Article
Medicine, General & Internal
Kenneth J. Nieser, Zachary N. Stowe, Jeffrey Newport, Jessica L. Coker, Amy L. Cochran
Summary: The study utilized a novel algorithm to automatically identify differential symptom patterns in postpartum depression and characterized individuals with different patterns. Differences in symptom patterns were associated with demographics and psychiatric histories. This has important implications for screening, diagnosis, and treatment of postpartum depression.
Article
Statistics & Probability
Mohammad Kazemi, Paulo Canas Rodrigues
Summary: Singular spectrum analysis is a powerful non-parametric method for time series analysis and forecasting. This paper introduces four robust alternatives to handle the presence of outliers in the singular spectrum analysis algorithm, which are compared with traditional methods through Monte Carlo simulations.
COMPUTATIONAL STATISTICS
(2023)
Letter
Biochemistry & Molecular Biology
Miri Adler, Avichai Tendler, Jean Hausser, Yael Korem, Pablo Szekely, Noa Bossel, Yuval Hart, Omer Karin, Avi Mayo, Uri Alon
Summary: Researchers have developed new methods to control for phylogenetic dependence and demonstrated the robustness of ParTI inference to phylogenetic dependence. They avoided p-hacking by testing the robustness of preprocessing choices and also provided new methods to control for population structure.
MOLECULAR BIOLOGY AND EVOLUTION
(2022)
Article
Computer Science, Interdisciplinary Applications
Andreas Alfons, Nufer Y. Ates, Patrick J. F. Groenen
Summary: Mediation analysis is a widely used statistical technique in social, behavioral, and medical sciences for studying the indirect effects of independent variables on dependent variables through intervening variables. However, existing methods are sensitive to outliers and deviations from normality assumptions, which can threaten the empirical testing of mediation mechanisms. The robmed package in R implements a robust procedure for mediation analysis that addresses these issues and provides various analysis methods and result visualization.
JOURNAL OF STATISTICAL SOFTWARE
(2022)
Article
Multidisciplinary Sciences
Andreas Leitherer, Angelo Ziletti, Luca M. Ghiringhelli
Summary: This paper presents a Bayesian deep learning method for crystal structure identification called ARISE, which is robust and capable of classifying a wide range of complex structures. The unsupervised analysis of internal neural network representations allows for accurate identification and understanding of complex patterns in crystal structures.
NATURE COMMUNICATIONS
(2021)
Article
Physics, Fluids & Plasmas
Chisa Hotta, Takashi Nakamaniwa, Tota Nakamura
Summary: Sine-square deformation (SSD) is a treatment proposed in quantum systems that gradually decreases the local energy scale from the center of the system towards the edges using a sine-squared envelope function. When applied to classical Ising models, SSD creates an extended canonical ensemble of local subsystems with their own effective temperatures. By normalizing the system temperature by the deformed local energy scale, a single calculation can produce physical quantities at various temperatures that quantitatively reproduce those of the uniform system.
Article
Computer Science, Artificial Intelligence
Ha-Young Shin, Hee-Seok Oh
Summary: This paper studies robust regression on Riemannian manifolds, proposes the use of M-type estimators for robust geodesic regression, and calculates the tuning parameters for these estimators. The results show that all M-type estimators are maximum likelihood estimators on compact symmetric spaces, and argue for the preference of the L-1 estimator over the L-2 and Huber estimators in high-dimensional spaces.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2022)
Article
Physics, Multidisciplinary
Ze-Guo Chen, Ruo-Yang Zhang, C. T. Chan, Guancong Ma
Summary: This study demonstrates the realization of non-Abelian braiding of multiple degenerate acoustic waveguide modes, exploring the dynamics and geometric phase variations. By switching the order of different braiding processes, the non-Abelian characteristics are revealed.
Article
Construction & Building Technology
Rui Nian Jin, Hitoshi Inada, Janos Negyesi, Daisuke Ito, Ryoichi Nagatomi
Summary: Environmental carbon dioxide (CO2) could have an impact on mental and physiological activities, but its effect on daytime sleepiness is still debated. In this study, the researchers used a combination of classical frequentist and Bayesian statistical methods to analyze the effect of CO2 exposure on daytime sleepiness and EEG signals. The results showed that daytime sleepiness was significantly influenced by exposure time, but not by the CO2 condition according to classical statistics. However, the Bayesian paired t-test suggested that CO2 exposure at a moderately high concentration could induce daytime sleepiness at a specific time point. EEG signals were significantly affected by short exposure to a high concentration of CO2, but exposure time did not have a significant impact. The Bayesian analysis of EEG results was generally consistent with the classical statistics, but showed different credible levels in the Bayes' factor. The study suggests that EEG may not be suitable for detecting objective sleepiness induced by CO2 exposure due to its high sensitivity to environmental CO2 concentration. This research provides valuable insights for reconsidering the use of EEG as an indicator of objective sleepiness.
Article
Geosciences, Multidisciplinary
K. G. van den Boogaart, P. Filzmoser, K. Hron, M. Templ, R. Tolosana-Delgado
Summary: Compositional data contain valuable information within the relationships between the compositional parts, which can be utilized for regression modeling. Balance coordinates are constructed to interpret regression coefficients and test hypotheses of subcompositional independence. Both classical least-squares regression and robust MM regression were compared within different regression models using a real data set from a geochemical mapping project.
MATHEMATICAL GEOSCIENCES
(2021)
Article
Evolutionary Biology
Jeanne Lemant, Cecile Le Sueur, Veselin Manojlovic, Robert Noble
Summary: This study proposes a new class of robust and universal tree balance indices, which enable meaningful comparison of trees with different numbers of leaves. The study also demonstrates that one of these indices is equivalent to the normalized reciprocal of Sackin's index, unifying the two most popular existing tree balance indices.
SYSTEMATIC BIOLOGY
(2022)
Article
Public, Environmental & Occupational Health
Athanasios Burlotos, Tayana Jean Pierre, Walter Johnson, Seth Wiafe, PROTRA Haiti Grp, Michelle Joseph
Summary: This study conducted geospatial epidemiology research on firearm injuries in Port-au-Prince, Haiti, using innovative methods. By combining multiple data sources, hotspots of injuries were identified, and neighborhood level relative-risk estimates were obtained. These geospatial methods can help address the growing burden of firearm injuries in Port-au-Prince.
INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS
(2023)
Article
Business, Finance
Lei Shu, Feiyang Lu, Yu Chen
Summary: This paper proposes a scaled independent component analysis method to find factors with stronger predictive power and applies it to economic data analysis, showing better forecasting performance.
FINANCE RESEARCH LETTERS
(2023)
Article
Economics
Shakil Khan, Hanna Maoh
Summary: This paper investigates the attitudes and perceptions of fleets operating entities (FOEs) towards electric vehicles (EVs) through a survey of over 1000 Canadian entities. The results suggest that technology and cost considerations may deter the adoption of EVs, while monetary and nonmonetary factors can support adoption. The analysis identifies two key constructs: early adopter attitudes and cost-consciousness. The study finds that corporate and government fleets have similar profiles, with some variations in their response to deterring factors. The sampled FOEs prioritize the risk of implementing new technology compared to total cost of ownership and environmental benefits.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Hospitality, Leisure, Sport & Tourism
David Buil-Gil, Rob Mawby
Summary: This study examines the crime reporting propensities of tourists and locals in Barcelona using two sets of surveys. The results indicate that international tourists are less likely to report personal crime to the police compared to locals, while domestic tourists may be more willing to report personal crime. However, both international and domestic tourists report vehicle crime more frequently than locals.
CURRENT ISSUES IN TOURISM
(2022)
Article
Management
Abderahman Rejeb, Karim Rejeb, Steven J. Simske, Horst Treiblmaier
Summary: This study examines the potentials and challenges of drones in supply chain management and logistics. The findings illustrate that potential strengths of drones in SCM and logistics include support of humanitarian logistics, reduced delivery time, reduced cost, improved flexibility, and increased sustainability. The challenges posed by drones in these areas are grouped into technical, organisational, safety-related, and regulatory issues.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2023)
Article
Education & Educational Research
Andrei O. J. Kwok, Horst Treiblmaier
Summary: This study examines the potential of blockchain technology to revolutionize education, particularly focusing on its benefits for students with limited access to educational resources. Through a systematic analysis of existing literature, the study identifies key factors influencing the adoption and use of blockchain in education. The findings highlight important themes at the macro and micro levels, providing insights into how blockchain can improve educational quality, accessibility, social inclusion, and equality.
ASIA PACIFIC EDUCATION REVIEW
(2022)
Article
Hospitality, Leisure, Sport & Tourism
Andreas Strebinger, Horst Treiblmaier
Summary: To successfully introduce blockchain-enabled booking platforms in the tourism and hospitality industry, providers need to understand their target audiences. A survey of 505 US consumers revealed that blockchain-enabled booking apps with discounts, additional services, and well-known brand names could attract up to half of the market.
INFORMATION TECHNOLOGY & TOURISM
(2022)
Review
Green & Sustainable Science & Technology
Abderahman Rejeb, Zailani Suhaiza, Karim Rejeb, Stefan Seuring, Horst Treiblmaier
Summary: This article analyzes and classifies existing research at the intersection of the circular economy and the Internet of Things (IoT), providing a structured framework for understanding the relationship between these two concepts. The review of 170 academic articles identifies important drivers and enablers, and highlights future research directions.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Computer Science, Information Systems
Horst Treiblmaier, Evgeny Gorbunov
Summary: The digital transformation of core marketing activities has a significant impact on the relationship between consumers and companies. This study examines the influence of biased information on consumers' attitudes towards cryptocurrencies, finding that exposure to positive information leads to more positive attitudes, while exposure to negative information weakens trust and risk perceptions.
Review
Green & Sustainable Science & Technology
Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Mohammad Iranmanesh, Horst Treiblmaier, Sandeep Jagtap
Summary: This study provides an overview of research on the food supply chain (FSC) during the COVID-19 pandemic using bibliometric techniques. The findings indicate a rapid expansion of FSC research during the pandemic, with a focus on the impact of COVID-19 on the FSC and agriculture, FSC resilience, food waste and insecurity, fisheries and aquaculture, blockchain technology, and governance and innovation.
Article
Engineering, Industrial
Manjot Singh Bhatia, Atanu Chaudhuri, Yasanur Kayikci, Horst Treiblmaier
Summary: Agricultural commodity supply chains face challenges such as multiple intermediaries, limited access to finance, and poor financial conditions for farmers. Blockchain-enabled supply chain finance solutions have the potential to address these issues. This paper applies the CIMO framework to analyze case studies of four firms implementing blockchain-enabled SCF solutions in agricultural commodity supply chains. The findings show that these solutions can reduce transaction costs and improve the financial conditions of farmers. The study provides insights and solutions for companies planning to develop and implement blockchain-enabled SCF solutions.
PRODUCTION PLANNING & CONTROL
(2023)
Article
Business
Horst Treiblmaier, Elena Petrozhitskaya
Summary: Blockchain technology is expected to drive marketing transformation and has potential advantages over traditional loyalty programs in terms of usage, accrual, relevance, expiration, and transferability. Two empirical studies, analyzing Twitter tweets and conducting a survey, show that consumers have a preference for blockchain-based loyalty programs due to their innovative customer services and properties of a sharing economy.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Management
Horst Treiblmaier, Abderahman Rejeb
Summary: This study investigates existing blockchain solutions for disaster prevention and relief through a multiple case study approach. The findings show that blockchain applications can enhance information flows and stakeholders' capabilities, thus improving disaster management. Furthermore, the study provides a theoretical foundation for future research.
JOURNAL OF BUSINESS LOGISTICS
(2023)
Article
Operations Research & Management Science
Andrei O. J. Kwok, Horst Treiblmaier
Summary: Blockchain can help small countries overcome constraints and strengthen their economies. This research develops a conceptual framework based on dynamic capabilities theory to explore the applicability of blockchain for economic development. The proposed framework integrates blockchain as an economic driver and dynamic capabilities on different levels, showcasing their impacts on various aspects of economic development. Regulatory and political factors at the international level determine the success of a national blockchain-based strategy. In conclusion, this study illustrates how blockchain can contribute to a small country's economic development by enabling dynamic capabilities.
JOURNAL OF DECISION SYSTEMS
(2023)
Review
Computer Science, Information Systems
Abderahman Rejeb, Karim Rejeb, Horst Treiblmaier
Summary: The metaverse is gaining attention for its potential to revolutionize industries and its societal impact. However, there is a lack of comprehensive review articles using bibliometric techniques. This study analyzes 595 metaverse-related journal articles and identifies the growth, trends, authors, and journals in the field. A keyword co-occurrence analysis reveals four significant clusters of metaverse-related interests, emphasizing its implications across sectors. This study highlights the need for more research and collaboration in advancing the metaverse field.
Review
Green & Sustainable Science & Technology
Abderahman Rejeb, Karim Rejeb, Yasanur Kayikci, Andrea Appolloni, Horst Treiblmaier
Summary: The goal of green procurement is to enhance sustainability by reducing waste and improving operational efficiencies. This study uses bibliometrics to summarize the literature on green procurement, identify research hotspots and trends, and uncover core topics and important research clusters.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Review
Business
Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Horst Treiblmaier
Summary: Crowdfunding has gained popularity as a financing method for entrepreneurs, attracting attention from researchers and practitioners. This study aims to investigate the core content and knowledge diffusion paths in the field of crowdfunding. The study uses co-word clustering and main path analysis to examine the historical development of crowdfunding research based on 1,528 journal articles. The analysis identifies seven themes and reveals the dominant topics and recent trends in crowdfunding research.
EUROPEAN JOURNAL OF INNOVATION MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Horst Treiblmaier
Summary: This paper discusses the energy use of Bitcoin, clarifies common misconceptions, and explores the relationship between Bitcoin and energy, as well as its incentive mechanism. The author thoroughly discusses various aspects of Bitcoin's energy use and integrates them into a comprehensive framework, providing a foundation for future research and evaluating Bitcoin's energy requirements from an environmental perspective.
BLOCKCHAIN-RESEARCH AND APPLICATIONS
(2023)
Review
Computer Science, Information Systems
Abderahman Rejeb, Karim Rejeb, Horst Treiblmaier, Andrea Appolloni, Salem Alghamdi, Yaser Alhasawi, Mohammad Iranmanesh
Summary: Recent improvements in IoT have led to rapid developments in healthcare. This article provides a summary of previous studies on the applications of IoT in healthcare. Through a comprehensive review and bibliometric analysis, the growth of IoT research in healthcare is objectively summarized. The findings reveal significant research hotspots, including IoT healthcare applications, blockchain applications, AI techniques, 5G telecommunications, and data analytics.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Karen Renaud, Merrill Warkentin, Ganna Pogrebna, Karl van der Schyff
Summary: Insider threats can cause significant damage due to insiders' access and trust. To mitigate these threats, organizations must understand different types of insider threats and employ tailored measures.
INFORMATION & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Quirin Demlehner, Sven Laumer
Summary: This article discusses the challenges brought by the rapid development of artificial intelligence in the adoption of technology at an individual level. It focuses on the role of biases and examines their impact on user decision making. Through a case study of three German car manufacturers, the article highlights the importance of the pre-announcement phase in information systems adoption and provides a comprehensive analysis of biases caused by individuals' cognitive limitations. It also reveals a notable spillover effect of users' experiences and opinions on AI from their personal lives to their professional lives, which contradicts previous findings in IS research.
INFORMATION & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xinyu Sun, Yan Zhang, Juan Feng
Summary: This study investigates the impact of online information on brand reputation and brand premium in the online market. The findings suggest that the presence of online information may change the situation of brand premium, and firms with lower reputation can potentially earn higher profits under certain conditions. Additionally, as the gap in brand reputation increases, the profits of both firms may also increase, leading to a win-win situation in brand competition.
INFORMATION & MANAGEMENT
(2024)
