bluuebunny/crossref_metadata_2025_split huggingface dataset:
Two complementary model-based methods for calculating the risk of international spreading of a novel virus from the outbreak epicentre. The case of COVID-19
Authors: Massad Eduardo , Amaku Marcos , Wilder-Smith Annelies , Costa dos Santos Paulo Cesar , Struchiner Claudio Jose , Coutinho Francisco Antonio Bezerra 
Published: June 2020

Abstract
We present two complementary model-based methods for calculating the risk of international spread of the novel coronavirus SARS-CoV-2 from the outbreak epicentre. One model aims to calculate the number of cases that would be exported from an endemic country to disease-free regions by travellers. The second model calculates the probability that an infected traveller will generate at least one secondary autochthonous case in the visited country. Although this paper focuses on the data from China, our methods can be adapted to calculate the risk of importation and subsequent outbreaks. We found an average R0 = 5.31 (ranging from 4.08 to 7.91) and a risk of spreading of 0.75 latent individuals per 1000 travellers. In addition, one infective traveller would be able to generate at least one secondary autochthonous case in the visited country with a probability of 23%.
A rare case of primary cardiac Hodgkin lymphoma in a child
Authors: Zoma Justino M. , Aggarwal Sanjeev , Gabali Ali , Kobayashi Daisuke 
Published: June 2020

AbstractPrimary pediatric cardiac tumors are extremely rare. We report a 14-year-old girl with primary cardiac Hodgkin lymphoma. The large right atrial tumor extended upward and occluded the superior caval vein and left innominate vein.
Non-linear analysis of heart rate variability for evaluating the acute effects of caffeinated beverages in young adults
Authors: Caliskan Serife G. , Bilgin Mehmet D. 
Published: June 2020

AbstractCaffeinated beverages are the most consumed substances in the world. High rate of uptake of these beverages leads to various cardiovascular disorders ranging from palpitations to coronary failure. The objective of the study is to ascertain how the complexity parameters of heart rate variability are affected by acute consumption of caffeinated beverages in young adults.Electrocardiogram measurements were performed before consuming drinks. After consuming the drinks, measurements were done again at 30 minutes and 60 minutes. Heart rate variability signals were acquired from electrocardiogram signals. Also, the signals were reconstructed in the phase space and largest Lyapunov exponent, correlation dimension, approximate entropy, and detrended fluctuation analysis values were calculated.Heart rate increased for energy drink and cola groups but not in coffee group. Non-linear parameter values of energy drink, coffee, and cola group are increased within 60 minutes after drink consumption. This change is statistically significant just for energy drink group.Energy drink consumption increases the complexity of the cardiovascular system in young adults significantly. Coffee and cola consumption have no significant effect on the non-linear parameters of heart rate variability.
Imparting interpretability to word embeddings while preserving semantic structure
Authors: Şenel Lütfi Kerem , Utlu İhsan , Şahinuç Furkan , Ozaktas Haldun M. , Koç Aykut 
Published: June 2020

AbstractAs a ubiquitous method in natural language processing, word embeddings are extensively employed to map semantic properties of words into a dense vector representation. They capture semantic and syntactic relations among words, but the vectors corresponding to the words are only meaningful relative to each other. Neither the vector nor its dimensions have any absolute, interpretable meaning. We introduce an additive modification to the objective function of the embedding learning algorithm that encourages the embedding vectors of words that are semantically related to a predefined concept to take larger values along a specified dimension, while leaving the original semantic learning mechanism mostly unaffected. In other words, we align words that are already determined to be related, along predefined concepts. Therefore, we impart interpretability to the word embedding by assigning meaning to its vector dimensions. The predefined concepts are derived from an external lexical resource, which in this paper is chosen as Roget’s Thesaurus. We observe that alignment along the chosen concepts is not limited to words in the thesaurus and extends to other related words as well. We quantify the extent of interpretability and assignment of meaning from our experimental results. Manual human evaluation results have also been presented to further verify that the proposed method increases interpretability. We also demonstrate the preservation of semantic coherence of the resulting vector space using word-analogy/word-similarity tests and a downstream task. These tests show that the interpretability-imparted word embeddings that are obtained by the proposed framework do not sacrifice performances in common benchmark tests.
Simulation-Trained Sparse Coding for High-Precision Phase Imaging in Low-Dose Electron Holography
Authors: Anada Satoshi , Nomura Yuki , Hirayama Tsukasa , Yamamoto Kazuo 
Published: June 2020

AbstractWe broaden the applicability of sparse coding, a machine learning method, to low-dose electron holography by using simulated holograms for learning and validation processes. The holograms, with shot noise, are prepared to generate a model, or a dictionary, that includes basic features representing interference fringes. The dictionary is applied to sparse representations of other simulated holograms with various signal-to-noise ratios (SNRs). Results demonstrate that this approach successfully removes noise for holograms with an extremely small SNR of 0.10, and that the denoised holograms provide the accurate phase distribution. Furthermore, this study demonstrates that the dictionary learned from the simulated holograms can be applied to denoising of experimental holograms of a p–n junction specimen recorded with different exposure times. The results indicate that the simulation-trained sparse coding is suitable for use over a wide range of imaging conditions, in particular for observing electron beam-sensitive materials.
Evaluation of daily dose accumulation with deformable image registration method using helical tomotherapy images for nasopharyngeal carcinoma
Authors: Thongsuk Warit , Nobnop Wannapha , Chitapanarux Imjai , Wanwilairat Somsak 
Published: June 2020

AbstractAim:Nasopharyngeal carcinoma (NPC) patients may have anatomical variations during their radiotherapy treatment course. In this study, we determine the daily accumulated dose by the deformable image registration (DIR) process for comparing with the planned dose and explore the number of fractions which the daily accumulated dose significantly changed from the planned dose.Methods:The validation of the DIR process in MIM software has been tested. One hundred and sixty-five daily megavoltage computed tomography (MVCT) images of NPC patients who were treated by helical tomotherapy were exported to MIM software to determine the daily accumulated dose and then compared with the planned dose.Results:The MIM software illustrated the acceptable validation for clinical application. The accumulated dose (D50%) of the planning target volume (PTV70) showed a decrease from the planned dose with an average of 0.5 ± 0.27% at the end of the treatment and was significantly different from the planned dose after the second fraction of the treatment (p-value = 0.008). In contrast, the accumulated dose of organ at risk (OAR) tended to increase from the planned dose and was significantly different after the fifth fraction (left parotid), the twelfth fraction (right parotid) and the second fraction (spinal cord).Findings:The inter-fractional anatomic changes cause the actual dose to be different from the planned dose. The dose differences and the number of fractions were varied in each target and OAR. The dose accumulation explored the necessary information for the radiation oncologist to consider adaptive treatment strategies to increase the efficiency of treatment.
What are the recovery and attrition outcomes for group CBT and individual CBT for generalised anxiety disorder in an IAPT service? An exploratory study
Authors: Fanous Marianne , Daniels Jo 
Published: June 2020

Abstract
Group cognitive behavioural therapy (gCBT) is commonly used in Increasing Access to Psychological Therapies (IAPT) services. However, there is limited knowledge of the efficacy of gCBT as a delivery format for generalised anxiety disorder (GAD). To address gaps in literature, this study aims to explore the efficacy and attrition of individual and group CBT interventions, respectively, at Step 3 for GAD using data from a routine IAPT service over a 24-month period. Data were retrospectively derived from a routine serviceʼs IAPTus database, separating those eligible for comparison into group (n = 44) and individual (n = 55) CBT for GAD. Outcomes were differences in pre–post self-reported anxiety (GAD-7) and depression (PHQ-9) scores, clinical recovery and attrition for gCBT and individual CBT. Both gCBT and individual CBT yielded significant reductions in self-reported anxiety and depression scores over time. Results indicate that 53% of patients attending individual CBT achieved clinical recovery, with similar but less competitive rates of 41% in gCBT. Attrition rates were similar between gCBT (29.5%) and individual CBT (27.3%), respectively. Preliminary results suggest that both individual and gCBT are effective interventions for GAD patients in IAPT, offering symptom alleviation and comparable recovery and attrition rates post-intervention. This observational design offers credibility and insight into a pragmatic evaluative and explorative comparison. gCBT may offer an acceptable and potentially economical alternative.

Key learning aims

(1)
To explore whether gCBT and individual CBT yield significant symptom reduction in self-reported anxiety and depression in GAD patients from a routine IAPT service.

(2)
To explore gCBT and individual CBT clinical recovery rates in non-optimum routine conditions.

(3)
To explore whether gCBT for GAD produces unacceptable attrition rates and if this differs from attrition rates in individual CBT for GAD in a routine IAPT service.
Efficacy of near-infrared spectroscopy cerebral oximetry on detection of critical cerebral perfusion during carotid endarterectomy under regional anesthesia
Authors: Rocha-Neves João P. , Pereira-Macedo Juliana , Moreira André L. , Oliveira-Pinto José P. , Afonso Graça , Mourão Joana , Andrade José P. , Vaz Ricardo P. , Mansilha Armando 
Published: June 2020

Summary: Background: Patients undergoing carotid endarterectomy (CEA) may suffer from cerebral hypoperfusion during the carotid cross-clamping. Near-infrared spectroscopy cerebral oximetry (NIRS) is a non-invasive method of regional cerebral oxygen saturation measurement reflecting changes in cerebral blood flow during CEA. The main goal of the study was to evaluate the accuracy of the NIRS in detecting cerebral hypoperfusion during CEA under regional anesthesia (RA) and compare it with awake neurological testing. Patients and methods: A prospective observational study of 28 patients that underwent CEA in RA and manifested neurologic deficits, and 28 consecutive controls from a tertiary and referral center, was performed. All patients were monitored with NIRS cerebral oximetry and awake testing as the control technique. Subsequently, operating characteristic curve and Cohen’s kappa coefficient were determined to evaluate the reliability of the monitoring test. Results: NIRS presented a sensitivity of 27.3% and a specificity of 89.3% in comparison to awake testing. Receiver operating characteristic (ROC) curve analysis demonstrated that a decrease of at least 20% in cerebral oxygen saturation is the best threshold to infer cerebral hypoperfusion. However, the respective area under the curve (AUROC) was 0.606 (95% CI: 0.456–0.756, P = 0.178) with a calculated Cohen’s kappa of 0.179, P = 0.093. Regarding 30-days outcomes, only awake testing has shown significant associations with stroke and postoperative complications ( P = 0.043 and P = 0.05), which were higher in patients with post-clamping neurologic deficits. Conclusions: NIRS demonstrated a reduced discriminative capacity for critical cerebral hypoperfusion, and does not seem to add substantial clinical benefits to the awake test.
Post‐Wildfire Surface Deformation Near Batagay, Eastern Siberia, Detected by L‐Band and C‐Band InSAR
Authors: Yanagiya Kazuki , Furuya Masato 
Published: June 2020

AbstractThawing of ice‐rich permafrost and subsequent ground subsidence can form characteristic landforms, and the resulting topography they create is collectively called “thermokarst.” The impact of wildfire on thermokarst development remains uncertain. Here, we report on the post‐wildfire ground deformation associated with the 2014 wildfire near Batagay, Eastern Siberia. We used Interferometric Synthetic Aperture Radar (InSAR) to generate both long‐term (1–4 years) and short‐term (subseasonal to seasonal) deformation maps. Based on two independent satellite‐based microwave sensors, we could validate the dominance of vertical displacements and their heterogeneous distributions without relying on in situ data. The inferred time series based on L‐band ALOS2 InSAR data indicated that the cumulative subsidence at the area of greatest magnitude was greater than 30 cm from October 2015 to June 2019 and that the rate of subsidence slowed in 2018. The burn severity was rather homogeneous, but the cumulative subsidence magnitude was larger on the east‐facing slopes where the gullies were also predominantly developed. The correlation suggests that the active layer on the east‐facing slopes might have been thinner before the fire. Meanwhile, C‐band Sentinel‐1 InSAR data with higher temporal resolution showed that the temporal evolution included episodic changes in terms of deformation rate. Moreover, we could unambiguously detect frost heave signals that were enhanced within the burned area during the early freezing season but were absent in the mid‐winter. We could reasonably interpret the frost heave signals within a framework of premelting theory instead of assuming a simple freezing and subsequent volume expansion of preexisting pore water.
Ocean Alkalinity, Buffering and Biogeochemical Processes
Authors: Middelburg Jack J. , Soetaert Karline , Hagens Mathilde 
Published: June 2020

AbstractAlkalinity, the excess of proton acceptors over donors, plays a major role in ocean chemistry, in buffering and in calcium carbonate precipitation and dissolution. Understanding alkalinity dynamics is pivotal to quantify ocean carbon dioxide uptake during times of global change. Here we review ocean alkalinity and its role in ocean buffering as well as the biogeochemical processes governing alkalinity and pH in the ocean. We show that it is important to distinguish between measurable titration alkalinity and charge balance alkalinity that is used to quantify calcification and carbonate dissolution and needed to understand the impact of biogeochemical processes on components of the carbon dioxide system. A general treatment of ocean buffering and quantification via sensitivity factors is presented and used to link existing buffer and sensitivity factors. The impact of individual biogeochemical processes on ocean alkalinity and pH is discussed and quantified using these sensitivity factors. Processes governing ocean alkalinity on longer time scales such as carbonate compensation, (reversed) silicate weathering, and anaerobic mineralization are discussed and used to derive a close‐to‐balance ocean alkalinity budget for the modern ocean.
Multisite Weather Generators Using Bayesian Networks: An Illustrative Case Study for Precipitation Occurrence
Authors: Legasa M. N. , Gutiérrez J. M. 
Published: June 2020

AbstractMany existing approaches for multisite weather generation try to capture several statistics of the observed data (such as pairwise correlations) in order to generate spatially and temporarily consistent series. In this work, we analyze the application of Bayesian networks to this problem, focusing on precipitation occurrence and considering a simple case study to illustrate the potential of this new approach. We use Bayesian networks to approximate the multivariate (multisite) probability distribution of observed gauge data, which is factorized according to the relevant (marginal and conditional) dependencies. This factorization allows the simulation of synthetic samples from the multivariate distribution, thus providing a sound and promising methodology for multisite precipitation series generation.
Geomagnetic Activity Control of Irregularities Occurrences Over the Crests of the African EIA
Authors: Amaechi P. O. , Oyeyemi E. O. , Akala A. O. , Amory‐Mazaudier C. 
Published: June 2020

AbstractThis paper investigated the behavior of ionospheric irregularities over the African equatorial ionization anomaly (EIA) crests during intense geomagnetic storms that occurred from 2012 to 2015. Irregularities were monitored using the rate of change of TEC index along with variations of the horizontal component of the Earth's magnetic field (H) and ionospheric electric current disturbance (Diono). The predictive capability of the Prompt Penetration Equatorial Electric Field Model (PPEFM) was assessed by comparing prompt penetration electric field (PPEF) inferred from interplanetary electric field and Diono with PPEF derived from the PPEFM, with emphasis on how well the model reproduced enhancement/reduction in the prereversal enhancement (PRE). Eastward PPEF triggered short duration irregularities on 23 April 2012, 17 March 2013, and 20 February 2014 while westward electric field reduced them thereafter. The PPEFM rightly predicted enhancement (reduction) in PRE on 17 March 2013 (19 February 2014) when irregularities were triggered (inhibited). It, however, showed no change in the PRE on 23 April 2012 and 20 February 2014. During the storms recoveries, irregularities were always inhibited/reduced over the trough by westward disturbance dynamo and the inhibition lasted longer during the superstorm of March 2015. Also, there was a hemispheric asymmetry in irregularities over the African EIA crests. On 16–17 July 2012, 15 November 2012, and 19 March 2013, there were differences in irregularities behavior. On these days, the asymmetry of the postsunset crests was pronounced in both hemispheres.
Equilibrium Temperatures and Directional Emissivity of Sunlit Airless Surfaces With Applications to the Moon
Authors: Rubanenko L. , Schorghofer N. , Greenhagen B. T. , Paige D. A. 
Published: June 2020

AbstractSolar irradiance dominates the heat flux incident on airless planetary bodies. In thermal equilibrium, surface roughness affects the temperature distribution by changing the incidence angle local to each slope. In order to simulate temperatures and thermal emissions at different phase angles, existing thermophysical models usually employ computationally expensive techniques such as ray tracing. Here we derive the equilibrium surface temperature distribution of sunlit Gaussian rough surfaces, providing an exact solution for the Sun at the zenith and an approximate solution for the general case. We find that although the slope distribution of realistic airless surfaces is often non‐Gaussian, their temperature distribution is well modeled assuming a Gaussian slope distribution. We additionally present closed‐form expressions that describe the radiation emitted from rough surfaces at different emissions angles and employ them to radiometrically estimate the roughness of the lunar surface using measurements obtained by Lunar Reconnaissance Orbiter (LRO) Diviner. Our model may also be applied to studying the roughness of resolved and unresolved surfaces on other airless planetary bodies.
Consumption of a high energy density diet triggers microbiota dysbiosis, hepatic lipidosis, and microglia activation in the nucleus of the solitary tract in rats
Authors: Minaya Dulce M. , Turlej Anna , Joshi Abhinav , Nagy Tamas , Weinstein Noah , DiLorenzo Patricia , Hajnal Andras , Czaja Krzysztof 
Published: June 2020

AbstractIntroductionObesity is a multifactorial chronic inflammatory disease. Consumption of high energy density (HED) diets is associated with hyperphagia, increased body weight and body fat accumulation, and obesity. Our lab has previously shown that short-term (4 weeks) consumption of a HED diet triggers gut microbiota dysbiosis, gut inflammation, and reorganization of the gut-brain vagal communication.ObjetivesThe aim of this study was to investigate the effect of long-term (6 months) consumption of HED diet on body composition, gut microbiome, hepatocellular lipidosis, microglia activation in the nucleus of the solitary tract, and systemic inflammation.MethodsMale Sprague–Dawley rats were fed a low energy density (LED) diet for 2 weeks and then switched to a HED diet for 26 weeks. Twenty-four-hour food intake, body weight, and body composition were measured twice a week. Blood serum and fecal samples were collected at baseline, 1, 4, 8, and 26 weeks after introduction of the HED diet. Serum samples were used to measure insulin, leptin, and inflammatory cytokines using Enzyme-linked Immunosorbent Assay. Fecal samples were assessed for 16 S rRNA genome sequencing.ResultsHED diet induced microbiota dysbiosis within a week of introducing the diet. In addition, there was significant microglia activation in the intermediate NTS and marked hepatic lipidosis after 4 weeks of HED diet. We further observed changes in the serum cytokine profile after 26 weeks of HED feeding.ConclusionsThese data suggest that microbiota dysbiosis is the first response of the organism to HED diets, followed by increased liver fat accumulation, microglia activation in the brain, and circulating levels of inflammatory markers. To our knowledge, this is the first study to present longitudinal and cross-sectional results on effect of long-term consumption of HED diets on all these parameters in a single cohort of animals.
A key role of the subdiaphragmatic vagus nerve in the depression-like phenotype and abnormal composition of gut microbiota in mice after lipopolysaccharide administration
Authors: Zhang Jiancheng , Ma Li , Chang Lijia , Pu Yaoyu , Qu Youge , Hashimoto Kenji 
Published: June 2020

AbstractThe vagus nerve plays a role in the cross talk between the brain and gut microbiota, which could be involved in depression. The subdiaphragmatic vagus nerve serves as a major modulatory pathway between the brain and gut microbiota. Here, we investigated the effects of subdiaphragmatic vagotomy (SDV) on the depression-like phenotype and the abnormal composition of gut microbiota in mice after lipopolysaccharide (LPS) administration. LPS caused a depression-like phenotype, inflammation, increase in spleen weight, and downregulation of synaptic proteins in the medial prefrontal cortex (mPFC) in the sham-operated mice. In contrast, LPS did not produce a depression-like phenotype and downregulated synaptic proteins in the mPFC after SDV. The spleen weight and plasma levels of pro-inflammatory cytokines in the SDV + LPS group were lower than those of the sham + LPS group. Interestingly, there were positive correlations between the plasma levels of pro-inflammatory cytokines and spleen weight, suggesting a relationship between inflammatory events and spleen weight. Furthermore, LPS led to significant alterations in gut microbiota diversity in sham-operated mice, but not SDV-operated mice. In an unweighted UniFrac PCoA, the dots representing the sham + LPS group were located far away from the dots representing the other three groups. Our results suggest that LPS produces a depression-like phenotype, increases spleen weight, triggers inflammation, downregulates synaptic proteins in the mPFC, and leads to abnormal composition of gut microbiota via the subdiaphragmatic vagus nerve. It is likely that the vagus nerve plays a crucial role in the brain–gut–microbiota axis.