Adaptive Ensemble with Human Memorizing Characteristics for Data Stream Mining

Combining several classifiers on sequential chunks of training instances is a popular strategy for data stream mining with concept drifts. This paper introduces human recalling and forgetting mechanisms into a data stream mining system and proposes a Memorizing Based Data Stream Mining (MDSM) model. In this model, each component classifier is regarded as a piece of knowledge that a human obtains through learning some materials and has a memory retention value reflecting its usefulness in the history. The classifiers with high memory retention values are reserved in a “knowledge repository.” When a new data chunk comes, most useful classifiers will be selected (recalled) from the repository and compose the current target ensemble. Based on MDSM, we put forward a new algorithm, MAE (Memorizing Based Adaptive Ensemble), which uses Ebbinghaus forgetting curve as the forgetting mechanism and adopts ensemble pruning as the recalling mechanism. Compared with four popular data stream mining approaches on the datasets with different concept drifts, the experimental results show that MAE achieves high and stable predicting accuracy, especially for the applications with recurring or complex concept drifts. The results also prove the effectiveness of MDSM model

Highly Stretchable Electronic‐Skin Sensors with Porous Microstructure for Efficient Multimodal Sensing with Wearable Comfort

Abstract Wearable electronic skins have aroused extensive interest in health detection, human–computer interaction, and robotics. However, it remains a great challenge to realize the multifunctional electronic skin with a wide detection range, high sensitivity, multi‐stimulus response, and wearable comfort on a single device. Here, a flexible porous thermoplastic polyurethane (TPU)/carbon black (CB) multimodal sensor that perceives multiple stimuli of pressure, strain, and humidity is prepared by the water vapor‐induced phase separation method. The as‐prepared device exhibits a wide pressure detection range (up to 49 kPa), excellent sensitivity (0.21 kPa−1), fast response (150 ms), and recovery time (120 ms). Furthermore, as a strain sensor, it is not only highly stretchable (730%), but also can operate over a strain range of 0–240% with a sensitivity of up to 1485.2 and excellent durability. Moreover, the designed sensor can detect humidity changes from 35% to 90% and has a fast response time (1.2 s), while enabling non‐contact sensing of a fingertip. Importantly, the porous TPU/CB film presents excellent breathability, enabling it to achieve a high level of comfort. Therefore, the perfect integration of these features ensures the potential applications of porous TPU/CB sensors in human activity detection, exhale monitoring, and breathable wearable devices

Hydrophobic wrapped carbon nanotubes coated cotton fabric for electrical heating and electromagnetic interference shielding

Load conductive component onto textiles via coating method is a simple and facile fabrication process to prepare flexible smart wearable device. However, this functional textile will suffer a significant damage after washing or mechanical wear, which hindered its application. In this study, polydopamine (PDA) was used as an interfacial agent to enhance the combination between carbon nanotubes (CNTs) and cotton fiber to fabricated a highly conductive fabric. Furthermore, a hydrophobic material 1H,1H,2H,2H-perfluorooctyltriethoxysilane (PFOTES) was introduced to the conductive fabric via dip-coating process, which effectively fixed the CNTs and simultaneously realize the water resistance of the composite fabric, as the contact angle for the fabric was up to 138°. Owning to the formation of a stable conductive path, the composite conductive fabric always possessed a surface resistance lower than 110 Ω/sq. Even after going through the repeated mechanical deformation or multiple stripping cycles, this conductive pathway of the composite fabric was still well maintained. Benefit from the excellent stability and high electrical conductivity, this fabric shows an attractive electromagnetic (EMI) shielding performance, as its EMI shielding effectiveness was 22 dB under 6.57–9.99 GHz and 23 dB under 11.9–18 GHz. Furthermore, the fabric exhibited an outstanding electric heating performance with the heating temperature reaches more than 85 °C at 6 V. Along with the facile preparation technique and stable functional performance, we expect that this hydrophobic conductive cotton fabric can be used as wearable electronics and for the design of various smart flexible devices

Role of Polymer Conformation and Hydrodynamics on Nanoparticle Deposits on a Substrate

A dynamics density functional theory approach was presented to investigate the polymer-mediated nanoparticle deposits on a solid surface. The equilibrium and nonequilibrium behaviors of nanoparticles in the flexible linear, flexible star, semiflexible linear, and semiflexible star polymer solutions were investigated to evaluate the polymer-induced entropic effects and solvent-mediated hydrodynamic interactions. The theoretical results are in remarkable agreement with the Brownian dynamic simulation data, providing the quantitative verification of particle agglomeration and polymer depletion. The description at the microscopic level reveals new insight into the structure–function relationship of semidilute polymer–particle suspensions under confinement

Influence of comorbid anxiety symptoms on cognitive deficits in patients with major depressive disorder

Background: Major depressive disorder (MDD) patients with comorbid anxiety symptoms showed obvious cognitive deficits. However, it remains unclear whether comorbid anxiety symptoms will make a specific contribution to cognitive deficits in MDD. Methods: Executive function, processing speed, attention and memory were assessed in 162 MDD patients, and 142 healthy controls (HCs) by a comprehensive neuropsychological battery. 14-item Hamilton Anxiety Rating Scale (HAM-A) was used for anxiety symptoms and MDD patients with HAM-A total score >14 were classified into MDD with comorbid anxiety (MDDA) group. A multivariate analysis of covariance and regression models was conducted to evaluate the effects of anxiety symptoms on cognitive deficits. Results: There were no significantly differences in all 4 cognitive domains between MDD alone and MDDA patients (all p < 0.05). In MDDA subgroup, HAM-A total score contributed to executive function and memory (both p < 0.05), while HAM-A psychic symptoms contributed to all 4 domains (all p < 0.05). Moreover, after controlling for the severity of depression, either anxiety symptoms shown as HAMA total score or psychic anxiety symptoms only contributed significantly to the executive function performance. Limitations: The cross-sectional design made it hard to acquire a cognitive performance trajectory accompanied by the fluctuations in anxiety symptoms. Conclusion: Our findings suggest that there is no significant difference in cognitive performance between MDD alone and MDDA patients. However, comorbid anxiety, especially psychic anxiety may contribute to extensive cognitive deficits in MDDA patients. Notably, anxiety symptoms only independently triggered executive dysfunction when eliminating effect of the severity of depression

The effects of childhood trauma on the onset, severity and improvement of depression: The role of dysfunctional attitudes and cortisol levels

Background: Childhood trauma is an important early social risk factor for the development of the major depressive disorder (MDD). Both childhood trauma and depression are associated with dysfunctional attitudes and dysregulation in stress hormones. We aimed to clarify the path from childhood trauma to depression and identify potential predictors of antidepressant treatment outcomes. Objectives: One hundred and thirty-nine MDD patients and 112 healthy controls were included at baseline. Depressive symptoms were assessed with both self-reported and expert-rated scales. Childhood trauma and dysfunctional attitudes were evaluated and blood cortisol levels were assayed. Patients received an open-label antidepressant trial with paroxetine and their depressive symptoms were monitored by the Hamilton Depression Rating Scale (HAMD) during 6 months of treatment. After 6 months, 94 patients received the same assessments as the baseline. Results: At baseline, the influence of childhood trauma on depression diagnosis was mediated by dysfunctional attitudes. In patients with MDD, the influence of childhood trauma on depression severity was mediated by both dysfunctional attitudes and cortisol levels. Baseline childhood trauma predicted the antidepressant treatment outcome during early treatment phase and baseline cortisol levels predicted the antidepressant treatment outcome at later treatment phase. After 6-month antidepressant treatment, a significant remission by time effect was found on dysfunctional attitudes and depression severity but not on cortisol levels. Conclusion: Effect of childhood trauma on depression onset was mediated by dysfunctional attitudes. The relationship between childhood trauma and depressive symptoms was mediated by dysfunctional attitudes and cortisol levels in MDD patients. Baseline childhood trauma and cortisol levels may be moderators for antidepressant treatment response at different treatment phase

Exploration of Major Cognitive Deficits in Medication-Free Patients With Major Depressive Disorder

Background: Major depressive disorder (MDD) is associated with a wide range of cognitive deficits. However, it remains unclear whether there will be a major cognitive deficit independently caused by depression at acute episodes of MDD. Method: A comprehensive neurocognitive test battery was used to assess the executive function, processing speed, attention, and memory in 162 MDD patients and 142 healthy controls (HCs). A multivariate analysis of variance, hierarchical regression analyses and general linear regression analyses were used to explore the possible major cognitive deficits and their predictor variables. Results: MDD patients showed extensive impairment in all four cognitive domains. Impairment of executive function and processing speed were found to persist even with other cognitive domains and clinical variables being accounted for. Executive function and processing speed were further predicted by total disease duration and depression severity, respectively. Conclusions: Executive function and processing speed may be two distinct major deficits at acute episodes of MDD. Furthermore, the executive function is likely originated from the cumulative effect of disease duration and processing speed is possibly derived from the temporary effect of current depressive episode.</p