Uncertainty of Feedback and State Estimation Determines the Speed of Motor Adaptation

Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation

FraudMemory: Explainable Memory-Enhanced Sequential Neural Networks for Financial Fraud Detection

The rapid development of electronic financial services brings significant convenience to our daily life. However, it also offers criminals the opportunity to exploit financial systems to do fraudulent transactions. Previous studies on fraud detection only deal with single type transactions and cannot adapt well to evolving environment in reality. In addition, their black box models pay less attention on the interpretability of fraud detection results. Here we propose a novel fraud detection algorithm called FraudMemory. It adopts state-of-art feature representation methods to better depict users and logs with multiple types in financial systems. Our model innovatively uses sequential model to capture the sequential patterns of each transaction and leverages memory networks to improve both the performance and interpretability. Also, with the incorporation of memory components, FraudMemory possesses high adaptability to the existence of concept drift. The empirical study proves that our model is a potential tool for financial fraud detection

EFFECTS OF TAl CHI EXERCISE ON GAIT PATTERN IN THE ELDERLY

The purpose of this study was to examine the normal walking pattern of 21 older adults who had practiced Tai Chi for more than 5 years (TC group) and 20 older adults who often performed other kinds of physical activity (CTRL group). The results of the study indicated that there were significant differences in kinematic parameters of the hip joint angles, and the curve of ground reaction force versus time between the two groups

Predicting Stock Price Movement Direction with Enterprise Knowledge Graph

Predicting stock price movement direction is a challenging task for financial investment. Previous researches focused on investigating the impacts of external factors (e.g., big events, economic influence and sentiments) in combination with the historical price to predict short-term stock price movement, while few researches leveraged the power of various relationships among enterprises. To bridge this gap, this research proposes power vector model and influence propagation model to mine the rich information in constructed Enterprise Knowledge Graph (EKG) for price movement prediction. In addition, Deep Neural Network (DNN) is introduced to train the model. The proposed model shows good prediction performance on the dataset of China top 500 enterprises

Strong, conductive carbon nanotube fibers as efficient hole collectors

We present the photovoltaic properties of heterojunctions made from single-walled carbon nanotube (SWNT) fibers and n-type silicon wafers. The use of the opaque SWNT fiber allows photo-generated holes to transport along the axis direction of the fiber. The heterojunction solar cells show conversion efficiencies of up to 3.1% (actual) and 10.6% (nominal) at AM1.5 condition. In addition, the use of strong, environmentally benign carbon nanotube fibers provides excellent structural stability of the photovoltaic devices

Contra-Directional Expression of Serum Homocysteine and Uric Acid as Important Biomarkers of Multiple System Atrophy Severity: A Cross-Sectional Study

Aims. There is evidence suggesting that inflammatory responses play a critical role in the pathogenesis of multiple system atrophy (MSA). Whether inflammatory mediators can be used as reliable biomarkers to detect the severity and progression of MSA remains largely unknown. Methods. We performed a cross-sectional study that included 47 patients with MSA and 50 healthy age-matched controls. Serum levels of homocysteine (Hcy), uric acid (UA) and C-reactive protein (CRP) were measured. These levels positively correlated with the severity of MSA, based on both motor and non-motor symptoms (NMS). Several scales were used to rate the severity of MSA, including the Unified multiple system atrophy rating scale (UMSARS), Parkinson’s disease sleep scale (PDSS), Non-motor Symptoms Scale (NMSS), the Schwab & England Activities of Daily Living Scale (ADL), Webster Scale, modified Hoehn and Yahr staging scale (H&Y), and the Mini-Mental State Examination (MMSE). Receiver Operating Characteristic (ROC) curves was applied to map the diagnostic accuracy of MSA against healthy subjects. Results. Compared with healthy subjects, we found that serum Hcy was higher, UA was lower, and CRP levels were unchanged in MSA patients. These findings were especially prominent in male patients. No significant differences of serum Hcy and UA were observed between patients of MSA and PD. Interestingly, there was a significant correlation between Hcy levels and MSA severity such as movement dysfunction, declined cognition, and cardiovascular symptoms. Additionally, the ROC curve for the combination of Hcy and UA (AUC 0.736) showed potential diagnostic value in discriminating MSA from healthy subjects. Conclusions. Our findings suggest that the inflammatory mediators Hcy and UA may play important roles in the pathogenesis of MSA. The measurement of serum Hcy and UA levels could then be a useful tool to accurately distinguish MSA from healthy subjects

The clinical characteristics of Chinese elderly patients with different durations of type 2 diabetes mellitus

AimsTo explore the clinical characteristics among elderly (aged ≥60 years) patients with type 2 diabetes (T2DM) of different durations.MethodsClinical characteristics were investigated in 3840 elderly T2DM patients according to their different durations of diabetes (< 1 year, 1~5 years, 5~10 years, and ≥ 10 years). Kruskal-Wallis and Dunn tests were used to assess the differences among groups for continuous variables. The chi-square and post hoc tests were carried out for dichotomous variables. The logistic regression was adopted to investigate the relationships between various durations of diabetes and the control rates of achieving the control targets for T2DM as well as diabetic vascular complications.ResultsThere were 972, 896, 875 and 1097 patients with a duration of diabetes of <1, 1~5, 5~10 and ≥10 years, respectively. In logistic regression models adjusted for age, sex, education, BMI, smoking and family history of diabetes, elderly T2DM patients with a duration of diabetes of ≥10 years were more likely to reach the comprehensive control targets for TC (ORTC = 1.36, 95% CI =1.14-1.63), LDL-C (ORLDL-C = 1.39, 95% CI =1.17-1.66), TG (ORTG = 1.76, 95% CI =1.46-2.12) and BMI (ORBMI = 1.82, 95% CI =1.52-2.18). Elderly T2DM patients with a duration of diabetes of 1~5 years were more likely to achieve the HbA1c control target (ORHbA1c = 1.92, 95% CI = 1.59-2.31) than elderly T2DM patients with a duration of diabetes of <1 year. Furthermore, in elderly T2DM patients with a duration of diabetes of 5~10 years or ≥ 10 years, the duration of diabetes was positively associated with diabetic macrovascular complications (coronary heart disease and peripheral artery disease). In elderly T2DM patients with a duration of diabetes of over 10 years, the duration of diabetes was associated with diabetes kidney disease (all P < 0.05).ConclusionsIt is worth noting that the clinical characteristics of elderly patients with type 2 diabetes in different durations of diabetes are different