bluuebunny/crossref_metadata_2025_split huggingface dataset:
Making Mindfulness Meditation a Healthy Habit
Authors: Miles Eleanor , Matcham Faith , Strauss Clara , Cavanagh Kate 
Published: November 2023

Abstract
Objectives
The benefits of mindfulness meditation can only be achieved if it is practiced, but health behavior research tells us that initiating and maintaining long-term behavior change is difficult. We propose that mindfulness meditation can be usefully viewed as a health behavior and that this perspective generates insights into how individuals can be supported to develop a healthy habit of mindfulness practice.

Method
We synthesize health behavior models with research on mindfulness practice and with mindfulness curricula to develop the Sussex Mindfulness MEDitation (SuMMed) model. This new theoretical model of mindfulness meditation as a health behavior outlines the stages individuals progress through as they develop a sustained habit of meditation and the processes that facilitate transition between these stages. We contextualize these processes within existing curricula and outline how they could be further supported.

Results
Our model generates a roadmap for future research as well as practical suggestions tailored to individuals at different stages of behavior change. In particular, our model highlights the need to support individuals to continue practice beyond formal instruction, and suggests how maintenance of a meditation habit could be facilitated.

Conclusions
Mindfulness meditation can be viewed as a health behavior, and understanding mindfulness practice through this lens can help bridge the challenges associated with developing and sustaining mindfulness practice.
Conditional cooperation and group size: experimental evidence from a public good game
Authors: Li Tianyi , Noussair Charles N. 
Published: November 2023

AbstractConditional cooperation is the tendency to cooperate if and only if others do so as well. It is the most common behavior in social dilemmas. We study how the incidence of conditional cooperation in the public goods game, the most widely studied social dilemma in experimental economics, varies with group size. In a laboratory experiment, we apply the strategy method to elicit how participants’ willingness to contribute to a public good depends on other group members’ decisions. A within-subject design allows us to evaluate and compare an individual participant's contribution behavior in different-sized groups. Two main findings emerge. First, the share of players who are conditional cooperators is consistent across group sizes. Second, the strategies chosen imply that conditional cooperators hold a (correct) belief that others are more cooperative in a larger than in a smaller group.
Field surveys in heterogeneous rock masses aimed at hydraulic conductivity assessment
Authors: Chicco Jessica Maria , Comina Cesare , Mandrone Giuseppe , Vacha Damiano , Vagnon Federico 
Published: November 2023

Abstract
In heterogeneous and fractured rock masses, joints are the most important elements controlling the hydraulic conductivity. Joints parameters are therefore crucial for estimating transport of mass and energy in many technical problems (e.g., slope stability, tunnels, geothermal and oil and gas studies). Hydraulic conductivity conceptual models follow well understood generalizations, but their quantitative estimation is not simple. Both laboratory and field tests have many limitations due to representativeness and scale effects. This study proposes a methodology for a preliminary hydraulic conductivity estimation in fractured and/or heterogeneous rock masses through a combination of in-situ geomechanical and geophysical measurements. Contact and no-contact geomechanical surveys were coupled with electric resistivity topographies in two selected test sites within a Mexican geothermal area in the framework of the Ge-Mex H2020 project. The test sites are representative of two different geological settings: a faulted rock mass with expected high hydraulic conductivity in proximity of the faulted areas and an abandoned marble quarry, with very good mechanical characteristics and negligible degree of fracturing. Moreover, both of them are located in remote areas with limited accessibility, in which rapid, time and cost-effective procedures are welcomed and recommended. The preliminary findings of this study were promising: estimated hydraulic conductivities were compared with independent laboratory measurements performed by other researchers showing a good correspondence and reliability. The proposed methodology demonstrated its reliability in decision making, in the technical support and its economical applicability also in similar difficult logistic situations.

Article Highlights

A combination of in-situ geomechanical and geophysical measurements was adopted for a preliminary hydraulic conductivity estimation;

Obtained field data were compared with independent laboratory estimations to assess the reliability of the proposed approach and compare representativeness and scale effects;

Even given the difficult logistic conditions and the limitations of the available comparisons the proposed methodology demonstrated its reliability in decision making.
Three-stage pyrolysis–steam reforming–water gas shift processing of household, commercial and industrial waste plastics for hydrogen production
Authors: Alshareef Rayed , Sait-Stewart Robert , Nahil Mohamad A. , Williams Paul T. 
Published: November 2023

AbstractFive common single plastics and nine different household, commercial and industrial waste plastics were processed using a three-stage (i) pyrolysis, (ii) catalytic steam reforming and (iii) water gas shift reaction system to produce hydrogen. Pyrolysis of plastics produces a range of different hydrocarbon species which are subsequently catalytically steam reformed to produce H2 and CO and then undergo water gas shift reaction to produce further H2. The process mimics the commercial process for hydrogen production from natural gas. Processing of the single polyalkene plastics (high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polypropylene (PP)) produced similar H2 yields between 115 mmol and 120 mmol per gram plastic. Even though PS produced an aromatic product slate from the pyrolysis stage, further stages of reforming and water gas shift reaction produced a gas yield and composition similar to that of the polyalkene plastics (115 mmol H2 per gram plastic). PET gave significantly lower H2 yield (41 mmol per gram plastic) due to the formation of mainly CO, CO2 and organic acids from the pyrolysis stage which were not conducive to further reforming and water gas shift reaction. A mixture of the single plastics typical of that found in municipal solid waste produced a H2 yield of 102 mmol per gram plastic. Knowing the gas yields and composition from the single plastics enabled an estimation of the yields from a simulated waste plastic mixture and a ‘real-world’ waste plastic mixture to be determined. The different household, commercial and industrial waste plastic mixtures produced H2 yields between 70 mmol and 107 mmol per gram plastic. The H2 yield and gas composition from the single waste plastics gave an indication of the type of plastics in the mixed waste plastic samples.
Graphical abstract
Revisioning and reinvigorating a hydrogeology distinguished lecture tour through learner-engaged workshops
Authors: Springer Abraham E. , Heimel Sierra , Riddell Jill L. , Dwyer Trevor , Fichera Marissa , Jones Michael , Kutsienyo Eusebius J. , Lilley Sara , Baude David 
Published: November 2023

AbstractAs geoscience and water related enrollment and degrees continue to decline, new methods are needed to recruit and engage students in these interesting and challenging interdisciplinary fields. An existing water-themed distinguished lecture tour was reinvented and reinvigorated to include a workshop to (1) promote interdisciplinary collaboration and (2) increase student engagement in earth sciences. The Geological Society of America has dedicated foundation support for a domestic and international lecture tour to promote the scientific discipline of hydrogeology. In addition to the lecture tour with a standard presentation and meetings with faculty, staff, and students, a half-day, interactive field demonstration of the inventory and assessment techniques for springs ecosystems was conducted at a spring near the lecture site. Local faculty hosts were encouraged to engage students in the planning and implementation of the demonstration workshop. The students were provided additional training to enter the interdisciplinary ecosystem data into a cloud-sourced database and to be actively engaged in producing a publication related to the springs ecosystems inventories and assessments. Of the participants of the demonstration workshops, students at eight of the host institutions became co-authors of the resulting manuscript. With the significant investment of time, resources, and logistics to implement a lecture tour, an additional interactive, hands-on, demonstration workshop is a cost-effective way to increase student engagement and provide interdisciplinary collaboration.
Changes in river systems and relevant hydrological responses in the Yangtze River Delta, China
Authors: Lin Zhixin , Xu Youpeng , Luo Shuang , Wang Qiang , Yu Zhihui 
Published: November 2023

AbstractRiver systems play an important role in the development of human society. However, they have been significantly affected by human activities, reducing the capacity for water supply, flood regulation, and aquatic ecosystem services. Identifying changes in river systems and hydrological responses to these changes is crucial for regional water management. In this study, based on the data derived from topographic maps of the 1960s, 1980s, and 2010s, we comprehensively quantified changes in river systems of the Yangtze River Delta (YRD), China. The results show that the density of rivers and the proportion of water surface decreased over the past several decades, while changes in the evolutionary coefficient of rivers and the ratio of area to length of rivers exhibited clear spatial differences. Low-grade rivers in urbanized areas have declined severely, leading to a simplification of river structure. Furthermore, the hydrological response to changes in the river system was revealed in the Taihu Lake Plain, an area of the YRD with a plain river network. A longitudinal functional connectivity index (LFCI) was adopted to assess the hydrological dynamics in water level, and it was found to have an increasing trend. In addition, the specific storage capacity (SSC) and the specific regulation capacity (SRC) were established to reveal the impact of changes in the structure and connectivity of the river system on the regulation and storage capacity, and both indicators exhibited a downward trend. Simulations based on the MIKE 11 model show that the reduction of tributaries across the region can result in an earlier peak timing and higher peak water level. Our results can support the development of river system protection and flood adaptation strategies in the delta plains.
Closing the domain gap: blended synthetic imagery for climate object detection
Authors: Kornfein Caleb , Willard Frank , Tang Caroline , Long Yuxi , Jain Saksham , Malof Jordan , Ren Simiao , Bradbury Kyle 
Published: November 2023

Abstract
Accurate geospatial information about the causes and consequences of climate change, including energy systems infrastructure, is critical to planning climate change mitigation and adaptation strategies. When up-to-date spatial data on infrastructure is lacking, one approach to fill this gap is to learn from overhead imagery using deep-learning-based object detection algorithms. However, the performance of these algorithms can suffer when applied to diverse geographies, which is a common case. We propose a technique to generate realistic synthetic overhead images of an object (e.g., a generator) to enhance the ability of these techniques to transfer across diverse geographic domains. Our technique blends example objects into unlabeled images from the target domain using generative adversarial networks. This requires minimal labeled examples of the target object and is computationally efficient such that it can be used to generate a large corpus of synthetic imagery. We show that including these synthetic images in the training of an object detection model improves its ability to generalize to new domains (measured in terms of average precision) when compared to a baseline model and other relevant domain adaptation techniques.
A Preliminary Study Connecting School Improvement and MTSS With Student Outcomes
Authors: Bohanon Hank S. , Wu Meng-Jia , Kushki Ali , LeVesseur Cheyne 
Published: November 2023

AbstractSchools have an increased focus on implementing schoolwide initiatives (e.g., multi-tiered systems of support; MTSS) to address risk factors related to dropping out. These interventions can involve multiple domains, including academic, behavioural, and social and emotional supports. Although researchers suggest that schoolwide interventions are effective, school staff may need help implementing various content (e.g., academic, behaviour) domains into a cohesive plan. This preliminary study focused on nine schools in the Midwestern United States that implemented schoolwide interventions as part of a statewide technical assistance approach. The research included using survey and extant data for all students to determine the connections between schoolwide interventions, school improvement, and student outcomes. Schools in this study that were higher on both school improvement and MTSS implementation had, in general, better student outcomes associated with predictors of dropping out of school. These findings indicate that school improvement and MTSS may be mutually beneficial enterprises that help school staff address factors related to dropping out.
Apples to advocacy: Evaluating consumer preferences for hard cider policies
Authors: Staples Aaron J. , Howard Philip H. , Conner David S. , Sirrine J. Robert , Ostrom Marcia R. , Miller Michelle 
Published: November 2023

AbstractHard cider is a sector of a maturing craft beverage industry that continues to experience growth in the United States. Cider is also experiencing challenges, however, such as competition from other alcohol markets, changing consumer preferences, the supply chain, and inflationary pressures. National policy changes may help promote more optimal outcomes for this sector, but public support is important to policy formation. This study uses survey data from a best-worst scaling experiment of consumers in four leading cider-producing states (Michigan, Washington, Wisconsin, and Vermont) to understand preferences toward ten broad cider policy initiatives. The results of multinomial logistic modeling reveal that consumers prefer policies mandating ingredients, nutrition facts, and allergen labeling across all ciders. The least preferred policy initiatives include allowing producers to use vintage on labeling and funding regional cider development. These results have important implications for stakeholders across the industry, including the benefits of labeling disclosures in marketing and the need to improve public awareness of barriers to cider industry development.
How to Save Pascal (and Ourselves) From the Mugger
Authors: Hiller Avram , Hasan Ali 
Published: November 2023

Abstract
In this article, we re-examine Pascal's Mugging, and argue that it is a deeper problem than the St. Petersburg paradox. We offer a way out that is consistent with classical decision theory. Specifically, we propose a “many muggers” response analogous to the “many gods” objection to Pascal's Wager. When a very tiny probability of a great reward becomes a salient outcome of a choice, such as in the offer of the mugger, it can be discounted on the condition that there are many other symmetric, non-salient rewards that one may receive if one chooses otherwise.
Online gait learning with Assist-As-Needed control strategy for post-stroke rehabilitation exoskeletons
Authors: Zou Chaobin , Zeng Chao , Huang Rui , Peng Zhinan , Zhang Jianwei , Cheng Hong 
Published: November 2023

AbstractLower limb exoskeletons (LLEs) have demonstrated their potential in delivering quantified repetitive gait training for individuals afflicted with gait impairments. A critical concern in robotic gait training pertains to fostering active patient engagement, and a viable solution entails harnessing the patient’s intrinsic effort to govern the control of LLEs. To address these challenges, this study presents an innovative online gait learning approach with an appropriate control strategy for rehabilitation exoskeletons based on dynamic movement primitives (DMP) and an Assist-As-Needed (AAN) control strategy, denoted as DMP-AAN. Specifically tailored for post-stroke patients, this approach aims to acquire the gait trajectory from the unaffected leg and subsequently generate the reference gait trajectory for the affected leg, leveraging the acquired model and the patient’s personal exertion. Compared to conventional AAN methodologies, the proposed DMP-AAN approach exhibits adaptability to diverse scenarios encompassing varying gait patterns. Experimental validation has been performed using the lower limb rehabilitation exoskeleton HemiGo. The findings highlight the ability to generate suitable control efforts for LLEs with reduced human-robot interactive force, thereby enabling highly patient-controlled gait training sessions to be achieved.
Introduction: the material culture of public space in early modern Europe
Authors: Nevola Fabrizio 
Published: November 2023

AbstractThis special issue draws on new research conducted by the PUblic REnaissance: Urban Cultures of Public Space between Early Modern Europe and the Present project, funded by the Humanities in the European Research Area (see: www.hiddencities.eu). The project considers how public spaces, from street corners to major city squares, were shaped by the everyday activities of ordinary city dwellers between 1450 and 1700. We have focused on the urban fabric, and the ways in which meanings are attached to specific sites in the city (and objects in museum collections) that are often overlooked – the material culture of public space. Our themes are familiar to urban historians – sociability, the circulation of knowledge, information or gossip, authority and its contestation – although by moving between textual sources, maps, the built fabric and museum artefacts, our interdisciplinary and cross-Europe approach is structured around material objects in the early modern period.
Data-to-text generation using conditional generative adversarial with enhanced transformer
Authors: Seifossadat Elham , Sameti Hossein 
Published: November 2023

AbstractIn this paper, we propose an enhanced version of the vanilla transformer for data-to-text generation and then use it as the generator of a conditional generative adversarial model to improve the semantic quality and diversity of output sentences. Specifically, by adding a diagonal mask matrix to the attention scores of the encoder and using the history of the attention weights in the decoder, this enhanced version of the vanilla transformer prevents semantic defects in the output text. Also, using this enhanced transformer along with a triplet network, respectively, as the generator and discriminator of conditional generative adversarial network, diversity and semantic quality of sentences are guaranteed. To prove the effectiveness of the proposed model, called conditional generative adversarial with enhanced transformer (CGA-ET), we performed experiments on three different datasets and observed that our proposed model is able to achieve better results than the baselines models in terms of BLEU, METEOR, NIST, ROUGE-L, CIDEr, BERTScore, and SER automatic evaluation metrics as well as human evaluation.
Legislative Civility, Gridlock, Polarization, and Productivity
Authors: Schreckhise William D. , Pierce John C. , Benjamin Francis A. , Lovrich Nicholas P. , Button Eric 
Published: November 2023

AbstractThis article examines the relationship between legislative civility and legislative productivity in US state legislatures. The research employs data from the National Survey of State Legislative Lobbyists and from the State Policy Innovation and Diffusion (SPID) database. The former dataset is used to generate an overall civility index for each state as developed by Kettler et al. The SPID database allows one to measure the legislative productivity of a state legislature. Employing these data, negative binomial and Poisson regression models reveal that state legislatures rated as more civil by their own lobbyists produced significantly more pieces of noteworthy legislation than those legislative bodies rated as less civil. These results suggest that the quality of internal legislative dynamics matters for legislative productivity.
Probabilistic Intraday Wastewater Treatment Plant Inflow Forecast Utilizing Rain Forecast Data and Sewer Network Sensor Data
Authors: Sonnenschein Björn , Ziel Florian 
Published: November 2023

AbstractForecasting of wastewater treatment plant inflow dynamics constitutes an enabler technology for wastewater treatment process optimization using model predictive control. However, accurate inflow prediction is still challenging, especially for strong rainfall events, where complex system dynamics and missing information on future rainfall represent limiting factors. We propose a seasonal probabilistic time series model for modeling the short‐term wastewater inflow accurately while providing quantification of forecast uncertainty. To ensure suitability for practical implementation, the unconstrained parameters of the predictive distribution are modeled as linear functions of the input variables in the framework of Generalized Additive Models for Location Scale and Shape. Non‐linear effects are approximated by Rectified Linear Units, accounting for buffering within the sewer network and flow‐dependent catchment response time. In addition to water level measurements from within the sewer network and rain rate measurements, rain forecasts are incorporated as exogenous regressors, where historical rain forecasts are used for model calibration. The model performance is evaluated on historical data from a German wastewater treatment plant using deterministic and probabilistic scoring rules. We benchmark against an autoregressive time series model and a long short‐term memory artificial neural network. Our results show that the proposed model unites the benefits of high prediction accuracy of the neural network and enhanced intelligibility of the autoregressive model, but accurate real‐time rain forecasts are mandatory for successful real‐world implementation.