Preparation and Characterization of Carbon Nanofibers and its Composites by Chemical Vapor Deposition

Hydrocarbon gas or carbon monoxide was pyrolyzed by chemical vapor deposition (CVD), and carbon nanofiber (CNF) synthesis was performed using transition metals such as Ni, Fe, and Co as catalysts. When synthesizing carbon nanofibers using the CVD method, experimental variables are temperature, catalysts, source gas, etc. Especially, the particle size of the catalyst is the most important factor in determining the diameter of carbon nanofibers. Hydrocarbon gases, such as CH4, C2H4, benzene, and toluene are used as the carbon source, and in addition to these reaction gases, nonreactive gases such as H2, Ar, and N2 gases are used for transportation. Synthesis occurs at a synthesis temperature of 600–900°C, and catalyst metals such as Ni, Co, and Fe are definitely required when synthesizing CNFs. Therefore, it is possible to synthesize CNFs in selective areas through selective deposition of such catalyst metals. In this study, CNFs were synthesized by CVD. Ethylene gas was employed as the carbon source for synthesis of CNFs with H2 as the promoting gas and N2 as the balancing gas. Synthesized CNFs can be used in various applications, such as composite materials, electromagnetic wave shielding materials, ultrathin display devices, carbon semiconductors, and anode materials of Li secondary batteries. In particular, there is an increasing demand for light-weight, small-scale, and high-capacity batteries for portable electronic devices, such as notebook computers or smartphones along with the recent issue of fossil energy depletion. Accordingly, CNFs and their silicon-series composites are receiving attention for use as anode materials for lithium secondary batteries that are eco-friendly, light weight, and high capacity

Synthesis and Characteristics of Carbon Nanofibers/Silicon Composites and Application to Anode Materials of Li Secondary Batteries

Among the various synthesizing technologies of carbon nanofibers (CNFs), chemical vapor deposition (CVD) technology, which uses hydrocarbon gas or carbon monoxide as a carbon source gas and pyrolyzes it to grow CNFs on transition metal catalysts, such as Ni, Fe, and Co, has been regarded as the most inexpensive and convenient method to produce CNFs for industrial use. Experimental variables for CVD are source gas, catalyst layers, temperature, and reaction time. Since the particle size of metal catalysts has an influence on the diameter of CNFs, it is possible to control the diameter of CNFs by varying particle sizes of the metal. As such, it is possible to synthesize CNFs selectively through the selective deposition of catalyst metals. In this study, CNFs were grown by CVD on C-fiber textiles, which had catalysts deposited via electrophoretic deposition. The CNFs were coated with a silica layer via hydrolysis of TEOS (tetraethyl orthosilicate), and the CNFs were oxidized by nitric acid. Due to oxidation, a hydroxyl group was created on the CNFs, which was then able to be used as an activation site for the SiO2. CNFs and the CNFs/SiO2 composite can be used in various applications, such as a composite material, electromagnetic wave shielding material, ultrathin display devices, carbon semiconductors, and anode materials of Li secondary batteries. In particular, there is an increasing demand for lightweight, small-scale, and high-capacity batteries for portable electronic devices, such as laptop computers or smart phones, along with the escalating concern of fossil energy depletion. Accordingly, CNFs and CNFs/SiO2 composites are receiving attention for their use as anode materials of Li secondary batteries, which are eco-friendly, lightweight, and high capacity. Therefore, the physicochemical properties and electrochemical performance data of synthesized CNFs and CNFs/SiO2 composite are described in this chapter

Dynamics of Social Influence on New Employees’ Use of Volitional IS: m-EHR Case in Hospital Setting

It is widely recognized that user resistance to Information Systems (IS) is particularly high in hospitals. In this regard, the future of mobile Electronic Health Record (m-EHR) systems is highly in question, mainly because their usage is not mandatory. Aiming to provide insights on how best to promote the use of m-EHR in hospitals, we investigate the effect of social influences on m-EHR usage by new doctors who recently began working at a hospital. Drawing upon the concept of organizational socialization and social influences, we hypothesize that coworkers’ m-EHR usage is positively associated with one by new doctors, and the strength of this association varies by the coworkers’ type of usage, by the hierarchical rankings of coworkers, and by the stage of socialization process in which the new doctors are situated. Our analyses using longitudinal m-EHR usage data (595,914 logs of 737 doctors) generally support our hypotheses

Optical Air-Gap Attacks:Analysis and IoT Threat Implications

Since 2008, the Korean government has instituted network separation technology, which physically isolates external internet networks from internal networks, aiming to thwart cyber-attacks. Consequently, the domestic financial sector was largely unaffected during global crises (2017 WannaCry ransomware outbreak and the 2021 Log4j vulnerability incident). However, there exist certain vulnerabilities owing to the presumption of their relative safety against cyber intrusions and the integration of cloud and Internet of Things (IoT) technologies in the current smart revolution. The existing network separation measures only mitigate one facet of potential cyber threats, rendering a comprehensive defense elusive. The rise of “air-gap” attacks, which exploit the isolated space between closed and external networks to illicitly transfer data and the existing research primarily substantiating the potential for data breaches from closed networks to their external counterparts are problems yet to be addressed. Thus, our study proposed a tangible optical air-gap attack methodology, harnessing readily available optical mediums within closed networks. Intricate measurement metrics that consider vital factors of the transmission environment were proposed. Moreover, acknowledging the proliferating integration of IoT devices, such as smart bulbs, to facilitate automation within closed networks, this study demonstrated the viability of optical air-gap attacks using these devices

Evaluating the Landscape of Personal Health Records in Korea: Results of the National Health Informatization Survey

Objectives This study examined the adoption and utilization of personal health records (PHR) across Korean medical institutions using data from the 2020 National Health and Medical Informatization Survey. Methods Spearheaded by the Ministry of Health and Welfare and prominent academic societies, this study surveyed PHR utilization in 574 medical institutions. Results Among these institutions, 84.9% (487 hospitals) maintained medical portals. However, just 14.1% (81 hospitals) had web-based or mobile PHRs, with 66.7% (28 of 42) of tertiary care hospitals adopting them. Tertiary hospitals led in PHR services: 87.8% offered certification issuance, 51.2% provided educational information, 63.4% supported online payment, and 95.1% managed appointment reservations. In contrast, general and smaller hospitals had lower rates. Online medical information viewing was prominent in tertiary hospitals (64.3%). Most patients accessed test results via PHRs, but other data types were less frequent, and only a few allowed downloads. Despite the widespread access to medical data through PHRs, integration with wearables and biometric data transfers to electronic medical records remained low, with limited plans for expansion in the coming three years. Conclusions Approximately two-thirds of the surveyed medical institutions provided PHRs, but hospitals and clinics in charge of community care had very limited PHR implementation. Government-led leadership is required to invigorate the use of PHRs in medical institutions

Safety and Usability Guidelines of Clinical Information Systems Integrating Clinical Workflow: A Systematic Review.

OBJECTIVES: The usability of clinical information systems (CISs) is known to be an essential consideration in ensuring patient safety as well as integrating clinical flow. This study aimed to determine how usability and safety guidelines of CIS consider clinical workflow through a systematic review in terms of the target systems, methodology, and guideline components of relevant articles. METHODS: A literature search was conducted for articles published from 2000 to 2015 in PubMed, Cochrane, EMBASE, Web of Science, and CINAHL. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement method was employed. Articles containing recommendations, principles, and evaluation items for CIS usability and safety were included. The selected articles were classified according to article type, methodology, and target systems. Taking clinical workflow into consideration, the components of guidelines were extracted and classified. RESULTS: A total of 7,401 articles were identified by keyword search. From the 76 articles remaining after abstract screening, 15 were selected through full-text review. Literature review (n = 7) was the most common methodology, followed by expert opinions (n = 6). Computerized physician order entry (n = 6) was the most frequent system. Four articles considered the entire process of clinical tasks, and two articles considered the principles of the entire process of user interface affecting clinical workflow. Only two articles performed heuristic evaluations of CISs. CONCLUSIONS: The usability and safety guidelines of CISs need improvement in guideline development methodology and with consideration of clinical workflow

Characteristics of poisoning in younger children according to different forms of the drugs

Purpose This study aimed to investigate the characteristics of poisoning drug ingested by younger children, and to compare the clinical outcome by drug forms. Methods This was a retrospective analysis based on medical records from the Emergency Department based Injury In-depth Surveillance (EDIIS) registry in Korea from January to December 2015. Patients aged 7 years or younger visiting the emergency department (ED) with drug poisoning were included. We classified the forms of drugs as tablets or syrup, and analyzed the characteristics by size, color, and shape. In addition, clinical outcomes and ED length of stay were compared according to the drug forms. Results A total of 308 cases were collected, and 202 patients finally were analyzed. Tablets and capsules (TACs) were more common than syrup (67.3% vs. 32.7%). Regarding clinical outcomes, patients who took TACs had higher admission rate (18.4% vs. 7.6%, P = 0.040) without a significant difference in ED length of stay compared to those who took syrups. While commonly ingested drugs in TACs were hormones, sedative and analgesics, frequent drugs in syrup were antihistamines and cold drugs. In 136 case of TACs, median long and short axes were 0.85 cm (interquartile range [IQR], 0.7-1.1 cm) and 0.72 cm (IQR, 0.59-0.82 cm), respectively. Chromatic TACs were 80 cases (52.8%) and more common than achromatic TACs. Round shapes were preferred than angular ones (96.3% vs. 3.7%). Conclusion In younger children poisonings, the TACs showed higher incidence and admission rate compared to syrups. Especially, chromatic TACs and round shapes were preferred. Therefore, drugs with these characteristics need to be stored more carefully

Let's Verify Step by Step

In recent years, large language models have greatly improved in their ability to perform complex multi-step reasoning. However, even state-of-the-art models still regularly produce logical mistakes. To train more reliable models, we can turn either to outcome supervision, which provides feedback for a final result, or process supervision, which provides feedback for each intermediate reasoning step. Given the importance of training reliable models, and given the high cost of human feedback, it is important to carefully compare the both methods. Recent work has already begun this comparison, but many questions still remain. We conduct our own investigation, finding that process supervision significantly outperforms outcome supervision for training models to solve problems from the challenging MATH dataset. Our process-supervised model solves 78% of problems from a representative subset of the MATH test set. Additionally, we show that active learning significantly improves the efficacy of process supervision. To support related research, we also release PRM800K, the complete dataset of 800,000 step-level human feedback labels used to train our best reward model