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Testing and estimating structural breaks in time series and panel data in Stata
Get PDFSupplementary Material is available online under a Creative Commons License at: https://journals.sagepub.com/doi/10.1177/1536867X251365449#supplementary-materials .Howto install: The latest version of the xtbreak package can be obtained by typing the following in Stata: net from https://janditzen.github.io/xtbreak/ Updates and further documentation can be found on GitHub.A preprint version of the article is available at arXiv:2110.14550v3 [econ.EM], https://arxiv.org/abs/2110.14550 ([v3] Wed, 22 Jan 2025 09:53:16 UTC (538 KB)). It has not been certified by peer review.Identifying structural change is a crucial step when analyzing time series and panel data. The longer the time span, the higher the likelihood that the model parameters have changed because of major disruptive events such as the 2007–2008 financial crisis and the 2020 COVID-19 outbreak. Detecting the existence of breaks and dating them is therefore necessary for not only estimation but also understanding drivers of change and their effect on relationships. In this article, we introduce a new community-contributed command called xtbreak, which provides researchers with a complete toolbox for analyzing multiple structural breaks in time series and panel data. xtbreak can detect the existence of breaks, determine their number and location, and provide break-date confidence intervals. We use xtbreak in examples to explore changes in the relationship between COVID-19 cases and deaths in the US using both aggregate and state-level data and in the relationship between approval ratings and consumer confidence using a panel of eight countries.Ditzen acknowledges financial support from Italian Ministry MIUR under the PRIN project Hi-Di NET- Econometric Analysis of High Dimensional
Models with Network Structures in Macroeconomics and Finance (grant 2017TA7TYC). Westerlund acknowledges financial support from the Knut and Alice Wallenberg Foundation through a Wallenberg Academy Fellowship
The Sharing Economy: A Systematic Literature Review and Research Agenda
Get PDFData Availability Statement:
The raw data required to reproduce the above findings are available to download from the Web of Science database. Also, please see the appendix.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/ijcs.70010#support-information-section .The sharing economy has emerged as a transformative model in the digital age. However, existing reviews often focus on isolated aspects and provide limited insights into its complexity. This paper comprehensively reviews 92 studies through a dual-framework approach, employing both the Antecedents–Decisions–Outcomes (ADO) and the Theories–Contexts–Methods (TCM) frameworks. The ADO framework reveals key factors influencing user decisions—including adoption, usage, booking, continued use, engagement, participation, purchase, and switching—that are shaped by economic, social, technological, trust-related, environmental, and political antecedents. Meanwhile, the TCM framework structures an in-depth examination of dominant theories (e.g., Technology Acceptance Model, Social Exchange Theory), diverse contexts (e.g., studies in China, the US), and methods (e.g., quantitative and qualitative) prevalent in the literature. Key findings emphasize the importance of regulatory dynamics and market shifts on user engagement and platform sustainability. Practical implications offer actionable guidance for platform managers to enhance user retention and to align strategies with evolving regulatory and market environments. The review also identifies future research directions to expand our understanding of global trends and challenges within the sharing economy.The authors received no specific funding for this work
Does model type influence the effectiveness of combined action observation and motor imagery training for novices learning an Ankle Pick takedown?
Get PDFData availability statement:
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://osf.io/3qgty/.Supplementary material:
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1596660/full#supplementary-material .Highlights:
• Combined action observation and motor imagery (AOMI) improves motor skill performance.
• AOMI training did not facilitate learning of an Ankle Pick takedown in novices.
• AOMI displaying an other-model led to mental representations becoming more functional.
• AOMI displaying a self-model led to mental representations becoming less functional.
• AOMI training combining self- and other-models may be most effective for learning.Introduction: Combined action observation and motor imagery (AOMI) training has been shown to facilitate motor skill performance, but limited research has explored its effectiveness on motor learning and factors that may moderate the effects of the intervention. This study examined the influence of model type on the effectiveness of AOMI training for novices learning an Ankle Pick takedown.
Methods: Twenty-eight novice participants (M = 28.07 ± 7.29 years) were randomly assigned to a control condition (n = 8), or to AOMI training that displayed footage of a self-model (AOMISELF; n = 10) or other-model (AOMIOTHER; n = 10). All training conditions included physical practice. A motor learning design incorporating pre-test (Day 1), acquisition (Days 2–6), post-test (Day 7), and retention-test (Day 14) was utilized. Motor skill performance, self-efficacy and mental representation structures were recorded as measures of learning.
Results: There were no significant differences between the training conditions across all twelve kinematics measures of motor skill performance. Self-efficacy scores increased for all training conditions over time. Both the AOMIOTHER and Control conditions led to improved functional changes in mental representation structures while the structures for the AOMISELF condition became less similar to the reference structure over time.
Discussion: Collectively, the largely null findings (n = 13, 92.86%) suggest that physical practice has the strongest influence on motor adaptations for this complex motor skill at these early stages of learning. However, the findings also suggest model type may be an important factor for novices using AOMI training. It is recommended that future research explores alternative modeling approaches, such as mixed-modeling incorporating both self- and other- footage, when designing AOMI interventions for sport.The author(s) declare that no financial support was received for the research and/or publication of this article
Brexit voters: Who has changed their mind?
Get PDFData availability statement:
This article uses two publicly available datasets: Bank of England/NMG Survey of Household Finances (2018 and 2019 waves), available at: https://www.bankofengland.co.uk/statistics/research-datasets. English Indices of Deprivation, published by the UK Department for Levelling Up, Housing and Communities. These provide official measures of relative deprivation in small areas across England and are available for multiple years (2004, 2007, 2010, 2015, and 2019). Available at: https://www.gov.uk/government/collections/english-indices-of-deprivation. The replication syntax and analysis code for this study are available at https://www.dropbox.com/scl/fi/zp7zjuas2gikv38sbbb60/Brexit-Views.do?rlkey=6e1nk9y2fwwww5njrir5qnso9&st=0jrx5quk&dl=0. This includes a fully annotated STATA .do file that reproduces the tables and models in the article, based on the publicly available datasets listed above.Acknowledgements:
The authors thank the participants at the Huddersfield Business School Conference 2020.We analyse which demographic groups in the UK were more likely to change their views on Brexit following the 2016 referendum on EU membership. Drawing on a large individual-level dataset of over 12,000 respondents, we find that women and middle-aged individuals were significantly more likely to shift towards a negative view of Brexit during the UK–EU negotiation period (2017 to 2019). Our analysis reveals that women and middle-age individuals were more likely to develop increasingly negative views of Brexit over time, while older individuals were more likely to report more favourable views. We also find that individuals with higher level of education were less likely to alter their views, maintaining consistent opinions over time. Importantly, we find no evidence that pre-referendum exposure to austerity policies influenced the likelihood of opinion change.The author(s) received no financial support for the research, authorship, and/or publication of this article
Neural-Network-Based Recursive State Estimation for Nonlinear Networked Systems With Binary-Encoding Mechanisms
Get PDFThis work addresses the problem of recursive state estimation for networked control systems with unknown nonlinearities and binary-encoding mechanisms (BEMs). To enhance transmission reliability and reduce network resource consumption, BEMs are used to convert measurement signals into binary bit strings (BBSs) of limited length, which are then transmitted to the estimator through noisy communication channels. During transmission, random bit errors may occur in the BBSs due to channel noise. For the considered nonlinear networked control systems affected by random bit errors, a neural-network (NN)-based recursive estimation strategy is proposed, where an NN with a time-varying tuning scalar is employed to approximate the unknown nonlinearity of the networked control systems. By using the proposed strategy, the upper bounds of the estimation error of the system state and the trace of the estimation error of the NN weight (NNW) are first derived. These bounds are then minimized by recursively designing both the estimator gain matrix and the tuning scalar of the NNW. Finally, the effectiveness of the proposed estimation strategy is demonstrated through a numerical example.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62273087 and 61933007);
10.13039/501100001809-Royal Society of U.K., and in part by the Alexander von Humboldt Foundation of Germany
Comparative study of common over-the-counter wound care products against early and mature biofilms of antibiotic-resistant wound pathogens
No full textData availability:
All data generated or analysed during this study are included in this published article and its Supplementary Information.Supplementary data:
Figures S1 to S3 and Supplementary Information S1 are available as Supplementary data online at: https://academic.oup.com/jacamr/article/7/6/dlaf233/8380916?login=false#supplementary-data .Background:
The global rise of antimicrobial resistance requires innovative and affordable wound care solutions. Moreover, managing wounds infected with priority pathogens remains a challenge. Despite the widespread availability of over-the-counter (OTC) antiseptics in wound care, comparative studies on their efficacy against biofilms or multidrug-resistant pathogens are limited.
Objectives:
This study compares the ability of different OTC antiseptics to disrupt biofilms of multidrug-resistant clinical isolates of Acinetobacter baumannii and Pseudomonas aeruginosa.
Methods:
The antimicrobial activity of seven antiseptics (polyhexanide, octenidine, chloroxylenol, chlorhexidine, ethanol, cetrimide, phenol) against early-stage (3-hour) and mature (24-hour) biofilms was determined by measuring reductions in colony-forming units (cfu)/biofilm while varying treatment exposure time.
Results:
All OTC products significantly reduced early-stage biofilms of both pathogens below detectable limits within 5 minutes (P < 0.0001, n = 3, LOD = 100 cfu/biofilm). In mature biofilms, significant differences emerged. Polyhexanide, octenidine and cetrimide yielded modest reductions in cfu count/biofilm (0.55–0.64-log) after 5 minutes, while chloroxylenol and phenol achieved ∼2.5-log reductions; notably, chlorhexidine reduced cfu/mature biofilms below detectable limits within 5 minutes. Extended exposure (60 minutes) enhanced the efficacy of phenol and ethanol, with chloroxylenol and octenidine reducing cfu/biofilm below detectable limits.
Conclusion:
OTC antiseptics are effective in eliminating early-stage biofilms; however, mature biofilms require either prolonged exposure, which may increase their toxicity and delay wound healing, or the use of potent formulations. Chlorhexidine gluconate, chloroxylenol and phenol offer an optimal balance between antibiofilm potency and tissue safety, offering promise for acute and chronic wound management particularly in low-resource settings.R.R.M.C. is supported by a Biotechnology and Biological Sciences Research Council New Investigator Award BB/V007823/1; UKRI1911; a Medical Research Council Award MR/Y001354/1; and the Academy of Medical Sciences, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy, the British Heart Foundation and Diabetes UK Springboard Award (SBF006\1040)
Tracks of Solidarity: Public Opinion and Railway Worker Strikes
No full textData Availability Statement:
Full replication data and code are available through the Harvard Dataverse, at: https://doi.org/10.7910/DVN/UKYKIQ .This study investigates the factors influencing public support for railway worker strikes in the United Kingdom. Using a seven-wave survey conducted from December 2022 to October 2023, the paper explores the relationship between public opinion and strike action in the context of British railways. Our analysis considers socioeconomic, political, and geographical factors. Key findings indicate significant variation in support based on political alignment, with right-leaning individuals and those who voted Conservative in the 2019 General Election showing less support for strikes. Surprisingly, proximity to railway stations and income levels did not significantly impact public support. Regional analysis reveals the North East of England, an area with lower rail usage, exhibits higher support for strikes. Furthermore, we find higher levels of support for strikes among ethnic minority groups. This paper contributes to understanding public sentiments on transport strikes, highlighting the complexity of public opinion shaped by political and regional factors. These insights are useful for policymakers and trades unions in addressing the challenges of public transport strikes and their broader societal impacts.This study was funded by the UKRI/ESRC (grant number ES/W011913/1) and the JSPS (grant number JPJSJRP 20211704)
Food waste management and the possibility of conversion of waste to electrical energy in Kuwait
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonFood waste management poses a significant environmental challenge in Kuwait, where over 90% of food waste is disposed of in landfills, leading to greenhouse gas emissions, leachate contamination, and inefficient land use. This study investigates anaerobic digestion as a sustainable waste-to-energy strategy, focusing on the influence of inoculum source, substrate composition, and hydrogen addition on biogas production and methane yield. The primary objective is to evaluate how different inoculum types and process enhancements impact methane generation from mono- and co-digestion of locally abundant food waste materials, including date fruit, meat, rice, and Sidr fruit. Anaerobic digestion experiments were conducted using two inoculum sources: wastewater-derived and food waste-derived. When digesting date fruit alone, wastewater inoculum produced 594 litres of biogas per kilogram of volatile solids with 59% methane, compared to 562 litres and 50% methane using food waste inoculum. Co-digestion of date fruit with rice and meat achieved the highest methane yield of 661 litres per kilogram of volatile solids at 66% methane concentration, attributed to
enhanced microbial synergy and nutrient balance. In comparison, Sidr fruit codigestion yielded 519 litres per kilogram with 67% methane, demonstrating high methane quality but a lower volumetric yield. This research is also the first to assess hydrogen injection in the anaerobic digestion of date fruit. Hydrogen addition at 0.67 millilitres per minute significantly increased methane production from 283 to 628 litres per kilogram of volatile solids, with methane concentration rising from 50.5% to 60%, highlighting the role of hydrogenotrophic methanogens. Overall, the findings demonstrate that inoculum type, substrate synergy, and hydrogen
enrichment are critical parameters in optimising biogas output. This study contributes new insights into anaerobic digestion process design and offers a scalable framework for sustainable energy generation from food waste in Kuwait
Human–robot collaboration in surgery at the nexus of knowledge, agency, and ownership
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The datasets generated and/or analyzed during the current study are not publicly available due to confidentiality agreements and the sensitive nature of the questions asked. Interviewees were assured that raw data would remain confidential and would not be shared. However, de-identified data may be available from the corresponding author upon reasonable request.Human-robot collaboration is transforming healthcare, particularly in surgical environments. Robotic surgery systems, embodied by advanced AI, are pivotal in augmenting human expertise across specialties such as gynecology and laparoscopic surgery. However, critical gaps remain in understanding how knowledge, agency, and ownership shape these collaborations. We address these gaps through semi-structured interviews with eleven healthcare professionals from diverse surgical roles. Our findings reveal that while robotic systems enhance precision and efficiency, they also generate tensions related to professional autonomy, control, and responsibility. Participants expressed ambivalent views, simultaneously demonstrating trust in the technology and strategic disengagement to preserve human authority. Concepts such as avatarization, the perception of robots as extensions of the self, and strategic ignorance emerged as key mechanisms through which professionals manage this evolving relationship. These dynamics point to the need for rethinking human–robot roles as fluid and co-constructed rather than fixed or hierarchical. We also emphasize the possible use of robotic systems to promote inclusivity and accessibility in healthcare while identifying structural barriers such as high costs, dependence on proprietary technology, and uneven organizational readiness. Our research enhances theoretical frameworks on human–robot interaction, providing practical and conceptual insights for the creation of equitable, sustainable, and context-sensitive robotic healthcare systems.Open access funding provided by Linnaeus University
Rethinking net zero: A new perspective on achieving net zero energy buildings
Get PDFSupplementary materials are available online at: https://www.sciencedirect.com/science/article/pii/S2772737825000331#sec0043 ."Energy" is an essential component of modern civilization, driving economic growth, technological innovation, and urbanization. However, the desire of the energy contributes to several geopolitical conflicts, emissions, and environmental deterioration. Since the building sector is highly energy-intensive with its construction and operations, addressing its energy requirement is crucial. A solution is provided by The Net Zero Energy Building (NZEB) strategy, applies to buildings whose annual energy consumption is equal to the amount of energy produced from renewable sources. This paper presents a new framework for designing energy-efficient buildings by developing the NZEB approach and integrating BIM. It introduces the Realistic Net-Zero Energy Building (RNZEB) method, that highlights the necessity for buildings to balance not only their operational energy consumes, also the embodied energy of materials utilises renewable resources throughout their whole lifespan. This study uses information collected from a conceptual residential project in London to demonstrate how the RNZEB approach is effective and how different structural systems (steel, reinforced concrete, timber) and building operations impact total energy consumption. The result demonstrates embodied energy of traditional steel house is 308,599.2 kWh, concrete house is 240,247.2 kWh, and timber house is 151,902.7 kWh. Employing low embodied energy materials reduces the energy footprint by 33.90 % for steel, 24.70 % for concrete, and 11.05 % for timber. Additionally, applying cutting-edge technologies results in impressive operational energy savings of up to 84.45 %. The RNZEB method's goal is to reset these reduced energies with renewable resources. Steel house in its 49th year, concrete in its 43rd, and timber in its 32nd year achieve the RNZE target
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