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EEG correlates of acquiring race driving skills
No full textObjective. Race driving is a complex motor task that involves multiple concurrent cognitive processes in different brain regions coordinated to maintain and optimize speed and control. Delineating the neuroplasticity accompanying the acquisition of complex and fine motor skills such as racing is crucial to elucidate how these are gradually encoded in the brain and inform new training regimes. This study aims, first, to identify the neural correlates of learning to drive a racing car using non-invasive electroencephalography (EEG) imaging and longitudinal monitoring. Second, we gather evidence on the potential role of transcranial direct current stimulation (tDCS) in enhancing the training outcome of race drivers. Approach. We collected and analyzed multimodal experimental data, including drivers’ EEG and telemetry from a driving simulator to identify neuromarkers of race driving proficiency and assess the potential to improve training through anodal tDCS. Main results. Our findings indicate that theta-band EEG rhythms and alpha-band effective functional connectivity between frontocentral and occipital cortical areas are significant neuromarkers for acquiring racing skills. We also observed signs of a potential tDCS effect in accelerating the learning process. Significance These results provide a foundation for future research to develop innovative race-driving training protocols using neurotechnology
Truthful two-facility location with candidate locations
Get PDFWe study a truthful two-facility location problem in which a set of agents have private positions on the line of real numbers and known approval preferences over two different facilities. Given the locations of the two facilities, the cost of an agent is the total distance from the facilities she approves. The goal is to decide where to place the facilities from a given finite set of candidate locations so as to (a) approximately optimize desired social objectives, and (b) incentivize the agents to truthfully report their private positions. We focus on the class of deterministic strategyproof mechanisms and show bounds on their approximation ratio in terms of the social cost (i.e., the total cost of the agents) and the max cost for several classes of instances depending on the preferences of the agents over the facilities
Gambling outlets as agents of local area disorganization: Crime and local institutions, the case of the UK
Get PDFAmid growing public and policy concerns there is a great need for a systematic analysis of the relationship between commodity industries and social disorganization. Using data from the ONS, the UK Census, the UK Police Street-level Crime Dataset, and the POI Ordnance Survey, we analyse the association between gambling outlets as an example of a commodity industry and crime events across England and Wales and explore the possibility of a heterogeneous effect dependent upon the level of deprivation and residential stability of an area. Our findings show that gambling outlets are significantly and positively associated with different types of crime even when controlling for other businesses, the areas’ demographic and socio-economic characteristics. Small businesses provide distinctive shielding effects – in areas of high density of small business owners, there is no significant correlation between crime types and gambling density. Our results have significant policy implications
A compartmental model to describe acute medical in-patient flow through a hospital
Get PDFManaging patient flow in hospitals is a critical part of effective secondary care. Considering a hospital as a multi-compartment system through which patients pass, we will derive relevant equations to allow a description of patient flow through these departments as a series of interconnected dynamic relationships. These relationships are determined by many factors, some known, and many interdependent. We do not need to, and indeed cannot, know all of these factors (as needed for discrete event simulation, or agent-based modelling), but will merely examine the net changes between compartments (i.e. a ‘system dynamics’ approach). Using this approach, we were able to identify two relevant states of equilibrium: the first (trivial) is when the hospital is empty; the second, is when there is activity. We plan to use bed usage data from a UK hospital in an attempt to validate this methodology and then assess its generalizability
Common wounds, collective healing: A phenomenological exploration of racial trauma as an outcome of experienced systemic racism in the UK
Get PDFRationale and Aims: The phenomenon of systemic racism (SR) is thought to be well understood, yet little is done to frame this concept from the perspectives of those most affected, the Global Majority (GM) populations. In the United Kingdom (UK), SR is often denied or inadequately addressed. A possible implication of this is racial trauma (RT); however, UK-based RT research is limited. This study aimed to explore how GM groups perceive SR to manifest across five UK institutional settings: education, employment, media, law enforcement and healthcare. Furthermore, the study highlighted how these experiences contribute to RT and how it presents in GM individuals in the UK. This study also explored participants’ coping strategies, acts of resistance and healing. Methods: This study utilised Interpretative Phenomenological Analysis (IPA). This incorporated the use of five focus groups and five one-to-one interviews. Sixteen GM individuals, aged 19-40 years old, participated in the study. Findings: Six superordinate and 19 sub-themes emerged, revealing unique experiences of SR and RT. Participants lived experiences of SR were characterised by institutional neglect, implicit biases, systematic exclusion and acts of resistance. The subsequent distress from these experiences aligned with existing definitions of RT. The group discourse facilitated empathy as participants made sense of their own stories and others. It was reported that focus group participation was healing. Discussion: The findings of this study reveal how SR and RT manifest in a UK context. Several frameworks are explored in relation to the findings, offering a lens to better understand SR and RT in the UK. The study offers unique insights into how SR is perceived and how this elicits RT in GM communities. The findings challenge traditional trauma frameworks and support the recognition of RT. This can inform community and clinical interventions to shape policy reforms, thereby reducing racial disparities
What is Wrong With Winner-Takes-All?
Get PDFABSTRACT
Modern market economies use competitions to distribute a range of social goods. Some theorists maintain that such competitions ought not to generate winner-takes-all outcomes. But the arguments that have been given against competitions with winner-takes-all outcomes fail to find fault with winner-takes-all outcomes per se (or so I argue). Is there, then, anything wrong with winner-takes-all outcomes? I argue that there is: winner-takes-all outcomes are wrong, in at least most distributive competitions, because they do not give people what they deserve.</jats:p
Outsourcing, offshoring and global value chains
No full textThis chapter explores how the ideas and practices associated with the disaggregation of large-scale organisations have been used as a direct consequence of dealing with the effects of worker collectivisation in single workplaces. Under high Fordism in the mid-twentieth century, unions enjoyed favourable bargaining positions due to the relative ease with which to recruit and mobilise members. Those employers with some veto power – multinationals – began disaggregating from this point on. Inspired by ‘transaction cost economics’ disaggregation began with outsourcing, then offshoring – thus furthering the difficulties for unions in collectivisation. What emerged were global value chains: international networks of production and consumption where the employer takes advantage of the ‘international division of labour’ – seeking low wages and non-unionised workforces in regimes that have low levels of employment regulation. More recently, following the consequences of these global production relocations and especially after the financial crises of 2008, deindustrialisation has brought a response from those deindustrialised areas. First, the hollowed-out local economies are subject to further race-to-the-bottom innovations under the guise of ‘flexibility’ and ‘agile’ which challenge even the notion of ‘contracts of employment’ as the basis of worker rights. Second, on the other hand, the political backlash, while nativist and xenophobic for the most part, also brings into play challenges to the whole outsourcing model, through movements such as ‘slowbalisation’
Coercive engineered migrations and environmental stress
Get PDFCountries can deliberately create, manipulate and exploit cross-border population movements to induce concessions from a target. Such ‘coercive engineered migrations’ are more likely to be successful when targeting domestically unstable states. I argue that environmental stress can add to this instability and ‘swamp’ a target’s ability to cope with cross-border population movements. Ultimately, the chances of migration-driven coercion to be successful should increase when target countries are both domestically unstable and suffer from environmental shocks. This claim is tested using quantitative data on the outcomes of coercive engineered migrations since the 1950s, which I combine with information on environmental extremes, as measured by the number of environmental disasters. Controlling for several other influences that may affect the outcome and employing sample-selection estimators that account for the non-random assignment of coercive engineered migration, the results support the argument as I show that the likelihood of successful migration-related coercion increases when domestically unstable target countries also face environmental disasters. This finding contributes to our understanding of migration as a foreign-policy instrument, it sheds new light on the role of environmental stress in international bargaining, and there are direct implications for conflict as a driver of cross-border population movements
Formal Modeling and Reliability Analysis of Hybrid System Based on Semi-continuous Colored Petri Net: A Case Study of Adaptive Cruise Control System
Get PDFNowadays, an Electronic Toll Collection (ETC) control system in highways has been widely adopted to smoothen traffic flow. However, as it is a complex business interaction system, there are inevitably flaws in its control logic process, such as the problem of vehicle fee evasion. Even we find that there are more than one way for vehicles to evade fees. This shows that it is difficult to ensure the completeness of its design. Therefore, it is necessary to adopt a novel formal method to model and analyze its design, detect flaws and modify it. In this paper, a Colored Petri net (CPN) is introduced to establish its model. To analyze and modify the system model more efficiently, a dynamic slicing method of CPN is proposed. First, a static slice is obtained from the static slicing criterion by backtracking. Second, considering all binding elements that can be enabled under the initial marking, a forward slice is obtained from the dynamic slicing criterion by traversing. Third, the dynamic slicing of CPN is obtained by taking the intersection of both slices. The proposed dynamic slicing method of CPN can be used to formalize and verify the behavior properties of an ETC control system, and the flaws can be detected effectively. As a case study, the flaw about a vehicle that has not completed the payment following the previous vehicle to pass the railing is detected by the proposed method
HybridBranchNetV2: Towards Reliable Artificial Intelligence in image classification Using Reinforcement Learning
Get PDFMany artificial intelligence (AI) algorithms struggle to adapt effectively in dynamic real-world scenarios, such as complex classification tasks and object relationship extraction, due to their predictable but non-adaptive behavior. This paper introduces HybridBranchNetV2, an optimized hybrid architecture designed to address these challenges. The key novelty of our approach lies in the integration of reinforcement learning for adaptive feature extraction and the use of graph-based techniques to analyze object relationships in complex environments. By dynamically adjusting feature extraction based on feedback from the environment, the model improves adaptability, while graph-based methods allow for a more comprehensive analysis of object relationships. Our extensive evaluations demonstrate that HybridBranchNetV2 achieves average 91.75% accuracy over four different challenging datasets. In particular, a 14% improvement obtained on the Visual Genome dataset and ImageNet 1K compared to the original HybridBranchNet model. Additional testing on CIFAR, Flowers, and ImageNet datasets revealed improvements of 6%, 1%, and 6%, respectively. These advancements not only enhance classification accuracy but also ensure efficient computation, making HybridBranchNetV2 suitable for real-time applications with minimal risk of overfitting. The proposed framework demonstrates significant improvements in adaptability, performance, and computational efficiency, addressing critical limitations in current AI models