The present study explores the intricate dynamics influencing the self-efficacy of Chinese university students through the interplay of participation in artistic activities, positive psychological ...capital, and emotional intelligence. In the context of technological advancements and various challenges post pandemic, this study delves into the multifaceted aspects of university life, where arts education plays a pivotal role in addressing students' emotional needs. By integrating emotional intelligence with self-efficacy, this study underscores the positive impact of artistic engagement on self-efficacy, while emphasizing on the transformative power of these pursuits. Also, this study establishes that the optimism and resilience contribute to this relationship by considering the mediating role of positive psychological capital. The moderating influence of emotional intelligence in the complex dynamics between arts education and positive psychological capital is another concern, thereby emphasizing the nuanced role of emotional intelligence. With a structured set of questions that were administered to 673 participants with 93.61% recovery rate, this study performs the Cronbach's α-test, validation factor, and several related tests in
29.0,
, and
25.0 software. Current results shows the importance of a holistic approach in Chinese institutions. With a focus on promoting artistic engagement to enhance students' self-efficacy, this study determines the profound impact of arts education on students' overall wellbeing and educational experience. In conclusion, this research highlights the constructive impact of artistic engagement on the self-efficacy of Chinese university students. Chinese institutions should encourage a varied range of artistic engagements as a response to the contemporary challenges confronted by their students.
The extraction speed of current art exchange element is relatively low, and its effect is relatively poor, so is the effect of art exchange. Therefore, a new art exchange method has been developed ...with respect to artificial intelligence technology, which analyzes the background of current art, providing a good environment foundation for the exchange place to integrate the artificial intelligence technology after the exchange, and interacts with the network artificial intelligence technology and the multimedia multielement exchange art in the control. It has been proved through practice that artificial intelligence technology embodies the advantages of design tools and the improvement of efficiency in modern art exchange; it allows the current diversity of artistic interaction and enables it to obtain new development in the current new technological background.
The efficient separation of photoexcited electrons and holes is crucial for improving the activity of photocatalytic hydrogen evolution. Herein, an efficient core–shell p–n heterojunction of ...ZnIn2S4@CuInS2 microflowers has been devised and fabricated by two-step hydrothermal method. The results revealed that the marigold-like microspheres of ZnIn2S4@CuInS2 heterojunction consisted of thin nanosheets, matched well in the lattice, and had a large interface contact area, which boosted charge separation and transfer for solar hydrogen production. Moreover, the intimate interfacial contact between n-type ZnIn2S4 and p-type CuInS2 resulted in the formation of unique p–n heterojunction, which further promoted charge separation due to the built-in electric field. As a consequence, the ZnIn2S4@CuInS2 photocatalyst with 5 atom % CuInS2 showed the highest production of H2 evolution (about 1168 μmol·g–1) among all prepared photocatalysts, which was nearly 4-fold the amount of the hydrogen production for the pristine ZnIn2S4. Therefore, the core–shell p–n heterojunction is an efficient structure design for the utilization of solar energy to obtain clean energy.
Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition ...algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.
Thrombocytopenia has been implicated in patients infected with severe acute respiratory syndrome coronavirus 2, while the association of platelet count and changes with subsequent mortality remains ...unclear.
The clinical and laboratory data of 383 patients with the definite outcome by March 1, 2020 in the Central Hospital of Wuhan were reviewed. The association between platelet parameters and mortality risk was estimated by utilizing Cox proportional hazard regression models.
Among the 383 patients, 334 (87.2%) were discharged and survived, and 49 (12.8%) died. Thrombocytopenia at admission was associated with mortality of almost three times as high as that for those without thrombocytopenia (P < 0.05). Cox regression analyses revealed that platelet count was an independent risk factor associated with in-hospital mortality in a dose-dependent manner. An increment of per 50 × 10
9
/L in platelets was associated with a 40% decrease in mortality (hazard ratio: 0.60, 95%CI: 0.43, 0.84). Dynamic changes of platelets were also closely related to death during hospitalization.
Baseline platelet levels and changes were associated with subsequent mortality. Monitoring platelets during hospitalization may be important in the prognosis of patients with coronavirus disease in 2019.
Abstract
Electrochemical CO
2
reduction (ECR) is highly attractive to curb global warming. The knowledge on the evolution of catalysts and identification of active sites during the reaction is ...important, but still limited. Here, we report an efficient catalyst (Ag-D) with suitable defect concentration operando formed during ECR within several minutes. Utilizing the powerful fast operando X-ray absorption spectroscopy, the evolving electronic and crystal structures are unraveled under ECR condition. The catalyst exhibits a ~100% faradaic efficiency and negligible performance degradation over a 120-hour test at a moderate overpotential of 0.7 V in an H-cell reactor and a current density of ~180 mA cm
−2
at −1.0 V vs. reversible hydrogen electrode in a flow-cell reactor. Density functional theory calculations indicate that the adsorption of intermediate COOH could be enhanced and the free energy of the reaction pathways could be optimized by an appropriate defect concentration, rationalizing the experimental observation.
Person re-identification aims to identify the same pedestrians across different camera views at different locations. This important yet difficult intelligent video analysis problem remains a vigorous ...area of research due to demands for performance improvements. Person re-identification involves two main steps: feature representation and metric learning. Handcrafted features, such as color and texture histograms, are frequently used for person re-identification, but most handcrafted features are limited by not being directly applicable to practical problems. Deep learning methods have obtained the state-of-the-art performance in a wide variety of applications, including image annotation, face recognition, and speech recognition. However, deep learning features are heavily dependent on large-scale labeling of samples. In this paper, by utilizing the Cross-view Quadratic Discriminant Analysis (XQDA) metric learning, we propose a novel scheme called deep multi-view feature learning (DMVFL), which exploits the collaboration between handcrafted and deep learning features in a simple but effective way. Furthermore, we prove that the XQDA is a robust algorithm. Extensive experiments on two challenging person re-identification data sets (VIPeR and GRID) demonstrate that DMVFL improves on current state-of-the-art methods.
In comparison with the fast development of binary mixture separations, ternary mixture separations are significantly more difficult and have rarely been realized by a single material. Herein, a new ...strategy of tuning the gate‐opening pressure of flexible MOFs is developed to tackle such a challenge. As demonstrated by a flexible framework NTU‐65, the gate‐opening pressure of ethylene (C2H4), acetylene (C2H2), and carbon dioxide (CO2) can be regulated by temperature. Therefore, efficient sieving separation of this ternary mixture was realized. Under optimized temperature, NTU‐65 adsorbed a large amount of C2H2 and CO2 through gate‐opening and only negligible amount of C2H4. Breakthrough experiments demonstrated that this material can simultaneously capture C2H2 and CO2, yielding polymer‐grade (>99.99 %) C2H4 from single breakthrough separation.
One‐step sieving separation of a ternary gas mixture (C2H2/CO2/C2H4) has been realized by a flexible MOF NTU‐65. Successful separation relies on tuning the gate‐opening pressure of this flexible framework to optimize the separation performance. Under an optimized temperature, NTU‐65 adsorbed large amount of C2H2 and CO2 but a negligible amount of C2H4, readily producing high‐purity C2H4 through a separation column.
Person re-identification aims to match the images of pedestrians across different camera views from different locations. This is a challenging intelligent video surveillance problem that remains an ...active area of research due to the need for performance improvement. Person re-identification involves two main steps: feature representation and metric learning. Although the keep it simple and straightforward (KISS) metric learning method for discriminative distance metric learning has been shown to be effective for the person re-identification, the estimation of the inverse of a covariance matrix is unstable and indeed may not exist when the training set is small, resulting in poor performance. Here, we present dual-regularized KISS (DR-KISS) metric learning. By regularizing the two covariance matrices, DR-KISS improves on KISS by reducing overestimation of large eigenvalues of the two estimated covariance matrices and, in doing so, guarantees that the covariance matrix is irreversible. Furthermore, we provide theoretical analyses for supporting the motivations. Specifically, we first prove why the regularization is necessary. Then, we prove that the proposed method is robust for generalization. We conduct extensive experiments on three challenging person re-identification datasets, VIPeR, GRID, and CUHK 01, and show that DR-KISS achieves new state-of-the-art performance.
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•Ultrasonically pretreated SPI will affect the binding mechanism between SPI and LUT.•Proper power pretreatment is beneficial to the binding between SPI and LUT.•High power ...pretreatment will reduce the binding between SPI and LUT.
The combination of protein and flavonoids can ameliorate the problems of poor solubility and stability of flavonoids in utilization. In this study, soybean protein isolate pretreated by ultrasonication was selected as the embedding wall material, which was combined with luteolin to form a soybean protein isolate-luteolin nanodelivery system. The complexation effect and structural changes of soybean protein isolate (SPI) and ultrasonic pretreatment (100 W, 200 W, 300 W, 400 W and 500 W) of soybean protein isolate with luteolin (LUT) were compared, as well as the changes in digestion characteristics and antioxidant activity in vitro. The results showed that proper ultrasonic pretreatment increased the encapsulation efficacy, loading amount and solubility to 89.72%, 2.51 μg/mg and 90.56%. Appropriate ultrasonic pretreatment could make the particle size and the absolute value of ζ-potential of SPI-LUT nanodelivery system decrease and increase respectively. The FTIR and fluorescence results show that appropriate ultrasonic pretreatment could reduce α-helix, β-sheet and random coil, increase β-turn, and enhance fluorescence quenching. The thermodynamic evaluation results indicate that the ΔG < 0, ΔH > 0 and ΔS > 0, so the interaction of LUT with the protein was spontaneous and mostly governed by hydrophobic interactions. The XRD results show that the LUT was amorphous and completely wrapped by SPI. The DSC results showed that ultrasonic pretreatment could improve the thermal stability of SPI-LUT nanodelivery system to 112.66 ± 1.69 °C. Digestion and antioxidant analysis showed that appropriate ultrasonic pretreatment increased the LUT release rate and DPPH clearance rate of SPI-LUT nanodelivery system to 89.40 % and 55.63 % respectively. This study is a preliminary source for the construction of an SPI nanodelivery system with ultrasound pretreatment and the deep processing and utilization of fat-soluble active substances.
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