bluuebunny/crossref_metadata_2025_split huggingface dataset:
A practical method for integrating community priorities in planning and implementing cancer control programs
Authors: Bilenduke Emily , Dwyer Andrea J. , Staples Elsa S. , Kilbourn Kristin , Valverde Patricia A. , Fernández Maria E. , Risendal Betsy C. 
Published: April 2023

Abstract
Purpose
Community engagement is essential in effective public health programs. This paper illustrates the methods used to engage community in the development of a multi-level implementation intervention to address cancer disparities related to hereditary cancer syndromes.

Methods
Implementation Mapping (IM), was used to guide the co-creation of an intervention. Key partners were recruited to a 13-member statewide community advisory board (CAB) representing healthcare and community-based organizations. As part of a needs assessment, a 3-round modified Delphi method with the CAB was used to identify implementation outcomes to use in later steps of IM. An anonymous online survey of a validated community engagement measure assessed CAB members’ satisfaction with the process.

Results
Using a modified Delphi method as part of the needs assessment of IM, the CAB identified three broad categories of strategies: Changing infrastructure using patient navigation; training and educating patients, navigators and providers; and supporting clinicians in case identification and management. Self-reported satisfaction with the IM and Delphi process was high.

Conclusions
Implementation Mapping facilitated the use of available evidence, new data, and community engagement to identify strategies to improve the delivery of programs to reduce hereditary cancer disparities. The modified Delphi method was easy to administer in a virtual environment and may be a useful for others in community-engaged research.
The phase-space architecture in extrasolar systems with two planets in orbits of high mutual inclination
Authors: Mastroianni Rita , Efthymiopoulos Christos 
Published: April 2023

AbstractWe revisit the secular 3D planetary three-body problem, aiming to provide a unified formalism representing all basic phenomena in the phase space as the mutual inclination between the planetary orbits increases. We propose a ‘book-keeping’ technique allowing to decompose the Hamiltonian as $$\mathcal {H}_\textrm{sec}=\mathcal {H}_\textrm{planar}+\mathcal {H}_\textrm{space}$$

H
sec

=

H
planar

+

H
space

, with $$\mathcal {H}_\textrm{space}$$

H
space

collecting all terms depending on the planets mutual inclination $$i_\textrm{mut}$$

i
mut

. We numerically compare several models obtained by multipole (Legendre) or Laplace–Lagrange expansions of $$\mathcal {H}_\textrm{sec}$$

H
sec

, aiming to define suitable truncation orders for these models. We explore the transition, as $$i_\textrm{mut}$$

i
mut

increases, from a ‘planar-like’ to a ‘Lidov–Kozai’ regime. Using a numerical example far from hierarchical limits, we find that the structure of the phase portraits of the (integrable) planar case is reproduced to a large extent also in the 3D case. A semi-analytical criterion allows to estimate the level of $$i_\textrm{mut}$$

i
mut

up to which the dynamics remains nearly integrable. We propose a normal form method to compute the basic periodic orbits (apsidal corotation orbits A and B) in this regime. We explore the sequence of saddle-node and pitchfork bifurcations by which the A and B families are connected to the highly inclined periodic orbits of the Lidov–Kozai regime. Finally, we perform a numerical study of phase portraits for different planetary mass and distance ratios and qualitatively describe the approach to the corresponding hierarchical limits.
The persistence of the critically endangered Asiatic cheetah relies upon urgent connectivity protection: a landscape genetics perspective
Authors: Khalatbari Leili , Godinho Raquel , Abolghasemi Hamed , Hakimi Ehsan , Ghadirian Taher , Jowkar Houman , Breitenmoser Urs , Brito José Carlos 
Published: April 2023

AbstractDecreasing genetic diversity, gene flow rates and population connectivity can increase inbreeding rates and extinction risks. Asiatic cheetah is a critically endangered mammal with large home range that suffered from extreme range reduction and population decline. Their population is now fragmented into two subpopulations. We used genetic markers to estimate genetic diversity, relatedness, minimum effective population size and gene flow, and to assess population structure. Putative corridors connecting subpopulations were inferred using connectivity models based on topography, land cover and human footprints resistance variables. Individual pairwise genetic relatedness was compared with resistance values obtained from these models and with Euclidean distances between samples to assess the most important factors shaping the current genetic structure. The estimated effective population size was extremely low (Ne = 11 to 17). Both Northern and Southern Subpopulations exhibited low genetic diversity and high relatedness. Several signatures of gene flow and movement of individuals between subpopulations were observed suggesting that inferred corridors potentially connecting subpopulations are functional. However, no traces of gene flow were observed for the latest generations, maybe due to a decrease of functional connectivity in recent years. The resistance model including all variables was best related to genetic relatedness, whereas population differentiation is mostly driven by isolation by distance. The very low estimated effective population size, decreased genetic diversity, and high relatedness of Asiatic cheetah suggests that population reinforcement, removing obstacles to connectivity and boosting prey population conservation in stepping stones are urgently needed to prevent the imminent extinction of iconic biodiversity.
Making Crime Visible in the Digital Age: The Ethnomethods of Data Policing
Authors: Buscariolli André 
Published: April 2023

AbstractAs digitalization advances, police officers can rely on data traces to expand their capacity to infer suspicion. Despite reasonably warning about the potentially intrusive and prejudicial character of data-driven policing techniques, criminal justice scholars have yet to engage with the epistemological bases by which officers make deductions from data, including concerning legal admissibility. This article proposes that examining data policing using thick descriptive accounts of lived police work provides insights into police officers’ judgments of what constitutes “reasonably objective” crime analysis. Drawing from ethnomethodology’s contributions to police work and technological practices, I examine how the symbolic processes by which officers highlight criminologically relevant phenomena from seemingly decontextualized data points reproduce and reshape long-established methodical police work.
The role of live transcripts in synchronous online L2 classrooms: Learning outcomes and learner perceptions
Authors: Qiao Wang , Yijun Chen 
Published: April 2023

AbstractThis study explored the role of live transcripts in online synchronous academic English classrooms by focusing on how automatically generated live transcripts influence the learning outcomes of lower-proficiency and higher-proficiency learners and on their perceptions towards live transcripts. The study adop ted a 2 × 2 factorial design, with the two factors being learner proficiency (high vs. low) and availability of live transcription (presence and absence). The participants were 129 second-year Japanese university students from four synchronous classes taught on Zoom by the same teacher under an academic English reading course. Learning outcomes in this study were evaluated according to the course syllabus through grades and participation in class activities. A questionnaire consisting of nine Likert-scale questions and a comment box was administered to explore participants’ perceived usefulness of, perceived ease of use of, and perceived reliance on live transcripts. Results showed that contrary to previous studies reporting the effectiveness of captioned audiovisual materials in L2 learning, live transcripts as a special type of captions were not effective in promoting the grades of learners of either proficiency. However, it significantly improved the activity participation of lower-proficiency learners, but not that of higher-proficiency learners. Questionnaire results showed that there were no significant differences between learners of two proficiencies in their perceptions towards live transcription, which contradicts previous findings that lower-proficiency learners tend to rely more on captions. Besides enhancement of lecture comprehension, participants reported innovative uses of live transcripts such as screenshots with transcripts for notetaking purposes and transcripts downloaded for later review.
A new hazard assessment workflow to assess soil contamination from large and artisanal scale gold mining
Authors: Thiombane Matar , De Vivo Benedetto , Niane Birane , Watts Michael J. , Marriott Andrew L. , Di Bonito Marcello 
Published: April 2023

AbstractGold mining activities are undertaken both at large and artisanal scale, often resulting in serious ‘collateral’ environmental issues, including environmental pollution and hazard to human and ecosystem health. Furthermore, some of these activities are poorly regulated, which can produce long-lasting damage to the environment and local livelihoods. The aim of this study was to identify a new workflow model to discriminate anthropogenic versus geogenic enrichment in soils of gold mining regions. The Kedougou region (Senegal, West Africa) was used as a case study. Ninety-four soil samples (76 topsoils and 18 bottom soils) were collected over an area of 6,742 km2 and analysed for 53 chemical elements. Robust spatial mapping, compositional and geostatistical models were employed to evaluate sources and elemental footprint associated with geology and mining activities. Multivariate approaches highlighted anomalies in arsenic (As) and mercury (Hg) distribution in several areas. However, further interpretation with enrichment factor (EFs) and index of geoaccumulation (IGeo) emphasised high contamination levels in areas approximately coinciding with the ones where artisanal and small scale mining (ASGM) activities occur, and robust compositional contamination index (RCCI) isolated potentially harmful elements (PHE) contamination levels in very specific areas of the Kedougou mining region. The study underlined the importance of complementary approaches to identify anomalies and, more significantly, contamination by hazardous material. In particular, the analyses helped to identify discrete areas that would require to be surveyed in more detail to allow a comprehensive and thorough risk assessment, to investigate potential impacts to both human and ecosystem health.
Integrating human values in software development using a human values dashboard
Authors: Nurwidyantoro Arif , Shahin Mojtaba , Chaudron Michel , Hussain Waqar , Perera Harsha , Shams Rifat Ara , Whittle Jon 
Published: April 2023

AbstractThere is a growing awareness of the importance of human values in software systems. However, limited tools are available to support the integration of human values during software development. Most of these tools are focused on concepts related to specific, well-known human values (e.g., privacy, security) in software engineering. This paper aims to (partially) address this gap by developing a human values dashboard. We conducted a multi-stage study to design, implement and evaluate a human values dashboard. First, an exploratory study was conducted by interviewing 15 software practitioners to investigate the possibility of using a human values dashboard to help address human values in software development, its potential benefits, and required features. Second, we experimented with four Machine Learning approaches to detect the presence of human values in issue discussions. We used the best approach to develop a human values dashboard for software development. The dashboard displays whether any human values are present in each issue discussion. Finally, we interviewed ten different practitioners to investigate the usefulness of the dashboard in practice. This study found that the human values dashboard could help raise awareness, focus attention, and prioritise issues based on the presence of values. This study also identified two potential challenges to the adoption of the dashboard. First, the possible incorrect issues description that can mislead the automated values identification in the dashboard. Second, the lack of willingness of a company to adopt the dashboard.
Knowing Food: Sustainability Politics, Food Policy Councils and the Co-Production of Knowledge
Authors: Schiller-Merkens Simone , Machin Amanda 
Published: April 2023

Abstract
As one of the major causes of climate change, there is an urgent need for a fundamental transformation of the food system. Calls for greater sustainability underscore the importance of integrating civil society and the local knowledge of citizens in this transformation process. One increasingly relevant organisation that can actively engage a plurality of actors from across civil society is the Food Policy Council (FPC). In this paper, we explore the potential role of FPCs in sustainability politics to create an alternative food system, with a focus on the co-production of knowledge for policy-making. We propose that the co-production of knowledge requires knowledge inclusion, exchange and transmission, and we focus on the challenges that can arise for FPCs. Our paper shows that bottom-up emerging FPCs constitute a new form of alternative food organisation that can integrate and support the critical capacity of civil society in food system transformation, but also face potential struggles in the co-production of knowledge for sustainable food policy-making. The paper further highlights that co-producing knowledge in and for sustainability transformation is fundamentally a political process, with politics broadly conceived. It not only has relevance for the institutions of formal politics, but emerges in and is intrinsically linked to the grassroots collective action of contentious and prefigurative politics in civil society. FPCs (re)politicise food by combining these various kinds of sustainability politics, which constitutes their transformative potential.
Links of positive affect and stress to HbA1c: a prospective longitudinal study
Authors: Horner Fiona S. , Helgeson Vicki S. , Korytkowski Mary T. 
Published: April 2023

AbstractWhile affect is linked to a number of diabetes outcomes, the specific role of positive affect (PA) in HbA1c remains unclear. The present study examined whether PA prospectively predicted lower HbA1c among adults with type 2 diabetes and whether this relation was moderated by stress. Participants were 123 adults (44.7% female; 60.2% White, 39.8% Black) recently diagnosed with type 2 diabetes. Perceived stress, diabetes-specific distress, and PA were assessed at baseline; HbA1c was assessed at baseline (T1), six months (T2), and five years (T3). PA was cross-sectionally associated with lower HbA1c at T1 and prospectively predicted lower HbA1c at T3. PA interacted with both measures of T1 stress to predict T1 HbA1c, and PA interacted with T3 perceived stress to predict T3 HbA1c. Interactions were consistent with stress buffering. Sensitivity analyses attentuated findings, but robust evidence remained for PA as a protective factor for blood glucose five years later and for a stress-buffering effect of PA on diabetes-specific distress. Findings suggest PA may be a clinically useful indicator among adults with type 2 diabetes and may be particularly important for those experiencing the greatest stress from their disease.
Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast
Authors: Parker Kai , Erikson Li , Thomas Jennifer , Nederhoff Kees , Barnard Patrick , Muis Sanne 
Published: April 2023

AbstractA 38-year hindcast water-level product is developed for the US Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water-level modeling framework utilized in this study combines a global-scale hydrodynamic model (Global Tide and Surge Model, GTSM-ERA5), a novel ensemble-based tide model, a parameterized wave setup model, and statistical corrections applied to improve modeled water-level components. Corrected water-level data are found to be skillful, with an RMSE of 13 cm, when compared to observed water-level measurement at tide gauge locations. The largest errors in the hindcast are location-based and typically found in the tidal component of the model. Extreme water levels across the region are driven by compound events, in this case referring to combined surge, tide, and wave forcing. However, the relative importance of water-level components varies spatially, such that tides are found to be more important in the center of the study region, non-tidal residual water levels to the north, and wave setup in the north and south. Hurricanes drive the most extreme water-level events within the study area, but non-hurricane events define the low to mid-level recurrence interval water-level events. This study presents a robust analysis of the complex oceanographic factors that drive coastal flood events. This dataset will support a variety of critical coastal research goals including research related to coastal hazards, landscape change, and community risk assessments.
Assessing the effectiveness of landslide slope stability by analysing structural mitigation measures and community risk perception
Authors: Kamal A. S. M. Maksud , Hossain Farhad , Ahmed Bayes , Rahman Md. Zillur , Sammonds Peter 
Published: April 2023

AbstractRainfall-induced landslides seriously threaten hilly environments, leading local authorities to implement various mitigation measures to decrease disaster risk. However, there is a significant gap in the current literature regarding evaluating their effectiveness and the associated community risk perception. To address this gap, we used an interdisciplinary and innovative approach to analyse the slope stability of landslides, evaluate the effectiveness of existing structural mitigation measures, and assess the risk perception of those living in danger zones. Our case study focused on the Kutupalong Rohingya Camp (KRC) in Cox’s Bazar, Bangladesh, which is home to over one million Rohingya refugees from Myanmar. Although various structural and non-structural countermeasures were implemented in the KRC to mitigate the impact of landslides, many of them failed to prevent landslides from occurring. We utilised a variety of methods from the physical sciences, including the infinite slope, limit equilibrium (LEM), and finite element (FEM) approaches, to calculate the factor of safety (FoS) for specific slopes. Additionally, in the social sciences domain, we conducted a questionnaire survey of approximately 400 Rohingya participants to assess the community’s perception of the interventions and the degree of disaster risk. Our findings indicated that slopes with a gradient greater than 40° were unstable (FoS < 1), which was present throughout the entire KRC area. The effectiveness of the LEM and FEM methods was evaluated for four dominant slope angles (40°, 45°, 50°, and 55°) under varying loads (0, 50, and 100 kN/m2). The slopes were found to be stable for lower slope angles but unstable for higher slope angles (> 50°) and increased overburden loads (50–100 kN/m2). Different mitigation measures were tested on the identified unstable slopes to assess their effectiveness, but the results showed that the countermeasures only provided marginal protection against landslides. Survey results revealed that at least 70% of respondents believed that concrete retaining walls are more effective in reducing landslide occurrence compared to other measures. Additionally, about 60% of the respondents questioned the reliability of the existing structural mitigation measures. The study also found that the cohesion and friction angle of lower sandstone and the cohesion of upper soil layers are important factors to consider when designing and implementing slope protection countermeasures in the KRC area.
Predicting the ripening time of ‘Hass’ and ‘Shepard’ avocado fruit by hyperspectral imaging
Authors: Han Yifei , Bai Shahla Hosseini , Trueman Stephen J. , Khoshelham Kourosh , Kämper Wiebke 
Published: April 2023

AbstractPredicting the ripening time of avocado fruit accurately could improve fruit storage and decrease food waste. No reasonable method exists for predicting the postharvest ripening time of avocado fruit during transport, storage or retail display. Here, hyperspectral imaging ranging from 388 to 1005 nm with 462 bands was applied to 316 ‘Hass’ and 160 ‘Shepard’ mature, unripe avocado fruit to predict how many days it took for individual fruit to become ripe. Three models were developed using partial least squares regression (PLSR), deep convolutional neural network (DCNN) regression and DCNN classification. Our PLSR models provided coefficients of determination (R2) of 0.76 and 0.50 and root mean squared errors (RMSE) of 1.20 and 1.13 days for ‘Hass’ and ‘Shepard’ fruit, respectively. The DCNN-based regression models produced similar results with R2 of 0.77 and 0.59, and RMSEs of 1.43 and 0.94 days for ‘Hass’ and ‘Shepard’ fruit, respectively. The prediction accuracies and RMSEs from DCNN classification models, respectively, were 67.28% and 1.52 days for ‘Hass’ and 64.06% and 1.03 days for ‘Shepard’. Our study demonstrates that the spectral reflectance of the skin of mature, unripe ‘Hass’ and ‘Shepard’ fruit provides adequate information to predict ripening time and, thus, has the potential to improve postharvest processing and reduce postharvest losses of avocado fruit.
Trust-Region Adaptive Frequency for Online Continual Learning
Authors: Kong Yajing , Liu Liu , Qiao Maoying , Wang Zhen , Tao Dacheng 
Published: April 2023

AbstractIn the paradigm of online continual learning, one neural network is exposed to a sequence of tasks, where the data arrive in an online fashion and previously seen data are not accessible. Such online fashion causes insufficient learning and severe forgetting on past tasks issues, preventing a good stability-plasticity trade-off, where ideally the network is expected to have high plasticity to adapt to new tasks well and have the stability to prevent forgetting on old tasks simultaneously. To solve these issues, we propose a trust-region adaptive frequency approach, which alternates between standard-process and intra-process updates. Specifically, the standard-process replays data stored in a coreset and interleaves the data with current data, and the intra-process updates the network parameters based on the coreset. Furthermore, to improve the unsatisfactory performance stemming from online fashion, the frequency of the intra-process is adjusted based on a trust region, which is measured by the confidence score of current data. During the intra-process, we distill the dark knowledge to retain useful learned knowledge. Moreover, to store more representative data in the coreset, a confidence-based coreset selection is presented in an online manner. The experimental results on standard benchmarks show that the proposed method significantly outperforms state-of-art continual learning algorithms.