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Purpose: This study used the industry-oriented capstone course to increase the employability of electrical engineering and computer science (EECS) students in technological university. Design/methodology/approach: In this study, EECS students were selected and divided into groups, and the non-equivalent pretest-posttest quasi-experimental research method was adopted. Findings: Industry-oriented capstone courses can improve students' employability, especially general ability, behaviour and attitude. Practical implications: The results of this study and many other studies show that capstone courses are helpful for the soft skills of students. Originality/value: This study provides evidence that industry-oriented capstone courses can improve EECS students' employability.

To realize the reutilization of waste Myrica rubra in the analytical field, we synthesized Myrica rubra–based N-doped carbon dots (MN-CDs) and further anchored them onto the surface of Fe3S4 to fabricate Fe3S4@MN-CD nanocomposites. The as-fabricated nanocomposites possessed higher peroxidase-mimetic activity than its two precursors, resulting from the synergistic effect between them, and could catalyze colorless 3,3′,5,5′-tetramethylbenzidine (TMB) into deep blue oxTMB with a strong 652-nm absorption. Under optimized conditions (initial solution pH, 3.5; incubation temperature, 35 ℃; Fe3S4@MN-CD concentration, 50 µg mL−1, and 652-nm absorption), Fe3S4@MN-CDs were employed for colorimetric assay of p-aminophenol (p-AP) with wide linear range (LR, 2.9–100 µM), low detection limit (LOD, 0.87 µM), and satisfactory recoveries (86.3–105%) in environmental waters. Encouragingly, this colorimetric assay provided the relative accuracy of 97.0–99.4% as compared with conventional HPLC-UV detection. A portable smartphone-based colorimetric application was developed by combining the Fe3S4@MN-CD-based visually chromogenic reaction with a "Thing Identify" APP software. Besides, we engineered an image-capturing device feasible for field use, in which the internal-compact sealing prevented external light source from entering photography chamber, thereby reducing light interference, and also the bottom light source enhanced the intensity of blue imaging. This colorimetric platform exhibited satisfactory LR (1–500 µM), low LOD (0.3 µM), and fortification recoveries (86.6–99.6%). In the chromogenic reaction catalyzed by Fe3S4@MN-CDs, ·O2− played a key role in concomitant with the participation of •OH and h+. Both the colorimetric assay and smartphone-based intelligent sensing show great promising in on-site monitoring of p-AP under field conditions. [ABSTRACT FROM AUTHOR]

Objective Based on the US National Health and Nutrition Survey from 2005 to 2021, an interpretable machine learning method was used to identify patients with depression in people over 65 years old. Methods The data of 2005 Mel 2018 and 2019-2020 were used as training set and test set, respectively, and three machine learning models of Lasso Logistic, random forest, and XG Boost were fitted. The best model of area under the curve (AUC) on the test set was selected and explained by interpretable machine learning model SHAP. Results The AUC value of XG Boost model was the highest, which was 0.933 (0.912-0.954). Sleep problems, health problems, and eosinophil count were the top three important variables affecting senile depression. The absolute values of SHAP were 1.16, 0.83, and 0.55, respectively, which showed the main influencing factors of each individual. Conclusion Machine learning is superior to logistic regression model in predicting depression in the elderly. Interpretable machine learning can explain the model from the global and individual levels to make predictions, open the black box of machine learning models, and can be used as a supplement to machine learning models in practical application. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence has demonstrated that bone marrow mesenchymal stem cells (BMSCs)-derived extracellular vesicles (EVs) can be used effectively to transfer drugs and biomolecules to target lesions. Meanwhile, BMSCs have been reported to be beneficial in the treatment of rheumatoid arthritis (RA). In this study, we employ gain- and loss-of-function experiments to determine how BMSCs-derived EVs alleviate RA in vitro and in vivo. Methods: We isolated EVs from BMSCs and characterized them by transmission electron microscopy and western blot analysis. The regulatory relationship between miR-21 and TET1 was predicted by bioinformatics analysis and validated by dual luciferase assay. Next, we utilized bisulfite sequencing PCR to decipher how TET1 promoted KLF4 transcription. Then, we established an RA mouse model and determined the role of miR-21 in RA progression. Functional assays were used to validate the role the miR-21-TET1-KLF4 regulatory axis in controlling mouse fibroblast-like synoviocytes (mFLS) cell proliferation and inflammatory cytokines secretion in vitro . Results: RT-qPCR results revealed that miR-21 was highly expressed in BMSCs-derived EVs, and confirmed that BMSCs-derived EVs transferred miR-21 into mFLS cells. Bioinformatic analysis predicted that TET1 was the directly downstream target of miR-21, which was further validated by dual luciferase assay. TET1 promoted KLF4 promoter methylation to increase its expression. Collectively, BMSCs-derived EVs relieved RA by delivering miR-21, while the exosomal miR-21 alleviated RA through targeting the TET1/KLF4 regulatory axis. Conclusion: miR-21 from BMSCs-derived EVs suppresses KLF4 to relive RA by targeting TET1.

The United States Nuclear Regulatory Commission issued requests for licensees to re-evaluate the seismic hazards at their sites after the accident at the Fukushima Daiichi Nuclear Power Plant in Japan on March 11 in 2011 and to identify and address any site-specific vulnerabilities associated with seismic hazards. The primary guidance for performing those evaluations is provided in the Electric Power Research Institute EPRI-1025287 report, which also provides guidance for evaluating spent fuel pool (SFP) integrity. In addition, the EPRI-3002009564 report also provides evaluation approaches regarding the effects of seismic ground motions on SFPs that supplement the guidance provided in EPRI-1025287. SFP integrity has become increasingly important for active and decommissioned nuclear power plants. According to EPRI-1025287, the SFP integrity evaluation emphasizes failure modes of the SFP that could result in "rapid drain-down." The definition of "rapid drain-down" is a failure that could lead to the uncovering of irradiated fuel stored in the SFP within 72 h of an earthquake. Possible failures can be classified into two categories: failures relevant to the SFP structure and failures relevant to non-structural elements. This paper aims to study the approaches of implementing seismic evaluation of an SFP structure. EPRI-3002009564 provides separate seismic evaluation approaches for plants with a ground motion response spectrum (GMRS) peak Sa ≤ 0. 8 g and for plants with a GMRS peak Sa > 0. 8 g. Structural dynamic analysis is also a common approach for implementing seismic evaluation if a detailed finite element model is available. In this paper, a sample SFP structure was evaluated using the two approaches, structural dynamic analysis and structural analysis criteria. The results indicate that shear failure controlled the failure mode of the SFP structure for both approaches. This shows that the two approaches drew the same conclusion regarding the failure mode. Furthermore, a smaller seismic margin was obtained using the structural analysis criteria, which means this evaluative approach is more conservative. [ABSTRACT FROM AUTHOR]

This study establishes a low-carbon supply chain game model under the centralized decision situation and the decentralized decision situation considering the manufacturer risk-aversion behavior, and discusses the influence of the manufacturer risk-aversion behavior on the optimal decision, profit, coordination, and complex dynamics of the supply chain. We find that comparing with the risk-neutral decentralized decision, the increase of manufacturer's risk tolerance attitude can narrow the gap between the supply chain profit and the centralized decision, but it will further reduce the carbon emission reduction level. The increase of risk tolerance of the manufacturer and carbon tax will narrow the stable region of the system. Under this situation, the manufacturer should carefully adjust parameters to prevent the system from losing stability, especially the adjustment parameters for carbon emission reduction level. When the system is in a chaotic state, the increase of carbon tax rate makes the system show more complex dynamic characteristics. Under the chaotic state, it is difficult for the manufacturer to make correct price decision and carbon emission reduction strategy for the next period, which damages its profit, but increases the profit of the retailer and the supply chain. Finally, the carbon emission reduction cost-sharing contract is proposed to improve the carbon emission reduction level and the supply chain efficiency, achieving Pareto improvement. The stability region of the system is larger than that in the centralized decision situation, but the increase of the cost sharing coefficient will reduce the stability of the system in the decentralized decision-making situation. [ABSTRACT FROM AUTHOR]