Use of deltopectoral flap for head and neck reconstruction

Theme: Challenges to specialists in the 21st centurypublished_or_final_versio

The expertise of internal accounting control personnel and financial statement conservatism: Korean evidence

The purpose of this study is to analyze how the expertise of internal accounting control personnel impacts financial statement conservatism. This study analyzed companies listed on the Korean stock market. Listed companies in Korea have been disclosing information on internal accounting personnel since 2012. Using a fixed-effect regression model, an analysis of 3,276 firm-years from 2012 to 2018 shows a positive correlation between the expertise of internal accounting control personnel and financial statement conservatism. The results from Ball and Shivakumar’s (2006) CF, DD, and Jones models are all significant at the 1% level, enhancing the robustness of the study’s findings. The coefficients were 0.872, 0.869, and 0.846, and the t-values were 3.93, 3.95, and 3.83 in each model. This indicates that firms with CPAs (Certified Public Accountant) among their internal accounting control personnel show stronger tendencies toward conservatism compared to those without CPAs. Furthermore, an analysis based on the firm ownership structure reveals a positive correlation between internal accounting control personnel expertise and financial statement conservatism in a non-Chaebol subsample (coefficient = 1.043, t-value = 3.58 in CF model); however, the results in the Chaebol subsample were not significant. This suggests that while having CPAs involved in non-Chaebol firms’ internal control is effective, it is not effective in Chaebol companies that are highly influenced by their owners

Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models

Diffusion models have become a popular approach for image generation and reconstruction due to their numerous advantages. However, most diffusion-based inverse problem-solving methods only deal with 2D images, and even recently published 3D methods do not fully exploit the 3D distribution prior. To address this, we propose a novel approach using two perpendicular pre-trained 2D diffusion models to solve the 3D inverse problem. By modeling the 3D data distribution as a product of 2D distributions sliced in different directions, our method effectively addresses the curse of dimensionality. Our experimental results demonstrate that our method is highly effective for 3D medical image reconstruction tasks, including MRI Z-axis super-resolution, compressed sensing MRI, and sparse-view CT. Our method can generate high-quality voxel volumes suitable for medical applications.Comment: ICCV23 poster. 15 pages, 9 figure

Design and Implementation of the Service-Aware Traffic Engineering (SATE) in the LISP Software- DefinedWireless Network (LISP-SDWN)

Software Defined Wireless Networks (SDWN) have been considered to have a feasible architecture that enables the fast deployment of new services and solutions in response to the explosion in the number of users and network traffic. Currently, the telecommunications sector is ensuring flexibility in network management and configuration. However, fluctuations in traffic are still beyond the control of SDWN providers. This paper suggests ways to manage fluctuations of traffic with service type. We propose the design of a service-aware network management service that achieves the maximum network utilization among heterogeneous Radio Access Networks (RANs) as a form of Traffic Engineering (TE). In this paper, we implement and test the Service-Aware Traffic Engineering (SATE) that distributes the network traffic to RANs according to the service type of traffic in the network layer. The traffic shift latency (e.g., from an LTE RAN to a Wi-Fi RAN) is considered as a performance metric that does not affect the end-to-end latency of some network applications (e.g., VoIP), and it is 3.51ms from our testbed. Therefore, it might not affect the end-to-end latency of the VoIP application in the telecommunications. SATE is implemented using OpenDaylight (ODL) and Ingress/Egress Tunneling Routers (xTRs) running on Vector Packet Processing (VPP)

Epidural blood patch for refractory low CSF pressure headache: a pilot study

Once believed an exceedingly rare disorder, recent evidence suggests that low cerebrospinal fluid (CSF) pressure headache has to be considered an important cause of new daily persistent headaches, particularly among young and middle-aged individuals. Treatment of low CSF pressure headache consists of non-invasive/conservative measures and invasive measures with epidural blood patch providing the cornerstone of the invasive measures. In the present pilot study we therefore aimed to evaluate the treatment efficacy of epidural blood patch (EBP) in treatment-refractory low-pressure headache. Our primary effect parameter was total headache burden defined as area under the curve (AUC: intensity × duration) and as secondary effect parameters we identified: intensity (VAS 0-10), frequency (days per month), duration in hours (total hours/month) and also medication days (days on medication/month). In our primary effect parameter we found a significant reduction in AUC with more than 25% and this is considered to be clinically relevant. We found also a significant and relevant reduction at −22% in intensity. A trend towards reduction in duration was seen. We found no statistically significant reduction in frequency. An increase in days with use of medication was found. Increased awareness of low CSF pressure headache is emphasized and a controlled larger randomized study is needed to confirm the results. However the present results, allows us to conclude that EBP in treatment-refractory low CSF pressure headache can be considered as a treatment option

Early Identification of Childhood Asthma: The Role of Informatics in an Era of Electronic Health Records

Emerging literature suggests that delayed identification of childhood asthma results in an increased risk of long-term and various morbidities compared to those with timely diagnosis and intervention, and yet this risk is still overlooked. Even when children and adolescents have a history of recurrent asthma-like symptoms and risk factors embedded in their medical records, this information is sometimes overlooked by clinicians at the point of care. Given the rapid adoption of electronic health record (EHR) systems, early identification of childhood asthma can be achieved utilizing (1) asthma ascertainment criteria leveraging relevant clinical information embedded in EHR and (2) innovative informatics approaches such as natural language processing (NLP) algorithms for asthma ascertainment criteria to enable such a strategy. In this review, we discuss literature relevant to this topic and introduce recently published informatics algorithms (criteria-based NLP) as a potential solution to address the current challenge of early identification of childhood asthma