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Gender, prison and reentry experiences : a matter of time
No full text"This book explores the unique reentry experiences of incarcerated men and women who are about to be released from prisons in Portugal. By analysing gendered reentry experiences through the narratives of men and women, Gender, Prison and Reentry Experiences sheds light on current practices and strategies adopted in prisons regarding reentry and examines the structural, institutional, and personal barriers that influence the reentry outcome. Gender, Prison and Reentry Experience examines the narratives built around an individual's prison experiences, their perception of the prison's impact on reentry, and their expectations after release. It reveals how men and women narrate and attribute meaning to their time in prison and how they navigate their 'prisoner' and 'gendered' identities. In doing so, this book demonstrates the importance of these identities in relation to recidivism and desistance, whilst also questioning the role incarceration has in further criminalising and obstructing an individuals' reentry process. It puts forward recommendations that aim to improve the lives of all incarcerated individuals within the current system, in addition to advocating for decarceration and prison abolition. It presents a novel contribution to the internationalisation of knowledge across multiple disciplinary subfields, namely critical reentry studies and feminist criminology, filling a gap in the current knowledge as few studies focus on prison experiences as a core aspect of understanding the reentry process. An accessible and compelling read, this book will appeal to students and scholars of criminology, sociology, law, desistance studies, and those interested in gaining a unique insight into the experience of incarcerated individuals"-- Provided by publishe
Mapping orthorhombic domains with geometrical phase analysis in rare-earth nickelate heterostructures
No full textMost perovskite oxides belong to the Pbnm space group, composed of an anisotropic unit cell, A-site antipolar displacements, and oxygen octahedral tilts. Mapping the orientation of the orthorhombic unit cell in epitaxial heterostructures that consist of at least one Pbnm compound is often needed for understanding and controlling the different degrees of coupling established at their coherent interfaces and, therefore, their resulting physical properties. However, retrieving this information from the strain maps generated with high-resolution scanning transmission electron microscopy can be challenging, because the three pseudocubic lattice parameters are very similar in these systems. Here, we present a novel methodology for mapping the crystallographic orientation in Pbnm systems. It makes use of the geometrical phase analysis algorithm, as applied to aberration-corrected scanning transition electron microscopy images, but in an unconventional way. The method is fast and robust, giving real-space maps of the lattice orientations in Pbnm systems, from both cross section and plan-view geometries, and across large fields of view. As an example, we apply our methodology to rare-earth nickelate heterostructures, in order to investigate how the crystallographic orientation of these films depends on various structural constraints that are imposed by the underlying single crystal substrates. We observe that the resulting domain distributions and associated defect landscapes mainly depend on a competition between the epitaxial compressive/tensile and shear strains, together with the matching of atomic displacements at the substrate/film interface. The results point toward strategies for controlling these characteristics by appropriate substrate choice
Scaling limit of an adaptive contact process
No full textWe introduce and study an interacting particle system evolving on the d-dimensional torus (Z/NZ)d. Each vertex of the torus can be either empty or occupied by an individual of type λ∈(0,∞). An individual of type λ dies with rate one and gives birth at each neighboring empty position with rate λ; moreover, when the birth takes place, the newborn individual is likely to have the same type as the parent but has a small probability of being a mutant. A mutant child of an individual of type λ has type chosen according to a probability kernel. We consider the asymptotic behavior of this process when N→∞ and, simultaneously, the mutation probability tends to zero fast enough that mutations are sufficiently separated in time so that the amount of time spent on configurations with more than one type becomes negligible. We show that, after a suitable time scaling and deletion of the periods of time spent on configurations with more than one type, the process converges to a Markov jump process on
(0,∞), whose rates we characteriz
A study on auto‐catalysis and product inhibition : a nucleophilic aromatic substitution reaction catalysed within the cavity of an octanuclear coordination cage
Get PDFThe ability of an octanuclear cubic coordination cage to catalyse a nucleophilic aromatic substitution reaction on a cavity‐bound guest was studied with 2,4‐dinitrofluorobenzene (DNFB) as the guest/substrate. It was found that DNFB undergoes a catalysed reaction with hydroxide ions within the cavity of the cubic cage (in aqueous buffer solution, pH 8.6). The rate enhancement of kcat/kuncat was determined to be 22, with cavity binding of the guest being required for catalysis to occur. The product, 2,4‐dinitrophenolate (DNP), remained bound within the cavity due to electrostatic stabilisation and exerts two apparently contradictory effects: it initially auto‐catalyses the reaction when present at low concentrations, but at higher concentrations inhibits catalysis when a pair of DNP guests block the cavity. When encapsulated, the UV/Vis absorption spectrum of DNP is red‐shifted when compared to the spectrum of free DNP in aqueous solution. Further investigations using other aromatic guests determined that a similar red‐shift on cavity binding also occurred for 4‐nitrophenolate (4NP) at pH 8.6. The red‐shift was used to determine the stoichiometry of guest binding of DNP and 4NP within the cage cavity, which was confirmed by structural analysis with X‐ray crystallography; and was also used to perform catalytic kinetic studies in the solution‐state
Can empathy provide a route to democratic inclusivity?
Get PDFHow can democracies promote full consideration of all relevant interests in political decision-making? Is there a role for empathy, especially where there are obstacles to direct inclusion of relevant groups, as for example in the case of future generations and citizens of other countries? Critics of existing uses of empathy in political theory press that limits to our capacity to empathise can lead to bias and partiality. I argue instead for a more nuanced ‘holistic’ approach to the use of empathy into democratic design. The approach recommends, first, that we be sensitive to the potential consequences of catalysing empathy in specific decision-making contexts, rather than making general prescriptions. Second, it asks us to consider how different methods of empathic induction generate insight and motivation of different strength and degrees of generality. Third, the approach proposes not only that empathy be introduced into existing institutions and designs, but that we aim through democratic design to bring patterns of power into closer alignment with naturally occurring patterns of empathy. Fourth, the approach recommends taking a pragmatic view of which interventions might be most useful in any particular institutional context
PSO-tuned variable forgetting factor recursive least square estimation of 2RC equivalent circuit model parameters for lithium-ion batteries
No full textTo improve the accuracy of Equivalent Circuit Models (ECM) for Electric Vehicles (EV) applications, parameter identification approaches based on Recursive Least Squares (RLS) filters have been proposed. The Variable Forgetting Factor RLS (VFFRLS) algorithms are regarded as one of the most accurate parameter identification methods for lithium-ion batteries. Commonly, a fixed forgetting factor is utilized with a conventional RLS to improve the accuracy, however, this algorithm fails to keep up with a real-time deviation in the environment. In this paper, a Particle Swarm Optimization (PSO) technique is presented for identifying the optimal VFFRLS parameters to compromise between identification accuracy and stability. The proposed method is applied on a second-order Thevenin model that is extensively utilized for Battery Management Systems (BMS) using MATLAB/Simulink software for a commercially available grade pouch cell
Validating the Fitbit Charge 4© wearable activity monitor for use in physical activity interventions
No full textCommercially available wearable activity monitors can promote physical activity behaviour. Clinical trials typically quantify physical activity with research grade activity monitors prior to testing interventions utilising commercially available wearable activity monitors aimed at increasing step count. Therefore, it is important to test the agreement of these two types of activity monitors. Observational. Thirty adults (20-65 years, n = 19 females) were provided a Fitbit Charge 4©. To determine reliability using an intraclass correlation coefficient, two, one-minute bouts of treadmill walking were performed at a self-selected pace. Subsequently, participants wore both an ActiGraph wGT3X-BT and the Fitbit for seven days. To determine agreement, statistical equivalence and the mean absolute percentage error were calculated and represented graphically with a Bland-Altman plot. Ordinary least products regression was performed to identify fixed or proportional bias. The Fitbit showed 'good' step count reliability on the treadmill (intraclass correlation coefficient = 0.75, 95 % CI = 0.53-0.87, p < 0.001). In free-living however, it overestimated step count when compared to the ActiGraph wGT3X-BT (mean absolute percentage error = 26.02 % ± 14.63). Measurements did not fall within the ± 10 % equivalence region and proportional bias was apparent (slope 95 % CI = 1.09-1.35). The Fitbit Charge 4© is reliable when measuring step count on a treadmill. However, there is an overestimation of daily steps in free-living environments which may falsely indicate compliance with physical activity recommendations
Virtual category learning : a semi-supervised learning method for dense prediction with extremely limited labels
No full textDue to the costliness of labelled data in real-world applications, semi-supervised learning, underpinned by pseudo labelling, is an appealing solution. However, handling confusing samples is nontrivial: discarding valuable confusing samples would compromise the model generalisation while using them for training would exacerbate the issue of confirmation bias caused by the resulting inevitable mislabelling. To solve this problem, this paper proposes to use confusing samples proactively without label correction. Specifically, a Virtual Category (VC) is assigned to each confusing sample in such a way that it can safely contribute to the model optimisation even without a concrete label. This provides an upper bound for inter-class information sharing capacity, which eventually leads to a better embedding space. Extensive experiments on two mainstream dense prediction tasks — semantic segmentation and object detection, demonstrate that the proposed VC learning significantly surpasses the state-of-the-art, especially when only very few labels are available. Our intriguing findings highlight the usage of VC learning in dense vision tasks