bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mice deficient in synaptic protease neurotrypsin show impaired spaced long-term potentiation and blunted learning-induced modulation of dendritic spines
Authors: Ferrer-Ferrer Maura , Jia Shaobo , Kaushik Rahul , Schneeberg Jenny , Figiel Izabela , Aleshin Stepan , Mironov Andrey , Safari Motahareh , Frischknecht Renato , Wlodarczyk Jakub , Senkov Oleg , Dityatev Alexander 
Published: March 2023

AbstractNeurotrypsin (NT) is a neuronal trypsin-like serine protease whose mutations cause severe mental retardation in humans. NT is activated in vitro by Hebbian-like conjunction of pre- and postsynaptic activities, which promotes the formation of dendritic filopodia via proteolytic cleavage of the proteoglycan agrin. Here, we investigated the functional importance of this mechanism for synaptic plasticity, learning, and extinction of memory. We report that juvenile neurotrypsin-deficient (NT−/−) mice exhibit impaired long-term potentiation induced by a spaced stimulation protocol designed to probe the generation of new filopodia and their conversion into functional synapses. Behaviorally, juvenile NT−/− mice show impaired contextual fear memory and have a sociability deficit. The latter persists in aged NT−/− mice, which, unlike juvenile mice, show normal recall but impaired extinction of contextual fear memories. Structurally, juvenile mutants exhibit reduced spine density in the CA1 region, fewer thin spines, and no modulation in the density of dendritic spines following fear conditioning and extinction in contrast to wild-type littermates. The head width of thin spines is reduced in both juvenile and aged NT−/− mice. In vivo delivery of adeno-associated virus expressing an NT-generated fragment of agrin, agrin-22, but not a shorter agrin-15, elevates the spine density in NT−/− mice. Moreover, agrin-22 co-aggregates with pre- and postsynaptic markers and increases the density and size of presynaptic boutons and presynaptic puncta, corroborating the view that agrin-22 supports the synaptic growth.
A comparison of methods for training population optimization in genomic selection
Authors: Fernández-González Javier , Akdemir Deniz , Isidro y Sánchez Julio 
Published: March 2023

AbstractKey messageMaximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A training set size of 50–55% (targeted) or 65–85% (untargeted) is needed to obtain 95% of the accuracy. AbstractWith the advent of genomic selection (GS) as a widespread breeding tool, mechanisms to efficiently design an optimal training set for GS models became more relevant, since they allow maximizing the accuracy while minimizing the phenotyping costs. The literature described many training set optimization methods, but there is a lack of a comprehensive comparison among them. This work aimed to provide an extensive benchmark among optimization methods and optimal training set size by testing a wide range of them in seven datasets, six different species, different genetic architectures, population structure, heritabilities, and with several GS models to provide some guidelines about their application in breeding programs. Our results showed that targeted optimization (uses information from the test set) performed better than untargeted (does not use test set data), especially when heritability was low. The mean coefficient of determination was the best targeted method, although it was computationally intensive. Minimizing the average relationship within the training set was the best strategy for untargeted optimization. Regarding the optimal training set size, maximum accuracy was obtained when the training set was the entire candidate set. Nevertheless, a 50–55% of the candidate set was enough to reach 95–100% of the maximum accuracy in the targeted scenario, while we needed a 65–85% for untargeted optimization. Our results also suggested that a diverse training set makes GS robust against population structure, while including clustering information was less effective. The choice of the GS model did not have a significant influence on the prediction accuracies.
Clinical Practices Following Train‐The‐Trainer Trauma Course Completion in Uganda: A Parallel‐Convergent Mixed‐Methods Study
Authors: Tang Zeyu , Kayondo Derick , Ullrich Sarah J. , Namugga Martha , Muwanguzi Peter , Klazura Gregory , Ozgediz Doruk , Armstrong‐Hough Mari 
Published: March 2023

AbstractBackgroundDespite the growth of trauma training courses worldwide, evidence for their impact on clinical practice in low‐ and middle‐income countries (LMICs) is sparse. We investigated trauma practices by trained providers in Uganda using clinical observation, surveys, and interviews.MethodsUgandan providers participated in the Kampala Advanced Trauma Course (KATC) from 2018 to 2019. Between July and September of 2019, we directly evaluated guideline‐concordant behaviors in KATC‐exposed facilities using a structured real‐time observation tool. We conducted 27 semi‐structured interviews with course‐trained providers to elucidate experiences of trauma care and factors that impact adoption of guideline‐concordant behaviors. We assessed perceptions of trauma resource availability through a validated survey.ResultsOf 23 resuscitations, 83% were managed without course‐trained providers. Frontline providers inconsistently performed universally applicable assessments: pulse checks (61%), pulse oximetry (39%), lung auscultation (52%), blood pressure (65%), pupil examination (52%). We did not observe skill transference between trained and untrained providers. In interviews, respondents found KATC personally transformative but not sufficient for facility‐wide improvement due to issues with retention, lack of trained peers, and resource shortages. Resource perception surveys similarly demonstrated profound resource shortages and variation across facilities.ConclusionsTrained providers view short‐term trauma training interventions positively, but these courses may lack long‐term impact due to barriers to adopting best practices. Trauma courses should include more frontline providers, target skill transference and retention, and increase the proportion of trained providers at each facility to promote communities of practice. Essential supplies and infrastructure in facilities must be consistent for providers to practice what they have learned.
Towards safe and effective femtosecond laser cleaning for the preservation of historic monuments
Authors: Brand Julia , Wain Alison , Rode Andrei V. , Madden Steve , Rapp Ludovic 
Published: March 2023

AbstractWe explore femtosecond laser cleaning of materials used in the construction of historic monuments, such as stone and steel covered in typical contaminants caused by harsh environments that may be found in urban areas. We address the cleaning of these materials from a conservation perspective, taking as examples the preservation and cleaning of iconic structures such as the steel and the granite of the Sydney Harbour Bridge, Hawkesbury sandstone, a popular building material of a variety of monuments in Sydney (Australia), Makrana marble taken from the Soami Bagh Samadh temple of Agra in India, and also graffiti removal. We demonstrate that femtosecond laser pulses can clean a range of different contaminants such as biofilm, environmental soiling, rust, and spray paints, while preserving the integrity of the underlying substrates. Femtosecond laser cleaning is a fast and effective method and a safer alternative to lasers with longer pulse durations for the preservation of historic monuments.
Parameters not empirically identifiable or distinguishable, including correlation between Gaussian observations
Authors: Hennig Christian 
Published: March 2023

AbstractIt is shown that some theoretically identifiable parameters cannot be empirically identified, meaning that no consistent estimator of them can exist. An important example is a constant correlation between Gaussian observations (in presence of such correlation not even the mean can be empirically identified). Empirical identifiability and three versions of empirical distinguishability are defined. Two different constant correlations between Gaussian observations cannot even be empirically distinguished. A further example are cluster membership parameters in k-means clustering. Several existing results in the literature are connected to the new framework. General conditions are discussed under which independence can be distinguished from dependence.
Sobolev-Type Embeddings for Neural Network Approximation Spaces
Authors: Grohs Philipp , Voigtlaender Felix 
Published: March 2023

AbstractWe consider neural network approximation spaces that classify functions according to the rate at which they can be approximated (with error measured in $$L^p$$

L
p

) by ReLU neural networks with an increasing number of coefficients, subject to bounds on the magnitude of the coefficients and the number of hidden layers. We prove embedding theorems between these spaces for different values of p. Furthermore, we derive sharp embeddings of these approximation spaces into Hölder spaces. We find that, analogous to the case of classical function spaces (such as Sobolev spaces, or Besov spaces) it is possible to trade “smoothness” (i.e., approximation rate) for increased integrability. Combined with our earlier results in Grohs and Voigtlaender (Proof of the theory-to-practice gap in deep learning via sampling complexity bounds for neural network approximation spaces, 2021. arXiv preprint arXiv:2104.02746), our embedding theorems imply a somewhat surprising fact related to “learning” functions from a given neural network space based on point samples: if accuracy is measured with respect to the uniform norm, then an optimal “learning” algorithm for reconstructing functions that are well approximable by ReLU neural networks is simply given by piecewise constant interpolation on a tensor product grid.
Extraordinary diversity among allopatric species in the genus Goniurosaurus (Squamata: Eublepharidae): understanding niche evolution and the need of conservation measures
Authors: Ngo Hai Ngoc , Rödder Dennis , Grismer Lee , Nguyen Truong Quang , Le Minh Duc , Qi Shuo , Ziegler Thomas 
Published: March 2023

AbstractGiven the high degrees of adaptation to specific microhabitats and restricted-range endemism, Goniurosaurus (Tiger geckos) serves as a unique model to study the complex evolution in lizards. Using phylogenetic analyses, we estimated the first divergence date of Goniurosaurus to the Eocene (~ 45.3 mya). The diversification within four monophyletic species groups began in the mid-Miocene between ~ 13.4 and 7.7 mya and continued to at least the early Pleistocene (~ 2 mya). Their ancestor was predicted to originate somewhere in contiguous continental Eastern Asia, whereas the current regions in which each monophyletic Goniurosaurus species group radiated are respectively their own ancestral regions. Together with factors of altitudinal gradient and climate conditions, we reconstructed relevant niche models of Goniurosaurus including ancestral reconstructions. Consequently, low elevations were predicted to be the most probable ancestral state for Goniurosaurus and all its groups as well. Both climatic niche conservatism and divergence have shaped the extraordinary species richness of allopatric Chinese and Vietnamese tiger geckos. In terms of endangerment, Goniurosaurus has been considered one of the most susceptible lizard groups under severe human impacts, especially climate change. The assessments of their niche evolution can provide a science-based pre-signal of vulnerability, thereby improving the efficacy of conservation measures to safeguard species of Goniurosaurus in the future. Accordingly, almost all closely related species of Goniurosaurus in China and Vietnam were identified with a high rate of niche conservatism, which should be included in conservation priorities under potential impacts of climate change.
Investigating the Validity of the Australian Early Development Census
Authors: Howells Sarah , Nguyen Ha Trong , Brinkman Sally , Mitrou Francis 
Published: March 2023

AbstractThis article continues evaluation of the construct validity of the Australian Early Development Census (AEDC) through comparison with linked data from a sample of 2216 4–5 year old children collected as part of the Longitudinal Study of Australian Children (LSAC). This builds on the construct validity assessment of Brinkman et al. (Early Educ Dev 18(3):427–451, 2007) based on a smaller sample of linked Australian Early Development Instrument (AvEDI) and LSAC children, in which moderate to large correlations were apparent between teacher-rated AvEDI domains and subconstructs and LSAC measures, with lower levels apparent for parent reported LSAC measures. In the current study, the data showed moderate to low correlations between the domains and subdomains from the AEDC and teacher reported LSAC data. Differences in testing times, data sources (e.g. teachers versus carers) and levels of exposure to formal schooling at the time of testing are all discussed to account for the observed outcomes.
How narratives about the secondary-tertiary transition shape undergraduate tutors’ sense-making of their teaching
Authors: Kontorovich Igor’ , Ovadiya Tikva 
Published: March 2023

AbstractDrawing on the commognitive framework, we construe the secondary-tertiary transition (STT) as a distinctive element in the pedagogical discourses of various communities. Our interest rests with university tutors in light of the emergent recognition of their impact on undergraduates’ mathematics learning in many tertiary contexts worldwide. We aim to understand the roles of STT communication in tutors’ reflections on incidents that took place in their tutorials. Our participants were undergraduate students in the advanced stages of their mathematics degrees in a large New Zealand university and who were enrolled in a mathematics education course. Throughout the semester, the participants led tutorial sessions for first-year students and wrote reflections on classroom incidents that drew their attention. Our data corpus consisted of 58 reflections from 38 tutors collected over four semesters. The analysis revealed that STT communication featured in tutors’ descriptions of classroom incidents, assisted them in making sense of unexpected events, positioned their instructional actions as replications of what was familiar to them from their own STT experience, and contributed toward generating new pedagogical narratives. We situate these findings in the literature concerning undergraduate tutoring and teachers’ perspectives on STT.
Innovation facilitators and sustainable development: a country comparative approach
Authors: Chaparro-Banegas Nuria , Ibañez Escribano Ana Maria , Mas-Tur Alicia , Roig-Tierno Norat 
Published: March 2023

AbstractNational and international organizations have introduced policies aimed at sustainable development. These policies are designed to encourage sustainable forms of business to meet the Sustainable Development Goals (SDGs) of the 2030 Agenda. Regional inequalities in sustainable development may be exacerbated by disparate levels of innovation. This paper analyzes the variations between clusters of countries according to the degree to which they have achieved the SDGs and their levels of innovation facilitators. Two types of analyses were employed. First, cluster analysis was used to examine changes in groups of regions with similar innovation characteristics between 2015 and 2020. Data for 122 countries were gathered from the World Bank, the SDG Index, and the Global Innovation Index. Second, multiple linear regression analysis was used to assess the power of the variables in the model to explain the level of sustainable development. The results reveal four clusters (low, medium, high, and very high innovative facilitators and sustainable development), as well as movements between those clusters from 2015 to 2020. The multiple linear regression analysis shows that the variables have explanatory power with respect to the dependent variable of sustainable development. This analysis also reveals different degrees of importance of the variables for each cluster. The findings highlight the need to consider the limitations of economic growth in terms of innovation facilitators to promote sustainable development. If policymakers recognize the limitations of economic growth and the physical ecosystem, degradation of the environment can be avoided, even when there is innovation. Global and individual social welfare can thus be ensured. This study offers valuable insights into how to achieve sustainable development through innovation facilitators by providing in-depth knowledge of the individual characteristics of innovation systems and considering the limitations of economic growth.
Hydrodynamic modelling and shape optimisation of second-generation coastal reservoirs in consideration of algal bloom occurrence
Authors: Wong Hui Ling , Teo Fang Yenn 
Published: March 2023

AbstractAlgal bloom has been a persistent problem for both fresh and marine water, with no exception for a coastal reservoir (CR). Among the algal bloom mitigations for a CR, shape optimisation to reduce algal bloom occurrence has been frequently mentioned. However, there was no literature found on the actual shape optimisation study or process for CR. Thus, this research was done to bridge this gap, particularly for the second-generation CR. Hydrodynamic model of MIKE 21 has been used, with secondary data obtained from published papers and Google Earth. The secondary data of critical velocity corresponding to algal growth were only available for cyanobacteria, chlorella, filamentous algae and phytoplankton. Hence, only these algae species were considered in the algal mapping. All models were simulated for eight idealised cases of second-generation CR at the Yangtze Estuary. These different geometric shapes were analysed and compared, considering several factors including the average velocity in the reservoir, presence of stagnant water, percentage of occurrence for each algae species and so on. From the results, the reservoir model with the shape of “shorter piano key” ranked the highest among all the shapes in terms of proneness to algal bloom, based on the flow velocity within the reservoir. From the findings, further shape optimisation was done on second-generation CRs. From shape optimisation process, the optimised shape of the “little dinosaur” and “little pencil” showed excellent reduction in algal blooming. However, “little dinosaur” was preferred as its location for algal bloom is small and controllable due to the presence of “piano key” structure. Lastly, all the findings were applied to an existing CR at Qingcaosha to see if shape optimisation based on the analysis can reduce areas prone to algal blooming. The optimised model of Qingcaosha showed great reduction on area prone to algal blooming compared to its original shape but the addition of “piano key” structure did not have significant impact on the reduction of algal bloom occurrence since the shape of Qingcaosha is highly dependent on its natural topography. From the study, it was concluded that shape optimisation for topographic-dependent CR should be done on case-by-case basis, following the flow direction in the reservoir. As for second-generation CR without topographical constraints, the shape optimisation can be done by placing inlet perpendicular to the flow direction, minimising corners, implementing piano-key-like structure, optimising shape based on flow direction and refer “little dinosaur” or “little pencil” for the overall shape optimisation design.
Phenotypic diversity of Medicago crop wild relatives growing in Lebanon
Authors: Karam Nisrine , Choueiry Zeina , Al-Beyrouthy Jostelle , Shehadeh Ali , Chalak Lamis , Yazbek Mariana 
Published: March 2023

AbstractMedicago L. (Fabaceae; Papillionoidae) has high nutritive value, palatability, and ability to improve the soil fertility which puts it as one of the world’s most important forages. Medicago genetic resources are suffering from anthropogenic destructions, overgrazing, climate change and drought. Using the results of a previous gap analysis, which prioritized the species and sites for in situ and ex situ conservation, this study aims to undertake ex situ conservation activities for high priority annual Lebanese species. Accessions of the target species were collected, multiplied, characterized and conserved at Genebank of The International Center for Agricultural Research in the Dry Areas (ICARDA). Based on characterization data, morphological diversity assessment is carried out to analyse the phenotypic variability pattern in relation with the environmental conditions of the collection sites. The analysis of 26 characters applied on 19 collected species has shown a significant variability for 13 characters. The species Medicago polymorpha L. from Chwaifat, M. polymorpha from Shebenieh, M. truncatula Gaertn and M. orbicularis (L.) Bartal from Jeita, and M. constricta Durieu from Bwerij had characters that could be related to drought tolerance as they have displayed a high early vigour and an early flowering. In depth analysis of the characters early vigour, days to flowering and days to pod formation within the species in relation to drought tolerance further informed our proposed management plan. On this basis, the accessions showing a high adaptability to harsh conditions will be subject to in situ conservation.
Impact of in vitro phytohormone treatments on the metabolome of the leafy liverwort Radula complanata (L.) Dumort
Authors: Blatt-Janmaat Kaitlyn , Neumann Steffen , Schmidt Florian , Ziegler Jörg , Qu Yang , Peters Kristian 
Published: March 2023

Abstract
Introduction
Liverworts are a group of non-vascular plants that possess unique metabolism not found in other plants. Many liverwort metabolites have interesting structural and biochemical characteristics, however the fluctuations of these metabolites in response to stressors is largely unknown.

Objectives
To investigate the metabolic stress-response of the leafy liverwort Radula complanata.

Methods
Five phytohormones were applied exogenously to in vitro cultured R. complanata and an untargeted metabolomic analysis was conducted. Compound classification and identification was performed with CANOPUS and SIRIUS while statistical analyses including PCA, ANOVA, and variable selection using BORUTA were conducted to identify metabolic shifts.

Results
It was found that R. complanata was predominantly composed of carboxylic acids and derivatives, followed by benzene and substituted derivatives, fatty acyls, organooxygen compounds, prenol lipids, and flavonoids. The PCA revealed that samples grouped based on the type of hormone applied, and the variable selection using BORUTA (Random Forest) revealed 71 identified and/or classified features that fluctuated with phytohormone application. The stress-response treatments largely reduced the production of the selected primary metabolites while the growth treatments resulted in increased production of these compounds. 4-(3-Methyl-2-butenyl)-5-phenethylbenzene-1,3-diol was identified as a biomarker for the growth treatments while GDP-hexose was identified as a biomarker for the stress-response treatments.

Conclusion
Exogenous phytohormone application caused clear metabolic shifts in Radula complanata that deviate from the responses of vascular plants. Further identification of the selected metabolite features can reveal metabolic biomarkers unique to liverworts and provide more insight into liverwort stress responses.