Intermediate Density Research Articles

Model of the Origin of a Ciguatoxic Grouper (Plectropomus leopardus)

Published data were used to model the transfer of ciguatoxins (CTX) across three trophic levels of a marine food chain on the Great Barrier Reef (GBR), Australia, to produce a mildly toxic common coral trout (Plectropomus leopardus), one of the most targeted food fishes on the GBR. Our model generated a 1.6 kg grouper with a flesh concentration of 0.1 µg/kg of Pacific-ciguatoxin-1 (P-CTX-1 = CTX1B) from 1.1 to 4.3 µg of P-CTX-1 equivalents (eq.) entering the food chain from 0.7 to 2.7 million benthic dinoflagellates (Gambierdiscus sp.) producing 1.6 pg/cell of the P-CTX-1 precursor, P-CTX-4B (CTX4B). We simulated the food chain transfer of ciguatoxins via surgeonfishes by modelling Ctenochaetus striatus feeding on turf algae. A C. striatus feeding on ≥1000 Gambierdiscus/cm2 of turf algae accumulates sufficient toxin in <2 days that when preyed on, produces a 1.6 kg common coral trout with a flesh concentration of 0.1 µg/kg P-CTX-1. Our model shows that even transient blooms of highly ciguatoxic Gambierdiscus can generate ciguateric fishes. In contrast, sparse cell densities of ≤10 Gambierdiscus/cm2 are unlikely to pose a significant risk, at least in areas where the P-CTX-1 family of ciguatoxins predominate. The ciguatera risk from intermediate Gambierdiscus densities (~100 cells/cm2) is more difficult to assess, as it requires feeding times for surgeonfish (~4-14 days) that overlap with turnover rates of turf algae that are grazed by herbivorous fishes, at least in regions such as the GBR, where stocks of herbivorous fishes are not impacted by fishing. We use our model to explore how the duration of ciguatoxic Gambierdiscus blooms, the type of ciguatoxins they produce, and fish feeding behaviours can produce differences in relative toxicities between trophic levels. Our simple model indicates thresholds for the design of risk and mitigation strategies for ciguatera and the variables that can be manipulated to explore alternate scenarios for the accumulation and transfer of P-CTX-1 analogues through marine food chains and, potentially, for other ciguatoxins in other regions, as more data become available.

Porous graphitized carbon-supported FeOCl as a bifunctional adsorbent-catalyst for the wet peroxide oxidation of chlorinated volatile organic compounds: Effect of mesopores and mechanistic study

Wet scrubbing coupled with adsorption-enhanced heterogeneous advanced oxidation processes (AOPs) are promising approaches to the treatment of chlorinated volatile organic compounds (CVOCs). However, microporous activated carbon-based adsorbents and catalyst supports have the disadvantage of difficult molecule diffusion. Herein, we have demonstrated that porous graphitized carbon (PGC) allowed faster intra-particle diffusion of organic molecules due to its well-developed mesoporous structure. Therefore, a wet scrubbing system containing H2O2 and a PGC-supported FeOCl catalyst has been developed to effectively remove gaseous dichloroethane, trichloroethylene, dichloromethane and chlorobenzene. The scrubber performed well at pH 3.0 using a FeOCl/PGC dosage of 0.2 g/L and initial H2O2 concentration of 40 mM. Its good long-term performance was achieved by replenishing H2O2 to maintain a suitable concentration. The degradation pathways of dichloroethane have been proposed using a combination of intermediate analysis and density functional theory calculations. PGC-supported catalysts may be desirable bifunctional adsorbent-catalyst materials for wet scrubbing of CVOCs.

Interactions between Small Inorganic Ions and Uncharged Monolayers on the Water/Air Interface.

The interaction of several simple electrolytes with uncharged insoluble monolayers is studied on the basis of tensiometric and potentiometric data for the surface electrolyte solution|air. The induced adsorption of electrolyte on the monolayer is determined via a combination of data for equilibrium spreading pressure and surface pressure versus area isotherms. We show that the monolayer-induced adsorption of electrolyte is not only strongly ion-specific but also surfactant-specific. The comparison between the ion-specific effects on a carboxylic acid monolayer at low pH and an ester monolayer shows that the anion series follows the same order while the cation series reverses. The effect of the electrolyte on the chemical potential of the monolayer shows attraction between the surfactant and the ions at low monolayer densities, but at high surface densities, repulsion seems to come into play. In nearly all investigated cases, a maximum of monolayer-induced electrolyte adsorption is observed at intermediate monolayer densities. This suggests specific interactions between the surfactant headgroup and the ions. The Volta potential data for the monolayers are analyzed on the basis of the equations of quadrupolar electrostatics. The analysis suggests that the ion-specific effect on the Volta potential is due to the ion-specific decrement of the bulk dielectric constant of the electrolyte solution. Moreover, we present evidence that in most cases the effect of the electrolyte on the orientation of the adsorbed dipoles cannot be neglected. Instead, the change in the ion distribution in the electric double layer seems to have a small effect on the Volta potential.

Amido-ene(amido) Ni(II)-Catalyzed Highly Enantioselective Transfer Hydrogenations of Ketone: Dual Functions of the Ene(amido) Group

Catalytic asymmetric transfer hydrogenation (ATH) reactions of ketones have become an important tool for producing enantiomerically pure alcohols that are widely used in the syntheses of bioactive compounds. However, the high toxicities and low abundances of traditionally employed precious metals serving as catalyst centers have impeded widespread application of precious metal-based catalysts in asymmetric synthesis. Development of catalysts from abundant and less toxic 3d metals is highly desirable but still challenging. We report herein the development of structurally well-defined (R,R)-amido-ene(amido) nickel catalysts for ATH of ketone substrates, facilitating access to a wide range of secondary (S)-configuration alcohols, many of which are synthetic building blocks of biologically relevant molecules, with up to 95% enantiomeric excess (e.e.) and broad scope of functional group tolerance. Catalytic intermediate isolation and density functional theory calculation ascribed the catalytic activity to stabilization of the electron-rich nickel center with the ene(amido) group via a π-backdonation interaction within the catalytic intermediates, while the stereoinduction mainly arises from a catalyst–substrate π–π interaction in the transition state for enantioselective hydride transfer.

Spatial patterns of large African cats: a large‐scale study on density, home range size, and home range overlap of lions Panthera leo and leopards Panthera pardus

Abstract Spatial patterns of and competition for resources by territorial carnivores are typically explained by two hypotheses: 1) the territorial defence hypothesis and 2) the searching efficiency hypothesis. According to the territorial defence hypothesis, when food resources are abundant, carnivore densities will be high and home ranges small. In addition, carnivores can maximise their necessary energy intake with minimal territorial defence. At medium resource levels, larger ranges will be needed, and it will become more economically beneficial to defend resources against a lower density of competitors. At low resource levels, carnivore densities will be low and home ranges large, but resources will be too scarce to make it beneficial to defend such large territories. Thus, home range overlap will be minimal at intermediate carnivore densities. According to the searching efficiency hypothesis, there is a cost to knowing a home range. Larger areas are harder to learn and easier to forget, so carnivores constantly need to keep their cognitive map updated by regularly revisiting parts of their home ranges. Consequently, when resources are scarce, carnivores require larger home ranges to acquire sufficient food. These larger home ranges lead to more overlap among individuals' ranges, so that overlap in home ranges is largest when food availability is the lowest. Since conspecific density is low when food availability is low, this hypothesis predicts that overlap is largest when densities are the lowest. We measured home range overlap and used a novel method to compare intraspecific home range overlaps for lions Panthera leo (n = 149) and leopards Panthera pardus (n = 111) in Africa. We estimated home range sizes from telemetry location data and gathered carnivore density data from the literature. Our results did not support the territorial defence hypothesis for either species. Lion prides increased their home range overlap at conspecific lower densities whereas leopards did not. Lion pride changes in overlap were primarily due to increases in group size at lower densities. By contrast, the unique dispersal strategies of leopards led to reduced overlap at lower densities. However, when human‐caused mortality was higher, leopards increased their home range overlap. Although lions and leopards are territorial, their territorial behaviour was less important than the acquisition of food in determining their space use. Such information is crucial for the future conservation of these two iconic African carnivores.

Role of three particle interactions in the determination of static pair correlation functions

The Static Pair correlation functions in gaseous mercury samples at temperatures 1623 K and 1723 K have been computed using (n,6) form of inter-particle interaction potential present among Hg atoms. Static Pair correlation function g(r) exhibits a straightforward relation to the strength of inter-particle interaction. These Structural functions can describe the state of order of any condensed matter. At low and intermediate densities, contribution towards interaction from a third particle beyond that present among a pair of particles, plays a dominant role. Computed results for g(r) function while incorporating three particle interactions at densities 2.1 g/cm3 (1623 K) and 3.0 g/cm3 (1723 K) have been reported and compared with the experimental results as well as with those obtained from two body interactions. An excellent agreement between computed and experimental results is clearly evident. Moreover, this can also be clearly observed that interplay of three particle interactions provides much better results as compared to that from two particle interactions.

Densidade de plantas e morfologia foliar afetam a produtividade, qualidade e nutrição do algodoeiro

ABSTRACT In sandy soils with frequent drought events, the choice of cultivar and plant density is crucial to improve water use efficiency and avoid losses in cotton yield and fiber quality. This study aimed to evaluate cotton cultivars’ yield and fiber quality at different plant densities. The study was carried out during two growing seasons (2017/2018 and 2018/2019) on sandy soil in southeastern Brazil. The cultivar TMG 47B2RF showed 27 and 29% higher yields under low and medium plant density, respectively, when compared with the highest plant density. The higher yield was due to the higher number of bolls in relation to the cultivar DBB 509B2RF. The boll weight of cultivar DBB 509B2RF was 23 and 22% higher under low and medium plant density, respectively. Fiber length and strength were higher in TMG 47B2RF compared to DBB 509B2RF. The leaf nutrient content was higher in DBB 509B2RF, except for Ca and Mg. When there is a regular rainfall, the low plant density results in higher yields, but intermediate plant density is the best option in cropping seasons with severe drought. The high density of plants in sandy soil environments was never a better option for none of the cultivars.

Learning topology optimization process via convolutional long‐short‐term memory autoencoder‐decoder

AbstractThis article proposed an autoencoder‐decoder architecture with convolutional long‐short‐term memory (ConvLSTM) cell for the purpose of learning topology optimization iterations. The overall topology optimization process is treated as time‐series data, with each iteration as a single step. The first few steps are fed into the encoder to generate encoder embedding, which is fed into the decoder. The decoder uses the encoder embedding as input and generates the result at each future step until the end of iteration. To train the proposed neural network, a large dataset is generated by a conventional topology optimization method, that is, solid isotropic material with penalization for intermediate densities, with randomly picked boundary conditions, load conditions, and volume constraints. Unlike other deep learning models introduced before, the proposed method can learn each topology optimization step iteratively and present the full optimization path. Furthermore, the proposed method can be extended to give solutions to unseen boundary and load conditions with a significant reduction in computation cost in a little sacrifice on the performance of the optimum design.

Normal range CAG repeat size variations in the HTT gene are associated with an adverse lipoprotein profile partially mediated by body mass index.

Tandem cytosine-adenine-guanine (CAG) repeat sizes of 36 or more in the huntingtin gene (HTT) cause Huntington's disease (HD). Apart from neuropsychiatric complications, the disease is also accompanied by metabolic dysregulation and weight loss, which contribute to a progressive functional decline. Recent studies also reported an association between repeats below the pathogenic threshold (<36) for HD and body mass index (BMI), suggesting that HTT repeat sizes in the non-pathogenic range are associated with metabolic dysregulation. In this study, we hypothesized that HTT repeat sizes < 36 are associated with metabolite levels, possibly mediated through reduced BMI. We pooled data from three European cohorts (n = 10 228) with genotyped HTT CAG repeat size and metabolomic measurements. All 145 metabolites were measured on the same targeted platform in all studies. Multilevel mixed-effects analysis using the CAG repeat size in HTT identified 67 repeat size metabolite associations. Overall, the metabolomic profile associated with larger CAG repeat sizes in HTT were unfavorable-similar to those of higher risk of coronary artery disease and type 2 diabetes-and included elevated levels of amino acids, fatty acids, low-density lipoprotein (LDL)-, very low-density lipoprotein- and intermediate density lipoprotein (IDL)-related metabolites while with decreased levels of very large high-density lipoprotein (HDL)-related metabolites. Furthermore, the associations of 50 metabolites, in particular, specific very large HDL-related metabolites, were mediated by lower BMI. However, no mediation effect was found for 17 metabolites related to LDL and IDL. In conclusion, our findings indicate that large non-pathogenic CAG repeat sizes in HTT are associated with an unfavorable metabolomic profile despite their association with a lower BMI.

Slower Auger Recombination in 12-Faceted Dodecahedron CsPbBr3 Nanocrystals.

Over the past two decades, intensive research efforts have been devoted to suppressions of Auger recombination in metal-chalcogenide and perovskite nanocrystals (PNCs) for the application of photovoltaics and light emitting devices (LEDs). Here, we have explored dodecahedron cesium lead bromide perovskite nanocrystals (DNCs), which show slower Auger recombination time compared to hexahedron nanocrystals (HNCs). We investigate many-body interactions that are manifested under high excitation flux density in both NCs using ultrafast spectroscopic pump-probe measurements. We demonstrate that the Auger recombination rate due to multiexciton recombinations are lower in DNCs than in HNCs. At low and intermediate excitation density, the majority of carriers recombine through biexcitonic recombination. However, at high excitation density (>1018 cm-3) a higher number of many-body Auger process dominates over biexcitonic recombination. Compared to HNCs, high PLQY and slower Auger recombinations in DNCs are likely to be significant for the fabrication of highly efficient perovskite-based photonics and LEDs.

Metamorphoses of the flow past an obstacle of a resonantly driven bistable polariton fluid

Motivated by recent experiments, we theoretically analyze the flow past an obstacle of a one-dimensional ``quantum fluid of light,'' which is resonantly driven, and exhibits bistability. The flow is found to abruptly change several times when the fluid velocity or the obstacle potential strength is increased. These transitions display unusual features. In contrast to the cases of usual fluids and superfluids, the transitions take place between stationary states. They involve the fluid bistability in an essential way. Remarkably, at the transitions points, the fluid in the obstacle wake lies in the unstable intermediate density state.

Host density shapes the relative contribution of vector-based and aerial transmission of a pathogenic fungus.

Pathogen transmission mode is a key determinant of epidemiological outcomes. Theory shows that host density can influence the spread of pathogens differentially depending on their mode of transmission. Host density could therefore play an important role in determining the pathogen transmission mode. We tested theoretical expectations using floral arrays of the alpine carnation Dianthus pavonius in field experiments of spore dispersal of the anther-smut fungus, Microbotryum, by vector (pollinator)-based floral transmission and passive aerial transmission at a range of host densities. Pollinators deposited fewer spores per plant at high host density than at lower density (ranging from a 0.2-2 m spacing between plants), and vector-based spore deposition at higher densities declined more steeply with distance from diseased plant sources. In contrast, while aerial spore deposition declined with distance from the diseased source, the steepness of this decline was independent of host density. Our study indicates that the amount and distance of vector-based transmission are likely to be a nonmonotonic function of host density as a result of vector behavior, which is not readily encapsulated by fixed dispersal functions. We conclude that the spatial spread of pathogens by vectors is likely to be greater at lower and intermediate densities, whereas the spatial spread of aerially transmitted pathogens would be greater at high densities. These contrasting patterns could lead to differential importance of each transmission mode in terms of its contribution to subsequent infections across host densities.

Topology optimization of micro-channel reactors using an improved multi-objective algorithm

This study proposes an improved multi-objective density-based topology optimization (TO) model for Newtonian and non-Newtonian fluid micro-channel reactor(NMCR, nNMCR) to substantially improve the overall performance of MCR. Flow, catalytic reaction, and heat transfer in MCR under constant pressure driving is described by built a multi-physics model of continuous-flow exothermic reaction. TO adopts the material density as the design variable to control the changes in fluid and solid domains. The artificial Darcy friction improved by polynomial function is used to add the impermeability of intermediate density, and the Helmholtz partial differential filter and hyperbolic tangent projection are applied to eliminate the checkerboard phenomenon and structural ill-conditioning. The improved multi-objective algorithm based on the weighted-sum method and pseudo-design domain concept are proposed to avoid the local topological structure simplification and unreasonable. In examples, the effects of reactor geometries and outlet angles θ on optimal configurations and performance parameters of NMCR and nNMCR are investigated. Additionally, optimal solution set under multi-objective functions with different weight factors ω1 is solved, and Pareto frontier is established accordingly to reveal the trade-off relationship between the single-objectives. MCR responds to the proportion increase of flow single-objective in multi-objective function by homogenizing the local catalyst blocks distribution and increasing the flow channel length, thereby affecting the flow, diffusion and mixing. The local catalyst distributions of NMCR and nNMCR are significantly different due to different fluid properties. From the perspective of engineering, this study provides an efficient and applicable optimization method for designing MCR with higher comprehensive performance.

Typical large graphs with given edge and triangle densities

The analysis of large simple graphs with extreme values of the densities of edges and triangles has been extended to the statistical structure of typical graphs of fixed intermediate densities, by the use of large deviations of Erdős-Rényi graphs. We prove that the typical graph exhibits sharp singularities as the constraining densities vary between different curves of extreme values, and we determine the precise nature of the singularities. The extension to graphs with fixed densities of edges and k-cycles for odd \(k>3\) is straightforward and we note the simple changes in the proof.

Speed of sound for hadronic and quark phases in a magnetic field

In this paper we calculate the speed of sound for three phases that may exist inside a magnetized hybrid neutron star at different density regions: A hadronic phase at low densities, quark-matter in the magnetic dual chiral density wave (MDCDW) phase at intermediate densities and a free-quark phase modeled by the MIT bag model at higher densities. It is found that the speed of sound exhibits a non-monotonic behavior, that goes from values smaller than the conformal limit (cs2<1/3) in the hadronic phase, to peak (cs2>1/3) in the MDCDW phase, to finally reach the conformal limit (cs2∼1/3) at higher densities for quarks in the MIT bag model. Also, the anisotropic speed of sound in the presence of a magnetic field is derived from first principles. This is a consequence of the anisotropy in the system's pressures produced by the breaking of the rotational symmetry in the presence of a magnetic field. The role played by the lowest Landau level contribution in affecting the speed of sound in the magnetized phases is discussed.

Speed of sound and liquid-gas phase transition in nuclear matter

We investigate the speed of sound in nuclear matter at finite temperature and density (chemical potential) in the nonlinear Walecka model. The numerical results suggest that the behaviors of sound speed are closely related to the the nuclear liquid-gas (LG) phase transition and the associated spinodal structure. The adiabatic sound speed is nonzero at the critical endpoint (CEP) in the mean-field approximation. We further derive the boundary of vanishing sound velocity in the temperature-density phase diagram, and point out the region where the sound wave equation is broken. The distinction between the speed of sound in nuclear matter and that in quark matter contains important information about the equation of state of strongly interacting matter at intermediate and high density. We also formulate the relations between differently defined speeds of sound using the fundamental thermodynamic relations.

An Improved Evolutionary Structure Optimization Method for Smooth Topology Design of Structures

To meet the needs of industrial production, an improved evolution structural optimization (ESO) method with high efficiency is proposed. The optimized design variables with intermediate density were designed using the windowed evolution structural optimization (WESO) method to increase the stability of the algorithm. The efficient calculation method of the element node sensitivity was established, which realizes the establishment of level set functions, smooth topological design of structures and the updating of design variables. The stability of the proposed algorithm was verified by the Zhou–Rozvany problem, two- and three-dimensional (3D) numerical results. The effectiveness and efficiency of the proposed algorithm was further verified by numerical comparison with other topology optimization frameworks. Lastly, the improved windowed ESO method was applied to the initial configuration design of the double-deck bridge structure, which not only provides guidance for its initial design but also demonstrates the applicability of the method in complex structural systems.

The asymptotic concentration approach combined with isogeometric analysis for topology optimization of two-dimensional linear elasticity structures

&lt;abstract&gt; &lt;p&gt;We propose an asymptotic concentration approach combined with isogeometric analysis (IGA) for the topology optimization of two-dimensional (2D) linear elasticity structures under the commonly-used framework of the solid isotropic materials and penalty (SIMP) model. Based on the SIMP framework, the B-splines are used as basis functions to describe geometric model in structural finite element analysis, which closely combines geometric modeling with structural analysis. Isogeometric analysis is utilized to define the geometric characteristics of the 2D linear elasticity structures, which can greatly improve the calculation accuracy. In addition, to eliminate the gray-scale intervals usually caused by the intermediate density in the SIMP approach, we utilize the asymptotic concentration method to concentrate the intermediate density values on either 0 or 1 gradually. Consequently, the intermediate densities representing gray-scale intervals in topology optimization results are sufficiently eliminated by virtue of the asymptotic concentration method. The effectiveness and applicability of the proposed method are illustrated by several typical examples.&lt;/p&gt; &lt;/abstract&gt;

Retracted Article: Constraining Neutron-Star Matter — Combination of heavy-ion experiments, astronomy and theory

This paper has been formally retracted because it has been accidentally published twice in the same volume. Request approved by the proceedings Editor and the Publisher on January 29, 2024.

Constraining Neutron-Star Matter — Combination of heavy-ion experiments and multi-messenger astronomy

Describing supernova explosions or neutron-star collisions requires a deep understanding of properties of nuclear matter at supra-saturation densities, and extreme neutron over proton asymmetries. So far, our knowledge about dense matter provided by astrophysical observations in the cores of neutron stars remains limited. However, dense nuclear matter is also probed in terrestrial heavy-ion collision (HIC) experiments. We demonstrate how, within a novel approach, using Bayesian inference, combining data from astrophysical multi-messenger observations of neutron stars and from HICs at relativistic energies, one can improve our understanding of dense nuclear matter. The inclusion of HIC data probing the nuclear matter equation-of-state (EoS) at supra-saturation density has the effect of increasing the predicted pressure in the core of neutron stars relative to previous analyses, and shifts the neutron-star radii expectation towards larger values, in accordance with recent observations by the Neutron Star Interior Composition Explorer mission. More remarkable is that, though the sources and methods of observation are orthogonal, the constraints from HIC experiments and multimessenger observations are consistent with each other. It shows that both methods can be complementary at intermediate densities, and strengthen each other. Another conclusion is that in order to be even more constraining, the constraint of the EoS of asymmetric nuclear matter by HIC methods should be improved above twice saturation density, which should be feasible with future experiments with enhanced precision and higher bombarding energy.