231 research outputs found

    Kalman Filtering with State Equality Constraints

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    Kalman filters are commonly used to estimate the states of a dynamic system. However, in the application of Kalman filters there is often known model or signal information that is either ignored or dealt with heuristically. For instance, constraints on state values (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. A rigorous analytic method of incorporating state equality constraints in the Kalman filter is developed. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraint surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a simple nonlinear vehicle tracking proble

    Degraded Impairment of Emotion Recognition in Parkinson's Disease Extends from Negative to Positive Emotions

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    Because of dopaminergic neurodegeneration, patients with Parkinson's disease (PD) show impairment in the recognition of negative facial expressions. In the present study, we aimed to determine whether PD patients with more advanced motor problems would show a much greater deficit in recognition of emotional facial expressions than a control group and whether impairment of emotion recognition would extend to positive emotions. Twenty-nine PD patients and 29 age-matched healthy controls were recruited. Participants were asked to discriminate emotions in Experiment 1 and identify gender in Experiment 2. In Experiment 1, PD patients demonstrated a recognition deficit for negative (sadness and anger) and positive faces. Further analysis showed that only PD patients with high motor dysfunction performed poorly in recognition of happy faces. In Experiment 2, PD patients showed an intact ability for gender identification, and the results eliminated possible abilities in the functions measured in Experiment 2 as alternative explanations for the results of Experiment 1. We concluded that patients' ability to recognize emotions deteriorated as the disease progressed. Recognition of negative emotions was impaired first, and then the impairment extended to positive emotions

    Deep learning system to predict the 5-year risk of high myopia using fundus imaging in children

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    Our study aims to identify children at risk of developing high myopia for timely assessment and intervention, preventing myopia progression and complications in adulthood through the development of a deep learning system (DLS). Using a school-based cohort in Singapore comprising 998 children (aged 6-12 years old), we train and perform primary validation of the DLS using 7456 baseline fundus images of 1878 eyes; with external validation using an independent test dataset of 821 baseline fundus images of 189 eyes together with clinical data (age, gender, race, parental myopia, and baseline spherical equivalent (SE)). We derive three distinct algorithms - image, clinical, and mix (image + clinical) models to predict high myopia development (SE ≤ -6.00 diopter) during teenage years (5 years later, age 11-17). Model performance is evaluated using the area under the receiver operating curve (AUC). Our image models (Primary dataset AUC 0.93-0.95; Test dataset 0.91-0.93), clinical models (Primary dataset AUC 0.90-0.97; Test dataset 0.93-0.94) and mixed (image + clinical) models (Primary dataset AUC 0.97; Test dataset 0.97-0.98) achieve clinically acceptable performance. The addition of 1 year SE progression variable has minimal impact on the DLS performance (clinical model AUC 0.98 versus 0.97 in the primary dataset, 0.97 versus 0.94 in the test dataset; mixed model AUC 0.99 versus 0.97 in the primary dataset, 0.95 versus 0.98 in test dataset). Thus, our DLS allows prediction of the development of high myopia by teenage years amongst school-going children. This has potential utility as a clinical decision support tool to identify "at-risk" children for early intervention.info:eu-repo/semantics/publishedVersio

    The effectiveness of adjunct mindfulness-based intervention in treatment of bipolar disorder: A systematic review and meta-analysis

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    BACKGROUND: Mindfulness-based interventions (MBIs) have been increasingly used as an adjunctive treatment to pharmacotherapy for a few psychiatric disorders. However, few studies have investigated the efficacy of MBIs in bipolar disorder (BD). METHODS: We performed a systematic review and meta-analysis to evaluate the efficacy of MBIs as an adjunctive treatment in BD. Major electronic databases were independently searched by two authors for controlled and uncontrolled studies which examined the effects of MBIs on psychiatric symptoms in subjects with BD. Data from original studies were synthesized by using a random effects model. RESULTS: Twelve trials were eligible for inclusion into current meta-analysis, including three controlled studies (n=132) and nine uncontrolled studies (n=142). In within-group analysis, MBIs significantly reduced depressive (7 studies, n=100, Hedges' g=0.58, p<0.001) and anxiety (4 studies, n=68, Hedges' g=0.34, p=0.043) symptoms, but not manic symptoms (6 studies, n=89, Hedges' g=0.09, p=0.488) and cognition (3 studies, n=43, Hedges' g=0.35, p=0.171), compared to baseline. In between-group analysis (intervention group versus waiting list group, all patients with BD), MBIs did not reduce depressive (3 studies, n=132, Hedges' g=0.46, p=0.315) or anxiety (3 studies, n=132, Hedges' g=0.33, p=0.578) symptoms. LIMITATIONS: Only three controlled trials compared MBIs to control conditions. CONCLUSIONS: Our meta-analysis showed significantly beneficial effects on depressive and anxiety symptoms of BD patients in within-group analysis. However, this significance was not observed in comparison with the control groups. Further clinical trials are warranted to investigate the differences in the benefits of MBIs between treatment and control subjects

    KCNN2 polymorphisms and cardiac tachyarrhythmias

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    Potassium calcium-activated channel subfamily N member 2 (KCNN2) encodes an integral membrane protein that forms small-conductance calcium-activated potassium (SK) channels. Recent studies in animal models show that SK channels are important in atrial and ventricular repolarization and arrhythmogenesis. However, the importance of SK channels in human arrhythmia remains unclear. The purpose of the present study was to test the association between genetic polymorphism of the SK2 channel and the occurrence of cardiac tachyarrhythmias in humans. We enrolled 327 Han Chinese, including 72 with clinically significant ventricular tachyarrhythmias (VTa) who had a history of aborted sudden cardiac death (SCD) or unexplained syncope, 98 with a history of atrial fibrillation (AF), and 144 normal controls. We genotyped 12 representative tag single nucleotide polymorphisms (SNPs) across a 141-kb genetic region containing the KCNN2 gene; these captured the full haplotype information. The rs13184658 and rs10076582 variants of KCNN2 were associated with VTa in both the additive and dominant models (odds ratio [OR] 2.89, 95% confidence interval [CI] = 1.505-5.545, P = 0.001; and OR 2.55, 95% CI = 1.428-4.566, P = 0.002, respectively). After adjustment for potential risk factors, the association remained significant. The population attributable risks of these 2 variants of VTa were 17.3% and 10.6%, respectively. One variant (rs13184658) showed weak but significant association with AF in a dominant model (OR 1.91, CI = 1.025-3.570], P = 0.042). There was a significant association between the KCNN2 variants and clinically significant VTa. These findings suggest an association between KCNN2 and VTa; it also appears that KCNN2 variants may be adjunctive markers for risk stratification in patients susceptible to SCD

    Comparison of coplanar and noncoplanar intensity-modulated radiation therapy and helical tomotherapy for hepatocellular carcinoma

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    <p>Abstract</p> <p>Background</p> <p>To compare the differences in dose-volume data among coplanar intensity modulated radiotherapy (IMRT), noncoplanar IMRT, and helical tomotherapy (HT) among patients with hepatocellular carcinoma (HCC) and portal vein thrombosis (PVT).</p> <p>Methods</p> <p>Nine patients with unresectable HCC and PVT underwent step and shoot coplanar IMRT with intent to deliver 46 - 54 Gy to the tumor and portal vein. The volume of liver received 30Gy was set to keep less than 30% of whole normal liver (V30 < 30%). The mean dose to at least one side of kidney was kept below 23 Gy, and 50 Gy as for stomach. The maximum dose was kept below 47 Gy for spinal cord. Several parameters including mean hepatic dose, percent volume of normal liver with radiation dose at X Gy (Vx), uniformity index, conformal index, and doses to organs at risk were evaluated from the dose-volume histogram.</p> <p>Results</p> <p>HT provided better uniformity for the planning-target volume dose coverage than both IMRT techniques. The noncoplanar IMRT technique reduces the V10 to normal liver with a statistically significant level as compared to HT. The constraints for the liver in the V30 for coplanar IMRT vs. noncoplanar IMRT vs. HT could be reconsidered as 21% vs. 17% vs. 17%, respectively. When delivering 50 Gy and 60-66 Gy to the tumor bed, the constraints of mean dose to the normal liver could be less than 20 Gy and 25 Gy, respectively.</p> <p>Conclusion</p> <p>Noncoplanar IMRT and HT are potential techniques of radiation therapy for HCC patients with PVT. Constraints for the liver in IMRT and HT could be stricter than for 3DCRT.</p
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