Decades of cognitive neuroscience research has shown that where we look is intimately connected to what we remember. In this article, we review findings from human and nonhuman animals, using ...behavioral, neuropsychological, neuroimaging, and computational modeling methods, to show that the oculomotor and hippocampal memory systems interact in a reciprocal manner, on a moment‐to‐moment basis, mediated by a vast structural and functional network. Visual exploration serves to efficiently gather information from the environment for the purpose of creating new memories, updating existing memories, and reconstructing the rich, vivid details from memory. Conversely, memory increases the efficiency of visual exploration. We call for models of oculomotor control to consider the influence of the hippocampal memory system on the cognitive control of eye movements, and for models of hippocampal and broader medial temporal lobe function to consider the influence of the oculomotor system on the development and expression of memory. We describe eye movement–based applications for the detection of neurodegeneration and delivery of therapeutic interventions for mental health disorders for which the hippocampus is implicated and memory dysfunctions are at the forefront.
Decades of cognitive neuroscience research has shown that where we look is intimately connected to what we remember. In this article, we review findings from human and nonhuman animals, using behavioral, neuropsychological, neuroimaging, and computational modeling methods, to show that the oculomotor and hippocampal memory systems interact in a reciprocal manner, on a moment‐to‐moment basis, mediated by a vast structural and functional network.
The diagnosis of the key components of rotating machinery systems is essential for the production efficiency and quality of manufacturing processes. The performance of the traditional diagnosis ...method depends heavily on feature extraction, which relies on the degree of individual's expertise or prior knowledge. Recently, a deep learning (DL) method is applied to automate feature extraction. However, training in the DL method requires a massive amount of sensor data, which is time consuming and poses a challenge for its applications in engineering. In this paper, a new data-driven fault diagnosis method based on compressed sensing (CS) and improved multiscale network (IMSN) is proposed to recognize and classify the faults in rotating machinery. CS is used to reduce the amount of raw data, from which the fault information is discovered. At the same time, it can be used to generate sufficient training samples for the subsequent learning. The one-dimensional compressed signal is converted to two-dimensional image for further learning. An IMSN is established for learning and obtaining deep features. It improves the diagnosis performance of the DL process. The faults of the key components are identified from a softmax model. Experimental analysis is performed to verify effectiveness of the proposed data-driven fault diagnosis method.
An extremely stable hydrogen-bonded organic framework, HOF-8, was fabricated. HOF-8 is not only thermally stable but also stable in water and common organic solvents. More interestingly, desolvated ...HOF-8 exhibits high CO2 adsorption as well as highly selective CO2 and C6H6 adsorption at ambient temperature.
Forming new associations is a fundamental process of building our knowledge system. At the brain level, how prior-knowledge influences acquisition of novel associations has not been thoroughly ...investigated. Based on recent cognitive neuroscience literature on multiple-component memory processing, we hypothesize that prior-knowledge triggers additional evaluative, semantic, or episodic-binding processes, mainly supported by the ventromedial prefrontal cortex (vmPFC), anterior temporal pole (aTPL), and hippocampus (HPC), to facilitate new memory encoding. To test this hypothesis, we scanned 20 human participants with functional magnetic resonance imaging (fMRI) while they associated novel houses with famous or nonfamous faces. Behaviorally, we found beneficial effects of prior-knowledge on associative memory. At the brain level, we found that the vmPFC and HPC, as well as the parahippocampal place area (PPA) and fusiform face area, showed stronger activation when famous faces were involved. The vmPFC, aTPL, HPC, and PPA also exhibited stronger activation when famous faces elicited stronger emotions and memories, and when associations were later recollected. Connectivity analyses also suggested that HPC connectivity with the vmPFC plays a more important role in the famous than nonfamous condition. Taken together, our results suggest that prior-knowledge facilitates new associative encoding by recruiting additional perceptual, evaluative, or associative binding processes.
Two metal–organic frameworks Zn2(Tipa)2(OH)·3NO3·12H2O (FIR-53, FIR denotes Fujian Institute of Research, Tipa = tris(4-(1H-imidazol-1-yl)phenyl)amine)) and Zn(Tipa)·2NO3·DMF·4H2O) (FIR-54) ...with large nanotubular channels were synthesized via Zn(II) ions coordinate the neutral Tipa ligand. The framework of FIR-53 contains 1D channels along the c axis with a cross section of 18 × 13 Å2. FIR-54 also consists of large channels with the 10.5 × 10.5 Å2 open windows. These porous materials efficiently trap Cr2O7 2– inorganic pollutant ions via the single-crystal-to-single-crystal (SC-SC) approach. The Cr2O7 2– uptake capacities of FIR-53 and FIR-54 are high to 74.2 and 103 mg/g, respectively. Furthermore, the Cr2O7 2– trapping–releasing process of FIR-53 displays good regeneration. Meaningfully, the structure of FIR-53 after ion exchange can be accurately obtained by single-crystal X-ray diffraction, which further elaborates the SC-SC transformation.
It is known that prior knowledge can facilitate memory acquisition. It is unclear, however, whether prior knowledge can affect post-encoding brain activity to facilitate memory consolidation. In this ...fMRI study, we asked participants to associate novel houses with famous/nonfamous faces and investigated how associative-encoding tasks with/without prior knowledge differentially affected post-encoding brain connectivity during rest. Besides memory advantages in the famous condition, we found that post-encoding hippocampal connectivity with the fusiform face area (FFA) and ventral-medial-prefrontal cortex (vmPFC) was stronger following encoding of associations with famous than non-famous faces. Importantly, post-encoding functional connectivity between the hippocampus (HPC) and FFA, and between the anterior temporal pole region (aTPL) and posterior perceptual regions (i.e., FFA and the parahippocampal place area), together predicted a large proportion of the variance in subsequent memory performance. This prediction was specific for face-house associative memory, not face/house item memory, and only in the famous condition where prior knowledge was involved. These results support the idea that when prior knowledge is involved, the HPC, vmPFC, and aTPL, which support prior episodic, social-evaluative/schematic, and semantic memories, respectively, continue to interact with each other and posterior perceptual brain regions during the post-encoding rest to facilitate off-line processing of the newly formed memory, and enhance memory consolidation.
Lithium (Li) metal is promising in the next‐generation energy storage systems. However, its practical application is still hindered by the poor cycling performance and serious safety issues for the ...consequence of dendritic Li. Herein, a dendrite‐free Li/carbon nanotube (CNT) hybrid is proposed, which is fabricated by direct coating molten Li on CNTs, for Li‐metal batteries. The favorable thermodynamic and kinetic conditions are the powerful force to drive the rapid lift upwards and infusion of molten Li into CNTs network, which is the key to form a uniform metallic layer in Li/CNTs hybrid. The obtained hybrid indicates super‐stable functions even at an ultrahigh current density of 40 mA cm−2 for 2000 cycles with a stripping/plating capacity of 2 mAh cm−2 in symmetric cells. Subsequently, this hybrid also demonstrates a significantly decreased resistance, excellent cycling stability at high current density and flexibility in the full Li‐S battery. This work provides valuable concepts in fabricating Li anodes toward Li‐metal batteries and beyond for their high‐level services.
A dendrite‐free Li/carbon nanotube (CNT) hybrid is fabricated by direct coating of molten Li on CNTs for Li‐metal batteries. Favorable thermodynamic and kinetic conditions are a powerful force to drive the rapid lift upward and infusion of molten Li into CNTs network. The obtained hybrid exhibits superstable function even at an ultrahigh current density.
The quality control of plastic products is an essential aspect of the plastic injection molding (PIM) process. However, the warpage and shrinkage deformations continue to exist because the PIM ...process is easily interfered with by several related or independent process parameters. Thus, great efforts have been devoted to optimizing process parameters to minimize the warpage and shrinkage deformations of products during the last decades. In this review, we begin by introducing the manufacturing process in PIM and the cause of warpage and shrinkage deformations, followed by the mechanism about how process parameters, like mold temperature, melt temperature, injection rate, injection pressure, holding pressure, holding and cooling duration, affect those defects. Then, we summarize the recent progress of the design of experiments and four advanced methods (artificial neural networks, genetic algorithm, response surface methodology, and Kriging model) on optimizing process parameters to minimize the warpage and shrinkage deformations. In the end, future perspectives of quality control in injection molding machines are discussed.
The selectivity control of Pd nanoparticles (NPs) in the direct CO esterification with methyl nitrite toward dimethyl oxalate (DMO) or dimethyl carbonate (DMC) remains a grand challenge. Herein, Pd ...NPs are incorporated into isoreticular metal–organic frameworks (MOFs), namely UiO‐66‐X (X=‐H, ‐NO2, ‐NH2), affording Pd@UiO‐66‐X, which unexpectedly exhibit high selectivity (up to 99 %) to DMC and regulated activity in the direct CO esterification. In sharp contrast, the Pd NPs supported on the MOF, yielding Pd/UiO‐66, displays high selectivity (89 %) to DMO as always reported with Pd NPs. Both experimental and DFT calculation results prove that the Pd location relative to UiO‐66 gives rise to discriminated microenvironment of different amounts of interface between Zr‐oxo clusters and Pd NPs in Pd@UiO‐66 and Pd/UiO‐66, resulting in their distinctly different selectivity. This is an unprecedented finding on the production of DMC by Pd NPs, which was previously achieved by Pd(II) only, in the direct CO esterification.
Incorporating Pd nanoparticles into metal–organic frameworks (MOFs) exhibits high selectivity for dimethyl carbonate (DMC), while Pd nanoparticles on MOFs and other supports give high selectivity for dimethyl oxalate (DMO) in the direct CO esterification with methyl nitrite. The Lewis acid microenvironment surrounding Pd NPs is responsible for the reversed product selectivity.
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