bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tropical friezes and the index in higher homological algebra
Authors: JØRGENSEN PETER 
Published: March 2020

AbstractCluster categories and cluster algebras encode two dimensional structures. For instance, the Auslander–Reiten quiver of a cluster category can be drawn on a surface, and there is a class of cluster algebras determined by surfaces with marked points.Cluster characters are maps from cluster categories (and more general triangulated categories) to cluster algebras. They have a tropical shadow in the form of so-called tropical friezes, which are maps from cluster categories (and more general triangulated categories) to the integers.This paper will define higher dimensional tropical friezes. One of the motivations is the higher dimensional cluster categories of Oppermann and Thomas, which encode (d + 1)-dimensional structures for an integer d ⩾ 1. They are (d + 2)-angulated categories, which belong to the subject of higher homological algebra.We will define higher dimensional tropical friezes as maps from higher cluster categories (and more general (d + 2)-angulated categories) to the integers. Following Palu, we will define a notion of (d + 2)-angulated index, establish some of its properties, and use it to construct higher dimensional tropical friezes.
Assessing the effects of different management scenarios on the conservation of small island vulture populations
Authors: ARESU MAURO , ROTTA ANDREA , FOZZI ALBERTO , CAMPUS ALFONSO , MUZZEDDU MARCO , SECCI DIONIGI , FOZZI ILARIA , DE ROSA DAVIDE , BERLINGUER FIAMMETTA 
Published: March 2020

SummaryAlthough the population of Griffon VultureGyps fulvusis significantly increasing in Europe, in Italy the species is still on the Red List as ‘Critically Endangered’, with the last natural population persisting on the island of Sardinia. Several episodes of poisoning hampered the success of conservation actions implemented in the years 1987–1995. In 2005 there were estimated to be only 31–32 territorial pairs, with the population occupying the territories of Alghero and Bosa. We used a long-term dataset of reproductive records from the Sardinian Griffon Vulture populations to run a population viability analysis (PVA) to evaluate the extinction risk using the Vortex simulation software. The model estimated the probability of extinction over the next five generations (estimated generation time: 11 years, simulation time used: 55 years) as 96.4% for the Alghero population, and near-zero for the Bosa population. We used sensitivity analyses to understand how uncertainty about parameter values affect model outcomes. Population projections were evaluated under different management scenarios tackling the main threats (poisoning and human disturbance) and implementing conservation actions (supplementary feeding and restocking). Our results showed that population size is a critical factor in affecting the projections of population dynamics of Griffon Vultures. Sensitivity analyses highlighted the importance of poisoning events to population persistence and showed that juvenile and adult mortality rates had a secondary impact on population viability. The only conservation measure effective in significantly increasing stochastic growth rates in the Alghero population, whose initial population was set at five individuals, was the complete removal of poisoning events. When targeting the Bosa population (initial population size 94 individuals), supplementary feeding, mitigation of the risk of poisoning episodes, restocking, and mitigation of human disturbance in the reproductive sites significantly increased stochastic growth rate. A cost-effectiveness analysis should be performed to prioritise interventions.
Witness algebra and anyon braiding
Authors: Blass Andreas , Gurevich Yuri 
Published: March 2020

AbstractTopological quantum computation employs two-dimensional quasiparticles called anyons. The generally accepted mathematical basis for the theory of anyons is the framework of modular tensor categories. That framework involves a substantial amount of category theory and is, as a result, considered rather difficult to understand. Is the complexity of the present framework necessary? The computations of associativity and braiding matrices can be based on a much simpler framework, which looks less like category theory and more like familiar algebra. We introduce that framework here.
Is the proton–boron fusion therapy effective?
Authors: Khaledi Navid , Wang Xufei , Hosseinabadi Roghiye B. , Samiei Farhad 
Published: March 2020

AbstractIntroduction:In the recent years, some publications (mainly from one group of authors) have dealt with the effectiveness of proton–boron fusion therapy (PBFT). This theory is based on the Q-value of three produced α particles in the reaction of protons with boron (11B). They claim that this reaction significantly increases the absorbed dose in the target volume. However, the current study would re-evaluate their method to show if PBFT is really effective.Methods and materials:A parallel 80-MeV proton beam was irradiated on a water medium in a cubic boron uptake region (BUR). The two-dimensional dose distribution and percentage depth dose of protons, alphas and all particles were calculated using tally F6 and mesh-tallies by Monte Carlo N Particle Transport code.Results:The results not only showed that the dose enhancement in BUR is neglectable but also the higher density of BUR in comparison with water led to decrement of dose in this region. Because of low cross section of boron for proton beam (<100 mb), the α particles’ dose is 1,000 times lower than the proton dose.Conclusions:The physical aspects and the simulation results did not show any effectiveness of the PBFT for proton therapy dose enhancement.
Direct Determination of a Bare Neutron Counter Yield Function
Authors: Nuntiyakul W. , Mangeard P.‐S. , Ruffolo D. , Evenson P. , Bieber J. W. , Clem J. , Hallgren A. , Madsen J. , Pyle R. , Sáiz A. , Tilav S. 
Published: March 2020

AbstractGround‐based neutron counters are a standard tool for detecting atmospheric showers from GeV range primary cosmic rays of either solar or galactic origin. Bare neutron counters, a type of lead‐free neutron monitor, function much like standard neutron monitors but have different yield functions primarily because they are more sensitive to neutrons of lower energy. When operated together with standard monitors, the different yield functions allow estimates to be made of the energy spectrum of galactic or solar particles. In 2010 a new array of 12 bare neutron detectors was installed at the South Pole to operate together with the neutron monitor there. Prior to installation, two of the detectors were operated on a ship that traveled from Sweden to Antarctica and back from November 2009 to April 2010. The purpose of this latitude survey was to use Earth's magnetic field as a spectrometer, blocking cosmic rays below the local cutoff rigidity (momentum per unit charge), from which we determined the response function versus rigidity of these bare counters. By comparing that measured response function to direct measurements of the cosmic ray spectrum taken by the PAMELA spacecraft, we were able to make a direct determination of the yield function for these detectors.
The Influence of Carbonate Platforms on the Geomorphological Development of a Mixed Carbonate‐Siliciclastic Margin (Great Barrier Reef, Australia)
Authors: Thran Amanda C. , East Madison , Webster Jody M. , Salles Tristan , Petit Carole 
Published: March 2020

AbstractSedimentation regimes on the Great Barrier Reef margin often do not conform to more conventional sequence stratigraphic models, presenting difficulties when attempting to identify key processes that control the margin's geomorphological evolution. By obstructing and modifying down‐shelf and down‐slope flows, carbonate platforms are thought to play a central role in altering the distribution and morphological presentation of common margin features. Using numerical simulations, we test the role of the carbonate platforms in reproducing several features (i.e., paleochannels, shelf‐confined fluvial sediment mounds, shelf‐edge deltas, canyons, and surface gravity flows) that have been described from observational data (seismic sections, multibeam bathymetry, sediment cores, and backscatter imagery). When carbonate platforms are present in model simulations, several notable geomorphological features appear, especially during lowstand. Upon exposure of the shelf, platforms reduce stream power, promoting mounding of fluvial sediments around platforms. On the outer shelf, rivers and streams are re‐routed and coalesce between platforms, depositing shelf‐edge deltas and incising paleochannels through knickpoint retreat. Additionally, steep platform topography triggers incision of slope canyons through turbidity currents, and platforms act as conduits for the localized delivery of land and shelf‐derived sediments to the continental slope and basin. When platforms are absent from the topographic surface, the model is unable to reproduce many of these features. Instead, a more typical “reciprocal‐type” sedimentation regime arises. Our results demonstrate the essential role of carbonate platform topography in modulating key bedload processes. Therefore, they exert direct control on the development of various geomorphological features within the shelf, slope, and basin environments.
Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2
Authors: Zhou Yadi , Hou Yuan , Shen Jiayu , Huang Yin , Martin William , Cheng Feixiong 
Published: March 2020

AbstractHuman coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV–host interactome and drug targets in the human protein–protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV–host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the “Complementary Exposure” pattern: the targets of the drugs both hit the HCoV–host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.
Framework for atomic-level characterisation of quantum computer arrays by machine learning
Authors: Usman Muhammad , Wong Yi Zheng , Hill Charles D. , Hollenberg Lloyd C. L. 
Published: March 2020

AbstractAtomic-level qubits in silicon are attractive candidates for large-scale quantum computing; however, their quantum properties and controllability are sensitive to details such as the number of donor atoms comprising a qubit and their precise location. This work combines machine learning techniques with million-atom simulations of scanning tunnelling microscopic (STM) images of dopants to formulate a theoretical framework capable of determining the number of dopants at a particular qubit location and their positions with exact lattice site precision. A convolutional neural network (CNN) was trained on 100,000 simulated STM images, acquiring a characterisation fidelity (number and absolute donor positions) of >98% over a set of 17,600 test images including planar and blurring noise commensurate with experimental measurements. The formalism is based on a systematic symmetry analysis and feature-detection processing of the STM images to optimise the computational efficiency. The technique is demonstrated for qubits formed by single and pairs of closely spaced donor atoms, with the potential to generalise it for larger donor clusters. The method established here will enable a high-precision post-fabrication characterisation of dopant qubits in silicon, with high-throughput potentially alleviating the requirements on the level of resources required for quantum-based characterisation, which will otherwise be a challenge in the context of large qubit arrays for universal quantum computing.
MHD surrogate model for convection in electromagnetically levitated molten metal droplets processed using the ISS-EML facility
Authors: Baker Evan B. , Nawer Jannatun , Xiao Xiao , Matson Douglas M. 
Published: March 2020

AbstractElectromagnetic levitation experiments in space are an essential tool for thermophysical property measurement and solidification studies. In light of the need for material properties as inputs to industrial process modeling, investigators need new tools for efficient experiment planning. MHD surrogate modeling is a parametric method for prediction of flow conditions during processing using the ISS-EML facility. Flow conditions in model Au, Zr, and Ti39.5Zr39.5Ni21 samples are predicted using the surrogate model. For Au, flow is shown be turbulent in nearly all experimental conditions, making property measurement difficult. For Zr, the flow is turbulent with the heater on and laminar with the heater off, allowing for property measurement during free-cooling experiments only. For TiZrNi, the flow is laminar under all experimental conditions, indicating that TiZrNi is an excellent candidate for EML experiments. This surrogate modeling approach can be easily applied to other materials of interest, enabling investigators to choose materials that will perform well in levitation and to tailor experiment parameters to achieve desirable flow conditions.
Artificial Intelligence based Models for Screening of Hematologic Malignancies using Cell Population Data
Authors: Syed-Abdul Shabbir , Firdani Rianda-Putra , Chung Hee-Jung , Uddin Mohy , Hur Mina , Park Jae Hyeon , Kim Hyung Woo , Gradišek Anton , Dovgan Erik 
Published: March 2020

AbstractCell Population Data (CPD) provides various blood cell parameters that can be used for differential diagnosis. Data analytics using Machine Learning (ML) have been playing a pivotal role in revolutionizing medical diagnostics. This research presents a novel approach of using ML algorithms for screening hematologic malignancies using CPD. The data collection was done at Konkuk University Medical Center, Seoul. A total of (882 cases: 457 hematologic malignancy and 425 hematologic non-malignancy) were used for analysis. In our study, seven machine learning models, i.e., SGD, SVM, RF, DT, Linear model, Logistic regression, and ANN, were used. In order to measure the performance of our ML models, stratified 10-fold cross validation was performed, and metrics, such as accuracy, precision, recall, and AUC were used. We observed outstanding performance by the ANN model as compared to other ML models. The diagnostic ability of ANN achieved the highest accuracy, precision, recall, and AUC ± Standard Deviation as follows: 82.8%, 82.8%, 84.9%, and 93.5% ± 2.6 respectively. ANN algorithm based on CPD appeared to be an efficient aid for clinical laboratory screening of hematologic malignancies. Our results encourage further work of applying ML to wider field of clinical practice.
Patterns of genetic diversity in North Africa: Moroccan-Algerian genetic split in Juniperus thurifera subsp. africana
Authors: Taib Asma , Morsli Abdelkader , Chojnacka Aleksandra , Walas Łukasz , Sękiewicz Katarzyna , Boratyński Adam , Romo Àngel , Dering Monika 
Published: March 2020

AbstractJuniperus thurifera is a key element of the forest communities in arid and semi-arid areas of the western Mediterranean. Previous genetic and morphological investigations suggested that Algerian populations are genetically more similar to European than to Moroccan populations and advocated their recognition at the variety rank. We aimed to investigate the spatial genetic structure in J. thurifera to verify the distinct character of the Algerian population in terms of the genetic breaks reported among several North African taxa. We also modelled species distributions since the Eemian to recognise the impact of past climatic changes on the current pattern of diversity and predict possible changes in species distribution in the future. Species-specific microsatellites were used in the analysis of 11 populations from Algeria, Morocco and Europe. We revealed the significant genetic distinctiveness of the Algerian populations from the Moroccan and European stands that may have important taxonomic and conservation implications. The diversity pattern revealed for J. thurifera reflects the east-west genetic splits reported among some North African plant and animal taxa and suggests an impact of shared historical processes. Additionally, modelling of the distribution allowed us to identify possible glacial refugia and their impact on the modern pattern of differentiation in J. thurifera. Reduction of species occurrence, especially in the European domain, is likely according to the future projections of the species distribution.
Earliest African evidence of carcass processing and consumption in cave at 700 ka, Casablanca, Morocco
Authors: Daujeard Camille , Falguères Christophe , Shao Qingfeng , Geraads Denis , Hublin Jean-Jacques , Lefèvre David , Graoui Mohssine El , Rué Mathieu , Gallotti Rosalia , Delvigne Vincent , Queffelec Alain , Arous Eslem Ben , Tombret Olivier , Mohib Abderrahim , Raynal Jean-Paul 
Published: March 2020

AbstractTo date, in Africa, evidence for animal processing and consumption in caves routinely used as living spaces is only documented in the late Middle Pleistocene of the North and South of the continent and postdates the Middle Pleistocene in East Africa. Here we report the earliest evidence in a North-African cave (Grotte des Rhinocéros at Casablanca, Morocco) of cut, percussion and human gnawing marks on faunal remains directly associated with lithic knapping activities in the same space and in a well-documented stratified context. Ages for this Acheulean site are provided by the dating of herbivorous teeth to 690–720 ka and 520–550 ka (lower and upper sets) by combined Electron Spin Resonance (ESR) and U-series techniques. Traces of butchery on gazelle, alcelaphin, and zebra bones demonstrate that hominins had primary access to herbivore carcasses. Hominins brought and consumed meat in the cave, as documented by herbivore bones bearing human tooth marks concentrated in a circumscribed area of the excavation. In Africa, this site provides the earliest evidence forin situcarcass processing and meat-eating in cave, directly associated with lithic production and demonstrates the recurrent use by early Middle Pleistocene hominins of a North African cave site 400 000 years before that byHomo sapiensat Jebel Irhoud (Morocco).
Three-gene PCR and high-resolution melting analysis for differentiating vertebrate species mitochondrial DNA for biodiversity research and complementing forensic surveillance
Authors: Ouso Daniel O. , Otiende Moses Y. , Jeneby Maamun M. , Oundo Joseph W. , Bargul Joel L. , Miller Scott E. , Wambua Lillian , Villinger Jandouwe 
Published: March 2020

AbstractReliable molecular identification of vertebrate species from morphologically unidentifiable tissue is critical for the prosecution of illegally-traded wildlife products, conservation-based biodiversity research, and identification of blood-meal hosts of hematophagous invertebrates. However, forensic identification of vertebrate tissue relies on sequencing of the mitochondrial cytochrome oxidase I (COI) ‘barcode’ gene, which remains costly for purposes of screening large numbers of unknown samples during routine surveillance. Here, we adapted a rapid, low-cost approach to differentiate 10 domestic and 24 wildlife species that are common in the East African illegal wildlife products trade based on their unique high-resolution melting profiles from COI, cytochrome b, and 16S ribosomal RNA gene PCR products. Using the approach, we identified (i) giraffe among covertly sampled meat from Kenyan butcheries, and (ii) forest elephant mitochondrial sequences among savannah elephant reference samples. This approach is being adopted for high-throughput pre-screening of potential bushmeat samples in East African forensic science pipelines.
Self-regulation versus social influence for promoting cooperation on networks
Authors: Madeo Dario , Mocenni Chiara 
Published: March 2020

AbstractCooperation is a relevant and controversial phenomenon in human societies. Indeed, although it is widely recognized essential for tackling social dilemmas, finding suitable policies for promoting cooperation can be arduous and expensive. More often, it is driven by pre-established schemas based on norms and punishments. To overcome this paradigm, we highlight the interplay between the influence of social interactions on networks and spontaneous self-regulating mechanisms on individuals behavior. We show that the presence of these mechanisms in a prisoner’s dilemma game, may oppose the willingness of individuals to defect, thus allowing them to behave cooperatively, while interacting with others and taking conflicting decisions over time. These results are obtained by extending the Evolutionary Game Equations over Networks to account for self-regulating mechanisms. Specifically, we prove that players may partially or fully cooperate whether self-regulating mechanisms are sufficiently stronger than social pressure. The proposed model can explain unconditional cooperation (strong self-regulation) and unconditional defection (weak self-regulation). For intermediate self-regulation values, more complex behaviors are observed, such as mutual defection, recruiting (cooperate if others cooperate), exploitation of cooperators (defect if others cooperate) and altruism (cooperate if others defect). These phenomena result from dynamical transitions among different game structures, according to changes of system parameters and cooperation of neighboring players. Interestingly, we show that the topology of the network of connections among players is crucial when self-regulation, and the associated costs, are reasonably low. In particular, a population organized on a random network with a Scale-Free distribution of connections is more cooperative than on a network with an Erdös-Rényi distribution, and, in turn, with a regular one. These results highlight that social diversity, encoded within heterogeneous networks, is more effective for promoting cooperation.