bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antenatal pyelonephritis: a three-year retrospective cohort study of two Irish maternity centres
Authors: Barry Rachel , Houlihan Elaine , Knowles Susan J. , Eogan Maeve , Drew Richard J. 
Published: May 2023

Abstract
Pyelonephritis affects 1–2% of pregnant women, and is associated with significant maternal and fetal morbidity. Antenatal pyelonephritis has been associated with PPROM (preterm premature rupture of membranes), preterm labour, low birth weight (LBW) and prematurity. A three-year retrospective dual-centre cohort study of antenatal pyelonephritis cases was conducted in two neighbouring Irish maternity hospitals – the Rotunda Hospital (RH) and the National Maternity Hospital (NMH). Patient demographics, clinical presentation, investigations, management and maternal/neonatal outcomes were recorded. A total of 47,676 deliveries (24,768 RH; 22,908 NMH) were assessed. 158 cases of antenatal pyelonephritis were identified (n = 88 RH, n = 70 NMH), with an incidence of 0.33%. The median age was 28 years. The median gestation was 27 + 6 weeks, with 51% presenting before 28 weeks’ gestation. Risk factors included; obesity (18.4%), diabetes mellitus (13.3%) and self-reported clinical history of recurrent urinary tract infection (28.5%). Rate of relapse with UTI in the same pregnancy was 8.2%. Renal ultrasound was performed in 30.4%. Predominant uropathogens were Escherichia coli (60%), Klebsiella pneumoniae (11%) and Proteus mirabilis (5%). 7.5% of cases had a concurrent bloodstream infection, 13.3% of cases were complicated by sepsis and 1.9% with septic shock. Complications including PPROM (6.3%), preterm delivery < 37 weeks’ gestation (11%), LBW < 2,500 g (8.2%) were comparable between sites. Delivery within 72 hours of diagnosis was noted in 7% (n = 11) of patients, of which three were preterm and one had LBW. Appropriate and prompt investigation and management of antenatal pyelonephritis is essential given the associated maternal and neonatal morbidity.
Antibiotic responsibility and agricultural publics: diverse stakeholder perceptions of antibiotic use in animal agriculture
Authors: Lansing David M. , Barrett Jaime 
Published: May 2023

AbstractThis paper examines diverse perspectives around the concept of responsibility concerning antibiotic use in animal agriculture. Antibiotic use in agriculture has been identified as a source of antimicrobial resistance, one of the largest public health threats today. In the United States, efforts to curb antibiotic use in farming draws on a diverse range of actors—including farmers, veterinarians, consumers, and public health advocates—and relies on a mix of industry standards and federal guidelines around responsible use. The paper selects a similarly diverse range of people and employs Q methodology to query the points of disagreement and consensus around the practices that constitute responsible antibiotic use in animal agriculture, and who is responsible for antimicrobial resistance. We find a diverse mix of actor types across three discourses, but with clear differences between farmers and public health advocates. We also argue that, in some cases, points of disagreement and agreement are often based on different interpretations of ideas, indicating points of common ground where there might appear to be disagreement, and areas of difference where there appears to be agreement. We argue that these flexible interpretations of some of the key issues around antibiotic use are nevertheless grounded in durable differences in views of what agriculture is and what it should be.
Tackling land’s ‘stubborn materiality’: the interplay of imaginaries, data and digital technologies within farmland assetization
Authors: Sippel Sarah Ruth 
Published: May 2023

AbstractThe nature of farming is – still – an essentially biological, and thus volatile, system, which poses substantial challenges to its integration into financialized capitalism. Financial investors often seek stability and predictability of returns that are hardly compatible with agriculture – but which are increasingly seen as achievable through data and digital farming technologies. This paper investigates how farmland investment brokers engage with, perceive, and produce farming data for their investors within a co-constructive process. Tackling land’s ‘stubborn materiality’ for investment, I argue, has material and immaterial components: it includes the re-imagination of farming as a financial asset that delivers reliable income streams for investors; and the re-engineering of farmland’s concrete materialities with digital farming technologies. Farmland investment brokers develop investor-suitable farmland imaginaries, underpinned by storytelling as well as the calculative ‘evidence’ of (digital) data. At the same time, digital technologies have become a key tool for transforming farms into ‘investment grade assets’ endowed with the rich data on farm performance and financial returns requested by investors. I conclude that the assetization and digitization of farmland need to be seen as closely intertwined and mutually reinforcing processes and identify key areas for future research on this intersection.
Innovative system based on natural polyelectrolyte complex and cellulose micro/nanofibers to improve drainability and properties of recycled paper
Authors: Bastida Gabriela A. , Zanuttini Miguel A. , Tarrés Quim , Fiol Núria , Delgado-Aguilar Marc , Galván María V. 
Published: May 2023

AbstractIn this work, the efficiency of a polyelectrolyte complex (PEC) to retain different cellulose micro/nanofibers (CMNFs) during paper formation and to improve the physical properties of recycled unbleached fiber paper was analyzed. CMNFs were obtained from a commercial bleached eucalyptus pulp (BEP) using a PFI refiner followed by a chemical treatment with oxalic acid at two different concentrations. Finally, the pulp was fibrillated using a high-pressure homogenizer at three different intensities. The PEC was formed by addition of the xylan (Xyl) solution on chitosan (CH) solution with a Xyl/CH mass ratio of 80/20. The required dosages of PEC solution to neutralize the charges of different nanocellulose fractions were determined by ζ-potential measurements, and the CMNF retentions on recycled unbleached fibers were evaluated in a Britt Dynamic Drainage Jar. The results showed that the maximum retention was obtained when the neutral PEC-CMNF system was added to pulp. Besides, a significant decrease on °SR was observed when PEC and PEC-CMNF systems were added to the untreated pulp, limiting the negative effects of nanocellulose addition on pulp drainability. The incorporation of PEC-CMNF systems to the handsheets increased the tensile index (up to 28%), Mullen index (up to 40%) and internal bonding (up to 255%). Finally, the compressive strength of the handsheets, namely SCT and CMT, increased up to 30 and 70%, respectively. These simultaneous improvement on drainability and mechanical properties makes the proposed PEC-CMNF system a promising solution for the production of packaging paper.
The Pilgrimage on the Camino de Santiago and Its Impacts on Marital and Familial Relationships: An Exploratory Study
Authors: Tykarski Sławomir , Mróz Franciszek 
Published: May 2023

AbstractThis paper presents the results of a survey conducted among people walking the pilgrimage route to the shrine of St James in Santiago de Compostela. The aim of the research was to investigate how a pilgrimage on the Camino de Santiago among a married couple or family affects marital or familial relationships, whether walking the trail to Compostela together influences the behaviour of family members towards each other and whether it forms positive attitudes and behaviour. The empirical basis of the study is the results of a survey among respondents who made the Camino de Santiago pilgrimage, as well as in-depth interviews conducted with 24 spouses of pilgrims along the Way of St James. The study revealed that doing the pilgrimage as a married couple or family had a positive impact on intra-family relationships. According to the interviewees, going on the pilgrimage together helped to strengthen marital bonds and trust, improve communication and mutual connection, show care and affection and improve contact with children.
ROAD-R: the autonomous driving dataset with logical requirements
Authors: Giunchiglia Eleonora , Stoian Mihaela Cătălina , Khan Salman , Cuzzolin Fabio , Lukasiewicz Thomas 
Published: May 2023

AbstractNeural networks have proven to be very powerful at computer vision tasks. However, they often exhibit unexpected behaviors, acting against background knowledge about the problem at hand. This calls for models (i) able to learn from requirements expressing such background knowledge, and (ii) guaranteed to be compliant with the requirements themselves. Unfortunately, the development of such models is hampered by the lack of real-world datasets equipped with formally specified requirements. In this paper, we introduce the ROad event Awareness Dataset with logical Requirements (ROAD-R), the first publicly available dataset for autonomous driving with requirements expressed as logical constraints. Given ROAD-R, we show that current state-of-the-art models often violate its logical constraints, and that it is possible to exploit them to create models that (i) have a better performance, and (ii) are guaranteed to be compliant with the requirements themselves.
Life cycle assessment of different strawberry production methods in Germany with a particular focus on plastic emissions
Authors: Galafton Christina , Maga Daniel , Sonnemann Guido , Thonemann Nils 
Published: May 2023

Abstract
Purpose
Using plastic for strawberry cultivation (so-called plasticulture) is widespread to extend cultivation, reduce weed stress and water and nutrient demand, and protect plants. We assess the environmental impacts of different plasticulture methods, including possible impacts caused by the (accidental) emission of plastics. The goals are to help farmers determine the most environmentally friendly cultivation technique and to test the inclusion of plastic pollution in life cycle assessment (LCA).

Methods
An LCA is conducted for a baseline scenario without plasticulture and 11 plasticulture scenarios. The scenarios are modeled using the regionalized ecoinvent 3.8 cut-off database. The functional unit is 1 kg of strawberries of marketable quality at the farm gate produced in the year 2021. The amounts of fertilizer, irrigation, and strawberry output of the scenarios are adapted depending on the plasticulture method based on an extensive literature review. The environmental impacts are assessed using the life cycle impact assessment methods of the Product Environmental Footprint (PEF) recommended by the Joint Research Centre of the European Commission, which is extended to account for plastic-related impacts. The impacts are normalized, weighted, and aggregated, resulting in one single impact score per scenario.

Results and discussion
The scenarios using either a combination of conventional mulch film and row cover or biodegradable mulch film have the lowest total impacts; a macro tunnel or greenhouse causes the highest impacts. There seems to be no trade-off between maximizing productivity and lowering environmental impacts: the scenario with the highest yield also has one of the lowest overall impacts. Only direct emissions are considered regarding plastic pollution. Besides, the plastic pollution impact category is currently limited to the persistence of plastic in the environment and is extendable to but is not yet accounting for exposure and effect of plastic emission on humans and ecosystems.

Conclusion
Plasticulture can increase the yield and reduce environmental impacts for strawberry cultivation compared to open field cultivation. With the used normalization and weighting factors, plastic pollution makes up a considerable share of the overall environmental impact of strawberry cultivation, supporting the recent efforts of different research groups to include plastic emissions in LCA by developing suitable characterization factors.
Machine Learning–Based Prediction of Functional Disability: a Cohort Study of Japanese Older Adults in 2013–2019
Authors: Lu Yongjian , Sato Koryu , Nagai Masato , Miyatake Hirokazu , Kondo Katsunori , Kondo Naoki 
Published: May 2023

Abstract
Background
It is important to identify older adults at high risk of functional disability and to take preventive measures for them at an early stage. To our knowledge, there are no studies that predict functional disability among community-dwelling older adults using machine learning algorithms.

Objective
To construct a model that can predict functional disability over 5 years using basic machine learning algorithms.

Design
A cohort study with a mean follow-up of 5.4 years.

Participants
We used data from the Japan Gerontological Evaluation Study, which involved 73,262 people aged  ≥ 65 years who were not certified as requiring long-term care. The baseline survey was conducted in 2013 in 19 municipalities.

Main Measures
We defined the onset of functional disability as the new certification of needing long-term care that was ascertained by linking participants to public registries of long-term care insurance. All 183 candidate predictors were measured by self-report questionnaires.

Key Results
During the study period, 16,361 (22.3%) participants experienced the onset of functional disability. Among machine learning–based models, ridge regression (C statistic = 0.818) and gradient boosting (0.817) effectively predicted functional disability. In both models, we identified age, self-rated health, variables related to falls and posture stabilization, and diagnoses of Parkinson’s disease and dementia as important features. Additionally, the ridge regression model identified the household characteristics such as the number of members, income, and receiving public assistance as important predictors, while the gradient boosting model selected moderate physical activity and driving. Based on the ridge regression model, we developed a simplified risk score for functional disability, and it also indicated good performance at the cut-off of 6/7 points.

Conclusions
Machine learning–based models showed effective performance prediction over 5 years. Our findings suggest that measuring and adding the variables identified as important features can improve the prediction of functional disability.
Morphological changes and protein degradation during the decomposition process of pig cadavers placed outdoors or in tents—a pilot study
Authors: Geissenberger J. , Amendt J. , Klampfer J. , Thuemmel L. , Jakob L. , Monticelli F. C. , Steinbacher P. , Pittner S. 
Published: May 2023

AbstractThe delimitation of the postmortem interval (PMI) is of utmost importance in forensic science. It is especially difficult to determine the PMI in advanced decomposition stages and/or when dead bodies are found under uncommon circumstances, such as tents, or other (semi-) enclosed environments. In such cases, especially when insect access is restricted, morphological assessment of body decomposition is one of the remaining approaches for delimitation of the PMI. However, as this method allows only vague statements/indications about the PMI, it is required to develop new and more reliable methods. One of the most important candidates is the biochemical analysis of protein degradation. In this regard, it has been demonstrated that specific skeletal muscle protein degradation patterns characterize certain time points postmortem and thus can be used as markers for PMI estimation. In order to test this method in different micro-environments, a pilot study using ten pig carcasses was conducted in summer in Northern Germany. The cadavers were openly placed outside (freely accessible for insects), as well as enclosed in tents nearby, and left to decompose to investigate decomposition processes over a time course of 10 days. Muscle samples of the M. biceps femoris were collected on a regular basis and processed via SDS-PAGE and degradation patterns of selected proteins identified by Western blotting. In addition, morphological changes of the cadavers during decomposition were assessed using the total body score (TBS). Results showed that postmortem protein degradation patterns are largely consistent between treatment groups (open field versus tents) despite major morphological differences in the decomposition rate. This field study provides evidence that muscle protein degradation is mostly unaffected by different levels of exposure, making it a sufficient candidate for PMI delimitation under various circumstances.
Evaluating cancer genetic services in a safety net system: overcoming barriers for a lasting impact beyond the CHARM research project
Authors: Okuyama Sonia , White Larissa L. , Anderson Katherine P. , Medina Elizabeth , Deutsch Sonia , Ransom Chelese , Jackson Paige , Kauffman Tia L. , Mittendorf Kathleen F. , Leo Michael C. , Bulkley Joanna E. , Wilfond Benjamin S. , Goddard Katrina AB , Feigelson Heather Spencer 
Published: May 2023

AbstractUnderserved patients face substantial barriers to receiving cancer genetic services. The Cancer Health Assessments Reaching Many (CHARM) study evaluated ways to increase access to genetic testing for individuals in underserved populations at risk for hereditary cancer syndromes (HCS). Here, we report the successful implementation of CHARM in a low-resource environment and the development of sustainable processes to continue genetic risk assessment in this setting. The research team involved key clinical personnel and patient advisors at Denver Health to provide input on study methods and materials. Through iterative and collaborative stakeholder engagement, the team identified barriers and developed solutions that would both facilitate participation in CHARM and be feasible to implement and sustain long term in clinical care. With a focus on infrastructure building, educational modules were developed to increase awareness among referring providers, and standard methods of identifying and managing HCS patients were implemented in the electronic medical record. Three hundred sixty-four DH patients successfully completed the risk assessment tool within the study, and we observed a sustained increase in referrals to genetics for HCS (from 179 in 2017 to 427 in 2021 post-intervention). Implementation of the CHARM study at a low-resourced safety net health system resulted in sustainable improvements in access to cancer genetic risk assessment and services that continue even after the study ended.Trial registration NCT03426878
Automatic Classification of Online Discussions and Other Learning Traces to Detect Cognitive Presence
Authors: Dornauer Verena , Netzer Michael , Kaczkó Éva , Norz Lisa-Maria , Ammenwerth Elske 
Published: May 2023

AbstractCognitive presence is a core construct of the Community of Inquiry (CoI) framework. It is considered crucial for deep and meaningful online-based learning. CoI-based real-time dashboards visualizing students’ cognitive presence may help instructors to monitor and support students’ learning progress. Such real-time classifiers are often based on the linguistic analysis of the content of posts made by students. It is unclear whether these classifiers could be improved by considering other learning traces, such as files attached to students’ posts. We aimed to develop a German-language cognitive presence classifier that includes linguistic analysis using the Linguistic Inquiry and Word Count (LIWC) tool and other learning traces based on 1,521 manually coded meaningful units from an online-based university course. As learning traces, we included not only the linguistic features from the LIWC tool, but also features such as attaching files to a post, tagging, or using terms from the course glossary. We used the k-nearest neighbor method, a random forest model, and a multilayer perceptron as classifiers. The results showed an accuracy of up to 82% and a Cohen’s κ of 0.76 for the cognitive presence classifier for German posts. Including learning traces did not improve the predictive ability. In conclusion, we developed an automatic classifier for German-language courses based on a linguistic analysis of students’ posts. This classifier is a step toward a teacher dashboard. Our work also provides the first fully CoI-coded German dataset for future research on cognitive presence.
Fundamental Understanding and Optimization Strategies for Dual-Ion Batteries: A Review
Authors: Chen Chong , Lee Chun-Sing , Tang Yongbing 
Published: May 2023

AbstractThere has been increasing demand for high-energy density and long-cycle life rechargeable batteries to satisfy the ever-growing requirements for next-generation energy storage systems. Among all available candidates, dual-ion batteries (DIBs) have drawn tremendous attention in the past few years from both academic and industrial battery communities because of their fascinating advantages of high working voltage, excellent safety, and environmental friendliness. However, the dynamic imbalance between the electrodes and the mismatch of traditional electrolyte systems remain elusive. To fully employ the advantages of DIBs, the overall optimization of anode materials, cathode materials, and compatible electrolyte systems is urgently needed. Here, we review the development history and the reaction mechanisms involved in DIBs. Afterward, the optimization strategies toward DIB materials and electrolytes are highlighted. In addition, their energy-related applications are also provided. Lastly, the research challenges and possible development directions of DIBs are outlined.
Evidence for Targeted and Universal Secondary School-Based Programs for Anxiety and Depression: An Overview of Systematic Reviews
Authors: Zbukvic Isabel , McKay Samuel , Cooke Samantha , Anderson Rebekah , Pilkington Vita , McGillivray Lauren , Bailey Alan , Purcell Rosemary , Tye Michelle 
Published: May 2023

AbstractWhile there are a number of systematic reviews on school-based mental health programs, there appears to be heterogeneity in their overall findings and conclusions, possibly due to the tendency to combine evidence from primary school and high school programs. To investigate the evidence for the effectiveness of targeted (for specific groups) and universal (for all students) mental health programs delivered in secondary schools, a systematic review of systematic reviews was conducted. A systematic search for reviews published from 2015 included outcomes for depression and anxiety—the most common mental health conditions—and quality appraisal of original studies in majority secondary school settings. A total of 395 references were screened and 14 systematic reviews were included. Of reviews that were assessed in full, most were excluded for not clearly separating studies in secondary school settings from primary school settings. Findings were generally positive but heterogenous in terms of quality and long-term outcomes. Interventions were mainly based on cognitive behavioural therapy (CBT), with results showing that targeted interventions are generally effective in the short-term for both anxiety and depression, while universal programs may be effective in some situations, typically in the short term and when programs were CBT-based; where reviews focused on universal resilience programs there were no significant effects. The overview shows a need for systematic reviews focused on secondary school settings, which consider contextual and individual factors that can influence the implementation and effectiveness of programs.