bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mortality prediction of the frailty syndrome in patients with severe mitral regurgitation
Authors: Shamekhi Jasmin , Al-Kassou Baravan , Weber Marcel , Goody Philip Roger , Zimmer Sebastian , Germeroth Jana , Gillrath Jana , Feldmann Katharina , Lohde Luisa , Sedaghat Alexander , Nickenig Georg , Sinning Jan-Malte 
Published: October 2022

AbstractIn this prospective observational study, we investigated the impact of geriatric syndromes and frailty on mortality and evaluated the prognostic value of different frailty, nutritional, and geriatric assessment tools in high-risk patients with severe mitral valve regurgitation (MR) who were evaluated for mitral valve therapies including surgical, interventional, and conservative treatment options. We prospectively assessed multiple parameters including the CONUT Score, the Katz Index of independence in activities of daily living (ADL), the Fried Frailty Phenotype (FFP), and the Essential Frailty Toolset (EFT) Score in 127 patients with severe symptomatic MR requiring surgical/interventional treatment versus conservative monitoring. We compared their predictive value on mortality including multivariate regression analysis to identify the most suitable tool to predict outcomes in these patient groups. The frailty syndrome as assessed with the CONUT Score, Katz Index, EFT Score, and FFP was associated with higher rates of comorbidities, significantly higher risk scores such as logistic EuroSCORE, EuroSCORE II, and STS-PROM, and significantly higher mortality rates. The EFT Score and FFP were independent predictors of one-year all-cause mortality in our study cohort (EFT Score: HR 1.9, 95% CI 1.2 to 3.2; p = 0.01; FFP: HR 1.8, 95% CI 1.1 to 3.1; p = 0.015). Geriatric syndromes and frailty are associated with increased mortality in high-risk patients with symptomatic severe MR. The EFT Score and the FFP were independent predictors of one-year all-cause mortality.
Prevalence and prediction of dropout during depression treatment in routine outpatient care: an observational study
Authors: van Dijk D. A. , Deen M. L. , van den Boogaard Th. M. , Ruhé H. G. , Spijker J. , Peeters F. P. M. L. 
Published: October 2022

AbstractEfficacious treatments are available for major depressive disorder (MDD), but treatment dropout is common and decreases their effectiveness. However, knowledge about prevalence of treatment dropout and its risk factors in routine care is limited. The objective of this study was to determine the prevalence of and risk factors for dropout in a large outpatient sample. In this retrospective cohort analysis, routinely collected data from 2235 outpatients with MDD who had a diagnostic work-up between 2014 and 2016 were examined. Dropout was defined as treatment termination without achieving remission before the fourth session within six months after its start. Total and item scores on the Dutch Measure for Quantification of Treatment Resistance in Depression (DM-TRD) at baseline, and demographic variables were analyzed for their association with dropout using logistic regression and elastic net analyses. Data of 987 subjects who started routine outpatient depression treatment were included in the analyses of which 143 (14.5%) dropped out. Higher DM-TRD-scores were predictive for lower dropout odds [OR = 0.78, 95% CI = (0.70–0.86),p < 0.001]. The elastic net analysis revealed several clinical variables predictive for dropout. Higher SES, higher depression severity, comorbid personality pathology and a comorbid anxiety disorder were significantly associated with less dropout in the sample. In this observational study, treatment dropout was relatively low. The DM-TRD, an easy-to-use clinical instrument, revealed several variables associated with less dropout. When applied in daily practice and combined with demographical information, this instrument may help to reduce dropout and increase treatment effectiveness.
Improved generalization performance of convolutional neural networks with LossDA
Authors: Liu Juncheng , Zhao Yili 
Published: October 2022

AbstractIn recent years, convolutional neural networks (CNNs) have been used in many fields. Nowadays, CNNs have a high learning capability, and this learning capability is accompanied by a more complex model architecture. Complex model architectures allow CNNs to learn more data features, but such a learning process tends to reduce the training model’s ability to generalize to unknown data, and may be associated with problems of overfitting. Although many regularization methods have been proposed, such as data augmentation, batch normalization, and Dropout, research on improving generalization performance is still a common concern in the training process of robust CNNs. In this paper, we propose a dynamically controllable adjustment method, which we call LossDA, that embeds a disturbance variable in the fully-connected layer. The trend of this variable is kept consistent with the training loss, while the magnitude of the variable can be preset to adapt to the training process of different models. Through this dynamic adjustment, the training process of CNNs can be adaptively adjusted. The whole regularization process can improve the generalization performance of CNNs while helping to suppress overfitting. To evaluate this method, this paper conducts comparative experiments on MNIST, FashionMNIST, CIFAR-10, Cats_vs_Dogs, and miniImagenet datasets. The experimental results show that the method can improve the model performance of Light CNNs and Transfer CNNs (InceptionResNet, VGG19, ResNet50, and InceptionV3). The average maximum improvement in accuracy of Light CNNs is 4.62%, F1 is 3.99%, and Recall is 4.69%. The average maximum improvement accuracy of Transfer CNNs is 4.17%, F1 is 5.64%, and Recall is 4.05%.
Search, save and share: family historians’ engagement practices with digital platforms
Authors: Roued Henriette , Castenbrandt Helene , Revuelta-Eugercios Bárbara Ana 
Published: October 2022

AbstractAlongside established heritage institutions, family historians are central figures in the ecosystem of digital heritage, both as contributors to and users of digitized historical sources. With that in mind, this research aims for a wide examination of family historians' engagement with the broader selection of available digital platforms, providing knowledge about how and why they choose to use one platform over another. This knowledge is important for the future development of sustainable digital platforms in the heritage sector. With a large variety of digitized source providers, many with free access platforms, Denmark and Danish family historians make an excellent case for this study. Through both a questionnaire and focus group interviews, using a grounded theory approach, this study has developed a model of engagement with digital platforms, referred to as a buffet model. This model illustrates how family historians pick and choose from a selection of digital platforms throughout their search and management of information as well as their community interaction. Moreover, through the lens of the Serious Leisure Perspective we find that family history is often a life-long leisure activity and family historians’ usage of digital platforms support this finding.
What is a fish? The life and legend of David L.G. Noakes
Authors: Bouvier Lynn D. , Baylis Jeffrey R. , Klemetsen Anders , Kristjánsson Bjarni K. , Li Judith L. , Magnan Pierre , McLaughlin Robert L. , Muir Andrew M. , Sakakura Yoshitaka , Skúlason Skúli 
Published: October 2022

AbstractDavid Lloyd George Noakes (1942–2020) is best known for his insatiable curiosity, his quick wit and dry sense of humor, his scientific contributions to the field of animal behaviour, and his ability to form and maintain long-lasting connections. His research interests were vast but remained grounded in early life history, behaviour, social behaviour, the evolution of behaviour, behavioural genetics, and evolutionary ecology. David had a remarkable ability to establish and maintain strong connections within the international academic community. David was also internationally recognized for his numerous contributions as a scientific editor, promoting accessibility to the international community that he served. We memorialize David’s legacy in this tribute article, ensuring that his accomplishments and the momentous impact he had on the scientific community are not soon forgotten.
An MMC-Based Temperature Control System for a Long-Term Data Collection
Authors: Woo K. R. , Kim H. B. , Kim H. L. , Kim Y. H. , Kwon D. H. , Lee D. Y. , Lee H. J. , Lee S. H. , Lee Y. C. , Lim H. S. 
Published: October 2022

AbstractWe developed a two-stage temperature control system for a long-term stable measurement of AMoRE neutrinoless double beta decay experiment using a dilution refrigerator. The first-stage control was made with a standard PID system using an AC bridge with a ruthenium oxide thermometer as the main thermometer of the mixing chamber plate. The second-stage control was obtained with a magnetic microcalorimeter (MMC) that is configured as a sensitive thermometer for a detector tower, the main experiment. Under single-stage temperature control on the temperature of the mixing chamber plate only with the RuO2 thermometer, the MMC recorded temperature stability of the detector plate of 9 μK rms over 100 min. Under two-stage temperature control, with the first-stage of the mixing chamber plate at 11 mK via the RuO2 thermometer and the second-stage of the detector plate at 12 mK via the MMC, the MMC recorded a temperature stability of 0.5 μK rms over 100 min. Moreover, the heat channels of the AMoRE experiment obtained considerable improvement in energy resolutions when switching from single-stage (RuO2) to two-stage (RuO2 + MMC) control.
Promoting Child Development During the COVID-19 Pandemic: Parental Perceptions of Tele-Home Visits in Early Head Start Programs
Authors: Vicente Delia , Venegas Melanie , Coker Tumaini R. , Guerrero Alma D. 
Published: October 2022

Abstract
Objective
The COVID-19 pandemic prompted families to receive Early Head Start (EHS) home-based services virtually. This qualitative study evaluated parental perceptions of EHS tele-home visits.

Methods
EHS parents who had transitioned to tele-home visits using any video-chat platform were recruited to participate in a Spanish or English virtual focus group that assessed their perceptions of tele-home visits. Using an iterative, consensus-seeking inductive content analysis approach, themes and subthemes were identified.

Results
Thirty-five mothers of children newborn to 3-years-old, where the majority were Latino and Spanish-speaking, participated in four focus groups. Several patterns pertaining to technology, child engagement, child learning and development, and parent-home visitor relationship emerged in the qualitative analysis. Mothers revealed varying degrees of digital proficiency, device preference, and technology challenges. Mothers reported variability in child engagement and concerns with missed socialization opportunities for children as a results of tele-home visits, but also reported increased self-efficacy in supporting child development, positive relationships with their home visitor, and overall satisfaction with services.

Conclusion
Parents revealed tele-home visits have the potential to be a viable service delivery method for EHS home-based programs. While parents perceived increased engagement and an uncompromised parent-home visitor relationship, they revealed areas of needed support that would optimize the use of tele-home visits.
COVID-19 Vaccination is not a Sufficient Public Policy to face Crisis Management of next Pandemic Threats
Authors: Coccia Mario 
Published: October 2022

AbstractThis study reveals that a vast vaccination campaign is a necessary but not sufficient public policy to reduce the negative impact of Coronavirus Disease 2019 (COVID-19) pandemic crisis because manifold factors guide the spread of this new infectious disease and related mortality in society. Statistical evidence here, based on a worldwide sample of countries, shows a positive correlation between people fully vaccinated and COVID-19 mortality (r = + 0.65, p-value < 0.01). Multivariate regression, controlling income per capita, confirms this finding. Results suggest that the increasing share of people vaccinated against COVID-19 seems to be a necessary but not sufficient health policy to reduce mortality of COVID-19. The findings here can be explained with the role of Peltzman effect, new variants, environmental and socioeconomic factors that affect the diffusion and negative impact of COVID-19 pandemic in society. This study extends the knowledge in this research field to design effective public policies of crisis management for facing next pandemic threats.
Evaluating the online impact of reporting guidelines for randomised trial reports and protocols: a cross-sectional web-based data analysis of CONSORT and SPIRIT initiatives
Authors: Orduña-Malea Enrique , Alonso-Arroyo Adolfo , Ontalba-Ruipérez José-Antonio , Catalá-López Ferrán 
Published: October 2022

AbstractReporting guidelines are tools to help improve the transparency, completeness, and clarity of published articles in health research. Specifically, the CONSORT (Consolidated Standards of Reporting Trials) and SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statements provide evidence-based guidance on what to include in randomised trial articles and protocols to guarantee the efficacy of interventions. These guidelines are subsequently described and discussed in journal articles and used to produce checklists. Determining the online impact (i.e., number and type of links received) of these articles can provide insights into the dissemination of reporting guidelines in broader environments (web-at-large) than simply that of the scientific publications that cite them. To address the technical limitations of link analysis, here the Debug-Validate-Access-Find (DVAF) method is designed and implemented to measure different facets of the guidelines’ online impact. A total of 65 articles related to 38 reporting guidelines are taken as a baseline, providing 240,128 URL citations, which are then refined, analysed, and categorised using the DVAF method. A total of 15,582 links to journal articles related to the CONSORT and SPIRIT initiatives were identified. CONSORT 2010 and SPIRIT 2013 were the reporting guidelines that received most links (URL citations) from other online objects (5328 and 2190, respectively). Overall, the online impact obtained is scattered (URL citations are received by different article URL IDs, mainly from link-based DOIs), narrow (limited number of linking domain names, half of articles are linked from fewer than 29 domain names), concentrated (links come from just a few academic publishers, around 60% from publishers), non-reputed (84% of links come from dubious websites and fake domain names) and highly decayed (89% of linking domain names were not accessible at the time of the analysis). In light of these results, it is concluded that the online impact of these guidelines could be improved, and a set of recommendations are proposed to this end.
A Review of the Extended EUV Corona Observed by the Sun Watcher with Active Pixels and Image Processing (SWAP) Instrument
Authors: West Matthew J. , Seaton Daniel B. , D’Huys Elke , Mierla Marilena , Laurenza Monica , Meyer Karen A. , Berghmans David , Rachmeler Laurel R. , Rodriguez Luciano , Stegen Koen 
Published: October 2022

AbstractThe Sun Watcher with Active Pixels and Image Processing (SWAP) instrument onboard ESA’s PRoject for On Board Autonomy 2 (PROBA2) has provided the first uncompressed, high-cadence, continuous, large field-of-view observations of the extended extreme-ultraviolet (EUV) corona for over a complete solar cycle. It has helped shape our understanding of this previously understudied region, and pioneered research into the middle corona. In this article, we present a review of all publications that have utilized these observations to explore the extended EUV corona, highlighting the unique contributions made by SWAP. The review is broadly divided into three main sections of SWAP-based studies about: i) long-lived phenomena, such as streamers, pseudo-streamers, and coronal fans; ii) dynamic phenomena, such as eruptions, jets, EUV waves, and shocks; iii) coronal EUV emission generation. We also highlight SWAP’s imaging capabilities, techniques that have been applied to observations to enhance the off-limb observations and its legacy.
$$\pi $$VAE: a stochastic process prior for Bayesian deep learning with MCMC
Authors: Mishra Swapnil , Flaxman Seth , Berah Tresnia , Zhu Harrison , Pakkanen Mikko , Bhatt Samir 
Published: October 2022

AbstractStochastic processes provide a mathematically elegant way to model complex data. In theory, they provide flexible priors over function classes that can encode a wide range of interesting assumptions. However, in practice efficient inference by optimisation or marginalisation is difficult, a problem further exacerbated with big data and high dimensional input spaces. We propose a novel variational autoencoder (VAE) called the prior encoding variational autoencoder ($$\pi $$
π
VAE). $$\pi $$
π
VAE is a new continuous stochastic process. We use $$\pi $$
π
VAE to learn low dimensional embeddings of function classes by combining a trainable feature mapping with generative model using a VAE. We show that our framework can accurately learn expressive function classes such as Gaussian processes, but also properties of functions such as their integrals. For popular tasks, such as spatial interpolation, $$\pi $$
π
VAE achieves state-of-the-art performance both in terms of accuracy and computational efficiency. Perhaps most usefully, we demonstrate an elegant and scalable means of performing fully Bayesian inference for stochastic processes within probabilistic programming languages such as Stan.
The role of digital technologies for the LCA empowerment towards circular economy goals: a scenario analysis for the agri-food system
Authors: Sica Daniela , Esposito Benedetta , Malandrino Ornella , Supino Stefania 
Published: October 2022

Abstract
Purpose
This paper aims to develop a scenario analysis on the experts’ perceptions of benefits and barriers related to adopting digital technologies for the life cycle assessment (LCA) to catalyse a circular economy transition in the agri-food system.

Methods
A literature review was performed to identify LCA’s digital technologies that can be implemented within the agri-food system. Furthermore, an in-depth interview with a panel of senior researchers was conducted to establish a set of items and assess the perceived benefits and barriers associated with an “empowered LCA”, i.e. a future-oriented LCA based on digital technologies. To this end, a two-stage exploratory factor analysis relying on the principal component analysis technique was carried out to refine the set of items. Finally, a covariance-based structural equation model was performed, built on a confirmatory factor analysis, to test the measurement model.

Results and discussion
The study’s findings provide five constructs to explore the potential benefits and barriers related to adopting a digital technologies-based LCA (empowered LCA) for a circular economy transition in the agri-food system. More specifically, the benefits can be assessed using the following constructs: “benefits for the data collection and analysis”, “benefits for the LCA analysts”, “benefits for the management” and “benefits for traceability”. In addition, the barriers have been evaluated using a single construct labelled “general barriers”.

Conclusions
The study highlights the relevance of digital technologies for a circular economy transition to develop a more reliable LCA, enhancing legislative compliance and supporting the traceability processes in the agri-food system. The associated implications for LCA experts, agri-food managers and policymakers are presented. Furthermore, limitations and future research directions are also discussed.
Exopolysaccharide production from Alkalibacillus sp. w3: statistical optimization and biological activity
Authors: Arayes Mervat A. , Mabrouk Mona E. M. , Sabry Soraya A. , Abdella Bahaa 
Published: October 2022

AbstractMicrobial exopolysaccharides (EPS) provide a broad range of applications. Thus, there is an increasing interest in the production, characterization, and use of EPS derived from various microorganisms. Extremophile polysaccharides have unique properties and applications due to its unique structures. The importance of exopolysaccharides synthesized by a new bacterial strain, Alkalibacillus sp. w3, was highlighted in this study. Alkalibacillus sp. w3, a haloalkalitolerant firmicute that was recovered from a salt lake, was optimized for EPS production, and its biological activities were studied. Exopolysaccharide synthesis was observed in Horikoshi I broth medium. The optimal culture conditions for achieving the highest exopolysaccharide production were a 7-day incubation period, pH 10, and 250 g/L of NaCl. The most effective carbon and nitrogen sources for EPS production were glucose and a combination of yeast extract and peptone. Additionally, Plackett-statistical Burman’s design showed that all factors tested had a favorable impact, with glucose having the greatest significance on the production of EPS. The model’s best predictions for culture conditions resulted in a two-fold improvement in EPS production compared to the original yield before optimization. The recovered EPS contained 65.13% carbohydrates, 30.89% proteins, and 3.98% lipids. Moreover, EPS produced by Alkalibacillus sp. w3 demonstrated anticancer activity against hepatocellular carcinoma (HepG2) and human colon carcinoma (HCT-116) cell lines, with IC50 values as low as 11.8 and 15.5 µg/mL, respectively, besides antibacterial activity against various Gram-positive, Gram-negative bacteria, and yeast. Based on these results, EPS made by Alkalibacillus sp. w3 has many useful properties, which make it suitable for use in the medical field.
Non-functioning pituitary microadenoma in children and adolescents: Is follow-up with diagnostic imaging necessary?
Authors: Borghammar Camilla , Tamaddon Ashkan , Erfurth Eva-Marie , Sundgren Pia C. , Siesjö Peter , Elfving Maria , Nilsson Margareta 
Published: October 2022

Abstract
Purpose
No consensus exists regarding follow-up recommendations for suspected pituitary microadenoma in children. To address this knowledge gap, we investigated the growth potential of pituitary solid and cystic lesions <10 mm in children and evaluated the accuracy of magnetic resonance imaging (MRI) measurements.

Methods
The children included were <18 years at first pituitary MRI and radiologically diagnosed with a non-functioning microadenoma or cyst <10 mm. Lesion size at first and latest MRI as well as all individual MRI examinations were re-evaluated.

Results
In total, 74 children, median age 12 years (range 3–17), had a non-functioning microadenoma, probable microadenoma, or cyst. Of these, 55 underwent repeated MRI (median 3, range 2–7) with a median follow-up of 37 months (range 4–189). None of the pituitary lesions without hormonal disturbances increased significantly during follow-up. Two radiologists agreed that no lesion could be identified in 38/269 (14%) MRI examinations, and in 51/231 (22%) they disagreed about lesion location. In 34/460 (7%) MRI measurements size differed >2 mm, which had been considered significant progression.

Conclusion
Non-functioning pituitary microadenoma in children has small size variations, often below the spatial resolution of the scanners. We suggest lesions <4 mm only for clinical follow-up, lesions 4–6 mm for MRI after 2 years and ≥7 mm MRI after 1 and 3 years, with clinical follow-up in between. If no progression, further MRI should only be performed after new clinical symptoms or hormonal disturbances.