Deep learning has been widely applied and brought breakthroughs in speech recognition, computer vision, and many other domains. Deep neural network architectures and computational issues have been ...well studied in machine learning. But there lacks a theoretical foundation for understanding the approximation or generalization ability of deep learning methods generated by the network architectures such as deep convolutional neural networks. Here we show that a deep convolutional neural network (CNN) is universal, meaning that it can be used to approximate any continuous function to an arbitrary accuracy when the depth of the neural network is large enough. This answers an open question in learning theory. Our quantitative estimate, given tightly in terms of the number of free parameters to be computed, verifies the efficiency of deep CNNs in dealing with large dimensional data. Our study also demonstrates the role of convolutions in deep CNNs.
Establishing a solid theoretical foundation for structured deep neural networks is greatly desired due to the successful applications of deep learning in various practical domains. This paper aims at ...an approximation theory of deep convolutional neural networks whose structures are induced by convolutions. To overcome the difficulty in theoretical analysis of the networks with linearly increasing widths arising from convolutions, we introduce a downsampling operator to reduce the widths. We prove that the downsampled deep convolutional neural networks can be used to approximate ridge functions nicely, which hints some advantages of these structured networks in terms of approximation or modeling. We also prove that the output of any multi-layer fully-connected neural network can be realized by that of a downsampled deep convolutional neural network with free parameters of the same order, which shows that in general, the approximation ability of deep convolutional neural networks is at least as good as that of fully-connected networks. Finally, a theorem for approximating functions on Riemannian manifolds is presented, which demonstrates that deep convolutional neural networks can be used to learn manifold features of data.
Full-color emissive carbon dots (CDs) hold a great promise for various applications, especially in light emitting diodes (LEDs). However, the existing synthetic routes for CDs are carried out in ...solutions, which suffer from low yields, high pressures, various byproducts, large amounts of waste solvents, and complicated photoluminescence (PL) origins. Therefore, it is necessary to explore large scale synthesis of CDs with high quantum yield (QY) across the entire visible range from a single carbon source by a solvent-free method. In this work, a series of CDs with tunable PL emission from 442 to 621 nm, QY of 23%–56%, and production yield within 34%–72%, are obtained by heating o-phenylenediamine with the catalysis of KCl. Detailed characterizations identify that, the differences between these CDs with respect to the graphitization degree, graphitic nitrogen content, and oxygen-containing functional groups, are responsible for their distinct optical properties, which can be modulated by controlling the deamination and dehydrogenation processes during reactions. Blue, green, yellow, red emissive films, and LEDs are prepared by dispersing the corresponding CDs into polyvinyl alcohol (PVA). All types of white LEDs (WLEDs) with high colorrendering- index (CRI), including warm WLEDs, standard WLEDs, and cool WLEDs, are also fabricated by mixing the red, green, and blue emissive CDs into PVA matrix by the appropriate ratios.
As a promising luminescent nanomaterial, carbon dots (CDs) have received tremendous attention for their great potential in biomedical applications, owing to their distinctive merits of ease in ...preparation, superior optical properties, good biocompatibility, and adjustable modification in structure and functionalities. However, most of the reported CDs exhibit insufficient excitation and emission in red/near-infrared (R/NIR) regions, which significantly limits their practical applications in biomedical assays and therapy. In the latest years, extensive studies have been performed to produce CDs with intensified R/NIR excitation and emission by designed reactions and precise separations. This review article summarizes state-of-the-art progress towards design and manufacture of CDs with long-wavelength or multicolor emissions, involving their synthetic routes, precursors, and luminescence mechanisms. Meanwhile, the applicable availability of CDs in bioimaging, sensing, drug delivery/release, and photothermal/photodynamic therapy, is systematically overlooked. The current challenges concerning feasible controls over optical properties of CDs and their new opportunities in biomedical fields are discussed.
The synthesis, optical properties, and biomedical applications of carbon dots with red or near-infrared emissions are summarized. Display omitted
With the rapid development of the coal industry, the possibility of spontaneous combustion of coal in the process of mining, storage and transportation has gradually increased. Coal in the pile state ...is very easy to lead to the occurrence of coal spontaneous combustion disaster because of the good heat storage environment and ventilation conditions. In order to study the impact regulation on the heat pipe heat dissipation effect under different heat source input power conditions, the working performance of the heat pipe is investigated by using methanol working material and no working material as a contrast. The experiments were conducted to determine the suitable working heat source environment for the gravity heat pipe by comparing and analyzing the wall temperature of the gravity heat pipe under different heat source input power as well as the use of the working material. The results show that the copper-methanol gravity heat pipe can best control the temperature of the heat source location to continue to rise, destroy its heat storage environment, and suppress the self-heating of the coal pile. The heat dissipation effect of the copper-methanol gravity heat pipe at the heat source input power of 75 W. It shows that different working materials have corresponding working environment. This experimental study is conducted to be able to destroy the self-heating environment of coal in the process of piling, which has certain guiding significance for the improvement of coal pile spontaneous combustion prevention technology.
Neuronal intranuclear inclusion disease (NIID) is a slowly progressing neurodegenerative disease characterized by eosinophilic intranuclear inclusions in the nervous system and multiple visceral ...organs. The clinical manifestation of NIID varies widely, and both familial and sporadic cases have been reported. Here we have performed genetic linkage analysis and mapped the disease locus to 1p13.3-q23.1; however, whole-exome sequencing revealed no potential disease-causing mutations. We then performed long-read genome sequencing and identified a large GGC repeat expansion within human-specific NOTCH2NLC. Expanded GGC repeats as the cause of NIID was further confirmed in an additional three NIID-affected families as well as five sporadic NIID-affected case subjects. Moreover, given the clinical heterogeneity of NIID, we examined the size of the GGC repeat among 456 families with a variety of neurological conditions with the known pathogenic genes excluded. Surprisingly, GGC repeat expansion was observed in two Alzheimer disease (AD)-affected families and three parkinsonism-affected families, implicating that the GGC repeat expansions in NOTCH2NLC could also contribute to the pathogenesis of both AD and PD. Therefore, we suggest defining a term NIID-related disorders (NIIDRD), which will include NIID and other related neurodegenerative diseases caused by the expanded GGC repeat within human-specific NOTCH2NLC.
Rumination is strongly and consistently correlated with depression. Although multiple studies have explored the neural correlates of rumination, findings have been inconsistent and the mechanisms ...underlying rumination remain elusive. Functional brain imaging studies have identified areas in the default mode network (DMN) that appear to be critically involved in ruminative processes. However, a meta-analysis to synthesize the findings of brain regions underlying rumination is currently lacking. Here, we conducted a meta-analysis consisting of experimental tasks that investigate rumination by using Signed Differential Mapping of 14 fMRI studies comprising 286 healthy participants. Furthermore, rather than treat the DMN as a unitary network, we examined the contribution of three DMN subsystems to rumination. Results confirm the suspected association between rumination and DMN activation, specifically implicating the DMN core regions and the dorsal medial prefrontal cortex subsystem. Based on these findings, we suggest a hypothesis of how DMN regions support rumination and present the implications of this model for treating major depressive disorder characterized by rumination.
•Rumination is strongly and consistently correlated with depression.•Meta-analyze the findings of brain regions regarding to rumination.•Specifically examined the contribution of three DMN subsystems to rumination.•Rumination is specifically correlated with the DMN core regions and the dorsal medial prefrontal cortex subsystem.
The boundary control problem of fractional ordinary differential equations coupled with a time fractional reaction–advection–diffusion equation with delay is studied in this paper. To ensure the ...asymptotic stability of the system we studied, a state feedback boundary controller is proposed. By backstepping method, we transform the fractional coupled system into a chosen target system under a controller. Furthermore, we obtain the existence and uniqueness of the state solution of the considered system. A Lyapunov functional is constructed to show the asymptotic stability of the fractional coupled system by the special fractional Halanay inequality. The asymptotic stability criterion of the fractional coupled system is described by Linear Matrix Inequalities (LIMs). Which can be easily solved and verified. Finally, the applicability of our theoretical results is showed by a numerical simulation.
The coronavirus disease (COVID-19) pandemic has impacted the economy, livelihood, and physical and mental well-being of people worldwide. This study aimed to compare the mental health status during ...the pandemic in the general population of seven middle income countries (MICs) in Asia (China, Iran, Malaysia, Pakistan, Philippines, Thailand, and Vietnam). All the countries used the Impact of Event Scale-Revised (IES-R) and Depression, Anxiety and Stress Scale (DASS-21) to measure mental health. There were 4479 Asians completed the questionnaire with demographic characteristics, physical symptoms and health service utilization, contact history, knowledge and concern, precautionary measure, and rated their mental health with the IES-R and DASS-21. Descriptive statistics, One-Way analysis of variance (ANOVA), and linear regression were used to identify protective and risk factors associated with mental health parameters. There were significant differences in IES-R and DASS-21 scores between 7 MICs (p<0.05). Thailand had all the highest scores of IES-R, DASS-21 stress, anxiety, and depression scores whereas Vietnam had all the lowest scores. The risk factors for adverse mental health during the COVID-19 pandemic include age <30 years, high education background, single and separated status, discrimination by other countries and contact with people with COVID-19 (p<0.05). The protective factors for mental health include male gender, staying with children or more than 6 people in the same household, employment, confidence in doctors, high perceived likelihood of survival, and spending less time on health information (p<0.05). This comparative study among 7 MICs enhanced the understanding of metal health in the general population during the COVID-19 pandemic.
The knowledge and skills of employees could play a valuable role in organizational success. Organizations seek practices to create a knowledge-sharing culture to take full advantage of individual ...competencies. However, the knowledge-hiding behavior of individuals is a hurdle in the internal dissemination of knowledge and expertise. It becomes more critical in the case of teaching institutions, where the students are taught and trained. Scholars are now putting their efforts into seeking the antecedents and consequences of knowledge-hiding behavior. This study also attempts to determine the role of interpersonal distrust as an antecedent of knowledge hiding behavior of music education students. Based on the social exchange theory, the present study attempts to check the association of interpersonal distrust with emotional exhaustion and knowledge hiding. For empirical investigation, this study assumes that interpersonal distrust positively enhances knowledge hiding and emotional exhaustion, respectively. Moreover, the present study also attempts to check the association of emotional exhaustion with knowledge hiding. This study also assessed the mediating role of emotional exhaustion in the relationship between interpersonal distrust and knowledge hiding. This current study also aims to check the moderating role of mental health self-efficacy in the relationship between emotional exhaustion and knowledge hiding. For empirical investigation, the present study collected the data from 310 music learning students of various Chinese universities through a structured questionnaire method using a convenient sampling technique. This study applied partial least square structural equation modeling for empirical analyses using Smart PLS software. The findings of this study revealed that interpersonal distrust does not directly influence knowledge hiding; however, interpersonal distrust has a positive association with emotional exhaustion. The findings also acknowledged that emotional exhaustion positively correlates with knowledge hiding. The results also confirmed that emotional exhaustion positively mediates the relationship between interpersonal distrust and knowledge hiding. Further, the outcomes depicted that mental health self-efficacy negatively moderates the relationship between emotional exhaustion and knowledge hiding. In addition, this study’s findings also serve the literature of knowledge hiding by providing important theoretical and practical implications.
PDF
