Continuous deep sedation (CDS) has the effect of making the patient unconscious until death, and that it has this effect is clearly an undesirable aspect of CDS. However, some authors have recently maintained that many physicians do not intend this effect when practicing CDS. According to these authors, CDS is differentiated into two types; in what is called “gradual” CDS (or CDS as a result of proportionate palliative sedation), physicians start with low doses of sedatives and increase them only gradually, (...) whereas in “rapid” CDS (or palliative sedation to unconsciousness), physicians rapidly administer a heavy dose that clearly induces unconsciousness from the beginning. The claim is that the physicians intend permanent unconsciousness only if they rapidly administer a heavy dose, but they do not intend it when the unconsciousness is the result of a gradual increase of sedatives. This paper attempts to refute these claims based on a close examination of the protocol of gradual CDS. If my argument is valid, the doctrine of double effect would not be useful in justifying most, if not all, cases of CDS. (shrink)

The “dead-donor rule” states that, in any case of vital organ donation, the potential donor should be determined to be dead before transplantation occurs. In many countries around the world, neurological criteria can be used to legally determine death (also referred to as brain death). Nevertheless, there is considerable controversy in the bioethics literature over whether brain death is the equivalent of biological death. This international legal review demonstrates that there is considerable variability in how different jurisdictions have evolved to (...) justify the legal status of brain death and its relationship to the dead-donor rule.In this article, we chose to review approaches that are representative of many different jurisdictions—the United States takes an approach similar to that of many European countries; the United Kingdom’s approach is followed by Canada, India, and influences many other Commonwealth countries; Islamic jurisprudence is applicable to several different national laws; the Israeli approach is similar to many Western countries, but incorporates noteworthy modifications; and Japan’s relatively idiosyncratic approach has received some attention in the literature. Illuminating these different justifications may help develop respectful policies regarding organ donation within countries with diverse populations and allow for more informed debate about brain death and the deaddonor rule. (shrink)

Objectives: This study aimed to conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) to improve subjective well-being (SWB), including evaluative, hedonic, and eudemonic well-being, and the mental component of quality of life (QOL) of working population. Methods: A literature search was conducted, using PubMed, Embase, PsycINFO, and PsycARTICLES. Eligible studies included those that were RCTs of any intervention, conducted among healthy workers, measured SWB as a primary outcome, and original articles in English. Study characteristics, intervention, outcomes, and (...) results on SWB outcomes were extracted by the investigators independently. After a brief narrative summarizing and classifying the contents of the interventions, the included outcomes were categorized into each aspect of SWB (evaluative, hedonic, and eudemonic well-being, and the mental component of QOL). Finally, the characteristics of the effective interventions for increasing each aspect were summarized, and the pooled effect of interventions on SWB was investigated by a meta-analysis. Publication bias was investigated by drawing a funnel plot and conducting Egger's test. Results: From the 5,450 articles found, 39 met the inclusion criteria for the systematic review. The interventions included in this review were classified into six categories (physical activity, ergonomics, psychological, environmental, multicomponent intervention, and others). The meta-analysis from 31 studies showed that the pooled effect of included interventions on SWB was significantly positive (standardized mean difference (SMD) = 0.51; standard error (SE) = 0.10). A funnel plot showed there were extremely large or small SMDs, and Egger's test was significant. Thus, we conducted sensitivity analysis, excluding these extreme SMDs, and confirmed that the estimated pooled effect was also significantly positive. Subgroup analyses for separate types of interventions showed the effects of psychological interventions (e.g., mindfulness, cognitive behavioral based approach, and other psychological interventions) were also significantly positive. Conclusion: The current study revealed the effectiveness of interventions for increasing SWB. Specifically, psychological interventions (e.g., mindfulness, cognitive behavioral based approach, and other psychological interventions) may be useful for improving SWB. (shrink)

The costs of agricultural inputs added to those of labor represent almost a third of the total cost of Brazilian sugarcane production. This study analyzes the behavior of the price per ton of sugarcane in Brazil, relating it to the main production costs of this cultivation. Twelve price indicators from January 2015 to December 2020 were evaluated. First, the data were adjusted to a multiple linear regression model to identify the significant variables on variation in the price per ton of (...) sugarcane. Then, the Monte Carlo simulation was used to measure the level of certainty of occurrence of these variables, and forecasts were obtained from the adjustment of ARIMA models. The results showed the influence of the costs of diesel oil, two agricultural pesticides, and daily laborers on the price of sugarcane, besides an increasing trend of its, providing relevant short-term projections for decision-making about investments in the agribusiness sector. (shrink)

Herring and mackerel are two of the most important pillars of Scottish fisheries. In recent years, global warming has caused a gradual rise in ocean temperatures. In order to survive and reproduce, herring and mackerel populations will migrate. This will have a huge impact on Scotland’s fisheries. Therefore, we need to predict the relocation of fish stocks in advance, make timely adjustments to the fishing range, and minimize the loss of the fishing industry. In this article, we subdivide the research (...) target sea area into 39 regions, establish the optimal SARIMA model for each region based on the collected seawater temperature time series data, and take region 13 and region 15 as examples to fit the ARIMA and ARIMA models with a period of 12. The results show that the SARIMA model fits well in all regions and predicts the temperature changes in the studied sea area from 2021 to 2050. Finally, according to the predicted sea temperature in different periods, the migration position of the fish school is predicted. (shrink)

In recent years, due to factors such as rising sea levels, several island nations such as Maldives, Tuvalu, Kiribati, and the Marshall Islands are in danger of disappearing completely. When the land of an island country disappeared, the human rights protection of Environmentally Displaced Persons in the migration process and the possible loss of their unique culture, language, and lifestyle have aroused great concern. We call such Environmentally Displaced Persons as EDPs. This study selects the EDPs’ data of 241 countries (...) or regions from 2008 to 2018, establishes an ARIMA model, and predicts the future population of EDPs. By combining the influencing factors of cultural loss, the risk assessment model of cultural loss is established to evaluate the possibility of cultural loss during the migration process of EDPs. We have established a Bayesian Network and a Fault Tree Model to demonstrate the improvement brought about by the implementation of policy recommendations from both qualitative and quantitative perspectives and use the method of fault tree analysis to illustrate the importance of policies from the degree of probability reduction after policy changes. Finally, based on the above model establishment and data analysis, corresponding countermeasures are proposed to protect EDPs’ human rights from being violated and their culture will not be lost. (shrink)

Electric-mechanical equipment manufacturing industries focus on the implementation of intelligent manufacturing systems in order to enhance customer services for highly customized machines with high-profit margins such as electric power transformers. Intelligent manufacturing consists in using supply chain data that are integrated for smart decision making during the production life cycle. This research, in cooperation with a large electric power transformer manufacturer, provides an overview of critical intelligent manufacturing technologies. An ontology schema forms the terminology relationships needed to build two intelligent (...) supply chain management modules for the IM system demonstration. The two core modules proposed in this research are the intelligent supplier selection and component ordering module and the product quality prediction module. The intelligent supplier selection and component ordering module dispatches orders that match the best options of suppliers based on combined analytic hierarchy process analysis and multiobjective integer optimization. In the case study, the intelligent supplier selection and component ordering module demonstrates several acceptable Pareto solutions based on strict constraints, which is a very challenging task for decision makers without assistance. The second module is the product quality prediction module which uses multivariate regression and ARIMA to predict the quality of the finished products. Results show that the R square values are very close to 1. The module shortens the time for the company to accurately judge whether the two semifinished iron cores for the product meet the quality requirements. The component supplier selection module and the finished product quality prediction module developed in this research can be extended to other IM systems for general high-end equipment manufacturers using mass customization. (shrink)

Based on the research of currency crisis pressure index, bank crisis pressure index, and asset bubble crisis pressure index, this paper introduces an external shock pressure index reflecting the impact of global economic changes on economy and synthesizes systemic financial crisis pressure based on the above four pressure indexes; then, all the alternative early warning indicators and the systemic risk pressure index constructed in this paper were tested for Granger causality. We build financial systemic risk pressure indexes, including currency crisis (...) pressure banking crisis pressure index, bubble crisis pressure index, and external shock pressure index to predict financial crises. Finally, four indicators that have a significant impact on the systemic financial crisis pressure index were selected, namely, the stock price index change rate, industrial added value growth rate, domestic and foreign real deposit interest rate differential, and foreign direct investment as a percentage of GDP. A dynamic Logit model with lagging binary variables is constructed, and compared with the traditional static Logit line, the actual dynamic fitting effect is better than the static Logit model. The dynamic Logit model is used to predict the early warning status of systemic financial crisis in 2020, and the forecast of various early warning indicators is realized by the ARIMA model. The final prediction results show that the probability of a systemic financial crisis in China in 2020 is extremely low, almost zero. This is in line with the overall improvement in the international economic situation in 2020 and the steady growth of the domestic economy. (shrink)

The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron, recurrent neural network, and autoregressive integrated moving average on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA-MLP and ARIMA-RNN. Because of the complicated and noisy nature of financial data, we combine novel machine-learning techniques such as MLP and RNN with ARIMA model to (...) predict the three stock market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA-MLP and ARIMA-RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root-mean-square error and mean absolute error. Apart from this, ARIMA-MLP outperformed the ARIMA-RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA-RNN beat the ARIMA-MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time-series forecasting. (shrink)

In this article, we discuss the use of time series models in communication research. More specifically, we consider autoregressive and moving-average processes, which together constitute the autoregressive integrated moving average-framework. This approach provides a comprehensive framework to deal with the essential issue of stationarity and to model the dynamics of any time series by estimating the autocorrelation structure. Underlying the models are questions as to what extent news tends to reproduce itself and how news flows adjust after deviations from the (...) normal news stream. The data illustrating the models consist of visibility-scores of the immigration issue in Dutch national newspapers. The empirical analysis demonstrates that the impact of immigration figures on this visibility is not significant when the ARIMA-framework is applied, while an analysis using OLS suggests a positive influence. (shrink)

As new energy vehicle is the future of automobile development, it is of great significance to dig deeper into the technical topics and development trends of new energy vehicles for accurately understanding the technical trends of the new energy vehicle industry, grasping development opportunities, and scientifically formulating strategic plans. This paper takes the patent texts in the field of new energy vehicles from 2000 to 2020 in the patent database of CNKI as the data source, identifies 25 technical topics implied (...) in the patent texts by using the LDA topic model, analyzes the evolution trend of the 25 technical topics in terms of importance and popularity, and predicts the popularity and development trend of each technical topic in new energy vehicles from 2021 to 2025 by constructing the ARIMA model. The popularity and development trend of each technology topic of new energy vehicles in China from 2021 to 2025 are predicted by constructing ARIMA model. Drawing on quantitative evidence, the study found that there are top five technical topics in terms of importance in this field, namely, Topic 8, Topic 5, Topic 14, Topic 9, and Topic 15. From 2014 to 2020, the importances of Topic 5, Topic 8, Topic 6, Topic 9, and Topic 15 are gradually rising. In terms of popularity of technical topics, from 2014 to 2020, the first to fifth topics are Topic 20, Topic 8, Topic 3, Topic 15, and Topic 10. Based on the prediction of ARIMA model, it is found that the popularity of these five technical topics is steadily increasing from 2021 to 2025, among which the popularity of Topic 20 will increase from 63.58 to 113.07, the largest increase in popularity among all technical topics. The paper provides implications for countries dedicated to developing the new energy vehicle industry. (shrink)

En los últimos años se ha propuesto una importante cantidad de métodos estadísticos demográficos. La gran mayoría han sido desarrollados con la finalidad de pronosticar las componentes demográficas y/o medidas derivadas a partir de la suposición de un modelo subyacente. El presente trabajo pretende realizar un ejercicio comparativo integral a través de la estimación y pronóstico de la fecundidad a partir de tres propuestas —métodos clásicos de pronóstico, tales como los modelos ARIMA y los suavizados exponenciales, modelos para datos (...) funcionales (MDF) y modelos jerárquicos bayesianos (MJB)—, como un primer paso hacia el estudio de las proyecciones de población derivadas de cada una de ellas, empleando datos de la Argentina. El ejercicio tiene como horizonte final la estimación de la mortalidad y la fecundidad a través de los tres métodos mencionados para luego integrarlos en proyecciones de población. (shrink)