bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying the factors influencing the development of bilateral investment treaties with health safeguards: a Machine Learning-based link prediction approach
Authors: Lu Haohui , Thow Anne Marie , Patay Dori , Tissaoui Takwa , Frank Nicholas , Rippin Holly , Hoang Tien Dat , Gomes Fabio , Alschner Wolfgang , Uddin Shahadat 
Published: December 2024

Abstract
A network analysis approach, complemented by machine learning (ML) techniques, is applied to analyse the factors influencing Bilateral Investment Treaties (BITs) at the country level. Using the Electronic Database of Investment Treaties, BITs with health safeguards from 167 countries were charted, resulting in 534 connections with countries as nodes and their BITs as edges. Network analysis found that, on average, a country established BITs with six other nations. Additionally, we used node embedding techniques to generate features from the network, such as the Jaccard coefficient, resource allocation, and Adamic Adar for downstream link prediction. This study employed five tree-based ML models to predict future BIT formations with health inclusion. The eXtreme Gradient Boosting model proved to be superior, achieving a 64.02% accuracy rate. Notably, the Common Neighbor centrality feature and the Capital Account Balance Ratio emerged as influential factors in creating new BITs with health inclusions. Beyond economic considerations, our study highlighted a vital intersection: the nexus between BITs, economic growth, and public health policies. In essence, this research underscores the importance of safeguarding public health in BITs and showcases the potential of ML in understanding the intricacies of international treaties.
Direct-on-Filter FTIR Analysis of Respirable Crystalline Silica: A Field Study to Demonstrate Utility for Routine Non-regulatory Monitoring in Coal Mines
Authors: Elie Garek , Pandey Rohit , Sarver Emily Allyn 
Published: December 2024

AbstractCrystalline silica is generally considered the most hazardous constituent of respirable coal mine dust, and new federal rules are aimed at further limiting exposures in US mines. For regulatory purposes, respirable crystalline silica (RCS) is monitored by collecting filter samples, which are analyzed for quartz (the predominant form of RCS) by Fourier transform infrared spectroscopy (FTIR) in a centralized laboratory. To enable more timely results, NIOSH has developed a direct-on-filter (DOF) FTIR analysis method and free “FAST” software that can be used in the field. For samples collected under specific conditions, FAST processes the FTIR spectral data to determine quartz mass (and mass concentration with user inputted sampling duration and flow rate). The DOF FTIR method is not approved for regulatory RCS monitoring; however, it could be quite useful for routine non-regulatory monitoring. This field study demonstrates how the method (including FAST) could be applied for that purpose, specifically using low-cost and widely available sampling components (i.e., generic 3-piece styrene cassettes and an expandable cyclone-cassette holder assembly that is designed to be compatible with these cassettes). Moreover, to demonstrate how quartz percentage could be estimated in the field, sampling for this study included continuous personal dust monitors (CPDMs), which are designed to measure respirable dust mass concentration. While the DOF FTIR method enables field-measurement of quartz mass (and mass concentration) using a filter sample, field-measurement of the respirable dust mass (and mass concentration) on that filter sample is impractical. This would require determination of the total sample mass, which is typically done with a sensitive microbalance. Thus, the paired CPDM approach is presented workable solution.
Artificial intelligence and the social dimension of sustainable development: through a security perspective
Authors: Malmio Irja 
Published: December 2024

AbstractArtificial Intelligence (AI) has been described as a great hope but also a threat to fulfilling the social goals of sustainable development, where one critical aspect is providing society with a safe and secure environment. At the same time, interdisciplinary analyses that connect the social effects of artificial intelligence with security issues have been relatively sparse. Accordingly, this article explores how the sociotechnical connection between AI, the social dimension of sustainable development, and security is being communicated in research conceptualizing this liaison. Conducive to this aim, a scoping review has been applied to holistically connect AI, social sustainability, and security while deploying a thematic content analysis to illustrate the central themes of this intersection. In total, 62 articles and eleven reports were included in the study. Six themes are explored: AI for social good, economic security, development and humanitarian aid, values, sociotechnical harms, and societal security. The article emphasizes the importance of aligning technology development with broader social objectives by highlighting the complex interplay between AI, social sustainability, and security. Understanding this link opens possibilities for developing AI solutions that contribute to social sustainability while identifying propensities in emerging technologies that can lead to ‘‘sociotechnical harm’’ with increased polarization and a deteriorated security situation.
Adding human values on the deepfake: co-designing fact-checking solutions to combat misinformation
Authors: Maia C. H. , Ariel P. , Nunes S. 
Published: December 2024

AbstractThe proliferation of misinformation poses a significant challenge to societies, and fact-checking emerges as a critical tool to combat this issue. In this work, we conduct an innovation impact assessment to question the use of technology to combat misinformation, specifically examining the ethical implications of this choice. To address this, we organized a workshop using the value sensitive design (VSD) methodology to explore questions in this context. The workshop introduced participants to the VSD framework, enabling them to critically assess whether specific scenarios align with human values, norms, and requirements. Real-world scenarios were discussed, including approaches implemented by legitimate news outlets and using 3D virtual characters by a Brazilian television employing deep learning. Participants analyzed how technology impacts journalism values, norms, and practices, focusing on aligning synthetic media technologies with automated fact-checking dissemination. In conclusion, the authors prepared recommendations from valuable insights into the complex ethical considerations surrounding synthetic media technologies for automatic fact-checking dissemination. It also facilitated cross-border discussions, with 11 participants from seven countries engaging in fruitful dialogue on this vital topic. The study proposed evaluation criteria for AI-generated content in this diversity, including privacy protection, inclusiveness, transparency, beauty standards conformity, engagement, meaningfulness, and effortlessness.
Safe motion planning and formation control of quadruped robots
Authors: Ji Zongrui , Dong Yi 
Published: December 2024

AbstractThis paper introduces a motion planning and cooperative formation control approach for quadruped robots and multi-agent systems. First, in order to improve the efficiency and safety of quadruped robots navigating in complex environments, this paper proposes a new planning method that combines the dynamic model of quadruped robots and a gradient-optimized obstacle avoidance strategy without Euclidean Signed Distance Field. The framework is suitable for both static and slow dynamic obstacle environments, aiming to achieve multiple goals of obstacle avoidance, minimizing energy consumption, reducing impact, satisfying dynamic constraints, and ensuring trajectory smoothness. This approach differs in that it reduces energy consumption throughout the movement from a new perspective. Meanwhile, this method effectively reduces the impact of the ground on the robot, thus mitigating the damage to its structure. Second, we combine the dynamic control barrier function and the virtual leader-follower model to achieve efficient and safe formation control through model predictive control. Finally, the proposed algorithm is validated through both simulations and real-world scenarios testing.
Criteria for the choice and monitoring of Menopausal Hormone Therapy
Authors: Ruan Xiangyan , Mueck Alfred O. 
Published: December 2024

AbstractTo review the criteria for the selection of estrogens and especially progestogens for optimizing Menopausal Hormone Therapy (MHT). The main criteria are primarily derived from the Women's Health Initiative (WHI)-trial, disclosing the main risks like endometrial cancer, coronary heart disease (CHD), stroke, venous tromboembolism (VTE) and breast cancer. In addition observational studies must be considered for individualizing MHT, because WHI has tested only one preparation and has a lot of problems like early opening of the hormone/placebo-code (i.e., loss of placebo control), in 60% MHT-initiation too late, and in 40% risk factors for cardiovascular diseases and breast cancer. Pharmacological properties should be considered, such as only oral, but not transdermal estradiol increases VTE-risk. The choice of progestogens could be dependent on the different "partial effects" on steroid receptors, e.g., use of anti-androgenic progestogens in metabolic syndrome, Polycystic Ovary Syndrome (PCOS) etc., taking advantage of the anti-mineralocorticoid effect of drospirenone to stabilize blood pressure and reduce the risk of stroke, selection of tibolone for patients with sexual dysfunctions because its androgenic properties etc. Most important for the selection of the progestogen is endometrial efficacy, primary indication for progestogens in MHT. Therefore regular endometrial monitoring is reommended, using sequential or continuous combined regimens; "hormonal curettage" and/or the progestogen challenge text to avoid endometrial hyperproliferation. Levonorgestrel-IUD as progestogen component can reduce progestogen-dependent risks, offering also contraception, but often with longer bleeding problems, in contrast to sequential regimens of MHT, which can be used to treat irregular bleedings. Other main indications are treatment of climacteric complaints and prevention of osteoporosis and possible other preventive options. Regarding contraindications, according to the general rules of "class-labeling", they are the same for every MHT despite there are differences in benefits and risks. Choice of the timing of MHT-initiation is crucial to whether cardiovascular prevention (early start) or (like in WHI) increased risk of CHD and stroke occurs. The increased risk of breast cancer can be reduced using progesterone or its isomer dydrogesterone. Since, however, this risk cannot been excluded with any MHT, recommendations for screening on the possible development of breast cancer are given, on the basis of own recent research. Criteria for the selection of MHT are mainly to reduce possible risks as seen in WHI since for every MHT efficacy is good and essentially the same. Often the best choice is estradiol combined with progesterone or dydrogesterone, but also other progestogens should be considered including LNG-IUD, to optimize and individualize MHT.
Tide-river interaction in the Pechora Delta as revealed by new measurements and numerical modeling
Authors: Panchenko Evgeniya , Krylenko Inna , Alabyan Andrei 
Published: December 2024

AbstractThe Pechora is the greatest river of the European Russian Arctic, flowing into the Barents Sea. Its estuarine area includes a vast delta, represented by extensive lowlands that are dissected by the complicated network of arms and branches. Despite the Pechora Delta is considered to be microtidal, tides with a range of 0.5–1 m during the low water period have a significant impact on the nature of currents in the main branches and the distribution of runoff among them during the tidal cycle. Tidal sea level fluctuations as well as storm surges determine the reversing pattern of currents over a significant extent of the delta branches. The modern field equipment combined with 2D hydrodynamic modeling has allowed to understand the contemporary flow features and evaluate their possible alterations under climate changes. The climate impact under considered scenarios is more pronounced during the low flow period, and this can lead to the propagation of tidal currents and an increase in water levels in the city of Naryan-Mar (100 km upstream from the mouth). From a flood risk perspective, sea level rise can be offset by a reduction in flood runoff.
Reboundless design: towards the prevention of rebound effects by design
Authors: Pigosso Daniela C. A. 
Published: December 2024

Abstract
Society’s most well-intended efforts to solve sustainability challenges have not yet achieved the expected gains due to rebound effects (i.e., negative consequences of interventions arising from induced changes in system behaviour). Rebound effects offset about 40% of potential sustainability gains, but the understanding of design as a key leverage point for preventing rebound effects is still untapped. In this position paper, three fundamental scientific gaps hampering the prevention of rebound effects are discussed: (1) limited knowledge about the rebound effects triggered by efficiency–effectiveness–sufficiency strategies; (2) the influence of the counterintuitive behaviour of complex socio-technical systems in giving rise to rebound effects is not yet understood and (3) the bounded rationality within design limits the understanding of rebound effects at a broader systemic level. To address the aforementioned gaps, novel methodologies, simulation models and strategies to enable the design of reboundless interventions (i.e., products, product/service-systems and socio-technical systems that are resilient to rebound effects) are required. Building on the strong foundation of systems and design theory, this position paper argues for the need to bridge the interdisciplinary gap in the interplay of design and rebound effects, qualitative and quantitative models, engineering and social sciences, and theory and practice.
Identifying species traits that predict vulnerability to climate change
Authors: Fordham Damien A. 
Published: December 2024

Abstract
Accurately predicting the vulnerabilities of species to climate change requires a more detailed understanding of the functional and life-history traits that make some species more susceptible to declines and extinctions in shifting climates. This is because existing trait-based correlates of extinction risk from climate and environmental disturbances vary widely, often being idiosyncratic and context dependent. A powerful solution is to analyse the growing volume of biological data on changes in species ranges and abundances using process-explicit ecological models that run at fine temporal and spatial scales and across large geographical extents. These simulation-based approaches can unpack complex interactions between species’ traits and climate and other threats. This enables species-responses to climatic change to be contextualised and integrated into future biodiversity projections and to be used to formulate and assess conservation policy goals. By providing a more complete understanding of the traits and contexts that regulate different responses of species to climate change, these process-driven approaches are likely to result in more certain predictions of the species that are most vulnerable to climate change.
Functional stasis and changing habitat preferences among mammalian communities from the PETM of the Bighorn Basin, Wyoming
Authors: Whittingham Misha A.J.B. , Korasidis Vera A. , Fraser Danielle 
Published: December 2024

Abstract
The transition between the Paleocene and Eocene epochs (ca. 56 Ma) was marked by a period of rapid global warming of 5 °C to 8 °C following a carbon isotope excursion (CIE) lasting 200 ky or less referred to as the Paleocene-Eocene Thermal Maximum (PETM). The PETM precipitated a significant shift in the composition of North American floral communities and major mammalian turnover. We explored the ecological impacts of this phenomenon by analyzing 173 mammal species from the Bighorn Basin, Wyoming, USA, including their associated body alongside a database of 30 palynofloral localities as proxies for habitat. For each time bin, we calculated mean and median differences in body mass and habitat preference between significantly aggregated and segregated mammal species. Aggregated species showed significant similarity in habitat preference only prior to the PETM, after which habitat preference ceased to be a significant factor in community assembly. Our measures of differences in body mass space provide no evidence of a significant impact of competitive interactions on community assembly across the PETM, aligning with previous work. Our results indicate the persistence of a stable mammalian functional community structure despite taxonomic turnover, climate change and broadening habitat preferences.
The de-ideologization of welfare politics: Political governments’ social policy measures in eight welfare states during the COVID-19 pandemic
Authors: Peltoniemi Johanna , Ketonen Eeva-Leena , Hiilamo Heikki 
Published: December 2024

AbstractDuring the global COVID-19 pandemic, many countries have expanded the level and coverage of current social insurance and social assistance programs as well as implemented new programs. Based on three separate datasets, V-Dem V-Party dataset; fourteen structured expert interviews; and a dataset of 114 social security measures, we study the link between the welfare regime, pandemic-related social policy measures, and incumbents’ ideological stand. Does the pandemic-related social policy measures mirror the political attitudes of the incumbents? What role did the welfare regime play? We scrutinise eight OECD countries (Denmark, Finland, Germany, Netherlands, Norway, Sweden, UK, and the US) representing three different welfare regimes: corporatist-conservative countries, liberal countries, and socio-democratic countries. The key findings of this article show that the pandemic-related social policy measures did not mirror the political attitudes of the incumbents.
Constrained Precipitation Extremes Reveal Unequal Future Socioeconomic Exposure
Authors: Liu Ziyi , Yue Yao , Slater Louise , Borthwick Alistair G. L. , Chai Yuanfang , Luan Xiaofan , Miao Chiyuan , Yang Zhonghua 
Published: December 2024

AbstractExtreme precipitation can lead to major flooding, impacting human health and safety. Thus, reliable projections of population and GDP exposure to future extreme precipitation are imperative. Here, we quantify future precipitation characteristics from robust emergent constraint relationships between historical and future monthly precipitation extremes (99th percentile) across 19 CMIP6 models (r2 > 0.7 in 74–84% of 0.5° global land grids), and narrow uncertainty by 37.0–39.5% (absolute reduction being 0.753–0.774 mm/day). The constrained grid‐averaged future 99th percentile extreme is 6.96 ± 0.0059, 7.03 ± 0.0061, 7.11 ± 0.0063, and 7.29 ± 0.0067 mm/day, under SSP126, SSP245, SSP370, and SSP585, respectively, which exceeds historical extremes substantially in terms of intensity (12.9–19.7%) and frequency (1.6–2.3 times more). Future population and GDP exposed to 99th percentile extreme precipitation grow quickly, and are projected to exceed 1 million people in 27–40 countries and 10 billion USD (2005 Purchasing‐Power Parity) in 48–77 countries. Growth of future population exposure is dominated by an increase in extreme precipitation frequency rather than a rise in population, especially in developed countries. GDP exposure is controlled by the coupled effects of rapid socio‐economic development and significant shifts in precipitation frequency. Using indices of socio‐economic vulnerability, government effectiveness and economic freedom, we identify the unequal situation that high‐risk countries with high exposure are commonly characterized by low GDP per capita and high sociopolitical instability.
Characterization of Reflectance Signatures Within Above Anvil Cirrus Plumes in GOES‐16 Infrared and Visible Imagery
Authors: Murphy Kelley M. , Mecikalski John R. , Bedka Kristopher M. , Cooney John W. , Homeyer Cameron R. 
Published: December 2024

AbstractAbove anvil cirrus plumes (AACPs) form atop deep convective storm anvils. Storms containing AACPs are closely associated with surface severe weather. AACPs often reside in the lower stratosphere, and their microphysics are thought to be characterized by smaller ice particles with increased reflectance in shortwave infrared (SWIR) satellite imagery. This study aimed to determine which SWIR channels exhibit the strongest unique signatures over AACP lifetimes, assess how NEXRAD GridRad radar‐derived fields associated with severe weather relate to AACP presence and evolution, and take steps toward a red‐green‐blue (RGB) recipe to identify AACPs. AACPs and non‐plume anvil regions were labeled and analyzed using 5‐min resolution Geostationary Operational Environmental Satellites (GOES)‐16 Advanced Baseline Imager observations for five storms between 2019 and 2021. Considered were 0.64, 1.37, 1.6, 2.24, 3.9 μm reflectances, and 10.3 μm brightness temperatures (BTs). Results show: (a) higher median reflectance of accumulated AACPs in the 0.64, 1.37, and 2.24 μm channels compared to non‐plumes, (b) the 60−79° solar zenith angle bin contained the most data, corresponded with an afternoon peak in storm intensity, and contained a large plume to non‐plume pixel ratio, (c) increased lower stratosphere water vapor associated with AACPs impacted the 1.37 μm reflectance, leading to smaller, more reflective cloud ice particles than non‐plume regions, (d) GridRad radar 10‐ and 40‐dBZ echo heights and column maximum reflectivity (CMR) show AACPs coinciding with a secondary maximum in CMR, and (e) an RGB combining 1.37 μm, 0.64 μm + 3.9 μm reflectance, and 10.3 μm BT visually revealed AACPs.
Adaptively Implicit Advection for Atmospheric Flows
Authors: Weller Hilary , Kühnlein Christian , Smolarkiewicz Piotr K. 
Published: December 2024

AbstractImplicit time‐stepping for advection is applied locally in space and time where Courant numbers are large, but standard explicit time‐stepping is used for the remaining solution which is typically the majority. This adaptively implicit advection scheme facilitates efficient and robust integrations with long time‐steps while having negligible impact on the overall accuracy, and achieving monotonicity and local conservation on general meshes. A novel and important aspect for the efficiency of the approach is that only one iteration is needed each time the linear equation solver is called for solving the advection equation. The demonstration in this paper uses the second‐order Runge‐Kutta implicit/explicit time integration in combination with a second/third‐order finite‐volume spatial discretization and is tested using deformation flow tracer advection on the sphere and a fully compressible model for atmospheric flows. Tracers are advected over the poles of highly anisotropic latitude‐longitude grids with very large Courant numbers and on quasi‐uniform hexagonal and cubed‐sphere meshes with the same algorithm. Buoyant flow simulations with strong local updrafts also benefit from adaptively implicit advection. Stably stratified compressible flow simulations require a stable combination of implicit treatment of gravity and acoustic waves as well as advection in order to achieve long time‐steps.