bluuebunny/crossref_metadata_2025_split huggingface dataset:
Midwifery Management of a Birthing Person with Cervical Edema During Labor
Authors: LoGiudice Jenna A. , Holland Eliza , Esposito Christa Palancia 
Published: October 2022

AbstractDuring active labor, a birthing person with cervical edema often has a dysfunctional or prolonged labor and, therefore, an increased risk for cesarean birth. Midwives seeking evidence on how to manage cervical edema when they are faced with this clinical situation will note a gap in the literature regarding the management of cervical edema that this report aims to fill. This case will discuss the use of intravenous diphenhydramine (Benadryl), the application of ice to the cervix, side‐lying release, epidural analgesia use, manual reduction of the cervix, and various positions to encourage reduction in cervical swelling. It is hoped these strategies will add to a midwife's clinical resources by providing ways to promote vaginal birth in the setting of cervical edema during labor.
No significant changes in preterm birth, low‐birth‐weight, and small‐for‐gestational‐age infants during the first year of the COVID‐19 pandemic in a rural area in Japan
Authors: Maki Yohei , Tokuda Atsuko , Kino Emi , Yamauchi Aya , Ohtsuka Teruo , Terao Kiminari 
Published: October 2022

AbstractAimsTo evaluate the coronavirus disease 2019 pandemic's impact on pregnancy outcomes in a Japanese rural area.MethodsThis retrospective study focused on the periods between March 1, 2020, and February 28, 2021 (during the coronavirus disease 2019 pandemic), and January 1, 2017, and December 31, 2019. Singleton pregnancies delivered at or after 22 gestational weeks were included. Preterm delivery, low‐birth‐weight, and small‐for‐gestational‐age infant rates during the pandemic were compared to those in the preceding 3 years.ResultsIn the pandemic and control groups, 1650 and 5762 pregnant women were included, respectively. Two pregnant women with coronavirus disease 2019 were identified (0.1%). There were no significant intergroup differences in preterm delivery rates (control, 4% vs. pandemic, 3.3%; difference: −0.7% [95% confidence interval: −1.7%–0.3%], p = 0.22). The low‐birth‐weight rate tended to decrease; however, the difference was insignificant (7.9% vs. 6.5%; difference: −1.4% [95% confidence interval: −2.8–0%], p = 0.06). The small‐for‐gestational‐age infant rate was significantly lower in the pandemic than in the control group (7.3% vs. 5.2%; difference: −2.1% [95% confidence interval: −3.3–0.8%], p < 0.01). However, the interrupted time series analysis showed no significant trend.ConclusionsThere were no significant changes in the rates of preterm delivery, low‐birth‐weight infants, and small‐for‐gestational‐age infants during the pandemic's first year compared to those in the preceding 3 years. Behavioral changes, such as “stay‐at‐home” measures, may not improve pregnancy outcomes in Japan.
Automatic concrete defect detection and reconstruction by aligning aerial images onto semantic‐rich building information model
Authors: Chen Junjie , Lu Weisheng , Lou Jinfeng 
Published: October 2022

AbstractConcrete defect information is of vital importance to building maintenance. Increasingly, computer vision has been explored for automated concrete defect detection. However, existing studies suffer from the challenging issue of false positives. In addition, 3D reconstruction of the defects to pinpoint their positions and geometries has not been sufficiently explored. To address these limitations, this study proposes a novel computational approach for detecting and reconstructing concrete defects from geotagged aerial images. A bundle registration algorithm is devised to align a batch of aerial photographs with a building information model (BIM). The registration enables the retrieval of material semantics in BIM to determine the regions of interest for defect detection. It helps rectify the camera poses of the aerial images, enabling precise defect reconstruction. Experiments demonstrate the effectiveness of the approach, which significantly reduced the false discovery rate from 70.8% to 56.8%, resulting in an intersection over union 6.4% higher than that of the traditional method. The geometry of the defects was successfully reconstructed in 3D world space. This study opens a new avenue to advance the field of defect detection by exploiting the rich information from BIM. The approach can be deployed at scale, supporting urban renovation, numerical simulation, and other smart applications.
Whole‐genome analyses disentangle reticulate evolution of primroses in a biodiversity hotspot
Authors: Stubbs Rebecca L. , Theodoridis Spyros , Mora‐Carrera Emiliano , Keller Barbara , Yousefi Narjes , Potente Giacomo , Léveillé‐Bourret Étienne , Celep Ferhat , Kochjarová Judita , Tedoradze Giorgi , Eaton Deren A. R. , Conti Elena 
Published: October 2022

Summary
Biodiversity hotspots, such as the Caucasus mountains, provide unprecedented opportunities for understanding the evolutionary processes that shape species diversity and richness. Therefore, we investigated the evolution of Primula sect. Primula, a clade with a high degree of endemism in the Caucasus.
We performed phylogenetic and network analyses of whole‐genome resequencing data from the entire nuclear genome, the entire chloroplast genome, and the entire heterostyly supergene. The different characteristics of the genomic partitions and the resulting phylogenetic incongruences enabled us to disentangle evolutionary histories resulting from tokogenetic vs cladogenetic processes. We provide the first phylogeny inferred from the heterostyly supergene that includes all species of Primula sect. Primula.
Our results identified recurrent admixture at deep nodes between lineages in the Caucasus as the cause of non‐monophyly in Primula. Biogeographic analyses support the ‘out‐of‐the‐Caucasus’ hypothesis, emphasizing the importance of this hotspot as a cradle for biodiversity.
Our findings provide novel insights into causal processes of phylogenetic discordance, demonstrating that genome‐wide analyses from partitions with contrasting genetic characteristics and broad geographic sampling are crucial for disentangling the diversification of species‐rich clades in biodiversity hotspots.
Development and validation of a prediction model for preoperative anxiety in children aged 2–12 years old
Authors: Cheng Zhangqin , Wang Liuyi , Li Lifang , Sun Bin , Zhang Yuhan , Su Yang , Wang Liwei 
Published: October 2022

AbstractBackgroundChildren with preoperative anxiety are at risk of perioperative adverse events, such as reflux aspiration, prolonged induction time, wake agitation, and delirium. Identifying children at high risk of severe preoperative anxiety may help anesthesiologists intervene and manage them in advance.AimThe authors hypothesized that the risk of developing serious preoperative anxiety in children is predictable by variables related to basic information about the parent and child. We developed a clinical prediction model to identify patients vulnerable to severe preoperative anxiety among children aged 2–12 years.MethodsWe enrolled patients aged 2–12 years who underwent elective surgery under general anesthesia and divided them into derivation (n = 340, 70.8%) and validation (n = 140, 29.2%) groups. Preoperative anxiety was assessed using the modified Yale Preoperative Anxiety Scale, and a high level of preoperative anxiety was defined as a score of >30. The following predictors were collected preoperatively: gender, age, weight, children's education level, only child, history of surgery, waiting time in the anesthesia waiting area, parental education level, parental anxiety, whether venous access had been established in the ward, and whether they had received anti‐anxiety interventions. A prediction model was built using binary logistic regression analysis; bootstrap was applied for internal validation, and external validation was performed using the validation datasets.ResultsThe prediction model had good discrimination, with an area under the receiver operator characteristic curve (AUC) of 0.961 (95% CI = 0.943–0.979) and 0.896 (95% CI = 0.842–0.950) in the derivation and validation cohorts, respectively. The predictive variables included in the final clinical model were pharmacological intervention (OR = 0.008, 95% CI = 0.002–0.025), nonpharmacological intervention (OR = 0.342, 95% CI = 0.104–1.127), parental education level (OR = 0.211, 95% CI = 0.108–0.411), parental anxiety (OR = 6.15, 95% CI = 2.396–15.786), only child (OR = 2.417, 95% CI = 1.065–5.488), history of surgery (OR = 3.513, 95% CI = 1.137–10.860), and age (OR = 0.692, 95% CI = 0.500–0.957).ConclusionsIn this study, a clinical prediction model was developed and validated for the first time. The proposed clinical prediction model can help doctors identify children most likely to develop a high level of preoperative anxiety.Clinical Trial Registration IdentifierChiCTR2100054409 (https://www.chictr.org.cn/index.aspx).
Effects of electroconvulsive therapy on the use of anxiolytics and sleep medications: a propensity score‐matched analysis
Authors: Tsuboi Takashi , Takaesu Yoshikazu , Hasegawa Naomi , Ochi Shinichiro , Fukumoto Kentaro , Ohi Kazutaka , Muraoka Hiroyuki , Okada Tsuyoshi , Kodaka Funitoshi , Igarashi Shun , Iida Hitoshi , Kashiwagi Hiroko , Hori Hikaru , Ichihashi Kayo , Ogasawara Kazuyoshi , Hashimoto Naoki , Iga Jun‐ichi , Nakamura Toshinori , Usami Masahide , Nagasawa Tatsuya , Kido Mikio , Komatsu Hiroshi , Yamagata Hirotaka , Atake Kiyokazu , Furihata Ryuji , Kikuchi Saya , Horai Tadasu , Takeshima Masahiro , Hirano Yoji , Makinodan Manabu , Matsumoto Junya , Miura Kenichiro , Hishimoto Akitoyo , Numata Shusuke , Yamada Hisashi , Yasui‐Furukori Norio , Inada Ken , Watanabe Koichiro , Hashimoto Ryota 
Published: October 2022

AimWe investigated the association of electroconvulsive therapy (ECT) with anxiolytic and sleep medication use in patients with major depressive disorder (MDD) and schizophrenia (SZ).MethodsThis nationwide observational study analyzed data from 3483 MDD inpatients and 6663 SZ inpatients. Patients with MDD and SZ were classified into those who underwent ECT during hospitalization and those who did not. A propensity score‐matching method was performed to adjust for preadmission characteristics and clinical information, which were expected bias between the two groups. Rates of anxiolytic and sleep medication use at discharge were compared in the matched sample.Results500 MDD patients were assigned to both groups. In the matched MDD sample, the rate of anxiolytic and sleep medication use at discharge was significantly lower in the ECT group than in the non‐ECT group (64.9% vs. 75.8%, P = 1.7 × 10−4). In the ECT group, the rate of anxiolytic and sleep medication use at discharge was significantly lower than that prior to admission (64.9% vs. 73.2%, P = 1.2 × 10−14). 390 SZ patients were allocated. In the matched SZ sample, the ECT group was not significantly different from the non‐ECT group in the rate of anxiolytics and sleep medications use at discharge (61.3% vs. 68.2%, P = 4.3 × 10−2). In the ECT group, the rate of anxiolytics and sleep medications use at discharge was significantly lower than that before admission (61.3% vs. 70.5%, P = 4.4 × 10−4), although this was not the primary outcome.ConclusionReduction of anxiolytic and sleep medication use may be considered positively when ECT is indicated for treatment of MDD.
Did the Younger Dryas to Holocene climate transition favour high seismicity rates in the north‐western Alps?
Authors: Banjan Mathilde , Crouzet Christian , Sabatier Pierre , Jomard Hervé , Bajard Manon , Demory Francois , Develle Anne‐Lise , Jenny Jean‐Philippe , Fanget Bernard , Malet Emmanuel , Findling Nathaniel , Alain Philippe , Didier Julien , Bichet Vincent , Clapot Sylvain , Messager Erwan 
Published: October 2022

ABSTRACTIn the French north‐western Alps, several lakes of glacial origin, such as Aiguebelette and La Thuile, present some mass‐transport deposits within their sedimentary sequences. These event layers can result from lake sediment destabilization eventually triggered by earthquakes. On Lake Aiguebelette, based on sedimentological, geochemical and magnetic analyses, and high‐resolution seismic and bathymetric surveys a ca 1 m thick event layer was identified in the deepest lake basin and a synchronous ca 2 cm thick deposit in the shallow basin. Age‐depth models based on radiocarbon ages reveal that both mass‐transport deposits in Lake Aiguebelette occurred around the Younger Dryas – Early Holocene climatic transition (i.e. 11 700 cal bp) time range. In Lake La Thuile, located 30 km away, unique mass‐transport deposits (translational slide type) were recorded at the same time range in sedimentary records. Additionally, high‐resolution seismic profiles previously acquired in Lake Annecy and Lake Bourget support the hypothesis of significant mass‐transport deposits occurring at the Younger Dryas – Early Holocene time range. These outcomes on four north‐western peri‐Alpine and Alpine lakes highlight the regional occurrence of mass‐transport deposits in the Younger Dryas – Early Holocene time range. Seismic and rockfall events are discussed as potential sources of these significant and similarly aged mass‐transport deposits. Based on this study and a literature review, the authors suggest that mechanisms induced by rapid climate change and glacial retreat, such as crustal rebound and erosional unloading, could favour the triggering of earthquakes and rockfall events. In the case of mass‐transport deposits archived in north‐western Alpine lakes during this time period, this study favours the hypothesis of increased seismicity as the primary source driving process involved.
Child Sex Tourism: Ambiguous Spaces in Bali
Authors: Hulsbergen Fliertje , Nooteboom Gerben 
Published: October 2022

ABSTRACTThe phenomenon of child sex tourism (CST) is intensified by the increased mobility of people worldwide. Current approaches to fight CST predominantly focus on enforcing legislation and disrupting the cycle of demand and supply, yet they have proven largely ineffective. This paper highlights the enabling properties of CST spaces in Bali and takes a new approach by focusing on the ambiguity of place, authority structures and actors. The analysis identifies four CST spaces – private homes, brothels, spa massage parlours and orphanages – which enable the persistence of CST. Understanding the ‘socio‐spatial properties’ of risk locations is key to disrupting and fighting CST more effectively.
Squeezed out by the market, seeking strength in the network: Makeshift temples and the spatio‐affective logics of survival in Singapore
Authors: Gao Quan , Woods Orlando , Kong Lily 
Published: October 2022

AbstractThis paper offers an understanding of the spatio‐affective workings of religious organisations – and the marketplaces they operate in and through – that go beyond capitalist logics. We do so by examining how makeshift temples representing various forms of ‘Chinese religion’ survive in Singapore. Capitalist logics fail to explain how such marginal and precarious religious organisations, which might be ‘squeezed out’ by the market, nonetheless manage to survive amid competition. Moreover, scarce attention has been paid to how religion as a social‐affective system might mediate the functioning of a religious market. This paper fills the lacuna by bringing an understanding of the affective resonances of Chinese religious practices into conversation with religious market theory. Rather than treating the market as a universal mechanism that moderates patterns of competition, growth, and decline, we focus instead on the spatio‐affective conditions through which a plurality of ‘actually existing’ religious marketplaces is made possible. We argue that makeshift temples in Singapore create an alternative order of the religious market that is organised by the affective economies and interpersonal relationships within which different ritual service providers compete, cohabit, and cooperate. These temples dismiss the spatio‐religious boundaries and regulation that define the neoliberal religious marketplace of Singapore by carving out sacred niches instead.
t-METASET: Task-Aware Acquisition of Metamaterial Datasets Through Diversity-Based Active Learning
Authors: Lee Doksoo , Chan Yu-Chin , Chen Wei (Wayne) , Wang Liwei , van Beek Anton , Chen Wei 
Published: October 2022

Abstract
Inspired by the recent achievements of machine learning in diverse domains, data-driven metamaterials design has emerged as a compelling paradigm that can unlock the potential of multiscale architectures. The model-centric research trend, however, lacks principled frameworks dedicated to data acquisition, whose quality propagates into the downstream tasks. Often built by naive space-filling design in shape descriptor space, metamaterial datasets suffer from property distributions that are either highly imbalanced or at odds with design tasks of interest. To this end, we present t-METASET: an active learning-based data acquisition framework aiming to guide both diverse and task-aware data generation. Distinctly, we seek a solution to a commonplace yet frequently overlooked scenario at early stages of data-driven design of metamaterials: when a massive (∼O(104)) shape-only library has been prepared with no properties evaluated. The key idea is to harness a data-driven shape descriptor learned from generative models, fit a sparse regressor as a start-up agent, and leverage metrics related to diversity to drive data acquisition to areas that help designers fulfill design goals. We validate the proposed framework in three deployment cases, which encompass general use, task-specific use, and tailorable use. Two large-scale mechanical metamaterial datasets are used to demonstrate the efficacy. Applicable to general image-based design representations, t-METASET could boost future advancements in data-driven design.
A Microencapsulated Phase-Change Material Suspension-Based Integrated Thermal Management System for Extended Range Electric Vehicle
Authors: Hu Sunan , Yao Mingyao , Zhu Bo , Zhang Nong , Yuan Ruoyang 
Published: October 2022

Abstract
In order to improve the temperature maintenance capacity for the battery of the extended-range electric vehicle (EREV) in a low-temperature environment, a microencapsulated phase-change material suspension (MPCMS)-based integrated thermal management system (ITMS) is proposed. The working modes of the proposed ITMS are divided based on series-parallel connections of the battery thermal management system (BTMS), motor thermal management system, motor thermal management system, and auxiliary power unit (APU) thermal management system; the structural parameters of the proposed ITMS are determined by robust design, and the system performance difference between the proposed ITMS and the traditional BTMS is verified through the comparative simulation in −20 °C environment. The results show that the proposed ITMS can significantly delay the decline of battery temperature in the charge-depleting (CD) stage and can reduce the time of the positive temperature coefficient (PTC) heater being on by 27.26%, and the total time being on by 54.82%. During the charge-sustaining (CS) stage, when the PTC heater is off, the average battery temperature will increase by 15.33 °C compared with the traditional BTMS. Based on the proposed ITMS, the temperature maintenance capability for the battery can be significantly improved, and the energy consumption of the PTC heater and vehicle can be reduced by 48.12–100% and 13.44–33.58%, respectively.
Leading at the Edge During COVID-19: Challenges, Opportunities, and Future Pandemic Preparedness
Authors: Elmer Steven J. , Kamm Kelly B. 
Published: October 2022

In this paper, we describe how the Department of Kinesiology and Integrative Physiology at Michigan Technological University assembled a COVID-19 pandemic response team to help protect the health of the campus and rural community. Specifically, our team worked to (a) enhance public health messaging, (b) manage the university contact tracing program, (c) expand health science curricula, (d) promote and facilitate physical activity as a key mitigation strategy, and (e) provide professional development opportunities for students. We also consider strategies to prepare for subsequent COVID-19 surges and future health emergencies. Leveraging our broad-based training in health science and “leading at the edge” was a critical asset for the campus and community and may serve as a model for other kinesiology departments and rural colleges and universities.
Management of chronic migraine
Authors: Hovaguimian Alexandra , Roth Julie 
Published: October 2022

ABSTRACT
Chronic migraine is a neurologic disorder associated with considerable disability, lost productivity, and a profound economic burden worldwide. The past five years have seen a dramatic expansion in new treatments for this often challenging condition, among them calcitonin gene related peptide antagonists and neuromodulatory devices. This review outlines the epidemiology of and diagnostic criteria and risk factors for chronic migraine. It discusses evidence based drug and non-drug treatments, their advantages and disadvantages, and the principles of patient centered care for adults with chronic migraine, with attention to differential diagnosis and comorbidities, clinical reasoning, initiation and monitoring, cost, and availability. It discusses the international guidelines on drug treatment for chronic migraine and evaluates non-drug treatments including behavioral and complementary therapies and lifestyle modifications. Finally, it discusses the management of chronic migraine in special populations, including pediatrics, pregnancy, and older people, and considers future questions and emerging research in the field.
Multicentre narrative research on major depression to integrate the experiences of patients, their caregivers and healthcare providers in Italy
Authors: Chesi Paola , Mencacci Claudio , Balestrieri Matteo , Pompili Maurizio , Varia Salvatore , Sagripanti Ubaldo , Reale Luigi , Marini Maria Giulia 
Published: October 2022

ObjectiveThis research aimed to investigate the experience of major depression by integrating the perspectives of patients, caregivers and healthcare providers through narrative-based medicine (NBM) to provide new insights to improve care relationships.Design and settingThe research was conducted in 2019 and involved five Italian psychiatric centres and targeted adult patients, their caregivers and healthcare providers to address data source triangulation. A sociodemographic survey and a narrative plot, based on Natural Semantic Metalanguage were collected. Narratives were analysed through NBM classifications, NVivo software and interpretative coding.ParticipantsThirty-six patients with a diagnosis of major depression, 27 caregivers and 33 healthcare providers participated in the research.ResultsAmong the 96 collected narratives, ‘lonely’ was the word patients used most frequently, while ‘sad’ and ‘lifeless’ were used most respectively by caregivers and healthcare providers. A positive care relationship was crucial for 84% of patients in relation to their care pathway, and nature (36%) and the arts (28%) were the most frequent resources. Caregivers expressed feelings of powerlessness and inadequacy, and 21% of them reported a declining social life while providing care to a loved one with depression. Thirty-one percent of mental health professionals experienced difficulties in their first encounter with patients; however, their emotions progressively moved towards trust and satisfaction. Furthermore, 89% of patients and healthcare providers and 58% of caregivers evaluated writing the narrative to be a positive experience.ConclusionFindings suggested the possible role for language in understanding major depression, thereby improving care relationships between patients and physicians. Care pathways might also be more attentive to caregivers, to reduce their risk of burnout. Finally, narrative medicine could be integrated with the care pathway as an additional space of expression, dialogue, reflection and development of empathy.