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Objectives: Ultrasound Needle, which is an improved ultrasonic horn device, has shown great potential for promoting the diffusion of thrombolytic drugs within clots and enhancing clot lysis efficiency. However, the clot lysis efficiency of different thrombolytic drugs with the synergy of Ultrasound Needle remains unknown. In this study, we aimed to compare the lysis efficiency of the non-fibrin-specific drug urokinase and fibrin-specific drug reteplase with the synergy of Ultrasound Needle. Materials and methods: Twenty-five milliliters of human blood was incubated for 1.5 h to form in vitro clots and then received the corresponding treatment protocols: control group (normal saline), US group (10 min of Ultrasound Needle treatment), UK group (30000IU of urokinase), r-PA group (2 mg of reteplase), US + UK group, and US + r-PA group. After treatment, the morphological changes of the clots were analyzed by B-mode ultrasound imaging and hematoxylin and eosin (H&E) staining. Lysis efficiency was evaluated based on the relative end weight (final weight/initial weight). The fibrin density of the different groups after treatment was assessed by immunofluorescence staining. Results: Morphological examination and relative end weight analysis showed that combination therapies induced a more thorough dissolution of clots compared with single therapies, and the US + r-PA group exhibited higher lysis efficiency than the US + UK group. In addition, immunofluorescence staining showed that the US + r-PA group had fewer remaining thrombus fibrins than the US + UK group after treatment. Conclusions: The Ultrasound Needle can significantly improve the clot lysis efficiency of both fibrinolytic drugs, and fibrin-specific reteplase exhibited superior lysis efficiency over non-fibrin-specific urokinase with the synergy of the Ultrasound Needle.

Under the background of carbon peak and carbon neutralization, it is vital to study the impact of digital economy on carbon emission reduction. Based on a provincial panel data from 2013 to 2019, this paper establishes a dynamic panel model, a dynamic spatial autoregressive model, and a dynamic threshold model to study the impact of digital economy on carbon emission intensity. Our findings show that digital economy has a significant inhibitory effect on carbon emission intensity. Results of regional heterogeneity show that the central region can transform the impact of digital economy on carbon emission reduction more efficiently. After adding the time lag term of carbon emission intensity, the impact coefficient of digital economy is still significant. Carbon emission intensity has obvious spatial effect, and the carbon emission of adjacent areas will significantly inhibit local carbon emission reduction activities. Under the threshold of innovation and environmental regulation, the emission reduction effect of digital economy is different. For regions with low technological level, digital economy is difficult to give full scope to its emission reduction advantages. At the same time, stricter environmental regulations can cooperate with digital economy to accelerate regional carbon emission reduction. Therefore, China should continue to improve the construction of digital infrastructure and promote the reform and innovation of enterprise digital technology in order to release the carbon emission reduction effect of digital economy.

A primary development plan for a country is to attain carbon neutrality and high-quality international commerce development. This study uses panel data from 30 provinces in mainland China to analyze the dynamic interplay between international trade, technological innovation, and carbon emissions. The findings show that foreign trade, technological progress, and carbon emissions all have their own “economic inertia” that can be self-motivated and self-reinforcing. Foreign commerce and carbon emissions are mutually inhibiting, but technical progress and carbon emissions are mutually reinforcing. This illustrates that achieving a positive cycle of international trade, technological improvement, and carbon emissions necessitates a significant baseline need. Overcoming carbon trade barriers is currently the most difficult challenge for Chinese enterprises involved in foreign commerce. Low-carbon technology advancements are a critical part in this process. Our research strengthens the positive connections between international trade and carbon emissions as a result of technological improvement and proposes a feasible plan for international trade to achieve carbon peaking and carbon neutrality.

Abstract In this study, a simple one-step ionic liquid-based ultrasound-assisted dispersive liquid–liquid microextraction technique was coupled with high-performance liquid chromatography for the analysis of four pyrethroids in three kinds of traditional Chinese medicine oral liquid preparations: simotang oral liquid, kangbingdu oral liquid, and huaji oral liquid. The extraction parameters were examined to improve extraction efficiency. The optimum extraction conditions were 50 μL of 1-octyl-3-methylimidazolium hexafluorophosphate utilized as the extraction solvent and 800 μL of acetonitrile applied as the dispersive solvent. The extraction was assisted by ultrasonication for 8 min. The limits of detection for the four pyrethroids were within 0.007–0.024 mg L−1, and the limits of quantitation ranged between 0.023 and 0.080 mg L−1. The accuracy of the pyrethroid determination ranged from 80.1 to 106.4%. It was indicated that the proposed ionic liquid-based ultrasound-assisted dispersive liquid–liquid microextraction method had an easy operation and was accurate and environmentally friendly. This approach has potential for the analysis of pyrethroids in traditional Chinese medicine oral liquid preparations.

In this paper, a novel method of QuEChERS-based extraction coupled with high-performance liquid chromatography has been developed for the simultaneous determination of ursolic acid (UA) and oleanolic acid (OA) in guava leaves. The QuEChERS-based extraction parameters, including the amount of added salt, vortex-assisted extraction time, and absorbent amount, and the chromatographic conditions were investigated for the analysis of UA and OA in guava leaves. Under the optimized conditions, the method showed good linearity over a range of 1–320 μg mL−1, with correlation coefficients above 0.999. The limits of detection of UA and OA were 0.18 and 0.36 μg mL−1, respectively. The intraday and interday precision were below 1.95 and 2.55%, respectively. The accuracies of the UA and OA determinations ranged from 97.4 to 111.4%. The contents of UA and OA in the guava leaf samples were 2.50 and 0.73 mg g−1, respectively. These results demonstrate that the developed method is applicable to the simultaneous determination of UA and OA in guava leaves.

Pyrethroid residues in traditional Chinese medicines have been a serious threat to the health and treatment of patients. However, because of the matrix complexity of traditional Chinese medicine, the detection of pyrethroid residues remains a challenge. Therefore, we developed a QuEChERS method coupled with high-performance liquid chromatography and ultraviolet detection (HPLC-UV) for the determination of pyrethroid pesticides in three kinds of traditional Chinese medicine oral liquid preparations, and we investigated and optimized the extraction conditions. The matrix effect was estimated in the organic solvent and the actual samples by comparing the slopes of calibration curves, and the results showed that the matrix effect is not significant when using the modified QuEChERS method. The pyrethroid pesticides could be completely separated in 30 min. The linear correlation coefficients were more than 0.999, and the recoveries of all the pyrethroid pesticides ranged from 87.2% to 104.8%. The intra-day precisions (n = 5) were 2.44–4.62%, and the inter-day precisions (n = 5) were 1.06–3.02%. Moreover, the limits of detection were in the range of 0.007–0.018 ng mL−1, while the limits of quantitation were in the range of 0.022–0.057 ng mL−1. This simple, low-cost, and highly sensitive analytical method can be a potential tool for the analysis of pyrethroid residues in traditional Chinese medicine oral liquid preparations.

Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms.

The unanticipated coronavirus disease 2019 (COVID-19) pandemic has hit global business heavily, disrupting the management of human resources across numerous industries. More than 500 articles (indexed in Scopus and the Web of Science) on the impact of the COVID-19 outbreak on emerging human resources issues and related practices were published from 1 January 2020 to 31 January 2021. In this study, we conduct a systematic literature review on emerging studies in the business and management field to explore what the emerging human resource issues are during the COVID-19 pandemic and propose related practices to solve these issues. The analysis of the published literature identifies nine main human resource issues across 13 industries. The findings of this study suggest that COVID-19 has enormous impact on conventional human resource management and requires the theoretical and empirical attention of researchers. The propositions nominate related human resource practices to deal with emerging human resources issues and identify several research venues for future studies in this field. [ABSTRACT FROM AUTHOR]

This paper aims to (1) compare consumers' preferences between individual products and bundles as well as (2) investigate some of the factors involved in bundle characteristics that may affect consumer's preferences. Those factors are complementarity, price level, and discount level. An online survey developed by means of questionnaires were collected from the Portuguese population. Student's t-tests were used to test the hypothesis formulated and to analyze the consumers' preferences. The findings corroborate that in a scenario where the bundle does not offer any discounts, preference of individual products is higher. When a 20% discount is assigned to bundles, the overall preference for individual products is still superior. By offering a discount level of 45%, the overall preference for bundles becomes higher. The positive effect of complementarity bundles valuation is confirmed. This is the first approach to evaluate the preferences between bundles and individual products in the Portuguese market. The findings contribute to clarify the customer map within a Business Model Canvas. Furthermore, this paper analyzes the bundle complementarity and discount level effects simultaneously. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and induced economic and social constraints have significantly impacted the confidence of both consumers and businesses. Despite that, comprehensive studies of the impact of the COVID-19 pandemic on the consumer and business sentiment are still lacking. Thus, in our research we aim to identify consumer and business confidence indicators' reaction to the spread of the COVID-19 pandemic in the Eurozone, the United States, and China. For this purpose, we used the method of correlation-regression analysis. We chose the consumer-confidence index, manufacturing purchasing manager's index, and services purchasing manager's index as dependent variables; and the number of confirmed cases of COVID-19, the number of deaths caused by COVID-19, and the mortality rate of COVID-19 infections as independent variables. The results showed a relatively rapid and robust effect of COVID-19 in the short period, but longer-term results depended on the region and were not so unambiguous: in the case of the Eurozone, the spread of COVID-19 pandemic did not affect the consumer-confidence index (CCI) or, in the cases of the United States and China, affected this index negatively; the purchasing managers' index (PMI) in the services sector was significantly negatively affected by the mortality risk of COVID-19 infection; and the impact on the purchasing managers' index (PMI) in the manufacturing industry appeared to be mixed. [ABSTRACT FROM AUTHOR]