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This study is aimed to investigate the clinical significance and the short-term prognostic value of fragmented QRS (fQRS) for patients with acute myocardial infarction (AMI). Three hundred patients with AMI were tested with retrospective analysis on the patients' clinical information, hospitalized treatment, fQRS onset time, location of lesions, and other relevant data, in order to assess the relationship between the presence of fQRS and its prognosis. The rates of malignant cardiac arrhythmia, left ventricular systolic dysfunction (LVSD), and mortality in the positive fQRS group were 13.6%, 29.2%, and 23.7%, respectively, with all showing a p value <0.05. For the ST segment elevation myocardial infarction (STEMI) subgroup, all the rates showed significant differences with a p value <0.01, while for the non-STEMI (NSTEMI) subgroup showed no significant differences. In patients with a positive fQRS, there were no differences in malignant cardiac arrhythmia between patients with and without percutaneous coronary intervention (PCI) (p>0.05). As for the LVSD and mortality, the p values between patients with and without PCI were 0.031 and 0.000, respectively, suggesting statistical significance. The results imply that AMI patients with positive fQRS especially for the patients with STEMI had higher rates of malignant cardiac arrhythmia, LVSD, and mortality than the non-fQRS group. Patients of AMI with positive fQRS, who underwent early revascularization, could lower the incidence of the cardiovascular event. In addition, the presence of fQRS could be used as an indication of early intervention treatment for patients.

Through-hole (TH) filling of a printed circuit board (PCB) was conducted with a copper electroplating solution. Tetranitroblue tetrazolium chloride (TNBT) was used as an inhibitor and acetic acid electrolyte instead of a traditional H2SO4 electrolyte was used for the copper electroplating. Moreover, functional insoluble anodes (DT) that were activated with iridium-based mixed metal oxides on Ti meshes were used instead of conventional soluble anodes (i.e., P-doped Cu). The TH filling performance of the copper electroplating solution was significantly enhanced when acetic acid electrolyte and DT anodes were used simultaneously in the copper electroplating bath.

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PurposeSmart manufacturing can lead to disruptive changes in production technologies and business models in the manufacturing industry. This paper aims to identify technological topics in smart manufacturing by using patent data, investigating technological trends and exploring potential opportunities.Design/methodology/approachThe latent Dirichlet allocation (LDA) topic modeling technique was used to extract latent technological topics, and the generalized linear mixed model (GLMM) was used to analyze the relative emergence levels of the topics. Topic value and topic competitive analyses were developed to evaluate each topic's potential value and identify technological positions of competing firms, respectively.FindingsA total of 14 topics were extracted from the collected patent data and several fast growth and high-value topics were identified, such as smart connection, cyber-physical systems (CPSs), manufacturing data analytics and powder bed fusion additive manufacturing. Several leading firms apply broad R&D emphasis across a variety of technological topics, while others focus on a few technological topics.Practical implicationsThe developed methodology can help firms identify important technological topics in smart manufacturing for making their R&D investment decisions. Firms can select appropriate technology strategies depending on the topic's emergence position in the topic strategy matrix.Originality/valuePrevious research studies have not analyzed the maturity levels of technological topics. The topic-based patent analytics approach can complement previous studies. In addition, this study provides a multi-valuation framework for exploring technological opportunities, thus providing valuable information that supports a more robust understanding of the technology landscape of smart manufacturing.