2,714 research outputs found
Effect of arbuscular mycorrhizal fungus on the growth and polyphenol production of medicinal plants: Ehretia asperula and Solanum procumben
The study was conducted to evaluate the influence of arbuscular mycorrhizal fungus (Rhizophagus intradices) on growth and polyphenol production of the two important and popular medicinal plants in Vietnam: Ehretia asperula Zoll. & Mor. and Solanum procumbens Lour. The results showed a significant effect of the fungus on the growth of these two species with the growth indices such as height, weight and P content that were all higher than those of non-AM plants; although the indices of AM symbiosis in the plant roots were not as high as other plants in previous studies. The effect of AM fungus on polyphenol production was different between the two species. In E. asperula, the effect of AM fungi on polyphenol production was not significant; whereas in S. procumbens, AM symbiosis significantly increased polyphenol production in plant biomass, especially in roots. The different growth times of the two species might cause the different effects of AM fungus on polyphenol production
Effects of Static and Dynamic Hamstring Stretching on Anaerobic Exercise Performance
Please view abstract in the attached PDF file
Bayesian signaling game based efficient security model for MANETs
Game Theory acts as a suitable tool offering promising solutions to security-related concerns in Mobile Ad Hoc Networks (i.e., MANETs). In MANETs, security forms a prominent concern as it includes nodes which are usually portable and require significant coordination between them. Further, the absence of physical organisation makes such networks susceptible to security breaches, hindering secure routing and execution among nodes. Game Theory approach has been manipulated in the current study to achieve an analytical view while addressing the security concerns in MANETs. This paper offers a Bayesian-Signaling game model capable of analysing the behaviour associated with regular as well as malicious nodes. In the proposed model, the utility of normal nodes has been increased while reducing the utility linked to malicious nodes. Moreover, the system employs a reputation system capable of stimulating best cooperation between the nodes. The regular nodes record incessantly to examine their corresponding nodes’ behaviours by using the belief system of Bayes-rules. On its comparison with existing schemes, it was revealed that the presented algorithm provides better identification of malicious nodes and attacks while delivering improved throughput and reduced false positive rate
Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization
Groundwater is one of the most valuable natural resources in the world (Jha
et al., 2007). However, it is not an unlimited resource; therefore
understanding groundwater potential is crucial to ensure its sustainable use.
The aim of the current study is to propose and verify new artificial
intelligence methods for the spatial prediction of groundwater spring
potential mapping at the Koohdasht–Nourabad plain, Lorestan province, Iran.
These methods are new hybrids of an adaptive neuro-fuzzy inference system
(ANFIS) and five metaheuristic algorithms, namely invasive weed optimization
(IWO), differential evolution (DE), firefly algorithm (FA), particle swarm
optimization (PSO), and the bees algorithm (BA). A total of 2463 spring
locations were identified and collected, and then divided randomly into two
subsets: 70 % (1725 locations) were used for training models and the
remaining 30 % (738 spring locations) were utilized for evaluating the
models. A total of 13 groundwater conditioning factors were prepared for
modeling, namely the slope degree, slope aspect, altitude, plan curvature,
stream power index (SPI), topographic wetness index (TWI), terrain roughness
index (TRI), distance from fault, distance from river, land use/land cover,
rainfall, soil order, and lithology. In the next step, the step-wise
assessment ratio analysis (SWARA) method was applied to quantify the degree
of relevance of these groundwater conditioning factors. The global
performance of these derived models was assessed using the area under the
curve (AUC). In addition, the Friedman and Wilcoxon signed-rank tests were
carried out to check and confirm the best model to use in this study. The
result showed that all models have a high prediction performance; however,
the ANFIS–DE model has the highest prediction capability (AUC  =  0.875),
followed by the ANFIS–IWO model, the ANFIS–FA model (0.873), the ANFIS–PSO
model (0.865), and the ANFIS–BA model (0.839). The results of this research
can be useful for decision makers responsible for the sustainable management
of groundwater resources.</p
Changes In Apparent Molar Water Volume and DKP Solubility Yield Insights on the Hofmeister Effect
This study examines the properties of a 4 × 2 matrix of aqueous cations and anions at concentrations up to 8.0 M. The apparent molar water volume, as calculated by subtracting the mass and volume of the ions from the corresponding solution density, was found to exceed the molar volume of ice in many concentrated electrolyte solutions, underscoring the nonideal behavior of these systems. The solvent properties of water were also analyzed by measuring the solubility of diketopiperazine (DKP) in 2.000 M salt solutions prepared from the same ion combinations. Solution rankings for DKP solubility were found to parallel the Hofmeister series for both cations and anions, whereas molar water volume concurred with the cation series only. The results are discussed within the framework of a desolvation energy model that attributes solute-specific changes in equilibria to solute-dependent changes in the free energy of bulk water
Exporting Vector Muscles for Facial Animation
In this paper we introduce a method of exporting vector muscles from one 3D face to another for facial animation. Starting from a 3D face with an extended version of Waters' linear muscle system, we transfer the linear muscles to a target 3D face. We also transfer the region division, which is used to increase the performance of the muscle as well as to control the animation. The human involvement is just as simple as selecting the faces which shows the most natural facial expressions in the animator's view. The method allows the transfer of the animation to a new 3D model within a short time. The transferred muscles can then be used to create new animations
Resonant Raman scattering of surface phonon polaritons mediated by excitons in WSe films
Surface phonon-polaritons propagating along interfaces of polar dielectrics
coexist with excitons in many van der Waals heterostructures, so understanding
their mutual interactions is of great interest. Here, we investigate the type I
surface phonon polariton of hBN via low-temperature resonant-Raman spectroscopy
in hBN/WSe2 heterostructures. The resonantly enhanced hBN surface phonon
polariton (SPhP) Raman signal, when laser energy is such that the scattered
photons have energy close to that of the WSe2 excitons, enables detailed
characterization of type I SPhP in hBN even when hBN is one monolayer thick. We
find that the measured bandwidth of the SPhP Raman signal depends on the
thicknesses of the hBN layer. We are able explain the experimental data using
transfer matrix method simulations of SPhP dispersions providing that we assume
the Raman scattering to be momentum non-conserving, as could be the case if
localized WSe2 exciton states participated in the process. We further show that
resonant Raman scattering from SiO2 SPhP can also be mediated by WSe.Comment: 23 pages, 11 figure
Advanced Multilevel Node Separator Algorithms
A node separator of a graph is a subset S of the nodes such that removing S
and its incident edges divides the graph into two disconnected components of
about equal size. In this work, we introduce novel algorithms to find small
node separators in large graphs. With focus on solution quality, we introduce
novel flow-based local search algorithms which are integrated in a multilevel
framework. In addition, we transfer techniques successfully used in the graph
partitioning field. This includes the usage of edge ratings tailored to our
problem to guide the graph coarsening algorithm as well as highly localized
local search and iterated multilevel cycles to improve solution quality even
further. Experiments indicate that flow-based local search algorithms on its
own in a multilevel framework are already highly competitive in terms of
separator quality. Adding additional local search algorithms further improves
solution quality. Our strongest configuration almost always outperforms
competing systems while on average computing 10% and 62% smaller separators
than Metis and Scotch, respectively
Chemical etching of silicon carbide in pure water by using platinum catalyst
Chemical etching of SiC was found to proceed in pure water with the assistance of a Pt catalyst. A 4H-SiC (0001) wafer was placed and slid on a polishing pad in pure water, on which a thin Pt film was deposited to give a catalytic nature. Etching of the wafer surface was observed to remove protrusions preferentially by interacting with the Pt film more frequently, thus flattening the surface. In the case of an on-axis wafer, a crystallographically ordered surface was obtained with a straight step-and-terrace structure, the height of which corresponds to that of an atomic bilayer of Si and C. The etching rate depended upon the electrochemical potential of Pt. The vicinal surface was observed at the potential at which the Pt surface was bare. The primary etching mechanism was hydrolysis with the assistance of a Pt catalyst. This method can, therefore, be used as an environmentally friendly and sustainable technology.Ai Isohashi, P. V. Bui, D. Toh, S. Matsuyama, Y. Sano, K. Inagaki, Y. Morikawa, and K. Yamauchi, "Chemical etching of silicon carbide in pure water by using platinum catalyst", Appl. Phys. Lett. 110, 201601 (2017) https://doi.org/10.1063/1.4983206
- …