bluuebunny/crossref_metadata_2025_split huggingface dataset:
GEANT4 simulation of a range verification method using delayed γ spectroscopy of a 92Mo marker
Authors: Kasanda E , Burbadge C , Bildstein V , Turko J , Spyrou A , Höhr C , Mücher D 
Published: September 2020

Abstract
In this work, we propose a novel technique for in-vivo proton therapy range verification. This technique makes use of a molybdenum hadron tumour marker, implanted at a short distance from the clinical treatment volume. Signals emitted from the marker during treatment can provide a direct measurement of the proton beam energy at the marker’s position. Fusion-evaporation reactions between the proton beam and marker nucleus result in the emission of delayed characteristic γ rays, which are detected off-beam for an improved signal-to-noise ratio. In order to determine the viability of this technique and to establish an experimental setup for future work, the Monte Carlo package GEANT4 was used in combination with ROOT to simulate a treatment scenario with the new method outlined in this work. These simulations show that the intensity of delayed γ rays produced from competing reactions yields a precise measurement of the range of the proton beam relative to the marker, with sub-millimetre uncertainty.
Scattering proton CT
Authors: Krah N , Quiñones C T , Létang J M , Rit S 
Published: September 2020

Abstract
Proton computed tomography (CT) is an imaging modality investigated mainly in the context of proton therapy as a complement to x-ray CT. It uses protons with high enough energy to fully traverse the imaged object. Common prototype systems measure each proton’s position and direction upstream and downstream of the object as well as the energy loss which can be converted into the water equivalent thickness. A reconstruction algorithm then produces a map of the relative stopping power in the object. As an alternative to energy-loss proton CT, it has been proposed to reconstruct a map of the object’s scattering power based on the protons’ angular dispersion which can be estimated from the measured directions. As in energy-loss proton CT, reconstruction should best be performed considering the non-linear shape of proton trajectories due to multiple Coulomb scattering (MCS), but no algorithm to achieve this is so far available in the literature.
In this work, we propose a filtered backprojection algorithm with distance-driven binning to account for the protons’ most likely path. Furthermore, we present a systematic study of scattering proton CT in terms of inherent noise and spatial resolution and study the artefacts which arise from the physics of MCS. Our analysis is partly based on analytical models and partly on Monte Carlo simulations.
Our results show that the proposed algorithm performs well in reconstructing relative scattering power maps, i.e. scattering power relative to that of water. Spatial resolution is improved by almost a factor of three compared to straight line projection and is comparable to energy-loss proton CT. Image noise, on the other hand, is inherently much higher. For example, in a water cylinder of 20 cm diameter, representative of a human head, noise in the central image pixel is about 40 times higher in scattering proton CT than in energy-loss proton CT. Relative scattering power in dense regions such as bone inserts is systematically underestimated by a few percent, depending on beam energy and phantom geometry.
Interfacial viscoelasticity and jamming of colloidal particles at fluid–fluid interfaces: a review
Authors: Ji Xiaoliang , Wang Xiaolu , Zhang Yongjian , Zang Duyang 
Published: September 2020

Abstract
Colloidal particles can be adsorbed at fluid–fluid interfaces, a phenomenon frequently observed in particle-stabilized foams, Pickering emulsions, and bijels. Particles adsorbed at interfaces exhibit unique physical and chemical behaviors, which affect the mechanical properties of the interface. Therefore, interfacial colloidal particles are of interest in terms of both fundamental and applied research. In this paper, we review studies on the adsorption of colloidal particles at fluid–fluid interfaces, from both thermodynamic and mechanical points of view, and discuss the differences as compared with surfactants and polymers. The unique particle interactions induced by the interfaces as well as the particle dynamics including lateral diffusion and contact line relaxation will be presented. We focus on the rearrangement of the particles and the resultant interfacial viscoelasticity. Particular emphasis will be given to the effects of particle shape, size, and surface hydrophobicity on the interfacial particle assembly and the mechanical properties of the obtained particle layer. We will also summarize recent advances in interfacial jamming behavior caused by adsorption of particles at interfaces. The buckling and cracking behavior of particle layers will be discussed from a mechanical perspective. Finally, we suggest several potential directions for future research in this area.
Resilience to climate shocks in the tropics
Authors: Hirons Mark , Beauchamp Emilie , Whitfield Stephen , Conway Declan , Asare Rebecca , Malhi Yadvinder 
Published: September 2020

Abstract
This focus collection on resilience to climate shocks in the tropics draws together 16 papers that predominantly examine the impacts of, and responses to, the 2015/2016 El Niño-Southern Oscillation event, in a range of contexts. This introductory synthesis contextualises the collection of papers by reviewing important concepts and highlighting some important insights that emerge from the collection. The papers in this collection collectively highlight: the value of longitudinal and interdisciplinary research in understanding both the roots of, and responses to, resilience challenges; the critical interaction between climatic and land-use changes; and the ways in which governance arrangements underpin societal decision-making across a range of scales and contexts to shape resilience.
Machine learning for aquatic plastic litter detection, classification and quantification (APLASTIC-Q)
Authors: Wolf Mattis , van den Berg Katelijn , Garaba Shungudzemwoyo P , Gnann Nina , Sattler Klaus , Stahl Frederic , Zielinski Oliver 
Published: September 2020

Abstract
Large quantities of mismanaged plastic waste are polluting and threatening the health of the blue planet. As such, vast amounts of this plastic waste found in the oceans originates from land. It finds its way to the open ocean through rivers, waterways and estuarine systems. Here we present a novel machine learning algorithm based on convolutional neural networks (CNNs) that is capable of detecting and quantifying floating and washed ashore plastic litter. The aquatic plastic litter detection, classification and quantification system (APLASTIC-Q) was developed and trained using very high geo-spatial resolution imagery (∼5 pixels cm−1 = 0.002 m pixel−1) captured from aerial surveys in Cambodia. APLASTIC-Q was made up of two machine learning components (i) plastic litter detector (PLD-CNN) and (ii) plastic litter quantifier (PLQ-CNN). PLD-CNN managed to categorize targets as water, sand, vegetation and plastic litter with an 83% accuracy. It also provided a qualitative count of litter as low or high based on a thresholding approach. PLQ-CNN further distinguished and enumerated the litter items in each of the classes defined as water bottles, Styrofoam, canisters, cartons, bowls, shoes, polystyrene packaging, cups, textile, carry bags small or large. The types and amounts of plastic litter provide benchmark information that is urgently needed for decision-making by policymakers, citizens and other public and private stakeholders. Quasi-quantification was based on automated counts of items present in the imagery with caveats of underlying object in case of aggregated litter. Our scientific evidence-based machine learning algorithm has the prospects of complementing net trawl surveys, field campaigns and clean-up activities for improved quantification of plastic litter. APLASTIC-Q is a smart algorithm that is easy to adapt for fast and automated detection as well as quantification of floating or washed ashore plastic litter from aerial, high-altitude pseudo satellites and space missions.
Generating directed networks with prescribed Laplacian spectra
Authors: Nicoletti Sara , Carletti Timoteo , Fanelli Duccio , Battistelli Giorgio , Chisci Luigi 
Published: September 2020

Abstract
Complex real-world phenomena are often modeled as dynamical systems on networks. In many cases of interest, the spectrum of the underlying graph Laplacian sets the system stability and ultimately shapes the matter or information flow. This motivates devising suitable strategies, with rigorous mathematical foundation, to generate Laplacians that possess prescribed spectra. In this paper, we show that a weighted Laplacian can be constructed so as to exactly realize a desired complex spectrum. The method configures as a non trivial generalization of existing recipes which assume the spectra to be real. Applications of the proposed technique to (i) a network of Stuart–Landau oscillators and (ii) to the Kuramoto model are discussed. Synchronization can be enforced by assuming a properly engineered, signed and weighted, adjacency matrix to rule the pattern of pairing interactions.
Detecting symmetries with neural networks
Authors: Krippendorf Sven , Syvaeri Marc 
Published: September 2020

Abstract
Identifying symmetries in data sets is generally difficult, but knowledge about them is crucial for efficient data handling. Here we present a method how neural networks can be used to identify symmetries. We make extensive use of the structure in the embedding layer of the neural network which allows us to identify whether a symmetry is present and to identify orbits of the symmetry in the input. To determine which continuous or discrete symmetry group is present we analyse the invariant orbits in the input. We present examples based on rotation groups SO(n) and the unitary group SU(2). Further we find that this method is useful for the classification of complete intersection Calabi-Yau manifolds where it is crucial to identify discrete symmetries on the input space. For this example we present a novel data representation in terms of graphs.
ELSA 2018 Cohort: Protective Behavioral Strategies as Mediators of the Relationship between Risk Factors and Alcohol Outcomes in Argentinean College Freshmen
Authors: Pilatti Angelina , Bravo Adrian J , Michelini Yanina , Pautassi Ricardo Marcos 
Published: September 2020

Abstract

Aims
The present study examined which types of alcohol protective behavioral strategies ([PBSs], Manner of Drinking [MOD] strategies, Serious Harm Reduction [SHR] or Limiting/Stopping Drinking strategies [LSD]) mediate the effects of a comprehensive number of distal antecedents on alcohol drinking quantity and alcohol-related negative consequences.

Methods
A sample of 762 last-month college freshman drinkers from Argentina (Mean age = 19.60 ± 3.80) completed a survey that assessed alcohol outcomes (drinking quantity during a typical week and alcohol-related negative consequences), frequency of use of PBS and a set of distal antecedents (i.e. age at drinking onset, drinking motives, college alcohol beliefs and impulsivity-like traits).

Results
MOD significantly mediated the effects of college alcohol beliefs (higher beliefs were associated with lower MOD use) and coping motives (higher coping motives were associated with lower MOD use) on alcohol outcomes. SHR significantly mediated the effects of sex (women reported more frequent SHR use) and enhancement motives (higher motivation was associated with lower SHR use) on alcohol-related negative consequences.

Conclusion
Our findings partially support a mediational role of PBS in the association between risk factors and alcohol outcomes, and offer valuable information for the design of interventions to reduce alcohol use in South-American college students. More studies examining PBS as mediators of distal antecedents are needed to fully understand the peculiarities of these associations in different cultures.
PhyloWGA: chromosome-aware phylogenetic interrogation of whole genome alignments
Authors: Adams Richard H , Castoe Todd A , DeGiorgio Michael 
Published: September 2020

Abstract

Summary
Here, we present PhyloWGA, an open source R package for conducting phylogenetic analysis and investigation of whole genome data.

Availabilityand implementation
Available at Github (https://github.com/radamsRHA/PhyloWGA).

Supplementary information
Supplementary data are available at Bioinformatics online.
Genetic source completeness of HIV-1 circulating recombinant forms (CRFs) predicted by multi-label learning
Authors: Tang Runbin , Yu Zuguo , Ma Yuanlin , Wu Yaoqun , Phoebe Chen Yi-Ping , Wong Limsoon , Li Jinyan 
Published: September 2020

Abstract

Motivation
Infection with strains of different subtypes and the subsequent crossover reading between the two strands of genomic RNAs by host cells’ reverse transcriptase are the main causes of the vast HIV-1 sequence diversity. Such inter-subtype genomic recombinants can become circulating recombinant forms (CRFs) after widespread transmissions in a population. Complete prediction of all the subtype sources of a CRF strain is a complicated machine learning problem. It is also difficult to understand whether a strain is an emerging new subtype and if so, how to accurately identify the new components of the genetic source.

Results
We introduce a multi-label learning algorithm for the complete prediction of multiple sources of a CRF sequence as well as the prediction of its chronological number. The prediction is strengthened by a voting of various multi-label learning methods to avoid biased decisions. In our steps, frequency and position features of the sequences are both extracted to capture signature patterns of pure subtypes and CRFs. The method was applied to 7185 HIV-1 sequences, comprising 5530 pure subtype sequences and 1655 CRF sequences. Results have demonstrated that the method can achieve very high accuracy (reaching 99%) in the prediction of the complete set of labels of HIV-1 recombinant forms. A few wrong predictions are actually incomplete predictions, very close to the complete set of genuine labels.

Availability and implementation
https://github.com/Runbin-tang/The-source-of-HIV-CRFs-prediction.

Supplementary information
Supplementary data are available at Bioinformatics online.
Hippocampal and Parahippocampal Gray Matter Structural Integrity Assessed by Multimodal Imaging Is Associated with Episodic Memory in Old Age
Authors: Köhncke Ylva , Düzel Sandra , Sander Myriam C , Lindenberger Ulman , Kühn Simone , Brandmaier Andreas M 
Published: September 2020

Abstract
Maintained structural integrity of hippocampal and cortical gray matter may explain why some older adults show rather preserved episodic memory. However, viable measurement models for estimating individual differences in gray matter structural integrity are lacking; instead, findings rely on fallible single indicators of integrity. Here, we introduce multitrait–multimethod methodology to capture individual differences in gray matter integrity, based on multimodal structural imaging in a large sample of 1522 healthy adults aged 60–88 years from the Berlin Aging Study II, including 333 participants who underwent magnetic resonance imaging. Structural integrity factors expressed the common variance of voxel-based morphometry, mean diffusivity, and magnetization transfer ratio for each of four regions of interest: hippocampus, parahippocampal gyrus, prefrontal cortex, and precuneus. Except for precuneus, the integrity factors correlated with episodic memory. Associations with hippocampal and parahippocampal integrity persisted after controlling for age, sex, and education. Our results support the proposition that episodic memory ability in old age benefits from maintained structural integrity of hippocampus and parahippocampal gyrus. Exploratory follow-up analyses on sex differences showed that this effect is restricted to men. Multimodal factors of structural brain integrity might help to improve our biological understanding of human memory aging.
Genotypic Resistance of Pyrazinamide but Not Minimum Inhibitory Concentration Is Associated With Longer Time to Sputum Culture Conversion in Patients With Multidrug-resistant Tuberculosis
Authors: Kuhlin Johanna , Davies Forsman Lina , Mansjö Mikael , Jonsson Nordvall Michaela , Wijkander Maria , Wagrell Charlotta , Jonsson Jerker , Groenheit Ramona , Werngren Jim , Schön Thomas , Bruchfeld Judith 
Published: September 2020

Abstract

Background
Pyrazinamide (PZA) resistance in multidrug-resistant tuberculosis (MDR-TB) is common; yet, it is not clear how it affects interim and treatment outcomes. Although rarely performed, phenotypic drug susceptibility testing (pDST) is used to define PZA resistance, but genotypic DST (gDST) and minimum inhibitory concentration (MIC) could be beneficial. We aimed to assess the impact of PZA gDST and MIC on time to sputum culture conversion (SCC) and treatment outcome in patients with MDR-TB.

Methods
Clinical, microbiological, and treatment data were collected in this cohort study for all patients diagnosed with MDR-TB in Sweden from 1992–2014. MIC, pDST, and whole-genome sequencing of the pncA, rpsA, and panD genes were used to define PZA resistance. A Cox regression model was used for statistical analyses.

Results
Of 157 patients with MDR-TB, 56.1% (n = 88) had PZA-resistant strains and 49.7% (n = 78) were treated with PZA. In crude and adjusted analysis (hazard ratio [HR], 0.49; 95% conficence interval [CI], .29-.82; P = .007), PZA gDST resistance was associated with a 29-day longer time to SCC. A 2-fold decrease in dilutions of PZA MIC for PZA-susceptible strains showed no association with SCC in crude or adjusted analyses (HR, 0.98; 95% CI, .73–1.31; P = .89). MIC and gDST for PZA were not associated with treatment outcome.

Conclusions
In patients with MDR-TB, gDST PZA resistance was associated with a longer time to SCC. Rapid PZA gDST is important to identify patients who may benefit from PZA treatment.
#Crohn’s: Historical Cohort of Twitter Activity
Authors: Facanali Marcio Roberto , Bortolozzo Graciolli Facanali Carolina , Queiroz Natália Sousa Freitas , Sobrado Carlos Walter , Nahas Sérgio Carlos , Safatle-Ribeiro Adriana Vaz 
Published: September 2020

AbstractBackgroundAnalysis of the Twitter activity on #Crohn’s, identifying individuals with interest in Crohn’s disease on Twitter.MethodsA historic cohort study was conducted about Twitter activity evaluation of #Crohn’s analyzed over a period of 9 years. For the Twitter analysis, a health-care social media analytics tool, Symplur Signals, was adopted.ResultsFrom 2011 until 2019, 627,000 tweets of #Crohn’s were detected, with 276,380 retweets by 109,937 users; of these users, 32.4% were patient advocates and 12.6% were doctors. There was a pattern of annual peak activity of the #Crohn’s, mainly in May and December, and less activity, usually in July. Of all tweets, 52.5% were categorized as positive and 47.5% as negative.ConclusionsSocial media, especially Twitter, represents an important information tool, but it is still underutilized by gastroenterologists. This study suggests a significant interference of international awareness campaigns about inflammatory bowel disease in the activity of #Crohn’s on Twitter, denoting an increase in debating this topic on the platform. Discussions on the subject by health professionals are still below expectations regarding the importance of the theme.
Evolutionary medical insights into the SARS-CoV-2 pandemic
Authors: Crespi Bernard 
Published: September 2020

AbstractThe author apply concepts and tools from evolutionary medicine to understanding the SARS-CoV-2 pandemic. The pandemic represents a mismatched conflict, with dynamics and pathology apparently driven by three main factors: (i) bat immune systems that rely on low inflammation but high efficacy of interferon-based defenses; (ii) viral tactics that differentially target the human interferon system, leading to substantial asymptomatic and pre-symptomatic transmission; and (ii) high mortality caused by hyper-inflammatory and hyper-coagulatory phenotypes, that represent dysregulated tradeoffs whereby collateral immune-induced damage becomes systemic and severe. This framework can explain the association of mortality with age (which involves immune life-history shifts towards higher inflammation and coagulation and reduced adaptive immunity), and sex (since males senesce faster than females). Genetic-risk factors for COVID-19 mortality can be shown, from a phenome-wide association analysis of the relevant SNPs, to be associated with inflammation and coagulation; the phenome-wide association study also provides evidence, consistent with several previous studies, that the calcium channel blocking drug amlodipine mediates risk of mortality.Lay Summary: SARS-CoV-2 is a bat virus that jumped into humans. The virus is adapted to bat immune systems, where it evolved to suppress the immune defenses (interferons) that mammals use to tell that they are infected. In humans, the virus can apparently spread effectively in the body with a delay in the production of symptoms and the initiation of immune responses. This delay may then promote overactive immune responses, when the virus is detected, that damage the body as a side effect. Older people are more vulnerable to the virus because they are less adapted to novel infectious agents, and invest less in immune defense, compared to younger people. Genes that increase risk of mortality from SARS-CoV-2 are functionally associated with a drug called amlodipine, which may represent a useful treatment.
Social Engagement and Cognitive Function of Older Adults in Mexico and the United States: How Universal Is the Interdependence in Couples?
Authors: Howrey Bret , Avila Jaqueline C , Downer Brian , Wong Rebeca 
Published: September 2020

Abstract

Objectives
Increased social engagement in older adults has been linked to positive cognitive outcomes; however, it is unclear if the social engagement of husbands and wives influences their own cognition as well as each other’s cognition. Moreover, it is unknown if any such patterns persist in different country contexts.

Methods
Data from the 2001 Mexican Health and Aging Study (MHAS) and the 2000 Health and Retirement Study (HRS) were combined, and comparable samples of married couples without cognitive impairment at baseline were drawn. Follow-up cognition data was obtained from the 2012 MHAS and the 2012 HRS. Structural equation models (SEM) were used to test the actor–partner interdependence model with moderating effect of country on the association of social engagement with cognition.

Results
Significant actor effects were observed for wives in both countries. Actor effects for husbands were observed in the United States only. In Mexico, a significant partner effect was observed where wives’ social engagement benefited their own cognition as well as their husbands’, but not vice versa. Partner effects were not observed in the United States. No moderation effects of country were observed.

Discussion
Our results suggest asymmetric patterns of actor–partner interdependence in Mexico, which may be reflective of the more traditional social role of women, and codependence within the couple. On the other hand, our results for the United States, where each spouse had significant actor effects but no partner effects, may suggest more independence within the couple.