AbstractThis study examines how a manufacturer can improve the robustness of an imperfect production system by implementing maintenance activities, which can be measured in terms of system reliability and product failure rate. A two‐dimensional maintenance policy comprising system reliability and the product defect rate is proposed to assess maintenance activity costs. The optimal thresholds of the two dimensions are analyzed to investigate the trade‐off between cost and system quality. A numerical example is provided to verify the proposed model's effectiveness. The results showed that the less stable the system, the greater the total costs incurred; therefore, lower stringent thresholds may be set to prevent frequent maintenance. Moreover, a sensitivity analysis is performed to investigate the essential parameters that significantly affect maintenance decisions. The results showed that the thresholds of the reliability function and defect rate significantly impact total costs. Any inaccurate assessment of system usage could lead to incorrect estimations and a substantial increase in cost.

This study looks into eco-friendly transactions via mobile payment (MP) adoption in the context of a global emphasis on responsible innovation and sustainable consumption. Focusing on MP adoption in Taiwan and the Philippines and utilizing SPSS and PROCESS tools, we uncover distinct patterns. The Philippines highlights the impact of social factors on hedonic motivations driving MP adoption, whereas Taiwan emphasizes functional aspects, underlining the need for region-specific strategies. By analyzing the interplay between hedonic and utilitarian motives, our research contributes to discussions on environmentally conscious transactional choices in diverse cultural contexts. We emphasize the seamless integration of FinTech innovation and ethical consumer decisions, advocating for sustainable practices in everyday financial transactions. Our findings address contemporary concerns about business ethics, environmental sustainability, and responsibility, offering a roadmap for fostering greener consumer behaviors.

Let G be a connected graph with vertex set V, where the distance between two vertices is the length of a shortest path between them. A set S⊆V is [1,2]-resolving if each vertex of G is at most distance-two away from a vertex in S and, given a pair of distinct vertices not in S, either there is a vertex in S adjacent to exactly one member of the given pair, or there are two vertices in S each of which is distance-two from exactly one member of the given pair. The [1,2]-dimension of G is the minimum cardinality of a [1,2]-resolving set of G. In this paper, we study the [1,2]-dimension of graphs by proving that the [1,2]-dimension problem is an NP-complete problem, and determine the [1,2]-dimension of some classes of graphs, such as paths, cycles, and full k-ary trees. We also introduce a generalization of metric dimension of which the (original) metric dimension and the [1,2]-dimension, as well as other metric dimension variants in the literature, are special instances.

Infantile hemangiomas (IHs) of the lips are associated with an increased risk of incomplete involution and ulceration, causing disfigurement. Treatment with oral propranolol (OPT) has credible efficacy but takes months to complete. Thus, this study aimed to investigate the efficacy of intralesional betamethasone injection (IBI) as an alternative treatment for protruding localized IHs of the lips. To investigate the efficacies of OPT and IBI, we designed a prospective, noninferiority, parallel-group study. The primary outcome assessed was treatment response rate. Secondary outcome assessments included lesion size changes and surgical rate. Additionally, complication rates and treatment durations of OPT and IBI were compared. The treatment response rate of IBI was not inferior to that of OPT (95.7% vs. 76.0%, respectively; a difference of 19.7%, 95% confidence interval [CI], -4.4% to 41.6%). The average surgical rate in the IBI group was significantly lower than that in the OPT group (8.7% vs. 40%, respectively; p=0.012), and the average duration of treatment for IBI was shorter than that of OPT (2.1 months vs. 6.3 months, respectively; p<0.001). There were no severe adverse drug events in either group. If not managed properly, small, localized lip IHs may cause disfigurement in a child. Our study demonstrated that IBI is as effective as OPT in treating protruding localized lip IHs. Moreover, IBI treatment has a shorter duration and lower surgical rate than OPT. With proper care, IBI is an effective treatment modality for small and localized lip IHs.

Granger causality is a classical and important technique for measuring predictability from one group of time series to another by incorporating information of the variables described by a full vector autoregressive (VAR) process. However, in some applications economic forecasts need to be made based on information provided merely by a portion of variates (e.g., removal of a listed stock due to halting, suspension or delisting). This requires a new formulation of forecast based on an embedded subprocess of VAR, whose theoretical properties are often difficult to obtain. To avoid the issue of identifying the VAR subprocess, we propose a computation‐based approach so that sophisticated predictions can be made by utilizing a reduced variable information set estimated from sampled data. Such estimated information set allows us to develop a suitable statistical hypothesis testing procedure for characterizing all designated Granger causal relationships, as well as a useful graphical tool for presenting the causal structure over the prediction horizon. Finally, simulated data and a real example from the stock markets are used to illustrate the proposed method.

AbstractCancer is among the leading causes of death in the world, with about 10 million deaths, one in every six deaths, related to cancer in 2020. In Taiwan, cancer insurance is the most popular commercial health product. However, the loss ratio of cancer products increases with policy year and exceeds 100% in many insurance companies. In addition, almost all cancer benefits are significantly limited in order to avoid financial insolvency. In this study, we evaluate the risk of cancer insurance from the perspective of morbidity compression. We use the data from Taiwan's National Health Insurance Research Database. Also, we apply the standardized mortality ratio and the Lee-Carter model to estimate the trend of cancer-related values. We find that cancer incidence rates gradually increase with time, which indicates that the assumption of morbidity compression is violated. On the other hand, the mortality rates of cancer patients decrease significantly annually. Thus, length of life with cancer increases, and so does the cancer insurance premium. We suggest that cancer insurance covers only the first five years of medical expenditure after the insured is diagnosed with cancer.

AbstractThe increasing use of machine learning and Large Language Models (LLMs) opens up opportunities to use these artificially intelligent algorithms in novel ways. This article proposes a methodology using LLMs to support traditional deductive coding in qualitative research. We began our analysis with three different sample texts taken from existing interviews. Next, we created a codebook and inputted the sample text and codebook into an LLM. We asked the LLM to determine if the codes were present in a sample text provided and requested evidence to support the coding. The sample texts were inputted 160 times to record changes between iterations of the LLM response. Each iteration was analogous to a new coder deductively analyzing the text with the codebook information. In our results, we present the outputs for these recursive analyses, along with a comparison of the LLM coding to evaluations made by human coders using traditional coding methods. We argue that LLM analysis can aid qualitative researchers by deductively coding transcripts, providing a systematic and reliable platform for code identification, and offering a means of avoiding analysis misalignment. Implications of using LLM in research praxis are discussed, along with current limitations.

Chronic post-traumatic stress disorder (PTSD) exhibits psychological abnormalities during fear memory processing in rodent models. To simulate long-term impaired fear extinction in PTSD patients, we constructed a seven-day model with multiple prolonged stress (MPS) by modifying manipulation repetitions, intensity, and unpredictability of stressors. Behavioral and neural changes following MPS conveyed longitudinal PTSD-like effects in rats for 6 weeks. Extended fear memory was estimated through fear retrieval induced-freezing behavior and increased long-term serum corticosterone concentrations after MPS manipulation. Additionally, memory retrieval and behavioral anxiety tasks continued enhancing theta oscillation activity in the prefrontal cortex-basal lateral amygdala-ventral hippocampus pathway for an extended period. Moreover, MPS and remote fear retrieval stimuli disrupted sleep-wake activities to consolidate fear memory. Our prolonged fear memory, neuronal connectivity, anxiety, and sleep alteration results demonstrated integrated chronic PTSD symptoms in an MPS-induced rodent model.