The neuroanatomical basis behind acupuncture practice is still poorly understood. Here, we used intersectional genetic strategy to ablate NPY+ noradrenergic neurons and/or adrenal chromaffin cells. ...Using endotoxin-induced systemic inflammation as a model, we found that electroacupuncture stimulation (ES) drives sympathetic pathways in somatotopy- and intensity-dependent manners. Low-intensity ES at hindlimb regions drives the vagal-adrenal axis, producing anti-inflammatory effects that depend on NPY+ adrenal chromaffin cells. High-intensity ES at the abdomen activates NPY+ splenic noradrenergic neurons via the spinal-sympathetic axis; these neurons engage incoherent feedforward regulatory loops via activation of distinct adrenergic receptors (ARs), and their ES-evoked activation produces either anti- or pro-inflammatory effects due to disease-state-dependent changes in AR profiles. The revelation of somatotopic organization and intensity dependency in driving distinct autonomic pathways could form a road map for optimizing stimulation parameters to improve both efficacy and safety in using acupuncture as a therapeutic modality.
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•Intersectional genetic manipulation of NPY+ sympathetic cells•Electroacupuncture stimulation (ES) drives distinct sympathetic pathways•ES operates in somatotopy- and intensity-dependent manners•NPY+ noradrenergic neurons bidirectionally modulate systemic inflammation
Liu et al. reveals a neuroanatomical basis for acupuncture practice, showing that electroacupuncture stimulation can drive distinct autonomic pathways and modulate systemic inflammation in somatotopy-, stimulation-intensity-, and disease-state-dependent manners.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Fault diagnosis technology is the science of identifying the operating state of a machine or unit, and it studies the response of the change in the operating state of the machine or unit in the ...diagnostic information. It can give an early warning to the failure state of the machine and stop the machine before a major failure occurs so as to protect the life safety of the on-site staff and avoid huge economic losses to the enterprise. For mechanical equipment, fault diagnosis consists of three main links: fault detection; fault identification; and fault classification. Aiming at the problems that need to be solved in the fault diagnosis of industrial robots, this paper adopts a data-driven intelligent diagnosis method to establish a fault diagnosis model of industrial robots based on Deep Belief Network (DBN) and DSmT theory. Firstly, based on wavelet transform and information energy entropy correlation theory, the vibration signal of industrial robot is extracted, and the energy entropy normalized eigenvector is established. Then, the energy entropy normalized feature vector is divided into training set and test set to complete the creation of DBN network model. Finally, using DSmT theory to carry out decision-making fusion, a fault diagnosis model for industrial robots is established, and experiments are carried out on the K-R-R540 robot to verify the applicability of the established fault diagnosis model. It is proved by experiments that the industrial robot fault diagnosis model based on the deep belief network can meet the requirements of the recognition accuracy of robot faults, and the model will perform poorly when the faults coexist with multiple faults.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Abstract
The COVID-19 pandemic and the subsequent lockdown brought about an exogenous and unparalleled stock market crash. The crisis thus provides a unique opportunity to test theories of ...environmental and social (ES) policies. This paper shows that stocks with higher ES ratings have significantly higher returns, lower return volatility, and higher operating profit margins during the first quarter of 2020. ES firms with higher advertising expenditures experience higher stock returns, and stocks held by more ES-oriented investors experience less return volatility during the crash. This paper highlights the importance of customer and investor loyalty to the resiliency of ES stocks. (JEL G12, G32, M14)
Received: June 3, 2020; editorial decision June 24, 2020 by Editor Andrew Ellul.
Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
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IZUM, KILJ, NUK, PILJ, SAZU, UL, UM, UPUK
Phototherapy has attracted widespread attention for cancer treatment due to its noninvasiveness and high selectivity. However, severe hypoxia, overexpressed glutathione and high levels of hydrogen ...peroxide (H2O2) of tumor microenvironment limit the antitumor efficiency of phototherapy. Herein, inspired by the specific response of nanozymes to the tumor microenvironment, a simple and versatile nanozyme-mediated synergistic dual phototherapy nanoplatform is constructed. In this study, tin ferrite (SnFe2O4, SFO) nanozyme as a photosensitizer was surface modified with polydopamine (denoted as P-SFO) and incorporated into poly(l-lactide) to fabricate an antitumor scaffold fabricated by selective laser sintering. On one hand, SFO nanozyme could act as a photoabsorber to convert light energy into heat for photothermal therapy (PTT). On the other hand, it played a role of photosensitizer in transferring the photon energy to generate reactive oxygen species (ROS) for photodynamic therapy (PDT). Importantly, its multivalent metal ions redox couples would decompose H2O2 into O2 for enhancing O2-dependent PDT and consume glutathione to relieve antioxidant capability of the tumors. Besides, polydopamine as a photothermal conversion agent further enhanced the photothermal performance of SFO. The results revealed the PLLA/P-SFO scaffold possessed a photothermal conversion efficiency of 43.52% for PTT and a high ROS generation capacity of highly toxic ·O2− and ·OH for PDT. Consequently, the scaffold displayed a prominent phototherapeutic effect with antitumor rate of 96.3%. In addition, the PLLA/P-SFO scaffolds possessed good biocompatibility for cell growth. These advantages endow PLLA/P-SFO scaffold with extensive applications in biomedical fields and opened up new avenue towards nanozyme-mediated synergistic phototherapy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•Chitosan/poly(vinyl alcohol)/graphene oxide composite nanofiber membranes were prepared and characterized.•Contact angle decreased significantly via the addition of graphene ...oxide.•Composite nanofiber membranes showed good antibacterial activity against Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus.
In this paper, chitosan (CS)/poly (vinyl alcohol) (PVA)/graphene oxide (GO) composite nanofibrous membranes were prepared via electrospinning. Such nanofibrous membranes have been characterized and investigated for their morphological, structural, thermal stability, hydrophilic and antibacterial properties. SEM images showed that the uniform and defect-free nanofibers were obtained and GO sheets, shaping spindle and spherical, were partially embedded into nanofibers. FTIR, XRD, DSC and TGA indicated the good compatibility between CS and PVA. There were strong intermolecular hydrogen bonds between the chitosan and PVA molecules. Contact angle measurement indicated that while increasing the content of GO, the distance between fibers increased and water drop showed wetting state on the surface of nanofibrous membranes. As a result, the contact angle decreased significantly. Meanwhile, good antibacterial activity of the prepared nanofibrous membranes were exhibited against Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In physics class, the residual data before and after noise elimination contains more image information. In the equivalent wave domain, the K-SVD method is used to eliminate noise in the noise image ...of each frequency band and the residual of each frequency band. The main objective is to improve the image quality of noise. The method is combined with the denoised sub-spectrum to obtain the denoised sub-spectrum with the residual signal. An inverse isomorphic wave is used for noise reduction. The simulation results show that the noise reduction algorithm using K-SVD is better than the equivalent waveform and K-SVD mode. This method has achieved good results in practical application.
In this paper, without separating the complex-valued neural networks into two real-valued systems, the quasi-projective synchronization of fractional-order complex-valued neural networks is ...investigated. First, two new fractional-order inequalities are established by using the theory of complex functions, Laplace transform and Mittag-Leffler functions, which generalize traditional inequalities with the first-order derivative in the real domain. Additionally, different from hybrid control schemes given in the previous work concerning the projective synchronization, a simple and linear control strategy is designed in this paper and several criteria are derived to ensure quasi-projective synchronization of the complex-valued neural networks with fractional-order based on the established fractional-order inequalities and the theory of complex functions. Moreover, the error bounds of quasi-projective synchronization are estimated. Especially, some conditions are also presented for the Mittag-Leffler synchronization of the addressed neural networks. Finally, some numerical examples with simulations are provided to show the effectiveness of the derived theoretical results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In this paper, we address a rain removal problem from a single image, even in the presence of large rain streaks and rain streak accumulation (where individual streaks cannot be seen and thus are ...visually similar to mist or fog). For rain streak removal, the mismatch problem between different streak sizes in training and testing phases leads to poor performance, especially when there are large streaks. To mitigate this problem, we embed a hierarchical representation of wavelet transform into a recurrent rain removal process: 1) rain removal on the low-frequency component and 2) recurrent detail recovery on high-frequency components under the guidance of the recovered low-frequency component. Benefiting from the recurrent multi-scale modeling of wavelet transform-like design, the proposed network trained on streaks with one size can adapt to those with larger sizes, which significantly favors real rain streak removal. The dilated residual dense network is used as the basic model of the recurrent recovery process. The network includes multiple paths with different receptive fields, thus it can make full use of multi-scale redundancy and utilize context information in large regions. Furthermore, to handle heavy rain cases where rain streak accumulation is presented, we construct a detail appearing rain accumulation removal to not only improve the visibility but also enhance the details in dark regions. The evaluation of both synthetic and real images, particularly on those containing large rain streaks and heavy accumulation, shows the effectiveness of our novel models, which significantly outperforms the state-of-the-art methods.
In this paper, we address the problem of video rain removal by considering rain occlusion regions, i.e., very low light transmittance for rain streaks. Different from additive rain streaks, in such ...occlusion regions, the details of backgrounds are completely lost. Therefore, we propose a hybrid rain model to depict both rain streaks and occlusions. Integrating the hybrid model and useful motion segmentation context information, we present a Dynamic Routing Residue Recurrent Network (D3R-Net). D3R-Net first extracts the spatial features by a residual network. Then, the spatial features are aggregated by recurrent units along the temporal axis. In the temporal fusion, the context information is embedded into the network in a "dynamic routing" way. A heap of recurrent units takes responsibility for handling the temporal fusion in given contexts, e.g., rain or non-rain regions. In the certain forward and backward processes, one of these recurrent units is mainly activated. Then, a context selection gate is employed to detect the context and select one of these temporally fused features generated by these recurrent units as the final fused feature. Finally, this last feature plays a role of "residual feature." It is combined with the spatial feature and then used to reconstruct the negative rain streaks. In such a D3R-Net, we incorporate motion segmentation, which denotes whether a pixel belongs to fast moving edges or not, and rain type indicator, indicating whether a pixel belongs to rain streaks, rain occlusions, and non-rain regions, as the context variables. Extensive experiments on a series of synthetic and real videos with rain streaks verify not only the superiority of the proposed method over state of the art but also the effectiveness of our network design and its each component.
To solve problems of heavy calculation burden and low solution accuracy for redundant robot in inverse kinematics problem,a solution method based on improved fruit fly optimization algorithm（IFOA） ...was proposed. On the basis of FOA,the evolutionary equation is optimized by adding an improved strategy of learning worst individuals. The ability of the IFOA to break away from the local optimum and to find the global optimum is greatly enhanced. Experimental results of several typical functions show that IFOA has better global search ability,faster speed,higher accuracy and reliability,compared with FOA. In the application of inverse kinematics problem of the redundant robot,the accuracy,speed and stability were improved effectively,and is thus applicable to solve the inverse kinematics problem of redundant robot.
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