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The digitization and automation of diagnostics and treatments promise to alter the quality of health care and improve patient outcomes, whereas the undersupply of medical personnel, high workload on medical professionals, and medical case complexity increase. Clinical decision support systems (CDSSs) have been proven to help medical professionals in their everyday work through their ability to process vast amounts of patient information. However, comprehensive adoption is partially disrupted by specific technological and personal characteristics. With the rise of artificial intelligence (AI), CDSSs have become an adaptive technology with human-like capabilities and are able to learn and change their characteristics over time. However, research has not reflected on the characteristics and factors essential for effective collaboration between human actors and AI-enabled CDSSs. Our study aims to summarize the factors influencing effective collaboration between medical professionals and AI-enabled CDSSs. These factors are essential for medical professionals, management, and technology designers to reflect on the adoption, implementation, and development of an AI-enabled CDSS. We conducted a literature review including 3 different meta-databases, screening over 1000 articles and including 101 articles for full-text assessment. Of the 101 articles, 7 (6.9%) met our inclusion criteria and were analyzed for our synthesis. We identified the technological characteristics and human factors that appear to have an essential effect on the collaboration of medical professionals and AI-enabled CDSSs in accordance with our research objective, namely, training data quality, performance, explainability, adaptability, medical expertise, technological expertise, personality, cognitive biases, and trust. Comparing our results with those from research on non-AI CDSSs, some characteristics and factors retain their importance, whereas others gain or lose relevance owing to the uniqueness of human-AI interactions. However, only a few (1/7, 14%) studies have mentioned the theoretical foundations and patient outcomes related to AI-enabled CDSSs. Our study provides a comprehensive overview of the relevant characteristics and factors that influence the interaction and collaboration between medical professionals and AI-enabled CDSSs. Rather limited theoretical foundations currently hinder the possibility of creating adequate concepts and models to explain and predict the interrelations between these characteristics and factors. For an appropriate evaluation of the human-AI collaboration, patient outcomes and the role of patients in the decision-making process should be considered.

Owing to the shortage of medical professionals, as well as demographic and structural challenges, new care models have emerged to find innovative solutions to counter medical undersupply. Team-based primary care using medical delegation appears to be a promising approach to address these challenges; however, it demands efficient communication structures and mechanisms to reinsure patients and caregivers receive a delegated, treatment-related task. Digital health care technologies hold the potential to render these novel processes effective and demand driven.BACKGROUNDOwing to the shortage of medical professionals, as well as demographic and structural challenges, new care models have emerged to find innovative solutions to counter medical undersupply. Team-based primary care using medical delegation appears to be a promising approach to address these challenges; however, it demands efficient communication structures and mechanisms to reinsure patients and caregivers receive a delegated, treatment-related task. Digital health care technologies hold the potential to render these novel processes effective and demand driven.The goal of this study is to recreate the daily work routines of general practitioners (GPs) and medical assistants (MAs) to explore promising approaches for the digital moderation of delegation processes and to deepen the understanding of subjective and perceptual factors that influence their technology assessment and use.OBJECTIVEThe goal of this study is to recreate the daily work routines of general practitioners (GPs) and medical assistants (MAs) to explore promising approaches for the digital moderation of delegation processes and to deepen the understanding of subjective and perceptual factors that influence their technology assessment and use.We conducted a combination of 19 individual and group interviews with 12 GPs and 14 MAs, seeking to identify relevant technologies for delegation purposes as well as stakeholders' perceptions of their effectiveness. Furthermore, a web-based survey was conducted asking the interviewees to order identified technologies based on their assessed applicability in multi-actor patient care. Interview data were analyzed using a three-fold inductive coding procedure. Multidimensional scaling was applied to analyze and visualize the survey data, leading to a triangulation of the results.METHODSWe conducted a combination of 19 individual and group interviews with 12 GPs and 14 MAs, seeking to identify relevant technologies for delegation purposes as well as stakeholders' perceptions of their effectiveness. Furthermore, a web-based survey was conducted asking the interviewees to order identified technologies based on their assessed applicability in multi-actor patient care. Interview data were analyzed using a three-fold inductive coding procedure. Multidimensional scaling was applied to analyze and visualize the survey data, leading to a triangulation of the results.Our results suggest that digital mediation of delegation underlies complex, reciprocal processes and biases that need to be identified and analyzed to improve the development and distribution of innovative technologies and to improve our understanding of technology use in team-based primary care. Nevertheless, medical delegation enhanced by digital technologies, such as video consultations, portable electrocardiograms, or telemedical stethoscopes, can counteract current challenges in primary care because of its unique ability to ensure both personal, patient-centered care for patients and create efficient and needs-based treatment processes.RESULTSOur results suggest that digital mediation of delegation underlies complex, reciprocal processes and biases that need to be identified and analyzed to improve the development and distribution of innovative technologies and to improve our understanding of technology use in team-based primary care. Nevertheless, medical delegation enhanced by digital technologies, such as video consultations, portable electrocardiograms, or telemedical stethoscopes, can counteract current challenges in primary care because of its unique ability to ensure both personal, patient-centered care for patients and create efficient and needs-based treatment processes.Technology-mediated delegation appears to be a promising approach to implement innovative, case-sensitive, and cost-effective ways to treat patients within the paradigm of primary care. The relevance of such innovative approaches increases with the tremendous need for differentiated and effective care, such as during the ongoing COVID-19 pandemic. For the successful and sustainable adoption of innovative technologies, MAs represent essential team members. In their role as mediators between GPs and patients, MAs are potentially able to counteract patients' resistance toward using innovative technology and compensate for patients' limited access to technology and care facilities.CONCLUSIONSTechnology-mediated delegation appears to be a promising approach to implement innovative, case-sensitive, and cost-effective ways to treat patients within the paradigm of primary care. The relevance of such innovative approaches increases with the tremendous need for differentiated and effective care, such as during the ongoing COVID-19 pandemic. For the successful and sustainable adoption of innovative technologies, MAs represent essential team members. In their role as mediators between GPs and patients, MAs are potentially able to counteract patients' resistance toward using innovative technology and compensate for patients' limited access to technology and care facilities.

This work was funded by the \"European Project on Ocean Acidification\" (EPOCA) (which received funding from the European Community's Seventh Framework Program (FP7/2007-2013) under grant agreement n° 211384) and partly by the Helmholtz Centre for Ocean Research Kiel (GEOMAR) and by the Center of Excellence \"The Future Ocean\" to ML; the Abbey-Santander Internationalization Fund, University of Basque Country (UPV/EHU), and Ministry of Science and Education (Government of Spain) to SBA; the Conselho Nacional de Desenvolvimento Científico e Tecnológico Brasil (CNPq, Processo: 405585/2013-6) to MNM; and ERC-STG-240222PACE for funding HS and AMV. Strains RCC1212 and RCC1258 were obtained from the RCC through the ASSEMBLE program (FP7-227799). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

In the NeuroIS field, experimental software needs to simultaneously present experimental stimuli to participants while recording, analyzing, or displaying neurophysiological measures. For example, a researcher might record a user's heart beat (neurophysiological measure) as the user interacts with an e-commerce website (stimulus) to track changes in user arousal or show a user's changing arousal levels during an exciting game. In this paper, we identify requirements for a NeuroIS experimental platform that we call Brownie and present its architecture and functionality. We then evaluate Brownie via a literature review and a case study that demonstrates Brownie's capability to meet the requirements in a complex research context. We also verify Brownie's usability via a quantitative study with prospective experimenters who implemented a test experiment in Brownie and an alternative software. We summarize the salient features of Brownie as follows: 1) it integrates neurophysiological measurements, 2) it incorporates real-time processing of neurophysiological data, 3i) it facilitates research on individual and group behavior in the lab, 4) it offers a large variety of options for presenting experimental stimuli, and 5) it is open source and easily extensible with open source libraries. In summary, we conclude that Brownie is innovative in its potential to reduce barriers for IS researchers by fostering replicability and research collaboration and to support NeuroIS and interdisciplinary research in cognate areas, such as management, economics, or human-computer interaction.

The performance of a solid oxide cell (SOC) under given operating conditions is often predicted by using cell models that subtract the different voltage loss contributions from the theoretical Nernst voltage, also called open circuit voltage minus losses models. The determination of kinetic parameters for Butler–Volmer-type equations describing activation losses at fuel and air electrodes, respectively, is therefore originally conducted at a single operating temperature, resulting in temperature-independent values for these parameters. Yet, significant temperature gradients across both the cell area and the height of the stack occur in SOC applications; thus, a proper representation of the temperature dependency of all electrochemical parameters is required. We therefore examine possible temperature dependencies of the kinetic parameters and their impact on cell performance. To this end, the kinetic parameters are experimentally determined within the operating window of the investigated cell (600 °C–700 °C), showing nonnegligible temperature dependencies for all parameters of the Butler–Volmer-type equation. The impact of these temperature dependencies on cell performance is evaluated by comparing the error between measurements and simulations with and without temperature-dependent parameters. Accounting for temperature-dependent parameters reduces the maximum cell voltage error between simulation and measurement. This reduction was from −5.4% to −5.1% in the electrolysis mode and from −9.7% to −7.9% in the fuel cell mode when the parametrization temperature matched the operating temperature (compared to a 100 K offset). Although the cell voltage improvement was moderate, a significant impact was observed on activation overpotentials, where neglecting temperature dependence led to deviations of up to 56% for the investigated cell.

Calcification of the cosmopolitan coccolithophore species \"Emiliania huxleyi\" was investigated in relation to the cell division cycle with the use of batch cultures. With a 12 : 12 h light: dark cycle, the population was synchronised to undergo division as a cohort, simultaneously passing through the Gl (assimilation), S (DNA replication), and G2+M (cell division and mitosis) phases. Cell division was followed with the use of quantitative DNA staining and flow cytometry. Simultaneously, carbon- 14 $(^{{\\rm{14}}} {\\rm{C}})$ assimilation in organic and inorganic carbon as well as cell abundance, size, and organic nitrogen content were measured at 2-h intervals. In additional experiments, changes in calcification and cell cycle stages were investigated in nitrogen-, phosphorus-, and light limited cultures. Calcification occurred only during the Gl cell cycle phase, as seen by the very tight correlation between the percentage of cells in Gl and calcification during the dark period. When growth was limited by nitrogen, cells decreased in size, remained in the Gl phase, and showed a moderate increase in the cell-specific calcite content. Limitation of growth by phosphorus, however, caused a significant increase in cell size and a dramatic increase in cellular calcite. Light limitation, by slowing the growth rate, prolonged the time cells spent in the Gl phase with a corresponding increase in the cellular calcite content. These results help explain the differing responses of coccolithophorid growth to nitrogen, phosphorus, and light limitation.

An international multi-disciplinary group of 24 researchers met to discuss ocean acidification (OA) during the Brazilian OA Network/Surface Ocean-Lower Atmosphere Study (BrOA/SOLAS) Workshop. Fifteen members of the BrOA Network (www. broa. furg. br) authored this review. The group concluded that identifying and evaluating the regional effects of OA is impossible without understanding the natural variability of seawater carbonate systems in marine ecosystems through a series of long-term observations. Here, we show that the western South Atlantic Ocean (WSAO) lacks appropriate observations for determining regional OA effects, including the effects of OA on key sensitive Brazilian ecosystems in this area. The impacts of OA likely affect marine life in coastal and oceanic ecosystems, with further social and economic consequences for Brazil and neighboring countries. Thus, we present (i) the diversity of coastal and open ocean ecosystems in the WSAO and emphasize their roles in the marine carbon cycle and biodiversity and their vulnerabilities to OA effects; (ii) ongoing observational, experimental, and modeling efforts that investigate OA in the WSAO; and (iii) highlights of the knowledge gaps, infrastructure deficiencies, and OA-related issues in the WSAO. Finally, this review outlines long-term actions that should be taken to manage marine ecosystems in this vast and unexplored ocean region.

E-commerce firms (ECFs) are known to internationalize digitally but may also opt for high international control in terms of depth (i.e., by choosing fully controlled operation modes to enable local offers and management) or breadth (i.e., through a subsidiary network to scale their business model and supply chain). Surprisingly, little is known about the role of ECFs’ international control decisions in foreign performance or how these decisions are affected by dynamic e-commerce market contexts. To address these gaps, the authors explore the effects of ECFs’ depth and breadth of control on foreign sales performance and the role of local e-commerce market size and growth as context factors. They refer to unique secondary data on 1,144 control decisions by 184 leading ECFs over time and apply multilevel modeling. The results show that ECFs generally improve foreign sales performance by choosing both higher depth and breadth of international control. However, these firms face trade-offs because both decisions affect performance differently and market growth moderates the effects positively and negatively. This allows direct implications for firms expanding digitally abroad but possibly struggling with sales performance.

This article studies (optimal) W^2m-1,ınfty -regularity for the polyharmonic equation (-)^m u = Q \\; H^n-1 where is a (suitably regular) (n-1) -dimensional submanifold of R^n , H^n-1 is the Hausdorff measure, and Q is some suitably regular density. As an application, we derive (optimal) W^3,ınfty -regularity for solutions of the biharmonic Alt–Caffarelli problem in two dimensions.

Purpose>Industry 4.0 is expected to significantly transform industrial value creation. However, research on business models affected through Industry 4.0, and on small- and medium-sized enterprises (SMEs), remains scarce. In response, the purpose of this paper is to address both aspects, further elaborating on the role that SMEs can take toward Industry 4.0 as provider or user.Design/methodology/approach>The paper used an exploratory research design based on 43 in-depth expert interviews within the three most important German industry sectors, mechanical and plant engineering, electrical engineering and automotive suppliers. Interviews were conducted with leading personnel of the respective enterprises, including 22 CEOs. They assign business model implications through Industry 4.0, referring to the Business Model Canvas, while the paper delineates between Industry 4.0 providers and users.Findings>The paper finds that key resources and value proposition are among the most affected elements of the business model, whereas channels are the least affected. Furthermore, distinct characteristics between Industry 4.0 providers and users can be delineated. In general, Industry 4.0 providers’ business models are significantly more affected than users, except for key partners and customer relationships.Research limitations/implications>Industry 4.0 remains at its early stages of implementation. As a result, many interviewees’ answers remain at a rather general level.Practical implications>Strategies for the further alignment of the business models are provided for Industry 4.0 providers and users.Originality/value>The paper is among the few that investigate Industry 4.0 in the context of SMEs and business models.