A layered abduction model of perception: Integrating bottom-up and top-down processing in a multi-sense agent

A layered-abduction model of perception is presented which unifies bottom-up and top-down processing in a single logical and information-processing framework. The process of interpreting the input from each sense is broken down into discrete layers of interpretation, where at each layer a best explanation hypothesis is formed of the data presented by the layer or layers below, with the help of information available laterally and from above. The formation of this hypothesis is treated as a problem of abductive inference, similar to diagnosis and theory formation. Thus this model brings a knowledge-based problem-solving approach to the analysis of perception, treating perception as a kind of compiled cognition. The bottom-up passing of information from layer to layer defines channels of information flow, which separate and converge in a specific way for any specific sense modality. Multi-modal perception occurs where channels converge from more than one sense. This model has not yet been implemented, though it is based on systems which have been successful in medical and mechanical diagnosis and medical test interpretation

Reducing uncertainty by using explanatory relationships

Explanatory relationships can be used effectively to reduce the uncertainty that remains after diagnostic hypotheses have been scored using local matching

Cardiac Rehabilitation Intervention and Quality of Life Indicators: A Validation Estimate of Ware's Model

Author Institution: Dept. of Counseling & Mental Health Services, University of Toledo, OHAuthor Institution: Dept. of Educational Foundations & Leadership, University of Akron, OHAuthor Institution: Dept. of Counseling, Summa Health System, University of Akron, OHAuthor Institution: Cardiac Rehabilitation Institute, Summa Health System, University of Akron, OHThe present study tests Ware’s (1987, 1990) prediction that patient evaluations of quality of life (QOL) are related to physical ability. QOL data from 302 patients were collected prior to initiation and upon completion of a 12-week cardiac rehabilitation program. Physical ability was measured in metabolic equivalents (METS). Pearson product moment correlation coefficients were calculated for the variables under study. Multiple regression analyses were conducted to test these relationships covarying patient diagnosis, and pre-treatment QOL score and patient demographics. Significant improvements from pre- to post-CR were found for METs and all QOL variables. Improvements in physical ability were significantly correlated with improvements in physical health related QOL indices, but not with mental health QOL indices. These relationships were present even when moderating variables were co-varied. Improvements in physical ability were predictive of decreased expectations that physical health would interfere with work or other daily activities. As the physical capabilities of our patients increased, they reported feeling less physical pain and were less limited by any pain they did experience. And, increased physical ability was associated with a brighter outlook on current and expected future health status. These findings provide support for Ware’s theory of QOL

Compositeness, Triviality and Bounds on Critical Exponents for Fermions and Magnets

We argue that theories with fundamental fermions which undergo chiral symmetry breaking have several universal features which are qualitatively different than those of theories with fundamental scalars. Several bounds on the critical indices $\delta$ and $\eta$ follow. We observe that in four dimensions the logarithmic scaling violations enter into the Equation of State of scalar theories, such as $\lambda\phi^4$, and fermionic models, such as Nambu-Jona-Lasinio, in qualitatively different ways. These observations lead to useful approaches for analyzing lattice simulations of a wide class of model field theories. Our results imply that $\lambda\phi^4$ {\it cannot} be a good guide to understanding the possible triviality of spinor $QED$.Comment: 12 pages, 3 figures (not included), ILL-(TH)-93-2

Universal Properties of Chiral Simmetry Breaking

We discuss chiral symmetry breaking critical points from the perspective of PCAC, correlation length scaling and the chiral equation of state. A scaling theory for the ratio $R_\pi$ of the pion to sigma masses is presented. The Goldstone character of the pion and properties of the longitudinal and transverse chiral susceptibilities determine the ratio $R_\pi$ which can be used to locate critical points and measure critical indices such as $\delta$. We show how PCAC and correlation length scaling determine the pion mass' dependence on the chiral condensate and lead to a practical method to measure the anomalous dimension $\eta$. These tools are proving useful in studies of the chiral transition in lattice QED and the quark-gluon plasma transition in lattice QCD.Comment: 19 pages, 4 figures. CERN-TH.6630/92 ILL-(TH)-92-1

Looking for the Logarithms in Four-Dimensional Nambu-Jona-Lasinio Models

We study the problem of triviality in the four dimensional Nambu-Jona-Lasinio model with discrete chiral symmetry using both large-N expansions and lattice simulations. We find that logarithmic corrections to scaling appear in the equation of state as predicted by the large-N expansion. The data from $16^4$ lattice simulations is sufficiently accurate to distinguish logarithmically trivial scaling from power law scaling. Simulations on different lattice sizes reveal an interesting interplay of finite size effects and triviality. We argue that such effects are qualitatively different for theories based on fundamental scalar rather than fermion fields. Several lessons learned here can be applied to simulations and analyses of more challenging field theories.Comment: 25 pages, 14 ps figure

A Pilot Randomized Clinical Trial of a Teamwork Intervention for Heart Failure Care Dyads

Background: Dyadic heart failure (HF) management can improve outcomes for patients and caregivers and can be enhanced through eHealth interventions. Objective: To evaluate the feasibility, acceptability, and preliminary efficacy of an eHealth dyadic teamwork intervention, compared to an attention control condition. Methods: We recruited 29 HF patient-caregiver dyads from inpatient units and randomized dyads to an intervention or a control group. We calculated enrollment and retention rates, described acceptability using interview and questionnaire data, and computed intervention effect sizes. Results: 37% of eligible dyads agreed to participate and 93% of randomized participants completed follow-up questionnaires. Participants found both study conditions to be acceptable. Between-group effect sizes suggested that the intervention led to improvements in relationship quality, self-efficacy, and quality of life for patients and caregivers. Conclusions: Dyadic recruitment from acute care settings is challenging. Findings provide initial evidence that our intervention can contribute to better health outcomes for HF dyads

Response of thin-film SQUIDs to applied fields and vortex fields: Linear SQUIDs

In this paper we analyze the properties of a dc SQUID when the London penetration depth \lambda is larger than the superconducting film thickness d. We present equations that govern the static behavior for arbitrary values of \Lambda = \lambda^2/d relative to the linear dimensions of the SQUID. The SQUID's critical current I_c depends upon the effective flux \Phi, the magnetic flux through a contour surrounding the central hole plus a term proportional to the line integral of the current density around this contour. While it is well known that the SQUID inductance depends upon \Lambda, we show here that the focusing of magnetic flux from applied fields and vortex-generated fields into the central hole of the SQUID also depends upon \Lambda. We apply this formalism to the simplest case of a linear SQUID of width 2w, consisting of a coplanar pair of long superconducting strips of separation 2a, connected by two small Josephson junctions to a superconducting current-input lead at one end and by a superconducting lead at the other end. The central region of this SQUID shares many properties with a superconducting coplanar stripline. We calculate magnetic-field and current-density profiles, the inductance (including both geometric and kinetic inductances), magnetic moments, and the effective area as a function of \Lambda/w and a/w.Comment: 18 pages, 20 figures, revised for Phys. Rev. B, the main revisions being to denote the effective flux by \Phi rather than

Robust Meta-Model for Predicting the Need for Blood Transfusion in Non-traumatic ICU Patients

Objective: Blood transfusions, crucial in managing anemia and coagulopathy in ICU settings, require accurate prediction for effective resource allocation and patient risk assessment. However, existing clinical decision support systems have primarily targeted a particular patient demographic with unique medical conditions and focused on a single type of blood transfusion. This study aims to develop an advanced machine learning-based model to predict the probability of transfusion necessity over the next 24 hours for a diverse range of non-traumatic ICU patients. Methods: We conducted a retrospective cohort study on 72,072 adult non-traumatic ICU patients admitted to a high-volume US metropolitan academic hospital between 2016 and 2020. We developed a meta-learner and various machine learning models to serve as predictors, training them annually with four-year data and evaluating on the fifth, unseen year, iteratively over five years. Results: The experimental results revealed that the meta-model surpasses the other models in different development scenarios. It achieved notable performance metrics, including an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.97, an accuracy rate of 0.93, and an F1-score of 0.89 in the best scenario. Conclusion: This study pioneers the use of machine learning models for predicting blood transfusion needs in a diverse cohort of critically ill patients. The findings of this evaluation confirm that our model not only predicts transfusion requirements effectively but also identifies key biomarkers for making transfusion decisions