Structural, petrophysical and geological constraints in potential field inversion using the Tomofast-x v1.0 open-source code

The quantitative integration of geophysical measurements with data and information from other disciplines is becoming increasingly important in answering the challenges of undercover imaging and of the modelling of complex areas. We propose a review of the different techniques for the utilisation of structural, petrophysical and geological information in single physics and joint inversion as implemented in the Tomofast-x open-source inversion platform. We detail the range of constraints that can be applied to the inversion of potential field data. The inversion examples we show illustrate a selection of scenarios using a realistic synthetic dataset inspired by real-world geological measurements and petrophysical data from the Hamersley region (Western Australia). Using Tomofast-x’s flexibility, we investigate inversions combining the utilisation of petrophysical, structural and/or geological constraints while illustrating the utilisation of the L-curve principle to determine regularisation weights. Our results suggest that the utilisation of geological information to derive disjoint interval bound constraints is the most effective method to recover the true model. It is followed by model smoothness and smallness conditioned by geological uncertainty, and cross-gradient minimisation.

Electronic service quality: a meta-analysis

PurposeResearch studies on electronic service quality (ESQ) have presented heterogeneous findings, with distinct effects of mediators and moderators, for instance. Hence, the purpose of this study is to present a systematic review and a quantitative integration of the main findings regarding the attributes and effects of ESQ.Design/methodology/approachA meta-analysis was conducted of 134 studies regarding ESQ. Based on the extant literature, authors propose a conceptual model that review quality attributes, meta-analyze their effects on general quality, perceived value, satisfaction, trust and loyalty and test the moderation of three contextual variables (i.e. mobile vs nonmobile device, online shopping vs pure service; specific site vs Internet).FindingsDirect effects indicate that all proposed associations are significant, but with high variability, thus suggesting moderating effects. For instance, (1) type of device used by the customer, (2) type of service under analysis and (3) unit of analysis (i.e. site vs Internet) affect the relationship between quality attributes and satisfaction. This study also supported perceived value and satisfaction as relevant mediators in the link quality → loyalty.Originality/valueThis study analyses the general attributes of the ESQ construct, without the restriction of a specific model or type of service, and then tested the influence of the context. This study also shows that a substantial portion of the quality effect is transferred to loyalty through perceived value and customer satisfaction.

Accuracy of the Language Environment Analysis System Segmentation and Metrics: A Systematic Review

Purpose The Language Environment Analysis (LENA) system provides automated measures facilitating clinical and nonclinical research and interventions on language development, but there are only a few, scattered independent reports of these measures' validity. The objectives of the current systematic review were to (a) discover studies comparing LENA output with manual annotation, namely, accuracy of talker labels, as well as involving adult word counts (AWCs), conversational turn counts (CTCs), and child vocalization counts (CVCs); (b) describe them qualitatively; (c) quantitatively integrate them to assess central tendencies; and (d) quantitatively integrate them to assess potential moderators. Method Searches on Google Scholar, PubMed, Scopus, and PsycInfo were combined with expert knowledge, and interarticle citations resulting in 238 records screened and 73 records whose full text was inspected. To be included, studies must target children under the age of 18 years and report on accuracy of LENA labels (e.g., precision and/or recall) and/or AWC, CTC, or CVC (correlations and/or error metrics). Results A total of 33 studies, in 28 articles, were discovered. A qualitative review revealed most validation studies had not been peer reviewed as such and failed to report key methodology and results. Quantitative integration of the results was possible for a broad definition of recall and precision ( M = 59% and 68%, respectively; N = 12–13), for AWC (mean r = .79, N = 13), CVC (mean r = .77, N = 5), and CTC (mean r = .36, N = 6). Publication bias and moderators could not be assessed meta-analytically. Conclusion Further research and improved reporting are needed in studies evaluating LENA segmentation and quantification accuracy, with work investigating CTC being particularly urgent. Supplemental Material https://osf.io/4nhms/

Design for Clean Technology Adoption: Integration of Usage Context, User Behavior, and Technology Performance in Design

Clean technologies aim to address climatic, environmental, and health concerns associated with their conventional counterparts. However, such technologies achieve these goals only if they are adopted by users and effectively replace conventional practices. Despite the important role that users play to accomplish these goals by making decisions whether to adopt such clean alternatives or not, currently, there is no systematic framework for quantitative integration of the behavioral motivations of users during the design process for these technologies. In this study, the theory of planned behavior (TPB) is integrated with usage-context-based design to provide a holistic approach for predicting the market share of clean versus conventional product alternatives based on users’ personal beliefs, social norms, and perception of behavioral control. Based on the mathematical linkage of the model components, technology design attributes can then be adjusted, resulting in the design of products that are more in line with users’ behavioral intentions, which can lead to higher adoption rates. The developed framework is applied in a case study of adoption of improved cookstoves in a community in Northern Uganda. Results indicate that incorporating TPB attributes into utility functions improves the prediction power of the model and that the attributes that users in the subject community prioritize in a clean cookstove are elicited through the TPB. Households’ decision-making behavior before and after a trial period suggests that design and marketing strategy should systematically integrate user’s behavioral tendencies prior to interventions to improve the outcomes of clean technology implementation projects.