Principles Of Decision Research Articles

Dilemmas of Powerlessness: The Ethical Dimensions of Political Action in the Swedish Parliament

Abstract What are the most challenging ethical dilemmas for politicians, and how do they handle them? The classical literature on ethical dilemmas in politics has mainly explored them as conflicts between ethical principles in high-stakes decisions. However, empirical evidence of the extent to which such dilemmas accurately reflect the experience of most politicians is scarce. Drawing on extensive in-depth interviews with Swedish parliamentarians, I show that their dilemmas stem mainly from powerlessness. Powerlessness in politics manifests itself in primarily two ways: relational powerlessness, which is driven by constraints like party and constituency loyalties, and inherent powerlessness due to formal and informal barriers like constitutional mandates and limited time and resources. This study contributes to the field of political ethics by anchoring political dilemmas in everyday democratic politics and by introducing powerlessness as a new central concept. In doing so, it supplements our understanding of ethical dilemmas in politics with insights from those confronting them.

Construction and SHAP interpretability analysis of a risk prediction model for feeding intolerance in preterm newborns based on machine learning

ObjectiveTo construct a highly accurate and interpretable feeding intolerance (FI) risk prediction model for preterm newborns based on machine learning (ML) to assist medical staff in clinical diagnosis.MethodsIn this study, a sample of 350 hospitalized preterm newborns were retrospectively analysed. First, dual feature selection was conducted to identify important feature variables for model construction. Second, ML models were constructed based on the logistic regression (LR), decision tree (DT), support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms, after which random sampling and tenfold cross-validation were separately used to evaluate and compare these models and identify the optimal model. Finally, we apply the SHapley Additive exPlanation (SHAP) interpretable framework to analyse the decision-making principles of the optimal model and expound upon the important factors affecting FI in preterm newborns and their modes of action.ResultsThe accuracy of XGBoost was 87.62%, and the area under the curve (AUC) was 92.2%. After the application of tenfold cross-validation, the accuracy was 83.43%, and the AUC was 89.45%, which was significantly better than those of the other models. Analysis of the XGBoost model with the SHAP interpretable framework showed that a history of resuscitation, use of probiotics, milk opening time, interval between two stools and gestational age were the main factors affecting the occurrence of FI in preterm newborns, yielding importance scores of 0.632, 0.407, 0.313, 0.313, and 0.258, respectively. A history of resuscitation, first milk opening time ≥ 24 h and interval between stools ≥ 3 days were risk factors for FI, while the use of probiotics and gestational age ≥ 34 weeks were protective factors against FI in preterm newborns.ConclusionsIn practice, we should improve perinatal care and obstetrics with the aim of reducing the occurrence of hypoxia and preterm delivery. When feeding, early milk opening, the use of probiotics, the stimulation of defecation and other measures should be implemented with the aim of reducing the occurrence of FI.

Application of deep learning algorithms for identifying deterioration in the ushnisha (Head Bun) of the Leshan Giant Buddha

The Leshan Giant Buddha’s ushnisha (Head Bun) has suffered from loss of lime plaster, cracks, and biological damage, compromising its structural integrity and reducing the effectiveness of the drainage system in the Buddha's head. The infiltration of moisture has led to water damage within the statue, significantly accelerating its weathering. This situation urgently requires protection and reinforcement measures. Detecting deterioration in the ushnisha is a crucial step in the preservation process. In this study, we utilized two deep learning models for pixel-level semantic segmentation of the damage. Due to the small size of the cracks, a weighted loss function was applied to improve both the training speed of the model and the efficiency of crack identification. This weighting strategy proved effective for both models. The weighted K-Net model achieved a mean accuracy (mAcc) of 90.23% and a mean intersection-over-union (mIoU) of 69.55%, with a damage segmentation speed of 7 images per second, which is 1309 times faster than manual segmentation. By applying the trained deep learning models to re-examine the ushnisha, we successfully identified damage that had been overlooked during manual annotation. Using the model’s enhanced results, we conducted a comprehensive quantification of the damage across all ushnisha and identified the most severely affected areas. Additionally, we performed a model interpretability analysis to explain the decision-making process and principles of the deep learning models. This research provides significant practical value for detecting and quantifying damage in the Leshan Giant Buddha.

Fostering Shared Decision-Making Between Patients and Health Care Professionals in Clinical Practice Guidelines: Protocol for a Project to Develop and Test a Tool for Guideline Developers.

Clinical practice guidelines (CPGs) are designed to assist health care professionals in medical decision-making, but they often lack effective integration of shared decision-making (SDM) principles to reflect patient values and preferences, particularly in the context of preference-sensitive CPG recommendations. To address this shortcoming and foster SDM through CPGs, the integration of patient decision aids (PDAs) into CPGs has been proposed as an important strategy. However, methods for systematically identifying and prioritizing CPG recommendations relevant to SDM and related decision support tools are currently lacking. The aim of the project is to develop (1) a tool for systematically identifying and prioritizing CPG recommendations for which SDM is considered particularly relevant and (2) a platform for PDAs to support practical SDM implementation. The project consists of 6 work packages (WPs). It is embedded in the German health care context but has an international focus. In WP 1, we will conduct a scoping review in bibliographic databases and gray literature sources to identify methods used to foster SDM via PDAs in the context of CPGs. In WP 2, we will conduct semistructured interviews with CPG experts to better understand the concepts of preference sensitivity and identify strategies for fostering SDM through CPGs. WP 3, a modified Delphi study including surveys and focus groups with SDM experts, aims to define and operationalize preference sensitivity. Based on the results of the Delphi study, we will develop a methodology for prioritizing key questions in CPGs. In WP 4, the tool will be developed. A list of relevant items to identify CPG recommendations for which SDM is most relevant will be created, tested, and iteratively refined, accompanied by the development of a user manual. In WP 5, a platform for creating and digitizing German-language PDAs will be developed to support the practical application of SDM during clinical encounters. WP 6 will conclude the project by testing the tool with newly developed and revised CPGs. The Brandenburg Medical School Ethics Committee approved the project (165122023-ANF). An international multidisciplinary advisory board is involved to guide the tool development on CPGs and SDM. Patient partners are involved throughout the project, considering the essential role of the patient perspective in SDM. As of February 20, 2024, we are currently assessing literature references to determine eligibility for inclusion in the scoping review (WP 1). We expect the project to be completed by December 31, 2026. The tool will enable CPG developers to systematically incorporate aspects of SDM into CPG development, thereby providing guideline-based support for the patient-practitioner interaction. Together, the tool for CPGs and the platform for PDAs will create a systematic link between CPGs, SDM, and PDAs, which may facilitate SDM in clinical practice. DERR1-10.2196/57611.

Environmental analysis in UK modern methods of construction (MMC) housing: insights from early-stage architectural design process

PurposeModern Methods of Construction (MMC) have been promoted as a solution to address housing shortages and meet sustainability goals in the UK. However, the practical functioning of MMC, particularly in relation to early-stage environmental analyses, remains underexplored. This study aims to fill this gap by providing empirical insights into how architects engage in environmental analysis in early-stage MMC housing designs.Design/methodology/approachThis qualitative pilot study is based on a detailed case study of a UK architectural firm specializing in modular housing. Semi-structured interviews were conducted with eight architects with varying MMC experience. Thematic analysis of the qualitative data allowed for the exploration of key themes influencing early-stage environmental analysis, offering a narrative account of architects’ experiences in MMC practices.FindingsThe study reveals that environmental analysis in MMC is shaped by social, organisational and project-based factors. Three key themes emerged: uncertainty in environmental assumptions, dependencies on external consultants and the dominance of Passivhaus principles in design decisions. These factors challenge the integration of environmental considerations during the early design stages of MMC projects.Research limitations/implicationsAs this is a single case study, the findings might not be generalizable. Future research should expand on multiple firms and project settings to validate and broaden these findings.Originality/valueThis study provides an in-depth understanding of the challenges architects face when integrating environmental analysis into MMC. This reveals the relational and interdependent nature of environmental analysis in MMC projects, where decisions are shaped by multiple social, organisational and project-specific factors. By emphasizing these interdependencies, this study provides original insights into how environmental considerations can be integrated more effectively into the early design stages of MMC projects.

Needs and opportunities for developing health and well-being profiles in Estonian local governments

Abstract The creation and implementation of health and wellbeing profile, an evidence-based framework for planning health promotion as holistic process, is the responsibility of public health practitioners, who tend work part-time and sometimes lack professional competences. The current study maps the level of awareness, attitudes, needs and possibilities of local government leaders and public health practitioners to develop and implement profiles effectively in Estonian local governments. Semi-structured interviews with leaders in local governments (10) and practitioners (9) were conducted in 2022-2023. Data was analysed using qualitative content analysis. Sample included representatives from all Estonian local governments (79 in total) and were categorized into subgroups based on local governments size, status of the profile, public health specialist employment, and educational background. Preliminary results indicate that leaders find as a supportive factors for enabling and encouraging profile compilation process for example: mandatory requirement; motivated implementors; well organized and effective workplan. Specialists find supportive factors to be cooperation on the national level, good communication practices and joint responsibility. Barriers for health promoters are the lack of time, motivation, financial resources, stakeholders understanding and meaningful action. The first qualitative study on these topics in Estonia highlight that creating a profile is supported by previous positive experience and have per contra an opposite negative effect to start the process. In general, the profile was considered necessary for helping identify problems and support decision-making processes for managing resources, however, assessment whether the profile should be obligatory is needed. In addition, there is a need for further support for the evidence-based decision-making process on the local level in health promotion by offering education and guidance from the national level. Key messages • Knowledge about the importance of public health, barriers and decision-making principles of local government leaders and specialists helps to develop interventions based on actual needs. • Continuously updated health and well-being profile ensures sustainability of health promotion action and is useful knowledge to policymakers, local government leaders and public health practitioners.

On the decision-making framework for policing: A proposal for improving police decision-making

This article introduces the Decision-Making Framework for Policing (DMFP), a comprehensive tool designed to enhance the decision-making understanding of police officers. The DMFP considers the principles of heuristic, naturalistic, and rational decision-making along a fluid cognitive continuum to create a framework that addresses the limitations of the existing police National Decision Model (NDM). It achieves this by including 10 proposed typologies of police decision-making including: Routine, Tactical, Operational, Crisis, Investigative, Ethical, Interpersonal, Administrative, Managerial, and Strategic. These are integrated alongside existing and adapted decision-making models which are presented using a mnemonic letter strategy. Although the DMFP is theoretical, and its utility is presently untested in comparison to the existing NDM, it is presented to provide a tool to help improve officers' tacit knowledge, pattern recognition, and experiential learning through provision of easily recallable mnemonic decision-models. Thereby fostering a deeper understanding of cognitive processes and the factors influencing police decisions, potentially increasing consistency in reasoning, reducing decision errors, and enhancing policing outcomes.

Navigating parental disagreement: ethical analysis and a proposed approach.

Shared decision-making in pediatrics can be problematic when disagreements arise. The impermissible-permissible-obligatory (I-P-O) framework helps define the limits of parental authority when clinicians disagree with parents. There is little guidance in the literature, however, on making critical clinical decisions when parents disagree with each other. We use a clinical case involving parental disagreement over resuscitation at borderline gestational age to provide context for an analysis of several potential approaches based on established ethical principles of pediatric decision-making. We identify four potential options for delivery room care: (1) Defer to the pregnant parent; (2) withhold resuscitation unless both parents agree to it; (3) attempt resuscitation if either parent requests it; (4) decide about resuscitation using a framework of advisability. The merits and flaws of each approach are discussed. We propose an expansion of the I-P-O framework that uses consideration of clinical details, an assessment of the patient's best interest, and parental values to determine clinical advisability to guide decision-making in the setting of parental discordance.

Опыт внедрения информационной системы с технологиями искусственного интеллекта в работу поликлиники для оптимизации организации периодических медицинских осмотров.

Organizing medical examinations for patients with minimal time losses is the most difficult task for an outpatient clinic when creating a New model of a medical organization providing primary health care. Since during medical examinations it is necessary to perform a whole range of works associated with certain sets of actions, the authors developed an information system with technologies of artificial intelligence, which was tested during periodic medical examinations. The purpose of the study is to develop and test an information system with technologies of artificial intelligence that allows balancing the capabilities of a medical organization and the needs of the patient when undergoing periodic medical examinations. Materials and methods. The tool for solving this problem was an artificial intelligence platform based on the principle of decision making by controlling the positions of attractors in the state space of the Hopfield neural network, which was built into the medical information system using HL7 FHIR. Results. The result of the work was the “Smart Clinic” project, which provides for the creation of an information system with technologies of artificial intelligence for routing patients during periodic medical examinations. The information system provided dynamic routing of patients in real time with the construction of the shortest trajectory and minimal movement across the floors of the building, based on current information about the workload of specialists and the duration of each stage of the examination. Conclusions. The use of an artificial intelligence information system in the outpatient clinic made it possible to reduce the average duration of a patient’s trajectory during a periodic medical examination by 45%, the average waiting time for an appointment – from 7 minutes to 3 minutes, and the total time for undergoing a preventive examination – from 200 to 150 minutes. This made it possible to increase the number of periodic medical examinations per year by 1.5 times, and the level of patient satisfaction reached 95%.

How High-Performing Personal Support Workers Set and Maintain Boundaries When Providing Care: A Case Study in Ontario, Canada.

Personal support workers (PSWs) provide a large proportion of in-home care services for Canadians. PSWs must negotiate with clients and their family on how prescribed care is delivered. How PSWs set and maintain professional and personal boundaries during care is poorly understood, and failure to manage boundaries can expose both PSWs and clients to risk. High-performing PSWs (n = 9) and supervisors (n = 4) within an Ontario, Canada, home care agency were engaged in workshops (n = 3) to identify field-tested strategies and tactics for identifying, managing, and supporting PSW boundaries. A boundary-management framework was generated, including types of boundary challenges; decision-making principles (e.g., consider the purpose of home care); response strategies (e.g., work with the client on an alternative solution); and tactics for action (e.g., use proactive reminders). Supervisory and organizational supports (e.g., enabling "shop-talk") were identified. The framework can inform teaching and practice materials for PSWs in Canada and other countries.

Implementing strong sustainability in a design process

The emergence of a post-growth era is expected that implies rethinking the production and consumption patterns with novel design models this forces higher educational institutions to reconsider their traditional ways of teaching sustainability in their curricula. Companies also need to overcome strategies that compartmentalize environment, society and economy in their industrial strategy in order to evolve in their support for the transition. The aim of this paper is to present a design process anchored in the Strong Sustainability paradigm to overcome the gap of how Strong Sustainability could be operationalised. Design Research Methodology (DRM) has been chosen as the supporting framework for the development of this project. The Design for Strong Sustainability (DfSoSy) methodology proposed, is built on three aspects of Strong Sustainability (Milieu, Regeneration, Safe and just operating space) successively applied in a sequenced iterative design process. The latter enable the integration of thought patterns associated with integrative, systemic and fractal or multi-scale thinking respectively. Moreover, the principle of sub-optimality is highlighted as a decision principle in SoSy. Results obtain has been validated as well on the pedagogical objectives as in the usefulness of the DfSoSy. The practical contribution of this study is the DfSoSy toolkit©.

Pengaruh Literasi Keuangan Syariah, Religiusitas, Inklusi Keuangan Syariah, Layanan Digital M-Banking Terhadap Keputusan Menabung Gen Z. Studi Kasus Nasabah BSI Jabodetabek

Islamic finance is a financial system based on the principles of Islamic sharia, which prohibits usury (interest), speculation, and investment in businesses that are considered haram. This financial system offers various products and services, such as savings, investment and financing, which are in accordance with sharia principles. In Indonesia, sharia financial institutions have developed rapidly and have become a choice for people who want to use financial services in accordance with sharia principles. Generation Z, which is a group born between the mid-1990s to the early 2010s, is known for its high technological skills and strong sharia financial values, resulting in an understanding of sharia finance and the application of these principles in financial decision making, including Saving money is important. This study aims to identify the influence of sharia financial literacy, religiosity, sharia financial inclusion, and digital m-banking services on Generation Z's saving decisions, with a focus on Bank Syariah Indonesia (BSI) customers in the Jabodetabek area. This type of research uses a quantitative approach with a sample of 135 respondents. The data analysis used is SEM-PLS assisted by the smartPLS 3 application. The results of this research show that Sharia Financial Literacy, Sharia Financial Inclusion and Religiosity have a positive and significant influence on Gen Z's Saving Decision, while the Digital Banking Services variable has no significant influence on Saving Decisions. Gen Z. This is due to several factors, including low literacy levels and internet network problems or being far from the city center.

PRINCIPLES OF SOCIAL MANAGEMENT AS A FACTOR IN MINIMIZING POLITICAL RISKS IN DECISION MAKING

The study draws conclusions from the analysis of the political risks of state power at the present stage of Russia’s development. The socio-political principles of management are analyzed, which are connected and interact with a group of organizational and technological mechanisms of political decision-making, which are integral elements of their common system of public administration. Organizational and technological mechanisms reflect the patterns of social management that are associated with the implementation of its organizational and technical functions and the minimization of political risks. They play an important role in creating the basis for the formation of managerial relations, determining essentially the distribution of power, the degree of centralization of the power of managers and the degree of real independence of the governed. Violation of these principles leads to political risks: unjustified fragmentation of the functions of management bodies, violation of the balance of rights and responsibilities of managers, increased demands on the managed and the unreasonableness of decisions. The peculiarities of personnel policy after the presidential elections of Russia are revealed. Proposals are made on mechanisms of social management based on the principles of social justice, as well as the use of existing potential based on the principles of decision-making and its justification in the context of political risks. The connection between the general picture of the world existing in culture and the way of attitude to the category of power in the public consciousness is substantiated.

Tumor board simulation improves interdisciplinary decision-making in medical students

IntroductionTraining of interdisciplinary clinical reasoning and decision-making skills, essential in daily clinical practice in oncological specialties, are still underrepresented in medical education. Therefore, at LMU University Hospital Munich, we implemented a didactically modified tumor board simulation with experts from five different disciplines (medical oncology, pathology, radiation oncology, radiology, and surgery) presenting patient cases into a one-week course on the basic principles of oncology. In this survey, we examined the self-assessed impact of our course on the interdisciplinary decision-making skills of medical students.MethodsBetween November-December 2023 and January-February 2024, we surveyed two cohorts of medical students in the third year of medical school in our one-week course before and after participating in the tumor board simulation. The objective was to evaluate the self-assessed knowledge in interdisciplinary clinical decision-making, in integrating ethical considerations into clinical reasoning, and in comprehension of various professional viewpoints in interdisciplinary decision-making. Knowledge was assessed using a five-step Likert scale from 1 (no knowledge) to 5 (complete knowledge).ResultsThe survey was answered by 76 students before and 55 after the simulation, equaling 60–70% of all 100 course participants. Mean knowledge level regarding principles of interdisciplinary clinical decision-making improved significantly in all of the following exemplary aspects: purpose and procedure of tumor boards in clinical practice (from 2.4 ± 1.1 to 4.0 ± 1.0, Spearman’s ρ = 0.6, p < 0.001), principles of dealing with ethical challenges in oncology (from 2.4 ± 1.1 to 3.4 ± 1.0, ρ = 0.4, p < 0.001), and principles of shared decision-making in oncology (2.7 ± 1.1 to 3.7 ± 1.0, ρ = 0.4, p < 0.001). Students reported that their skills in clinical decision-making and ability to discuss oncological patient cases from different professional viewpoints improved due to the teaching course.ConclusionBy employing our interdisciplinary one-week course and a didactically modified tumor board simulation featuring experts from various oncological disciplines, medical students’ comprehension of interdisciplinary clinical decision-making in oncology improved significantly.

Application of Sensitivity Analysis for Multiple Attribute Decision Making in Lean Production System

Lean production is a dynamic process that is governed by a set of decision-making principles. The concept of MCDM has been widely used in lean production systems. In this paper, the methodology and approach of MADM, particularly focusing on Multi-Attribute Decision Making, encompass several key steps and considerations. To assess the degree of lean manufacturing implementation, a questionnaire was developed based on scholarly literature. The questionnaire consisted of 52 questions that assessed the implementation of four strategies: JIT, TPM, 5S Kaizen, and VSM. The study employed a three-stage elimination strategy, consisting of an elimination search and a TOPSIS-based ranking of lesions. Total Productivity Management was found to be the most effective and widely adopted approach among the 18 companies surveyed. TPM was the most widely adopted and effective waste reduction technique among the companies. The MADM ideology has significant future potential in various domains, including healthcare, supply chain management, energy and environmental management, financial sector, e-commerce, and marketing. This study provides insight into the practical application of waste reduction techniques by various industries and their potential benefits for a nascent company seeking to adopt such practices. These objectives aim to advance understanding, methodologies, and applications of MADM, particularly within lean production systems, while addressing challenges and leveraging advancements in technology for improved decision-making and performance optimization.

Multi-modal incomplete label information three-way bidirectional decision-making: Applications of disease assessment

Disease assessment involves two stages of decision-making process. The first process is to infer the development trend of the disease through the existing judgment conditions, which is to make a positive estimation (prediction) decision. The second process is to update the judgment conditions for different disease states and optimize the clinical assessment evidence by fusing disease progression data, that is, to make a reverse evaluation (optimization) decision by reviewing historical diagnostic and treatment data to summarize the best judgment conditions for the disease characteristics. Therefore, we construct a three-way bidirectional decision method for multi-modal incomplete labeling information, considering the mixed data features with no labels and labels, and the bidirectional decision features of positive prediction and reverse optimization. Specifically, the method first introduces semi-supervised learning (SSL) into the rough sets, constructs a rough sets model based on cosine similarity relation, generates pseudo-labels for incomplete information, and explains the positive prediction decision process principle. Second, the gradient space is constructed on the predictive information system by the three-way decision-making principle, the loss function formed by the combination of KL divergence and cross entropy loss function is used to find the direction of the fastest decline in attribute information value, and the optimal decision rule and the automatic updating strategy of the threshold value are obtained. At the same time, the principle of the reverse optimization decision process is explained. Finally, multimodal information from pathological tissue images is used to evaluate clinical progress problem. A pathological tissue images dataset includes 2000 colorectal cancer and 300 kidney disease cases used for simulation experiments. The proposed three-way bidirectional decision-making model can be widely applied to actual decision-making scenarios for evaluating clinical progress of different diseases. Compared with previous studies, this method can realize objective calculation and automatic update of threshold and loss values and effectively solve complex prediction and optimization decision-making problems.

Chest wall resections for non-small cell lung cancer: a literature review.

The development of early screening for lung cancer has led to improved overall survival in patients with non-small cell lung cancer (NSCLC). However, the management of NSCLC patients with resectable and potentially resectable chest wall invasion (CWI) requires attention. The purpose of this review is to summarize the role of surgery (chest wall resections) in NSCLC patients with CWI. A literature search and review from three databases (PubMed, Embase, and ScienceDirect) comprised the last 39 years. This review was focused on the treatment of NSCLC patients with CWI, mainly including the preoperative evaluation, principles of treatment and strategic decision-making, surgical complications, and prognostic factors. Through the collection of relevant literature on NSCLC that invades the chest wall, this narrative review describes the actual role in clinical practice and future developments of chest wall resections. Preoperative treatment requires the multidisciplinary team (MDT) team to conduct accurate clinical staging of the patient and pay attention to the patient's lymph node status and rib invasion status. The successful implementation of chest wall resection and possible chest wall reconstruction requires refined individualized treatment based on the patient's clinical characteristics, supplemented by possible postoperative systemic treatment. Surgery plays an important role in treating NSCLC patients with CWI, and a collaborative, experienced MDT is an essential component of the successful treatment of CWI with lung cancer. In the future, more high-quality clinical research is needed to focus on CWI patients so that patients can receive more effective treatment options and better clinical prognosis.

Effect of decision-making principle on P2G–CCS–CHP complementary energy system based on IGDT considering energy uncertainty

As one of the most promising large-scale de-fossilization technologies currently available, Power-to-Gas (P2G) is expected to promote utilization of renewable sources and mitigate the effects of greenhouse gas. Through the coupling of P2G, Combined Heat and Power (CHP) as well as Carbon Capture and Storage (CCS), the P2G–CCS–CHP microgrid energy system could achieve hierarchical energy transfer and green-powered interconversion of gas, electricity and heat flows. However, the conversion of multiple energy shapes between different facilities is deeply intertwined with renewable energy sources, greatly increasing risk of unbalance operation and impacting the overall robustness and economic viability of system. To address these challenges, this study proposes a decision-making framework based on Information Gap Decision Theory (IGDT) method for a P2G–CCS–CHP system. The real-time balancing of heat & power loads and supply, the mechanism of gas-electricity-heat interaction, as well as recycling pattern of synthetic fuel within the system are carefully addressed to achieve optimal operation. Different scheduling schemes are obtained by setting up two separating decision principles, namely risk-seeking (RS) and risk-avoiding (RA), to solve these uncertainties and ensure robust decision making. Meanwhile, adaptability of decision-making methodology is analyzed based on several criteria including share of recycled green-powered fuel, ecological friendliness, carbon trading benefit, etc. Results show that adding of P2G module enables a 12.6% reduction in carbon emissions and generates 1252.2 kg of green powered gas, highlighting the eco-friendly nature of the multi energy system (MES). About 21.5% of the renewable energy flows participate the interconversion of electric-heat-gas and about 17.7% of total carbon flow is circulated as synthetic fuel within the system. In addition, conservative tendency is witnessed in the case of risk-seeking decision mode, leading to an approximate 13.22% increase in the operation costs, compared with risk-avoiding mode. The proposed IGDT decision strategy has shown significant compatibility in dealing with the impact of multiple uncertainties.

Adding the risk of stock collapse over time to stock assessments and harvest allocation decisions

Abstract Globally, many fisheries have experienced collapse even though most of these fisheries had management plans with harvest control rules and were supported by scientific modelling that explicitly accounted for uncertainty. Recognizing that an informed decision on risks of a stock collapse versus harvest is only possible when the outcomes of the technical measures are described explicitly. We propose that the cumulative probability of stock collapse over a range of harvest levels would provide a perspective of the future consequences of harvesting decisions. Adding to the harvest level negotiations the consideration of how long a fishery should sustain the livelihoods of fishers may provide managers, fishers, and other stakeholders with a more tangible understanding of the risks within the context of precautionary principles in decision-making. We use a time series from the Canadian Cod fishery of the Southern Gulf of St. Lawrence, from which we construct and calibrate a simplified model as an emulator of more comprehensive models to demonstrate the approach. The implications of adding an analysis of the probabilities of stock collapse for a range of harvest levels and using a risk matrix to inform decision-making are discussed for four selected years 1974, 1986, 1993, and 2017.

Ethical challenges in health care during collective hunger strikes in public or occupied spaces.

Public collective hunger strikes take place in complex social and political contexts, require medical attention and present ethical challenges to physicians. Empirical research, the ethical debate to date and existing guidelines by the World Medical Association focus almost exclusively on hunger strikes in detention. However, the public space differs substantially with regard to the conditions for the provision of health care and the diverse groups of healthcare providers or stakeholders involved. By reviewing empirical research on the experience of health professionals with public collective hunger strikes, we identified the following ethical challenges: (1) establishment of a trustful physician-striker relationship, (2) balancing of medico-ethical principles in medical decision-making, (3) handling of loyalty conflicts and (4) preservation of professional independence and the risk of political instrumentalization. Some of these challenges have already been described and discussed, yet not contextualized for public collective strikes, while others are novel. The presence of voluntary physicians may offer opportunities for a trustful relationship and, hence, for ethical treatment decisions. According to our findings, it requires more attention to how to realise autonomous medical decisions in the complex context of a dynamic, often unstructured and politically charged setting, which ethical norms should shape the professional role of voluntary physicians, and what is the influence of the hunger strikers'collective on individual healthcare decisions. Our article can serve as a starting point for further ethical discussion. It can also provide the basis for the development of potential guidelines to support health professionals involved in public collective hunger strikes.