Multiple Selves, Marginalised Voices: Exploring Black Female Psychology Students' Experiences of Constructing Identity in UK Higher Education

Introduction: What kinds of identity do Black female psychology students construct within higher education? Higher education research in the US and UK points to integration and attainment issues for Black and Minority Ethnic students. Black female students’ experiences are not fully explored among accounts of university experience. As an under researched group, their ‘stories’ risk being lost. This research learned from individual and collective voices of Black women enrolled on an undergraduate psychology degree programme at Russell Group and post-1992 London universities. Semi-structured interviews were used to explore how traditional [18-21 years at the point of enrolment] and nontraditional [22 years and above] Black female students construct identity within higher education. Theoretically driven sub-questions explored concepts such as self-efficacy and a sense of belonging. Method: A pluralistic approach was used to explore experiences. Research was carried out across four phases: in Phase 1, qualitative content analysis was used to explore the experience of nontraditional students. In Phases 2 and 4, interpretative phenomenological analysis was used for traditional students. In Phase 3, a thematic analysis was used for mixed student groups. The research drew on social constructionism and intersectionality to situate students’ experiences. The researcher acknowledged her subjectivity as a mature Black woman when interpreting students’ narratives and used reflexivity to support an authentic exploration. Findings: The participants constructed multiple identities in their academic environments. Nontraditional students constructed an identity of ‘hyphenated’ selves viewed through lenses of maturity and ethnicity. A sense of belonging was noted as crucial for their experience. Traditional students constructed ‘shifting’ selves in response to vacillating between challenges for transitioning and realising a ‘future’ self. Their multiple identities were complicated by a sense of ‘unbelonging’, social class, perceptions of structural racism, and a lack of culturally responsive support that frustrated their attempts to form interpersonal relationships with staff and students. Different theoretical/methodological approaches appeared to be most useful for understanding the experience of different student groups. Discussion: Identity construction is psychologically taxing for these participants with implications for progression and attainment in higher education. Their experiences and perceptions of constructing identities ‘at the margins’ [that is, places of invisibility/hypervisibility] shed further light on the complexity of identity construction in Black women. The findings permit reasonable and novel theoretical inferences for the academic experiences of Black female students in these samples

Four-Dimensional Neuronal Signaling by Nitric Oxide: A Computational Analysis

Nitric oxide (NO) is now recognized as a transmitter of neurons that express the neuronal isoform of the enzyme nitric oxide synthase. NO, however, violates some of the key tenets of chemical transmission, which is classically regarded as occurring at points of close apposition between neurons. It is the ability of NO to diffuse isotropically in aqueous and lipid environments that has suggested a radically different form of signaling in which the transmitter acts four-dimensionally in space and time, affecting volumes of the brain containing many neurons and synapses. Although ¿volume signaling¿ clearly challenges simple connectionist models of neural processing, crucial to its understanding are the spatial and temporal dynamics of the spread of NO within the brain. Existing models of NO diffusion, however, have serious shortcomings because they represent solutions for ¿point-sources,¿ which have no physical dimensions. Methods for overcoming these difficulties are presented here, and results are described that show how NO spreads from realistic neural architectures with both simple symmetrical and irregular shapes. By highlighting the important influence of the geometry of NO sources, our results provide insights into the four-dimensional spread of a diffusing messenger. We show for example that reservoirs of NO that accumulate in volumes of the nervous system where NO is not synthesized contribute significantly to the temporal and spatial dynamics of NO spread

Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent

Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain–body– environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour

Flexible couplings: diffusing neuromodulators and adaptive robotics

Recent years have seen the discovery of freely diffusing gaseous neurotransmitters, such as nitric oxide (NO), in biological nervous systems. A type of artificial neural network (ANN) inspired by such gaseous signaling, the GasNet, has previously been shown to be more evolvable than traditional ANNs when used as an artificial nervous system in an evolutionary robotics setting, where evolvability means consistent speed to very good solutions¿here, appropriate sensorimotor behavior-generating systems. We present two new versions of the GasNet, which take further inspiration from the properties of neuronal gaseous signaling. The plexus model is inspired by the extraordinary NO-producing cortical plexus structure of neural fibers and the properties of the diffusing NO signal it generates. The receptor model is inspired by the mediating action of neurotransmitter receptors. Both models are shown to significantly further improve evolvability. We describe a series of analyses suggesting that the reasons for the increase in evolvability are related to the flexible loose coupling of distinct signaling mechanisms, one ¿chemical¿ and one ¿electrical.

Natural Selection of Paths in Networks

We present a novel algorithm that exhibits natural selection of paths in a network. If each node and weighted directed edge has a unique identifier, a path in the network is defined as an ordered list of these unique identifiers. We take a population perspective and view each path as a genotype. If each node has a node phenotype then a path phenotype is defined as the list of node phenotypes in order of traversal. We show that given appropriate path traversal, weight change and structural plasticity rules, a path is a unit of evolution because it can exhibit multiplicative growth (i.e. change it’s probability of being traversed), and have variation and heredity. Thus, a unit of evolution need not be a spatially distinct physical individual. The total set of paths in a network consists of all possible paths from the start node to a finish node. Each path phenotype is associated with a reward that determines whether the edges of that path will be multiplicatively strengthened (or weakened). A pair-wise tournament selection algorithm is implemented which compares the reward obtained by two paths. The directed edges of the winning path are strengthened, whilst the directed edges of the losing path are weakened. Edges shared by both paths are not changed (or weakened if diversity is desired). Each time a node is activated there is a probability that the path will mutate, i.e. find an alternative route that bypasses that node. This generates the potential for a novel but correlated path with a novel but correlated phenotype. By this process the more frequently traversed paths are responsible for most of the exploration. Nodes that are inactive for some period of time are lost (which is equivalent to connections to and from them being broken). This network-based natural selection compares favourably with a standard pair-wise tournament-selection based genetic algorithm on a range of combinatorial optimization problems and continuous parametric optimization problems. The network also exhibits memory of past selective environments and can store previously discovered characters for reuse in later optimization tasks. The pathway evolution algorithm has several possible implementations and permits natural selection with unlimited heredity without template replication

Blogging the Maternal: Self-Representations of the Pregnant and Postpartum Body

This paper analyzes how dominant media images of the pregnant and postpartum body contribute to women's self-perceptions and it evaluates how the content of the blog reflects, reinforces (inadvertently) and challenges Western cultural understandings of pregnancy and mothering. Résumé Cet article analyse les images dominates des media du corps de la femme enceinte etdu corps postpartum contribuent aux perceptions que les femmes ont d'elles-même et évalue comment le contenu du blog reflète, renforce par mégarde et met au dé fi les connaissances de la culture occidentale de la grossesse et du maaternage

Reversal and Prevention of the Respiratory-Depressant Effects of Heroin by the Novel μ-Opioid Receptor Antagonist Methocinnamox in Rhesus Monkeys.

One consequence of the ongoing opioid epidemic is a large number of overdose deaths. Naloxone reverses opioid-induced respiratory depression; however, its short duration of action limits the protection it can provide. Methocinnamox (MCAM) is a novel opioid receptor antagonist with a long duration of action. This study examined the ability of MCAM to prevent and reverse the respiratory-depressant effects (minute volume [V E]) of heroin in five monkeys. MCAM (0.32 mg/kg) was given before heroin to determine whether it prevents respiratory depression; heroin dose-effect curves were generated 1, 2, 4, and 8 days later, and these effects were compared with those of naltrexone (0.032 mg/kg). Heroin dose dependently decreased V E. MCAM and naltrexone prevented respiratory depression, shifting the heroin dose-effect curve rightward at least 10-fold. MCAM, but not naltrexone, attenuated these effects of heroin for 4 days. MCAM (0.1–0.32 mg/kg) was given 30 minutes after heroin to determine whether it reverses respiratory depression; heroin dose-effect curves were generated 1, 2, 4, 8, and 16 days later, and these effects were compared with those of naloxone (0.0032–0.1 mg/kg). MCAM and naloxone reversed respiratory depression within 30 minutes, although only MCAM antagonized heroin on subsequent days. Thus, MCAM prevents and reverses respiratory depression, the potentially lethal effect of heroin, longer than opioid receptor antagonists currently in use. Because of its sustained effects, MCAM might provide more effective rescue from and protection against the fatal respiratory-depressant effects of opioids, thereby improving treatment of opioid overdose. </p

The Evolution of Reaction-diffusion Controllers for Minimally Cognitive Agents

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Studying Innovation in Businesses: New Research Possibilities

The rapid pace of globalization and technological change has created demand for more and better analysis to answer key policy questions about the role of businesses in innovation. This demand was codified into law in the America COMPETES Act. However, existing business datasets are not adequate to create an empirically based foundation for policy decisions. This paper argues that the existing IRS data infrastructure could be used in a number of ways to respond to the national imperative. It describes the legal framework within which such a response could take place, and outlines the organizational features that would be required to establish an IRS/researcher partnership. It concludes with a discussion of the role for the research policy community.Business microdata, innovation, confidentiality, researcher access, tax policy

Solving graph connectivity problems on JAGs

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaf 53).by Parry Husbands.M.S