Incapacitous patients, assisted reproductive technology, and the importance of informed consent

This is the author accepted manuscript. The final version is available from Cambridge University Press via the DOI in this recordThe principle of self-determination has gained significant judicial support over the last three decades, and the choice to procreate using assisted reproductive technology is a clear example of our right to choose a treatment that enhances our personal lives. The Human Fertilisation and Embryology Act 1990 (as amended in 2008) stipulates that each party must give written, informed consent to ensure that our reproductive materials are used within strict parameters. However, the growing number of posthumous conception cases in several jurisdictions has raised concerns, particularly in situations where gametes are extracted from incapacitous patients without their consent, leading to posthumous parenthood. The landmark case of Y v A Healthcare NHS Trust [2018] EWCOP 18 caused significant concern when it authorised the retrieval, storage and use of sperm from a suspected brain stem dead man for procreative purposes under the Mental Capacity Act 2005. It has never been known to be in the ‘best interests’ of a patient who lacks capacity to procreate in English law, and the consequences of this decision could be highly significant, raising questions about the exploitation of incapacitous patients and the misuse of genetic material. The decision has since been confirmed as the correct approach by the Court of Protection in Re X (Catastrophic Injury: Collection and Storage of Sperm) [2022] EWCOP 48, and a public consultation has now been opened by the Human Fertilisation and Embryology Authority. This paper examines the rigorous consent regime of the 1990 Act and the ethical complexities of retrieving gametes from incapacitous patients for procreative purposes. It will be determined that the 1990 Act's preference for a rigorous consent regime for public policy reasons is appropriate, and any alternative forms of consent could open a slippery slope to the unethical use of vulnerable individuals for their reproductive materials

Using Strategy Improvement to Stay Alive

We design a novel algorithm for solving Mean-Payoff Games (MPGs). Besides solving an MPG in the usual sense, our algorithm computes more information about the game, information that is important with respect to applications. The weights of the edges of an MPG can be thought of as a gained/consumed energy -- depending on the sign. For each vertex, our algorithm computes the minimum amount of initial energy that is sufficient for player Max to ensure that in a play starting from the vertex, the energy level never goes below zero. Our algorithm is not the first algorithm that computes the minimum sufficient initial energies, but according to our experimental study it is the fastest algorithm that computes them. The reason is that it utilizes the strategy improvement technique which is very efficient in practice

A Neurosemantic Theory of Concrete Noun Representation Based on the Underlying Brain Codes

This article describes the discovery of a set of biologically-driven semantic dimensions underlying the neural representation of concrete nouns, and then demonstrates how a resulting theory of noun representation can be used to identify simple thoughts through their fMRI patterns. We use factor analysis of fMRI brain imaging data to reveal the biological representation of individual concrete nouns like apple, in the absence of any pictorial stimuli. From this analysis emerge three main semantic factors underpinning the neural representation of nouns naming physical objects, which we label manipulation, shelter, and eating. Each factor is neurally represented in 3–4 different brain locations that correspond to a cortical network that co-activates in non-linguistic tasks, such as tool use pantomime for the manipulation factor. Several converging methods, such as the use of behavioral ratings of word meaning and text corpus characteristics, provide independent evidence of the centrality of these factors to the representations. The factors are then used with machine learning classifier techniques to show that the fMRI-measured brain representation of an individual concrete noun like apple can be identified with good accuracy from among 60 candidate words, using only the fMRI activity in the 16 locations associated with these factors. To further demonstrate the generativity of the proposed account, a theory-based model is developed to predict the brain activation patterns for words to which the algorithm has not been previously exposed. The methods, findings, and theory constitute a new approach of using brain activity for understanding how object concepts are represented in the mind

On fractionality of the path packing problem

In this paper, we study fractional multiflows in undirected graphs. A fractional multiflow in a graph G with a node subset T, called terminals, is a collection of weighted paths with ends in T such that the total weights of paths traversing each edge does not exceed 1. Well-known fractional path packing problem consists of maximizing the total weight of paths with ends in a subset S of TxT over all fractional multiflows. Together, G,T and S form a network. A network is an Eulerian network if all nodes in N\T have even degrees. A term "fractionality" was defined for the fractional path packing problem by A. Karzanov as the smallest natural number D so that there exists a solution to the problem that becomes integer-valued when multiplied by D. A. Karzanov has defined the class of Eulerian networks in terms of T and S, outside which D is infinite and proved that whithin this class D can be 1,2 or 4. He conjectured that D should be 1 or 2 for this class of networks. In this paper we prove this conjecture.Comment: 18 pages, 5 figures in .eps format, 2 latex files, main file is kc13.tex Resubmission due to incorrectly specified CS type of the article; no changes to the context have been mad

Improved model identification for non-linear systems using a random subsampling and multifold modelling (RSMM) approach

In non-linear system identification, the available observed data are conventionally partitioned into two parts: the training data that are used for model identification and the test data that are used for model performance testing. This sort of 'hold-out' or 'split-sample' data partitioning method is convenient and the associated model identification procedure is in general easy to implement. The resultant model obtained from such a once-partitioned single training dataset, however, may occasionally lack robustness and generalisation to represent future unseen data, because the performance of the identified model may be highly dependent on how the data partition is made. To overcome the drawback of the hold-out data partitioning method, this study presents a new random subsampling and multifold modelling (RSMM) approach to produce less biased or preferably unbiased models. The basic idea and the associated procedure are as follows. First, generate K training datasets (and also K validation datasets), using a K-fold random subsampling method. Secondly, detect significant model terms and identify a common model structure that fits all the K datasets using a new proposed common model selection approach, called the multiple orthogonal search algorithm. Finally, estimate and refine the model parameters for the identified common-structured model using a multifold parameter estimation method. The proposed method can produce robust models with better generalisation performance

Simulation of the Zero Temperature Behavior of a 3-Dimensional Elastic Medium

We have performed numerical simulation of a 3-dimensional elastic medium, with scalar displacements, subject to quenched disorder. We applied an efficient combinatorial optimization algorithm to generate exact ground states for an interface representation. Our results indicate that this Bragg glass is characterized by power law divergences in the structure factor $S(k)\sim A k^{-3}$. We have found numerically consistent values of the coefficient $A$ for two lattice discretizations of the medium, supporting universality for $A$ in the isotropic systems considered here. We also examine the response of the ground state to the change in boundary conditions that corresponds to introducing a single dislocation loop encircling the system. Our results indicate that the domain walls formed by this change are highly convoluted, with a fractal dimension $d_f=2.60(5)$. We also discuss the implications of the domain wall energetics for the stability of the Bragg glass phase. As in other disordered systems, perturbations of relative strength $\delta$ introduce a new length scale $L^* \sim \delta^{-1/\zeta}$ beyond which the perturbed ground state becomes uncorrelated with the reference (unperturbed) ground state. We have performed scaling analysis of the response of the ground state to the perturbations and obtain $\zeta = 0.385(40)$. This value is consistent with the scaling relation $\zeta=d_f/2- \theta$, where $\theta$ characterizes the scaling of the energy fluctuations of low energy excitations.Comment: 20 pages, 13 figure

Variations on the Stochastic Shortest Path Problem

In this invited contribution, we revisit the stochastic shortest path problem, and show how recent results allow one to improve over the classical solutions: we present algorithms to synthesize strategies with multiple guarantees on the distribution of the length of paths reaching a given target, rather than simply minimizing its expected value. The concepts and algorithms that we propose here are applications of more general results that have been obtained recently for Markov decision processes and that are described in a series of recent papers.Comment: Invited paper for VMCAI 201

Cognitive Information Processing

Contains reports on three research projects.Center for Advanced Television StudiesAmerican Broadcasting CompanyAmpex CorporationColumbia Broadcasting Systems (until 5/86)Harris Corporation (until 5/86)Home Box OfficeKodak (from 1/87)Public Broadcasting ServiceNational Broadcasting CompanyRCA CorporationTektronixZenith (from 5/86)3M Company (until 5/86)International Business Machines, Inc.Defense Advanced Research Agency (Contract N00014-85-K-0213

Revealing components of the galaxy population through nonparametric techniques

The distributions of galaxy properties vary with environment, and are often multimodal, suggesting that the galaxy population may be a combination of multiple components. The behaviour of these components versus environment holds details about the processes of galaxy development. To release this information we apply a novel, nonparametric statistical technique, identifying four components present in the distribution of galaxy H$\alpha$ emission-line equivalent-widths. We interpret these components as passive, star-forming, and two varieties of active galactic nuclei. Independent of this interpretation, the properties of each component are remarkably constant as a function of environment. Only their relative proportions display substantial variation. The galaxy population thus appears to comprise distinct components which are individually independent of environment, with galaxies rapidly transitioning between components as they move into denser environments.Comment: 12 pages, 10 figures, accepted for publication in MNRA