bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new correlation model for predicting the melting and boiling temperatures of the Lennard-Jones systems
Authors: Sun Chenyang , Zhang Yaning , Hou Chaofeng , Ge Wei 
Published: December 2022

Abstract
The Lennard-Jones (LJ) potential function is widely employed in molecular dynamics simulations. In this study, the LJ potentials under different characteristic diameter σ and characteristic energy ε were simulated, and the changes in properties such as number density, total energy, phase transition latent heat, and phase transition temperature were detailed. With the increase of σ, the melting and boiling temperatures of the LJ systems and the thermodynamic temperature range corresponding to liquid decrease, while with the increase of ε, the melting and boiling temperatures and the thermodynamic temperature range of liquid increase. Moreover, the phase transition latent heat hardly changes with the increase of σ, but significantly increases with ε. The number densities at the melting and boiling temperatures are only dependent on σ, and are not nearly influenced by ε. Furthermore, based on a modified Lindemann’s melting criterion, a new empirical correlation model is proposed to predict the melting and boiling temperatures of the LJ systems, where the phase transition points are in good agreement with the experimental values. For the melting point, the absolute error between the formula and the experimental measurement for inert gas and methane is no more than 10 K, and for the boiling point, the absolute error is less than 15 K. By this new presented model, some thermophysical properties of the LJ potential systems can be quickly obtained and evaluated.
Non-locality ≠ quantum entanglement
Authors: Guo Xingyu , Ma Chen-Te 
Published: December 2022

Abstract
The unique entanglement measure is concurrence in a two-qubit pure state. The maximum violation of Bell’s inequality is monotonically increasing for this quantity. Therefore, people expect that pure state entanglement is relevant to the non-locality. For justification, we extend the study to three qubits. We consider all possible three-qubit operators with a symmetric permutation. When only considering one entanglement measure, the numerical result contradicts expectation. Therefore, we conclude ‘non-locality ≠ quantum entanglement’. We propose the generalized R-matrix or correlation matrix for the new diagnosis of quantum entanglement. We then demonstrate the evidence by restoring the monotonically increasing result.

PACS numbers: 00.00, 20.00, 42.10
On the emergence of traffic jams in a stochastic traffic flow driven by additive and multiplicative white Gaussian noise processes
Authors: Singh Aman Kumar , Meyer Jarrett , Ramakrishnan Subramanian 
Published: December 2022

Abstract
Understanding the influence of random phenomena on the emergence of jams in vehicular traffic flows is a fundamental question in the study of traffic flow dynamics. Motivated by the fact that additive and multiplicative white Gaussian noise processes represent fundamentally distinct sources of randomness that can engender qualitatively different patterns in the dynamics of traffic flow, here we compare and contrast the influences of those two distinct stochastic processes on the formation of traffic jams. Analyzing the macroscopic dynamics of spatially homogeneous single-lane traffic flow using a car distribution function that evolves according to a Fokker–Planck type equation, we first obtain the equilibrium distribution function in closed form for traffic flow driven by additive as well as multiplicative white Gaussian noise. We then derive the mean first passage time (MFPT) for both cases and also present results that elucidate the influence of varying noise strength on both the equilibrium distribution function and the MFPT. Additionally, we obtain fundamental diagrams corresponding to speed versus flux of vehicle flow for both cases that further highlight the distinct effects of the two types of noise. In summary, the results underscore the contrasting influences of additive and multiplicative noise processes on the emergence of traffic jams and thereby contribute to advancing our understanding of this aspect of stochastic traffic flow. The findings could also help improve our understanding of how randomness affects traffic flows that are a combination of human and self-driven vehicles.
Ontogeny influences tree growth response to soil fertility and neighbourhood crowding in an old-growth temperate forest
Authors: Ren Jing , Fang Shuai , Wang Qing-Wei , Liu Hongyan , Lin Fei , Ye Ji , Hao Zhanqing , Wang Xugao , Fortunel Claire 
Published: December 2022

AbstractBackground and aimsAbiotic and biotic factors simultaneously affect tree growth and thus shape community structure and dynamics. In particular, trees of different size classes show different growth responses to soil nutrients and neighbourhood crowding, but our understanding of how species’ joint responses to these factors vary between size classes remains limited in multi-storied temperate forests. Here, we investigated size class differences in tree growth response to soil gradients and neighbourhood crowding in an old-growth temperate forest.MethodsWe combined growth data over 15 years from 38 902 individuals of 42 tree species with trait data in a 25-ha temperate forest plot in northeast China. We built hierarchical Bayesian models of tree growth to examine the effects of soil gradients and neighbourhood crowding between size classes and canopy types.Key resultsWe found that soil and neighbours mainly acted separately in shaping tree growth in small and large trees. Soil total nitrogen and phosphorus increased tree growth in small trees, in particular of understorey species, but not in large trees. Neighbours reduced tree growth in both tree size classes, with stronger effects on large than small trees, and on canopy than understorey species. Furthermore, small trees with higher specific leaf area grew faster in fertile soils, and small trees with less seed mass grew faster in crowded environments. Large trees with higher specific leaf area, specific root length and less seed mass grew faster in crowded environments, while these traits had limited influence on tree growth response to soil gradients.ConclusionsOur study highlights the importance of size class in modulating the response of tree growth to soil and neighbours, and the differential role of species canopy types and functional traits in capturing these effects in large vs. small trees.
Ineffective integration of multiple anti-predator defenses in a rotifer: a low-cost insurance?
Authors: He Yuhan , Zhu Konghao , Zhao Kangshun , He Liang , Candolin Ulrika , Xu Jun , Zhang Huan 
Published: December 2022

Abstract
To maximize survival, prey often integrates multiple anti-predator defenses. How the defenses interact to reduce predation risk is, however, poorly known. We used the rotifer Brachionus calyciflorus to investigate how morphological (spines) and behavioral (floating) defenses are integrated against a common predatory rotifer, Asplanchna brightwellii, and if their combined use improves survival. To this end, we assessed the cost of the behavioral defense and the efficiency of both defenses, individually and combined, as well as their mutual dependency. The results show that the behavioral defense is costly in reducing foraging activity, and that the two defenses are used simultaneously, with the presence of the morphological defense enhancing the use of the behavioral defense, as does the pre-exposure to predator cues. However, while the morphological defense reduces predation risk, the behavioral defense does not, thus, adding the costly behavioral defense to the morphological defense does not improve survival. It is likely that the cost of the behavioral defense is low given its reversibility—compared to the cost of misidentifying the predator species—and that this has promoted the adoption of both defenses, as general low-cost insurance rather than as a tailored strategy toward specific predators. Thus, the optimal strategy in the rotifer appears to be to express both morphological and behavioral defenses when confronted with the cues of a potential predator.
Scaling neighbor joining to one million taxa with dynamic and heuristic neighbor joining
Authors: Clausen Philip T L C 
Published: December 2022

Abstract

Motivation
The neighbor-joining (NJ) algorithm is a widely used method to perform iterative clustering and forms the basis for phylogenetic reconstruction in several bioinformatic pipelines. Although NJ is considered to be a computationally efficient algorithm, it does not scale well for datasets exceeding several thousand taxa (&gt;100 000). Optimizations to the canonical NJ algorithm have been proposed; these optimizations are, however, achieved through approximations or extensive memory usage, which is not feasible for large datasets.

Results
In this article, two new algorithms, dynamic neighbor joining (DNJ) and heuristic neighbor joining (HNJ), are presented, which optimize the canonical NJ method to scale to millions of taxa without increasing the memory requirements. Both DNJ and HNJ outperform the current gold standard methods to construct NJ trees, while DNJ is guaranteed to produce exact NJ trees.

Availability and implementation
https://bitbucket.org/genomicepidemiology/ccphylo.git

Supplementary information
Supplementary data are available at Bioinformatics online.
Visual Omics: a web-based platform for omics data analysis and visualization with rich graph-tuning capabilities
Authors: Li Heng , Shi Mijuan , Ren Keyi , Zhang Lei , Ye Weidong , Zhang Wanting , Cheng Yingyin , Xia Xiao-Qin 
Published: December 2022

Abstract

Summary
With the continuous development of high-throughput sequencing technology, bioinformatic analysis of omics data plays an increasingly important role in life science research. Many R packages are widely used for omics analysis, such as DESeq2, clusterProfiler and STRINGdb. And some online tools based on them have been developed to free bench scientists from programming with these R packages. However, the charts generated by these tools are usually in a fixed, non-editable format and often fail to clearly demonstrate the details the researchers intend to express. To address these issues, we have created Visual Omics, an online tool for omics data analysis and scientific chart editing. Visual Omics integrates multiple omics analyses which include differential expression analysis, enrichment analysis, protein domain prediction and protein–protein interaction analysis with extensive graph presentations. It can also independently plot and customize basic charts that are involved in omics analysis, such as various PCA/PCoA plots, bar plots, box plots, heat maps, set intersection diagrams, bubble charts and volcano plots. A distinguishing feature of Visual Omics is that it allows users to perform one-stop omics data analyses without programming, iteratively explore the form and layout of graphs online and fine-tune parameters to generate charts that meet publication requirements.

Availability and implementation
Visual Omics can be used at http://bioinfo.ihb.ac.cn/visomics. Source code can be downloaded at http://bioinfo.ihb.ac.cn/software/visomics/visomics-1.1.tar.gz.

Supplementary information
Supplementary data are available at Bioinformatics online.
Dual-site transcranial direct current stimulation to treat tinnitus: a randomized controlled trial
Authors: Cardon Emilie , Jacquemin Laure , Vermeersch Hanne , Joossen Iris , Moyaert Julie , Mertens Griet , Vanderveken Olivier M , Lammers Marc J W , Van de Heyning Paul , Van Rompaey Vincent , Gilles Annick 
Published: December 2022

AbstractTranscranial direct current stimulation (tDCS) has been proposed as a potential intervention for subjective tinnitus, but supporting evidence remains limited. We aimed to investigate the effect of anodal high-definition tDCS of the left temporal area and right dorsolateral prefrontal cortex on tinnitus severity.This double-blind randomized controlled trial included 77 patients (age range 18–79, 43 male) with chronic subjective tinnitus as their primary complaint. Thirty-eight subjects received six consecutive sessions of dual-site sequential high-definition-tDCS with electrodes positioned over the left temporal area and right dorsolateral prefrontal cortex. Both areas were stimulated for 15 min per session, with total stimulation time amounting to 30 min. Thirty-nine subjects received sham stimulation. The primary outcome measure was the change in tinnitus severity, as evaluated by the Tinnitus Functional Index, from baseline to a follow-up visit at 8 ± 2 weeks after treatment completion. Secondary outcomes included changes in perceived tinnitus loudness, as measured with a visual analogue scale and a tinnitus matching procedure, as well as scores on the Hospital Anxiety and Depression Scale, and the Hyperacusis Questionnaire.No differences in Tinnitus Functional Index change scores were identified between the active treatment and sham control groups (linear regression: P = 0.86). The Tinnitus Functional Index scores decreased significantly over time in both groups (P = 0.0012), indicating the presence of a considerable placebo effect. These change scores were significantly influenced by sex (linear regression: P = 0.037) and baseline symptoms of anxiety (linear regression: P = 0.049) in both groups. In general, Tinnitus Functional Index scores decreased more profoundly in males and in subjects with a higher degree of anxiety at baseline. None of the included secondary measures differed significantly between experimental arms.Our results suggest that dual-site sequential high-definition-tDCS of the left temporal area and right dorsolateral prefrontal cortex does not alleviate tinnitus severity. Interestingly, in our study population, fluctuations in tinnitus severity were influenced by gender and concurrent mental condition. It is therefore important to take these factors into account when conducting or planning randomized controlled trials in tinnitus populations.
Case report: intravenous leiomyomatosis with intracaval and intracardiac growth
Authors: Kikuchi Daniel S , Goulbourne Clive A , Starbuck Kristen D , Fernandes Marcelo F 
Published: December 2022

Abstract

Background
Intravenous leiomyomatosis (IVL) is a rare, benign smooth muscle cell tumour that extends beyond the pelvis. These tumours grow within vascular channels and can progress to involve the heart and pulmonary vasculature.

Case Summary
A 44-year-old female initially presented to her primary care physician for subacute bloating. In the weeks leading up to her presentation, she was in good health. On admission, computed tomography (CT) imaging of the abdomen and pelvis was notable for a mixed solid and cystic mass arising from the fundal myometrium with invasion into the inferior vena cava (IVC). Transthoracic echocardiogram (TTE) was notable for mobile mass in the right atrium originating from the IVC. The mass was further evaluated by cardiac magnetic resonance (CMR) imaging before a multidisciplinary, single-staged thoracoabdominal resection was performed. The procedure was well tolerated, and the entire mass was successfully removed without complication. Subsequently, pathological analysis of the resected tumour revealed benign smooth muscle cells, confirming the diagnosis of IVL.

Discussion
Intravenous leiomyomatosis is a rare cause of right-sided cardiac tumours but should be considered in premenopausal females, even those with a prior history of hysterectomy. The clinical presentation of patients with IVL is varied and imaging including CMR, CT, and TTE to evaluate the tissue characteristics and source of the cardiac mass should be performed. Finally, while imaging revealing a freely mobile pelvic mass extending into the IVC and right heart chambers is strongly suggestive of IVL, definitive diagnosis requires pathological analysis of resected tissue.
What are the outcomes of dietary interventions in Heart Failure with preserved Ejection Fraction? A systematic review and meta-analysis
Authors: Forsyth Faye , Mulrennan Sandra , Burt Jenni , Hartley Peter , Kuhn Isla , Lin Helen , Mant Jonathan , Tan Sapphire , Zhang Roy , Deaton Christi 
Published: December 2022

Abstract

Aims
To determine the efficacy of dietary interventions in Heart Failure with preserved Ejection Fraction (HFpEF).

Method and results
Keyword searches were performed in five bibliographic databases to identify randomized or controlled studies of dietary interventions conducted in HFpEF or mixed heart failure (HF) samples published in the English language. Studies were appraised for bias and synthesized into seven categories based on the similarity of the intervention or targeted population. The quality of the body of evidence was assessed via the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. Twenty-five unique interventions were identified; 17 were considered for meta-analysis. Most studies were judged to be at high risk of bias. There was moderate-quality evidence that caloric restriction led to clinically meaningful improvements in blood pressure and body weight. There was moderate-quality evidence that carbohydrate restriction resulted in meaningful reductions in blood pressure. There was very low-quality evidence that protein supplementation improved blood pressure and body weight and moderate-quality evidence for clinically meaningful improvements in function.

Conclusions
While some types of dietary interventions appeared to deliver clinically meaningful change in critical outcomes; the study heterogeneity and overall quality of the evidence make it difficult to make firm recommendations. Greater transparency when reporting the nutritional composition of interventions would enhance the ability to pool studies.

Registration
PROSPERO CRD42019145388.
Ghat: an R package for identifying adaptive polygenic traits
Authors: Mahmoud Medhat , Tost Mila , Ha Ngoc-Thuy , Simianer Henner , Beissinger Timothy 
Published: December 2022

Abstract
Identifying selection on polygenic complex traits in crops and livestock is important for understanding evolution and helps prioritize important characteristics for breeding. Quantitative trait loci (QTL) that contribute to polygenic trait variation often exhibit small or infinitesimal effects. This hinders the ability to detect QTL-controlling polygenic traits because enormously high statistical power is needed for their detection. Recently, we circumvented this challenge by introducing a method to identify selection on complex traits by evaluating the relationship between genome-wide changes in allele frequency and estimates of effect size. The approach involves calculating a composite statistic across all markers that capture this relationship, followed by implementing a linkage disequilibrium-aware permutation test to evaluate if the observed pattern differs from that expected due to drift during evolution and population stratification. In this manuscript, we describe “Ghat,” an R package developed to implement this method to test for selection on polygenic traits. We demonstrate the package by applying it to test for polygenic selection on 15 published European wheat traits including yield, biomass, quality, morphological characteristics, and disease resistance traits. Moreover, we applied Ghat to different simulated populations with different breeding histories and genetic architectures. The results highlight the power of Ghat to identify selection on complex traits. The Ghat package is accessible on CRAN, the Comprehensive R Archival Network, and on GitHub.
Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet®, the National Patient-Centered Clinical Research Network
Authors: Marsolo Keith , Kiernan Daniel , Toh Sengwee , Phua Jasmin , Louzao Darcy , Haynes Kevin , Weiner Mark , Angulo Francisco , Bailey Charles , Bian Jiang , Fort Daniel , Grannis Shaun , Krishnamurthy Ashok Kumar , Nair Vinit , Rivera Pedro , Silverstein Jonathan , Zirkle Maryan , Carton Thomas 
Published: December 2022

AbstractObjectiveThis article describes the implementation of a privacy-preserving record linkage (PPRL) solution across PCORnet®, the National Patient-Centered Clinical Research Network.Material and MethodsUsing a PPRL solution from Datavant, we quantified the degree of patient overlap across the network and report a de-duplicated analysis of the demographic and clinical characteristics of the PCORnet population.ResultsThere were ∼170M patient records across the responding Network Partners, with ∼138M (81%) of those corresponding to a unique patient. 82.1% of patients were found in a single partner and 14.7% were in 2. The percentage overlap between Partners ranged between 0% and 80% with a median of 0%. Linking patients’ electronic health records with claims increased disease prevalence in every clinical characteristic, ranging between 63% and 173%.DiscussionThe overlap between Partners was variable and depended on timeframe. However, patient data linkage changed the prevalence profile of the PCORnet patient population.ConclusionsThis project was one of the largest linkage efforts of its kind and demonstrates the potential value of record linkage. Linkage between Partners may be most useful in cases where there is geographic proximity between Partners, an expectation that potential linkage Partners will be able to fill gaps in data, or a longer study timeframe.
Evaluating resources composing the PheMAP knowledge base to enhance high-throughput phenotyping
Authors: Wan Nicholas C , Yaqoob Ali A , Ong Henry H , Zhao Juan , Wei Wei-Qi 
Published: December 2022

AbstractObjectiveA previous study, PheMAP, combined independent, online resources to enable high-throughput phenotyping (HTP) using electronic health records (EHRs). However, online resources offer distinct quality descriptions of diseases which may affect phenotyping performance. We aimed to evaluate the phenotyping performance of single resource-based PheMAPs and investigate an optimized strategy for HTP.Materials and MethodsWe compared how each resource produced top-ranked concept unique identifiers (CUIs) by term frequency—inverse document frequency with Jaccard matrices comparing single resources and the original PheMAP. We correlated top-ranked concepts from each resource to features used in established Phenotype KnowledgeBase (PheKB) algorithms for hypothyroidism, type II diabetes mellitus (T2DM), and dementias. Using resources separately, we calculated multiple phenotype risk scores for individuals from Vanderbilt University Medical Center’s BioVU DNA Biobank and compared phenotyping performance against rule-based eMERGE algorithms. Lastly, we implemented an ensemble strategy which classified patient case/control status based upon PheMAP resource agreement.ResultsJaccard similarity matrices indicate that the similarity of CUIs comprising single resource-based PheMAPs varies. Single resource-based PheMAPs generated from MedlinePlus and MedicineNet outperformed others but only encompass 81.6% of overall disease phenotypes. We propose the PheMAP-Ensemble which provides higher average accuracy and precision than the combined average accuracy and precision of single resource-based PheMAPs. While offering complete phenotype coverage, PheMAP-Ensemble significantly increases phenotyping recall compared to the original iteration.ConclusionsResources comprising the PheMAP produce different phenotyping performance when implemented individually. The ensemble method significantly improves the quality of PheMAP by fully utilizing dissimilar resources to capture accurate phenotyping data from EHRs.