Reasonable Decisions Research Articles

Factors Involved in Shared Decision-making Regarding Treatment Selection by Patients With Cancer.

Patients diagnosed with cancer are expected to choose one or more treatment modalities after receiving corresponding explanations of the options. When making these choices, patients consider the effects of treatment and aspects related to their quality of life. These concerns can cause confusion and conflict owing to the complicated information provided by medical caregivers. The objective of the study was to identify perceptions of cancer treatment in patients with cancer and the decision-making factors affecting their treatment choices. In this observational (cross-sectional) study, an online questionnaire survey was administered to 194 Japanese cancer patients with treatment experience. Patient information, perceptions of explanations provided by healthcare professionals, treatment views, and reasons for treatment decisions were subjected to a simple tabulation. Content and factor analysis was conducted to determine important treatment selection elements. Regarding treatment perception, 60.3% of respondents (n=117) considered treatment a financial and family burden, 47.4% (n=92) had concerns about physical pain, and 40.2% (n=78) were worried about increased stress. Regarding decision-making quality, 95.9% determined their preferred treatment within one week, 49.0% reported difficulties in making their decisions, and 83.0% chose their treatment themselves. Major decisive factors were prolonging life, opinions of medical staff, and accepting treatment risks (68.0%, 68.6%, and 60.3% of patients, respectively). The main attitudes toward treatment were anxiety, expectations of benefit, and expectations of support and care. SDM should enable patients to visualize the changes that their bodies will experience and include discussions on prognosis. Psychological care should be prioritized to alleviate anxiety and improve readiness for decision-making; attention should be paid to the extent and timing of information provision.

Optimal Project Portfolio Selection Considering Cascading Failure Among Projects

A novel model is proposed for optimal project portfolio selection (PPS). Different from previous PPS methods that consider the interdependence, interaction, or synergy relationships among projects, this article considers the cascading failure process caused by these relationships. Specifically, we first construct a PP network (PPN) and determine the initial load and capacity of the projects (nodes). Afterward, we simulate the cascading failure process by attacking one or more projects in the PP and distribute the load of the failed projects to nonfailed neighboring projects. The cascading failure process ends until no project fails. Finally, we propose a new indicator to measure and compare each PPN's cascading failure results, based on which the optimal PP is selected. A numerical experiment is conducted to depict the PPS process. The results of this study provide guiding implications for project portfolio management decision-makers, helping them consider PPS problems from a new perspective and make more reasonable decisions.

Mutual Influence Mechanism and Optimization Strategy of University Town and Urban Economic Growth Based on Time Series Forecasting Model

Abstract University towns and urban economic growth have important interactions, and time series forecasting models can enable urban planners to better clarify the relationship between the two so as to make more scientific and reasonable decisions. Based on the time series forecasting model constructed in this paper, this paper analyzes and forecasts the relationship between university cities and urban economic growth in C. The main conclusions of this paper are that the p-value of ARIMA(0,2,3) and ARIMA(1,1,1) models is lower than 0.05, and the prediction accuracy of ARIMA(1,1,1) model is higher than that of ARIMA(0,2,3) and ARIMA(1,1,1) model in the prediction of the two. ARIMA(0,2,3) with predicted values of 27631.3, 31541.5, and 24412.45, and the error values from the actual values are only 304.98, 1997.49, and 867.95. This paper’s time series prediction model has achieved good results, as evidenced by this. Y1 shows a highly positive correlation with X1, X3, and X4 and a significant positive correlation with X2, which leads to the conclusion that the total amount of investment in urban construction of the university city of C city has a substantial relationship with the economic growth of C city.

Bioética clínica, deliberação e digitalização da medicina

Abstract The development of cognitive technologies and the robotization in health care may intensify the relational distance between healthcare professionals and patients. Therefore, bioethical reflection is essential to find the most appropriate means to integrate the benefits of digital technologies into health care, ensuring ethical care. Thus, bioethics provides healthcare professionals and patients with discursive resources, aiming to enable the most prudent and reasonable decision-making. The exercise of communicative competence is crucial in the process of digitalizing medical activities and in the use of data analysis through artificial intelligence. Deliberative practice and patient-centered medical care are the ethical directives for the introduction of computational technology in medicine, preserving humanized and dialogical health care.

Ethical reasoning in medical decisions: the physician-patient dilemma

Ethical reasoning in medical decisions: the physician-patient dilemma

Eugenic Continuities: Youth, Sex, Disability, and the Rise of Liberal Eugenics in the Late Twentieth Century

Abstract: This article places the landmark 1986 Supreme Court of Canada decision E. (Mrs.) v. Eve within its avowedly anti-eugenic context. Then it compares the trial record and appellate documents of Eve to the notorious 1927 American case Buck v. Bell . It outlines the legal reasoning of the Eve decision, its reception, and the different trajectories of law in the US, the UK, and Australia. These multiple points of historical comparison expose a series of unresolved eugenic continuities in the politics of youth, sex, and disability. The interpretation challenges more conventional definitions, periodization, and understandings of eugenics, drawing attention to the formation of "liberal" eugenics in the late twentieth century.

Звітність суб’єктів господарювання як джерело аналізу та інструмент управління

The article summarizes the results of the study of the modern specifics of reporting of an economic entity and its types in the context of consideration as a source of analysis and management needs. An analysis of modern types of reporting from the standpoint of their essence, purpose, brief overview of indicators and interconnectedness of data on the activities of an economic entity is carried out. Attention is focused on transformational changes in economic emphasis and the development of sustainability reporting and taking into account strategic prospects. This made it possible to substantiate the conclusion about the growing role of reporting in increasing the level of development and competitiveness of enterprise. It is argued that a comprehensive analysis of reporting provides a wider range of indicators for managerial decision-making, which allows making more reasonable and high-quality managerial decisions on activities and determining directions for improving the processes taking place in the enterprise. The principles of formation and the principles of selection of types of reporting of economic entities necessary for management, in accordance with the objectives and requests of the management system in modern conditions, are determined. A structural-logical scheme of the relationship between types of reporting and the managerial process has been proposed, which reflects the step-by-step analytical component, as well as the corresponding steering algorithms that are adequate to different levels and types of management. It is proved that the use of information data of all types of reporting will allow to effectively analyze and evaluate, as well as determine the directions of development of an economic entity, taking into account the existing modern challenges. The place of types of reporting in the managerial process of enterprise is determined, which shows their importance in determining new vectors of development of economic entities in an unstable and competitive environment. In the perspective, the relevant direction of research is the development and substantiation of new methodological approaches to the analysis of the reporting of economic entities, argumentation of the composition of analytical indicators and solving the problem of identifying tasks and algorithms for their calculations.

A Target-Aware Well Path Control Method Based on Transfer Reinforcement Learning

Summary In the actual construction process, well path control is a challenging task mainly due to the inevitable well deflection caused by geological factors, drilling tools as well as borehole enlargement. Most conventional well path control methods focus on elaborate mechanism model construction. The methods are typically constructed on the basis of certain constraints or assumptions, which reflect their limited ability to accurately capture the actual drilling process, low level of intelligence, poor anti-interference performance, and weak adaptive capacity. To address these challenges, this paper proposes a target-aware well path control method that integrates reinforcement learning and transfer learning. The proposed method employs a deep deterministic policy gradient model based on the prioritized experience replay mechanism and leverages transfer learning to accelerate model learning. This enables the construction of a target-aware well path adaptive control system with strong anti-interference capability. The proposed target-aware control method of well path based on reinforcement learning and transfer learning can accurately track the preset trajectory in diverse geological environments, reach the target area with high precision, and make reasonable trajectory optimization decisions with measurement while drilling (MWD) even when the target trajectory does not match the actual distribution of the reservoir. This approach exhibits excellent anti-interference and adaptive abilities.

Формирование полимерных материалов повышенной термостабильности

Due to its versatility, low cost and relative environmental safety, polyvinyl chloride be-longs to the most widely used group of thermoplastics. The key method in the production of composites based on polyvinyl chloride is the introduction of additives that improve the required characteristics. The expansion of the scope of polymeric materials leads to the development of composites with increased thermal stability. Achieving this goal with the help of phosphorus-containing and halogen-containing additives is not always justified and possible. Mineral fillers do not lose their relevance in the production of composites with increased thermal stability. Sustainable development contributes to the need for certain reasonable decisions to ensure the safety of our planet. One of these is the involvement of waste in the production cycle. The main factor in using fillers is to ensure a uniform distribution of particles, which is achievedby reducing the particle size of a filler, among other things. The paper shows the potential use of vermiculite and eggshell as fillers for polymers with increased thermal stability. Formulations of PVC compositions containing the listed fillers have been compiled. The synergism of the effect of these additives on the thermoanalytical characteristics of PVC compositions has been studied. Their joint influence of compounds with their content on the rheology has been determined.

A simulation-based comparison of drug-drug interaction signal detection methods.

Several statistical methods have been proposed to detect adverse drug reactions induced by taking two drugs together. These suspected adverse drug reactions can be discovered through post-market drug safety surveillance, which mainly relies on spontaneous reporting system database. Most previous studies have applied statistical models to real world data, but it is not clear which method outperforms the others. We aimed to assess the performance of various detection methods by implementing simulations under various conditions. We reviewed proposed approaches to detect signals indicating drug-drug interactions (DDIs) including the Ω shrinkage measure, the chi-square statistic, the proportional reporting ratio, the concomitant signal score, the additive model and the multiplicative model. Under various scenarios, we conducted a simulation study to examine the performances of the methods. We also applied the methods to Korea Adverse Event Reporting System (KAERS) data. Of the six methods considered in the simulation study, the Ω shrinkage measure and the chi-square statistic with threshold = 2 had higher sensitivity for detecting the true signals than the other methods in most scenarios while controlling the false positive rate below 0.05. When applied to the KAERS data, the two methods detected one known DDI for QT prolongation and one unknown (suspected) DDI for hyperkalemia. The performance of various signal detection methods for DDI may vary. It is recommended to use several methods together, rather than just one, to make a reasonable decision.

A fuzzy approach for selection of best available techniques

Sustainable development is the most important challenge in recent years, and it is extremely important to save the environment, safety and well-being of lives now and future generations. In this regard, the role of environmental regulation methods aiming at the use of innovation-based green technologies is increasing. The modern regulation principles incentivize the implementation of best available techniques. Evaluating best available techniques is a difficult problem and requires taking into account numerous criteria. The application of optimization models offers an objectively based basis for reasonable decisions making. Hence, the design of new effective methods for determination of the best available techniques is an actual research direction. The problem of BAT estimation includes a variety of parameters whose values cannot be defined exactly, which defines their representation in terms of the theory of fuzzy sets. The present paper is devoted to the use of the fuzzy-based methods for the best available techniques selection process. The proposed methods are an extension of the information-mathematical toolbox for the solution of the selection problem of the best available techniques.

Real-time prediction of wave-induced hull girder loads for a large container ship based on the recurrent neural network model and error correction strategy

Real-time acquisition of wave-induced hull girder loads of a sailing ship will help the captain make reasonable decisions, which is of great significance for improving the safety of the ship's navigation. This paper investigates the real-time prediction method of hull girder loads based on the Recurrent Neural Network (RNN) model and error correction strategy. Firstly, taking the vertical bending moment, horizontal bending moment, and torsional moment at the mid-ship position of a large container ship as examples, corresponding neural network prediction models are established through parameter influence analysis. Secondly, various sea state conditions are used to verify the feasibility of established network prediction models to predict the hull girder loads in real-time. The VBM prediction model performs better than the TM prediction model and HBM prediction model, and the errors of the TM prediction model and HBM prediction model are slightly larger in some cases. Lastly, an improved prediction model based on an error correction strategy is proposed to improve the prediction accuracy of the neural network prediction model, and the adequate performance of the error correction strategy is discussed.

Development of an express risk assessment in tender participation for contracting construction organizations in civil and agro-industrial construction

Participation in a tender is an integral part of the activities of contracting construction organizations. The difficulty lies in the fact that contractors have to make a decision on participation or non-participation in the tender quite quickly from the moment the customer posts information about the procurement. Incorrect decisions made by the contractor at this stage lead to lost profits, financial losses, ineffectiveness, loss of reputation and other unpleasant consequences. To level out this situation, the paper describes existing approaches to assessing the risks of participation in tender activities, which can protect the contractor from participating in unwanted procurement. In order to assess the feasibility of participating in a procurement, the authors propose the development of an algorithm for express risk assessment of a contractor's participation in a tender, which suggests, under limited time, to make a reasonable decision on the need to participate in a particular tender. This requires a qualitative and quantitative assessment of the contractor’s main risks, which are combined into two main groups: the risk of loosing the tender and the risk of future losses. The authors propose methods for assessing risks and classifying them as high, medium and low levels. The paper provides an example of practical testing of the proposed express assessment.

Visual Explanation for Open-Domain Question Answering With BERT.

Open-domain question answering (OpenQA) is an essential but challenging task in natural language processing that aims to answer questions in natural language formats on the basis of large-scale unstructured passages. Recent research has taken the performance of benchmark datasets to new heights, especially when these datasets are combined with techniques for machine reading comprehension based on Transformer models. However, as identified through our ongoing collaboration with domain experts and our review of literature, three key challenges limit their further improvement: (i) complex data with multiple long texts, (ii) complex model architecture with multiple modules, and (iii) semantically complex decision process. In this paper, we present VEQA, a visual analytics system that helps experts understand the decision reasons of OpenQA and provides insights into model improvement. The system summarizes the data flow within and between modules in the OpenQA model as the decision process takes place at the summary, instance and candidate levels. Specifically, it guides users through a summary visualization of dataset and module response to explore individual instances with a ranking visualization that incorporates context. Furthermore, VEQA supports fine-grained exploration of the decision flow within a single module through a comparative tree visualization. We demonstrate the effectiveness of VEQA in promoting interpretability and providing insights into model enhancement through a case study and expert evaluation.

Joint optimization of two-dimensional warranty period and maintenance strategy considering availability and cost constraints

Abstract Warranty can improve customer satisfaction and increase product sales, but it will bring additional economic burden to manufacturers, so making reasonable warranty decisions is particularly important. The current research focuses more on the interests of manufacturers, while there is less attention paid to indicators that consumers are concerned about, such as system availability. To solve this problem, a joint optimization model of the two-dimensional warranty period and preventive maintenance (PM) strategy considering availability and cost constraints was established. Based on the failure dependence analysis of multi-component systems, the actual failure rate function is constructed by using the failure dependence coefficient matrix. Based on the comprehensive consideration of imperfect PM and minimum maintenance, the two-dimensional warranty cost model and system availability model are established, respectively. Aiming at maximum availability and considering the warranty cost budget constraint, a joint optimization model of the two-dimensional warranty period and PM strategy was built, and a model-solving algorithm combining grid search and binary search was introduced. The effectiveness of the model is verified by the case analysis, and the necessity of the PM strategy and considering failure dependence are reflected in the model comparative analysis and parameter sensitivity analysis. Finally, reasonable suggestions are put forward for manufacturers’ warranty decisions through the result analysis.

АЛГОРИТМ УПРАВЛЕНИЯ ЭКОНОМИЧЕСКОЙ БЕЗОПАСНОСТЬЮ ПРЕДПРИЯТИЙ ТАБАЧНОЙ ПРОМЫШЛЕННОСТИ В КОНТЕКСТЕ НАЦИОНАЛЬНЫХ УГРОЗ И ВНУТРИСТРАНОВЫХ РИСКОВ

In the presented scientific article, the author analyzes the main trends in the de-velopment of the tobacco industry of the Russian Federation and key players in the tobacco market. A trend analysis of the production and sale of tobacco products, as well as restrictive measures of state policy aimed at reducing the consumption of tobacco products in accordance with current legislation, was carried out. The information on the size of the shadow tobacco market is pre-sented and it is concluded that the growth in sales of illegal types of tobacco products represents one of the threats to economic security for tobacco industry enterprises. Focusing on modern national threats, the author's vision of the es-sence of the algorithm for ensuring the economic security of the tobacco industry was presented and the main stages were presented, with a concretization of the list of actions. When conducting a set of analytical procedures, primary infor-mation from the monitoring system of threats to the economic security of tobacco industry enterprises is used, which makes it possible to identify and analyze not only internal threats related to the financial condition of the enterprise, opera-tional risks, managerial efficiency and other factors, but also external threats, the occurrence of which is caused by the situation on the international the arena and the national economy. Regular monitoring of these threats helps to prevent fi-nancial losses, reputational damage and other negative consequences. promptly respond to stressful situations, develop strategies to prevent threats and make reasonable decisions for successful business development.

An Empirical Study of Shanghai Composite Index Forecasts and Trend Trading Strategies Based on ARIMA Model

ARIMA model is often used to forecast time series, and stock price prediction has always been a concern of investors. Accurate stock price prediction helps to make reasonable decisions in the unpredictable financial market. By modeling historical data, this paper uses ARIMA model to fit the change law of time series data, and then predict future stock changes. This paper selects the closing price data of Shanghai Composite Index on all trading days from August 19, 2019, to August 18, 2023, conducts stationarity test on it, completes the identification and sequencing of ARIMA model, conducts model test, analyzes and forecasts stock prices based on this model. The results show that the ARIMA model has a good forecasting effect on the short-term change rule of stock price time series, and has a certain reference significance for investors to make stock investment. The results show that the selected test data fits the ARIMA model well.

Акустическая картина запуска винтовых компрессоров как диагностический параметр технического состояния

The emergence of new opportunities for fixing and analyzing noise allows us to perform visualization and analysis of sound vibrations as diagnostic signs of the serviceability of the compression unit during the start-up period, the most informative stage of the manifestation of incipient damage. The use of screw compressors, at present, is the most rational due to the absence of shock processes, the possibility of long-term operation with a minimum amount of maintenance operations, the effective solution of issues of managing work schedules, minimal dynamic loads at startup, etc. Screw compressors with a frequency of rotation of the drive motor 3000 rpm and a power of 100…300 kW have found the greatest distribution. Ensuring long-term op-eration of screw compressors requires reasonable decision-making to restore operational capability on the basis of data on the actual condition of individual elements of the mechanism. The research methods are presented in the form of a practical analysis of the noise level and vibration acceleration of screw compressors. Acoustic and vibration parameters of the unit start-up were obtained, information frequencies of damage to the main nodes were presented, as well as a time-frequency spectrogram of the start-up. The results of the conducted acoustic studies of the start-up of the compressor unit consisting of Sabroe screw compressors SAB — 163 and SAB — 330 constitute the main content of this work, which allow us to conclude that it is necessary to implement three-level diagnostics of rotary mechanisms to prevent sudden failures of the compression unit.

Development of an explainable artificial intelligence model for Asian vascular wound images.

Chronic wounds contribute to significant healthcare and economic burden worldwide. Wound assessment remains challenging given its complex and dynamic nature. The use of artificial intelligence (AI) and machine learning methods in wound analysis is promising. Explainable modelling can help its integration and acceptance in healthcare systems. We aim to develop an explainable AI model for analysing vascular wound images among an Asian population. Two thousand nine hundred and fifty-seven wound images from a vascular wound image registry from a tertiary institution in Singapore were utilized. The dataset was split into training, validation and test sets. Wound images were classified into four types (neuroischaemic ulcer [NIU], surgical site infections [SSI], venous leg ulcers [VLU], pressure ulcer [PU]), measured with automatic estimation of width, length and depth and segmented into 18 wound and peri-wound features. Data pre-processing was performed using oversampling and augmentation techniques. Convolutional and deep learning models were utilized for model development. The model was evaluated with accuracy, F1 score and receiver operating characteristic (ROC) curves. Explainability methods were used to interpret AI decision reasoning. A web browser application was developed to demonstrate results of the wound AI model with explainability. After development, the model was tested on additional 15 476 unlabelled images to evaluate effectiveness. After the development on the training and validation dataset, the model performance on unseen labelled images in the test set achieved an AUROC of 0.99 for wound classification with mean accuracy of 95.9%. For wound measurements, the model achieved AUROC of 0.97 with mean accuracy of 85.0% for depth classification, and AUROC of 0.92 with mean accuracy of 87.1% for width and length determination. For wound segmentation, an AUROC of 0.95 and mean accuracy of 87.8% was achieved. Testing on unlabelled images, the model confidence score for wound classification was 82.8% with an explainability score of 60.6%. Confidence score was 87.6% for depth classification with 68.0% explainability score, while width and length measurement obtained 93.0% accuracy score with 76.6% explainability. Confidence score for wound segmentation was 83.9%, while explainability was 72.1%. Using explainable AI models, we have developed an algorithm and application for analysis of vascular wound images from an Asian population with accuracy and explainability. With further development, it can be utilized as a clinical decision support system and integrated into existing healthcare electronic systems.

Activities efficiency assessment of the governing body’s task force under environmental emergency

Purpose. To work out the method for activities efficiency assessment of the governing body’s task force under environmental emergency. In order to achieve this goal, it is proposed to apply an integrated approach that allows increasing the effectiveness of its work. Methodology. The method for activities efficiency assessment of the governing body’s task force under environmental emergency was applied which allowed determining the degree of its capabilities realization. To study this process, a systematic approach was used, according to which the governing body is considered as a complex system that has a hierarchical structure and is a set of functionally interconnected structural units, united in their activities by the shared goal, concept and action plan. Findings. As the task force’s activity basis, a reasonable decision was determined of the governing body’s head, at the development and implementation of which the task force’s work is aimed. The task force’s efforts coordination is carried out in accordance with the tasks, directions, areas, time and methods of tasks performing that are assigned to the subdivisions of the governing body. As the main factor in activities efficiency assessment, the training level of the governing body’s task force was determined, that stipulates its professional and personal features. Originality. The proposed method for activities efficiency assessment of the governing body’s task force is estimated using an integral index – the degree of its capabilities realization to perform tasks. In the mentioned method, the criterion for activities efficiency of the governing body’s task force is determined as a condition under which the quotient from division of the total capabilities realized by the governing body’s task force indicator by the indicator of its total potential capabilities is in the range 0.8–1. A diagram of the method for assessing the task force’s activities efficiency was elaborated, containing interrelated blocks (activities), direct connections and feedback, which generally characterizes the sequence and actions content of the governing body’s head when implementing the mentioned method. Practical value. An example of estimating the activities efficiency of the governing body’s task force to achieve the goal in terms of an integral index – the degree of its capabilities realization to perform tasks, which is calculated using the proposed method, was considered. The initial data for calculation were the main tasks performed by the environmental emergency response headquarters’ task force, standard time indicators and prescribed time for tasks performance designated by the governing body’s head. On this basis, an analysis of the headquarters’ actions on eliminating the emergency consequences connected with the blowing up of the Kakhovska HPP was carried out, its main tasks and features of the decision-making process in uncertain conditions were established. The directions of increasing activities efficiency of the governing body’s task force were elaborated, in particular by increasing their professional competence, implementing innovative approaches to the transformation of governing styles, rational tasks distribution.