Digital Nudge Stacking and Backfiring: Understanding Sustainable E-Commerce Purchase Decisions

Background: The consumption of ‘fast fashion’, which is expedited by cost-effective e-commerce systems, represents one of the major factors contributing to the acceleration of climate change. An emerging approach to steer consumers in the direction of more sustainable purchase decisions is digital nudging. This paper explores digital nudging in the context of green fashion e-commerce by testing the effectiveness of two nudging strategies on the decision to choose green fashion products (GFP) over regular fashion items. Method: This study was conducted as a between-subject online experiment (n=320) with four conditions simulating an e-commerce scenario. The participants were presented with different products: one was ecologically friendly, and another was the regular option. Depending on their randomized group allocation, the participants experienced a default nudge, a social norm nudge, a combination of both strategies, or no nudge. In addition, we conducted 10 qualitative interviews to gain a deeper understanding of consumers’ decision process. Results: Our experiment failed to demonstrate statistically significant relationships between the various nudging strategies and GFP purchase decisions. However, additional explorative analyzes confirmed a backfire effect for the combination of nudging strategies. This reveals the previously overlooked influence of participants’ identification on the effectiveness of digital nudging strategies. In addition, qualitative interviews revealed individual factors that influence sustainable e-commerce purchase decisions. Conclusion: This study contributes to information systems research by explaining the differences in the effectiveness of different nudging strategies regarding high-involvement compared to low-involvement products. Moreover, it provides empirical evidence of a backfire effect resulting from a combination of digital nudging strategies (i.e., digital nudge stacking). Finally, the study underscores the leverage that individual factors have on both GFP purchase decision and the effectiveness of nudges

Towards Digital Solutions For Value Stream Analysis and Design: Systematic Literature Review And Market Analysis

Recognized as a core element of lean management practice, value stream analysis and design is widely adopted by improvement teams in industrial settings to optimize value creation and eliminate waste. The advancement of value stream analysis and design, incorporating elements such as material flow cost accounting, information logistics, and external influential factors, requires change how improvement teams should think and operate. Emerging complexity of method application and the rise in data volumes underscores the need for novel workflows and the necessity for digital solutions that empower improvement teams in their duties. While existing research focuses on conceptual design of digital solutions, recently no systematic analysis of concepts and solutions from research and practice regarding core aspects of value stream analysis and design has been conducted. To address this research gap, this paper adapts a three-phase research design within a y-model structured process. A systematic literature review and a market analysis are conducted to identify digital solutions for value stream analysis and design. Solutions are showcased and evaluated via concept matrices. Contributing findings of this paper are an assessment of selected concepts form research and solutions from practice as well as the deduction of research-focused requirements, practice-focused requirements, and currently neglected requirements

An update on dissolved methane distribution in the subtropical North Atlantic Ocean

Methane (CH4) is a potent greenhouse gas and plays a significant role in recent increasing global temperatures. The oceans are a natural source of methane contributing to atmospheric methane concentrations, yet our understanding of the oceanic methane cycle is poorly constrained. Accumulating evidence indicates that a significant part of oceanic CH4 is produced in oxygenated surface waters as a by-product of phytoplanktonic activity. This study focused on the subtropical North Atlantic Ocean (26∘ N, 80′ W and 26∘ N, 18′ W) where the distribution of dissolved CH4 concentrations and associated air–sea fluxes during winter 2020 were investigated. Water samples from 64 stations were collected from the upper water column up to depths of 400 m. The upper oxic mixed layer was oversaturated in dissolved CH4 with concentrations ranging 3–7 nmol L−1, with the highest concentrations of 7–10 nmol L−1 found to the east of the transect, consistent with other subtropical regions of the world's oceans. The high anomalies of dissolved CH4 were found to be associated with phosphate-depleted waters and regions where the abundance of the ubiquitous picocyanobacteria Synechococcus and Prochlorococcus were elevated. Although other phytoplanktonic phyla cannot be excluded, this suggests that cyanobacteria contribute to the release of CH4 in this region. The calculation of air–sea fluxes further confirmed the subtropical North Atlantic Ocean as a source of CH4. This study provides evidence to corroborate the key role that picocyanobacteria play in helping to explain the oversaturation of CH4 found in surface mixed layer of the open ocean, otherwise known as the “ocean methane paradox”

Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case Study

The discipline of process mining has a solid track record of successful applications to the healthcare domain. Within such research space, we conducted a case study related to the Intensive Care Unit (ICU) ward of the Uniklinik Aachen hospital in Germany. The aim of this work is twofold: developing a normative model representing the clinical guidelines for the treatment of COVID-19 patients, and analyzing the adherence of the observed behavior (recorded in the information system of the hospital) to such guidelines. We show that, through conformance checking techniques, it is possible to analyze the care process for COVID-19 patients, highlighting the main deviations from the clinical guidelines. The results provide physicians with useful indications for improving the process and ensuring service quality and patient satisfaction. We share the resulting model as an open-source BPMN file.Comment: 12 pages, 2 figures, 3 tables, 15 reference

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning.

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.This work was supported by an intramural grant to LM (START 46/16) and EZ (START 113/17). LM has received a grant by the Deutsche Forschungsgemeinschaft (DFG, MA 7082/1–1). We thank Dr Claycomb and his coworkers for providing the HL-1 cells and a detailed documentation. The Immunohistochemistry and Confocal Microscopy Unit, a core facility of the Interdisciplinary Center for Clinical Research (IZKF) Aachen, within the Faculty of Medicine at the RWTH Aachen University, supported this work

Microbial ecosystem responses to alkalinity enhancement in the North Atlantic Subtropical Gyre

In addition to reducing carbon dioxide (CO2) emissions, actively removing CO2 from the atmosphere is widely considered necessary to keep global warming well below 2°C. Ocean Alkalinity Enhancement (OAE) describes a suite of such CO2 removal processes that all involve enhancing the buffering capacity of seawater. In theory, OAE both stores carbon and offsets ocean acidification. In practice, the response of the marine biogeochemical system to OAE must be demonstrably negligible, or at least manageable, before it can be deployed at scale. We tested the OAE response of two natural seawater mixed layer microbial communities in the North Atlantic Subtropical Gyre, one at the Western gyre boundary, and one in the middle of the gyre. We conducted 4-day microcosm incubation experiments at sea, spiked with three increasing amounts of alkaline sodium salts and a 13C-bicarbonate tracer at constant pCO2. We then measured a suite of dissolved and particulate parameters to constrain the chemical and biological response to these additions. Microbial communities demonstrated occasionally measurable, but mostly negligible, responses to alkalinity enhancement. Neither site showed a significant increase in biologically produced CaCO3, even at extreme alkalinity loadings of +2,000 μmol kg−1. At the gyre boundary, alkalinity enhancement did not significantly impact net primary production rates. In contrast, net primary production in the central gyre decreased by ~30% in response to alkalinity enhancement. The central gyre incubations demonstrated a shift toward smaller particle size classes, suggesting that OAE may impact community composition and/or aggregation/disaggregation processes. In terms of chemical effects, we identify equilibration of seawater pCO2, inorganic CaCO3 precipitation, and immediate effects during mixing of alkaline solutions with seawater, as important considerations for developing experimental OAE methodologies, and for practical OAE deployment. These initial results underscore the importance of performing more studies of OAE in diverse marine environments, and the need to investigate the coupling between OAE, inorganic processes, and microbial community composition

Whole-heart dynamic three-dimensional magnetic resonance perfusion imaging for the detection of coronary artery disease defined by fractional flow reserve: determination of volumetric myocardial ischaemic burden and coronary lesion location

Aims Dynamic three-dimensional-cardiac magnetic resonance (3D-CMR) perfusion proved highly diagnostic for the detection of angiographically defined coronary artery disease (CAD) and has been used to assess the efficacy of coronary stenting procedures. The present study aimed to relate significant coronary lesions as assessed by fractional flow reserve (FFR) to the volume of myocardial hypoenhancement on 3D-CMR adenosine stress perfusion imaging and to define the inter-study reproducibility of stress inducible 3D-CMR hypoperfusion. Methods and results A total of 120 patients with known or suspected CAD were examined in two CMR centres using 1.5 T systems. The protocol included cine imaging, 3D-CMR perfusion during adenosine infusion, and at rest followed by delayed enhancement (DE) imaging. Fractional flow reserve was recorded in epicardial coronary arteries and side branches with ≥2 mm luminal diameter and >40% severity stenosis (pathologic FFR < 0.75). Twenty-five patients underwent an identical repeat CMR examination for the determination of inter-study reproducibility of 3D-CMR perfusion deficits induced by adenosine. Three-dimensional CMR perfusion scans were visually classified as pathologic if one or more segments showed an inducible perfusion deficit in the absence of DE. Myocardial ischaemic burden (MIB) was measured by segmentation of the area of inducible hypoenhancement and normalized to left ventricular myocardial volume (MIB, %). Three-dimensional CMR perfusion resulted in a sensitivity, specificity, and diagnostic accuracy of 90, 82, and 87%, respectively. Substantial concordance was found for inter-study reproducibility [Lin's correlation coefficient: 0.98 (95% confidence interval: 0.96-0.99)]. Conclusion Three-dimensional CMR stress perfusion provided high diagnostic accuracy for the detection of functionally significant CAD. Myocardial ischaemic burden measurements were highly reproducible and allowed the assessment of CAD severit

Molecular Classification of Neuroendocrine Tumors of the Thymus

INTRODUCTION: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. METHODS: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. RESULTS: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). CONCLUSIONS: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication. peerReviewe

OSHDB: a framework for spatio-temporal analysis of OpenStreetMap history data

Abstract OpenStreetMap (OSM) is a collaborative project collecting geographical data of the entire world. The level of detail of OSM data and its data quality vary much across different regions and domains. In order to analyse such variations it is often necessary to research the history and evolution of the OSM data. The OpenStreetMap History Database (OSHDB) is a new data analysis tool for spatio-temporal geographical vector data. It is specifically optimized for working with OSM history data on a global scale and allows one to investigate the data evolution and user contributions in a flexible way. Benefits of the OSHDB are for example: to facilitate accessing OSM history data as a research subject and to assess the quality of OSM data by using intrinsic measures. This article describes the requirements of such a system and the resulting technical implementation of the OSHDB: the OSHDB data model and its application programming interface

An LRP5 Receptor with Internal Deletion in Hyperparathyroid Tumors with Implications for Deregulated WNT/β-Catenin Signaling

Gunnar Westin and colleagues report the expression of an aberrantly spliced LRP5 receptor in primary and spontaneous parathyroid tumors and implicate it in the deregulated activation of the Wnt/β-catenin signaling pathway