bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intensified Northern Hemisphere Glaciation Facilitates Continuous Accumulation of Late Pliocene Loess on the Western Margin of the Pamir
Authors: Zan Jinbo , Ning Wenxiao , Heller Friedrich , Fang Xiaomin , Zhang Weilin , Kang Jian 
Published: August 2022

AbstractThick eolian loess sequences in arid Central Asia (CA) contain a wealth of information on the intensity variations of midlatitude westerlies and the aridification history of the nearby deserts. In this study, detailed lithologic and magnetostratigraphic investigations suggest that loess deposits on the western margin of the Pamir Plateau began to accumulate at around 2.7 Ma, representing the most complete and oldest loess‐paleosol sequence in western CA. The widely distributed continuous loess deposition in the region suggests a rapid desiccation of CA during the late Pliocene. A synthesis of the initial timing and spatial distribution of late Cenozoic eolian deposits on the Eurasian continent further demonstrates that the dramatic increase in global ice volume exerted a dominant role in the expansion of eolian loess deposits in CA, China, and Europe, and middle Pleistocene expansion is a crucial precondition for the establishment of modern distribution patterns of the Eurasian loess belt.
Impact of Mountains in Southern China on the Eocene Climates of East Asia
Authors: Zhang Zijian , Zhang Zhongshi , He Zhilin , Tan Ning , Guo Zhengtang , Zhu Jiang , Steinig Sebastian , Donnadieu Yannick , Ladant Jean‐Baptiste , Chan Wing‐Le , Abe‐Ouchi Ayako , Niezgodzki Igor , Knorr Gregor , Hutchinson David K. , de Boer Agatha M. 
Published: August 2022

AbstractInconsistencies in the Eocene climates of East Asia have been revealed in both geological studies and simulations. Several earlier reconstructions showed an arid zonal band in mid‐latitude China, but others showed a humid climate in the same region. Moreover, previous Eocene modeling studies have demonstrated that climate models can simulate both scenarios in China. Therefore, it is essential to investigate the cause of this model spread. We conducted a series of experiments using Norwegian Earth System Model 1‐F and examined the impact of mountains in Southern China on the simulated Eocene climate. These mountains, including the Gangdese and Southeast Mountains, are located along the main path of water vapor transport to East Asia. Our results reveal that the Southeast Mountains play the dominant role in controlling the simulated precipitation in Eastern China during the Eocene. When the heights of the Southeast Mountains exceed ∼2,000 m, an arid zonal band appears in mid‐latitude China, whereas humid climates appear in Eastern China when the elevation of the Southeast Mountains is relatively low.
The Shear‐Relative Variation of Inflow Angle and Its Relationship to Tropical Cyclone Intensification
Authors: Ming Jie , Liu Ruixue , Zhang Jun A. , Rogers Robert F. 
Published: August 2022

AbstractCharacterizing inflow structure is important to better represent tropical cyclone impacts in numerical models. While much research has considered the impact of storm translation on the distribution of inflow angle, comparatively less research has examined its distribution relative to the environmental wind shear. This study analyzes data from 3,655 dropsondes in 44 storms to investigate the radial and shear‐relative distribution of surface inflow angle. Emphasis is placed on its relationship with intensity change. The results show that the radial variation in the inflow angle is small and not significantly dependent on the shear magnitude or intensity change rate. In contrast, the azimuthal distribution of the inflow angle shows a significant asymmetry, with the amplitude of the asymmetry increasing with shear magnitude. The maximum inflow angle is located in the downshear side. The degree of asymmetry is larger in the outer core than in the eyewall. Intensifying storms have a smaller degree of asymmetry than steady‐state storms under moderate shear.
The Art of Landslides: How Stochastic Mass Wasting Shapes Topography and Influences Landscape Dynamics
Authors: Campforts Benjamin , Shobe Charles M. , Overeem Irina , Tucker Gregory E. 
Published: August 2022

AbstractBedrock landslides shape topography and mobilize large volumes of sediment. Yet, interactions between landslide‐produced sediment and fluvial systems that together govern large‐scale landscape evolution are not well understood. To explain morphological patterns observed in steep, landslide‐prone terrain, we explicitly model stochastic landsliding and associated sediment dynamics. The model accounts for several common landscape features such as slope frequency distributions, which include values in excess of regional stability limits, quasi‐planar hillslopes decorated with straight, closely spaced channel‐like features, and accumulation of sediment in valley networks rather than on hillslopes. Stochastic landsliding strongly affects the magnitude and timing of sediment supply to the fluvial system. We show that intermittent sediment supply is ultimately reflected in topography. At dynamic equilibrium, landslide‐derived sediment pulses generate persistent landscape dynamism through the formation and breaching of landslide dams and epigenetic gorges as landslides force shifts in channel positions. Our work highlights the importance of interactions between landslides and sediment dynamics that ultimately control landscape‐scale response to environmental change.
An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n‐Moment Bulk Microphysics Scheme
Authors: Bieli Melanie , Dunbar Oliver R. A. , de Jong Emily K. , Jaruga Anna , Schneider Tapio , Bischoff Tobias 
Published: August 2022

AbstractThe small‐scale microphysical processes governing the formation of precipitation particles cannot be resolved explicitly by cloud resolving and climate models. Instead, they are represented by microphysics schemes that are based on a combination of theoretical knowledge, statistical assumptions, and fitting to data (“tuning”). Historically, tuning was done in an ad hoc fashion, leading to parameter choices that are not explainable or repeatable. Recent work has treated it as an inverse problem that can be solved by Bayesian inference. The posterior distribution of the parameters given the data—the solution of Bayesian inference—is found through computationally expensive sampling methods, which require over evaluations of the forward model; this is prohibitive for many models. We present a proof of concept of Bayesian learning applied to a new bulk microphysics scheme named “Cloudy,” using the recently developed Calibrate‐Emulate‐Sample (CES) algorithm. Cloudy models collision‐coalescence and collisional breakup of cloud droplets with an adjustable number of prognostic moments and with easily modifiable assumptions for the cloud droplet mass distribution and the collision kernel. The CES algorithm uses machine learning tools to accelerate Bayesian inference by reducing the number of forward evaluations needed to . It also exhibits a smoothing effect when forward evaluations are polluted by noise. In a suite of perfect‐model experiments, we show that CES enables computationally efficient Bayesian inference of parameters in Cloudy from noisy observations of moments of the droplet mass distribution. In an additional imperfect‐model experiment, a collision kernel parameter is successfully learned from output generated by a Lagrangian particle‐based microphysics model.
Can intracellular Staphylococcus aureus in osteomyelitis be treated using current antibiotics? A systematic review and narrative synthesis
Authors: Zelmer Anja R. , Nelson Renjy , Richter Katharina , Atkins Gerald J. 
Published: August 2022

AbstractApproximately 40% of treatments of chronic and recurrent osteomyelitis fail in part due to bacterial persistence.Staphylococcus aureus, the predominant pathogen in human osteomyelitis, is known to persist by phenotypic adaptation as small-colony variants (SCVs) and by formation of intracellular reservoirs, including those in major bone cell types, reducing susceptibility to antibiotics. Intracellular infections withS. aureusare difficult to treat; however, there are no evidence-based clinical guidelines addressing these infections in osteomyelitis. We conducted a systematic review of the literature to determine the demonstrated efficacy of all antibiotics against intracellularS. aureusrelevant to osteomyelitis, including protein biosynthesis inhibitors (lincosamides, streptogramins, macrolides, oxazolidines, tetracyclines, fusidic acid, and aminoglycosides), enzyme inhibitors (fluoroquinolones and ansamycines), and cell wall inhibitors (beta-lactam inhibitors, glycopeptides, fosfomycin, and lipopeptides). The PubMed and Embase databases were screened for articles related to intracellularS. aureusinfections that compared the effectiveness of multiple antibiotics or a single antibiotic together with another treatment, which resulted in 34 full-text articles fitting the inclusion criteria. The combined findings of these studies were largely inconclusive, most likely due to the plethora of methodologies utilized. Therefore, the reported findings in the context of the models employed and possible solutions for improved understanding are explored here. While rifampicin, oritavancin, linezolid, moxifloxacin and oxacillin were identified as the most effective potential intracellular treatments, the scientific evidence for these is still relatively weak. We advocate for more standardized research on determining the intracellular effectiveness of antibiotics inS. aureusosteomyelitis to improve treatments and patient outcomes.
Dental education in primary care: 14 years of Peninsula Dental School
Authors: Tredwin Christopher , Hanks Sally , Witton Rob , McColl Ewen , Coelho Cathy 
Published: August 2022

AbstractPeninsula Dental School, established in 2006, was the UK's first new dental school in 40 years. It had the freedom to develop a completely new dental education curriculum planned on pedagogic thinking, designed to equip the dental care professionals of the twenty-first century. This was based on three distinct pillars: professionalism (developing a student's trust in their own autonomy); dental skills of the highest order (not just technical skills but also communication skills); and social engagement. As such, a truly innovative approach to dental education was created that has strong roots in evidence.This paper describes the University of Plymouth Peninsula Dental School's achievements against these initial objectives under the following areas: training in primary care; a novel spiralling integrated curriculum and assessments; facilities reaching out to deliver patient care; bringing meaningful patient contact to students from the earliest months of their course; embedding community engagement within the curriculum; development of Peninsula Dental Social Enterprise; and team working, training a variety of dental care profession students side by side.The University of Plymouth Peninsula Dental School, working with all its partners, has successfully pioneered and delivered significant changes in the field of education and continues to strive to further develop these and more for the future.
Corneal irregularity and visual function using anterior segment optical coherence tomography in TGFBI corneal dystrophy
Authors: Abe Yuito , Omoto Takashi , Kitamoto Kohdai , Toyono Tetsuya , Yoshida Junko , Asaoka Ryo , Yamagami Satoru , Miyai Takashi , Usui Tomohiko 
Published: August 2022

AbstractThe purpose of this study was to evaluate corneal irregular astigmatism of patients with granular and lattice corneal dystrophy (GCD and LCD). 70 GCD, 35 LCD, and 81 control eyes were included. Anterior and posterior corneal topographic data obtained from anterior segment optical coherence tomography were expanded into four components via Fourier harmonic analysis. These components were compared with healthy eyes and the association between each component and best-corrected visual acuity (BCVA) was investigated. Anterior and posterior components increased in both GCD and LCD eyes. Anterior and posterior components of GCD2, anterior of LCD type 1 (LCD1), posterior of LCD type IIIA (LCD 3A), and type IV (LCD4) significantly increased. BCVA was significantly associated with anterior and posterior components in LCD eyes but not in GCD. The anterior components of LCD1, anterior and posterior of LCD3A, and posterior of LCD4
, were positively correlated with BCVA. As conclusions, in GCD eyes, anterior and posterior components differed from those of the control but BCVA was not significantly associated with them. In LCD eyes, the anterior and posterior components increased, and BCVA was significantly associated with the anterior and posterior components.
The association between dose of hemodialysis and patients mortality in a prospective cohort study
Authors: Liu Shu-Xin , Wang Zhi-Hong , Zhang Shuang , Xiao Jia , You Lian-Lian , Zhang Yu , Dong Cui , Wang Xue-Na , Wang Zhen-Zhen , Wang Sheng-Nan , Song Jia-Ni , Zhao Xiu-Nan , Yan Xin-Yi , Yu Shu-Fan , Zhang Yi-Nan 
Published: August 2022

AbstractDialysis adequacy is a known risk factor for mortality in maintenance hemodialysis (MHD) patients. However, the optimal dialysis dose remains controversial. Therefore, we aimed to explore the relationship between dialysis dose and all-cause and cardiovascular disease (CVD) mortality among MHD. We examined the associations of dialysis dose with mortality in a cohort (n = 558) of MHD patients from 31 December 2015 to 31 December 2020. Dialysis adequacy was assessed using baseline Single-pool Kt/Vurea (spKt/V), which was categorized into three groups, and the lowest dose group was used as the reference category. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression models. A total of 214 patients died (64.5% for CVD). Compared with the low-dose group, high-dose group could reduce the risk of all-cause mortality by 33% (HR = 0.67, 95% CI: 0.47–0.98). Of note, when stratification by age, high-dose group was associated with both lower all-cause (HR = 0.46, 95% CI: 0.26–0.81) and CVD mortality (HR = 0.42, 95% CI: 0.20–0.88) among patients with age below 65 years. When stratification by dialysis age, high-dose group was associated with decreased risk of CVD mortality (HR = 0.43, 95% CI: 0.20–0.91) among patients with dialysis age over 60 months. spKt/V is a simple index of hemodialysis dose used in clinical practice and a useful modifiable factor in predicting the risk of death, especially in MHD patients under 65 years old or dialysis age more than 60 months.
Association between plant-based diets and metabolic health status in adolescents with overweight and obesity
Authors: Mokhtari Elahe , Mirzaei Saeideh , Asadi Ali , Akhlaghi Masoumeh , Saneei Parvane 
Published: August 2022

AbstractThe association of plant-based diets with health status is underestimated in pediatrics. We aimed to examine the relation between plant-based diets (including overall plant-based index (PDI), healthy plant-based (hPDI) and unhealthy plant-based (uPDI)) and metabolic health status in Iranian adolescents with overweight/obesity. We conducted a cross-sectional study on 203 adolescents with overweight/obesity (12–18 years old) selected by a multistage cluster random-sampling method. Usual dietary intakes were assessed through a validated 147-item food frequency questionnaire (FFQ). Anthropometric indices and blood pressure values were measured and fasting blood samples were drawn. For classification of participants into metabolically healthy obese (MHO) or metabolically unhealthy obese (MUO) groups, two methods of International Diabetes Federation (IDF) and combination of IDF with Homeostasis Model Assessment Insulin Resistance (HOMA-IR) were applied. No significant association was observed between higher adherence to PDI and odds of MUO status defined by both IDF and IDF/HOMA-IR strategies. After adjustments for all potential confounders, adolescents in the highest tertile of hPDI, compared with those in the lowest tertile, had 85% (95% CI 0.05–0.43) and 84% (95% CI 0.05, 0.52) lower odds of being MUO based on IDF and IDF/HOMA-IR criteria, respectively. Greater adherence to uPDI was associated with odd of 3.95 (95% CI 1.41, 11.12) and 4.06 (95% CI 1.31, 12.57) of being MUO based on IDF and IDF/HOMA-IR definitions, after considering all potential confounders. Stratified analysis revealed that these associations were stronger in girls and overweight subjects. Adherence to healthy plant-based foods was inversely associated with odds of MUO status in Iranian adolescents. In contrast, unhealthy plant-based diets was directly associated with MUO in pediatrics. Further studies with prospective nature, are required to affirm these results.
Prediction of B cell epitopes in proteins using a novel sequence similarity-based method
Authors: Ras-Carmona Alvaro , Lehmann Alexander A. , Lehmann Paul V. , Reche Pedro A. 
Published: August 2022

AbstractPrediction of B cell epitopes that can replace the antigen for antibody production and detection is of great interest for research and the biotech industry. Here, we developed a novel BLAST-based method to predict linear B cell epitopes. To that end, we generated a BLAST-formatted database upon a dataset of 62,730 known linear B cell epitope sequences and considered as a B cell epitope any peptide sequence producing ungapped BLAST hits to this database with identity ≥ 80% and length ≥ 8. We examined B cell epitope predictions by this method in tenfold cross-validations in which we considered various types of non-B cell epitopes, including 62,730 peptide sequences with verified negative B cell assays. As a result, we obtained values of accuracy, specificity and sensitivity of 72.54 ± 0.27%, 81.59 ± 0.37% and 63.49 ± 0.43%, respectively. In an independent dataset incorporating 503 B cell epitopes, this method reached accuracy, specificity and sensitivity of 74.85%, 99.20% and 50.50%, respectively, outperforming state-of-the-art methods to predict linear B cell epitopes. We implemented this BLAST-based approach to predict B cell epitopes at http://imath.med.ucm.es/bepiblast.
A study of socio-economic inequalities in self-reported oral and general health in South-East Norway
Authors: Lyshol Heidi , Grøtvedt Liv , Fagerhaug Tone Natland , Feuerherm Astrid J. , Jakhelln Gry , Sen Abhijit 
Published: August 2022

AbstractThis study assesses the association between socioeconomic determinants and self-reported health using data from a regional Norwegian health survey. We included 9,068 participants ≥ 25 years. Survey data were linked to registry data on education and income. Self-reported oral and general health were separately assessed and categorized into ‘good’/‘poor’. Exposures were educational level, personal income, and economic security. Prevalence ratios (PR) were computed to assess the associations between socioeconomic determinants and self-reported health using Poisson regression models. Participants with low education or income had poorer oral and general health than those with more education or higher income. Comparing the highest and lowest education levels, adjusted PRs for poor oral and general health were 1.27 (95%CI, 1.11–1.46) and 1.43 (95%CI, 1.29–1.59), respectively. Correspondingly, PRs for lowest income quintiles compared to highest quintile were 1.34 (95%CI, 1.17–1.55) and 2.10 (95%CI, 1.82–2.43). Low economic security was also significantly associated with poor oral and general health. There were socioeconomic gradients and positive linear trends between levels of education and income in relation to both outcomes (P-linear trends < 0.001). We found statistical evidence of effect modification by gender on the association between education and oral and general health, and by age group between income and oral health.
Smart coordination of predictive load balancing for residential electric vehicles based on EMD‐Bayesian optimised LSTM
Authors: Akil Murat , Dokur Emrah , Bayindir Ramazan 
Published: August 2022

AbstractThe charging load forecasting of residential Electric Vehicles help grid operators make informed decisions in terms of scheduling and managing demand response. The residence can include integrated residential appliances with multi‐state and high‐frequency features. For this reason, it is difficult to estimate the total load of residence accurately. To overcome this problem, this paper proposes a hybrid forecasting model using the empirical mode decomposition and Bayesian optimised Long Short‐Term Memory for load balancing based on residential electricity meter data. The residential electricity meter data includes three datasets as Electric Vehicle, heat pump and photovoltaic system. To decompose of the data characteristics, the empirical mode decomposition method performs to the original data. Then, the Bayesian optimised Long Short‐Term Memory is applied to forecast for each sub‐component of the data sequentially. The main features of the proposed model include a significant improvement in prediction accuracy and capture the local maximums. The advantage of the proposed method over existing methods are also verified over with experiments of data‐driven on the IEEE 33 busbar test system. The result of simulation forecasting model indicates that predict closely the busbar outflow power, voltage drop, transformer loading states and power losses to compare with actual load model.
Numerical study on stability of composite cutter bar milling system in rotating coordinate frame
Authors: Zhang Yuhuan , Ren Yongsheng , Zhang Jinfeng 
Published: August 2022

AbstractThis paper studies the chatter stability of composite cutter bar milling system in rotating coordinate frame. The main contribution of this paper is establishing a continuous distributed chatter analysis model for a composite cutter bar milling system in rotating coordinate frame. The stability of the milling system with a rotary symmetric dynamic cutter bar is predicted using the semi‐discrete time domain method. The effects such as internal damping, external damping, and symmetrical and asymmetric laminates on the stability of the milling system were analysed, and the results were compared between rotating and fixed coordinate frames. The results are consistent for symmetrical cutter bars in both the rotating and fixed coordinate frames. A new chatter instability zone appears at high rotating speeds due to the material internal damping of the rotating composite cutter bar.
Acute Colonic Pseudo-Obstruction
Authors: Arthur Thomas , Burgess Adele 
Published: August 2022

AbstractAcute colonic pseudo-obstruction (ACPO) is a functional disorder of the large intestine distinguished by colonic dysmotility resulting in colonic distension in the absence of mechanical obstruction. The underlying pathophysiology of ACPO remains unclear despite technological advances in understanding the physiology of colonic motility, such as spatio-temporal mapping and high-resolution manometry. In many ways, the management of ACPO has remained relatively unchanged for 40 years. Patients with perforation or suspected ischemia undergo operative intervention, while patients without undergo initial conservative management with bowel rest, correction of electrolyte disturbances, and mobilization. Patients who fail conservative management or have prominent cecal dilatation undergo decompression with either neostigmine or colonoscopy. A subset of patients with ACPO will have recurrent symptoms despite endoscopic and medical management. For these patients who are difficult to manage, an underlying colonic functional disorder, such as slow-transit dysmotility or chronic intestinal pseudo-obstruction may be considered. The following review of ACPO aims to provide a concise update of the causes, diagnosis, and management of this emergency surgical condition.