This study reports a microfluidic chip-based wearable colorimetric sensor for detecting sweat glucose. The device consisted of five microfluidic channels branching out from the center and connected ...to the detection microchambers. The microchannels could route the sweat excreted from the epidermis to the microchambers, and each of them was integrated with a check valve to avoid the risk of the backflow of the chemical reagents from the microchamber. The microchambers contained the pre-embedded glucose oxidase (GOD)–peroxidase–o-dianisidine reagents for sensing the glucose in sweat. It was found that the color change caused by the enzymatic oxidation of o-dianisidine could show a more sensitive response to the glucose than that of the conventional GOD–peroxidase–KI system. This sensor could perform five parallel detections at one time. The obtained linear range for sweat glucose was 0.1–0.5 mM with a limit of detection of 0.03 mM. The sensor was also used to detect the glucose in sweat samples from a group of subjects engaged in both fasting and postprandial trials. The results showed that our wearable colorimetric sensor can reveal the subtle differences existing in the sweat glucose concentration after the fasting and the oral glucose uptake.
The preparation of aluminum matrix composites (AMCs) by laser additive manufacturing (AM) technology has become an important means of improving performance of aluminum alloys. In this work, a novel ...in-situ synthesis method of selective laser melting combined combustion synthesis (SLM-CS) was used to prepare dual-phase reinforced AMCs. The feasibility of a B4C–Ti combustion synthesis reaction system to produce TiB2 and TiC ceramics by selective laser melting (SLM) was verified. AlSi10Mg alloy matrix composites with dual reinforcements were then fabricated by SLM, and systematic qualitative and quantitative phase analysis was carried out. The calculation results of the graphical-extrapolation method show that the lattice constant of α-Al matrix phase in the composites increases from 0.40466 nm to 0.40528 nm. The effects of a series of reactants with different chemical element composition ratios on the characteristics of melting process and non-equilibrium solidification microstructure were studied. The preliminary principles of the combustion chemical reaction under the rapid and continuous laser scanning were concluded from the theory and experiments results. In terms of mechanical properties, an appropriate amount of ceramic particles results in a significant improvement in the microhardness and elastic modulus, and yet composites prepared with a mixture powder amount greater than 0.7 wt % witnessing a clear drop in the tensile strength as well.
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•Composites were successfully produced via independent B4C-Ti combustion chemical reaction system in SLMed AlSi10Mg alloy.•Si released from α-Al is attributed to the formation of up to 18% Ti3SiC2 uniformly distributed in the melt pool.•The lattice constant of α-Al increases due to solid solution substitution, also indicating the scale of chemical reaction.•The chemical reaction provides additional heat input, largely influencing the size and morphology of the molten pool.•An increased amount of ceramics significantly improves the microhardness and clearly reduces the fracture strength.
Due to strong learning ability, convolutional neural networks (CNNs) have been developed in image denoising. However, convolutional operations may change original distributions of noise in corrupted ...images, which may increase training difficulty in image denoising. Using relations of surrounding pixels can effectively resolve this problem. Inspired by that, we propose a robust deformed denoising CNN (RDDCNN) in this paper. The proposed RDDCNN contains three blocks: a deformable block (DB), an enhanced block (EB) and a residual block (RB). The DB can extract more representative noise features via a deformable learnable kernel and stacked convolutional architecture, according to relations of surrounding pixels. The EB can facilitate contextual interaction through a dilated convolution and a novel combination of convolutional layers, batch normalisation (BN) and ReLU, which can enhance the learning ability of the proposed RDDCNN. To address long‐term dependency problem, the RB is used to enhance the memory ability of shallow layer on deep layers and construct a clean image. Besides, we implement a blind denoising model. Experimental results demonstrate that our denoising model outperforms popular denoising methods in terms of qualitative and quantitative analysis. Codes can be obtained at https://github.com/hellloxiaotian/RDDCNN.
This paper studies time-varying group formation control for heterogeneous multi-agent systems (MAS). Two subgroups of heterogeneous MAS consisting of second-order dynamic and Euler-Lagrange (E-L) ...dynamic agents, three subgroups of heterogeneous MAS consisting of first-order, second-order dynamic and E-L dynamic agents are considered respectively. Firstly, through the assumption of the formation-tracking feasibility condition and the design of the formation compensation vectors in the controller, the time-varying formation control can be transformed into a consensus problem. Then, a distributed controller based on neighbor information is designed and sufficient conditions for time-varying formation control are obtained. The time-varying group formation problem of heterogeneous MAS is analyzed by Lyapunov stability theory and eigenvalue theory. Finally, two simulation results show that the proposed controller can realize the time-varying formation control of heterogeneous group MAS.
Abstract
Background
Perioperative neurocognitive disorders (PNDs) are considered the most common postoperative complication in geriatric patients. However, its pathogenesis is not fully understood. ...Surgery-triggered neuroinflammation is a major contributor to the development of PNDs. Neuroinflammation can influence N-methyl-D-aspartate receptor (NMDAR) expression or function which is closely associated with cognition. We, therefore, hypothesized that the persistent changes in NMDAR expression or function induced by transient neuroinflammation after surgery were involved in the development of PNDs.
Methods
Eighteen-month-old male Sprague–Dawley rats were subjected to abdominal surgery with sevoflurane anesthesia to establish the PNDs animal model. Then, we determined the transient neuroinflammation by detecting the protein levels of proinflammatory cytokines and microglia activation using ELISA, western blot, immunohistochemistry, and microglial morphological analysis from postoperative days 1–20. Persistent changes in NMDAR expression were determined by detecting the protein levels of NMDAR subunits from postoperative days 1–59. Subsequently, the dysfunction of synaptic NMDAR was evaluated by detecting the structural plasticity of dendritic spine using Golgi staining. Pull-down assay and western blot were used to detect the protein levels of Rac1-GTP, phosphor-cofilin, and Arp3, which contribute to the regulation of the structural plasticity of dendritic spine. Finally, glycyrrhizin, an anti-inflammatory agent, was administered to further explore the role of synaptic NMDAR dysfunction induced by transient neuroinflammation in the neuropathogenesis of PNDs.
Results
We showed that transient neuroinflammation induced by surgery caused sustained downregulation of synaptic NR2A and NR2B subunits in the dorsal hippocampus and led to a selective long-term spatial memory deficit. Meanwhile, the detrimental effect of neuroinflammation on the function of synaptic NMDARs was shown by the impaired structural plasticity of dendritic spines and decreased activity of the Rac1 signaling pathways during learning. Furthermore, anti-inflammatory treatment reversed the downregulation and hypofunction of synaptic NR2A and NR2B and subsequently rescued the long-term spatial memory deficit.
Conclusions
Our results identify sustained synaptic NR2A and NR2B downregulation and hypofunction induced by transient neuroinflammation following surgery as important contributors to the development of PNDs in elderly rats.
In this study, adaptive time-varying group formation control for second-order multi-agent systems with an undirected topology is studied. First, a conventional multi-group adaptive time-varying ...formation control protocol is presented, and the stability of the system is analyzed based on the Lyapunov method. Considering that traditional methods of dealing with nonlinear dynamics cannot be directly applied to the time-varying formation problem, the parameter estimation method is used to track the unknown internal nonlinear dynamics of an agent. A virtual leader and filter are introduced to solve the problem of variable derivation and repeated derivation of the system state, and the adaptive rate of time-varying formation converges to a stable value. Finally, the feasibility of the results is verified using two simulation results.
Abstract
Wearable optical sensors have emerged as a promising technology, opening up a new way to monitor human sweat. With the advancement of integrated optical devices, optical materials, and ...structure design, the current optical skin interfaces primarily employ four analytical methods to transmit sweat chemical information into optical signals: colorimetry, surface-enhanced Raman spectroscopy, fluorescence, and electrochemiluminescence. To improve portability, many external laser source devices and imaging modules are upgraded based on different optical methods. Here, we summarize recent progress in optical sweat sensors, focusing on their principles, development, advantages, and limitations. Finally, current challenges and future prospects of wearable optical sensors in materials, sweat collection, data analysis, and external integrated electronics are discussed.
The multi-label recognition of damaged waste bottles has important significance in environmental protection. However, most of the previous methods are known for their poor performance, especially in ...regards to damaged waste bottle classification. In this paper, we propose the use of a serial attention frame (SAF) to overcome the mentioned drawback. The proposed network architecture includes the following three parts: a residual learning block (RB), a mixed attention block (MAB), and a self-attention block (SAB). The RB uses ResNet to pretrain the SAF to extract more detailed information. To address the effect of the complex background of waste bottle recognition, a serial attention mechanism containing MAB and SAB is presented. MAB is used to extract more salient category information via the simultaneous use of spatial attention and channel attention. SAB exploits the obtained features and its parameters to enable the diverse features to improve the classification results of waste bottles. The experimental results demonstrate that our proposed model exhibited good recognition performance in the collected waste bottle datasets, with eight labels of three classifications, i.e., the color, whether the bottle was damage, and whether the wrapper had been removed, as well as public image classification datasets.
An observation simulator is established for the Spectroscopy Focusing Array (SFA) and Polarimetry Focusing Array (PFA) onboard the planned enhanced X-ray Timing and Polarimetry observatory (eXTP). It ...consists of photon generation, imaging, detection, and event readout to generate data products, which can be analyzed by the standard astronomical analysis software. It is used to simulate a few astronomical sources to estimate and understand the impact of the payload and platform design configurations on the scientific goals of eXTP, including the background estimation of the central pixel in SFA, position dependence of silicon drift detector signals and its impacts, and pointing jitter requirements. The joint data analysis of the SFA and PFA payloads shows that the PFA image can help estimate the impact of nearby sources on the target source and select the proper pixels for the background estimation of the central pixel in SFA. The spectral and timing study of the millisecond pulsar depicts that the position dependence of silicon drift detector signals itself has an insignificant impact on the results. The type-C low-frequency quasi-periodic oscillations of black holes ranging from 0.01 Hz to 30 Hz are considered to raise the pointing jitter requirements of the telescope. In this case, the stability of the telescope should be less than 12
″
to avoid any spurious modulation signal. These examples demonstrate the necessity of an end-to-end observation simulator in the space mission, which will be further tested and improved by the ground segment in a wider range of applications.
The neural circuits underlying sleep-wakefulness and general anesthesia have not been fully investigated. The GABAergic neurons in the bed nucleus of the stria terminalis (BNST) play a critical role ...in stress and fear that relied on heightened arousal. Nevertheless, it remains unclear whether BNST GABAergic neurons are involved in the regulation of sleep-wakefulness and anesthesia. Here, using in vivo fiber photometry combined with electroencephalography, electromyography, and video recordings, we found that BNST GABAergic neurons exhibited arousal-state-dependent alterations, with high activities in both wakefulness and rapid-eye movement sleep, but suppressed during anesthesia. Optogenetic activation of these neurons could initiate and maintain wakefulness, and even induce arousal from anesthesia. However, chronic lesion of BNST GABAergic neurons altered spontaneous sleep-wakefulness architecture during the dark phase, but not induction and emergence from anesthesia. Furthermore, we also discovered that the BNST-ventral tegmental area pathway might participate in promoting wakefulness and reanimation from steady-state anesthesia. Collectively, our study explores new elements in neural circuit mechanisms underlying sleep-wakefulness and anesthesia, which may contribute to a more comprehensive understanding of consciousness and the development of innovative anesthetics.
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