Being present in caring encounters : a relational perspective on autonomy for older persons in municipal home help services

The care of the old in Sweden and worldwide is developing towards an “aging in place.” Older people in Sweden are expected to remain in their own homes supported by municipal home help services. This development has entailed that older people’s need of support as well professional carers workload has increased. The older persons need of support is assessed by care managers, and research shows that they are in an exposed position when applying and often do not have their preferences met. In addition research also shows professional carers’ difficulties in the care of the old and their need for support. The suggestion is a relational perspective in the care of the old to promote older persons’ autonomy due to their increased dependency. Up until now there has been little research into older peoples’ experiences of autonomy in municipal home help services. This thesis was therefore considered important to enhance knowledge and understanding of older persons’ and their professional carers’ lived experiences in everyday life. The overall aim of this thesis was to develop knowledge of older persons’ opportunities to make independent decisions and to consider how professional carers can help them to improve their independence. This thesis compromise four studies (I-IV) and has a qualitative and a live world approach. In order to deepen the understanding of the meaning of older persons’ and professional carers’ experiences they were followed over time. Interviews have been conducted with older persons and professional carers before, during and after the professional carers participated in an educational programme. Data was analysed I-IV with a phenomenological hermeneutic method. The aim of study I was to illuminate the meaning of older persons’ dependence on caregivers’ help and of their opportunity to make independent decisions. The findings reveal that they are either struggling to make independent decisions or resigning themselves to not being able to do so. The aim of study II was to illuminate the meaning of carers’ experiences of being in caring situations when a conflict of interest arises with the older person receiving care. The finding reveals that they are ambivalent in conflict situations, weighing older persons’ right to self-determination against external demands. The aim of study III was to illuminate the meaning of older persons’ independent decision making concerning their daily care. The findings revealed how they live with uncertainty as to how to relate to independence and dependence with regard to themselves and others, and how they try to comprehend everyday life. The aim of study IV was to illuminate the meaning of professional carers’ experiences of supporting older persons’ to make independent decisions in caring situations. The findings revealed that they are being torn between respecting independence and dependence and it is therefore complicated to support older persons to make independent decisions. A deeper understanding was reached considering the findings I-IV and disclosed; waiting for others to comprehend their everyday life, torn between external and internal demands and striving for interdependency in caring encounters. The conclusion of this thesis is that a relational perspective on autonomy as a shared-decision making could be valuable in the care of the old to enable for professional carers to support older persons in making independent decisions. The implication for practice is a person-centred care in the care of the old to promote a relational perspective on autonomy

Towards practical and provable domain adaptation

One of the most central questions in statistical modeling is how well a model will generalize. Absent strong assumptions we find that this question is difficult to answer in a meaningful way. In this work we seek to increase our understanding of the domain adaptation setting through two different lenses. First, we investigate whether tractably computable and tight generalization bounds on the performance of neural network classifiers exist in the current literature. The tightest bounds we find use a portion of the input data to tighten the gap between measured performance and the calculated bound. We present evaluations of four bounds using this tightening method on classifiers applied to image classification tasks: Two bounds from the literature in addition to two of our own construction. Further, we find that for situations lacking domain overlap, the existing literature lacks the tools to achieve tight, tractably computable bounds for the neural network models which we use. We conclude that a new approach might be needed. In the second part we therefore consider a setting where we change our underlying assumptions to ones which might be more plausible. This setting, based on learning using privileged information, is shown to result in consistent learning. We also show empirical gains over comparable methods when our assumptions are likely to hold, both in terms of performance and sample efficiency. In summary, the work set out herein has been a first step towards a better understanding of domain adaptation and how using data and new assumptions can help us further our knowledge about this topic

Nyquist Stability Analysis of an AC-Grid Connected VSC-HVDC System Using a Distributed Parameter DC Cable Model

In this paper, a two-terminal VSC-HVDC system embedded in a weak grid ac environment is considered, emphasizing modeling, controller design, and small-signal stability analysis. Traditionally, the dc cable is modeled by \Pi -sections, implying that care has to be taken when using the model for higher frequencies or in cases of higher cable impedance density, such as submarine cables. Here, a distributed parameter cable model is used to overcome this problem. The VSC-HVDC system can be described as two cascaded blocks. The first block is a transfer function that will differ depending on what input and output variables are considered, but which is in all realistic cases stable. The second block is a feedback loop, where the forward path is a rational function and the return path is a dissipative infinite dimensional function, remaining the same in all cases. The stability is then analyzed, using the Nyquist criterion, in a straightforward manner. Numerical examples are given by the use of MATLAB. The result is that if the VSC-HVDC system using a single \Pi -section cable model is stable, so is the VSC-HVDC system using a distributed parameter cable model

Enthymemes and Topoi in Dialogue

In Enthymemes and Topoi in Dialogue, Ellen Breitholtz presents a novel and precise account of reasoning from an interactional perspective. The account draws on the concepts of enthymemes and topoi, originating in Aristotelian rhetoric and dialectic, and integrates these in a formal dialogue semantic account using TTR, a type theory with records. Argumentation analysis and formal approaches to reasoning often focus the logical validity of arguments on inferences made in discourse from a god’s-eye perspective. In contrast, Breitholtz’s account emphasises the individual perspectives of interlocutors and the function and acceptability of their reasoning in context. This provides an analysis of interactions where interlocutors have access to different topoi and therefore make different inferences. Readership: All interested in the pragmatics-rhetoric interface and in theories of meaning and coherence in dialogue and discourse

Practicality of generalization guarantees for unsupervised domain adaptation with neural networks

Understanding generalization is crucial to confidently engineer and deploy machine learningmodels, especially when deployment implies a shift in the data domain. For such domainadaptation problems, we seek generalization bounds which are tractably computable andtight. If these desiderata can be reached, the bounds can serve as guarantees for adequateperformance in deployment. However, in applications where deep neural networks are themodels of choice, deriving results which fulfill these remains an unresolved challenge; mostexisting bounds are either vacuous or has non-estimable terms, even in favorable conditions.In this work, we evaluate existing bounds from the literature with potential to satisfy ourdesiderata on domain adaptation image classification tasks, where deep neural networks arepreferred. We find that all bounds are vacuous and that sample generalization terms accountfor much of the observed looseness, especially when these terms interact with measures ofdomain shift. To overcome this and arrive at the tightest possible results, we combine eachbound with recent data-dependent PAC-Bayes analysis, greatly improving the guarantees.We find that, when domain overlap can be assumed, a simple importance weighting extensionof previous work provides the tightest estimable bound. Finally, we study which termsdominate the bounds and identify possible directions for further improvement

Finite-time state-constrained optimal control for input-affine systems with actuator noise

Abstract: We show that a linearizing transformation of the Hamilton-Jacobi-Bellman (HJB) equation can be applied to certain finite-time problem such that the time dependence can be separated and also has a simple analytical solution. The remaining state dependence is the solution to a linear eigenvalue problem that may have an analytical solution or is readily solved numerically. The efficiency of the method is illustrated by an inventory control problem

Solving the Hamilton-Jacobi-Bellman Equation for a Stochastic System with State Constraints

We present a method for solving the Hamilton-Jacobi-Bellman (HJB) equation for a stochastic system with state constraints. A variable transformation is introduced which turns the HJB equation into a combination of a linear eigenvalue problem, a set of partial differential equations (PDE:s), and a point-wise equation. For a fixed solution to the eigenvalue problem, the PDE:s are linear and the point-wise equation is quadratic, indicating that the problem can be solved efficiently using an iterative scheme. As an example, we numerically solve for the optimal control of a Linear Quadratic Gaussian (LQG) system with state constraints. A reasonably accurate solution is obtained even with a very small number of collocation points (three in each dimension), which suggests that the method could be used on high order systems, mitigating the curse of dimensionality

Temperature and food quantity effects on the harpacticoid copepod Nitocra spinipes : combining in vivo bioassays with population modeling

The harpacticoid copepod Nitocra spinipes has become a popular model species for toxicity testing over the past few decades. However, the combined influence of temperature and food shortage, two climate change-related stressors, has never been assessed in this species. Consequently, effects of three temperatures (15, 20 and 25˚C) and six food regimes (between 0 and 5 × 10^5 algal cells/mL) on the life cycle of N. spinipes were examined in this study. Similarly to other copepod species, development times and brood sizes decreased with rising temperatures. Mortality was lowest in the 20˚C temperature setup, indicating a close-by temperature optimum for this species. Decreasing food concentrations led to increased development times, higher mortality and a reduction in brood size. A sex ratio shift toward more females per male was observed for increasing temperatures, while no significant relationship with food concentration was found. Temperature and food functions for each endpoint were integrated into an existing individual-based population model for N. spinipes which in the future may serve as an extrapolation tool in environmental risk assessment. The model was able to accurately reproduce the experimental data in subsequent verification simulations. We suggest that temperature, food shortage, and potentially other climate change-related stressors should be considered in environmental risk assessment of chemicals to account for non-optimal exposure conditions that may occur in the field. Furthermore, we advocate combining in vivo bioassays with population modeling as a cost effective higher tier approach to assess such considerations

Optimal Control of a Batch Reactor Using the Linearized Hamilton-Jacobi-Bellman Equation

AbstractIn this work we present an efficient method for solving an optimal control problem for a batch reactor, where a temperature dependent exothermic reaction takes place within a preset duration and within specified temperature bounds. The Hamilton-Jacobi-Bellman (HJB) equation corresponding to the optimal control problem is nonlinear and has infinite boundary conditions due to the state constraints (bounds on temperature and concentration), which makes it troublesome to solve. However, using a logarithmic transformation, the HJB-equation is transformed into a linear partial differential equation with zero boundary conditions. Furthermore, the problem can then be solved using variable separation such that the time- dependent part has an analytical solution and the state dependent part becomes a linear eigenvalue problem which can readily be solved using standard software