A neonatal pustule:Langerhans cell histiocytosis

Langerhans cell histiocytosis (LCH) is a rare, clinically heterogeneous disease that most commonly occurs in pediatric populations. Congenital self-limited LCH is a benign variant of LCH. It most commonly presents as a diffuse eruption and reports of single lesion cases are infrequent in the literature. Even in the case of congenital self-limited LCH, there is potential for future multisystem relapse, making long-term follow-up important. We present a case of single lesion self-limited LCH in a full-term male infant with interesting morphology. Physical examination revealed a painless, 6 millimeter, well-demarcated, papule encircled by erythema with central hemorrhage. An infectious workup was negative and a punch biopsy was obtained, which showed a dermal infiltrate of histiocytes consistent with a diagnosis of LCH. The lesion healed without intervention within three weeks. Our case highlights the need for dermatologists to consider LCH in the differential diagnosis for lesions of varying morphology in children, as proper identification is necessary to monitor for multisystem recurrence

Automatic 3D City Modeling Using a Digital Map and Panoramic Images from a Mobile Mapping System

Three-dimensional city models are becoming a valuable resource because of their close geospatial, geometrical, and visual relationship with the physical world. However, ground-oriented applications in virtual reality, 3D navigation, and civil engineering require a novel modeling approach, because the existing large-scale 3D city modeling methods do not provide rich visual information at ground level. This paper proposes a new framework for generating 3D city models that satisfy both the visual and the physical requirements for ground-oriented virtual reality applications. To ensure its usability, the framework must be cost-effective and allow for automated creation. To achieve these goals, we leverage a mobile mapping system that automatically gathers high-resolution images and supplements sensor information such as the position and direction of the captured images. To resolve problems stemming from sensor noise and occlusions, we develop a fusion technique to incorporate digital map data. This paper describes the major processes of the overall framework and the proposed techniques for each step and presents experimental results from a comparison with an existing 3D city model

Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach

The metaverse is regarded as a new wave of technological transformation that provides a virtual space for people to interact through digital avatars. To achieve immersive user experiences in the metaverse, real-time rendering is the key technology. However, computing-intensive tasks of real-time rendering from metaverse service providers cannot be processed efficiently on a single resource-limited mobile device. Alternatively, such mobile devices can offload the metaverse rendering tasks to other mobile devices by adopting the collaborative computing paradigm based on Coded Distributed Computing (CDC). Therefore, this paper introduces a hierarchical game-theoretic CDC framework for the metaverse services, especially for the vehicular metaverse. In the framework, idle resources from vehicles, acting as CDC workers, are aggregated to handle intensive computation tasks in the vehicular metaverse. Specifically, in the upper layer, a miner coalition formation game is formulated based on a reputation metric to select reliable workers. To guarantee the reliable management of reputation values, the reputation values calculated based on the subjective logical model are maintained in a blockchain database. In the lower layer, a Stackelberg game-based incentive mechanism is considered to attract reliable workers selected in the upper layer to participate in rendering tasks. The simulation results illustrate that the proposed framework is resistant to malicious workers. Compared with the best-effort worker selection scheme, the proposed scheme can improve the utility of metaverse service provider and the average profit of CDC workers

Blockchain-assisted Twin Migration for Vehicular Metaverses: A Game Theory Approach

As the fusion of automotive industry and metaverse, vehicular metaverses establish a bridge between the physical space and virtual space, providing intelligent transportation services through the integration of various technologies, such as extended reality and real-time rendering technologies, to offer immersive metaverse services for Vehicular Metaverse Users (VMUs). In vehicular metaverses, VMUs update vehicle twins (VTs) deployed in RoadSide Units (RSUs) to obtain metaverse services. However, due to the mobility of vehicles and the limited service coverage of RSUs, VT migration is necessary to ensure continuous immersive experiences for VMUs. This process requires RSUs to contribute resources for enabling efficient migration, which leads to a resource trading problem between RSUs and VMUs. Moreover, a single RSU cannot support large-scale VT migration. To this end, we propose a blockchain-assisted game approach framework for reliable VT migration in vehicular metaverses. Based on the subject logic model, we first calculate the reputation values of RSUs considering the freshness of interaction between RSUs and VMUs. Then, a coalition game based on the reputation values of RSUs is formulated, and RSU coalitions are formed to jointly provide bandwidth resources for reliable and large-scale VT migration. Subsequently, the RSU coalition with the highest utility is selected. Finally, to incentivize VMUs to participate in VT migration, we propose a Stackelberg model between the selected coalition and VMUs. Numerical results demonstrate the reliability and effectiveness of the proposed schemes.Comment: Transactions on Emerging Telecommunications Technologies (ISSN: 2161-3915

An Interview with APPLE Lecture Speaker Professor James Pennebaker

On February 24, 2017, the TESOL/AL Web Journal (represented by Eun Young Kang, Yulin Liu, Sarah Sok, Di Yu and Yuna Seong) had the opportunity to sit down with Professor James Pennebaker, guest speaker for the 2017 Applied Linguistics & Language Education (APPLE) Lecture Series, hosted annually by the TESOL/Applied Linguistics Programs at Teachers College, Columbia University. Professor Pennebaker spoke about his research and advice he has for current and future researchers in the TESOL and Applied Linguistics fields. Professor James Pennebaker is the Regents Professor of Psychology at the University of Texas at Austin. He is also the Executive Director of a university-wide educational initiative called Project 2021. His work on expressive writing found that physical health can improve by writing about traumatic events/experience. We thank Professor Pennebaker for the great opportunity to learn more about his work and research. We also thank Fred Tsutagawa for videotaping and Dr. Hoa Nguyen for coordinating the APPLE Lecture Series Interview

Multifunctional-high resolution imaging plate based on hydrophilic graphene for digital pathology

In the present study, we showed that hydrophilic graphene can serve as an ideal imaging plate for biological specimens. Graphene being a single-atom-thick semi-metal with low secondary electron emission, array tomography analysis of serial sections of biological specimens on a graphene substrate showed excellent image quality with improved z-axis resolution, without including any conductive surface coatings. However, the hydrophobic nature of graphene makes the placement of biological specimens difficult; graphene functionalized with polydimethylsiloxane oligomer was fabricated using a simple soft lithography technique and then processed with oxygen plasma to provide hydrophilic graphene with minimal damage to graphene. High-quality scanning electron microscopy images of biological specimens free from charging effects or distortion were obtained, and the optical transparency of graphene enabled fluorescence imaging of the specimen; high-resolution correlated electron and light microscopy analysis of the specimen became possible with the hydrophilic graphene plate

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features

PurposeCognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment.MethodsIn this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients.ResultsThe classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%.ConclusionsThe model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment

Validity of Self-reported Healthcare Utilization Data in the Community Health Survey in Korea

To evaluate the sensitivity and specificity of Community Health Survey (CHS), we analyzed data from 11,217 participants aged ≥ 19 yr, in 13 cities and counties in 2008. Three healthcare utilization indices (admission, outpatient visits, dental visits) as comparative variables and the insurance benefit claim data of the Health Insurance Review & Assessment Service as the gold-standard were used. The sensitivities of admission, outpatient visits, and dental visits in CHS were 54.8%, 52.1%, and 61.0%, respectively. The specificities were 96.4%, 85.6%, and 82.7%, respectively. This is the first study to evaluate the validity of nationwide health statistics resulting from questionnaire surveys and shows that CHS needs a lot of efforts to reflect the true health status, health behavior, and healthcare utilization of the population