Browsing by Author "Chung S.-H."

Background: Lead-exposed workers may suffer adverse health effects under the currently regulated blood lead (BPb) levels. However, a probabilistic assessment about lead exposure-associated anemia risk is lacking. The goal of this study was to examine the association between lead exposure and anemia risk among factory workers in Taiwan. Methods: We first collated BPb and indicators of hematopoietic function data via health examination records that included 533 male and 218 female lead-exposed workers between 2012 and 2014. We used benchmark dose (BMD) modeling to estimate the critical effect doses for detection of abnormal indicators. A risk-based probabilistic model was used to characterize the potential hazard of lead poisoning for job-specific workers by hazard index (HI). We applied Bayesian decision analysis to determine whether BMD could be implicated as a suitable BPb standard. Results: Our results indicated that HI for total lead-exposed workers was 0.78 (95% confidence interval: 0.50-1.26) with risk occurrence probability of 11.1%. The abnormal risk of anemia indicators for male and female workers could be reduced, respectively, by 67-77% and 86-95% by adopting the suggested BPb standards of 25 and 15 μg/dL. Conclusions: We conclude that cumulative exposure to lead in the workplace was significantly associated with anemia risk. This study suggests that current BPb standard needs to be better understood for the application of lead-exposed population protection in different scenarios to provide a novel standard for health management. Low-level lead exposure risk is an occupational and public health problem that should be paid more attention. ? 2017 The Author(s).

Data science and analytics are attracting more and more attention from researchers and practitioners in recent years. Due to the rapid development of advanced technologies nowadays, a massive amount of real time data regarding flight information, flight performance, airport conditions, air traffic conditions, weather, ticket prices, passengers comments, crew comments, etc., are all available from a diverse set of sources, including flight performance monitoring systems, operational systems of airlines and airports, and social media platforms. Development of data analytics in aviation and related applications is also growing rapidly. This paper concisely examines data science and analytics in aviation studies in several critical areas, namely big data analysis, air transport network management, forecasting, and machine learning. The papers featured in this special issue are also introduced and reviewed, and future directions for data science and analytics in aviation are discussed. ? 2020 Elsevier Ltd

Epidermal growth factor receptor (EGFR) is an important oncoprotein that promotes cell growth and proliferation. Dasatinib, a bcr-abl inhibitor, has been approved clinically for the treatment of chronic myeloid leukemia and demonstrated to be effective against solid tumors in vitro through Src inhibition. Here, we disclose that EGFR degradation mediated dasatinib-induced apoptosis in head and neck squamous cell carcinoma (HNSCC) cells. HNSCC cells, including Ca9-22, FaDu, HSC3, SAS, SCC-25, and UMSCC1, were treated with dasatinib, and cell viability, apoptosis, and underlying signal transduction were evaluated. Dasatinib exhibited differential sensitivities against HNSCC cells. Growth inhibition and apoptosis were correlated with its inhibition on Akt, Erk, and Bcl-2, irrespective of Src inhibition. Accordingly, we found that down-regulation of EGFR was a determinant of dasatinib sensitivity. Lysosome inhibitor reversed dasatinib-induced EGFR down-regulation, and c-cbl activity was increased by dasatinib, indicating that dasatinib-induced EGFR down-regulation might be through c-cbl-mediated lysosome degradation. Increased EGFR activation by ligand administration rescued cells from dasatinib-induced apoptosis, whereas inhibition of EGFR enhanced its apoptotic effect. Estrogen receptor α (ERα) was demonstrated to play a role in Bcl-2 expression, and dasatinib inhibited ERα at the pretranslational level. ERα was associated with EGFR in dasatinib-treated HNSCC cells. Furthermore, the xenograft model showed that dasatinib inhibited HSC3 tumor growth through in vivo downregulation of EGFR and ERα. In conclusion, degradation of EGFR is a novel mechanism responsible for dasatinibinduced apoptosis in HNSCC cells. ? 2012 Neoplasia Press, Inc. All rights reserved.

Over the past decades, we have witnessed the rapid development of giant fashion brands in the retail market which inspires a lot of operational research (OR) studies in fashion retail supply chains (FRSCs). In fact, FRSCs are highly consumer-demand driven and face many operational challenges coming from high demand and supply side uncertainties. Realizing the significance of fashion retail supply chain management (FRSCM) and a lack of comprehensive review on the topic, we develop this paper which examines the operational models on FRSCM in the mainstream OR literature. We organize this review systematically with respect to the core functional areas of FRSCs, namely the manufacturer, retailer, consumer, and fashion retail supply chain system. In each functional area, insights regarding the related studies as well as the specific OR model features and assumptions are generated. Finally, we conclude the review by summarizing the major findings and proposing promising future research areas (from both OR modeling and practical perspectives). ? 2018 Elsevier B.V.

Supply chain operations have entered the digital era with the emergence of blockchain technology. In this paper, we discuss how the mean?ariance (MV)approach can be applied to explore global supply chain operations risk with air logistics in the blockchain technology era. To be specific, we examine the related literature from four areas, namely air-logistics operations, demand management, supply management, and supply-demand coordination. We propose how the blockchain technology can be applied to facilitate the implementation of mean-variance risk analysis for global supply chain operations. We then highlight several promising areas for further studies. A future research agenda is developed. ? 2019 Elsevier Ltd

Today, many e-tailers sell through e-platforms. Some of them sell products through both their own direct-online (DO) sales channel and e-platforms, while some give up their own DO sales channel and sell solely through e-platforms. Motivated by the popularity of e-platforms, we explore in this paper the optimal channel selection and e-platform service contracting problem. We build analytical models to explore “when” an e-tailer should choose “which” channel structure. Based on the commonly-observed industrial practices, in the basic models, we derive the optimal e-platform service contract which is a revenue-sharing plus fixed fee (RSF) service contract. We establish the conditions under which the e-tailer's optimal channel selection choice will also be optimal for the e-platform systems. To test robustness of the research findings, three extensions are examined. For the extended model with a separate manufacturer, as well as the extended analysis with a social welfare optimization objective, we reveal that all the findings in the basic models remain valid. However, when the e-tailer decides both product pricing and quality, we uncover that the RSF service contract fails to achieve robust systems optimization. We hence show how the use of a cost-sharing RSF service contract can help. ? 2022 Elsevier Ltd

Air-cargo transportation has become increasingly important for global logistics systems nowadays. However, due to the intensive market competition and diverse uncertainties arising from demand and operating costs, the pricing decisions for air-cargo carriers are extremely challenging but underexplored. Besides, many airlines are holding risk-averse attitudes in decision making in order to survive in the highly volatile and competitive market. Therefore, in this paper, we apply the mean-variance theory to characterize the risk-averse behaviors of decision makers, and analytically derive the equilibrium prices for two competing risk-averse air-cargo carriers under demand and cost uncertainties. Then, we uncover how the crucial factors, like risk sensitivity coefficients, market competition, market share, demand uncertainty, and cost uncertainty, affect the carriers' optimal prices. In addition, important cost thresholds and relative risk-averse attitude thresholds are identified. Our analytical results demonstrate the symmetry in the optimal prices and critical thresholds for the two carriers. Besides, we reveal the importance to consider both carrier's own and the competitor's risk attitudes and operating characteristics in decision making when market competition exists. Moreover, we reveal the direct and indirect impacts of risk attitudes on the optimal prices, thus highlighting the importance to integrate risk considerations into the optimal pricing decision framework. Finally, we show that market situations play a critical role in characterizing the effects of diverse parameters on the equilibrium prices, which should be carefully evaluated by decision makers in air-cargo carriers. ? 2013 IEEE.

In the fashion industry, many brands operate under different kinds of franchising systems. In many cases, there is a fixed royalty charged by the franchisor. We observe that some franchisors insist on charging the fixed royalty as an upfront payment (before starting the franchising operations), whereas some request the franchisees to pay after the franchising operations have started. We name the first scenario as the upfront payment (URP) plan and the later one as the later payment (LRP) plan. In this paper, based on real world observed franchising arrangements for sustainable fashion brands, we build analytical models to compare the URP plan and the LRP plan from the supply chain finance perspective. We find that the social welfare performance (SWP) under the URP scenario depends on the value of royalty payment, while the SWP under the LRP scenario is not affected by the royalty payment. Moreover, the profit risks of the franchisee, the supply chain and the social welfare all increase with the order quantity. In the extended model, we explore the case when both the fixed royalty and the variable royalty co-exist. Finally, we explore the supply chain coordination problems and generate managerial insights. ? 2019 Elsevier B.V.

Container-shipping-lines (CSLs) operate in a highly competitive market with high demand volatility. Unlike many other industries in which risk-averse attitude is dominating, it is well known that many CSLs exhibit risk-seeking behaviors. In this paper, by using the mean-risk formulation, we analytically study the effects of risk attitude and demand volatility on the service pricing game between two CSLs. We find that the equilibrium prices increase when CSLs can accept more risk, and being slightly risk-seeking can help maximize the expected profits of both CSLs. We discover the risk-attitude convergence effect, which theoretically reveals that the ?ptimal risk attitudes??for the CSLs move in the same direction. Therefore, our research suggests that both CSLs should hire slightly risk-seeking managers in a competitive shipping market. In addition, we explore the impacts brought by demand volatility and find that the equilibrium prices increase (decrease) in the demand volatility when CSLs are risk-seeking (risk-averse). We uncover that when an individual CSL's risk sensitivity level is small and its rival is risk-seeking, its own expected profit under the decentralized case could be larger than that in centralized case. Finally, for robustness checking of our research findings, we investigate the scenarios with multiplicative randomness of demand, asymmetric information on risk attitude and multiple (more than two) competing CSLs, and find that our main findings still hold. Counterintuitively, in the case with multiplicatively random demand, we analytically find that CSLs may not prefer a large market potential when they are risk-averse. ? 2020 Elsevier Ltd

Today, in the market with ever-changing consumer preferences, three-dimensional (3D) printing is becoming an overwhelming trend. In this paper, we explore the use of 3D printing in mass customization (MC) programs. We consider the case when 3D printing brings extra self-design fun to consumers, which is highlighted in MC practices of the auto company BMW and the furniture company Poltrona Frau, and also changes the cost formula (i.e., the marginal product variety cost) of the MC product. In addition, the roles played by the risk attitudes of the MC manufacturer and consumers, consumer returns, as well as consumers??time sensitive behaviors, are also uncovered. We find that under the case with a low consumer's willingness to pay for the traditional ?eady-made product variety enjoyment??(RPVE), even the maximized product variety level and the additional self-design fun cannot make the 3D printing based MC more profitable. In addition, compared to the markets with risk-averse and risk-neutral consumers, the 3D printing based MC can increase more MRBs and a higher consumer surplus by simultaneously highlighting the high self-design fun and the high RPVE in a market with risk-seeking consumers. The high flexibility and responsiveness of 3D printing also shows its advantages in remanufacturing the consumer returned MC items and enhancing MC programs??overall lead-time. Finally, applying 3D printing in creating molds can also help the MC manufacturer tackle demand uncertainties. These findings all provide a good reference to the application of 3D printing in MC operations. ? 2021 Elsevier B.V.