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UNSTRUCTURED Correction: Frequent Mobile Electronic Medical Records (EMR) Users Respond More Quickly to Emergency Department Consultation Requests In “Frequent Mobile Electronic Medical Records (EMR) Users Respond More Quickly to Emergency Department Consultation Requests” ([JMIR Mhealth Uhealth 2020;8(2):e14487]) the authors noted one error. [Under tilte page “Author Kwang Yul Jung, MD1 “ has been replaced by “Kwang Yul Jung, MD1,2”] The correction will appear in the online version of the paper on the JMIR Publications website on [November 1, 2022], together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.

Empirical research reports various behaviors exhibited by investors, including voluntary concurrent investments, which are called bandwagon investments. However, the current theoretical understandi...

[Purpose] It aims to suggest the differential factors to enhance the customer satisfaction and to activate the shopping in the convenience store (CVS). [Methodology] Convenience store service convenience (CVS SERVCON) was developed at the first time and the gap of relative importance level between the owners and the consumers was assessed by AHP analysis method..[Findings] First, the importance of access convenience was assessed as the first priority in both CVS owners’ group and the consumers’ group, while the detailed elements showed the differences which required the improvements. Based on the consumers’ assessment, the importance of location was relatively low. They assessed relatively high on 24 hours operation of CVS and personal services. Second with respect to the transaction convenience, CVS owners’ group rated it as the fourth priority while the consumers’ group rated as the second, which requires the improvement. Third in terms of benefit utility and value-added service of post-benefit convenience which are the sub-factors of benefit convenience, the rate on the importance from the consumers showed higher than that from the owners, which requires the improvement. [Implications] Based on this study results, CVS operating companies are anticipated to be able to satisfy the customers, moreover, to secure the loyal customers if they concentrate the resources to develop the differentiation strategy on the areas where the consumers’ demands are high while performs the maintenance strategy on the areas where their demands are low. In addition, this study contributed the theoretical expansion of SERVCON upon development of CVS SERVCON to comply with its definition.

Process simulation and design as well as economic analysis were carried out to evaluate technical and economic feasibility of steam reforming of methanol in a membrane reactor (MR) for ultra-pure H2 production. Using a commercial process simulator, Aspen HYSYS®, comparative studies were conducted to investigate the effect of operating conditions including the H2 permeance (1 × 10−5 - 6 × 10−5 mol m−2 s−1 Pa−1), a H2O sweep gas flow rate (1–20 kmol h−1), and a reaction temperature (448–493 K) in a conventional packed-bed reactor (PBR) and the MR using a previously reported reaction kinetics. Improved performances such as methanol conversions and H2 yields were observed in the MR compared to the PBR and several design guidelines for the MR were obtained to develop H2 separation membranes with optimal H2 permeance and to select a suitable H2O sweep gas flow rate. In addition, economic analysis based on itemized cost estimations was conducted for a small-sized H2 fueling station by calculating a unit H2 production cost for both the PBR and the MR reflecting a current economic status in Korea. As a result, a cost saving of about 23% was obtained in the MR (7.24 $ kgH2−1) compared to the PBR (9.37 $ kgH2−1) confirming the benefit of employing the MR for ultra-pure H2 production.

When contagious respiratory diseases, such as coronavirus disease 2019, break out, the public can curb the spread of the diseases by wearing filtering facepiece respirators until vaccines and treatments are developed. It is a formidable task for supply chain managers to satisfy the demand; however, the demand for filtering facepiece respirators has been immense and continuous during the pandemic. This research provides a conceptual framework with implementable supply chain management strategies to cope with the surging demand. Our framework is based on the disaster management cycle.

Due to the lack of vaccines and treatments, filtering facepiece respirators are a primary and effective tool to dampen the spread of COVID-19. To meet the huge and continuous demand for filtering facepiece respirators, this concept paper suggests a supply chain management framework based on the disaster management principle. This concept paper adopts an exploratory and qualitative literature review to provide managerial insights for the supply chain participants. Due to implementation delay and strategic interdependency, the supply chain management strategies need to be systematically integrated. A viable way to integrate strategies is based on the disaster management cycle: mitigation, preparation, response, and recovery phases. Our model integrates innovative and successful but overlooked supply chain management strategies. First, the production capacity should be flexible so that the production mode in emergency and normal situations can be different. Second, the concept paper and development facilities can utilize their capacities for actual production in emergencies. Third, the quality certification process should accommodate the flexible production capacities. Fourth, inventory stockpiling should be renewable. This concept paper contributes to policymakers, healthcare sector decision-makers, stakeholders throughout the FFR supply chain to cope with future crises caused by pandemics by providing a systematic approach to constructing an effective, flexible, and resilient supply chain.

Background Specialty consultation is a critical aspect of emergency department (ED) practice, and a delay in providing consultation might have a significant clinical effect and worsen ED overcrowding. Although mobile electronic medical records (EMR) are being increasingly used and are known to improve the workflow of health care providers, limited studies have evaluated their effectiveness in real-life clinical scenarios. Objective For this study, we aimed to determine the association between response duration to an ED specialty consultation request and the frequency of mobile EMR use. Methods This retrospective study was conducted in an academic ED in Seoul, South Korea. We analyzed EMR and mobile EMR data from May 2018 to December 2018. Timestamps of ED consultation requests were retrieved from a PC-based EMR, and the response interval was calculated. Doctors’ log frequencies were obtained from the mobile EMR, and we merged data using doctors’ deidentification numbers. Pearson’s product-moment correlation was performed to identify this association. The primary outcome was the relationship between the frequency of mobile EMR usage and the time interval from ED request to consultation completion by specialty doctors. The secondary outcome was the relationship between the frequency of specialty doctors’ mobile EMR usage and the response time to consultation requests. Results A total of 25,454 consultations requests were made for 15,555 patients, and 252 specialty doctors provided ED specialty consultations. Of the 742 doctors who used the mobile EMR, 208 doctors used it for the specialty consultation process. After excluding the cases lacking essential information, 21,885 consultations with 208 doctors were included for analysis. According to the mobile EMR usage pattern, the average usage frequency of all users was 13.3 logs/day, and the average duration of the completion of the specialty consultation was 51.7 minutes. There was a significant inverse relationship between the frequency of mobile EMR usage and time interval from ED request to consultation completion by specialty doctors (coefficient=–0.19; 95% CI –0.32 to –0.06; P=.005). Secondary analysis with the response time was done. There was also a significant inverse relationship between the frequency of specialty doctors’ mobile EMR usage and the response time to consultation requests (coefficient=–0.18; 95% CI –0.30 to –0.04; P=.009). Conclusions Our findings suggest that frequent mobile EMR usage is associated with quicker response time to ED consultation requests.

The production of many minerals and fossil fuels is unstable, and managing volatilities is an important task for managers. External shocks have been regarded as sources of market instability, but a recent empirical analysis showed that external shocks do not fully explain the price volatilities of coproducts. The present study provides an analytic model that identifies the endogenous sources of the market instability of jointly produced metals using a game-theoretic approach. In this model, a joint product company that produces both a primary product and a by-product competes with two firms: 1) a primary product company that produces only primary products in the primary market; and 2) a by-product company that produces only the by-product in the secondary market. This study models the competition among these firms as single-period, sequential quantity competitions. The results indicate that competition causes market instability if the joint product firm sets its production after observing the decisions of other firms and if the joint product firm has efficient capacity. The numerical example, which is motivated by zinc and indium markets, suggests that the endogenous factor affected the markets in 2013. Moreover, endogenous instability will be more important as the price sensitivity to production quantity increases, the relative size of the by-product market grows, and the by-product production technology improves.

BACKGROUND Mobile health apps have emerged as supportive tools in the management of advanced cancers. However, only a few apps have self-monitoring features, and they are not standardized and validated. OBJECTIVE This study aimed to develop and validate a multidisciplinary mobile care system with self-monitoring features that can be useful for patients with advanced gastrointestinal cancer. METHODS The development of the multidisciplinary mobile health management system was divided into 3 steps. First, the service scope was set up, and the measurement tools were standardized. Second, the service flow of the mobile care system was organized. Third, the mobile app (Life Manager) was developed. The app was developed to achieve 3 major clinical goals: support for quality of life, nutrition, and rehabilitation. Three main functional themes were developed to achieve clinical goals: a to-do list, health education, and in-app chat. Thirteen clinically oriented measures were included: the modified Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events questionnaire, Scored Patient-Generated Subjective Global Assessment (PG-SGA), distress, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, International Physical Activity Questionnaire–Short Form, Low anterior resection syndrome score, satisfaction rate, etc. To validate the system, a prospective observational study was conducted. Patients with gastric cancer or colon cancer undergoing chemotherapy were recruited. We followed the subjects for 12 weeks, and selected clinical measures were taken online and offline. RESULTS After the development process, a multidisciplinary app, the Life Manager, was launched. For evaluation, 203 patients were recruited for the study, of whom 101 (49.8%) had gastric cancer, and 102 (50.2%) were receiving palliative care. Most patients were in their fifties (35.5%), and 128 (63.1%) were male. Overall, 176 subjects (86.7%) completed the study. Among subjects who dropped out, the most common reason was the change of patient’s clinical condition (51.9%). During the study period, subjects received multiple health education sessions. For the gastric cancer group, the “general gastric cancer education” was most frequently viewed (322 times), and for the colon cancer group, the “warming-up exercise” was most viewed (340 times). Of 13 measurements taken from subjects, 9 were taken offline (response rate: 52.0% to 90.1%), and 3 were taken online (response rate: 17.6% to 57.4%). The overall satisfaction rate among subjects was favorable and ranged from 3.93 (SD 0.88) to 4.01 (SD 0.87) on the 5-point Likert scale. CONCLUSIONS A multidisciplinary mobile care system for patients with advanced gastrointestinal cancer was developed with clinically oriented measures. A prospective study was performed for its evaluation, which showed favorable satisfaction.

Proton exchange membrane fuel cell (PEMFC) systems with their own fuel conversion unit typically consist of a fuel processing subsystem, a fuel cell stack subsystem, a work recovery-air supply subsystem, and a power electronics subsystem. Since these subsystems have different physical characteristics, their integration into a single system level unit makes the optimization problem of synthesis/design and operation/control highly complex. Thus, dynamic system/subsystem/component modeling and highly effective optimization strategies are required. Furthermore, uncertainties in the results of system optimization can be affected by any number of sources of uncertainty such as the load profiles and cost models. These uncertainties can be taken into account by treating the problem probabilistically. The difficulty with doing this, particularly when large-scale dynamic optimization with a large number of degrees of freedom is being used, is that the traditional probabilistic approaches are simply too computationally intensive. This difficulty can be overcome by the use of approximate approaches such as the response sensitivity analysis (RSA) method based on Taylor series expansion. Thus, in this paper, a stochastic modeling and uncertainty analysis methodology for energy system synthesis/design and operation/control which uses the RSA method is proposed and employed for calculating the uncertainties on the system outputs. Their effects on the development and control optimization of a 5 kWe PEMFC system are assessed by taking the uncertainties into account in the objectives and constraints. It is shown that these uncertainties significantly affect the reliability of being able to meet certain constraints (e.g., that on the CO concentration) during the synthesis/design and operation/control optimization process.

During system development, large-scale, complex energy systems require multi-disciplinary efforts to achieve system quality, cost, and performance goals. As systems become larger and more complex, the number of possible system configurations and technologies, which meet the designer’s objectives optimally, increases greatly. In addition, both transient and environmental effects may need to be taken into account. Thus, the difficulty of developing the system via the formulation of a single optimization problem in which the optimal synthesis/design and operation/control of the system are achieved simultaneously is great and rather problematic. This difficulty is further heightened with the introduction of uncertainty analysis, which transforms the problem from a purely deterministic one into a probabilistic one. Uncertainties, system complexity and nonlinearity, and large numbers of decision variables quickly render the single optimization problem unsolvable by conventional, single-level, optimization strategies. To address these difficulties, the strategy adopted here combines a dynamic physical decomposition technique for large-scale optimization with a response sensitivity analysis method for quantifying system response uncertainties to given uncertainty sources. The feasibility of such a hybrid approach is established by applying it to the synthesis/design and operation/control of a 5 kW proton exchange membrane (PEM) fuel cell system.

This paper describes a simplified physics-based method derived from fundamental relationships to accurately predict the dynamic response of the steam bottoming cycle of a combined cycle power plant to the changes in gas turbine exhaust temperature and flow rate. The method offers two advantages: (1) rapid calculation of various modes of combined cycle transient performance such as startup, shutdown and load ramps for conceptual design and optimization studies; (2) transparency of governing principles and solution methods for ease of use by a wider range of practitioners. Thus, the method facilitates better understanding and dissemination of said studies. All requisite formulas and methods described in the paper are readily amenable to implementation on a computational platform of the reader’s choice.Copyright © 2013 by ASME

Korean Abstract: 선거 등의 정치적 사건은 경제에 미치는 영향으로 인해 주식시장 참여자들에게 많은 관심의 대상이다. 투자자들의 미래 시장 상황에 대한 기대를 옵션거래 정보로부터 추출한 위험중립 확률분포를 통해 유추하는 방법이 널리 사용되고 있다. 이 연구에서는 2중 혼합로그 정규분포를 가정하여 선거에 대한 투자자들의 기대 변화를 살펴보았다. 2004년 17대 국회의원 총선거의 경우 투자자들이 지각하는 불확실성이 선거결과 발표 이후 오히려 증가하는 모습을 보였다. 2007년 17대 대통령 선거를 분석한 결과, 여론조사 결과와는 달리 투자자들은 선거 전 상당한 불확실성을 감지하고 있었으며, 이 불확실성이 선거결과의 발표에 반응하여 빠르게 해소되었다는 것을 알 수 있다. 2008년 18대 국회의원 선거의 경우 선거 발표 전의 예측과 거의 차이가 없는 결과가 나오면서 투자자들의 기대에 별다른 영향을 끼치지 못했음이 밝혀졌다. 이를 종합해 볼 때, 투자자들은 단순히 선거결과에 반응하는 것이 아니라, 선거결과가 경제에 미칠 영향을 종합적으로 판단하여 기대를 형성하고 있음을 알 수 있었다. English Abstract: Due to its significant impact on the financial markets, the political events such as elections have intrigued investors. Inferring investors’ expectation through the implied risk neutral distribution is widely used. This research studies the change of investors’ expectation around election days under the mixture of two log-normal assumptions. In the 17th general election at 2004, the investors’ perceived risk increased after the final returns. In the 17th presidential election at 2007, on the contrary to the polls, investors perceive a significant amount of uncertainty before the election. However the uncertainty was resolved quickly after the final return. In the 18th general election at 2008, there was no important effect of the final return, since the result was well predicted beforehand. In sum, investors react to not only the final returns but also the comprehensive effect of the election.

As primary tools for the development of energy systems, optimization techniques have been studied for decades. However, for large-scale synthesis/design and operation/control optimization problems, it may turn out that it is impractical to solve the entire problem as a single optimization problem. In this paper, a multi-level optimization strategy, dynamic iterative local-global optimization (DILGO), is utilized for the synthesis/design and operation/control optimization of a 5 kWe PEMFC (Proton Exchange Membrane Fuel Cell) system. The strategy decomposes the system into three subsystems: a stack subsystem (SS), a fuel processing subsystem (FPS), and a work and air recovery subsystem (WRAS) and, thus, into three optimization sub-problems. To validate the decomposition strategy, the results are compared with a single-level dynamic optimization, in which the whole system is optimized together. In addition, for the purpose of comparison between different optimization algorithms, gradient-based optimization results are compared with those for a hybrid heuristic/gradient-based optimization algorithm.Copyright © 2008 by ASME

An often used approach to the synthesis/design optimization of energy systems is to only use steady state operation and high efficiency (or low total life cycle cost) at full load as the basis for the synthesis/design. Transient and partial load operations are considered secondarily by system and control engineers once the synthesis/design is fixed (i.e. system testing with standard load profiles). This paper considers the system dynamics from the very beginning of the synthesis/design process by developing the system using a set of transient thermodynamic, kinetic, geometric as well as cost models developed and implemented for the components of a 5 kW PEMFC (Proton Exchange Membrane Fuel Cell) system. The system is composed of three subsystems: a stack subsystem (SS), a fuel processing subsystem (FPS), and a work and air recovery subsystem (WRAS). In addition, state space is used in a looped set of optimizations to illustrate the effect of the control system on the synthesis/design optimization and to develop a set of optimal multi-input, multi-output (MIMO) controllers consistent with the optimal synthesis/design of the PEMFC system. It is shown that these MIMO controllers correspond to the ones found in a non-looped optimization in which the gains for the controllers are part of the decision variable set for the overall synthesis/design and operation/control optimization. These last set of results are then compared with the optimizations results found with the traditional approach of using a single load point in order to show the advantage of the dynamic optimization.

A stochastic modeling and uncertainty analysis methodology for energy system synthesis/design is proposed in this paper and applied to the development of the fuel processing subsystem (FPS) of a proton exchange membrane fuel cell (PEMFC) system. The FPS consists of a steam methane reformer, both high and low temperature water-gas shift reactors, a CO preferential oxidation reactor, a steam generator, a combustor, and several heat exchangers. For each component of the system, detailed thermodynamic, geometric, chemical kinetic, and cost models are developed and integrated into an overall model for the subsystem. Conventionally, in energy system synthesis/design, such models are treated deterministically, using a specific set of non-probabilistic input variable values that produce a specific set of non-probabilistic output variable values. Even though these input values, which include the specific load profile (i.e. electrical, thermal, and/or aerodynamic) for which the system or subsystem is synthesized/designed, can have significant uncertainties that inevitably propagate through the system to the outputs, such deterministic approaches are unable to quantify these uncertainties and their effect on the final synthesis/design and operation/control. This deficiency can, of course, be overcome by treating the inputs and outputs probabilistically. The difficulty with doing this, particularly when large-scale dynamic optimization with a large number of degrees of freedom is being used to determine the optimal synthesis/design and operation/control of the system, is that the traditional probabilistic approaches (e.g., Monte Carlo Method) are so computationally intensive that combined with large-scale optimization it renders the problem computationally intractable. This difficulty can be overcome by the use of approximate approaches such as the response sensitivity analysis (RSA) method based on Taylor series expansion. In this study, RSA is employed and developed by the authors for use with dynamic energy system optimization. Load profile and cost models are treated as probabilistic input values and uncertainties in output results investigated. The results for the uncertainty analysis applied to the optimization of the FPS synthesis/design and operation/control are compared with those found using a Monte Carlo approach with good results. In this paper, the FPS synthesis/design and operation optimization is treated as a multi-objective optimization problem to minimize the capital cost and operating cost simultaneously, and uncertainty effects on the optimization are assessed by taking uncertainties into account in the objectives and constraints. Optimization results show that there is little effect on the objective (the operating cost and capital cost), while the constraints (e.g., that on the CO concentration) can be significantly affected during the synthesis/design and operation/control optimization.Copyright © 2008 by ASME

Proton exchange membrane fuel cells (PEMFCs) are one of the leading candidates in alternative energy conversion devices for transportation, stationary, and portable power generation applications. Such systems with their own fuel conversion unit typically consist of several subsystems: a fuel processing subsystem, a fuel cell stack subsystem, a work recovery-air supply subsystem, and a power electronics subsystem. Since these subsystems have different physical characteristics, their integration into a single system/subsystem level unit make the problems of optimal dynamic system synthesis/design and operation/control highly complex. Thus, dynamic system/subsystem/component modeling and highly effective optimization strategies are required. Furthermore, uncertainties in the results of system synthesis/design and operation/control optimization can be affected by any number of sources of uncertainty such as the load profiles and cost models. These uncertainties can be taken into account by treating the problem probabilistically. The difficulty with doing this, particularly when large-scale dynamic optimization with a large number of degrees of freedom is being used to determine the optimal synthesis/design and operation/control of the system, is that the traditional probabilistic approaches (e.g., Monte Carlo Method) are so computationally intensive that combined with large-scale optimization it renders the problem computationally intractable. This difficulty can be overcome by the use of approximate approaches such as the response sensitivity analysis (RSA) method based on Taylor series expansion. Thus, in this paper, a stochastic modeling and uncertainty analysis methodology for energy system synthesis/design and operation/control which uses the RSA method is proposed and employed for calculating the uncertainties on the system outputs. Their effects on the synthesis/design and operation/control optimization of a 5kWe PEMFC system are assessed by taking the uncertainties into account in the objectives and constraints. It is shown that these uncertainties significantly affect the reliability of being able to meet certain constraints (e.g., that on the CO concentration) during the synthesis/design and operation/control optimization process. These and other results are presented.

One of the fundamental questions encountered in finance is how much the price of risk is. Although capital asset pricing model is ingenious, it explains poorly the price of risky asset in real world. The major reason for the defect lies on the strong assumptions of rational representative investor and evident investors' utility function. Researchers have suggested several ways to operationalize empirical tests, but none of them is perfect. The aim of this paper is to answer the question about investors' willingness to pay for risk. The willingness of investors is represented by the Euler equations of consumption as a price of risk. This research suggests a method to calculate the willingness of investors, without any assumption about investors' preference and market efficiency. The proposed method, which is named as Implied Risk Appetite, shows its adequacy through the result of the empirical research which is conducted in the Korean market.