bluuebunny/crossref_metadata_2025_split huggingface dataset:
The use of e-consent in surgery and application to neurosurgery: a systematic review and meta-analysis
Authors: Mirza Asfand Baig , Khoja Abbas Khizar , Ali Fizza , El-Sheikh Mustafa , Bibi-Shahid Ammal , Trindade Jandira , Rocos Brett , Grahovac Gordan , Bull Jonathan , Montgomery Alexander , Arvin Babak , Sadek Ahmed-Ramadan 
Published: September 2023

AbstractIntroductionThe integration of novel electronic informed consent platforms in healthcare has undergone significant growth over the last decade. Adoption of uniform, accessible, and robust electronic online consenting applications is likely to enhance the informed consent process and improve the patient experience and has the potential to reduce medico-legal ramifications of inadequate consent. A systematic review and meta-analysis was conducted to evaluate the utility of novel electronic means of informed consent in surgical patients and discuss its application to neurosurgical cohorts.MethodsA review of randomised controlled trials, non-randomised studies of health interventions, and single group pre-post design studies in accordance with the PRISMA statement. Random effects modelling was used to estimate pooled proportions of study outcomes. Patient satisfaction with the informed consent process and patients’ gain in knowledge were compared for electronic technologies versus non-electronic instruments. A sub-group analysis was conducted to compare the utility of electronic technologies in neurosurgical cohorts relative to other surgical patients in the context of patient satisfaction and knowledge gain.ResultsOf 1042 screened abstracts, 63 studies were included: 44 randomised controlled trials (n = 4985), 4 non-randomised studies of health interventions (n = 387), and 15 single group pre-post design studies (n = 872). Meta-analysis showed that electronic technologies significantly enhanced patient satisfaction with the informed consent process (P < 0.00001) and patients’ gain in knowledge (P < 0.00001) compared to standard non-electronic practices. Sub-group analysis demonstrated that neurosurgical patient knowledge was significantly enhanced with electronic technologies when compared to other surgical patients (P = 0.009), but there was no difference in patient satisfaction between neurosurgical cohorts and other surgical patients with respect to electronic technologies (P = 0.78).ConclusionsNovel electronic technologies can enhance patient satisfaction and increase patients’ gain in knowledge of their surgical procedures. Electronic patient education tools can significantly enhance patient knowledge for neurosurgical patients. If used appropriately, these modalities can shorten and/or improve the consent discussion, streamlining the surgical process and improving satisfaction for neurosurgical patients.
Does context recollection depend on the base-rate of contextual features?
Authors: Nieznański Marek , Obidziński Michał , Ford Daria 
Published: September 2023

AbstractEpisodic recollection is defined by the re-experiencing of contextual and target details of a past event. The base-rate dependency hypothesis assumes that the retrieval of one contextual feature from an integrated episodic trace cues the retrieval of another associated feature, and that the more often a particular configuration of features occurs, the more effective this mutual cueing will be. Alternatively, the conditional probability of one feature given another feature may be neglected in memory for contextual features since they are not directly bound to one another. Three conjoint recognition experiments investigated whether memory for context is sensitive to the base-rates of features. Participants studied frequent versus infrequent configurations of features and, during the test, they were asked to recognise one of these features with (vs. without) another feature reinstated. The results showed that the context recollection parameter, representing the re-experience of contextual features in the dual-recollection model, was higher for frequent than infrequent feature configurations only when the binding of feature information was made easier and the differences in the base-rates were extreme, otherwise no difference was found. Similarly, base-rates of features influenced response guessing only in the condition with salient differences in base-rates. The Bayes factor analyses showed that the evidence from two of our experiments favoured the base-rate neglect hypothesis over the base-rate dependency hypothesis; the opposite result was obtained in the third experiment, but only when high base-rate disproportion and facilitated feature binding conditions were used.
Executive summary of the 14th HHT international scientific conference
Authors: Ola Roxana , Hessels Josefien , Hammill Adrienne , Friday Cassi , Clancy Marianne , Al-Samkari Hanny , Meadows Stryder , Iyer Vivek , Akhurst Rosemary 
Published: September 2023

AbstractHereditary Hemorrhagic Telangiectasia (HHT) is an autosomal dominant vascular disorder characterized by small, dilated clustered vessels (telangiectasias) and by larger visceral arteriovenous malformations (AVMs), which directly connect the feeding arteries with the draining veins. These lesions are fragile, prone to rupture, and lead to recurrent epistaxis and/or internal hemorrhage among other complications. Germline heterozygous loss-of-function (LOF) mutations in Bone Morphogenic Protein 9 (BMP9) and BMP10 signaling pathway genes (endoglin-ENG, activin like kinase 1 ACVRL1 aka ALK1, and SMAD4) cause different subtypes of HHT (HHT1, HHT2 and HHT-juvenile polyposis (JP)) and have a worldwide combined incidence of about 1:5000. Expert clinicians and international scientists gathered in Cascais, Portugal from September 29th to October 2nd, 2022 to present the latest scientific research in the HHT field and novel treatment strategies for people living with HHT. During the largest HHT scientific conference yet, participants included 293 in person and 46 virtually. An impressive 209 abstracts were accepted to the meeting and 59 were selected for oral presentations. The remaining 150 abstracts were presented during judged poster sessions. This review article summarizes the basic and clinical abstracts selected as oral presentations with their new observations and discoveries as well as surrounding discussion and debate. Two discussion-based workshops were also held during the conference, each focusing on mechanisms and clinical perspectives in either AVM formation and progression or current and future therapies for HHT. Our hope is that this paper will represent the current progress and the remaining unanswered questions surrounding HHT, in order to serve as an update for those within the field and an invitation to those scientists and clinicians as yet outside of the field of HHT.
A defined clathrin-mediated trafficking pathway regulates sFLT1/VEGFR1 secretion from endothelial cells
Authors: Kinghorn Karina , Gill Amy , Marvin Allison , Li Renee , Quigley Kaitlyn , Singh Simcha , Gore Michaelanthony T. , le Noble Ferdinand , Gabhann Feilim Mac , Bautch Victoria L. 
Published: September 2023

AbstractFLT1/VEGFR1 negatively regulates VEGF-A signaling and is required for proper vessel morphogenesis during vascular development and vessel homeostasis. Although a soluble isoform, sFLT1, is often mis-regulated in disease and aging, how sFLT1 is trafficked and secreted from endothelial cells is not well understood. Here we define requirements for constitutive sFLT1 trafficking and secretion in endothelial cells from the Golgi to the plasma membrane, and we show that sFLT1 secretion requires clathrin at or near the Golgi. Perturbations that affect sFLT1 trafficking blunted endothelial cell secretion and promoted intracellular mis-localization in cells and zebrafish embryos. siRNA-mediated depletion of specific trafficking components revealed requirements for RAB27A, VAMP3, and STX3 for post-Golgi vesicle trafficking and sFLT1 secretion, while STX6, ARF1, and AP1 were required at the Golgi. Live-imaging of temporally controlled sFLT1 release from the endoplasmic reticulum showed clathrin-dependent sFLT1 trafficking at the Golgi into secretory vesicles that then trafficked to the plasma membrane. Depletion of STX6 altered vessel sprouting in 3D, suggesting that endothelial cell sFLT1 secretion influences proper vessel sprouting. Thus, specific trafficking components provide a secretory path from the Golgi to the plasma membrane for sFLT1 in endothelial cells that utilizes a specialized clathrin-dependent intermediate, suggesting novel therapeutic targets.
MICROSTATELAB: The EEGLAB Toolbox for Resting-State Microstate Analysis
Authors: Nagabhushan Kalburgi Sahana , Kleinert Tobias , Aryan Delara , Nash Kyle , Schiller Bastian , Koenig Thomas 
Published: September 2023

AbstractMicrostate analysis is a multivariate method that enables investigations of the temporal dynamics of large-scale neural networks in EEG recordings of human brain activity. To meet the enormously increasing interest in this approach, we provide a thoroughly updated version of the first open source EEGLAB toolbox for the standardized identification, visualization, and quantification of microstates in resting-state EEG data. The toolbox allows scientists to (i) identify individual, mean, and grand mean microstate maps using topographical clustering approaches, (ii) check data quality and detect outlier maps, (iii) visualize, sort, and label individual, mean, and grand mean microstate maps according to published maps, (iv) compare topographical similarities of group and grand mean microstate maps and quantify shared variances, (v) obtain the temporal dynamics of the microstate classes in individual EEGs, (vi) export quantifications of these temporal dynamics of the microstates for statistical tests, and finally, (vii) test for topographical differences between groups and conditions using topographic analysis of variance (TANOVA). Here, we introduce the toolbox in a step-by-step tutorial, using a sample dataset of 34 resting-state EEG recordings that are publicly available to follow along with this tutorial. The goals of this manuscript are (a) to provide a standardized, freely available toolbox for resting-state microstate analysis to the scientific community, (b) to allow researchers to use best practices for microstate analysis by following a step-by-step tutorial, and (c) to improve the methodological standards of microstate research by providing previously unavailable functions and recommendations on critical decisions required in microstate analyses.
Ocean Biology Studied from Space
Authors: Sathyendranath Shubha , Brewin Robert J. W. , Ciavatta Stefano , Jackson Tom , Kulk Gemma , Jönsson Bror , Vicente Victor Martinez , Platt Trevor 
Published: September 2023

AbstractVisible spectral radiometric measurements from space, commonly referred to as ocean-colour measurements, provide a rich stream of information on ocean biota as well as on biological and ecosystem processes. The strength of the ocean-colour technology for observing marine life lies in its global reach, combined with its ability to sample the field at a variety of spatial and temporal scales that match the scales of the processes themselves. Another advantage lies in the growing length of the time series of ocean-colour-derived products, enabiling investigations into any long-term changes, if present. This paper presents an overview of the principles and applications of ocean-colour data. The concentration of chlorophyll-a, the major pigment present in phytoplankton–single-celled, free-floating plants that are present in the sunlit layers of the ocean–was the first, and remains the most common, biological variable derived from ocean-colour data. Over the years, the list of ocean-colour products have grown to encompass many measures of the marine ecosystem and its functions, including primary production, phenology and ecosystem structure. Applications that exploit the data are many and varied, and include ecosystem-based fisheries management, biogeochemical cycles in the ocean, ecosystem health and climate change. An integrated approach, incorporating other modes of ocean observations and models with satellite observations, is needed to investigate the mysteries of the marine ecosystem.
Behavior of Mothers after Infant Loss in Bonnet Macaques (Macaca radiata)
Authors: Arlet Malgorzata E. , Anand Ashvita , Saikia Anushka , Kaasik Ants , Sirigeri Sindhuja , Isbell Lynne A. , Singh Mewa 
Published: September 2023

AbstractMother–offspring bonds in primates often last for life and shape the behavior of both mother and offspring. Therefore, the death of an infant may trigger an emotional response from its mother akin to human grief, which is characterized by active distress and passive depression. Our goal was to investigate whether the behavior of female bonnet macaques (Macaca radiata) changed after the loss of their infants. In the Thenmala area, southern India, between 2020 and 2022, we observed 18 mothers in two groups who lost, in total, 19 infants and three juveniles aged < 18 months. We compared affiliative, aggressive, and stress-related behavior of females before and after the death of their infants. We also examined individual variation in responses to infant loss. After the death of their infants, females withdrew socially, stayed on the periphery of the group, and had fewer companions. Bereaved females were less involved in grooming and hugging and initiated aggressive behavior more frequently than before they lost their infants. Moreover, females who lost infants showed frequent stress-related behaviors, such as self-scratching and yawning compared with when their infants were alive. Our results suggest that female bonnet macaques react to deaths of their infants in a manner that is consistent with the interpretation of grief in humans and other primates.
Domestic Violence among LGBT + People in China: Results from a national court rulings review
Authors: Lu Yuliang 
Published: September 2023

Abstract
Purpose
Domestic violence has been an emerging area of study in recent decades for lesbians, gay men, bisexuals, and transgender people (LGBT +). While some research discussed domestic violence among LGBT + couples in Western countries, very little attention was paid to the patterns of domestic violence in the Chinese context. Against this backdrop, this study sought to elucidate the prevalence and distinctive features of family violence against LGBT + individuals that have been recorded by court rulings, as well as to scrutinize the responses of the judicial system towards these cases of violence.

Methods
This study utilized a qualitative research approach, relying on court rulings as the primary data source. Specifically, data were collected from the official website that publishes judgments from courts at all levels of China. Content analysis and discourse analysis were employed as analytical techniques to uncover the underlying patterns of family violence among LGBT + people and examine the responses of the judicial system concerning the protection of LGBT + individuals.

Results
Through an analysis of the court rulings, the findings reveal a total of fifty-three cases of family violence involving LGBT + individuals. These cases constitute approximately ten percent of all criminal cases concerning the LGBT + population. Among these cases, forty cases involve violence perpetrated by LGBT + intimate partners. The violence can be further classified into distinct categories, including break-up violence, sexual violence, and violence occurring in daily life. The consequences of such violence typically result in fatalities or physical injuries. Another form of violence examined in the study is observed within legal partnerships, such as between a heterosexual husband and his lesbian wife. This type of violence also tends to lead to severe outcomes, including deaths or bodily harm to the victim. Furthermore, one noteworthy case of family violence discussed in the research involves a parent–child relationship.

Conclusions
This study uncovers multiple sources of violence experienced by LGBT + individuals within the context of domestic relationships in China. While LGBT + individuals can employ criminal law to protect their rights as citizens, the legal recognition of same-sex relationships remains rare. Yet, this legal recognition could change the situation in same-sex families troubled by family violence.
Footprint of a topological phase transition on the density of states
Authors: De Moor Joris , Sadel Christian , Schulz-Baldes Hermann 
Published: September 2023

AbstractFor a generalized Su–Schrieffer–Heeger model, the energy zero is always critical and hyperbolic in the sense that all reduced transfer matrices commute and have their spectrum off the unit circle. Disorder-driven topological phase transitions in this model are characterized by a vanishing Lyapunov exponent at the critical energy. It is shown that away from such a transition the density of states vanishes at zero energy with an explicitly computable Hölder exponent, while it has a characteristic divergence (Dyson spike) at the transition points. The proof is based on renewal theory for the Prüfer phase dynamics and the optional stopping theorem for martingales of suitably constructed comparison processes.
The impact of shareholder litigation risk on income smoothing
Authors: Li Yiwei , Song Wei , Sun Tingyu , Zhang Qingjing 
Published: September 2023

AbstractThis paper investigates whether and how shareholder litigation influences income smoothing. Using the ruling of the Ninth Circuit Court of Appeals in 1999 as an exogenous shock to the threat of litigation, we find that the increasing difficulty of class action lawsuits decreases income smoothing. This finding is robust to different model specifications. We also show that such an effect is stronger for firms that are more likely to face greater pressure from the threat of shareholder litigation risk. Overall, our findings extend the literature on investigating how class action lawsuits can affect the motivation of income smoothing.
Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks
Authors: Kwok Wai M. , Streftaris George , Dass Sarat C. 
Published: September 2023

AbstractParameter estimation and associated uncertainty quantification is an important problem in dynamical systems characterised by ordinary differential equation (ODE) models that are often nonlinear. Typically, such models have analytically intractable trajectories which result in likelihoods and posterior distributions that are similarly intractable. Bayesian inference for ODE systems via simulation methods require numerical approximations to produce inference with high accuracy at a cost of heavy computational power and slow convergence. At the same time, Artificial Neural Networks (ANN) offer tractability that can be utilized to construct an approximate but tractable likelihood and posterior distribution. In this paper we propose a hybrid approach, where Laplace-based Bayesian inference is combined with an ANN architecture for obtaining approximations to the ODE trajectories as a function of the unknown initial values and system parameters. Suitable choices of customized loss functions are proposed to fine tune the approximated ODE trajectories and the subsequent Laplace approximation procedure. The effectiveness of our proposed methods is demonstrated using an epidemiological system with non-analytical solutions—the Susceptible-Infectious-Removed (SIR) model for infectious diseases—based on simulated and real-life influenza datasets. The novelty and attractiveness of our proposed approach include (i) a new development of Bayesian inference using ANN architectures for ODE based dynamical systems, and (ii) a computationally fast posterior inference by avoiding convergence issues of benchmark Markov Chain Monte Carlo methods. These two features establish the developed approach as an accurate alternative to traditional Bayesian computational methods, with improved computational cost.
Very few scientific publications and newspaper articles focus on catastrophic events and their effects on urban wildlife
Authors: Walters Marlene , Cen Christina , Lung Julia , Li Yaochi , Lea Julianne , Yeh Pamela 
Published: September 2023

AbstractThe COVID-19 pandemic upended daily life and disrupted human activity in urban centers all over the world. Stay-at-home orders emptied urban spaces, removing or decreasing stressors on urban wildlife associated with human presence. Anecdotal observations of unusual urban wildlife behavior spread virally across social media, but some of these reports were proven false or fabricated. Here we examined both scientific publications and local newspapers to understand how extensively urban catastrophes are covered with respect to their effects on wildlife. We read all article titles from January 1980–June 2023 in 100 high impact journals in biology to determine if prior research exists that could inform our understanding of this phenomenon. Additionally, we used a keyword search to find scientific journal articles about wildlife responses during events in which large-scale evacuations of urban environments occurred. We found 37 scientific articles on this topic, with 13 of those published in the highest impact biology journals. The majority of publications identified (70%) were about wildlife responses to the COVID-19 public health response. Finally, we searched local newspapers in areas where hurricanes struck urban centers. We found 25 newspaper articles reporting on wildlife in relation to urban natural disasters. These were typically anecdotes, but nearly always consulted a credible, expert source. Ultimately, more research focused on urban areas before and after catastrophic or sudden changes will allow biologists to develop a baseline expectation for urban wildlife behavior in the absence of humans.
EEG-based emotion recognition using a temporal-difference minimizing neural network
Authors: Ju Xiangyu , Li Ming , Tian Wenli , Hu Dewen 
Published: September 2023

AbstractElectroencephalogram (EEG) emotion recognition plays an important role in human–computer interaction. An increasing number of algorithms for emotion recognition have been proposed recently. However, it is still challenging to make efficient use of emotional activity knowledge. In this paper, based on prior knowledge that emotion varies slowly across time, we propose a temporal-difference minimizing neural network (TDMNN) for EEG emotion recognition. We use maximum mean discrepancy (MMD) technology to evaluate the difference in EEG features across time and minimize the difference by a multibranch convolutional recurrent network. State-of-the-art performances are achieved using the proposed method on the SEED, SEED-IV, DEAP and DREAMER datasets, demonstrating the effectiveness of including prior knowledge in EEG emotion recognition.
The Occasional Democratisation of Party Leadership Selection: A Mechanism-Centred Approach
Authors: Küppers Anne 
Published: September 2023

AbstractMembership ballots have gained increasing popularity for party leadership selection around the globe. Still, our understanding of why parties use primaries is limited. This is due to two shortcomings of existing research: First, previous research has failed to satisfactorily operationalise subjective concepts such as electoral defeat. Second, quantitative studies cannot account for causal complexity. Thus, to uncover the puzzle of why parties use party primaries, this article pursues a novel approach. I offer new insights by using theory-testing process tracing to uncover the complex causal mechanisms that explain the use of membership ballots, taking Germany as an example. In the four cases studied, I find that it is a combination of an electoral shock, internal conflict, and instrumental motives that explain the decision to hold a primary for party leadership selection.