bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of financial relationships between Japanese certified pediatric hematologist/oncologists and pharmaceutical companies: a cross‐sectional analysis of personal payments from pharmaceutical companies between 2016 and 2019
Authors: Kamamoto Sae , Murayama Anju , Kusumi Eiji , Yoshida Makoto , Saito Hiroaki , Sawano Toyoaki , Yamashita Erika , Tanimoto Tetsuya , Ozaki Akihiko 
Published: August 2022

AbstractThis cross‐sectional study evaluated the magnitude of personal payments made by pharmaceutical companies to pediatric hematologist‐oncologists (PHOs) board‐certified by the Japanese Society of Pediatric Hematology/Oncology (JSPHO), using publicly disclosed data. Among all 307 PHOs, 215 (70.0%) PHOs received $916 703 personal payments from 54 pharmaceutical companies between 2016 and 2019 in total. Median four‐year payments per PHO was $1440 (interquartile range, $523‐$4015). Payments per PHO significantly increased during the study period, by 23.8% (95% confidence interval: 15.3%‐32.8%,P< 0.001) annually. Furthermore, leading PHOs, including university professors, society board members, and clinical practice guideline authors, received far larger personal payments from the companies.
High achievers, Schadenfreude and Gluckschmerz in New Zealanders and Chinese
Authors: Phillips James G. , Landhuis C. Erik , Wood Jay K. , Wang Ying 
Published: August 2022

AbstractThe willingness to support (or denigrate) high‐profile individuals online was examined across cultures using the Tall Poppy Scale. A sample of 106 Chinese and 164 New Zealand Europeans answered an online questionnaire addressing their preference for high achievers to be rewarded or fail. Participants were asked whether they would vote to support reality TV contestants, and offered further information (about success or failure) on a debrief page. The Favour Reward scale predicted willingness to vote and support others. The Favour Fall subscale tended to predict time spent viewing achievement‐related information on a debrief page. The Chinese sample did not prefer reward of high achievers, instead favoring their fall, but spent less time per click on the debrief page, suggesting they disliked recognizing individual achievement.
Mannose‐binding lectin genotype is associated with respiratory disease in young children: A multicenter cohort study
Authors: Ruffles Tom , Basu Kaninika , Inglis Sarah K. , Bremner Stephen , Rabe Heike , Memon Anjum , Seddon Paul , Tavendale Roger , Palmer Colin N. A. , Mukhopadhyay Somnath , Fidler Katy 
Published: August 2022

AbstractBackgroundMannose‐binding lectin (MBL) is an important component of the innate immune system. Polymorphisms in the MBL2 gene and promoter region are directly associated with MBL‐deficiency. We sought to determine the association between MBL genotype on the frequency of common childhood respiratory infections, respiratory symptoms, and atopic outcomes in early childhood.MethodsMBL2 gene variants were analyzed in newborns recruited to the GO‐CHILD multicenter prospective cohort study. Follow‐up for respiratory infection and atopy diagnoses and symptoms, healthcare utilization, and medication prescription were conducted by postal questionnaires at 12 and 24 months.ResultsGenotyping and follow‐up were completed in 1004 children. Genotypes associated with MBL‐deficiency were associated with an increased risk of bronchiolitis (relative risk [RR] 1.95, 95% confidence interval [CI] 1.33–2.85) and pneumonia (RR 2.46, 95% CI 1.16–5.22). MBL‐deficient genotypes were associated with an increased risk of wheeze with shortness of breath episodes (RR 1.22, 95% CI 1.04–1.43), emergency department attendance (RR 1.90 95% CI 1.13–3.19), and hospital admission (RR 2.01, 95% CI 1.04–3.89) for wheeze. MBL‐deficient genotypes were associated with a reduced risk of developing atopic dermatitis (RR 0.72, 95% CI 0.53–0.98).ConclusionThe positive association between MBL‐deficient genotypes and bronchiolitis and pneumonia, as well as a severe wheeze phenotype in some young children, supports the hypothesis that MBL is an important component of innate immunity in the vulnerable period before the maturation of the adaptive immune system. Identification of disease‐modifying genotypes may help target preventative strategies in high‐risk infants.
Pressure‐Dependent Chemical Decomposition of an HMX‐Based PBX During Low‐Velocity Impacts
Authors: Tchikladzé Nicolas , Picart Didier , Camus Stéphanie 
Published: August 2022

AbstractHMX decomposition kinetics are usually calibrated in the temperature range around 200 °C. This leads to an underestimation of several orders of magnitude of the thermal explosion times during impacts compared to measurements collected in Henson and Smilowitz, in Non‐shock initiation of explosives, Shock wave science and technology reference library, 2010. It highlights the incomplete physics used in the single‐ or multi‐stage decomposition kinetics to model the solid‐to‐gas transformation of HMX. The experimental device proposed in this work allows the observation of sample pressure and size during heating tests and thus allows the phase transition and thermal explosion of the samples to be observed in real time. The Henson and Smilowitz model is revisited by integrating (1) the mechanical resistance of the molecular network to the phase change and (2) a dependence of the vaporization and sublimation rates on the pressure. The latter describes the pressure‐dependence on the virtual melting mechanism and consequently on the presence or absence of δ‐HMX in the solid and liquid states. Good correlations between the numerical results and data are obtained. The modified model is then extrapolated to the low velocity impact range.
Lithium decorated C3N as high capacity reversible hydrogen storage material: Insights from density functional theory
Authors: Zhang Xinhui , Hao Jinbo , Gao Shuli , Wu Liyuan , Wu Ge , Chen Feng , Gao Le , Lu Pengfei 
Published: August 2022

AbstractLithium‐decorated (Li‐decorated) C3N has been investigated as a potential material for high capacity reversible hydrogen storage. The energetic stability, dynamical stability, and thermal stability were studied. The cohesive energy of C3N (7.03 eV/atom) denotes the energetic stability, imaginary frequencies are not found from the result of phonon spectrum calculation, and the free energy vibrates slightly around −64.63 eV during the 5000 fs period and no structure reconstruction. Electronic properties showed the band gaps are 0.39 and 1.12 eV, via PBE and HSE calculations, respectively. The four probable Li‐adsorbed sites were calculated, indicating that the hollow site above the center of a hexagon ring HC site is the most likely site to absorb Li atom. Hydrogen molecules were added one by one to research the maximum hydrogen gravimetric density. Each Li atom can attach 10 hydrogen molecules within the range of physical adsorption processes (−0.1 to −0.4 eV/H2) and the hydrogen storage capacity can reach as high as 8.81 wt%. Li‐decorated C3N has great potential for on‐board reversible solid‐state hydrogen molecule storage application.
The Unitary Master Ward Identity: Time Slice Axiom, Noether’s Theorem and Anomalies
Authors: Brunetti Romeo , Dütsch Michael , Fredenhagen Klaus , Rejzner Kasia 
Published: August 2022

AbstractThe C*-algebraic formulation of generic interacting quantum field theories, recently presented by Detlev Buchholz and one of the authors (KF), is enriched by a unitary version of the Master Ward Identity, which was postulated some time ago by Franz Marc Boas, Ferdinand Brennecke and two of us (MD,KF). It is shown that the corresponding axiom implies the validity of the time slice axiom. Moreover, it opens the way for a new approach to Noether’s Theorem where it yields directly the unitaries implementing the symmetries. It also unravels interesting aspects of the role of anomalies in quantum field theory.
The effect of microfluidization pressure on the physical stability of vitamin A in oil-in-water emulsions
Authors: Banasaz Shahin , Morozova Ksenia , Ferrentino Giovanna , Scampicchio Matteo 
Published: August 2022

AbstractIn this study, vitamin A was encapsulated within oil-in-water emulsions by high-pressure microfluidization prepared using phosphate buffer (90%), corn oil (10%), and whey protein isolate (2%) as an emulsifier. The influence of microfluidization pressure (10, 50, 100, 200 MPa) on the particle size, zeta potential, and the physical and chemical stability of emulsions was evaluated. The physical stability of emulsion was determined by multiple light scattering technique. The content of vitamin A was measured by HPLC–DAD during an accelerated storage test at 40 °C during 4 weeks. The color of the samples was monitored using a colorimeter. The results showed that the lowest particle size distribution and the highest absolute value of zeta potential on the droplets’ surface charge were obtained by applying a pressure of 100 MPa. Nanoemulsions prepared at 100 MPa also showed the highest colloidal stability. However, higher microfluidization pressure (up to 200 MPa) had a negative impact on the prepared emulsion’s stability. The results of chemical stability by HPLC measurements during storage time were in agreement with the results of physical stability and color change.
Asymmetries in the ENSO phase space
Authors: Dommenget By Dietmar , Al-Ansari Maryam 
Published: August 2022

AbstractEl Niño Southern Oscillation (ENSO) dynamics are best described by the recharge oscillator model, in which the eastern tropical Pacific sea surface temperatures (T) and subsurface heat content (thermocline depth; h) have an out-of-phase relationship. This defines a 2-dimensional phase space diagram between T and h. In an idealized, stochastically forced damped oscillator, the mean phase space diagram should be a perfectly symmetrical circle with a clockwise propagation over time. However, the observed phase space shows strong asymmetries. In this study we illustrate how the ENSO phase space can be used to discuss the phase-dependency of ENSO dynamics. A normalized spherical coordinate system allows the definition of phase-depending ENSO growth rates and phase transition speeds. Based on these we discuss the implications of the observed asymmetries with regards to the dynamics and predictability of ENSO; with a particular focus on the variations in the growth rate and coupling of ENSO along the oscillation cycle. Using linear and non-linear recharge oscillator models we will show how dynamics and noise are driving ENSO at different phases of the ENSO cycles. The results illustrate that the ENSO cycle with positive phase transitions is present in all phases but has strong variations in its strength. Much of these variations result from presenting the ENSO phase space with estimates of h based on the iso-thermal depth, that is not ideal as it is not out-of-phase with T. Future work should address how h can be estimated better, including aspects such as the vertical temperature gradients and the meridional or zonal range. We further illustrated that a non-linear growth rate of T can explain most of the observed non-linear phase space characteristics.
Remote effect of model systematic bias in tropical SST on the cold bias over the Tibetan Plateau
Authors: Wu Yuting , Hu Xiaoming , Li Zhenning , Cai Ming , Lu Mengmeng , Yang Song 
Published: August 2022

AbstractMost state-of-the-art climate models substantially underestimate the near-surface air temperature (SAT) over the Tibetan Plateau (TP), especially for the cold season. While previous studies have attributed this cold bias to local factors such as the elevation difference, coarse resolution, and excessive snow cover, this investigation addresses the potential contributions of the systematic bias of tropical sea surface temperature (SST) to the TP cold bias. Experiments with the NCAR Community Atmosphere Model demonstrate that tropical SST bias results in an apparent cold bias over the TP, especially in boreal winter, and explains about 40% of the deviation in multi-model mean SAT over the TP relative to station observations. Forced by the tropical SST bias, heat flux exhibits an anomalous divergence over the plateau, causing a cooling center in the mid- and lower-troposphere over the TP. This atmospheric cooling in turn leads to a reduction of the downward longwave radiative fluxes reaching the surface, less energy supply, and thus a cold bias over the TP.
Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning
Authors: Denizdurduran Berat , Markram Henry , Gewaltig Marc-Oliver 
Published: August 2022

AbstractFrom the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal joints with antagonistic muscle pairs is finding methods robust to address this ill-posed nonlinear problem. To address this computational problem, we implemented a twofold optimization and learning framework to be specialized in addressing the redundancies in the muscle control . In the first part, we used model predictive control to obtain energy efficient skeletal trajectories to mimick human movements. The second part is to use deep reinforcement learning to obtain a sequence of stimulus to be given to muscles in order to obtain the skeletal trajectories with muscle control. We observed that the desired stimulus to muscles is only efficiently constructed by integrating the state and control input in a closed-loop setting as it resembles the proprioceptive integration in the spinal cord circuits. In this work, we showed how a variety of different reference trajectories can be obtained with optimal control and how these reference trajectories are mapped to the musculoskeletal control with deep reinforcement learning. Starting from the characteristics of human arm movement to obstacle avoidance experiment, our simulation results confirm the capabilities of our optimization and learning framework for a variety of dynamic movement trajectories. In summary, the proposed framework is offering a pipeline to complement the lack of experiments to record human motion-capture data as well as study the activation range of muscles to replicate the specific trajectory of interest. Using the trajectories from optimal control as a reference signal for reinforcement learning implementation has allowed us to acquire optimum and human-like behaviour of the musculoskeletal system which provides a framework to study human movement in-silico experiments. The present framework can also allow studying upper-arm rehabilitation with assistive robots given that one can use healthy subject movement recordings as reference to work on the control architecture of assistive robotics in order to compensate behavioural deficiencies. Hence, the framework opens to possibility of replicating or complementing labour-intensive, time-consuming and costly experiments with human subjects in the field of movement studies and digital twin of rehabilitation.
Machine learning applications in upper gastrointestinal cancer surgery: a systematic review
Authors: Bektaş Mustafa , Burchell George L. , Bonjer H. Jaap , van der Peet Donald L. 
Published: August 2022

AbstractBackgroundMachine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Therefore, this systematic review aims to provide a comprehensive overview of ML applications within upper gastrointestinal surgery for malignancies.MethodsA systematic search was performed in PubMed, EMBASE, Cochrane, and Web of Science. Studies were only included when they described machine learning in upper gastrointestinal surgery for malignancies. The Cochrane risk-of-bias tool was used to determine the methodological quality of studies. The accuracy and area under the curve were evaluated, representing the predictive performances of ML models.ResultsFrom a total of 1821 articles, 27 studies met the inclusion criteria. Most studies received a moderate risk-of-bias score. The majority of these studies focused on neural networks (n = 9), multiple machine learning (n = 8), and random forests (n = 3). Remaining studies involved radiomics (n = 3), support vector machines (n = 3), and decision trees (n = 1). Purposes of ML included predominantly prediction of metastasis, detection of risk factors, prediction of survival, and prediction of postoperative complications. Other purposes were predictions of TNM staging, chemotherapy response, tumor resectability, and optimal therapy.ConclusionsMachine Learning algorithms seem to contribute to the prediction of postoperative complications and the course of disease after upper gastrointestinal surgery for malignancies. However, due to the retrospective character of ML studies, these results require trials or prospective studies to validate this application of ML.Graphical abstract
Lagrange and $$H({\text {curl}},{{\mathcal {B}}})$$ based finite element formulations for the relaxed micromorphic model
Authors: Schröder Jörg , Sarhil Mohammad , Scheunemann Lisa , Neff Patrizio 
Published: August 2022

AbstractModeling the unusual mechanical properties of metamaterials is a challenging topic for the mechanics community and enriched continuum theories are promising computational tools for such materials. The so-called relaxed micromorphic model has shown many advantages in this field. In this contribution, we present significant aspects related to the relaxed micromorphic model realization with the finite element method (FEM). The variational problem is derived and different FEM-formulations for the two-dimensional case are presented. These are a nodal standard formulation $$H^1({{\mathcal {B}}}) \times H^1({{\mathcal {B}}})$$

H
1

(
B
)

×

H
1

(
B
)

and a nodal-edge formulation $$H^1({{\mathcal {B}}}) \times H({\text {curl}}, {{\mathcal {B}}})$$

H
1

(
B
)

×
H

(
curl
,
B
)

, where the latter employs the Nédélec space. In this framework, the implementation of higher-order Nédélec elements is not trivial and requires some technicalities which are demonstrated. We discuss the computational convergence behavior of Lagrange-type and tangential-conforming finite element discretizations. Moreover, we analyze the characteristic length effect on the different components of the model and reveal how the size-effect property is captured via this characteristic length parameter.
The role of optimization in some recent advances in data-driven decision-making
Authors: Baardman Lennart , Cristian Rares , Perakis Georgia , Singhvi Divya , Skali Lami Omar , Thayaparan Leann 
Published: August 2022

AbstractData-driven decision-making has garnered growing interest as a result of the increasing availability of data in recent years. With that growth many opportunities and challenges have sprung up in the areas of predictive and prescriptive analytics. Often, optimization can play an important role in tackling these issues. In this paper, we review some recent advances that highlight the difference that optimization can make in data-driven decision-making. We discuss some of our contributions that aim to advance both predictive and prescriptive models. First, we describe how we can optimally estimate clustered models that result in improved predictions. Next, we consider how we can optimize over objective functions that arise from tree ensemble models in order to obtain better prescriptions. Finally, we discuss how we can learn optimal solutions directly from the data allowing for prescriptions without the need for predictions. For all these new methods, we stress the need for good performance but also the scalability to large heterogeneous datasets.
Hybrid Iterative Ensemble Smoother for History Matching of Hierarchical Models
Authors: Oliver Dean S. 
Published: August 2022

AbstractThe choice of a prior model can have a large impact on the ability to assimilate data. In standard applications of ensemble-based data assimilation, all realizations in the initial ensemble are generated from the same covariance matrix with the implicit assumption that this covariance is appropriate for the problem. In a hierarchical approach, the parameters of the covariance function, for example, the variance, the orientation of the anisotropy and the ranges in two principal directions, may all be uncertain. Thus, the hierarchical approach is much more robust against model misspecification. In this paper, three approaches to sampling from the posterior for hierarchical parameterizations are discussed: an optimization-based sampling approach (randomized maximum likelihood, RML), an iterative ensemble smoother (IES), and a novel hybrid of the previous two approaches (hybrid IES). The three approximate sampling methods are applied to a linear-Gaussian inverse problem for which it is possible to compare results with an exact “marginal-then-conditional” approach. Additionally, the IES and the hybrid IES methods are tested on a two-dimensional flow problem with uncertain anisotropy in the prior covariance. The standard IES method is shown to perform poorly in the flow examples because of the poor representation of the local sensitivity matrix by the ensemble-based method. The hybrid method, however, samples well even with a relatively small ensemble size.
Why pay more for robot in esophageal cancer surgery?
Authors: Rebecchi Fabrizio , Ugliono Elettra , Allaix Marco Ettore , Morino Mario 
Published: August 2022

AbstractEsophagectomy is the gold standard for the treatment of resectable esophageal cancer. Traditionally, it is performed through a laparotomy and a thoracotomy, and is associated with high rates of postoperative complications and mortality. The advent of robotic surgery has represented a technological evolution in the field of esophageal cancer treatment. Robot-assisted Minimally Invasive Esophagectomy (RAMIE) has been progressively widely adopted following the first reports on the safety and feasibility of this procedure in 2004. The robotic approach has better short-term postoperative outcomes than open esophagectomy, without jeopardizing oncologic radicality. The results of the comparison between RAMIE and conventional minimally invasive esophagectomy are less conclusive. This article will focus on the role of RAMIE in the current clinical scenario with particular attention to its possible benefits and perspectives.
Appraisal of Gene-Environment Interactions in GWAS for Evidence-Based Precision Nutrition Implementation
Authors: San-Cristobal Rodrigo , de Toro-Martín Juan , Vohl Marie-Claude 
Published: August 2022

Abstract
Purpose of Review
This review aims to analyse the currently reported gene-environment (G × E) interactions in genome-wide association studies (GWAS), involving environmental factors such as lifestyle and dietary habits related to metabolic syndrome phenotypes. For this purpose, the present manuscript reviews the available GWAS registered on the GWAS Catalog reporting the interaction between environmental factors and metabolic syndrome traits.

Recent Findings
Advances in omics-related analytical and computational approaches in recent years have led to a better understanding of the biological processes underlying these G × E interactions. A total of 42 GWAS were analysed, reporting over 300 loci interacting with environmental factors. Alcohol consumption, sleep time, smoking habit and physical activity were the most studied environmental factors with significant G × E interactions.

Summary
The implementation of more comprehensive GWAS will provide a better understanding of the metabolic processes that determine individual responses to environmental exposures and their association with the development of chronic diseases such as obesity and the metabolic syndrome. This will facilitate the development of precision approaches for better prevention, management and treatment of these diseases.