Salesperson human capital investment and heterogeneous export enterprises performance

This paper aims to study the impact of salesperson human capital investment on the export performance of heterogeneous enterprises in China. To distinguish the different effects on the staff level and the management level, we define the human capital investment for the overall salespersons as human capital investment I and the human capital investment for the sales managers as human capital investment II, respectively measured by the salary of the ordinary salespersons and the ratio of expenses to sales. We find that human capital investment I has a significant positive effect on export performance, while human capital investment II shows a “positive U-shaped” relationship with export performance. Considering the heterogeneity of enterprise, the positive effect of human capital investment I is more significant than that of human capital investment II in enterprises with high R&D intensity. Moreover, with the improvement of technology intensity, both the promotion of human capital investment I and human capital investment II would generate greater influence on export performance

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique

Objectives/Hypothesis: To develop a deep-learning–based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design: Retrospective study. Methods: A total of 24,667 laryngoscopy images (normal, vocal nodule, polyps, leukoplakia and malignancy) were collected to develop and test a convolutional neural network (CNN)-based classifier. A comparison between the proposed CNN-based classifier and the clinical visual assessments (CVAs) by 12 otolaryngologists was conducted. Results: In the independent testing dataset, an overall accuracy of 96.24% was achieved; for leukoplakia, benign, malignancy, normal, and vocal nodule, the sensitivity and specificity were 92.8% vs. 98.9%, 97% vs. 99.7%, 89% vs. 99.3%, 99.0% vs. 99.4%, and 97.2% vs. 99.1%, respectively. Furthermore, when compared with CVAs on the randomly selected test dataset, the CNN-based classifier outperformed physicians for most laryngeal conditions, with striking improvements in the ability to distinguish nodules (98% vs. 45%, P <.001), polyps (91% vs. 86%, P <.001), leukoplakia (91% vs. 65%, P <.001), and malignancy (90% vs. 54%, P <.001). Conclusions: The CNN-based classifier can provide a valuable reference for the diagnosis of laryngeal neoplasms during laryngoscopy, especially for distinguishing benign, precancerous, and cancer lesions. Level of Evidence: NA Laryngoscope, 130:E686–E693, 2020

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

Bio-inspired design of an in situ multifunctional polymeric solid-electrolyte interphase for Zn metal anode cycling at 30 mA cm\u3csup\u3e-2\u3c/sup\u3eand 30 mA h cm\u3csup\u3e-2\u3c/sup\u3e

A solid-electrolyte interphase (SEI) is highly desirable to restrain Zn dendrite growth and side reactions between a Zn anode and water in rechargeable aqueous zinc-ion batteries (RAZBs), but remains a challenge. Here, inspired by the bio-adhesion principle, a stable SEI of polydopamine is constructed successfully on a Zn anode via an in situ electrochemical polymerization process of a dopamine additive. This in situ polymeric SEI offers multifunctional features with abundant functional groups and outstanding hydrophilicity for regulating Zn nucleation to achieve dendrite-free Zn deposition, high Zn-ion conductivity for fast Zn2+ transport, and strong adhesion capability for blocking interfacial side reactions. Consequently, the Zn electrodes exhibited high reversibility with 99.5% coulombic efficiency and outstanding stability, even at ultrahigh current density and areal capacity (30 mA cm-2 and 30 mA h cm-2). Moreover, a prolonged lifespan can be attained for the Zn/V2O5 full cell in a lean electrolyte (9 μL mA h-1) and with a low capacity ratio of the negative electrode to the positive electrode (∼2). This work provides inspiration for the design of SEI layers in aqueous battery chemistry and promotes the practical application of RAZBs