-connected inverter branch. This structure is known as the UnifiedPower Quality Conditioner (UPQC) and the Unified Power Flow Controller (UPFC), whichare used in active power filters and in power flow control in electrical grids. The systemapproach developed in this work for implementing grid service functions aims to combine thevarious approaches for this in a single system.The series branch consists of an inverter system connected by a transformer in series to theupstream network and is able to compensate for asymmetrical and harmonic distorted voltages.The parallel branch consists of a second inverter system, which is connected in parallel to thegrid and is able to compensate for asymmetrical and harmonic distorted currents. Incombination with a battery system, the parallel branch can also provide active power-basedfunctions, such as primary control and power fluctuation compensation. All these grid-specificdynamic control functions are implemented based on symmetrical components (SC) withindividual controller loops for the positive, negative and zero sequences in the fundamentaland harmonic frequency range. To use the SC for real-time control, all measured voltages andcurrents are separated into different harmonic components using the heterodyne method. Thecombination of the heterodyne method with the SC transformation allows for the individualand decoupled control under asymmetrical and harmonic distorted conditions.The simulation and application tests carried out during the research show, that unbalanced andharmonic distorted voltages and currents can be controlled selectively and in a decoupledmanner. By considering the effective impedance of the grid connection point individually, forevery harmonic frequency under control, allows for a stable operation and good transientresponse - also at difficult impedance characteristics, such as found at a 3-leg, 4-wire splitcapacitor inverter topology.Finally, several inverters were connected in parallel to increase the output power forexperiments under real grid conditions. The successful operation of a whole system consistingof several inverters demonstrates the flexibility and scalability of the approach. The control hasa positive impact on the capacity and stability of the examined grid area by reducing powerfluctuations and unsymmetrical and harmonic voltages and currents. The experiments confirmthe effectiveness of the decoupled control also under real grid conditions

Attitudes of lecturers and students towards disability and inclusion of Higher Education disabled students and the impact on disabled students’ lived experiences

Disabled university students face barriers and are among those likelier to withdraw and have lower degree outcomes (OfS 2023). One potential barrier impacting disabled students’ university experience and outcomes is lecturers and students’ attitudes. Phase one of this two-phase study which adopts a critical realist framework, employs Q-Methodology to investigate lecturers and students’ attitudes towards disability and inclusion of disabled higher education (HE) students. Phase two Interpretive Phenomenological Analysis (IPA) of semi-structured interviews with disabled students explores the impact of attitudes on their lived experience.Using Q Method Software, thirty-one lecturers sorted forty-five statements describing the spectrum of attitudes towards disability and inclusion and provided optional post-sort survey and interview data. Two stances about inclusion emerged from factor analysis and interpretation: cautiously committed with concerns and confidently committed with concerns. Both groups are committed to inclusion of disabled students. However, the majority group is more cautious and concerned about expertise. The second group is more ableism aware and confident implementing inclusion but shares group one’s concerns about training. Fifty-two students sorted thirty-nine Q-sort statements. Analysis of thirty-three non-disabled students’ data revealed two views: pro-inclusion and confidently proactive, and pro-inclusion but cautious. Both groups share concerns relating to discrimination faced by disabled students. However, the minority group are more cautious about disability inclusion. The second group are more empathetic, ableism aware and confident to challenge discrimination. Analysis of nineteen disabled students’ data uncovered one perspective: pro-inclusion but concerned about ableist barriers.Phase two IPA of eight semi-structured interviews with disabled students revealed four Group Experiential Themes: Diagnosis, disclosure and identity issues; Reasonable adjustments and knowledgeable, empathetic lecturers- for some; Supportive, empathetic peers and sense of belonging- for some; Facing ableism beyond university.The findings contribute to academic discourse in this sparsely researched area and highlight future research implications. The thesis recommendations for HE policy and practice will positively impact disabled students’ university experience and outcomes