151398 research outputs found
Sort by
The education of children in residential care: A systematic review of the enablers and barriers of educational attainment
No full textA comparison of international modeling methods for evaluating health economics of colorectal cancer screening: a systematic review
No full textObjectivesCost-effectiveness analysis (CEA) is an accepted approach to evaluate cancer screening programs. CEA estimates partially depend on modeling methods and assumptions used. Understanding common practice when modeling cancer relies on complete, accessible descriptions of prior work. This review’s objective is to comprehensively examine published CEA modeling methods used to evaluate colorectal cancer (CRC) screening from an aspiring modeler’s perspective. It compares existing models, highlighting the importance of precise modeling method descriptions and essential factors when modeling CRC progression.MethodsMEDLINE, EMBASE, Web of Science, and Scopus electronic databases were used. The Consolidated Health Economic Evaluation Reporting Standards statement and data items from previous systematic reviews formed a template to extract relevant data. Specific focus included model type, natural history, appropriate data sources, and survival analysis.ResultsSeventy-eight studies, with 52 unique models were found. Twelve previously published models were reported in 39 studies, with 39 newly developed models. CRC progression from the onset was commonly modeled, with only 6 models not including it as a model component.ConclusionsModeling methods needed to simulate CRC progression depend on the natural history structure and research requirements. For aspiring modelers, accompanying models with clear overviews and extensive modeling assumption descriptions are beneficial. Open-source modeling would also allow model replicability and result in appropriate decisions suggested for CRC screening programs.<br/
Providing concentrate feed outside of the milking robot increases feed intake in dairy cows without reducing motivation to visit the robot
No full textAppropriate and adequate feeding is essential to maintaining good health, productivity and welfare of dairy cows. Within automatic milking systems, concentrate feed is offered inside the milking robot, and is thought to play a key role in motivating cows to visit the robot for milking. As concentrate feed delivery takes place during milking, the amount of concentrate a cow can consume is limited by milking duration and consumption rate. Thus, some cows may require supplementary feeding, but concerns exist regarding the potential negative effects of allocating concentrate outside of the milking robot on motivation to visit the robot for milking. The study’s primary aims were to assess the effects of providing 80% of the cows’ concentrate allocation inside the robot or inside an out-of-parlour feeder (OOPF) on 1) milking frequency, refused milkings, and OOPF visit frequency, 2) lying time, 3) milk yield, and 4) partial mixed ration (PMR) intake and amount of daily concentrate allocation not consumed by the cows, and 5) time spent in the robot and OOPF. Forty-eight mid-late lactation dairy cows were split into two treatment groups, one of which received 80% of their concentrate ration inside the milking robot and 20% inside the OOPF (robot high), whereas the other received 20% of their concentrate inside the milking robot and 80% via the OOPF (robot low). The study took place over a four-week period. GLMMs assessed the effects of treatment and time on the dependent variables milking frequency, refused milkings, OOPF visit frequency, lying time, milk yield, PMR intake, and amount of concentrate feed left unconsumed. No effects of treatment on milking frequency, refused milkings, milking time, or lying time were found. As expected, ‘robot low’ cows visited more frequently and spent more time in the OOPF than ‘robot high’ cows. Finally, ‘robot high’ cows left more of their allocated concentrate ration unconsumed, which suggests that feed consumption may be limited by milking duration and may result in cows not meeting their energy targets. In conclusion, allocating a portion of concentrate feed outside of the milking robot does not affect motivation to visit the robot or time spent resting, only briefly affects PMR intake and milk yield, and may enable cows to better meet their concentrate feed targets, all of which may positively affect health, productivity and welfare
A novel nested gene Aff3ir participates in vascular remodeling by enhancing endothelial cell differentiation in mice
No full textAccountability and AI: redundancy, overlaps and blind-Spots
No full textArtificial Intelligence (AI) increasingly reshapes public sector activities, raising critical questions about its impact on traditional democratic accountability. Despite recent achievements in unpacking the multiple forms and dimensions of accountability, limited attention has been given to how diverse AI forms - beyond their perception as a singular phenomenon - uniquely contribute to accountability challenges. This paper examines how different AI schools (like connectionist and symbolic) affect accountability in public governance, using the AI, Algorithmic and Automation Incidents and Controversies (AIAAIC) repository to analyze 115 real-world public sector AI incidents. Our methodology clusters cases by AI school to identify recurring accountability issues: redundancy (unnecessary accountability efforts), overlaps (competing accountability demands), and blind-spots (insufficient or no accountability appears evident). Our findings reveal that connectionist systems dominate public sector deployments, often linked to transparency issues. Less commonly deployed AI forms, such as symbolic or analogizer systems, may better align with public governance principles under certain conditions. This study highlights compatibility issues between AI forms and accountability dimensions, emphasizing how algorithmic design choices significantly shape governance outcomes. By addressing these challenges, the paper advances understanding of AI accountability in public administration and reinforces the need for strategic AI adoption to enhance democratic processes.<br/
On the association of attitudes towards NATO and weapon deliveries for Ukraine with vote intentions in Germany
No full textStudies have shown that foreign policy events can sway voting intentions. While initial analyses have explored Germany’s response to the Russian invasion of Ukraine and its foreign policy implications, public perspectives on this matter remain relatively unexplored, despite visible consequences like soaring energy and food prices, and concerns about escalating the war. To address this gap, the article delves into how Germans’ attitudes towards NATO’s role in the Russian invasion and the supply of weapons to Ukraine impact their voting intentions. Drawing on GLES data, our research reveals that rejecting further weapons deliveries significantly increases support for the radical-right AfD. Conversely, endorsement of such deliveries sees increased support for the Greens, FDP, and CDU/CSU. No significant effects are observed for the SPD and the Left Party. Notably, attitudes towards NATO and weapons play a role in the likelihood of supporting a new party associated with former Left Party politician, Sahra Wagenknecht. Crucially, these effects persist even when considering socio-demographic and ideological factors, underscoring the pivotal role of these issues in shaping party competition
Public accountability in an unpredictable world: tales of the unexpected
No full textThis paper aims to provide an overview of the different research themes and concepts that surround the investigation of crises and how these affect the delivery of important public services. It offers a critical reflection on what crisis means, how frequently we can identify one, and how this affects our notions of accountability (and possibly transparency) in the delivery of public services. Such considerations are based on a critical assessment of some of the main literature in the area, as well as the papers that form part of this special issue and which were initially presented at the ‘What is the Future of Public Accountability in the Aftermath of Crisis?’ workshop organized by the International Centre of Public Accountability, Durham University (UK) in November 2022. Thus, the particular contribution of the paper is a research agenda that focuses on issues relating to crisis and public-service organizations as an encouragement to accounting and public-management researchers to investigate accountability and governance issues in the face of crisis. This provides a stepping stone for more evidence-based discussion of the impact of crises on these organizations. The paper also reflects on a stronger and much-needed engagement between research and practice to make sure lessons are learnt, and mistakes not repeated, in the aftermath of crises.<br/
PEVuln: a benchmark dataset for using machine learning to detect vulnerabilities in PE malware
No full textIn this paper, we present a benchmark dataset for training and evaluating static PE malware machine learning models, specifically for detecting known vulnerabilities in malware. Our goal is to enable further research in defense against malware by exploiting their bugs or weaknesses. After recognising limitations in current malware datasets regarding exploitable malware, our dataset addresses these gaps by utilizing the malware vulnerability database Malvuln, and software vulnerability database ExploitDB to create a new malware dataset with 684 vulnerable malware samples, 35,241 non-vulnerable malware samples, 1,425 vulnerable benign samples, and 7,905 non-vulnerable benign samples, detailed with timestamps, families, threat mapping, vulnerability mapping, and obfuscation analysis. This 4-class dataset lays the foundation for advancing future research in analysis and vulnerability exploitation in malware using machine learning. We also provide baseline results using state-of-the-art models for malware classification to benchmark the performance of the dataset, where the binary tasks achieve F1 scores above 0.90, while the multi-class task attains an F1-Score of 0.958.<br/
European union funding of interest groups: Reassessing the balancing function and the promotion of good organizational practices
No full textThe question of the legitimacy of government funding of interest groups as a democratic practice has been extensively discussed by scholars. On the one hand, research suggests that well‐resourced interest groups are better equipped to capture European Union (EU) funds, raising some questions regarding the elitist character of the EU system of interest representation. On the other hand, EU funds have been found to address imbalances in the system of interest representation by directing funding streams toward underrepresented citizen groups. The present study contributes to this open discussion, by 1) analyzing to which extent findings from previous studies can be replicated with a more nuanced research design and by employing the largest existing dataset on interest groups and EU funding, and by 2) testing new hypotheses inspired by an alternative theoretical focus to mainstream approaches: associative democracy. To do so, we use data from the Comparative Interest Group Survey, a dataset of almost 2500 organizations across eight EU countries (Belgium, the Netherlands, Sweden, Portugal, Slovenia, Lithuania, the Czech Republic and Poland) and at the EU level. Our results offer two main contributions. By replicating recent studies, our findings nuance conclusions drawn this far regarding existing biases in the EU system of interest representation: it is true that rich and experienced interest groups are more likely to obtain EU funding. However, EU funding is also more likely to be allocated to NGOs, especially when they operate in business‐dominated policy areas. Moreover, we find that EU funds are not as concentrated in EU‐15 member states as previously thought. Finally, inspired by associative democracy, we show that EU funding is more often allocated where good practices are in place. These include membership representation as core function and membership influence over internal decision‐making processes
How sticky is sticky? A note on gametophyte adherence of the macroalga Saccharina latissima (Phaeophyceae)
No full textTemperate marine systems are ideal environments for expanding global seaweed aquaculture, yet high costs, particularly from macroalgal nursery facilities, have become a limiting factor for industry development. Recent research has explored the use of binder-seeding, whereby juvenile kelp life stages are seeded directly onto rope using adhesive solutions and deployed directly at sea. This method is used to reduce our reliance on nursery facilities and reduce aquaculture costs. While binder-seeding has shown mixed results, a more simplistic approach by Klaus Lüning has received less attention. Klaus Lüning (1979) commented that kelp gametophytes were naturally ‘sticky’ and attach to substrata within ‘a short time’, potentially highlighting a natural and more cost-effective seeding technique. Here, we explored the natural adherence of Saccharina latissima gametophytes to aquaculture twine. Cultures were sprayed onto twine and left to adhere for eight increasing time periods, before being submerged in seawater and measured after 10 weeks of growth. Gametophytes were found to adhere and grow successfully on twine after immediate submergence in seawater, however significant differences in sporophyte lengths and density after 10 weeks growth were observed among time treatments. Sporophyte lengths and densities were found to be highest when the culture was left to adhere for 30 min prior to submergence in seawater, potentially highlighting a time-sensitive sweet spot for natural gametophyte seeding. Further, we confirm that Lüning's observation of kelp gametophytes sticking to substrata after a ‘short time’ was in fact ‘immediate’, thereby shorter than previously thought.<br/