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This paper investigates the correlation between the persistent impact of the epidemic on investment risk in the post-epidemic period and the response measures. A high correlation is found between market performance and policies introduced due to the ongoing impact of the epidemic. Further validation is provided by using the CSI 300 as a reference portfolio and by selecting ten stocks from the CSI 300 in the capital markets services sector to calculate the correlation coefficient between the latter and the former. It is found that placing assets in capital market services companies leads to lower investment risk, and the correlation between investment risk and the ongoing impact of the epidemic is moderately low. However, placing assets in capital markets services firms is not a better choice currently if investors want to obtain a higher return on their assets.

Business valuations are often used today by stakeholders to estimate the economic value of the benefits a business generates. In this case, financial market participants use a variety of valuation methods to determine the price they are willing to pay or accept to achieve a stock sale. Therefore, this paper conducts financial statement analysis and common valuation methods on the basis of Airbus annual report, and then evaluates some other factors that affect valuation. The study found that Airbus got rid of high leverage and implemented sustainable development in recent years. The stock price based on common valuation methods is lower than the market value. However, this paper believes that due to the current situation of Airbus and the capital market, the current market value is reasonable.

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Parameter estimation is vital for modeling and control of fuel cell systems. However, the nonlinear parameterization is an intrinsic characteristic in the fuel cell models such that classical parameter estimation schemes developed for linearly parameterized systems cannot be applied. In this paper, an alternative framework of adaptive parameter estimation is designed to address the real-time parameter estimation for fuel cell systems. The parameter estimation can be divided into two cascaded components. First, the dynamics with the unknown parameters are estimated by a new unknown system dynamics estimator (USDE). Inspired by an invariant manifold, this USDE is designed by applying simple filter operations such that the information of the state derivative is not required. Secondly, an adaptive law driven by the function approximation error is proposed for recovering unknown model parameters. Exponential convergence of the estimated parameters to the true values can be proved under the monotonicity condition. Finally, experimental results on a practical proton exchange membrane fuel cell system are given to verify the effectiveness of the proposed schemes.

Book value is the value presented on the balance sheet. In contrast to book value, which reflects the past value, market value is based on the current value of the enterprise and includes all price influencing factors in the market. An accurate valuation of an enterprise is critical to making correct investment decisions. The gap between the book value and market value of an enterprise can lead to deviations in enterprise value valuation, which can affect the judgment of financial statement users. However, the current accounting standards cannot meet such decision-making needs of information users and need to be improved in the future reform. The purpose of this paper is to analyze the reasons for the gap at the empirical level and to assess the implications for the reform of accounting standards.

Large-scale classification poses great challenges to storage and computation. There are two major solutions to address the problem: data compression and quantization. In the paper, we study the method of first reducing data dimension by random projection and then quantizing the projections to ternary and binary codes, which has been widely applied in practice. Often, the extreme quantization would degrade the accuracy of classification due to high quantization errors. Interestingly, however, we observe that the quantization could result in performance improvement, rather than degradation, if the data for quantization are preprocessed by sparse transform. Also, the quantization gain could be obtained with the random projections of the data, if both the data and random projection matrices are sparse enough, such that the resulting projections remain sparse. The intriguing performance is verified and analyzed with extensive experiments.

Carbon nanotubes (CNTs) are ideal candidates for beyond-silicon nano-electronics because of their high mobility and low-cost processing. Recently, assembled massively aligned CNTs have emerged as an important platform for semiconductor electronics. However, realizing sophisticated complementary nano-electronics has been challenging due to the p-type nature of carbon nanotubes in air. Fabrication of n-type behavior field effect transistors (FETs) based on assembled aligned CNT arrays is needed for advanced CNT electronics. Here in this paper, we report a scalable process to make n-type behavior FETs based on assembled aligned CNT arrays. Air-stable and high-performance n-type behavior CNT FETs are achieved with high yield by combining the atomic layer deposition dielectric and metal contact engineering. We also systematically studied the contribution of metal contacts and atomic layer deposition passivation in determining the transistor polarity. Based on these experimental results, we report the successful demonstration of complementary metal-oxide-semiconductor inverters with good performance, which paves the way for realizing the promising future of carbon nanotube nano-electronics.

Apple xyloglucan (XyG) structural features (molecular weight and building motifs) were studied in relation with the hemicellulose interaction with cellulose nanofiber (CNF) through adsorption isotherm, high performance size exclusion chromatography and high-performance anion exchange chromatography analyses. Up to 75.6 μg of apple XyG adsorbed/mg of CNF. XyG adsorption depended on both Mw and XyG/CNF ratio. The adsorption capacity increased with Mw irrespectively of XyG/CNF ratio. At XyG/CNF ratio 0.05, the adsorption of high Mw populations (2.0 × 10

Mingrui Chen,1 Qiulin Chen,1 Tao Tao2 1Department of Neurosurgery, Chongqing Red Cross Hospital (People’s Hospital of Jiangbei District), Jiangbei, Chongqing 400020, People’s Republic of China; 2Department of Rehabilitation Medicine, Guizhou Provincial People’s Hospital, Guiyang, Guizhou 550002, People’s Republic of ChinaCorrespondence: Tao Tao Tel +86 13985162824Email 13985162824@163.comPurpose: Traumatic brain injury (TBI) is a major cause of morbidity and mortality worldwide. Increasing evidence indicates that activated microglia play an important role in the inflammatory response in TBI. Inhibiting M1 and stimulating M2 activated microglia have protective effects in several animal models of central nervous system (CNS) disorders. In the present study, we investigated whether tanshinone IIA (TNA) protects neurons by shifting microglia polarization in a mouse TBI model and further investigated the mechanism in vitro.Materials and Methods: Forty C57BL/6 mice were used to investigate the effect of TNA on microglia polarization in TBI. BV-2 cells were used to examine the mechanism of TNA in regulating microglia polarization.Results: Normal saline (NS), TNA and the combination of TNA with ICI 182,780 (ICI, an estrogen receptor antagonist) were used to treat the TBI mice. After TBI, mice from each group demonstrated functional improvement. The improvement rate in mice treated with TNA was faster than other groups. ICI partially reversed the benefits from TNA treatment. TNA treatment significantly reduced TBI-induced neuronal loss. The number of microglia after TBI was not significantly changed by TNA treatment. However, TNA treatment significantly decreased M1 macrophage markers (iNOS, TNFα and IL-1β) and increased M2 macrophage markers (CD206, arginase 1 and Ym1). This effect was partially abolished by ICI. TNA treatment downregulated M1 macrophage markers and upregulated M2 macrophage markers in BV-2 cells under LPS stimulation. IL-10 was significantly increased by TNA treatment without a significantly change of IL-4 and IL-13 expression. IL-10 knockdown completely abolished the effect of TNA on microglial M2 polarization.Conclusion: Taken together, our data demonstrated that TNA attenuates neuronal loss in mouse TBI model and promotes M2 microglia by ERβ/IL-10 pathway. Thus, TNA could be a potential drug for TBI and/or the disorders that caused by microglial over-activation in CNS.Keywords: tanshinone IIA; TNA, traumatic brain injury; TBI, microglia, interleukins, macrophage polarization

Orientation-controlled growth of two-dimensional (2D) transition metal dichalcogenides (TMDCs) may enable many new electronic and optical applications. However, previous studies reporting aligned growth of WSe2 usually yielded very small domain sizes. Herein, we introduced gold vapor into the chemical vapor deposition (CVD) process as a catalyst to assist the growth of WSe2 and successfully achieved highly aligned monolayer WSe2 triangular flakes grown on c-plane sapphire with large domain sizes (130 µm) and fast growth rate (4.3 µm·s−1). When the aligned WSe2 domains merged together, a continuous monolayer WSe2 was formed with good uniformity. After transferring to Si/SiO2 substrates, field effect transistors were fabricated on the continuous monolayer WSe2, and an average mobility of 12 cm2·V−1·s−1 was achieved, demonstrating the good quality of the material. This report paves the way to study the effect of catalytic metal vapor in the CVD process of TMDCs and contributes a novel approach to realize the growth of aligned TMDC flakes.

Red phosphorus offers a high theoretical sodium capacity and has been considered as a candidate anode for sodium-ion batteries. Similar to silicon anodes for lithium-ion batteries, the electrochemical performance of red phosphorus is plagued by the large volume variation upon sodiation. Here we perform in situ transmission electron microscopy analysis of the synthesized red-phosphorus-impregnated carbon nanofibers with the corresponding chemo-mechanical simulation, revealing that, the sodiated red phosphorus becomes softened with a “liquid-like” mechanical behaviour and gains superior malleability and deformability against pulverization. The encapsulation strategy of the synthesized red-phosphorus-impregnated carbon nanofibers has been proven to be an effective method to minimize the side reactions of red phosphorus in sodium-ion batteries, demonstrating stable electrochemical cycling. Our study provides a valid guide towards high-performance red-phosphorus-based anodes for sodium-ion batteries., Red phosphorus is a promising anode for Na-ion batteries but suffers from large volume change upon cycling. Here the authors show a red-phosphorus-impregnated carbon nanofiber design in which the sodiated red phosphorus is featured by a “liquid-like” behavior and ultra-stable electrochemical performance is realized.

In the work, we study the exemplar-based classification method, which categorizes novel objects by comparing their similarity to the exemplars previously stored by class. The exemplar storage and similarity calculation will pose great challenges for large-scale classification. To reduce data complexity, we propose to first reduce data dimension by random projection and then quantize the projections to binary or ternary codes. Intuitively, the extreme quantization will degrade the accuracy of classification due to significant information loss. Interestingly, however, we observe that the quantization could provide comparable or even superior accuracy, if the data to be quantized are the sparse features generated with common filters. Furthermore, this quantization property could be preserved in the random projections of sparse features, if both the features and random projection matrices are sufficiently sparse. By conducting extensive experiments, we validate and analyze this intriguing property.

Within the apple pomace biorefinery cascade processing framework aiming at adding value to an agroindustrial waste, after pectin recovery, this study focused on hemicellulose. The structure of the major apple hemicellulose, xyloglucan (XyG), was assessed as a prerequisite to potential developments in industrial applications. DMSO-LiCl and 4 M KOH soluble hemicelluloses from pectin-extracted apple pomace were purified by anion exchange chromatography. XyG structure was assessed by coupling xyloglucanase and endo-β-1,4-glucanase digestions to HPAEC and MALDI-TOF MS analyses. 71.9% of pomaces hemicellulose were recovered with starch. DMSO-LiCl and 4 M KOH soluble XyG exhibited Mw of 19 and 140 kDa, respectively. Besides the XXXG, XLXG, XXLG, XXFG, XLFG and XLLG structures, novel oligosaccharides with degree of polymerization of 6-10 were observed after xyloglucanase digestion. Cellobiose and cellotriose were revealed randomly distributed in XyG backbone and were more present in DMSO-LiCl soluble XyG. Residual pomace remains a potential source of other materials.

Developing convenient and accurate SARS-CoV-2 antigen test and serology test is crucial in curbing the global COVID-19 pandemic. In this work, we report an improved indium oxide (InSupplementary material (materials and methods for device fabrication, functionalization of In

Recently, the method that learns networks layer by layer has attracted increasing interest for its ease of analysis. For the method, the main challenge lies in deriving an optimization target for each layer by inversely propagating the global target of the network. The target propagation is an ill-posed problem, due to involving the inversion of nonlinear activations from low-dimensional to high-dimensional spaces. To address the problem, the existing solution is to learn an auxiliary network to specially propagate the target. However, the network lacks stability, and moreover, it leads to higher complexity for network learning. In the letter, we show that target propagation could be achieved by modeling the network's each layer with compressed sensing, without the need of auxiliary networks. Experiments show that the proposed method could achieve better performance than the auxiliary network-based method.

International audience; Structural elucidation of plant cell wall xyloglucan through the analysis of enzymatically produced fragmentsrequires detailed knowledge of enzymes hydrolytic mechanism. In this note, the mode of action and cleavage siteof commercial recombinant xyloglucanases (GH74, Paenibacillus sp.) was studied on native and fluorescent-tagged tamarind xyloglucan. In complement to information provided by the manufacturer, GH74 hydrolysiswas shown dual endo/exo- and exo-processive with low affinity towards labelled reducing-ends. GH74 accom-modated X/G in its subsite --1 and X/L in its subsite +1. Moreover, hydrolysis kinetic indicated a GH74 activityinhibition by excess products. These results will help for application of this enzyme in xyloglucans structuralanalysis or for processing cell walls.

Adjacent vertebral compression fracture (AVCF) is the primary factor affecting satisfaction after PKP surgery. In addition to osteoporosis, certain structural characteristics of the vertebral body itself also increase their risk. The purpose of this study was to explore the impact of biomechanical changes on AVCF after balancing other factors.As a routine treatment of OVCF, the postoperative refracture of PKP is a serious problem. The aim of our study was to explore the impact of lumbar biomechanical changes on the risk of AVCF. A propensity score matching was performed to balance the interference of osteoporosis, which is the primary risk factor of AVCF.A retrospective, single-center case-control study was performed. From September 2013 to March 2020, 1752 patients were enrolled, and AVCF was assessed in 80 of these patients. A propensity score matching (PSM) analysis was performed, and 5 potential confounding factors were matched (age, BMI, number of fractured vertebral bodies, fracture region, and HDL). The preoperative and postoperative radiological factors were measured in the matched cohort of 48 pairs. A conditional logistic regression analysis to adjust the comparative risks.The preoperative wedge angle and its postoperative recovery of the AVCF group were significantly higher than that of the non-AVCF group. The local kyphosis of the fractured vertebral body between the two groups was similar, but the recovery in the AVCF group was slightly higher than that in the non-AVCF group. The preoperative and postoperative relative anterior height (RAH) of the fractured vertebral body was familiar in two groups, so was the recovery of RAH. The preoperative spino-sacral angle (SSA) was significantly higher in the AVCF group than in the non-AVCF group. The preoperative wedge angle was identified as the only significant risk factor for AVCF in the multivariate analysis.In conclusion, a larger preoperative fracture vertebral wedge angle is a risk factor for AVCF. For such high-risk patients, surgeons should be cautious about surgical decisions. The postoperative active measures and tailored surveillance should be attached to great importance as well.

Nonvolatile, flexible artificial synapses that can be used for brain-inspired computing are highly desirable for emerging applications such as human-machine interfaces, soft robotics, medical implants, and biological studies. Printed devices based on organic materials are very promising for these applications due to their sensitivity to ion injection, intrinsic printability, biocompatibility, and great potential for flexible/stretchable electronics. Herein, we report the experimental realization of a nonvolatile artificial synapse using organic polymers in a scalable fabrication process. The three-terminal electrochemical neuromorphic device successfully emulates the key features of biological synapses: long-term potentiation/depression, spike timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow energy consumption. The artificial synapse network exhibits an excellent endurance against bending tests and enables a direct emulation of logic gates, which shows the feasibility of using them in futuristic hierarchical neural networks. Based on our demonstration of 100 distinct, nonvolatile conductance states, we achieved a high accuracy in pattern recognition and face classification neural network simulations.

Severe lithium (Li) dendrite growth during the plating/stripping process, which results in low Coulombic efficiency and safety issues, strongly hinders the practical applications of Li metal anodes. Herein, we propose a novel design of three-dimensional (3D) interconnected graphene (IG) framework synthesized with the help of nickel (Ni) microspheres for stable Li metal anodes. The as-prepared IG framework consists of multiple stacks of two-dimensional (2D) graphene layers and plenty of hollow graphene microspheres in between, and thus provides protective layers on the top to suppress lithium dendrites, sufficient surface area to reduce the effective current density, as well as ion channels for fast Li transport, which is confirmed by post-cycle morphology characterization. When Li foil was used as the counter electrode for Li deposition, the assembled coin cell maintained an average Coulombic efficiency of more than 97.5% for 100 cycles at current density of 1 mA cm−2 with a Li loading of 1 mAh cm−2. Furthermore, we achieved stable cycling for more than 300 h at a current density of 1 mA cm−2 with a Li loading of 2 mAh cm−2 when assembled as symmetric cells. This strategy of vertically stacking 2D materials provides a novel approach towards dendrite-free Li metal anodes for the next-generation energy storage systems.

International audience; Three natural deep eutectic solvents (NADES; choline chloride (CC): lactic acid (LA), CC: oxalic acid (OA), CC: urea (U)) in the ratio 1:2 were tested as a pretreatment of apple pomace prior to hot water extraction of pectin. The pretreatment duration and temperature (for 0.5-2h, at 40-80 degrees C) was adjusted to limit cell wall polysaccharides losses and degradation. Extraction yields and sugar composition were used to evaluate the impact of the pretreatment on pectin extraction and the molecular weight and degree of esterification of pectin were characterized. Results showed that CC:LA and CC:U pretreatments led to close overall recovery yields with the control using water instead of NADES. Instead, CC:OA led to polysaccharides degradation and loss. The cell wall monosaccharides composition was affected after CC:LA and CC:U pretreatments at 60 degrees C and above, while it was preserved by CC:LA pretreatments at 40 degrees C for 1h. Moreover, CC:LA pretreatment facilitated hot water extraction of a large amount (33.1%-56.1% of uronic acid recovery) of high Mw HM pectin comparable with pectin obtained through classical method. CC:U pretreatment led to saponification and affected pectin composition by introducing choline. Thus, CC:LA pretreatment of apple pomace followed by water extraction offers a "green" alternative for mineral acid pectin extraction while CC:U allows functionalizing pectin in apple pomace prior to hot water extraction.

Cockpit Voice Recorder (CVR) records all the sound signals related to the accident in the cockpit before the crash. Accurate analysis of the cockpit voice signal is the basis for exploring the real reason behind the flight accident, which often starts from the separation of cockpit mixed signals. In this paper, a Fast Independent Component Analysis (FastICA) method for mixed signal separation is proposed. The basic idea of the method, three classical assumptions and the independence criteria of separation results are presented. The FastICA algorithm is analyzed theoretically, and the blind separation experiment of cockpit mixed signals is realized in this paper. The simulation experiment result shows that although FastICA algorithm is complex in theory, the realize of this algorithm is concise and clear, which can quickly and effectively separate these signals, and provide research basis for accurate analysis of the causes of aircraft accidents in the later stage.

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Summary Flexible sensors are essential for advancing implantable and wearable bioelectronics toward monitoring chemical signals within and on the body. Developing biosensors for monitoring multiple neurotransmitters in real time represents a key in vivo application that will increase understanding of information encoded in brain neurochemical fluxes. Here, arrays of devices having multiple In2O3 nanoribbon field-effect transistors (FETs) were fabricated on 1.4-μm-thick polyethylene terephthalate (PET) substrates using shadow mask patterning techniques. Thin PET-FET devices withstood crumpling and bending such that stable transistor performance with high mobility was maintained over >100 bending cycles. Real-time detection of the small-molecule neurotransmitters serotonin and dopamine was achieved by immobilizing recently identified high-affinity nucleic-acid aptamers on individual In2O3 nanoribbon devices. Limits of detection were 10 fM for serotonin and dopamine with detection ranges spanning eight orders of magnitude. Simultaneous sensing of temperature, pH, serotonin, and dopamine enabled integration of physiological and neurochemical data from individual bioelectronic devices., Graphical Abstract, Highlights • We fabricated flexible In2O3 nanoribbon transistors using cleanroom-free processes • Flexible In2O3 transistors withstood crumpling and bending with stable performance • Flexible aptamer biosensors detect neurotransmitters in real time • Multiplexed sensors monitor temperature, pH, serotonin, and dopamine simultaneously, Nanoscience; Bioelectronics; Nanotechnology Fabrication