Diagnosis by integrating model-based reasoning with knowledge-based reasoning

Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis

A study in the cognition of individuals’ identity: Solving the problem of singular cognition in object and agent tracking

This article compares the ability to track individuals lacking mental states with the ability to track intentional agents. It explains why reference to individuals raises the problem of explaining how cognitive agents track unique individuals and in what sense reference is based on procedures of perceptual-motor and epistemic tracking. We suggest applying the notion of singular-files from theories in perception and semantics to the problem of tracking intentional agents. In order to elucidate the nature of agent-files, three views of the relation between object- and agent-tracking are distinguished: the Independence, Deflationary and Organism-Dependence Views. The correct view is argued to be the latter, which states that perceptual and epistemic tracking of a unique human organism requires tracking both its spatio-temporal object-properties and its agent-properties

A scientometric analysis and review of fall from height research in construction

Fall from height (FFH) in the construction industry has earned much attention among researchers in recent years. The present review-based study introduced a science mapping approach to evaluate the FFH studies related to the construction industry. This study, through an extensive bibliometric and scientometric assessment, recognized the most active journals, keywords and the nations in the field of FFH studies since 2000. Analysis of the authors’ keywords revealed the emerging research topics in the FFH research community. Recent studies have been discovered to pay more attention to the application of Computer and Information Technology (CIT) tools, particularly building information modelling (BIM) in research related to FFH. Other emerging research areas in the domain of FFH include rule checking, and prevention through design. The findings summarized the mainstream research areas (e.g., safety management program), discussed existing research gaps in FFH domain (e.g., the adaptability of safety management system), and suggests future directions in FFH research. The recommended future directions could contribute to improving safety for the FFH research community by evaluating existing fall prevention programs in different contexts; integrating multiple CIT tools in the entire project lifecycle; designing fall safety courses to workers associated with temporary agents and prototype safety knowledge tool development. The current study was restricted to the FFH literature sample included the journal articles published only in English and in Scopus

Objective assessment of functional and motor-cognitive outcomes among asymptomatic primary hyperparathyroidism patients undergoing parathyroidectomy using wearable technologies: a pilot study towards better informed clinical decision-making

For the past 40 years, most patients with Primary Hyperparathyroidism (PHPT) have presented with the asymptomatic form of PHPT. Despite the dominance of the asymptomatic PHPT phenotype, current National Institutes of Health (NIH) indications for parathyroidectomy fail to identify as many as 80% of patients afflicted with asymptomatic PHPT. To date, studies of the therapeutic benefits of parathyroidectomy among asymptomatic PHPT patients have relied on general health questionnaires and patient reports of their satisfaction with the surgery. The purpose of the present study was to implement objective, quantifiable metrics in assessing whether or not asymptomatic PHPT patients experience improvements in domains salient to them such as mobility and cognitive function following parathyroidectomy. This information may help set the foundation for more accurately identifying patients who would benefit from parathyroidectomy. We hypothesized that asymptomatic patients would exhibit improvement in motor-cognitive outcomes following successful parathyroidectomy. We performed a single-center prospective assessment of gait, frailty, and motor-cognitive function among patients diagnosed with PHPT. Demographics, medical history, and perioperative labs were recorded. Pre- and post-surgical measures included the Fried frailty criteria, the PROMIS 10 Global Health Scale, and gait analysis under habitual (ST), walking while performing working memory test (dual-task: DT), and fast-walking conditions, an upper extremity frailty (UEF) test, and an interactive trail-making task (iTMT) . Descriptive statistics, Chi-squared, 2-sample t tests, and repeated measures analysis of variance were applied where appropriate. 22 parathyroidectomy patients (male 7; 31.8%); median age of 54.9 (standard deviation=15.5) years participated. The prevalence of frailty/pre-frailty was 60% at baseline and reduced to 33% at 3 weeks post-op. PROMIS 10 physical health improved significantly by 3 months post-op (d=0.93, p=0.010). DT and fast walk velocities were significantly increased by 3 weeks post-op (p<0.050) with highest effect size observed during DT conditions (24%, Cohen's effect size d=1.30 , p=0.017). ST velocity increased but not significantly (17.5%, d=0.46, p=0.422). Results from UEF tests and iTMT did not achieve statistical significance at any visit date. Asymptomatic PHPT patients experience significant resolution of motor-cognitive symptoms as measured by DT gait and PROMIS 10 Global Health Scale following parathyroidectomy performed by a skilled surgeon

GaitGCI: Generative Counterfactual Intervention for Gait Recognition

Gait is one of the most promising biometrics that aims to identify pedestrians from their walking patterns. However, prevailing methods are susceptible to confounders, resulting in the networks hardly focusing on the regions that reflect effective walking patterns. To address this fundamental problem in gait recognition, we propose a Generative Counterfactual Intervention framework, dubbed GaitGCI, consisting of Counterfactual Intervention Learning (CIL) and Diversity-Constrained Dynamic Convolution (DCDC). CIL eliminates the impacts of confounders by maximizing the likelihood difference between factual/counterfactual attention while DCDC adaptively generates sample-wise factual/counterfactual attention to efficiently perceive the sample-wise properties. With matrix decomposition and diversity constraint, DCDC guarantees the model to be efficient and effective. Extensive experiments indicate that proposed GaitGCI: 1) could effectively focus on the discriminative and interpretable regions that reflect gait pattern; 2) is model-agnostic and could be plugged into existing models to improve performance with nearly no extra cost; 3) efficiently achieves state-of-the-art performance on arbitrary scenarios (in-the-lab and in-the-wild).Comment: Accepted by CVPR202

The age-related contribution of cognitive function to dual-task gait in middle-aged adults in Spain : observations from a population-based study

Poor dual-task gait performance is associated with a risk of falls and cognitive decline in adults aged 65 years or older. When and why dual-task gait performance begins to deteriorate is unknown. This study aimed to characterise the relationships between age, dual-task gait, and cognitive function in middle age (ie, aged 40-64 years). We conducted a secondary analysis of data from community-dwelling adults aged 40-64 years that took part in the Barcelona Brain Health Initiative (BBHI) study, an ongoing longitudinal cohort study in Barcelona, Spain. Participants were eligible for inclusion if they were able to walk independently without assistance and had completed assessments of both gait and cognition at the time of analysis and ineligble if they could not understand the study protocol, had any clinically diagnosed neurological or psychiatric diseases, were cognitively impaired, or had lower-extremity pain, osteoarthritis, or rheumatoid arthritis that could cause abnormal gait. Stride time and stride time variability were measured under single-task (ie, walking only) and dual-task (ie, walking while performing serial subtractions) conditions. Dual-task cost (DTC; the percentage increase in the gait outcomes from single-task to dual-task conditions) to each gait outcome was calculated and used as the primary measure in analyses. Global cognitive function and composite scores of five cognitive domains were derived from neuropsychological testing. We used locally estimated scatterplot smoothing to characterise the relationship between age and dual-task gait, and structural equation modelling to establish whether cognitive function mediated the association between observed biological age and dual tasks. 996 people were recruited to the BBHI study between May 5, 2018, and July 7, 2020, of which 640 participants completed gait and cognitive assessments during this time (mean 24 days [SD 34] between first and second visit) and were included in our analysis (342 men and 298 women). Non-linear associations were observed between age and dual-task performance. Starting at 54 years, the DTC to stride time (β=0·27 [95% CI 0·11 to 0·36]; p<0·0001) and stride time variability (0·24 [0·08 to 0·32]; p=0·0006) increased with advancing age. In individuals aged 54 years or older, decreased global cognitive function correlated with increased DTC to stride time (β=−0·27 [−0·38 to −0·11]; p=0·0006) and increased DTC to stride time variability (β=−0·19 [−0·28 to −0·08]; p=0·0002). Dual-task gait performance begins to deteriorate in the sixth decade of life and, after this point, interindividual variance in cognition explains a substantial portion of dual-task performance

International Law Status of WTO Dispute Settlement Reports: Obligation to Comply or Option to Buy Out ?

In four further parts of this comment, I undertake to fulfill my obligation to present a more thorough analysis. In part II, I briefly introduce some of the different elements that would go into normal treaty interpretation related to the issue in question, such as which text should be part of the analysis and whether preparatory work or intent of the parties, including statements by some nation-state governmental officials made contemporaneously with the drafting of the treaty, should be considered. Likewise, I mention the importance of the forty seven years of GATT practice to the interpretive process, and I note that one way to sharpen the focus of treaty interpretation is to assess the relevance of a prediction of what the WTO Appellate Body would decide if the issue came before it. In part III, I take a detailed look at the various treaty text provisions. The texts themselves are contained in an appendix so that the reader can examine them in context, if he or she wishes. In part IV, I outline several of the important policies that support the view I am taking and that I believe to be enormously significant in suggesting that the Schwartz and Sykes approach is markedly deficient. Finally, in part V, I briefly summarize my conclusions and perceptions

Knowledge-based vision and simple visual machines

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong