Based on the newly designed ligand 4′‐(3,5‐dicarboxyphenyl)‐4,2′:6′,4′′‐terpyridine (DCTP), a unique semi‐conductive 3D framework {CuΙCuΙΙ2(DCTP)2NO3⋅1.5 DMF}n (1) with a narrow band gap of 2.1 eV, ...was obtained and structurally characterized. DFT calculations with van de Waals correction employed to explore the electronic structure of 1, clearly revealed its semi‐conductive behavior. Furthermore, we found that 1 exhibits a superior band alignment with water to produce hydrogen and degrade organic pollutants. Without adding any photosensitizers, 1 displays an efficiently photocatalytic hydrogen production in water based on the photo‐generated electrons under UV/Vis light. 1 also exhibits excellent photo‐degradation of methyl blue under visible‐light owing to the strong oxidization of excited holes. It is the first example of MOFs with doubly photocatalytic activities related to photo‐generated electrons and holes, respectively.
Narrow band gap: The metal–organic framework (MOF) {CuΙCuΙΙ2(DCTP)2NO3⋅1.5 DMF}n has a narrow band gap of 2.1 eV and is a semiconductor. Theoretical and experimental investigations confirmed its performance in photocatalytic hydrogen generation and in organic‐dye degradation. It is the first report for MOFs exhibiting two different photocatalytic activities based on photo‐generated electrons and holes.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Excellent electroconductivity, fire resistance, and mechanical properties are several important indexes for electromagnetic shielding sealing materials. In this work, a novel functionalized graphene ...decorated with a nickel-Schiff base (rGO-Salen-Ni) was first synthesized
via
a chemical modification process, and applied in enhancing the mechanical properties, electroconductivity, and fire resistance of a thermoplastic polyurethane elastomer (TPU). The experimental result illustrated that the rGO-Salen-Ni significantly improved the above vital properties of TPU. First, the tensile strength, elongation at break, and storage modulus of the TPU containing only 1.5 wt% rGO-Salen-Ni (TPU/rGO-Salen-Ni1.5) were respectively increased by 1.50 times, 1.58 times, and 2.17 times; second, the electrical conductivity of the TPU/rGO-Salen-Ni1.5 was increased by 5 orders of magnitude in comparison with that of a pure TPU, up to 7.3 × 10
−5
S m
−1
; finally, the TPU/rGO-Salen-Ni1.5 displayed excellent flame retardancy; for instance, the peak of heat release rate, total heat release, and total smoke production were respectively decreased by 43%, 22%, and 28% compared with the corresponding values of pure TPU. The analysis of the enhancement in mechanical properties and electroconductivity of TPU/rGO-Salen-Ni revealed that the uniform dispersion of rGO-Salen-Ni, resulting from the incorporation of the nickel-Schiff base into the GO, was the leading reason for their improvements. The study on the flame-retardant mechanism demonstrated that a more continuous and compact protective layer related to the nickel-Schiff base played the key role in the excellent fire resistance of TPU/rGO-Salen-Ni. The rGO-Salen-Ni shows great potential for application in electromagnetic shielding sealing materials.
Excellent electroconductivity, fire resistance, and mechanical properties are several important indexes for electromagnetic shielding sealing materials.
To achieve efficient and real-time classification and recognition of freshwater fish on limited equipment resources, this study proposes a method based on the YOLOv5s network to learn freshwater fish ...dataset images based on machine vision technology. Firstly, replace the backbone network of YOLOv5s with ShuffleNetV2 of the lightweight network to improve the efficiency of architecture design and ensure the detection speed. Secondly, the lightweight convolution GSConv is introduced to reduce the complexity of the network, maintain the accuracy of the network, and achieve the lightweight effect. Finally, the combination of ShuffleNetV2 and lightweight convolution GSConv can significantly improve the lightweight effect while maintaining accuracy. The algorithm was validated with four datasets of Rhodeinae, goldfish, grass carp, and stone moroko, which are all typical carp. The results showed that the improved network model FLOPs is 4.9 G, which was 69% less than YOLOv5s, the model size was 6.1 MB, which was 58% less than YOLOv5s, and the improved model mAP0.5 could reach 95.5%.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Precise synthesis of polyoxometalates (POMs) is important for the fundamental understanding of the relationship between the structure and function of each building motif. However, it is a ...great challenge to realize the atomic-level tailoring of specific sites in POMs without altering the major framework. Herein, we report the case of Ce-mediated molecular tailoring on gigantic {Mo
132
}, which has a closed structural motif involving a never seen {Mo
110
} decamer. Such capped wheel {Mo
132
} undergoes a quasi-isomerism with known {Mo
132
} ball displaying different optical behaviors. Experiencing an ‘Inner-On-Outer’ binding process with the substituent of {Mo
2
} reactive sites in {Mo
132
}, the site-specific Ce ions drive the dissociation of {Mo
2
*
} clipping sites and finally give rise to a predictable half-closed product {Ce
11
Mo
96
}. By virtue of the tailor-made open cavity, the {Ce
11
Mo
96
} achieves high proton conduction, nearly two orders of magnitude than that of {Mo
132
}. This work offers a significant step toward the controllable assembly of POM clusters through a Ce-mediated molecular tailoring process for desirable properties.
Often real-world datasets are incomplete and contain some missing attribute values. Furthermore, many data mining and machine learning techniques cannot directly handle incomplete datasets. Missing ...value imputation is the major solution for constructing a learning model to estimate specific values to replace the missing ones. Deep learning techniques have been employed for missing value imputation and demonstrated their superiority over many other well-known imputation methods. However, very few studies have attempted to assess the imputation performance of deep learning techniques for tabular or structured data with continuous values. Moreover, the effect on the imputation results when the continuous data need to be discretized has never been examined. In this paper, two supervised deep neural networks, i.e., multilayer perceptron (MLP) and deep belief networks (DBN), are compared for missing value imputation. Moreover, two differently ordered combinations of data discretization and imputation steps are examined. The results show that MLP and DBN significantly outperform the baseline imputation methods based on the mean, KNN, CART, and SVM, with DBN performing the best. On the other hand, when considering the discretization of continuous data, the order in which the two steps are combined is not the most important, but rather, the chosen imputation algorithm. That is, the final performance is much better when using DBN for imputation, regardless of whether discretization is performed in the first or second step, than the other imputation methods.
•Deep learning for imputing missing continuous values of tabular or structured data is studied.•In particular, multilayer perceptron (MLP) and deep belief networks (DBN) are employed.•Two different ordered combinations of data discretization and imputation steps are examined.•MLP and DBN significantly outperform the baseline imputation methods.•DBN is the better choice for imputation when the discretization of continuous data is required.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
We numerically investigate both the streaking time delay and the oscillation amplitude of the momentum shift of the photoelectron and justify them physically by developing a classical model ...based on the weak field approximation. The streaking time delay is insensitive to the extreme ultraviolet (XUV) pulse duration, while the oscillation amplitude obviously reduces as the XUV duration increases. This XUV duration dependence is attributed to the ionization probability of electron at initial times other than the peak of the XUV pulse. We propagate the classical electron trajectories originating at different initial times in the coupled Coulomb-laser (IR) potential and average the momentum shift for each trajectory over the width of the XUV pulse. By extracting the streaking time delay and the oscillation amplitude from this averaged momentum shift, the classical model results and the time-dependent Schrödinger equation results are found to be in good agreement. Both the insensitivity of the streaking time delay and the sensitivity of the oscillation amplitude on the XUV pulse width are well explained by our classical model considering initial ionization time average. Analytical estimation for the oscillation amplitude is obtained from the model of initial ionization time average.
A stable metal–organic framework pillared by Keggin‐type polyoxometalate, Cu6(Trz)10(H2O)4H2SiW12O40⋅8 H2O (Trz=1,2,4‐triazole) (1), has been prepared under hydrothermal condition. The 2D layer ...structure with a 22‐member ring was formed by Cu2+ ions, which are connected with each other via the Trz ligands on the ab plane. Thus, the 2D layers are further interconnected through Keggin polyoxoanions to generate a 3D porous network with a small 1D channel. Moreover, the presence of polyoxoanions make it exhibit selective adsorption of water and proton‐conducting properties. Additionally it showed efficient intrinsic peroxidase‐like activity, providing a simple and sensitive colorimetric assay to detect H2O2.
Squaring up: A highly stable polyoxometalate‐pillared metal–organic framework, which has been prepared by a hydrothermal method (see figure), exhibits selective adsorption of water, proton‐conducting properties, and efficient intrinsic peroxidase‐like activity, providing a simple and sensitive colorimetric assay for the detection of H2O2.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Intuitive, efficient, and unconstrained interactions require human–machine interfaces (HMIs) to accurately recognize users' manipulation intents. Susceptibility to interference and conditional usage ...mode of HMIs will lead to poor experiences that limit their great interaction potential. Herein, a programmable and ultrasensitive haptic interface enabling closed‐loop human–machine interactions is reported. A cross‐scale architecture design strategy is proposed to fabricate the haptic interface, which optimizes the hierarchical contact process. The synergistic optimization of the cross‐scale architecture between carbon nanotubes and the multiscale sensing structure realizes a haptic interface with ultrahigh sensitivity and a wide detection range of 15.1 kPa−1 and 180 kPa, which are improved by more than 900% over the performance of the common interface. The rapid response time of <5 ms and the limit of detection of 8 Pa of the haptic interface far surpass the somatosensory perception of human skin, which enables the haptic interface to accurately recognize interactive intents. A wireless pressure‐data interactive glove (wireless PDI glove) is designed and realizes a round‐the‐clock operation, noise immunity, and efficient interactive control, which perfectly compensate for the flaws of typical vision and voice recognition modes.
Carbon nanotube and methylcellulose are combined to achieve complementary advantages for preparing sensitive composite material with high electrical property and high stability. Through flexible transfer technology, a cross‐scale architecture design strategy with the sensitive composite material is proposed to construct high‐performance haptic interface. A wireless pressure‐data interactive glove assembled with the haptic interfaces efficiently realizes free, round‐the‐clock, and closed‐loop interactions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The aim of this study is to reveal the clinical and histopathological features of HBsAg-positive and HBeAg-positive chronic hepatitis B infected patients with high level of HBV DNA, from 17 hospitals ...and medical centres in China, with alanine aminotransferase levels within the lower region of normal range versus those with levels within the upper region of normal range and to investigate the clinical risk factors for the requirement of treatment through the examination of liver biopsy.
Liver biopsy was performed on high level of HBV DNA of 455 patients with HBsAg-positive and HBeAg-positive chronic hepatitis B infection and persistently normal alanine aminotransferase level. Liver necroinflammation and fibrosis were graded per the Knodell histological activity index and Ishak's fibrosis score, respectively. Univariate analysis of the clinical parameters versus necroinflammation and fibrosis was carried out.
Of the subjects in this multicentre-based study, 5.49% and 10.11% had significant necroinflammation with Knodell histological activity index ≥ 9 and hepatic fibrosis stages with Ishak scores ≥ 3, respectively. The subjects were stratified into three age groups (30-39, 40-49 and ≥ 50 years), and our data clearly suggested that age, particularly in the age group over 50, was an independent predictor of liver necroinflammation and fibrosis. Lower HBV-DNA viral levels were found in patients with Knodell histological activity index ≥ 9 or advanced fibrosis (Ishak scores ≥ 3).
Our results showed that histological changes in liver tissues were observed in a significant proportion of patients with persistently normal alanine aminotransferase level. According to the data evaluation results, liver biopsy is advisable for HBeAg-positive chronic hepatitis B infected patients aged older than 40 and high HBV-DNA viral load in China.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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