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Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Model-based reinforcement learning is a promising direction to improve the sample efficiency of reinforcement learning with learning a model of the environment. Previous model learning methods aim at fitting the transition data, and commonly employ a supervised learning approach to minimize the distance between the predicted state and the real state. The supervised model learning methods, however, diverge from the ultimate goal of model learning, i.e., optimizing the learned-in-the-model policy. In this work, we investigate how model learning and policy learning can share the same objective of maximizing the expected return in the real environment. We find model learning towards this objective can result in a target of enhancing the similarity between the gradient on generated data and the gradient on the real data. We thus derive the gradient of the model from this target and propose the Model Gradient algorithm (MG) to integrate this novel model learning approach with policy-gradient-based policy optimization. We conduct experiments on multiple locomotion control tasks and find that MG can not only achieve high sample efficiency but also lead to better convergence performance compared to traditional model-based reinforcement learning approaches. [ABSTRACT FROM AUTHOR]

Glutamate is traditionally viewed as the first messenger to activate NMDAR (N-methyl-d-aspartate receptor)-dependent cell death pathways in stroke1,2, but unsuccessful clinical trials with NMDAR antagonists implicate the engagement of other mechanisms3–7. Here we show that glutamate and its structural analogues, including NMDAR antagonist l-AP5 (also known as APV), robustly potentiate currents mediated by acid-sensing ion channels (ASICs) associated with acidosis-induced neurotoxicity in stroke4. Glutamate increases the affinity of ASICs for protons and their open probability, aggravating ischaemic neurotoxicity in both in vitro and in vivo models. Site-directed mutagenesis, structure-based modelling and functional assays reveal a bona fide glutamate-binding cavity in the extracellular domain of ASIC1a. Computational drug screening identified a small molecule, LK-2, that binds to this cavity and abolishes glutamate-dependent potentiation of ASIC currents but spares NMDARs. LK-2 reduces the infarct volume and improves sensorimotor recovery in a mouse model of ischaemic stroke, reminiscent of that seen in mice with Asic1a knockout or knockout of other cation channels4–7. We conclude that glutamate functions as a positive allosteric modulator for ASICs to exacerbate neurotoxicity, and preferential targeting of the glutamate-binding site on ASICs over that on NMDARs may be strategized for developing stroke therapeutics lacking the psychotic side effects of NMDAR antagonists.Glutamate functions as a positive allosteric modulator for acid-sensing ion channels to exacerbate ischaemic neurotoxicity. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive finite-time tracking control problem for a class of constrained pure-feedback systems with time-varying delays and unknown initial states. By designing a novel shifting function and using the state transformation, there is no need to know the initial value of states. Instead of employing barrier Lyapunov functions, the modified nonlinear state-dependent functions are constructed to solve the deferred state constraints, avoiding the feasibility conditions on virtual controllers. The effect of time-varying delays is eliminated by combining the radial basis function neural networks with a finite covering lemma, and the requirement that the derivative of time-varying delays should be less than one in Lyapunov-Krasovskii functional method is relaxed. The asymmetric saturation nonlinearity is solved by designing an auxiliary system. The system coordinate transformation is employed to solve the design difficulty brought by the nonaffine structure. Then, an adaptive finite-time tracking control scheme is developed based on the command filtered backstepping technique. The developed control scheme can not only make all states satisfy the asymmetric time-varying constraints after a predefined time, but also guarantee the finite-time tracking performance. Finally, simulation examples are given to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Psoriasis is an immune-mediated skin disease associated with neurogenic inflammation, but the underlying molecular mechanism remains unclear. We demonstrate here that acid-sensing ion channel 3 (ASIC3) exacerbates psoriatic inflammation through a sensory neurogenic pathway. Global or nociceptor-specific Asic3 knockout (KO) in female mice alleviates imiquimod-induced psoriatic acanthosis and type 17 inflammation to the same extent as nociceptor ablation. However, ASIC3 is dispensable for IL-23-induced psoriatic inflammation that bypasses the need for nociceptors. Mechanistically, ASIC3 activation induces the activity-dependent release of calcitonin gene-related peptide (CGRP) from sensory neurons to promote neurogenic inflammation. Botulinum neurotoxin A and CGRP antagonists prevent sensory neuron-mediated exacerbation of psoriatic inflammation to similar extents as Asic3 KO. In contrast, replenishing CGRP in the skin of Asic3 KO mice restores the inflammatory response. These findings establish sensory ASIC3 as a critical constituent in psoriatic inflammation, and a promising target for neurogenic inflammation management. Psoriasis is a skin disease associated with neurogenic inflammation. Here, the authors activation of ASIC3 on sensory neurons that leads to the release of CGRP, which triggers inflammation through dendritic cells and drives psoriatic inflammation. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the Hyers–Ulam stability of the coefficient multipliers on the Hardy space H 2 and the Bergman space A 2 , meanwhile, we also investigate the Hyers–Ulam stability of the coefficient multipliers between the Bergman space A 2 and the Hardy space H 2 . We give the necessary and sufficient condition for the coefficient multipliers to have the Hyers–Ulam stability on the Hardy space H 2 , on the Bergman space A 2 and between the Bergman space A 2 and the Hardy space H 2 , respectively. We also show that the best constant of Hyers–Ulam stability exists under different circumstances. Some results generalized the results of MacGregor and Zhu when p = 2 in MacGregor and Zhu article (Mathematika 42:413–426, 1995). Moreover, some illustrative examples are also discussed. [ABSTRACT FROM AUTHOR]

In recent years, the safe and reliable transmission of image information has received wide attention from scholars. A "one-image, one-secret" image encryption algorithm using chaotic systems and DNA sequences is proposed to address the problems of smaller key space and inability to resist against cropping attacks in encryption algorithms. A new 2-D chaotic system is used to generate a 2-D random matrix equal in size to the color image. The algorithm layers color images into R, G, B three-channel 2-D matrices, blocking the three 2-D matrices after layering and the 2-D random matrix. Chaotic sequences generated by hyperchaotic systems determine how DNA is encoded, decoded, and operated between DNA sub-blocks, which increases the diversity of DNA encoding and operation. Association of images to be encrypted with the 4-D hyperchaotic system, which ensures the "one image, one secret" encryption effect. Simulation results show the effectiveness of the encryption algorithm. Theoretical analysis and simulation experimental result show that the algorithm has large key capacity, strong key sensitivity, and the encrypted image had anti-crop performance, which is important for the research of improving the image encryption effect. [ABSTRACT FROM AUTHOR]

A series of novel carboxamide compounds containing benzoxazole motif was synthesized through multiple steps, including electrophilic substitution, cyclization, reduction and amide formation. These processes utilized ortho-aminophenol and heptafluoro-2-iodopropane as starting materials. The structures of these compounds (4a–4r) were characterized by 1H NMR, 13C NMR, and HRMS. Bioassay results revealed that most of these compounds exhibited significant insecticidal activity against Mythimna separata at 500 mg/L. Among them, compound 6-chloro-N-(4-methoxy-3-(6-(perfluoropropan-2-yl)benzo[d]oxazol-2-yl)phenyl)-N-methylnicotinamide (4r) possessed the highest activity, even at 4 mg/L. Molecular docking predicted the binding modes of 4r. These novel carboxamide compounds containing benzoxazole motifs offer valuable insights for designing insecticidal compounds targeting GABA receptors, aiming to control lepidopteran pests effectively. [ABSTRACT FROM AUTHOR]

With the wide application of cantilever roadheader in urban subway tunnel construction, accurate prediction of excavation performance of cantilever roadheader in rock stratum has become a research hotspot. Accurate prediction of tunneling performance of cantilever roadheader in rock stratum is the key to its successful application in tunnel engineering. Based on Guiyang Rail Transit Line 1 and Line 3, this paper conducts field investigation and statistical analysis of data on the construction performance and tunneling characteristics of roadheader, and establishes a prediction database of tunneling performance of hard rock cantilever roadheader. The principal component analysis (PCA) was introduced into the deep belief network (DBN) to optimize the input parameters of the DBN model, and the PCA–DBN model for the performance prediction of hard rock cantilever roadheader was proposed. The new model is trained and predicted based on the data of Guiyang Rail Transit Line 1, and the rationality and feasibility of the model are verified through the field data test and analysis of Guiyang Rail Transit Line 3. The results show that the performance prediction model of hard rock cantilever roadheader based on PCA–DBN can realize real-time and continuous prediction of tunneling performance of ground roadheader in front of tunnel face according to engineering measured data. The comparative analysis with the DBN model shows that the accuracy of the PCA–DBN prediction model is better than that of the DBN model, which can better adapt to complex and changeable geological conditions. The new model provides a new method and possibility for accurately predicting the tunneling performance of cantilever roadheader in hard rock. Highlights: A prediction database of hard rock cantilever roadheader tunneling performance was established. The performance prediction model of hard rock cantilever roadheader based on PCA–DBN was established. The performance prediction model realizes real-time and continuous prediction of tunneling performance of ground roadheader. The prediction accuracy of PCA–DBN is higher than DBN in predicting the performance of cantilever roadheader. [ABSTRACT FROM AUTHOR]

The red-necked longhorn beetle, Aromia bungii, is an invasive wood-boring insect that has recently invaded Europe and Japan, seriously damaging stone fruit trees in both native and invaded regions. Rose oxide, including both cis- and trans-isomers, was previously found in the volatiles produced by A. bungii adults, while the inter- and intra-specific behavioral functions of this compound remain unclear. By manually shaking the beetles, a much greater amount of rose oxide was released from the beetles, compared to that released from nondisturbed beetles. Rose oxide was further determined to be original from a white-colored secretion which was immediately sprayed by the beetles that were hand captured or squeezed by tweezers. These findings indicate that this pungent compound putatively has a role as an allomone component released from the defensive secretion by A. bungii adults when threatened, which may be an adaptive defensive strategy against the predation of natural enemies such as insectivorous birds. Y-tube olfactory assays revealed that rose oxide, at a high concentration, was significantly repellent to both sexes of A. bungii adults, suggesting that rose oxide may also have a function in the intraspecific communication of A. bungii. Considering the low price of the commercially available products, this repellent effect of rose oxide may facilitate the development of novel control strategies, such as push–pull strategy, for A. bungii. [ABSTRACT FROM AUTHOR]

Reinforcement learning (RL) interacts with the environment to solve sequential decision-making problems via a trial-and-error approach. Errors are always undesirable in real-world applications, even though RL excels at playing complex video games that permit several trial-and-error attempts. To improve sample efficiency and thus reduce errors, model-based reinforcement learning (MBRL) is believed to be a promising direction, as it constructs environment models in which trial-and-errors can occur without incurring actual costs. In this survey, we investigate MBRL with a particular focus on the recent advancements in deep RL. There is a generalization error between the learned model of a non-tabular environment and the actual environment. Consequently, it is crucial to analyze the disparity between policy training in the environment model and that in the actual environment, guiding algorithm design for improved model learning, model utilization, and policy training. In addition, we discuss the recent developments of model-based techniques in other forms of RL, such as offline RL, goal-conditioned RL, multi-agent RL, and meta-RL. Furthermore, we discuss the applicability and benefits of MBRL for real-world tasks. Finally, this survey concludes with a discussion of the promising future development prospects for MBRL. We believe that MBRL has great unrealized potential and benefits in real-world applications, and we hope this survey will encourage additional research on MBRL. [ABSTRACT FROM AUTHOR]

Based on the theory of developmental evaluation, this paper develops a new development-oriented research evaluation model called "four abilities", with "basic development ability", "process development ability", "achievement ability" and "influence ability" as key dimensions, which can be applied in different situations such as recruitment, performance appraisal, promotion evaluation, tenure review, and selection of honorary academic awards. Based on the data from the Youth Fund of the Ministry of Management Science of National Natural Science Foundation of China (NSFC) from 2014 to 2018, this paper takes the developmental evaluation of early career researchers as an example, treating the existing research output as the development goal and the "development ability" of early career researchers as the explanatory factor. Then the propensity score matching method (PSM) method is adopted to control the sample self-selection bias in the way of reverse order evaluation, so as to explain whether the guiding indicator "development ability" is conducive to the development of researchers. The results indicate that strong "process development ability" of newly recruited researchers in the first 3 years of employment period can significantly promote their future research performance, which has important implications for the current evaluative culture overemphasizing short-term output. Through the application of the "four abilities" model integrating various dimensions composed of potential, capacity, output and impact, researchers at different career stages are guided to concentrate more on long-term academic mission and to achieve better career development based on their differentiated development needs. [ABSTRACT FROM AUTHOR]

Circular RNA circSKA3 (spindle and kinetochore-related complex subunit 3) has been identified as a prognostic factor in ischemic stroke. The objective of this study was to investigate the association of circSKA3 with the risk of extracranial artery stenosis (ECAS) and plaque instability in patients with ischemic stroke. We constructed a competing endogenous RNA (ceRNA) network regulated by circSKA3 based on differentially expressed circRNAs and mRNAs between five patients and five controls. Gene Ontology (GO) analysis was performed on the 65 mRNAs within the network, revealing their primary involvement in inflammatory biological processes. A total of 284 ischemic stroke patients who underwent various imaging examinations were included for further analyses. Each 1 standard deviation increase in the log-transformed blood circSKA3 level was associated with a 56.3% increased risk of ECAS (P = 0.005) and a 142.1% increased risk of plaque instability (P = 0.005). Patients in the top tertile of circSKA3 had a 2.418-fold (P < 0.05) risk of ECAS compared to the reference group (P for trend = 0.02). CircSKA3 demonstrated a significant but limited ability to discriminate the presence of ECAS (AUC = 0.594, P = 0.015) and unstable carotid plaques (AUC = 0.647, P = 0.034). CircSKA3 improved the reclassification power for ECAS (NRI: 9.86%, P = 0.012; IDI: 2.97%, P = 0.007) and plaque instability (NRI: 36.73%, P = 0.008; IDI: 7.05%, P = 0.04) beyond conventional risk factors. CircSKA3 played an important role in the pathogenesis of ischemic stroke by influencing inflammatory biological processes. Increased circSKA3 was positively associated with the risk of ECAS and plaque instability among ischemic stroke patients. [ABSTRACT FROM AUTHOR]

Different concentrations of NH4Cl are introduced to MAPbI3 precursor solution, planar MAPbI3 perovskite films, and solar cells' performance with or without NH4Cl have been studied. The NH4Cl/MAPbI3 films exhibit increased grain size and narrowed grain boundaries. The light absorption of perovskite films with different concentrations of NH4Cl was also evaluated. To understand the growth of perovskite films with NH4Cl added to perovskite precursor solutions, XRD and XPS spectroscopy were conducted on different perovskite film samples. By adding NH4Cl, the MAPbI3 film shows good crystal quality and the shift of Pb peaks indicates that NH4Cl is not physically mixed but chemically incorporated into MAPbI3 films. We attribute the effect to Cl ions of NH4Cl combining with free lead ions of MAPbI3 so as to fill the vacancy of volatile I ions in the NH4Cl–MAPbI3 films. The 20 mg NH4Cl-based device showed an enhanced performance of a PCE of 13.67% compared to the device without adding NH4Cl with a PCE of 10.24%. The introduction of 20 mg NH4Cl achieved the best passivation effect. Using a 20 mg NH4Cl device, the trap density can be reduced to 0.84 × 1016 cm−3, resulting in more efficient charge removal from the surface and improved performance. [ABSTRACT FROM AUTHOR]

To assess resolving-like activity by a novel chemically-modified curcumin (CMC2.24) in a "two-hit" model of diabetes-associated periodontitis. Macrophages from rats were cultured in the presence/absence of either Lipopolysaccharide (LPS, 1st hit); or advanced-glycation-end products (AGE, 2nd hit); or both combined. CMC2.24 was added as treatment. The conditioned media were analyzed for MMP-9, cytokines (IL-1β, IL-6, TNF-α), resolvins (RvD1, RvE1, lipoxin A4), and soluble receptor for AGE (sRAGE). The phenotypes of M1/M2 macrophage were analyzed by flow cytometry. Both LPS/AGE-alone, and two-combined, dramatically increased the secretion of MMP-9 by macrophages. CMC2.24 "normalized" the elevated levels of MMP-9 under all conditions. Moreover, CMC2.24 significantly reduced the secretion of IL-1β and IL-6 with a fewer effects on TNF-α. Importantly, CMC2.24 increased RvD1 and sRAGE secretion by macrophages exposed to LPS/AGE; and both treatment groups exhibited increased M2 relative to M1 populations. Furthermore, scatter-diagram showed the macrophages gradually shifted from M1 towards M2 with CMC2.24-treated, whereas LPS/AGE-alone groups remained unchanged. CMC2.24 "normalized" cytokines and MMP-9, but also enhanced RvD1 and sRAGE in macrophages. Crucially, CMC2.24 appears to be a potent inhibitor of the pro-inflammatory M1 phenotype; and a promotor of the pro-resolving M2 phenotype, thus acting like a crucial "switch" to reduce inflammation. [ABSTRACT FROM AUTHOR]

Pedestrian trajectory prediction is a necessary component of autonomous driving technology. However, current methods face two troubles when utilized to the actual world, one is the distribution difference between training and testing environments, and the other is catastrophic forgetting. These two issues will lead to an inevitable drop in the overall performance of the model in real-world scenarios. To tackle these two issues, we propose a framework that consists of modules for domain adaptation and continual learning. Specifically, a pedestrian interplay modeling method based totally on pedestrian social habits is proposed. Moreover, we add a domain adaptation module to analyze the data distribution difference between the source domain and the target domain, so as to alleviate the domain difference problem. Finally, a continual learning module is introduced to retain the information which is learned to limit the change of model parameters to deal with the catastrophic forgetting. We design trajectory prediction experiments that conform to real-world activities, and the experimental results verify the superiority of our proposed model. To the best of our knowledge, we are the first work that attempts to apply domain adaptation and continual learning methods to remedy real-world trajectory prediction problems. [ABSTRACT FROM AUTHOR]

The ability to rapidly recognize words and link them to referents is central to children's early language development. This ability, often called word recognition in the developmental literature, is typically studied in the looking-while-listening paradigm, which measures infants' fixation on a target object (vs. a distractor) after hearing a target label. We present a large-scale, open database of infant and toddler eye-tracking data from looking-while-listening tasks. The goal of this effort is to address theoretical and methodological challenges in measuring vocabulary development. We first present how we created the database, its features and structure, and associated tools for processing and accessing infant eye-tracking datasets. Using these tools, we then work through two illustrative examples to show how researchers can use Peekbank to interrogate theoretical and methodological questions about children's developing word recognition ability. [ABSTRACT FROM AUTHOR]

Chinese medicine (CM) is an important resource for human life understanding and discovery of drugs. However, due to the unclear pharmacological mechanism caused by unclear target, research and international promotion of many active components have made little progress in the past decades of years. CM is mainly composed of multi-ingredients with multi-targets. The identification of targets of multiple active components and the weight analysis of multiple targets in a specific pathological environment, that is, the determination of the most important target is the main obstacle to the mechanism clarification and thus hinders its internationalization. In this review, the main approach to target identification and network pharmacology were summarized. And BIBm (Bayesian inference modeling), a powerful method for drug target identification and key pathway determination was introduced. We aim to provide a new scientific basis and ideas for the development and international promotion of new drugs based on CM. [ABSTRACT FROM AUTHOR]

Itch is an unpleasant sensation that provokes the desire to scratch. While acute itch serves as a protective system to warn the body of external irritating agents, chronic itch is a debilitating but poorly-treated clinical disease leading to repetitive scratching and skin lesions. However, the neural mechanisms underlying the pathophysiology of chronic itch remain mysterious. Here, we identified a cell type-dependent role of the anterior cingulate cortex (ACC) in controlling chronic itch-related excessive scratching behaviors in mice. Moreover, we delineated a neural circuit originating from excitatory neurons of the ACC to the ventral tegmental area (VTA) that was critically involved in chronic itch. Furthermore, we demonstrate that the ACC→VTA circuit also selectively modulated histaminergic acute itch. Finally, the ACC neurons were shown to predominantly innervate the non-dopaminergic neurons of the VTA. Taken together, our findings uncover a cortex–midbrain circuit for chronic itch-evoked scratching behaviors and shed novel insights on therapeutic intervention. [ABSTRACT FROM AUTHOR]

The higher-order modified Korteweg–de Vries (mKdV) equation with constants background is revealed based on the Riemann–Hilbert problem (RHP). With the derivation of RHP, the one-soliton solution (oSS) and simple breather solution (sBS) of the higher-order mKdV equation are obtained for the first time. In addition, the dynamic behavior of the oSS and sBS were further discussed by some corresponding graphs with selecting appropriate parameters, which have not been studied in published works. [ABSTRACT FROM AUTHOR]

Although patients are undergoing similar lipid-lowering therapy (LLT) with statins, the outcomes of coronary plaque in diabetic mellitus (DM) and non-DM patients are different. Clinical data of 239 patients in this observational study with acute coronary syndrome was from our previous randomized trial were analyzed at 3 years, and 114 of them underwent OCT detection at baseline and the 1-year follow-up were re-anlayzed by a novel artificial intelligence imaging software for nonculprit subclinical atherosclerosis (nCSA). Normalized total atheroma volume changes (ΔTAVn) of nCSA were the primary endpoint. Plaque progression (PP) was defined as any increase in ΔTAVn. DM patients showed more PP in nCSA (ΔTAVn; 7.41 (− 2.82, 11.85) mm3 vs. − 1.12 (− 10.67, 9.15) mm3, p = 0.009) with similar reduction of low-density lipoprotein cholesterol (LDL-C) from baseline to 1-year. The main reason is that the lipid component in nCSA increases in DM patients and non-significantly decreases in non-DM patients, which leads to a significantly higher lipid TAVn (24.26 (15.05, 40.12) mm3 vs. 16.03 (6.98, 26.54) mm3, p = 0.004) in the DM group than in the non-DM group at the 1-year follow-up. DM was an independent predictor of PP in multivariate logistic regression analysis (OR = 2.731, 95% CI 1.160–6.428, p = 0.021). Major adverse cardiac events (MACEs) related to nCSA at 3 years were higher in the DM group than in the non-DM group (9.5% vs. 1.7%, p = 0.027). Despite a comparable reduction in LDL-C levels after LLT, more PP with an increase in the lipid component of nCSA and a higher incidence of MACEs at the 3-year follow-up was observed in DM patients. Trial registration: ClinicalTrials.gov. identifier: NCT02140801. [ABSTRACT FROM AUTHOR]

To explore the potential significance of the reverberation of calcification by comparing both intravascular ultrasound (IVUS) and optical coherence tomography (OCT) measurement post manual coregistration. The reverberation phenomenon is often detected by IVUS for severe calcified lesions post rotational atherectomy (RA), which is thought to be due to the glassy and smooth inner surfaces of calcifications. Because of the poor penetration of IVUS, it is impossible to measure the thickness of calcifications, and the relationship between multiple reverberations and the thickness of calcification lesions has not been reported before. A total of forty-nine patients with severe calcified coronary lesions that were detected by IVUS and OCT simultaneously were enrolled in our retrospective study. If reverberation phenomena were detected by IVUS, intravascular imaging (IVI) data (including distance between the IVUS catheter center and the inner surface of the reverberation signal, the intervals between all adjacent reverberation signals, the number of layers of reverberation in IVUS, and the thickness of the calcification in OCT) were measured at the same position and same direction (each cross-section had 4 mutually perpendicular directions) at 1-mm intervals. The correlation between each reverberation observational value and OCT data was the primary target in this retrospective study, and the correlation between reverberation and calcium crack post predilatation was analyzed in other 15 patients. Four hundred twenty-eight valid observational points were analyzed simultaneously by IVUS and OCT; among them, 300 points had a single layer of reverberation, 83 had double layers of reverberation and 42 had multiple layers (≥ 3 layers) of reverberation by IVUS detection post-RA. Multivariate logistic regression analysis showed that the number of layers of reverberation by IVUS was significantly related to the thickness of calcifications by OCT at the same point and in the same direction (p < 0.001). Single, double, and multiple layers of reverberation in IVUS correspond to median calcification thicknesses (interquartile ranges (IQRs)) of 0.620 mm (0.520–0.720), 0.950 mm (0.840–1.040) and 1.185 mm (1.068–1.373), respectively, by OCT detection. Another 100 points in other 15 patients with integrated IVUS data pre- and post-predilatation showed that only single layer of reverberation was related to calcium crack (p < 0.001). The number of layers of reverberation signal detected by IVUS is positively correlated with the thickness of calcifications measured by OCT post-RA and single layer of reverberation is correlated to calcium crack post-predilatation. [ABSTRACT FROM AUTHOR]

In microglia, Toll-like receptor 4 (TLR4) is well known to contribute to neuroinflammatory responses following brain ischemia. TLR4 is also expressed in neurons and can mediate the conduction of calcium (Ca2+) influx, but the mechanistic link between neuronal TLR4 signaling and brain ischemic injury is still poorly understood. Here, primary neuronal cell cultures from TLR4 knockout mice and mice with conditional TLR4 knockout in glutamatergic neurons (TLR4cKO) were used to establish ischemic models in vitro and in vivo, respectively. We found that deleting TLR4 would reduce the neuronal death and intracellular Ca2+ increasement induced by oxygen and glucose deprivation (OGD) or lipopolysaccharide treatment. Infarct volume and functional deficits were also alleviated in TLR4cKO mice following cerebral ischemia/reperfusion (I/R). Furthermore, TLR4 and N-methyl-d-aspartate receptor subunit 2B (NMDAR2B) were colocalized in neurons. Deletion of TLR4 in neurons rescued the upregulation of phosphorylated NMDAR2B induced by ischemia via Src kinase in vitro and in vivo. Downstream of NMDAR2B signaling, the interaction of neuronal nitric oxide synthase (nNOS) with postsynaptic density protein-95 (PSD-95) was also disrupted in TLR4cKO mice following cerebral I/R. Taken together, our results demonstrate a novel molecular neuronal pathway in which TLR4 signaling in neurons plays a crucial role in neuronal death and provide a new target for neuroprotection after ischemic stroke. [ABSTRACT FROM AUTHOR]

In order to prepare semitransparent and high efficiency ultrathin perovskite solar cells by improving photons absorption efficiency, different periodic structures are introduced and described in ultrathin perovskite solar cells. Perovskite periodic structure modifications are aimed to improve the current of the ultrathin perovskite solar cells, so as to obtain high performance of the ultrathin perovskite solar cells. The COMSOL Multi physics is used to construct the ultrathin perovskite solar cells with different periodic structures of spherical, rectangular and triangular, making the ultrathin devices (with very thin absorption layer) capable of full absorption of incident sunlight. The periodic structures effectively increase the contact area between functional layer and electrodes, thus increasing the current of the device. It is shown that the device current increased with increasing effective contact area. Compared with previous studies, the current of triangle structure solar cells have been increased by 19% compared to the layered structure. In addition, the results of simulations are compared with experiments of the layered structure. It is shown that the current of the prepared device was similar with our simulation results, which confirms the correctness of numerical calculations and robustness of obtained results. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The association between gut microbiome and chronic metabolic disease including polycystic ovary syndrome (PCOS), is well documented, however, the relationship between the gut microbiota and serum metabolites remains unknown. In this study, untargeted metabolomics together with a 16S rRNA gene sequencing tool was used to detect small molecule serum metabolites and the gut microbiome. We identified 15 differential metabolites between PCOS patients and the healthy control. Lysophosphatidylcholine (LPC) (18:2, 20:3, 18:1, P-16:0, 17:0, 15:0, 18:3, 20:4), phosphatidylcholine(PC), ganglioside GA2 (d18:1/16:0) and 1-linoleoylglycerophosphocholine were increased in the PCOS group, and the concentrations of phosphoniodidous acid, bilirubin, nicotinate beta-d-ribonucleotide and citric acid were decreased in the PCOS group, suggesting a lipid metabolism and energy metabolism disorder in the PCOS patients. The diversity of gut microbiota in PCOS group was lower than that in healthy controls. Escherichia/Shigella, Alistipes and an unnamed strain 0319_6G20 belonging to Proteobacteria were important distinguishing genera (LDA > 3.5) in PCOS. Prevotella_9 was positively correlated with phosphoniodidous acid, nicotinate beta-d-ribonucleotide and citric acid concentrations, and negatively correlated with the concentration of LPC (20:3) and 1-linoleoylglycerophosphocholine; Roseburia was negatively correlated with LPC concentration (20:4), while the characteristic genus 0319_6G20 of PCOS was positively correlated with LPC concentration (20:3) (COR > 0.45). SF-36 in the PCOS group was significantly lower than that in the healthy control (HC) group, which was associated with the presence of Escherichia-Shigella and Alistipes. Our finding demonstrated the correlation between the gut microbiota and serum metabolites in PCOS, and therefore characteristic gut microbiota and metabolites may play an important role in the insulin resistance and the mood changes of PCOS patients. [ABSTRACT FROM AUTHOR]

In this paper, a novel semiquantum private comparison (SQPC) protocol based on single kind of Bell states is proposed, which allows two classical parties to judge the equality of their private inputs securely and correctly under the help of a semi-honest third party (TP) who possesses complete quantum capabilities. TP is allowed to misbehave on her own but cannot conspire with anyone else. Our protocol needs none of unitary operations, quantum entanglement swapping or the reordering operations. Moreover, our protocol only needs to prepare single kind of Bell states as initial quantum resource. Detailed security analysis turns out that our protocol is secure against various outside and participant attacks. Compared with most of the existing SQPC protocols based on Bell states, our protocol is more feasible in practice. [ABSTRACT FROM AUTHOR]

Numerous studies focused on the association between lung function impairment and inflammation caused by fine particulate matter (PM2.5), but the causal relationships are difficult to clarify. In the current study, twenty healthy Chinese young adults who participated in 7 days of observation every four seasons were enrolled, and autoregression models (AM) and classification and regression trees (CART) in a machine learning framework were applied to analyze the association among PM2.5 exposure, inflammation, and lung function from a data structure perspective. There were strong cross-correlations between personal dose of PM2.5 (Dw) and lung functions (vital capacity (VC), forced vital capacity (FVC), etc.). These cross-correlation coefficients were associated with inflammatory indicators (uteroglobin (UG), serum amyloid (SAA), and fractional exhaled nitric oxide (FeNO)). CART reported that inflammatory indicators UG and SAA had the predictive ability of the directional association between Dw and FVC at 1-day lag and that high levels of UG and SAA predicted that PM2.5 exposure induced lung function decline. Consistently, lower lung function indicators at a 2-day lag after personal PM2.5 exposure predicted the high value of inflammatory indicator FeNO. Taken together, we applied machine learning algorithms to analyze repeated measurement data, finding that inflammation and lung function decline caused by PM2.5 could affect each other. [ABSTRACT FROM AUTHOR]

Ferroptosis is a recently discovered modulated cell death mechanism caused by the accumulation of iron-dependent lipid peroxides to toxic levels and plays an important role in tumor immunology and neurology. Recent studies have shown that ferroptosis may play a crucial role in bacterial infection pathogenesis, which may be useful in anti-infection therapies. However, how bacteria enter cells to induce ferroptosis after invading the host immune system remains largely unknown. In addition, the current studies only focus on the relationship between a single bacterial species or genus and host cell ferroptosis, and there is no systematic summary of its regulatory mechanism. Therefore, our review firstly sums up the role of ferroptosis in bacterial infection and its regulatory mechanism, and innovatively speculates on the function and potential mechanism of extracellular vesicles (EVs) in bacterial-induced ferroptosis, in order to provide possible novel directions and ideas for future anti-infection research. Key points: • Ferroptosis presents a novel mechanism for bacterial host interaction • EVs provide the potential mechanism for bacterial-induced ferroptosis • The relationship of EVs with ferroptosis provides possible directions for future treatment of bacterial infection [ABSTRACT FROM AUTHOR]

In this article, the issue of adaptive neural fixed-time tracking control for uncertain robotic manipulators subject to input saturation, external disturbance and prescribed constraints is studied. To handle the influence of input saturation, a novel auxiliary nonlinear dynamic system is constructed in which the system state is fixed-time stable. Radial basis function neural networks (RBF NNs) are used to approximate the system uncertainty. Instead of adjusting all weight vectors of RBF NNs, only one parameter is needed to be updated online. Then, based on performance function and auxiliary dynamic system, a fixed-time sliding mode controller with prescribed transient and steady-state performance is developed. Through theoretical analysis, it is concluded that the position tracking error can stabilize around the equilibrium point in fixed time and satisfy the prescribed requirements. Meanwhile, all signals in the closed-loop system are proved to be fixed-time stable by using the Lyapunov method. Finally, simulation results are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Let (M 1 , g (1)) , (M 2 , g (2)) be closed Riemannian spin manifolds. We study the existence of solutions of the Spinorial Yamabe problem on the product M 1 × M 2 equipped with a family of metrics ε - 2 g (1) ⊕ g (2) , ε > 0 . Via variational methods and blow-up techniques, we prove the existence of solutions which depend only on the factor M 1 , and which exhibit a spike layer as ε → 0 . Moreover, we locate the asymptotic position of the peak points of the solutions in terms of the curvature tensor on (M 1 , g (1)) . [ABSTRACT FROM AUTHOR]

The landscape plant, Cinnamomum camphora, is a broad-spectrum insect-repelling tree species, mainly due to a diversity of terpenoids, such as camphor. Despite its formidable chemical defenses, C. camphora is easily attacked and invaded by a monophagous weevil pest, Pagiophloeus tsushimanus. Deciphering the key olfactory signal components regulating host preference could facilitate monitoring and control strategies for this pest. Herein, two host volatiles, camphor and ocimene, induced GC-EAD/EAG reactions in both male and female adult antennae. Correspondingly, Y-tube olfactometer assays showed that the two compounds were attractive to both male and female adults. In field assays, a self-made trap device baited with 5 mg dose d(+)-camphor captured significantly more P. tsushimanus adults than isopropanol solvent controls without sexual bias. The trunk gluing trap device baited with bait can capture adults, but the number was significantly less than that of the self-made trap device and adults often fell after struggling. The cross baffle trap device never trapped adults. Neither ocimene nor isopropanol solvent control captured adults. When used in combination, ocimene did not enhance the attraction of d(+)-camphor to both female and male adults. These results indicate that d(+)-camphor is a key active compound of P. tsushimanus adults for host location. The combination of the host-volatile lure based on d(+)-camphor and the self-made trapping device is promising to monitor and provide an eco-friendly control strategy for this novel pest P. tsushimanus in C. camphora plantations. [ABSTRACT FROM AUTHOR]

Purposes: Few studies focus on the mental health of deaf population. This study aims to explore the association between social support and optimism and advance knowledge of why and for whom increased social support was effective. 771 deaf and hard-of-hearing (D/HH) students from two special education colleges in China were investigated. Questionnaires regarding social support, belief about adversity and optimism were distributed online. Multivariate linear regression and structural equation model were performed to examine mediating and moderating effects. This study found that perceived social support was positively associated with optimism in 771 Chinese college students who were D/HH. The study also found that having a belief in being able to face adversity successfully was associated with great social support. The relationship between a positive perspective regarding dealing with adversity and optimism was moderated by gender. For females, a positive belief regarding dealing with adversity was related to optimism. For males there was no relationship between belief about adversity and optimism. Additional consideration needs to be given to those D/HH students who report little social support and to females who do not believe they can successfully overcome adversity. Our study identified the risk population for intervention to improve mental health and well-being in D/HHcommunities. [ABSTRACT FROM AUTHOR]

Threat and extinction memories are crucial for organisms' survival in changing environments. These memories are believed to be encoded by separate ensembles of neurons in the brain, but their whereabouts remain elusive. Using an auditory fear-conditioning and extinction paradigm in male mice, here we discovered that two distinct projection neuron subpopulations in physical proximity within the insular cortex (IC), targeting the central amygdala (CeA) and nucleus accumbens (NAc), respectively, to encode fear and extinction memories. Reciprocal intracortical inhibition of these two IC subpopulations gates the emergence of either fear or extinction memory. Using rabies-virus-assisted tracing, we found IC-NAc projection neurons to be preferentially innervated by intercortical inputs from the orbitofrontal cortex (OFC), specifically enhancing extinction to override fear memory. These results demonstrate that IC serves as an operation node harboring distinct projection neurons that decipher fear or extinction memory under the top-down executive control from OFC. Ensembles of fear and extinction memories compete and interact to drive opposing behaviors. Here the authors identified insular cortical circuits as an executive gateway that decipher between fear and extinction memories via distinct subcortical pathways. [ABSTRACT FROM AUTHOR]

This paper solves the prescribed-time control problem for a class of robotic manipulators with system uncertainty and dead zone input. To make the system stable within a given convergence time T, a novel prescribed-time adaptive neural tracking controller is proposed by using the temporal scale transformation method and Lyapunov stability theory. Unlike the finite-time and the fixed-time stability where the convergence time depends on the controller parameters, the convergence time constant T is introduced into the proposed controller so that the closed-loop system will be stable within T. To cope with the system uncertainty, radial basis function neural networks (RBFNNs) are used and only need to update one parameter online. In addition, by choosing the same structure and parameters of RBFNNs, the proposed method can shorten the convergence time of the neural networks. Finally, simulation results are presented to demonstrate the effectiveness of the prescribed-time controller. [ABSTRACT FROM AUTHOR]

In this paper, a lightweight three-user secure quantum summation protocol is put forward by using single-particle states, which can accomplish the goal that three users cooperate together to calculate the modulo 2 addition of their private messages without the help of a third party. This protocol only requires single-particle states rather than quantum entangled states as the initial quantum resource and only needs single-particle measurements and Bell basis measurements. This protocol needs none of quantum entanglement swapping, the Pauli operations, the controlled-not (CNOT) operation, the Hadamard gate or a pre-shared private key sequence. Security analysis proves that this protocol is secure against both the outside attacks and the participant attacks. Compared with the existing two-dimensional three-user quantum summation protocols, this protocol more or less takes advantage over them on the aspects of the initial quantum resource, users' quantum measurement, the usage of quantum entanglement swapping, the usage of Pauli operations, the usage of CNOT operation or the usage of Hadamard gate. [ABSTRACT FROM AUTHOR]

Dynamic model calibration is an important issue and has broad applications in robotics. However, most of the previous works only focus on the robot dynamic calibration on torque level; that is, the identified parameters can predict the joint torques of robot. Unfortunately, little attention has been paid to the robot dynamic calibration on current level; that is, the identified parameters can predict the motor currents of robot. In order to address this problem, the main contribution of this article is to propose a systematic framework for robot dynamic calibration on current level, which includes modeling, identification and its applications. To the best of the authors' knowledge, it is the first systematic work on the robot dynamic calibration on current level. Specifically, a novel dynamic identification model on current level is firstly derived. Then, an identification method based on iterations is proposed to identify the dynamic parameters on current level. Afterward, two applications based on the identification results on current level are explored. One application is to use the current-level identification results for identifying joint drive gains accurately. The other application is to use the current-level identification results to compute current residuals for robot collision detection. The advantage of the current residuals is to contain less cumulative errors. Finally, the proposed theories are validated by various experiments on the UR10 robot. [ABSTRACT FROM AUTHOR]

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an attention mechanism can be regarded as a dynamic weight adjustment process based on features of the input image. Attention mechanisms have achieved great success in many visual tasks, including image classification, object detection, semantic segmentation, video understanding, image generation, 3D vision, multimodal tasks, and self-supervised learning. In this survey, we provide a comprehensive review of various attention mechanisms in computer vision and categorize them according to approach, such as channel attention, spatial attention, temporal attention, and branch attention; a related repository https://github.com/MenghaoGuo/Awesome-Vision-Attentions is dedicated to collecting related work. We also suggest future directions for attention mechanism research. [ABSTRACT FROM AUTHOR]

Sparse Subspace Clustering (SSC) based clustering methods have achieved great success since these methods could effectively explore the low-dimensional subspace structure embedded in the original data. However, most existing subspace clustering methods are designed for vectorial data from linear spaces, thus not suitable for high dimensional data (such as imageset or video) with the non-linear manifold structure. In this paper, we propose a unified framework about kernelized sparse subspace clustering on Grassmann manifolds, which can learn the optimal affinity graph with the best clustering index matrix. The experimental results on six public datasets illustrate that the proposed method is obviously better than most related clustering methods based on Grassmann manifolds. [ABSTRACT FROM AUTHOR]

In this paper, we put forward a novel single-state three-party semiquantum key agreement (SQKA) protocol with three-particle GHZ entangled states first. Different with previous quantum key agreement (QKA) protocols, the proposed single-state three-party SQKA protocol can realize the goal that a quantum party and two classical parties who only possess limited quantum capabilities equally contribute to the generation of a shared private key over quantum channels. Detailed security analysis turns out that the proposed single-state three-party SQKA protocol is secure against several famous attacks from an outside eavesdropper, such as the Trojan horse attack, the entangle-measure attack, the measure-resend attack and the intercept-resend attack. Moreover, it can resist the participant attack, which means that the shared private key cannot be determined fully by any nontrivial subset of three parties. The proposed single-state three-party SQKA protocol has the following nice features: (1) it only employs one kind of three-particle GHZ entangled states as initial quantum resource; (2) it does not need pre-shared keys among different parties; (3) it does not need unitary operations or quantum entanglement swapping. Finally, we generalize the proposed single-state three-party SQKA protocol into the case of N -party by only employing one kind of N -particle GHZ entangled states as initial quantum resource, which inherits the nice features of its three-party counterpart. [ABSTRACT FROM AUTHOR]

Twenty six novel pyrimidin-4-amine derivatives containing the 1,2,4-oxadiazole motif were synthesized. Their chemical structures were confirmed by 1H nuclear magnetic resonance (NMR), 13C NMR, and highresolution mass spectrography. The insecticidal activity results indicated that some of them possessed excellent insecticidal activity (100%) against Mythimna separate, especially for compounds 6d, 6f, 6o, 6w, 6y and 6z. These compounds exhibited no activity against the insects Aphis medicagini and Tetranychus cinnabarinus. The structure-insecticidal activity relationships are discussed. Density functional theory analysis can potentially be used to design more active compounds. These results provide useful insecticide design information for further optimization. [ABSTRACT FROM AUTHOR]

With the advent of virtualization techniques and software-defined networking (SDN), network function virtualization (NFV) shifts network functions (NFs) from hardware implementations to software appliances, between which exists a performance gap. How to narrow the gap is an essential issue of current NFV research. However, the cumbersomeness of deployment, the water pipe effect of virtual network function (VNF) chains, and the complexity of the system software stack together make it tough to figure out the cause of low performance in the NFV system. To pinpoint the NFV system performance issues, we propose NfvInsight, a framework for automatic deployment and benchmarking VNF chains. Our framework tackles the challenges in NFV performance analysis. The framework components include chain graph generation, automatic deployment, and fine granularity measurement. The design and implementation of each component have their advantages. To the best of our knowledge, we make the first attempt to collect rules forming a knowledge base for generating reasonable chain graphs. NfvInsight deploys the generated chain graphs automatically, which frees the network operators from executing at least 391 lines of bash commands for a single test. To diagnose the performance bottleneck, NfvInsight collects metrics from multiple layers of the software stack. Specifically, we collect the network stack latency distribution ingeniously, introducing only less than 2.2% overhead. We showcase the convenience and usability of NfvInsight in finding bottlenecks for both VNF chains and the underlying system. Leveraging our framework, we find several design flaws of the network stack, which are unsuitable for packet forwarding inside one single server under the NFV circumstance. Our optimization for these flaws gains at most 3x performance improvement. [ABSTRACT FROM AUTHOR]

In this study, 123 PM2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM2.5 concentration was 80.5 ± 38.2 μg/m3, with higher PM2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM2.5 mass concentration, respectively. SO42−, NO3− and NH4+ were the dominant components, accounting for 40.2% of PM2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO3−/SO42− was 0.86 ± 0.72, indicating that stationary sources play dominant role on PM2.5 concentration. The ratio of OC/EC was 2.9 ± 1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the predictors for second-stage posterior direct decompression (PDD) after lateral lumbar interbody fusion (LLIF) procedure. Methods: We studied patients who underwent LLIF for degenerative lumbar spinal stenosis in the last five years, from July 2016 to June 2021. All surgical levels were grouped according to Schizas' central canal stenosis (CCS) classification, Pathria's facet joint degeneration (FJD) classification, Bartynski's lateral recess stenosis (LRS) classification, and Lee's foraminal stenosis (FS) classification. Second-stage PDD rates of each subgroup and their annual change were analyzed. Evaluation of risk factors associated with PDD was investigated. Results: A total of 901 segments from 557 patients were included. The overall PDD rate was 29.97%. An overall PDD rate of 75.21% for grade D CCS, 29.74% for grade C CCS, 41.67% for grade 3 FJD, 37.61% for grade 3 LRS, and 40.70% for grade 3 FS was shown. While there was a continuous decline in annual PDD rate in the past four years, the annual PDD rate for grade D remained at very high levels. Logistic regression analysis had shown grade D CCS as the utmost risk factor for PDD (OR = 17.77). And grade 3 LRS (OR = 4.63), grade 3 FS (OR = 2.42), grade C CCS (OR = 2.41), and grade 3 FJD (OR = 2.04) were also moderately correlated with PDD, which meant they only moderately increased the risk of PDD. Conclusion: Extreme severe lumbar CCS (grade D) is the greatest determinant to perform the second-stage PDD procedure after LLIF. [ABSTRACT FROM AUTHOR]