A Model for Contextualizing Natural Language Discourse

This paper describes a computational model of semantic processing in natural language discourse understanding based on the distribution of knowledge over multiple spaces as proposed by Fauconnier (1985), Dinsmore (1987a), K a m p (1980), Johnson-Laird (1985) and others. Among the claims made about such a partitioned representation of knowledge are the following: First, it promotes a more direct, more natural mapping from surface discourse sentence to internal representation. Second, it supports more efficient reasoning and retrieval processes over that internal representation. Finally, it provides an accurate account of many of the most recalcitrant problems in natural language discourse understanding. Among these are implicit information, presupposition, referential opacity, tense and aspect, and common-sense reasoning in complex domains. The model identifies two fundamental levels of semantic processing: contextualization, in which an appropriate space for assimilating the information conveyed in a discourse sentence is located, and construction, in which the information is actually assimilated into that space. Contextualization allows the full semantics of the discourse to be realized implicitly in the internal representation. It also accounts for the use of moods, tenses, and various adverbials in discourse. The interaction of the contextualization processes with the semantics of aspectual operators provides an account of the discourse use of aspect

Localization of metal ions in DNA

M-DNA is a novel complex formed between DNA and transition metal ions under alkaline conditions.  The unique properties of M-DNA were manipulated in order to rationally place metal ions at specific regions within a double-stranded DNA helix.   Investigations using thermal denaturation profiles and the ethidium fluorescence assay illustrate that the pH at which M-DNA formation occurs is influenced heavily by the DNA sequence and base composition.  For instance, DNA with a sequence consisting of poly[d(TG)•d(CA)] is completely converted to M-DNA at pH 7.9 while DNA consisting entirely of poly[d(AT)] remains in the B-DNA conformation until a pH of 8.6 is reached.  The pH at which M-DNA formation occurs is further decreased by the incorporation of 4-thiothymine (s4T).  DNA oligomers with a mixed sequence composed of half d(AT) and the other half d(TG)•d(CA) showed that only 50% of the DNA is able to incorporate Zn2+ ions at pH 7.9.  This suggests that only regions corresponding to the tracts of d(TG)•d(CA) are being transformed.   Duplex DNA monolayers were self-assembled on gold through a Au-S linkage and both B- and M-DNA conformations were studied using X-ray photoelectron spectroscopy (XPS) in order to better elucidate the location of the metal ions.  The film thickness, density, elemental composition and ratios for samples were analyzed and compared.  The DNA surface coverage, calculated from both XPS and electrochemical measurements, was approximately 1.2 x 1013 molecules/cm2 for B-DNA.  All samples showed distinct peaks for C 1s, O 1s, N 1s, P 2p and S 2p as expected for a thiol-linked DNA.  On addition of Zn2+ to form M-DNA the C 1s, P 2p and S 2p showed only small changes while both the N 1s and O 1s spectra changed considerably.  This result is consistent with Zn2+ interacting with oxygen on the phosphate backbone as well as replacing the imino protons of thymine (T) and guanine (G) in M-DNA.   Analysis of the Zn 2p spectra also demonstrated that the concentration of Zn2+ present under M-DNA conditions is consistent with Zn2+ binding to both the phosphate backbone as well as replacing the imino protons of T or G in each base pair.  After the M-DNA monolayer is washed with a buffer containing only Na+ the Zn2+ bound to the phosphate backbone is removed while the Zn2+ bound internally still remains. Variable angle x-ray photoelectron spectroscopy (VAXPS) was also used to examine monolayers consisting of mixed sequence oligomers.  Preliminary results suggest that under M-DNA conditions, the zinc to phosphate ratio changes relative to the position of the d(TG)•d(CA) tract being at the top or bottom of the monolayer.    Electrochemistry was also used to investigate the properties of M-DNA monolayers on gold and examine how the localization of metal ions affects the resistance through the DNA monolayer.  The effectiveness of using the IrCl62-/3- redox couple to investigate DNA monolayers and the potential advantages of this system over the standard Fe(CN)63-/4- redox couple are demonstrated.  B-DNA monolayers were converted to M-DNA by incubation in buffer containing 0.4 mM Zn2+ at pH 8.6 and studied by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA) with IrCl62-/3-.   Compared to B-DNA, M-DNA showed significant changes in CV, EIS and CA spectra.  However, only small changes were observed when the monolayers were incubated in Mg2+ at pH 8.6 or in Zn2+ at pH 6.0.  The heterogeneous electron-transfer rate (kET) between the redox probe and the surface of a bare gold electrode was determined to be 5.7 x 10-3 cm/s.  For a B-DNA modified electrode, the kET through the monolayer was too slow to be measured.  However, under M-DNA conditions, a kET of 1.5 x 10-3 cm/s was reached.  As well, the percent change in resistance to charge transfer (RCT), measured by EIS, was used to illustrate the dependence of M-DNA formation on pH.  This result is consistent with Zn2+ ions replacing the imino protons on thymine and guanine residues.  Also, at low pH values, the percent change in RCT seems to be greater for d(TG)15•d(CA)15 compared to oligomers with mixed d(AT) and d(TG)•d(CA) tracts.  The IrCl62-/3- redox couple was also effective in differentiating between single-stranded and double-stranded DNA during dehybridization and rehybridization experiments.

Intellectual Disability and Assistive Technology: Opening the GATE Wider

The World Health Organization has launched a program to promote Global Cooperation on Assistive Technology (GATE). The objective of the GATE program is to improve access to high quality, affordable assistive technology for people with varying disabilities, diseases, and age-related conditions. As a first step, GATE has developed the assistive products list, a list of priority assistive products based on addressing the greatest need at population level. A specific group of people who can benefit from user appropriate assistive technology are people with intellectual disabilities. However, the use of assistive products by people with intellectual disabilities is a neglected area of research and practice, and offers considerable opportunities for the advancement of population health and the realization of basic human rights. It is unknown how many people with intellectual disabilities globally have access to appropriate assistive products and which factors influence their access. We call for a much greater focus on people with intellectual disabilities within the GATE program. We present a framework for understanding the complex interaction between intellectual disability, health and wellbeing, and assistive technology

Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial

Background:Multiple chronic conditions (multimorbidity) are becomingmore prevalent among aging populations. Digital health technologies have thepotential to assist in the self-management of multimorbidity, improving theawareness and monitoring of health and well-being, supporting a betterunderstanding of the disease, and encouraging behavior change.Objective:The aim of this study was to analyze how 60 older adults(mean age 74, SD 6.4; range 65-92 years) with multimorbidity engaged withdigital symptom and well-being monitoring when using a digital health platformover a period of approximately 12 months. Methods:Principal component analysis and clustering analysis wereused to group participants based on their levels of engagement, and the dataanalysis focused on characteristics (eg, age, sex, and chronic healthconditions), engagement outcomes, and symptom outcomes of the differentclusters that were discovered.Results:Three clusters were identified: the typical user group, theleast engaged user group, and the highly engaged user group. Our findings showthat age, sex, and the types of chronic health conditions do not influenceengagement. The 3 primary factors influencing engagement were whether the samedevice was used to submit different health and well-being parameters, thenumber of manual operations required to take a reading, and the daily routineof the participants. The findings also indicate that higher levels ofengagement may improve the participants’ outcomes (eg, reduce symptomexacerbation and increase physical activity).Conclusions:The findings indicate potential factors that influence olderadult engagement with digital health technologies for home-based multimorbidityself-management. The least engaged user groups showed decreased health andwell-being outcomes related to multimorbidity self-management. Addressing thefactors highlighted in this study in the design and implementation ofhome-based digital health technologies may improve symptom management andphysical activity outcomes for older adults self-managing multimorbidity.</p

Building a Risk Model for the Patient-centred Care of Multiple Chronic Diseases

With the increase of multimorbidity due to population ageing, managing multiple chronic health conditions is a rising challenge. Machine-learning can contribute to a better understanding of persons with multimorbidity (PwMs) and how to design an effective framework of care and support for them. We present a risk model of older PwMs that was derived from the TILDA dataset, a longitudinal study of the ageing Irish population. This model is based on a 26-nodes Bayesian network that represents patients possibly having one or more chronic conditions among diabetes, chronic obstructive pulmonary disease and arthritis, through a joint probability distribution of demographic, symptomatic and behavioral dimensions. We describe our method, give an exploratory analysis of the risk model, and assess its prediction accuracy in a cross-validation experiment. Finally we discuss its use in supporting management of care for PwMs, drawing on comments from health practitioners on the model

Home-based Digital Health Technologies for Older Adults to Self-Manage Multiple Chronic Conditions: A Data-Informed Analysis of User Engagement from a Longitudinal Trial

BACKGROUND: Ageing populations are resulting in higher prevalence of people with multiple chronic conditions (multimorbidity). Digital health platforms have great potential to support self-management of multimorbidity, increasing a person's awareness of their health and well-being, supporting a better understanding of diseases and encouraging behaviour change. However, little research has explored the long-term engagement of older adults with such digital interventions. METHODS: The aim of this study is to analyse how 60 older adults with multimorbidity engaged with digital symptom and well-being monitoring through a digital health platform over a period of approximately 12 months. Data analysis focused on user retention, frequency of monitoring, intervals in monitoring and patterns of daily engagement. RESULTS: Our findings show that the overall engagement with the digital health platform was high, with more than 80% of participants using the technology devices for over 200 days. The submission frequency for symptom parameters (e.g. blood glucose (BG), blood pressure (BP), etc.) was between three and four times per week which was higher than that of self-report (2.24) and weight (2.84). Submissions of exercise (6.12) and sleep (5.67) were more frequent. The majority of interactions happened in the morning time. The most common time of submission for symptom parameters was 10 am, whereas 8 am was the most common time for weight measurements. CONCLUSIONS: The findings indicate the patterns of engagement of older adults with complex chronic diseases with digital home-based self-management systems