bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal stability of fecal cortisol metabolites in mountain-dwelling ungulates
Authors: Donini Valerio , Iacona Elisa , Pedrotti Luca , Macho-Maschler Sabine , Palme Rupert , Corlatti Luca 
Published: March 2022

AbstractFecal cortisol metabolites (FCMs) are widely used to track stress responses in wildlife and captive species. Rules of thumb suggest that samples should be collected as soon as possible after defecation, to avoid decay of FCMs. To date, however, only a few studies investigated the stability of defecated FCMs over time, and most of them were conducted in controlled laboratory conditions. Here, we investigated the stability of FCMs over seven consecutive days, in two mountain-dwelling ungulates, under natural environmental conditions using a semi-experimental approach. Fecal samples from Northern chamoisRupicapra rupicapra(n = 24) and red deerCervus elaphus(n = 22) were collected in summer of 2020 within the Stelvio National Park, Italy, and placed in an open area above 2000 m a.s.l. For the next 7 days, we collected a portion of each sample, and all sub-samples were analyzed with an 11-oxoetiocholanolone enzyme immunoassay. Exposure, temperature, and precipitation were fitted as covariates in non-linear generalized mixed models to assess FCM variation over time, and competing models were selected using AICc. For chamois, the best model included only time as a predictor, while for red deer, it included time, precipitation, and exposure. For both species, FCM values decreased rapidly from the first days after deposition until the fourth day. For red deer, in northern-exposed samples, FCM values decreased slower than in south-exposed ones; furthermore, FCM values increased with increasing precipitation. Our results offer a solid methodological basis to wildlife researchers and practitioners interested in the investigation of the ecological factors affecting stress variation in wildlife and support the recommendation to collect samples as fresh as possible, to avoid misleading inference. Further studies are necessary to evaluate the stability of FCMs when other enzyme immunoassays are used.
In vitro angiotensin-converting enzyme and dipeptidyl peptidase-IV inhibitory, and antioxidant activity of blue mussel (Mytilus edulis) byssus collagen hydrolysates
Authors: CunhaNeves Adriana , Harnedy-Rothwell Pádraigín A. , FitzGerald Richard J. 
Published: March 2022

AbstractLarge quantities of mussel byssus are generated annually as a co-product of the mussel-processing industry. This fibrous material is a rich source of collagen, which when extracted has potential uses as an alternative source of collagen for food applications. However, due the complex structure of the material, the extraction of the collagenous components using food-friendly strategies has proved challenging to date. An enzyme-aided method, using a proline endoproteinase, was employed for the extraction of collagen from mussel byssus yielding 138.82 ± 2.25 mg collagen/g dry weight. Hydrolysates of the collagen extract were generated using five food-grade enzyme preparations with Corolase® PP giving the highest extent of hydrolysis. Reversed-phase and gel permeation high-performance liquid chromatography of the extracted collagen and its enzymatic hydrolysates showed significant hydrolysis of collagen. The hydrolysates generated with Corolase® PP showed the highest in vitro bioactivities: angiotensin-converting enzyme (ACE) IC50 = 0.79 ± 0.17 mg/ml, dipeptidyl peptidase-IV (DPP-IV) IC50 = 0.66 ± 0.17 mg/ml and oxygen radical absorbance capacity (ORAC) activity = 311.23 ± 13.41 µmol trolox equivalents (TE)/g. The results presented herein indicate that in addition to acting as an alternative source of collagen for food applications, mussel byssus collagen-derived hydrolysates have potential applications as functional food ingredients for the management of metabolic diseases such as type II diabetes and hypertension.
Surgical Task‐Sharing in the Western Canadian Arctic: A Networked Model Between Family Physicians with Enhanced Surgical Skills and Specialist Surgeons
Authors: Falk Ryan , Topstad Dawnelle , Lee Laura 
Published: March 2022

AbstractBackgroundWith the loss of generalism in the surgical specialties, there has been a move in Canada to train family physicians in enhanced surgical skills (FP‐ESS) to address the surgical needs of rural and remote populations. This research project sought to describe one network integrating FP‐ESS and specialist surgeons, focusing on the role of FP‐ESS and their relationship with specialist surgeons, in the surgical care of the Beaufort Delta Region of the Northwest Territories of Canada.MethodsUsing a participatory approach, semi‐structured interviews were conducted with 22 stakeholders within the surgical system. Interviews were transcribed and reviewed, then imported into NVivo 12 for analysis. First‐level coding was performed based on both deductive and inductive reasoning in an iterative fashion during interview collection to develop and refine the codebook. This was followed by second‐level categorizing.ResultsThe FP‐ESS physicians provide cesarean section services to maintain a local obstetrics program, to provide gastrointestinal endoscopy, and to provide emergency on‐call support, as described by one stakeholder. FP‐ESS work together with specialist surgeons through an informal network keeping surgical care as close to home as possible. FP‐ESS within this health regions were seen as “a really big gain to the system.”ConclusionsThis study deepens our understanding of rural surgical service delivery, in particular where FP‐ESS and specialist surgeons function collaboratively. It also contributes to strengthening rural surgical systems in Canada and therefore to addressing the health gap between rural/remote/indigenous and urban populations.
Possible climatically driven, later prehistoric woodland decline on Ben Lomond, central Scotland
Authors: Barclay Rebecca , Ferreira Carla , Ballantyne Emma , Tipping Richard , Tisdall Eileen 
Published: March 2022

AbstractLater prehistoric woodland decline over most parts of Scotland is widely regarded as having been anthropogenic, via a range of mechanisms, to create farmland. Climatic causes are seen only to have driven the rapid expansion and then terminal decline of Pinus sylvestris around 2000 cal BC. Here we report radiocarbon dated analyses of pollen, microscopic charcoal, coprophilous fungal spores and peat humification from a small, water-shedding interfluve peat bog at 230 m elevation on the west-facing slope of the mountain Ben Lomond in west-central Scotland. The record spans the interval ca. 3450 − 200 cal BC. It shows marked and rapid changes in woodland composition before ca. 2600 cal BC, and from then to ca. 1940 cal BC a gradual decline of Betula woodland. This happened with no palaeoecological or archaeological evidence for anthropogenic activity. Woodland decline is interpreted at this site as climatically driven, perhaps through paludification or, more likely, exposure to wind, within a period of pronounced climatic deterioration. Anthropogenic activities are hinted at only after ca. 850 cal BC.
Comparisons of the risk of myopericarditis between COVID-19 patients and individuals receiving COVID-19 vaccines: a population-based study
Authors: Chou Oscar Hou In , Zhou Jiandong , Lee Teddy Tai Loy , Kot Thompson , Lee Sharen , Wai Abraham Ka Chung , Wong Wing Tak , Zhang Qingpeng , Cheng Shuk Han , Liu Tong , Vassiliou Vassilios S. , Cheung Bernard Man Yung , Tse Gary 
Published: March 2022

Abstract
Background
Both COVID-19 infection and COVID-19 vaccines have been associated with the development of myopericarditis. The objective of this study is to (1) analyse the rates of myopericarditis after COVID-19 infection and COVID-19 vaccination in Hong Kong, (2) compared to the background rates, and (3) compare the rates of myopericarditis after COVID-19 vaccination to those reported in other countries.

Methods
This was a population-based cohort study from Hong Kong, China. Patients with positive RT-PCR test for COVID-19 between 1st January 2020 and 30th June 2021 or individuals who received COVID-19 vaccination until 31st August were included. The main exposures were COVID-19 positivity or COVID-19 vaccination. The primary outcome was myopericarditis.

Results
This study included 11,441 COVID-19 patients from Hong Kong, four of whom suffered from myopericarditis (rate per million: 326; 95% confidence interval [CI] 127–838). The rate was higher than the pre-COVID-19 background rate in 2019 (rate per million: 5.5, 95% CI 4.1–7.4) with a rate ratio of 55.0 (95% CI 21.4–141). Compared to the background rate, the rate of myopericarditis among vaccinated subjects in Hong Kong was similar (rate per million: 5.5; 95% CI 4.1–7.4) with a rate ratio of 0.93 (95% CI 0.69–1.26). The rates of myocarditis after vaccination in Hong Kong were comparable to those vaccinated in the United States, Israel, and the United Kingdom.

Conclusions
COVID-19 infection was associated with significantly higher rate of myopericarditis compared to the vaccine-associated myopericarditis.

Graphical abstract
Simulation of ITD-Dependent Single-Neuron Responses Under Electrical Stimulation and with Amplitude-Modulated Acoustic Stimuli
Authors: Hu Hongmei , Klug Jonas , Dietz Mathias 
Published: March 2022

AbstractInteraural time difference (ITD) sensitivity with cochlear implant stimulation is remarkably similar to envelope ITD sensitivity using conventional acoustic stimulation. This holds true for human perception, as well as for neural response rates recorded in the inferior colliculus of several mammalian species. We hypothesize that robust excitatory-inhibitory (EI) interaction is the dominant mechanism. Therefore, we connected the same single EI-model neuron to either a model of the normal acoustic auditory periphery or to a model of the electrically stimulated auditory nerve. The model captured most features of the experimentally obtained response properties with electric stimulation, such as the shape of rate-ITD functions, the dependence on stimulation level, and the pulse rate or modulation-frequency dependence. Rate-ITD functions with high-rate, amplitude-modulated electric stimuli were very similar to their acoustic counterparts. Responses obtained with unmodulated electric pulse trains most resembled acoustic filtered clicks. The fairly rapid decline of ITD sensitivity at rates above 300 pulses or cycles per second is correctly simulated by the 3.1-ms time constant of the inhibitory post-synaptic conductance. As the model accounts for these basic properties, it is expected to help in understanding and quantifying the binaural hearing abilities with electric stimulation when integrated in bigger simulation frameworks.
Formalizing the four-layer metamodeling stack with MetaMorph: potential and benefits
Authors: Döller Victoria 
Published: March 2022

AbstractEnterprise modeling deals with the increasing complexity of processes and systems by operationalizing model content and by linking complementary models and languages, thus amplifying the model value beyond mere comprehensible pictures. To enable this amplification and turn models into computer-processable structures, a comprehensive formalization is needed. This paper presents the formalismMetaMorphbased on typed first-order logic and provides a perspective on the potential and benefits of formalization that arise for a variety of research issues in conceptual modeling.MetaMorphdefines modeling languages as formal languages with a signature$$\varSigma $$Σ—comprising object types, relation types, and attributes through types and function symbols—and a set of constraints. Four case studies are included to show the effectiveness of this approach. Applying theMetaMorphformalism to the next level in the hierarchy of models, we create , a formal modeling language for metamodels. We show that is self-describing and therefore complete the formalization of the full four-layer metamodeling stack. On the basis of our generic formalism applicable to arbitrary modeling languages, we examine four current research topics—modeling with power types, language interleaving & consistency, operations on models, and automatic translation of formalizations to platform-specific code—and how to approach them with theMetaMorphformalism. This shows that the rich knowledge stack on formal languages in logic offers new tools for old problems.
Trust in Healthcare during COVID-19 in Europe: vulnerable groups trust the least
Authors: Beller Johannes , Schäfers Jürgen , Haier Jörg , Geyer Siegfried , Epping Jelena 
Published: March 2022

Abstract
Aim
We examined predictors of trust in the healthcare system during the COVID-19 pandemic in 27 European countries.

Subjects and methods
We used population-based data drawn from the Living, working and COVID-19 survey (N = 21,884, 52% female, ages 18 to 92 years) covering 27 European countries dated June and July 2020. Multilevel linear regression, linear regression, and regression-tree analyses were conducted.

Results
We found that most participants tended to trust the healthcare system, although a substantial part could still be classified as distrusting (approx. 21%). Multiple variables, including being middle-aged or of older age, being female, lower levels of education, unemployment, worse general health status, having income difficulties, having unmet needs for healthcare, no healthcare contact during the COVID-19 pandemic, higher mental distress, and loneliness, were significantly associated with lower levels of trust. Among these variables mental distress, income difficulties, and unmet needs for healthcare emerged as especially important and, across European regions and countries, consistent predictors for lower trust in the healthcare system during the COVID-19 pandemic.

Conclusions
Medically vulnerable subgroups, such as individuals with unmet healthcare needs, higher levels of mental distress, and older age, as well as people living in socially and economically vulnerable situations, such as higher levels of loneliness and financial difficulties, were the least trusting of the healthcare system during the COVID-19 pandemic. As these vulnerable subgroups are also at highest risk for contracting COVID-19 and experiencing negative COVID-19-related outcomes, more targeted prevention and intervention efforts should be implemented in these groups.
Physical activity, mental and physical health during the Covid-19 outbreak: longitudinal predictors of suicide ideation in Germany
Authors: Brailovskaia Julia , Truskauskaite-Kuneviciene Inga , Kazlauskas Evaldas , Gelezelyte Odeta , Teismann Tobias , Margraf Jürgen 
Published: March 2022

Abstract
Aim
Suicide ideation has increased since the outbreak of Covid-19 in many countries. The present longitudinal study investigated potential predictors of suicide ideation.

Subject and methods
Data of 406 participants from Germany (age M = 27.69, SD = 6.88) were assessed via online surveys in spring 2020 (baseline, BL) and in spring 2021 (follow-up, FU).

Results
The current results reveal a significant increase in symptoms of depression, anxiety, and stress between 2020 and 2021. Positive mental health (PMH), sense of control, and physical health significantly decreased. Depression symptoms (BL), PMH (BL), and consciously enhanced physical activity since the pandemic outbreak (FU) significantly predicted 12-month suicide ideation (FU). In a moderated mediation analysis, the positive relationship between depression and suicide ideation was significantly mediated by PMH. Consciously enhanced physical activity significantly moderated the negative association between PMH and suicide ideation.

Conclusion
The context of Covid-19 could negatively impact mental health and physical health. This might increase the risk for suicide ideation. However, PMH and physical activity might serve as protective factors. The protective effect of physical activity could be especially important in people with high depression symptoms and low PMH, such as clinical patients. Potential ways of how PMH and physical activity could be enhanced in the Covid-19 context to prevent suicide ideation are discussed.
High-Temperature Superconductivity in Hydrides: Experimental Evidence and Details
Authors: Eremets M. I. , Minkov V. S. , Drozdov A. P. , Kong P. P. , Ksenofontov V. , Shylin S. I. , Bud’ko S. L. , Prozorov R. , Balakirev F. F. , Sun Dan , Mozaffari S. , Balicas L. 
Published: March 2022

AbstractSince the discovery of superconductivity at ~ 200 K in H3S [1], similar or higher transition temperatures,Tcs, have been reported for various hydrogen-rich compounds under ultra-high pressures [2]. Superconductivity was experimentally proved by different methods, including electrical resistance, magnetic susceptibility, optical infrared, and nuclear resonant scattering measurements. The crystal structures of superconducting phases were determined by X-ray diffraction. Numerous electrical transport measurements demonstrate the typical behavior of a conventional phonon-mediated superconductor: zero resistance belowTc, shift ofTcto lower temperatures under external magnetic fields, and pronounced isotope effect. Remarkably, the results are in good agreement with the theoretical predictions, which describe superconductivity in hydrides within the framework of the conventional BCS theory. However, despite this acknowledgement, experimental evidences for the superconducting state in these compounds have recently been treated with criticism [3–7], which apparently stems from misunderstanding and misinterpretation of complicated experiments performed under very high pressures. Here, we describe in greater detail the experiments revealing high-temperature superconductivity in hydrides under high pressures. We show that the arguments against superconductivity [3–7] can be either refuted or explained. The experiments on the high-temperature superconductivity in hydrides clearly contradict the theory of hole superconductivity [8] and eliminate it [3].
A Unified Neural Network Framework for Extended Redundancy Analysis
Authors: Vijayakumar Ranjith , Choi Ji Yeh , Jung Eun Hwa 
Published: March 2022

AbstractComponent-based approaches have been regarded as a tool for dimension reduction to predict outcomes from observed variables in regression applications. Extended redundancy analysis (ERA) is one such component-based approach which reduces predictors to components explaining maximum variance in the outcome variables. In many instances, ERA can be extended to capture nonlinearity and interactions between observed and components, but only by specifying a priori functional form. Meanwhile, machine learning methods like neural networks are typically used in a data-driven manner to capture nonlinearity without specifying the exact functional form. In this paper, we introduce a new method that integrates neural networks algorithms into the framework of ERA, called NN-ERA, to capture any non-specified nonlinear relationships among multiple sets of observed variables for constructing components. Simulations and empirical datasets are used to demonstrate the usefulness of NN-ERA. The conclusion is that in social science datasets with unstructured data, where we expect nonlinear relationships that cannot be specified a priori, NN-ERA with its neural network algorithmic structure can serve as a useful tool to specify and test models otherwise not captured by the conventional component-based models.
Blood biochemical variables, antioxidative status, and histological features of intestinal, gill, and liver tissues of African catfish (Clarias gariepinus) exposed to high salinity and high-temperature stress
Authors: Dawood Mahmoud A. O. , Noreldin Ahmed E. , Sewilam Hani 
Published: March 2022

AbstractAfrican catfish is a freshwater species with a high ability to resist brackish water conditions, but heat stress may impair the health status of fish. Thus, the impact of varying levels of water salinity (0, 4, 8, and 12 ppt) was investigated on the growth performance, survival rate, and blood biochemistry of African catfish (average weight: 180.58 ± 2.8 g and average length: 38 ± 1.2 cm) for 4 weeks; then, fish were stressed with high temperature (32 °C) for 72 h. The growth performance and survival rate were markedly higher in fish reared in 0, 4, and 8 ppt than fish in 12 ppt (p < 0.05). Before heat stress, the superoxide dismutase (SOD), catalase (CAT), glutathione (GSH) activities, and malondialdehyde (MDA) levels were markedly increased in fish stressed with 12-ppt salinity (p < 0.05). After heat stress, all groups showed a marked increased SOD, CAT, GSH, and MDA levels than fish before heat stress in the same manner (p < 0.05). Furthermore, fish in the 12 ppt group showed severe intestinal, gill, and liver histological features. The levels of blood glucose and cortisol were markedly increased in fish exposed with 8 and 12 ppt than 0 ppt gradually either before or after heat stress (p < 0.05). The highest values of ALT, AST, urea, creatinine, and the lowest total protein, albumin, and globulin were observed in fish reared in 12 ppt. Significant salinity and heat stress interactions were seen on the ALT, AST, urea, creatinine, total protein, albumin, and globulin values (p < 0.05). The integrated multi-biomarker response (IBR) results showed marked differences among the groups and increased gradually before and after heat stress, with the highest IBR in 12 ppt. In conclusion, growing African catfish in high salinity (12 ppt) hampered the growth performance and health status while the heat stress improved the antioxidative status vis-a-vis increased lipid peroxidation along with higher stress-related markers in expressed both blood and tissue.
The Promises and Challenges of Artificial Intelligence for Teachers: a Systematic Review of Research
Authors: Celik Ismail , Dindar Muhterem , Muukkonen Hanni , Järvelä Sanna 
Published: March 2022

AbstractThis study provides an overview of research on teachers’ use of artificial intelligence (AI) applications and machine learning methods to analyze teachers’ data. Our analysis showed that AI offers teachers several opportunities for improved planning (e.g., by defining students’ needs and familiarizing teachers with such needs), implementation (e.g., through immediate feedback and teacher intervention), and assessment (e.g., through automated essay scoring) of their teaching. We also found that teachers have various roles in the development of AI technology. These roles include acting as models for training AI algorithms and participating in AI development by checking the accuracy of AI automated assessment systems. Our findings further underlined several challenges in AI implementation in teaching practice, which provide guidelines for developing the field.