bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying Driving Factors in Flood‐Damaging Processes Using Graphical Models
Authors: Vogel Kristin , Weise Laura , Schröter Kai , Thieken Annegret H. 
Published: October 2018

AbstractFlood damage estimation is a core task in flood risk assessments and requires reliable flood loss models. Identifying the driving factors of flood loss at residential buildings and gaining insight into their relations is important to improve our understanding of flood damage processes. For that purpose, we learn probabilistic graphical models, which capture and illustrate (in‐)dependencies between the considered variables. The models are learned based on postevent surveys with flood‐affected residents after six flood events, which occurred in Germany between 2002 and 2013. Besides the sustained building damage, the survey data contain information about flooding parameters, early warning and emergency measures, property‐level mitigation measures and preparedness, socioeconomic characteristics of the household, and building characteristics. The analysis considers the entire data set with a total of 4,468 cases as well as subsets of the data set partitioned into single flood events and flood types: river floods, levee breaches, surface water flooding, and groundwater floods, to reveal differences in the damaging processes. The learned networks suggest that the flood loss ratio of residential buildings is directly influenced by hydrological and hydraulic aspects as well as by building characteristics and property‐level mitigation measures. The study demonstrates also that for different flood events and process types the building damage is influenced by varying factors. This suggests that flood damage models need to be capable of reproducing these differences for spatial and temporal model transfers.
Lagrangian Modeling of Reactive Transport in Heterogeneous Porous Media With an Automatic Locally Adaptive Particle Support Volume
Authors: Sole‐Mari Guillem , Fernàndez‐Garcia Daniel 
Published: October 2018

AbstractThe particle support volume is crucial for simulating reactive transport with Lagrangian methods as it dictates the interaction among particles. Assuming that it is constant in space, the particle support volume can be selected by means of kernel density estimation theory, an approach that has been shown to provide accurate estimates in simple setups. However, the particle support volume should intuitively vary with the particle position and evolve with time so as to mimic the local behavior of the solute plume. In this paper, we present a new approach to select a locally optimal particle support volume in reactive transport simulations. We consider that each particle has a different support volume that can locally adapt its shape and size with time based on the nearby particle distribution. By introducing a new optimality criterion, closed‐form expressions of the particle support volume are presented under certain assumptions. In advection‐dominated transport, we propose to orient the support volume along the local velocities. Numerical simulations of solute transport in a randomly heterogeneous porous medium demonstrate that the new approach can substantially increase accuracy with a more rapid convergence to the true solution with the number of particles. The error reduction seen in local approaches is particularly important in regions with extreme (high and low) density of particles. The method is shown to be computationally efficient, displaying better results than traditional histogram or global kernel methods for the same computational effort.
Technical Note: An Operational Implementation of Recursive Digital Filter for Base Flow Separation
Authors: Rammal Mohamad , Archambeau Pierre , Erpicum Sebastien , Orban Philippe , Brouyère Serge , Pirotton Michel , Dewals Benjamin 
Published: October 2018

AbstractBase flow estimation is of overwhelming importance in hydrological modeling and water resource management. One of the widely used techniques to derive base flow from measured streamflow is the recursive digital filter (RDF). Yet its application still raises methodological issues related to the determination of its parameters. In this study, we propose a practical and automatic procedure to calibrate the RDF with respect to the measured streamflow. The method operationality and robustness are first demonstrated on three gauging stations in the Ourthe catchment (Belgium). The calibrated parameters compare well with those obtained by a standard graphical approach. Next, the proposed approach is compared to the technique of conductance mass balance for two gauging stations in the Hoyoux catchment (Belgium). A fair agreement between the results of the two techniques is obtained, suggesting that the proposed automatic calibration procedure of RDF takes the base flow separation process to a higher level of practicality and transparency.
Evaluation of the Generalized and Rescaled Complementary Evaporation Relationships
Authors: Crago Richard D. , Qualls Russell J. 
Published: October 2018

AbstractA rigorous approach to the complementary relationship (CR) in land surface evaporation was introduced by Brutsaert (2015, https://doi.org/10.1002/2015WR017720) in which the problem was cast in nondimensional form for generality, boundary conditions (BCs) were established from physical constraints, and a suitable mathematical solution was formulated. Building on Brutsaert's insightful foundation, Crago et al. (2016, https://doi.org/10.1002/2016WR019753) showed the need, for rational reasons, to modify Brutsaert's BCs by introducing Emax, an upper limit to the apparent potential evaporation corresponding to an actual evaporation of 0. Following the rigorous approach of Brutsaert, this paper presents the derivation and resulting CR. The BC associated with Emax requires a solution that is rescaled with regard to Brutsaert's dimensionless framework and represents a fundamentally different solution from that of Brutsaert. In essence, this formulation acknowledges a pattern of organized variability, which exists within the data when scaled in Brutsaert's dimensionless framework, and our rescaled CR reorganizes the data, collapsing it toward a more universal representation. Our rescaled CR, implemented with two versions of Emax, one based on mass transfer and another on the Penman equation, is evaluated alongside Brutsaert's original formulation. Multiyear data sets from seven Fluxnet sites in Australia, ranging from a sparsely vegetated ephemeral tropical wetland to a temperate forest with a 75‐m‐tall canopy were used to test the formulations on a weekly basis. All three formulations performed adequately. Overall, the rescaled model with Emax based on the Penman equation performed best; it extracts more information with no additional observational data requirements.
Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement
Authors: Fowler Keirnan , Coxon Gemma , Freer Jim , Peel Murray , Wagener Thorsten , Western Andrew , Woods Ross , Zhang Lu 
Published: October 2018

AbstractRainfall‐runoff models are often deficient under changing climatic conditions, yet almost no recent studies propose new or improved model structures, instead focusing on model intercomparison, input sensitivity, and/or quantification of uncertainty. This paucity of progress in model development is (in part) due to the difficulty of distinguishing which cases of model failure are truly caused by structural inadequacy. Here we propose a new framework to diagnose the salient cause of poor model performance in changing climate conditions, be it structural inadequacy, poor parameterization, or data errors. The framework can be applied to a single catchment, although larger samples of catchments are helpful to generalize and/or cross‐check results. To generate a diagnosis, multiple historic periods with contrasting climate are defined, and the limits of model robustness and flexibility are explored over each period separately and for all periods together. Numerous data‐based checks also supplement the results. Using a case study catchment from Australia, improved inference of structural failure and clearer evaluation of model structural improvements are demonstrated. This framework enables future studies to (i) identify cases where poor simulations are due to poor calibration methods or data errors, remediating these cases without recourse to structural changes; and (ii) use the remaining cases to gain greater clarity into what structural changes are needed to improve model performance in changing climate.
Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series
Authors: Koriath C. , Kenny J. , Adamson G. , Druyeh R. , Taylor W. , Beck J. , Quinn L. , Mok T. H. , Dimitriadis A. , Norsworthy P. , Bass N. , Carter J. , Walker Z. , Kipps C. , Coulthard E. , Polke J. M. , Bernal-Quiros M. , Denning N. , Thomas R. , Raybould R. , Williams J. , Mummery C. J. , Wild E. J. , Houlden H. , Tabrizi S. J. , Rossor M. N. , Hummerich H. , Warren J. D. , Rowe J. B. , Rohrer J. D. , Schott J. M. , Fox N. C. , Collinge J. , Mead S. 
Published: October 2018

AbstractNext-generation genetic sequencing (NGS) technologies facilitate the screening of multiple genes linked to neurodegenerative dementia, but there are few reports about their use in clinical practice. Which patients would most profit from testing, and information on the likelihood of discovery of a causal variant in a clinical syndrome, are conspicuously absent from the literature, mostly for a lack of large-scale studies. We applied a validated NGS dementia panel to 3241 patients with dementia and healthy aged controls; 13,152 variants were classified by likelihood of pathogenicity. We identified 354 deleterious variants (DV, 12.6% of patients); 39 were novel DVs. Age at clinical onset, clinical syndrome and family history each strongly predict the likelihood of finding a DV, but healthcare setting and gender did not. DVs were frequently found in genes not usually associated with the clinical syndrome. Patients recruited from primary referral centres were compared with those seen at higher-level research centres and a national clinical neurogenetic laboratory; rates of discovery were comparable, making selection bias unlikely and the results generalisable to clinical practice. We estimated penetrance of DVs using large-scale online genomic population databases and found 71 with evidence of reduced penetrance. Two DVs in the same patient were found more frequently than expected. These data should provide a basis for more informed counselling and clinical decision making.
Uncovering the complex genetics of human temperament
Authors: Zwir Igor , Arnedo Javier , Del-Val Coral , Pulkki-Råback Laura , Konte Bettina , Yang Sarah S. , Romero-Zaliz Rocio , Hintsanen Mirka , Cloninger Kevin M. , Garcia Danilo , Svrakic Dragan M. , Rozsa Sandor , Martinez Maribel , Lyytikäinen Leo-Pekka , Giegling Ina , Kähönen Mika , Hernandez-Cuervo Helena , Seppälä Ilkka , Raitoharju Emma , de Erausquin Gabriel A. , Raitakari Olli , Rujescu Dan , Postolache Teodor T. , Sung Joohon , Keltikangas-Järvinen Liisa , Lehtimäki Terho , Cloninger C. Robert 
Published: October 2018

AbstractExperimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic–phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37–53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.
Discharge Performance of Zinc-Air Flow Batteries Under the Effects of Sodium Dodecyl Sulfate and Pluronic F-127
Authors: Hosseini Soraya , Lao-atiman Woranunt , Han Siow Jing , Arpornwichanop Amornchai , Yonezawa Tetsu , Kheawhom Soorathep 
Published: October 2018

AbstractZinc-air batteries are a promising technology for large-scale electricity storage. However, their practical deployment has been hindered by some issues related to corrosion and passivation of the zinc anode in an alkaline electrolyte. In this work, anionic surfactant sodium dodecyl sulfate (SDS) and nonionic surfactant Pluronic F-127 (P127) are examined their applicability to enhance the battery performances. Pristine zinc granules in 7 M KOH, pristine zinc granules in 0–8 mM SDS/7 M KOH, pristine zinc granules in 0–1000 ppm P127/7 M KOH, and SDS coated zinc granules in 7 M KOH were examined. Cyclic voltammograms, potentiodynamic polarization, and electrochemical impedance spectroscopy confirmed that using 0.2 mM SDS or 100 ppm P127 effectively suppressed the anode corrosion and passivation. Nevertheless, direct coating SDS on the zinc anode showed adverse effects because the thick layer of SDS coating acted as a passivating film and blocked the removal of the anode oxidation product from the zinc surface. Furthermore, the performances of the zinc-air flow batteries were studied. Galvanostatic discharge results indicated that the improvement of discharge capacity and energy density could be sought by the introduction of the surfactants to the KOH electrolyte. The enhancement of specific discharge capacity for 30% and 24% was observed in the electrolyte containing 100 ppm P127 and 0.2 mM SDS, respectively.
Ginkgolide B promotes neuronal differentiation through the Wnt/β-catenin pathway in neural stem cells of the postnatal mammalian subventricular zone
Authors: Li Ming-Yang , Chang Chia-Ting , Han Yueh-Ting , Liao Chien-Po , Yu Jenn-Yah , Wang Tsu-Wei 
Published: October 2018

AbstractChinese herbal medicines (CHMs) have been used to treat human diseases for thousands of years. Among them, Ginkgo biloba is reported to be beneficial to the nervous system and a potential treatment of neurological disorders. Since the presence of adult neural stem cells (NSCs) brings hope that the brain may heal itself, whether the effect of Ginkgo biloba is on NSCs remains elusive. In this study, we found that Ginkgo biloba extract (GBE) and one of its main ingredients, ginkgolide B (GB) promoted cell cycle exit and neuronal differentiation in NSCs derived from the postnatal subventricular zone (SVZ) of the mouse lateral ventricle. Furthermore, the administration of GB increased the nuclear level of β-catenin and activated the canonical Wnt pathway. Knockdown of β-catenin blocked the neurogenic effect of GB, suggesting that GB promotes neuronal differentiation through the Wnt/β-catenin pathway. Thus, our data provide a potential mechanism underlying the therapeutic effect of GBE or GB on brain injuries and neurodegenerative disorders.
Angle-dependent electron-electron correlation in the single ionization of H2 in strong laser fields
Authors: Wu Wan-Yang , He Feng 
Published: October 2018

AbstractThe one-photon ionization and tunneling ionization of H2 exposed to strong XUV and infrared laser pulses are studied by numerically simulating the four-dimensional time-dependent Schrödinger equation, which includes two-electron dynamics for arbitrary angle between the molecular axis and the laser polarization direction. In the one-photon single ionization of H2, one electron escapes fast and the other bound electron is not disturbed but remains in coherent superposition of two electronic states of $${{\bf{H}}}_{{\bf{2}}}^{{\boldsymbol{+}}}$$

H

2

+

. In another case, under the irradiation of strong infrared laser pulses, one electron tunnels through the laser-dressed Coulomb barrier, and the other bound electron has enough time to adapt to the potential of $${{\bf{H}}}_{{\bf{2}}}^{{\boldsymbol{+}}}$$

H

2

+

and thus is prone to transfer to the ground electronic state of $${{\bf{H}}}_{{\bf{2}}}^{{\boldsymbol{+}}}$$

H

2

+

. In the intermediate regime, between the one photon and tunneling regimes, this electron-electron correlation depends strongly on the laser frequency, laser intensity and on the angle between laser polarization and the molecular axis.
Landscape of alternative splicing in Capra_hircus
Authors: Xu Tieshan , Xu Feng , Gu Lihong , Rong Guang , Li Mao , Qiao Fei , Shi Liguang , Wang Dingfa , Xia Wanliang , Xun Wenjuan , Cao Ting , Liu Yiming , Lin Zhemin , Zhou Hanlin 
Published: October 2018

AbstractAlternative splicing (AS) is a fundamental regulatory process in all higher eukaryotes. However, AS landscapes for a number of animals, including goats, have not been explored to date. Here, we sequenced 60 samples representing 5 tissues from 4 developmental stages in triplicate using RNA-seq to elucidate the goat AS landscape. In total, 14,521 genes underwent AS (AS genes), accounting for 85.53% of intron-containing genes (16,697). Among these AS genes, 6,342 were differentially expressed in different tissues. Of the AS events identified, retained introns were most prevalent (37.04% of total AS events). Functional enrichment analysis of differential and specific AS genes indicated goat AS mainly involved in organ function and development. Particularly, AS genes identified in leg muscle were associated with the “regulation of skeletal muscle tissue development” GO term. Given genes were associated with this term, four of which (NRG4, IP6K3, AMPD1, and DYSF) might play crucial roles in skeletal muscle development. Further investigation indicated these five genes, harbored 13 ASs, spliced exclusively in leg muscle, likely played a role in goat leg muscle development. These results provide novel insights into goat AS landscapes and a valuable resource for investigation of goat transcriptome complexity and gene regulation.
Interplay between P. gingivalis, F. nucleatum and A. actinomycetemcomitans in murine alveolar bone loss, arthritis onset and progression
Authors: Ebbers Meinolf , Lübcke Paul M. , Volzke Johann , Kriebel Katja , Hieke Cathleen , Engelmann Robby , Lang Hermann , Kreikemeyer Bernd , Müller-Hilke Brigitte 
Published: October 2018

AbstractIncreasing evidence supports the association of periodontitis with rheumatoid arthritis. Even though a prominent role has been postulated for Porphyromonas gingivalis, many bacterial species contribute to the pathogenesis of periodontal disease. We therefore investigated the impact of Porphyromonas gingivalis as well as other major pathobionts on the development of both, periodontitis and arthritis in the mouse. Pathobionts used - either alone or in combination - were Porphyromonas gingivalis, Fusobacterium nucleatum and Aggregatibacter actinomycetemcomintans. Periodontitis was induced via oral gavage in SKG, DBA/1 and F1 (DBA/1 × B10.Q) mice and collagen-induced arthritis was provoked via immunization and boost with bovine collagen type II. Alveolar bone loss was quantified via micro computed tomography, arthritis was evaluated macroscopically and histologically and serum antibodies were assessed. Among the strains tested, only F1 mice were susceptible to P. gingivalis induced periodontitis and showed significant alveolar bone loss. Bone loss was paralleled by antibody titers against P. gingivalis. Of note, mice inoculated with the mix of all three pathobionts showed less alveolar bone loss than mice inoculated with P. gingivalis alone. However, oral inoculation with either F. nucleatum or A. actinomycetemcomintans alone accelerated subsequent arthritis onset and progression. This is the first report of a triple oral inoculation of pathobionts combined with collagen-induced arthritis in the mouse. In this interplay and this particular genetic setting, F. nucleatum and A. actinomycetemcomitans exerted a protective impact on P. gingivalis induced alveolar bone loss. By themselves they did not induce periodontitis yet accelerated arthritis onset and progression.
Impact of the Coal Mining on the Spatial Distribution of Potentially Toxic Metals in Farmland Tillage Soil
Authors: Li Fang , Li Xinju , Hou Le , Shao Anran 
Published: October 2018

AbstractCoal mining areas are prone to hazardous element contamination because of mining activities and the resulting wastes, mainly including Cr, Ni, Cu, Zn, Cd and Pb. This study collected 103 samples of farmland tillage soil surrounding a coal mine in southwestern Shandong province and monitored the heavy metal concentrations of each sample by inductively coupled plasma mass spectrometer (ICP-MS). Statistics, geostatistics, and geographical information systems (GIS) were used to determine the spatial pattern of the potentially toxic metals above in the coal mining area. The results show that the toxic metal concentrations have wide ranges, but the average values for Cr, Ni, Cu, Zn, Cd and Pb are 72.16, 29.53, 23.07, 66.30, 0.14 and 23.71 mg Kg−1, which mostly exceed the natural soil background contents of Shandong Province. The element pairs Ni-Cu, Ni-Zn, and Cu-Zn have relatively high correlation coefficients (0.805, 0.505, 0.613, respectively). The Kriging interpolation results show that the contents of soil toxic metals are influenced by coal mining activities. Moreover, micro-domain variation analysis revealed the toxic metals in the typical area of the coal transportation line. These findings offer systematic insight into the influence of coal mining activities on toxic metals in farmland tillage soil.