bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using functional traits to model annual plant community dynamics
Authors: Metcalfe Helen , Milne Alice E. , Deledalle Florent , Storkey Jonathan 
Published: September 2020

AbstractPredicting the response of biological communities to changes in the environment or management is a fundamental pursuit of community ecology. Meeting this challenge requires the integration of multiple processes: habitat filtering, niche differentiation, biotic interactions, competitive exclusion, and stochastic demographic events. Most approaches to this long‐standing problem focus either on the role of the environment, using trait‐based filtering approaches, or on quantifying biotic interactions with process‐based community dynamics models. We introduce a novel approach that uses functional traits to parameterize a process‐based model. By combining the two approaches we make use of the extensive literature on traits and community filtering as a convenient means of reducing the parameterization requirements of a complex population dynamics model whilst retaining the power to capture the processes underlying community assembly. Using arable weed communities as a case study, we demonstrate that this approach results in predictions that show realistic distributions of traits and that trait selection predicted by our simulations is consistent with in‐field observations. We demonstrate that trait‐based filtering approaches can be combined with process‐based models to derive the emergent distribution of traits. While initially developed to predict the impact of crop management on functional shifts in weed communities, our approach has the potential to be applied to other annual plant communities if the generality of relationships between traits and model parameters can be confirmed.
Previous exposure mediates the response of eelgrass to future warming via clonal transgenerational plasticity
Authors: DuBois Katherine , Williams Susan L. , Stachowicz John J. 
Published: September 2020

AbstractMortality and shifts in species distributions are among the most obvious consequences of extreme climatic events. However, the sublethal effects of an extreme event can have persistent impacts throughout an individual’s lifetime and into future generations via within‐generation and transgenerational phenotypic plasticity. These changes can either confer resilience or increase susceptibility to subsequent stressful events, with impacts on population, community, and potentially ecosystem processes. Here, we show how a simulated extreme warming event causes persistent changes in the morphology and growth of a foundation species (eelgrass, Zostera marina) across multiple clonal generations and multiple years. The effect of previous parental exposure to warming increased aboveground biomass, shoot length, and aboveground–belowground biomass ratios while also greatly decreasing leaf growth rates. Long‐term increases in aboveground–belowground biomass ratios could indicate an adaptive clonal transgenerational response to warmer climates that reduces the burden of increased respiration in belowground biomass. These transgenerational responses were likely decoupled from clonal parent provisioning as rhizome size of clonal offspring was standardized at planting and rhizome starch reserves were not impacted by warming treatments. Future investigations into potential epigenetic mechanisms underpinning such clonal transgenerational plasticity will be necessary to understand the resilience of asexual foundation species to repeated extreme climatic events.
Functional differentiation accompanies taxonomic homogenization in freshwater fish communities
Authors: Campbell Sara E. , Mandrak Nicholas E. 
Published: September 2020

AbstractThe addition of nonnative species and loss of native species has modified the composition of communities globally. Although changes in β‐diversity have been well documented, there is a need for studies incorporating multiple time periods, more than one dimension of biodiversity, and inclusion of nestedness and turnover components to understand the underlying mechanisms structuring community composition and assembly. Here, we examined temporal changes in functional dissimilarity of fish communities of the Laurentian Great Lakes and compared these changes to those of taxonomic dissimilarity by decade from 1870 to 2010. Jaccard‐derived functional dissimilarity index was used to quantify changes in functional β‐diversity within communities, between all possible pairs of communities, and using a multiple‐site index among all communities. β‐diversity was partitioned into components of nestedness and turnover, and changes were examined over time. Similar to patterns in taxonomic dissimilarity, each community functionally differentiated from the historical community of 1870, with Lake Superior changing the most (~24%) and Lake Ontario the least (~14%). Although communities have become taxonomically homogenized, functional β‐diversity among all communities has increased over time, indicating functional differentiation. This is likely due to functional similarity between the communities being historically high (i.e., ~88% similar in 1870). The higher taxonomic relative to functional turnover indicates that the species being replaced between communities are functionally redundant, which could occur given the harsh environmental conditions of the region and/or as a result of the recent glacial history of the region. High functional nestedness across communities reflects dispersal limitations, with smaller communities being functional subsets of large communities closer to source populations. The functional differentiation observed is likely due to nonnative species with functional traits unique to the region establishing or the loss of functionally redundant native species; however, it is important to note that patterns of homogenization were periodically observed through time. Our study demonstrates the possible factors regulating diversity in the Laurentian Great Lakes fish communities, that patterns of taxonomic and functional β‐diversity are dynamic over time and vary in the magnitude and direction of change, and that taxonomic diversity should not be used to predict changes in functional diversity.
Development of discharge plasma waveguide with external magnetic field for laser plasma acceleration
Authors: Osawa Makito , Kajiuchi Yuki , Sawada Kyouhei , Takahashi Kazumasa , Sasaki Toru , Kikuchi Takashi 
Published: September 2020

AbstractTo improve the acceleration length in laser plasma acceleration, we investigate the discharge plasma waveguide with a magnetic field. The discharge circuit consists of two pulsed‐power circuits for preionization and main discharge. Discharges were repeated through the circuit using high‐power semiconductor switches. Laser propagation characteristics of discharge plasma waveguide with the external magnetic field were observed. The results show that the reproducibility of waveguide with the external magnetic field is relatively high compared to that without magnetic field. The laser intensity gradually decreases with the strength of external magnetic field. These results suggest that the electron density profile is possible to control using the discharge plasma waveguide with an external magnetic field.
Sexism and racism perceptions: It depends on who does it and why
Authors: Bastart Jennifer , Branscombe Nyla R. , Sarda Elisa , Delmas Florian 
Published: September 2020

AbstractOutgroup perpetrators of discrimination are perceived as more biased than ingroup perpetrators, potentially because perpetrator group membership drives inferences regarding their motivation to discriminate. Consequently, when outgroup perpetrators provide hostile justification, greater discrimination and illegitimacy will be perceived compared to when ingroup perpetrators do so. In contrast, benevolent justifications reduce differences in discrimination and illegitimacy perception for outgroup versus ingroup perpetrators. In two experiments (Ns = 243; 382) dealing with sexism and racism, results supported our reasoning that the perpetrator’s explicit justification moderates the influence of the perpetrator’s group membership on discrimination and illegitimacy perception. Results of a third experiment (N = 489) show that when no justifications are provided, the prototype effect on discrimination perception mirrors the prototype effect under hostile justification, but not under benevolent justification. The results are more mixed concerning perceived illegitimacy. We discuss the implications of these findings regarding the processes underlying the prototype effect.
Low Temperature Hydrothermal Method for Synthesis of Crystalline Fe2O3 and their Oxygen Evolution Performance
Authors: Rana Supriya , Yadav Krishna K. , Sood Kritika , Ankush  , Mehta S. K. , Jha Menaka 
Published: September 2020

AbstractHydrothermal method for the synthesis of hematite (α‐Fe2O3) has been done at 120 °C. Morphological study reveals the formation of spherical nanoparticles of average size ∼10 nm. The prepared electrode (Fe2O3 dropcosted over graphite sheet) used as a working electrode for the oxygen evolution reaction in 1 M KOH. The linear sweep voltammetry confirms that the as‐prepared electrode requires 340 mV potential to reach a current density of 1 mA/cm2 and 510 mV potential for 10 mA/cm2. Further, the kinetics of electrocatalyst has been investigated using Tafel slope, mass activity and Turn over frequency.
Fast, Simple and Sensitive Determination of Coumaric Acid in Fruit Juice Samples by Magnetite Nanoparticles‐zeolitic Imidazolate Framework Material
Authors: Şenocak Ahmet 
Published: September 2020

AbstractIn this work, magnetic iron nanoparticle (Fe3O4) was functionalized a zeolitic imidalozate framework (ZIF‐4) material by co‐precipitation process to provide a magnetic hybrid nanomaterial, viz. Fe3O4@ZIF‐4. The structural characterization was performed different spectroscopic, thermal and microscopic techniques. Moreover, voltammetric sensor properties of Fe3O4@ZIF‐4 nanohybrid material for determination of p‐coumaric acid (CA) were performed by differential pulse (DPV) and cyclic voltammetry (CV). A reliable and selective electroanalytical method exhibited for the detection of CA. It was found that the deposition of Fe3O4@ZIF‐4 nanohybrid on a glassy carbon electrode (GCE) brought about 2.3, 3.5 and 5.0 fold more sensitive than Fe3O4/GCE, ZIF‐4/GCE and unmodified GCE responses to CA in Britton‐Robinson (B−R) buffer solution (a pH of 4). The detection, quantification limits and linear range of CA were determined as 0.18, 0.60 μM and 0.50–12.00 μM. The stability, repeatability and selectivity of the suggested Fe3O4@ZIF‐4 modified GCE sensor was fully investigated. In addition, an application of orange juices samples was performed on modified electrode for determination of CA, which was showed by a standard addition method with verifying of High Performance Liquid Chromatography (HPLC) analysis. Besides the ease of synthesis and low price, the suggested Fe3O4@ZIF‐4/GCE sensor offers repeatability, selectivity, stability and easy to apply to real samples.
Highly Sensitive Impedimetric Biosensor Based on Thermolysin Immobilized on a GCE Modified with AuNP‐decorated Graphene for the Detection of Ochratoxin A
Authors: Zinoubi Khaoula , Chrouda Amani , Soltane Raya , Al‐Ghamdi Youssef O. , Garallah Almalki Sami , Osman Gamal , Barhoumi Houcine , Jaffrezic Renault Nicole 
Published: September 2020

AbstractThe fabrication of a thermolysin‐based biosensor capable of detecting ochratoxin A (OTA) from food samples is described. The electrochemical deposition of calcium cross‐linked cellulose film (CCLC) and gold nanoparticles (AuNPs) on graphene (GR) for modification of a glassy carbon electrode (GCE) is the first step. Then the thermolysin (TLN) enzyme in a polyvinyl alcohol (PVA)/polyethylenimine (PEI) matrix is immobilized. The impedimetric biosensor response is linear from 0.2 nM to 100 nM with a detection limit of 0.2 nM. The obtained stable and reproducible biosensor is then applied for the detection of OTA in spiked extracts from coffee beans.
An enhanced adaptive global‐best harmony search algorithm for continuous optimization problems
Authors: Yarmohamadi Hasan , Zhang Qianyun , Jiao Pengcheng , Alavi Amir H. 
Published: September 2020

AbstractThis paper presents an enhanced adaptive global‐best harmony search (EAGHS) to solve global continuous optimization problems. The global‐best HS (GHS) is one of the strongest versions of the classical HS algorithm that hybridizes the concepts of swarm intelligence and conventional HS. However, randomized selection of harmony in the permissible interval diverts the GHS algorithm from the global optimum. To address this issue, the proposed EAGHS method introduces a dynamic coefficient into the GHS algorithm to increase the search power in early iterations. Various complex and extensively‐applied benchmark functions are used to validate the developed EAGHS algorithm. The results indicate that the EAGHS algorithm offers faster convergence and better accuracy than the standard HS, GHS and other similar algorithms. Further analysis is performed to evaluate the sensitivity of the proposed method to the changes of parameters such as harmony memory consideration rate, harmony search memory, and larger dimensions.
Sum‐throughput maximization for overlay cognitive wireless powered network with energy harvesting capability
Authors: Rezaie Mostafa , Dosaranian‐Moghadam Mohamad , Bakhshi Hamidreza , Hassannejad Bibalan Mohammadreza 
Published: September 2020

AbstractIn this article, a novel time division multiple access (TDMA)‐based approach for optimal resource allocation in an overlay cognitive wireless powered communication network is proposed. In this network, power in the secondary network (SN) is provided by the primary network (PN) in addition to its own wireless network. Using the TDMA and a harvest‐then‐transmit protocol, the time and power allocation for downlink wireless energy transfer (WET) and uplink wireless information transmission (WIT) are jointly optimized to maximize the sum‐throughput in SN. Quality of service in PN and power and time in SN, as the main constrains are considered for sum‐throughput maximization in this network. This is a non‐convex problem which gets converted to a convex problem using active interference‐temperature control technique. Moreover, a new closed‐form expression which results in sub‐optimal power and time‐allocation (SO‐PT‐A) is addressed. The performance of proposed algorithm is compared with the equal time allocation (ETA) and fixed TDMA‐allocation (FTDMA‐A) algorithms which impose some special constraints for optimal power and time allocation. The simulation results depict that the SO‐PT‐A algorithm outperforms the ETA and FTDMA‐A algorithms. Eventually, the performance of the SO‐PT‐A algorithm is evaluated with other well‐known algorithms considering different values of the average and maximum transmit power of the hybrid‐access point (H‐AP), the number of secondary users (SUs) and path loss exponent.
Deep learning in medical imaging: A brief review
Authors: Serte Sertan , Serener Ali , Al‐Turjman Fadi 
Published: September 2020

AbstractResearchers have used deep learning methods for a human level or better disease identification and detection. This paper reports, in brief, the recent work in deep learning identification of diseases occurring at three unique parts of the human body: the skin, the thorax, and the eye. While earlier reviews reported on the theory, applications, and challenges of such research, what distinguishes this work from the others is the reporting and comprehensive analysis of the key results. In doing so, the paper not only summarizes the major conclusions drawn from them but also emphasizes their weaknesses. The hope is to help the researchers see the big picture in deep learning classification of the diseases of the skin, the thorax and the eye, and guide them to find the right future research direction.
Reduced order framework for convection dominant and pure diffusive problems based on combination of deep long short‐term memory and proper orthogonal decomposition/dynamic mode decomposition methods
Authors: Kherad Mahdi , Moayyedi Mohammad Kazem , Fotouhi Faranak 
Published: September 2020

AbstractIn many real‐world applications, mathematical models are highly complex, and numerical simulations in high‐dimensional systems are challenging. Model order reduction is a useful method to obtain a reasonable approximation by significantly reducing the computational cost of such problems. Deep learning technology is a recent improvement in artificial neural networks that can find more hidden information from the data. Deep learning has the advantage of processing data in its raw form and trains the nonlinear system with different levels of representation and predicts the data. In this article, a reduced order model framework based on a combination of deep learning [long short‐term memory (LSTM)] and proper orthogonal decomposition/dynamic mode decomposition (POD/DMD) modes is presented. Due to the robustness and stability of the LSTM recurrent neural network in predicting chaotic dynamical systems, we consider LSTM architecture to develop our data‐driven reduced order modeling (ROM). We investigate the proposed method performance by solving two well‐known canonical cases: a steady shear flow exhibiting the Kelvin‐Helmholtz instability, and two‐dimensional and unsteady mass diffusion equation. The focus of this article is to use LSTM deep recursive neural network to learn the time dynamics and POD/DMD to generate the order reduction model. The results show that the proposed method is very accurate in predicting time dynamics and input reconstruction.
Diacylglycerol lipase alpha in astrocytes is involved in maternal care and affective behaviors
Authors: Schüle Lena‐Louise , Glasmacher Sandra , Gertsch Jürg , Roggan Marie Denise , Transfeld Janis‐Lisa , Bindila Laura , Lutz Beat , Kolbe Carl‐Christian , Bilkei‐Gorzo Andras , Zimmer Andreas , Leidmaa Este 
Published: September 2020

AbstractGenetic deletion of cannabinoid CB1 receptors or diacylglycerol lipase alpha (DAGLa), the main enzyme involved in the synthesis of the endocannabinoid (eCB) 2‐arachidonoylglycerol (2‐AG), produced profound phenotypes in animal models of depression‐related behaviors. Furthermore, clinical studies have shown that antagonists of CB1 can increase the incidence and severity of major depressive episodes. However, the underlying pathomechanisms are largely unknown. In this study, we have focused on the possible involvement of astrocytes. Using the highly sensitive RNAscope technology, we show for the first time that a subpopulation of astrocytes in the adult mouse brain expresses Dagla, albeit at low levels. Targeted lipidomics revealed that astrocytic DAGLa only accounts for a minor percentage of the steady‐state brain 2‐AG levels and other arachidonic acid derived lipids like prostaglandins. Nevertheless, the deletion of Dagla in adult mouse astrocytes had profound behavioral consequences with significantly increased depressive‐like behavioral responses and striking effects on maternal behavior, corresponding with increased levels of serum progesterone and estradiol. Our findings therefore indicate that lipids from the DAGLa metabolic axis in astrocytes play a key regulatory role in affective behaviors.
Birth weight is associated with adolescent brain development: A multimodal imaging study in monozygotic twins
Authors: Hayward Dana A. , Pomares Florence , Casey Kevin F. , Ismaylova Elmira , Levesque Melissa , Greenlaw Keelin , Vitaro Frank , Brendgen Mara , Rénard Felix , Dionne Ginette , Boivin Michel , Tremblay Richard E. , Booij Linda 
Published: September 2020

AbstractPrevious research has shown that the prenatal environment, commonly indexed by birth weight (BW), is a predictor of morphological brain development. We previously showed in monozygotic (MZ) twins associations between BW and brain morphology that were independent of genetics. In the present study, we employed a longitudinal MZ twin design to investigate whether variations in prenatal environment (as indexed by discordance in BW) are associated with resting‐state functional connectivity (rs‐FC) and with structural connectivity. We focused on the limbic and default mode networks (DMNs), which are key regions for emotion regulation and internally generated thoughts, respectively. One hundred and six healthy adolescent MZ twins (53 pairs; 42% male pairs) followed longitudinally from birth underwent a magnetic resonance imaging session at age 15. Graph theoretical analysis was applied to rs‐FC measures. TrackVis was used to determine track count as an indicator of structural connectivity strength. Lower BW twins had less efficient limbic network connectivity as compared to their higher BW co‐twin, driven by differences in the efficiency of the right hippocampus and right amygdala. Lower BW male twins had fewer tracks connecting the right hippocampus and right amygdala as compared to their higher BW male co‐twin. There were no associations between BW and the DMN. These findings highlight the possible role of unique prenatal environmental influences in the later development of efficient spontaneous limbic network connections within healthy individuals, irrespective of DNA sequence or shared environment.
Avoidable environmental disasters and infant health: Evidence from a mining dam collapse in Brazil
Authors: Carrillo Bladimir , Da Mata Daniel , Emanuel Lucas , Lopes Daniel , Sampaio Breno 
Published: September 2020

AbstractWe study the health consequences of one of the largest environmental disasters of the world mining industry, which largely stemmed from regulatory failure. Exploiting the timing and location of the Mariana mine tailings dam collapse in Brazil, we show that in utero exposure to the tragedy significantly reduced birth weight and increased infant mortality. The adverse effects were stronger for infants born to less educated and nonmarried mothers. These findings indicate that poorly enforced environmental regulation may have long‐term welfare impacts on local communities.
Transient free convection of a second‐grade fluid flowing in a vertical cylinder
Authors: Dwivedi Naveen , Singh Arun Kumar , Singh Ashok Kumar 
Published: September 2020

AbstractThe intention of the present article is to examine the transient effect on the free convection of the second‐grade fluid flowing in a vertical cylinder. We have found the analytical solution of the derived governing partial differential equations in nondimensional form corresponding to the velocity as well as the temperature fields by applying the Laplace transformation method in terms of the Bessel function of the first kind. To obtain the impacts of the appropriate parameters related to the given equations, such as the second‐grade fluid parameter and the Prandtl number, the numerical values of the velocity are discussed and displayed in graphs. Furthermore, the mass flow rate and the skin friction at the inner surface of the cylinder are given in a tabular form. The influence of the second‐grade fluid parameter is to decelerate the velocity as well as the mass flow rate and to enhance the steady‐state time.