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SUMMARY Section 404 of the Sarbanes-Oxley Act (SOX; U.S. House of Representatives 2002) continues to be controversial. Using samples of Securities and Exchange Commission (SEC) registrants with market capitalizations of less than $150 million, we find that non-accelerated filers have a significantly larger reduction in the likelihood of material misstatements, discretionary revenues, and discretionary accruals compared to smaller accelerated filers after non-accelerated filers became subject to the requirements of Section 404(a). Our findings are consistent with the argument that management reporting on internal controls (Section 404(a)) may be a cost-effective alternative to internal control audits (Section 404(b)) for smaller U.S. public companies.

Parotid gland disease is one of the main causes of facial paralysis, and parotid gland tumor is a great threat to the life of patients. The main diagnostic way of parotid diseases is imaging examination, so it is of great significance for the rapid classification of parotid image. In conclusion, 51 CT images of parotid malignant tumors and 101 CT images of parotid pleomorphic adenomas are selected as the research data set, and an intelligent and efficient machine learning algorithm is proposed for the practical classification of parotid images. At the same time, this paper also explores the privacy protection of medical images. Based on the advantages of deep learning, such as no feature engineering, strong adaptability and easy conversion, ResNet50 model in deep learning is selected as the basic network framework to achieve the purpose of rapid classification of parotid CT images. This is the first time that ResNet50 classification algorithm is applied to the practical classification of parotid tumor CT images. The results show that the accuracy of the test set converges to 90% when the model is iterated 1000 times, which also proves that this study has certain practical significance and application value for the auxiliary diagnosis of parotid gland tumor and other head and neck tumors. Simultaneously, this paper also explores the application of desensitization strategy in CT images of parotid tumors, which improves the performance of the model and also greatly protects the privacy of patients, and has a good application prospect in medical big data.

We examine the effects of corporate networks involving common directors and auditors (i.e., connections creating single or double ties between companies) on two important monitoring roles: financial reporting quality and auditor dismissal decisions. We also investigate how shocks to the networks, in the form of the audit failing to detect misstatements, affect these networks' structure. The investigations are important because these networks can have significant effects on firm governance and may have different effects when they overlap. We have three primary findings about double‐tie networks: (i) there is no evidence that they improve overall financial reporting quality beyond the effect of single‐tie networks; (ii) they lower directors' willingness to dismiss the auditor, even when there is a signal of an audit failure within the network; and (iii) they allow audit‐quality problems to spread between companies. Our results demonstrate the importance of investigating multiple types of networks and how shocks travel through them. Our findings also lend credence to concerns that “cozy” relationships between directors and auditors diminish the link between poor audit quality and market‐imposed reputation penalties—specifically, auditor dismissals.

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