bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying and Approaching Barriers to Environmental Flow Implementation Using Social–Ecological Systems Thinking
Authors: Grupper Madeline A. , Horne Avril C. , Webb J. Angus , Olden Julian 
Published: January 2025

ABSTRACTEnvironmental flows are a key tool for ensuring the sustainability of rivers, but successful implementation remains limited. Many barriers to implementation relate to the broader context of water management, social acceptance, or governance. Yet, there remains a disconnect between the social science and biophysical literature on environmental flows. This has led to widespread calls to bring social sciences into environmental flows. However, social science is a wide‐ranging discipline and there is no consensus on how its tools and concepts can assist environmental flows implementation. We examine the role of social–ecological systems (SES) and frameworks in guiding the links between social science and traditional environmental flow methods to best target implementation barriers. We concentrate on the characteristic ways in which SES frameworks interpret relationships in a system. We make the case for a greater focus on connecting environmental flow applications to broader SES and water management contexts during the design stages of environmental flow programs. We illustrate this with a case study from the Kaiela in south‐east Australia. Leveraging SES frameworks and characteristic thinking to complement environmental flows in these early stages can help identify potential barriers and where complementary social science efforts could improve implementation. Rather than expanding the scope of environmental flow assessments, this approach would contextualize them within sustainable water management efforts, forging better links to existing social science disciplines.
Measurement, self-similarity, and TNT equivalence of blasts from exploding wires
Authors: Morsel A. , Masi F. , Kotronis P. , Stefanou I. 
Published: January 2025

Abstract
Reduced-scale experiments offer a controlled and safe environment for studying the effects of blasts on structures. Traditionally, these experiments rely on the detonation of solid or gaseous explosive mixtures, with only limited understanding of alternative explosive sources. This paper presents a detailed investigation of the blasts produced by exploding aluminum wires for generating shock waves of controlled energy levels. We meticulously design our experiments to ensure a precise quantification of the underlying uncertainties and conduct comprehensive parametric studies. We draw practical relationships of the blast intensity with respect to the stand-off distance and the stored energy levels. The analysis demonstrates self-similarity of blasts with respect to the conventional concept of the scaled distance, a desirable degree of sphericity of the generated shock waves, and high repeatability. Finally, we quantify the equivalence of the reduced-scale blasts from exploding wires with high explosives, including TNT. This experimental setup and the present study demonstrate the high degree of robustness and effectiveness of exploding aluminum wires as a tool for controlled blast generation and reduced-scale structural testing.
Manuscript publication of abstracts presented at gynecologic surgery societies’ annual meetings
Authors: Fitzsimmons Kasey C. , Hamilton Kacey M. , Schneyer Rebecca J. , Toussia-Cohen Shlomi , Fan Shannon , Farsa Nikki R. , Levin Gabriel , Wright Kelly N. , Meyer Raanan 
Published: January 2025

Abstract

Purpose
To study characteristics and identify factors associated with full manuscript publication of oral abstracts presented at gynecologic surgery societies’ annual meetings.

Study design
We reviewed all oral abstracts presented at four major gynecologic surgery meetings in 2018. Oral abstracts subsequently published as peer-reviewed manuscripts were compared to those that were not published. Descriptive statistical analysis and multivariable regression analyses were conducted to identify factors associated with peer-reviewed manuscript publication.

Results
A total of 396 oral presentation abstracts from the four nationally recognized gynecologic societies were identified. The overall journal publication rate was 47.4% (188/396). The rate of publication of oral abstracts was 35.1% (72/205) for those presented at AAGL, 73.8% (62/84) for AUGS, 53.2% (42/79) for SGO and 42.9% (12/28) for SGS. In multivariable regression analysis, last author’s H-index [aOR 95% CI 1.02 (1.00–1.03)], academic center affiliation [aOR 95% CI 2.29 (1.20–4.37)], and randomized controlled trials [aOR 95% CI 2.47 (1.12–5.47)] were associated with journal publication. Of the published articles, the median time to publication was 3.0 years [1.0–5.0], the median journal impact factor was 3.9 [1.8–4.8], the median relative citation ratio was 1.0 [0.4–1.9], and the median number of citations per year was 2.0 [1.0–4.1].

Conclusions
In the field of gynecologic surgery, several factors, including the last researcher’s H-index, academic affiliation, randomized controlled trial design and type of societal meeting are associated with increased odds of an oral abstract ultimately reaching full manuscript peer-reviewed publication. These findings can serve researchers in the fields of gynecologic surgical subspecialties.
Deep learning and computer vision in plant disease detection: a comprehensive review of techniques, models, and trends in precision agriculture
Authors: Upadhyay Abhishek , Chandel Narendra Singh , Singh Krishna Pratap , Chakraborty Subir Kumar , Nandede Balaji M. , Kumar Mohit , Subeesh A. , Upendar Konga , Salem Ali , Elbeltagi Ahmed 
Published: January 2025

Abstract
Plant diseases cause significant damage to agriculture, leading to substantial yield losses and posing a major threat to food security. Detection, identification, quantification, and diagnosis of plant diseases are crucial parts of precision agriculture and crop protection. Modernizing agriculture and improving production efficiency are significantly affected by using computer vision technology for crop disease diagnosis. This technology is notable for its non-destructive nature, speed, real-time responsiveness, and precision. Deep learning (DL), a recent breakthrough in computer vision, has become a focal point in agricultural plant protection that can minimize the biases of manually selecting disease spot features. This study reviews the techniques and tools used for automatic disease identification, state-of-the-art DL models, and recent trends in DL-based image analysis. The techniques, performance, benefits, drawbacks, underlying frameworks, and reference datasets of more than 278 research articles were analyzed and subsequently highlighted in accordance with the architecture of computer vision and deep learning models. Key findings include the effectiveness of imaging techniques and sensors like RGB, multispectral, and hyperspectral cameras for early disease detection. Researchers also evaluated various DL architectures, such as convolutional neural networks, vision transformers, generative adversarial networks, vision language models, and foundation models. Moreover, the study connects academic research with practical agricultural applications, providing guidance on the suitability of these models for production environments. This comprehensive review offers valuable insights into the current state and future directions of deep learning in plant disease detection, making it a significant resource for researchers, academicians, and practitioners in precision agriculture.
Exploring the Correlation of Physiological Stress Signals with Student Exam Performance: A Preliminary Study
Authors: K. Kasap Ayşegül , Kurt Burçin 
Published: January 2025

Abstract
Stress responses in real-world settings are less studied compared to controlled laboratory environments, limiting our understanding of their impact on cognitive performance. This study investigates the relationship between physiological stress signals and academic performance using an open-access dataset of 10 students assessed across three exam sessions (Midterm 1, Midterm 2, and Final Exam). Physiological measures, including electrodermal activity (EDA), heart rate (HR), and skin surface temperature (TEMP), along with exam grades, were analyzed using traditional hypothesis testing, bootstrap method, correlation analysis, and regression tree modeling. To address the small sample size, we validated traditional hypothesis test results with the bootstrap method, and both approaches were compatible. Hypothesis testing revealed no significant differences in physiological measures across exam sessions, supporting the null hypothesis. Grades differed significantly between the final exam and both midterms (p < 0.05). Stress fluctuations were also analyzed across three periods (beginning, middle, and end) for each exam, revealing temporal response variations. Correlation analysis showed a moderate negative relationship between EDA and HR (r = − 0.504, p < 0.01) and a weak positive relationship between EDA and TEMP (r = 0.417, p < 0.05), both intensifying during the final exam. Regression analysis explained 78% of the variance in grades (R2 = 0.78), with regression tree modeling identifying lower skin temperature (< 28 °C) and higher EDA (≥ 0.19) as predictors of poorer performance. These findings underscore the interplay between physiological stress responses and academic outcomes, emphasizing the need for further research and interventions to support student success.
The associations of long-term physical activity in adulthood with later biological ageing and all-cause mortality – a prospective twin study
Authors: Kankaanpää Anna , Tolvanen Asko , Joensuu Laura , Waller Katja , Heikkinen Aino , Kaprio Jaakko , Ollikainen Miina , Sillanpää Elina 
Published: January 2025

Abstract
Objectives: The association between leisure-time physical activity (LTPA) and a lower risk of mortality is susceptible to bias from multiple sources. We investigated the potential of biological ageing to mediate the association between long-term LTPA and mortality and whether the methods used to account for reverse causality affect the interpretation of this association. Methods: Study participants were twins from the older Finnish Twin Cohort (n = 22,750; 18–50 years at baseline). LTPA was assessed using questionnaires in 1975, 1981 and 1990. The mortality follow-up lasted until 2020 and biological ageing was assessed using epigenetic clocks in a subsample (n = 1,153) with blood samples taken during the follow-up. Using latent profile analysis, we identified classes with distinct longitudinal LTPA patterns and studied differences in biological ageing between these classes. We employed survival models to examine differences in total, short-term and long-term all-cause mortality, and multilevel models for twin data to control for familial factors. Results: We identified four classes of long-term LTPA: sedentary, moderately active, active and highly active. Although biological ageing was accelerated in sedentary and highly active classes, after adjusting for other lifestyle-related factors, the associations mainly attenuated. Physically active classes had a maximum 7% lower risk of total mortality over the sedentary class, but this association was consistent only in the short term. After accounting for familial factors and excluding participants reporting prevalent cardiovascular diseases, LTPA exhibited less favourable associations with mortality. Conclusion: The association between LTPA and lower all-cause mortality may be largely due to genetic confounding and reverse causality.
Text mining technologies applied to free-text answers of students in e-assessment
Authors: Charitopoulos Angelos , Rangoussi Maria , Metafas Dimitris , Koulouriotis Dimitrios 
Published: January 2025

Abstract
Educational Text Mining is a rapidly growing field, thanks to the adoption of modern probabilistic and machine learning algorithms. The current study focuses on student e-assessment by means of open-ended questions that require free-text answers (i.e., student essays), whose analysis and evaluation are resource-demanding tasks for the instructor, even when supported by modern e-learning platforms. Topic modeling through the Latent Dirichlet Allocation algorithm is employed in an experimental setup, aiming to (a) extract meaningful topics from the body of pooled student answers (interpretable in the educational context of the course), (b) align the extracted topics with the ‘native’ internal structure of the body of texts, and (c) offer recommendations for the teacher in the form of alternative (meaningful) restructurings of the e-assessment units and consequently of the course content units. Quantitative and qualitative evaluation of the extracted topic models have yielded positive results regarding the first two aims, and as far as the third aim is concerned, the extracted topic models expilicitly suggest that the teacher should proceed with relevant restructurings of the course content. These recommendations are of practical use for the teacher, especially when the teacher seeks to restructure the content of the course towards either fewer or more internal units. In conclusion, topic modeling provides a spectrum of possibilities to the teacher who is interested in exploring ways to improve the structure and organization of a course.
Nanoscale interfacial tribology behavior between clay and sand: effects of cations, normal load and sliding velocity
Authors: He Zhenyu , Zheng Yuan-Yuan , Yin Zhen-Yu , Wei Pengchang 
Published: January 2025

Abstract
The interfacial tribology between clay and sand could significantly affect the mechanical stability of soil structures, while it remains unclear in the microscale. In this study, molecular dynamics (MD) simulation method has been employed to investigate the nanoscale friction behavior between quartz and montmorillonite at dry state, where quartz and montmorillonite are the common components of sand and clay, respectively. The effects of normal load, interlayer cations, and sliding velocity on their frictional behavior were discussed. The simulation results indicated that the stick–slip effect during friction process was gradually weakened with the increasing sliding velocity or decreasing normal load. The shear stress increased with the increasing normal load, exhibiting an approximately linear relationship. The order of friction coefficients of montmorillonite-quartz with different interlayer cations was Ca2+ > Zn2+ > Ni2+ > Pb2+ > Li+ > Rb+ > Cs+ > K+, illustrating that the friction coefficient of montmorillonite-quartz systems with divalent cations was greater than that with monovalent cations. The friction angle of montmorillonite-quartz with different interlayer cations varies from 6.96 to 17.28°. Moreover, the friction load rose linearly with the sliding velocity, indicating that nanoscale friction was velocity-dependent.
On the Changes of Residual Stress States of S550MC + 100Cr6 Cladded Steel Upon Tensile Deformation
Authors: Krochmal M. , Wegener T. , Zeisberg J. , Niendorf T. 
Published: January 2025

Abstract
The present study focuses on the evolution of residual stress (RS) and internal damage of a S550MC + 100Cr6 cladded steel after pre-deformation. Deformation-induced internal porosity was hardly found. RS depth profiles point at tensile RS in the 100Cr6 clad layer. These are most pronounced when minor pre-deformation levels are considered. A higher degree of deformation leads to reduced magnitudes of RS. This can be rationalized based on reduced differences in layer strength due to local strain hardening.
Data-driven modeling of staged planetary gearbox vibration signature
Authors: Graja Oussama , Ghorbel Ahmed , Hentati Taissir , Chaari Fakher , Walha Lassad , Jablonski Adam , Dziedziech Kajetan , Barszcz Tomasz , Haddar Mohamed 
Published: January 2025

Abstract
Modeling planetary gearboxes is an important field of research, since it helps in condition based monitoring of the system. Multiple models with different approaches were developed last decades. They showed interesting results, but they did not reflect all involved phenomena. Indeed, specifically in a complex rotating systems such as staged planetary gearboxes, those models only approximated the dynamic behavior of the investigated system. Hence, in this paper, an algorithm of modeling staged planetary gearbox vibration signature is proposed based on exclusively measured vibration signals. First, in section 2, the dynamic mode decomposition (DMD) will be introduced. Second, in section 3, the DMD algorithm will be implemented on simulated mathematical functions to prove its robustness on future state prediction. Then, in section 4, the experimental staged planetary gearbox test rig is presented. Finally, in section 5, the DMD algorithm is applied to multiple measured vibration signals with different operating conditions as given in section 4. Interesting results are conducted and limits of the approach are presented.
Time effect of elastic energy release of surrounding rock and evaluation method of reasonable advancing speed
Authors: Yuan Ruifu , Ma Qi , Zhang Qunlei , Feng Chun , Wei Chunfu , Gao Yan 
Published: January 2025

Abstract
To reveal the rock burst mechanism, the stress and failure characteristics of coal-rock strata under different advancing speeds of mining working face were explored by theoretical analysis, simulation, and engineering monitoring. The relationship between energy accumulation and release was analyzed, and a reasonable mining speed according to specific projects was recommended. The theoretical analysis shows that as the mining speed increases from 4 to 15 m/d, the rheological coefficient of coal mass ranges from 0.9 to 0.4, and the elastic energy of coal mass accumulation varies from 100 to 900 kJ. Based on the simulation, there is a critical advancing speed, the iteration numbers of simulation are less than 15,000 per mining 10 m coal seam, the overburden structure is obvious, the abutment pressure in coal mass is large, and the accumulated energy is large, which is easy to cause strong rock burst. When the iteration number is greater than 15,000, the static force of coal mass increases slightly, but there is no obvious rock burst. Based on engineering monitoring, the mining speed of a mine is less than 8 m/d, and the periodic weighting distance is about 17 m; as the mining speed is greater than 10 m/d, and the periodic weighting distance is greater than 20 m; as the mining speed is 3–8 m/d, and the range of high stress in surrounding rock is 48 m; as the advancing speed is 8–12 m/d, and the high-stress range in surrounding rock is 80 m. Moreover, as the mining speed is less than 8 cut cycles, the micro seismic energy is less than 10,000 J; as the mining speed is 12 cut cycles, the micro-seismic energy is about 20,000 J. In summary, the advancing speed is positively correlated with the micro seismic event; as the mining speed increases, the accumulated elastic energy of surrounding rock is greater, which is easy to cause rock burst. The comprehensive analysis indicates the daily advance speed of the mine is not more than 12 cut cycles.
Creating nature-based play settings for children through looking, listening, learning and modifying in a Swedish landscape laboratory
Authors: Mårtensson Fredrika , Wiström Björn , Hedblom Marcus , Litsmark Anna , Gabriel Amanda , Herngren Linnea , Ågren Josefin , Sang Åsa Ode 
Published: January 2025

Abstract
Children's outdoor play and access to nature are important for their health and development of environmental agency but there is a global decline of green spaces available to them. The aim is to explore the possibilities of creating nature-based outdoor settings for play and learning which benefit children as well as the wildlife and wider ecosystems. A fieldwork on developing nature based play settings in an outdoor landscape laboratory in Sweden involved university students (3 days) and children, two groups of 3–5 years olds (8 days) and one group of 6-year-olds (4 days). Field notes from ethnographic work was at the core of the process and involved practitioners and scholars in landscape architecture, vegetation design, ecology and environmental psychology. An iterative place-based process of learning guided the process, including following phases: (1) looking and listening attentive to the physical environment and to the children´s activities in a setting (2) transdisciplinary learning based on results from the analysis of field notes and the dialogues, and, (3) modifications of settings. In two of the five settings investigated an intervention to improve the setting was set up, followed by further investigations, illustrating the iterative character of the process with elements of co-creation. The results reveal the potentials in collaborative work setting out to develop features in nature as woodland, meadow, water and paths, so that they align well with children´s needs as well as nature conservation. The material should be useful in efforts to make natural environment more accessible to children and to the conceptual development of play biotopes, useful in the design and management of sustainable living environments.
Biochar-microplastics interaction modulates soil nitrous oxide emissions and microbial communities
Authors: Zou Ziheng , Yu Qidong , Chen Runyu , Wang Jinyang , Liu Xueyan 
Published: January 2025

Abstract
Biochar has been proposed as a soil amendment in vegetable fields, where the widespread use of plastic film leads to significant retention of microplastics (MPs) in the soil. However, the interactive effect of biochar and MPs on plant growth and soil functions remains poorly understood. Here, we conducted a pot experiment to examine the effects of biochar application in the presence of conventional and biodegradable microplastics (0.05% w/w) on the growth of coriander, soil nitrogen (N) cycling processes, and microbial communities. The results showed that biochar application increased aboveground biomass by increasing plant available N of NH4
+, regardless of the presence of MPs. Biochar also significantly reduced soil nitrous oxide (N2O) emissions by an average of 16% without MPs. However, when MPs were present, the effect of biochar on N2O emissions was lessened depending on the MP type. Polylactic acid consistently reduced soil N2O emissions and the abundance of N2O production genes, irrespective of biochar application. Conversely, polyethylene without biochar reduced N2O emissions primarily by inhibiting N-related functional genes responsible for nitrification and denitrification. This inhibitory effect was reversed when biochar was applied, leading to a 26% increase in N2O emissions due to increased nifH and nirK gene abundance. Although biochar and MPs did not significantly alter microbial α-diversity, they altered the composition and structure of bacterial and fungal communities, linked to changes in soil N turnover. Our study underscores the critical role of MP type in assessing the effects of biochar on soil N cycling and N2O emissions. Consequently, plastic pollution may complicate the ability of biochar to improve plant growth and soil functions, depending on the characteristics of the MPs.

Graphical Abstract