bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards an integrated phosphorus, carbon and nitrogen cycling model for topographically diverse grasslands
Authors: Bilotto Franco , Vibart Ronaldo , Mackay Alec , Costall Des , Harrison Matthew Tom 
Published: September 2022

AbstractContemporary science on how livestock influence nutrient cycling in grazing systems is limited, particularly in topographically complex (i.e., slopes and aspects) hill country landscapes. Prominent slope and aspect variation affects primary production, animal behaviour and nutrient return. Here, we embed recent scientific advancements in nutrient dynamics across complex landscapes to (1) set up a soil organic carbon (SOC) saturation function to an existing SOC and total soil phosphorus (TSP) model (Bilotto et al. J N Z Grassl 81:171–178, 2019. https://doi.org/10.33584/jnzg.2019.81.397), (2) include total soil nitrogen (TSN) dynamics, and (3) establish if the model (herein the Grass-NEXT model) can simulate the spatial and temporal changes of TSP, SOC and TSN in hill country. A long-term P fertiliser experiment with contrasting different P fertilisation levels and associated sheep stocking regimes (herein, ‘farmlets’) was used for model testing. The Grass-NEXT model predicted TSP and SOC stocks with strong accuracy and precision (model performance), and TSN with a moderate performance across farmlets [Concordance Correlation Coefficient (CCC), 0.75, 0.72 and 0.49, respectively]. Grass-NEXT model simulated TSP, SOC and TSN distribution with moderate/strong performance across slopes (CCC, 0.94, 0.80 and 0.70) and aspects (CCC, 0.83, 0.67 and 0.51). Consistent with observed data, modelled changes in TSP and TSN were greater on low slopes and eastern aspects, but no clear pattern was observed for SOC stocks. The Grass-NEXT model provides an intuitive research tool for exploring management options for increasing SOC and TSN, as well as an instrument for monitoring and reporting on nutrient dynamics in complex landscapes.
Extending the EQ-5D: the case for a complementary set of 4 psycho-social dimensions
Authors: Chen Gang , Olsen Jan Abel 
Published: September 2022

Abstract
Objectives
The EQ-5D is the most widely applied preference-based health-related quality of life measure. However, concerns have been raised that the existing dimensional structure lacks sufficient components of mental and social aspects of health. This study empirically explored the performance of a coherent set of four psycho-social bolt-ons: Vitality; Sleep; Personal relationships; and Social isolation.

Methods
Cross-sectional surveys were conducted with online panel members from five countries (Australia, Canada, Norway, UK, US) (total N = 4786). Four bolt-ons were described using terms aligned with EQ nomenclature. Latent structures among all nine dimensions are studied using an exploratory factor analysis (EFA). The Shorrocks-Shapely decomposition analyses are conducted to illustrate the relative importance of the nine dimensions in explaining two outcome measures for health (EQ-VAS, satisfaction with health) and two for subjective well-being (the hedonic approach of global life satisfaction and an eudemonic item on meaningfulness). Sub-group analyses are performed on older adults (65 +) and socially disadvantaged groups.

Results
Strength of correlations among four bolt-ons ranges from 0.34 to 0.49. As for their correlations with the EQ-5D dimensions, they are generally much less correlated with four physical health dimensions than with mental health dimensions (ranged from 0.21 to 0.50). The EFA identifies two latent factors. When explaining health, Vitality is the most important. When explaining subjective well-being, Social isolation is second most important, after Anxiety/depression.

Conclusion
We provide evidence that further complementing the current EQ-5D-5L health state classification system with a coherent set of four bolt-on dimensions that will fill its psycho-social gap.
Communication of Diagnostic Uncertainty in Primary Care and Its Impact on Patient Experience: an Integrative Systematic Review
Authors: Dahm Maria R. , Cattanach William , Williams Maureen , Basseal Jocelyne M. , Gleason Kelly , Crock Carmel 
Published: September 2022

AbstractBackgroundDiagnostic uncertainty is a pervasive issue in primary care where patients often present with non-specific symptoms early in the disease process. Knowledge about how clinicians communicate diagnostic uncertainty to patients is crucial to prevent associated diagnostic errors. Yet, in-depth research on the interpersonal communication of diagnostic uncertainty has been limited. We conducted an integrative systematic literature review (PROSPERO CRD42020197624, unfunded) to investigate how primary care doctors communicate diagnostic uncertainty in interactions with patients and how patients experience their care in the face of uncertainty.MethodsWe searched MEDLINE, PsycINFO, and Linguistics and Language Behaviour Abstracts (LLBA) from inception to December 2021 for MeSH and keywords related to ‘communication’, ’diagnosis’, ‘uncertainty’ and ‘primary care’ environments and stakeholders (patients and doctors), and conducted additional handsearching. We included empirical primary care studies published in English on spoken communication of diagnostic uncertainty by doctors to patients. We assessed risk of bias with the QATSDD quality assessment tool and conducted thematic and content analysis to synthesise the results.ResultsInclusion criteria were met for 19 out of 1281 studies. Doctors used two main communication strategies to manage diagnostic uncertainty: (1) patient-centred communication strategies (e.g. use of empathy), and (2) diagnostic reasoning strategies (e.g. excluding serious diagnoses). Linguistically, diagnostic uncertainty was either disclosed explicitly or implicitly through diverse lexical and syntactical constructions, or not communicated (omission). Patients’ experiences of care in response to the diverse communicative and linguistic strategies were mixed. Patient-centred approaches were generally regarded positively by patients.DiscussionDespite a small number of included studies, this is the first review to systematically catalogue the diverse communication and linguistic strategies to express diagnostic uncertainty in primary care. Health professionals should be aware of the diverse strategies used to express diagnostic uncertainty in practice and the value of combining patient-centred approaches with diagnostic reasoning strategies.
GIS and fuzzy logic integration in land suitability assessment for surface irrigation: the case of Guder watershed, Upper Blue Nile Basin, Ethiopia
Authors: Haile Mesfin Mamo , Abebe Asnake Kassahun 
Published: September 2022

AbstractBefore planning the use of existing land resources for irrigation, it is necessary to determine their availability. The primary goal of this research was to examine the Guder watershed's land resource potential for irrigation development and to create a geo-referenced map of these resources using a geographic information system coupled with fuzzy logic. Irrigation suitability criteria such as slope, land use, proximity to water body, rainfall deficit, soil texture class, soil depth, soil drainage classes, and proximity to road were considered when evaluating prospective irrigable properties. The criteria maps were divided into four suitability classes using a natural break interval range technique. According to the study's findings, 39.8% of the watershed area is Highly suitable, 34.5% is moderately acceptable, 24.5% is marginally suitable, and 1.2% is not suitable for the aforementioned reasons. According to the irrigation suitability study of these characteristics, 70.42% of the slope, 15.57% of the slope, 10.6% of the slope, and 3.95% of the slope are Highly, moderately, and marginally suitable for surface irrigation, respectively. In addition, 15% of the soil in the study Area is suitable for a surface irrigation system. In terms of land cover and use, 75% is highly favorable, whereas 0.3% is not suitable for irrigation development. GIS and remote sensing offer a straightforward and powerful framework for combining spatially complicated field variables for land suitability research. This study demonstrates the effectiveness of the fuzzy logic technique combined with GIS as an effective model for finding prospective irrigable land on a continental scale.
Die COVID-19-Pandemie im Schuljahr 2020/21: Wie haben sich die kognitiven Grundfähigkeiten von Schulkindern der Primarstufe entwickelt?
Authors: Rollett Wolfram , Leitgeb Thomas , Scharenberg Katja 
Published: September 2022

ZusammenfassungEine wichtige aktuelle Frage der empirischen Bildungsforschung ist, welchen Einfluss die zur Eindämmung der COVID-19-Pandemie getroffenen gesellschaftlichen Maßnahmen auf die kognitive Entwicklung von Schüler_innen hatten. Damit ist auch die Frage verbunden, ob bildungsbenachteiligte Gruppen von Schüler_innen in Abhängigkeit ihrer individuellen oder familiären Voraussetzungen besondere Nachteile in ihrer kognitiven Entwicklung erlitten haben. Um diesen Fragestellungen nachzugehen, wurden die Daten von 104 Schüler_innen der dritten Schulstufe dreier österreichischer Volksschulen (Primarstufe) hinsichtlich der Entwicklung ihrer kognitiven Grundfähigkeiten in den Bereichen Schlussfolgerndes Denken und Rechnerisches Denken (KFT 1–3; Heller und Geisler 1983) analysiert. Darüber hinaus wurden individuelle Merkmale der Schüler_innen sowie Merkmale ihres häuslichen Umfeldes erfasst. Die Testung der kognitiven Grundfähigkeiten erfolgte zu Beginn und Ende des Schuljahres 2020/21 und damit vor und nach den gesamtgesellschaftlichen und schulischen Maßnahmen zur Eindämmung der zweiten und dritten Corona-Welle in Österreich (u. a. Kontaktbeschränkungen, Schulschließungen, Fernunterricht und Quarantänemaßnahmen). Im Untersuchungszeitraum wäre nach metaanalytischen Befunden der Intelligenzforschung (Rindermann 2011) altersgemäß eine positive signifikante Entwicklung von Schüler_innen in den durchschnittlichen Testleistungen von etwa d = 0,40 zu erwarten gewesen. Empirisch zeigten sich jedoch keine signifikanten Veränderungen. Dies gilt auch für die Streuungen in den Testleistungen. Gleichzeitig entwickelten sich Kinder aus Elternhäusern mit höherem Bildungshintergrund und jene mit umfassenderer Ausstattung mit digitalen Endgeräten sowie mit Internetzugang signifikant besser. Die Befunde weisen damit darauf hin, dass sich die Kinder in unserer Stichprobe in dem durch pandemieeindämmende Maßnahmen geprägten Schuljahr im Durchschnitt nicht so positiv entwickelt haben, wie dies zu erwarten gewesen wäre. Dabei ist es auch zu Schereneffekten gekommen, die auf kognitive Einbußen bei benachteiligten Schülergruppen hinweisen.
Insights on mechanisms of aluminum phytotoxicity mitigation by canola straw biochars from different regions
Authors: Dong Ying , Yu Yuanchun , Wang Ruhai , Chang E. , Hong Zhineng , Hua Hui , Liu Hui , Jiang Jun , Xu Renkou 
Published: September 2022

AbstractTo better understand the amendment effects and mechanisms of aluminum (Al(III)) phytotoxicity mitigation by different regional crop straw biochars, wheat seedling root elongation trials were conducted. The contributions of liming effect, oxygen-containing surface functional group adsorption, and oxyanions precipitation to Al(III) phytotoxicity mitigation by Ca(OH)2, pristine and ash-free canola straw biochar were evaluated. The results indicated that biochars derived from canola straw collected from four different regions (Yingtan, Xuancheng, Nanjing, and Huaiyin) caused 22–70% wheat seedling root elongation, which might be linked to liming effect. Incorporation of the corresponding ash-free biochars caused 15–30% elongation, which could be attributed to the surface functional group adsorption. About 0–60% of changes could be explained by Al(III) precipitation with inorganic oxyanions. These findings provide new insights into the physicochemical properties, potential applications, efficiencies, and underlying mechanisms of crop straw biochar in alleviating Al(III) phytotoxicity, which is dependent on the cultivation soil, and indicate similar application of crop straw biochar for acidic soil amelioration, contaminated soil remediation, and arable soil improvement.
Graphical Abstract
Development and internal validation of predictive models to assess risk of post-acute care facility discharge in adults undergoing multi-level instrumented fusions for lumbar degenerative pathology and spinal deformity
Authors: Arora Ayush , Demb Joshua , Cummins Daniel D. , Deviren Vedat , Clark Aaron J. , Ames Christopher P. , Theologis Alekos A. 
Published: September 2022

Abstract
Purpose
To develop a model for factors predictive of Post-Acute Care Facility (PACF) discharge in adult patients undergoing elective multi-level (≥ 3 segments) lumbar/thoracolumbar spinal instrumented fusions.

Methods
The State Inpatient Databases acquired from the Healthcare Cost and Utilization Project from 2005 to 2013 were queried for adult patients who underwent elective multi-level thoracolumbar fusions for spinal deformity. Outcome variables were classified as discharge to home or PACF. Predictive variables included demographic, pre-operative, and operative factors. Univariate and multivariate logistic regression analyses informed development of a logistic regression-based predictive model using seven selected variables. Performance metrics included area under the curve (AUC), sensitivity, and specificity.

Results
Included for analysis were 8866 patients. The logistic model including significant variables from multivariate analysis yielded an AUC of 0.75. Stepwise logistic regression was used to simplify the model and assess number of variables needed to reach peak AUC, which included seven selected predictors (insurance, interspaces fused, gender, age, surgical region, CCI, and revision surgery) and had an AUC of 0.74. Model cut-off for predictive PACF discharge was 0.41, yielding a sensitivity of 75% and specificity of 59%.

Conclusions
The seven variables associated significantly with PACF discharge (age > 60, female gender, non-private insurance, primary operations, instrumented fusion involving 8+ interspaces, thoracolumbar region, and higher CCI scores) may aid in identification of adults at risk for discharge to a PACF following elective multi-level lumbar/thoracolumbar spinal fusions for spinal deformity. This may in turn inform discharge planning and expectation management.
Combined effect of fertilizer micro-dosing and intercropped millet/cowpea effect on agronomic and economic advantages in prone Sahel area, Niger
Authors: Abdoul-Karim Toudou Daouda , Sanoussi Atta , Soulé Moussa , Yacoubou Bakasso 
Published: September 2022

AbstractClimate change is affecting crop production in the West Africa Sahel. Farmers develop many adaptation strategies However, few of them have been tested to find their climate smartness, primarily their agronomic and economic benefits. Therefore, this study aimed to evaluate the field experiment in two successive years, 2020 and 2021, in rainy conditions, the combined effect of millet/cowpea intercropping and fertilizer microdosing on the yield and their economic advantages. Two genotypes of cowpea (ISV128 and Tiligré) and a variety of millet, Heini Kirey Précoce (HKP), were intercropped. At the treatment level, there is a net benefit of the crop association compared to the pure cultivation of each of the millet and cowpea species with total LERs, an average of 1.48 in 2020, and 1.43 in 2021 for microdose treatment and 1.55 in 2020 and 1.13 in 2021 for the control. However, there is no significant difference in cowpea genotype on LER and millet yields in the 2 years (P = 0.65 in 2020 and 0.29 in 2021). Yields of millet and cowpea were higher in the sole crop than in intercropping. The intercropping showed a significantly higher monetary advantage than the sole millet crop in both years. ISV128 is the most profitable because it is less competitive and less aggressive in intercropping with millet and offers a considerable monetary advantage. The findings are invaluable in implementing resilience strategies for smallholders who must be encouraged to adopt these cultural practices due to global warming.
Tuning photoluminescence behaviors in strained monolayer belt-like MoS2 crystals confined on TiO2(001) surface
Authors: Wang Yuanye , Zhou Jun , Liu Yalin , Zhang Weifeng , Zhao Zihan , Li Xiaotian , Chen Qiaoni , Liu Nan , Shen Xi , Yu Richeng , Nie Jiacai , Dou Ruifen 
Published: September 2022

AbstractWe report on a monolayer (ML) MoS2 belt-like single crystal directly fabricated on the Rutile-TiO2(001) surface via chemical vapor deposition (CVD). We find that the photoluminescence (PL) behaviors in the ML MoS2 single crystal strongly depend on their shapes and the interface of MoS2/TiO2. Compared with the as-grown triangular ML MoS2, the PL peak position is in a blue shift and the PL intensity is increased for the as-grown ML MoS2 belt. Moreover, the PL peak position is in the blue shift by about 38 meV and the intensity is enhanced by nearly 15 times for the as-grown ML MoS2 belt crystal on TiO2 than those samples transferred onto SiO2/Si substrate. This special PL behavior can be attributed to the in-plane compressive strain that is introduced during the CVD growth of ML MoS2 belts confined by the substrate. The energy band of the strained ML MoS2 belt is changed with an up-shift in the conduction band minimum (VBM) and a down-shift in the valence band maximum (CBM), and the band gap is thus enlarged. This results in the energy band structural realignment in the interface of MoS2/TiO2, thereby weakening the charge transferring from the TiO2 substrate to MoS2 and suppressing the concentration of charged excitons to finally enhance the PL intensity of the ML MoS2 belt. The substrate-confined ML MoS2 belts provide a new route for tailoring light-matter interactions to upgrade their weak quantum yields and low light absorption, which can be utilized in optoelectronic and nanophotonic devices.
A Bayesian Deep Learning Approach to Near‐Term Climate Prediction
Authors: Luo Xihaier , Nadiga Balasubramanya T. , Park Ji Hwan , Ren Yihui , Xu Wei , Yoo Shinjae 
Published: September 2022

AbstractSince model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state‐of‐the‐art decadal climate prediction efforts, we pursue a complementary machine‐learning‐based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre‐industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.
Effects of single- and multiple-dose oxytocin treatment on amygdala low-frequency BOLD fluctuations and BOLD spectral dynamics in autism
Authors: Alaerts Kaat , Bernaerts Sylvie , Wenderoth Nicole 
Published: September 2022

AbstractPrior neuroimaging clinical trials investigating the neural effects of intranasal administration of the neuropeptide oxytocin demonstrated a key role of the amygdala in oxytocin’s neuromodulatory effects. These studies mostly demonstrated the acute effects of single-dose administrations, examining task-dependent effects of oxytocin on brain activity elicited during explicit experimental tasks or stimuli presentations. The increased consideration of oxytocin as a potential ameliorating treatment in autism spectrum disorder (ASD) requires a better understanding of how multiple-dose oxytocin administration affects intrinsic, task-free, amygdala function. In this double-blind, randomized, placebo-controlled trial with between-subject design, 38 adult men with ASD underwent resting-state fMRI scanning before and after oxytocin or placebo treatment. Effects were assessed either after a single-dose administration, consisting of 24 international units, or after multiple-dose treatment, consisting of 4 weeks of once-daily nasal spray administrations. Compared to placebo, oxytocin induced a decrease in intrinsic resting-state BOLD signal amplitudes of the bilateral amygdala (fractional amplitudes of low-frequency fluctuations) and modulated cross-frequency interactions between adjacent BOLD frequency components. The right amygdala showed a pattern of reduced cross-frequency harmonicity, while the left amygdala showed a relative increase in harmonic cross-frequency interactions after oxytocin treatment. Notably, the direction and magnitude of BOLD spectral changes induced after a single-dose were qualitatively similar to treatment effects induced after multiple-dose treatment. Furthermore, the identified spectral changes in amygdalar BOLD amplitude and cross-frequency harmonicity were associated with improved feelings of tension, reflecting oxytocin’s anxiolytic, stress-reducing neuromodulatory role. The observed effects of oxytocin on amygdalar BOLD spectral characteristics and associated behaviors contribute to a deeper mechanistic understanding of the intrinsic, task-free neuromodulatory dynamics that underlie single- and multiple-dose oxytocin treatment in ASD. European Clinical Trial Registry (Eudract 2014-000586-45).
An EGFR/HER2-targeted conjugate sensitizes gemcitabine-sensitive and resistant pancreatic cancer through different SMAD4-mediated mechanisms
Authors: Yao Hongjuan , Song Wenping , Cao Rui , Ye Cheng , Zhang Li , Chen Hebing , Wang Junting , Shi Yuchen , Li Rui , Li Yi , Liu Xiujun , Zhou Xiaofei , Shao Rongguang , Li Liang 
Published: September 2022

AbstractChemoresistance limits its clinical implementation for pancreatic ductal adenocarcinoma (PDAC). We previously generated an EGFR/HER2 targeted conjugate, dual-targeting ligand-based lidamycin (DTLL), which shows a highly potent antitumor effect. To overcome chemoresistance in PDAC, we aim to study DTLL efficacy when combined with gemcitabine and explore its mechanisms of action. DTLL in combination with gemcitabine show a superior inhibitory effect on the growth of gemcitabine-resistant/sensitive tumors. DTLL sensitizes gemcitabine efficacy via distinct action mechanisms mediated by mothers against decapentaplegic homolog 4 (SMAD4). It not only prevents neoplastic proliferation via ATK/mTOR blockade and NF-κB impaired function in SMAD4-sufficient PDACs, but also restores SMAD4 bioactivity to trigger downstream NF-κB-regulated signaling in SMAD4-deficient tumors and to overcome chemoresistance. DTLL seems to act as a SMAD4 module that normalizes its function in PDAC, having a synergistic effect in combination with gemcitabine. Our findings provide insight into a rational SMAD4-directed precision therapy in PDAC.