A
bstract
The pion-pole contribution to hadronic light-by-light scattering in the anomalous magnetic moment of the muon (
g
− 2)
μ
is fully determined by the doubly-virtual pion transition form ...factor. Although this crucial input quantity is, in principle, directly accessible in experiment, a complete measurement covering all kinematic regions relevant for (
g
−2)
μ
is not realistic in the foreseeable future. Here, we report in detail on a reconstruction from available data, both space- and time-like, using a dispersive representation that accounts for all the low-lying singularities, reproduces the correct high- and low-energy limits, and proves convenient for the evaluation of the (
g
− 2)
μ
loop integral. We concentrate on the systematics of the fit to
e
+
e
−
→ 3
π
data, which are key in constraining the isoscalar dependence, as well as the matching to the asymptotic limits. In particular, we provide a detailed account of the pion transition form factor at low energies in the time- and space-like region, including the error estimates underlying our final result for the pion-pole contribution,
a
μ
π
0
−
pole
=
62.6
−
2.5
+
3.0
×
10
−
11
, and demonstrate how forthcoming singly-virtual measurements will further reduce its uncertainty.
A
bstract
We address the contribution of the 3
π
channel to hadronic vacuum polarization (HVP) using a dispersive representation of the
e
+
e
−
→ 3
π
amplitude. This channel gives the second-largest ...individual contribution to the total HVP integral in the anomalous magnetic moment of the muon (
g
− 2)
μ
, both to its absolute value and uncertainty. It is largely dominated by the narrow resonances
ω
and
ϕ
, but not to the extent that the off-peak regions were negligible, so that at the level of accuracy relevant for (
g
− 2)
μ
an analysis of the available data as model independent as possible becomes critical. Here, we provide such an analysis based on a global fit function using analyticity and unitarity of the underlying
γ
∗
→ 3
π
amplitude and its normalization from a chiral low-energy theorem, which, in particular, allows us to check the internal consistency of the various
e
+
e
−
→ 3
π
data sets. Overall, we obtain
a
μ
3
π
|
≤1.8 GeV
= 46
.
2(6)(6) × 10
−10
as our best estimate for the total 3
π
contribution consistent with all (low-energy) constraints from QCD. In combination with a recent dispersive analysis imposing the same constraints on the 2
π
channel below 1 GeV, this covers nearly 80% of the total HVP contribution, leading to
a
μ
HVP
= 692
.
3(3
.
3) × 10
−10
when the remainder is taken from the literature, and thus reaffirming the (
g
−2)
μ
anomaly at the level of at least 3
.
4
σ
. As side products, we find for the vacuum-polarization-subtracted masses
M
ω
= 782
.
63(3)(1) MeV and
M
ϕ
= 1019
.
20(2)(1) MeV, confirming the tension to the
ω
mass as extracted from the 2
π
channel.
•EMD is applied to reduce the complexity of the prediction subsequence.•The SE of the decomposed sub-sequence is induced to improve the prediction precision of wind speed.•LSTM is applied to predict ...the high frequency sub-sequences.•The ARIMA is employed to predict the low frequency sub-sequences and one residual.•A hybrid EMD-LSTM-ARIMA model is successfully proposed for wind speed prediction.
Wind speed is the key factor of wind power generation. With the increase of the proportion of wind power generation in total power generation, the accurate prediction of wind speeds plays an important role in the stable operations of power grids. However, the strong randomness of wind speeds makes it difficult to accurately predict wind speeds. Thus, a wind speed prediction model combining empirical mode decomposition (EMD) with some novel recurrent neural networks (RNN) and the autoregressive integrated moving average (ARIMA) is proposed to solve the problem. The selected RNNs are long short-term memory network (LSTM) and the gated recurrent unit (GRU) network. In this model, EMD is used to decompose the wind speed sequence to reduce the complexity and non-stationary of the series. The entropy of the samples of the sub-sequences after decomposition is calculated. Consequently, LSTM is applied to predict the high frequency sub-sequences with large entropy while the ARIMA is employed to predict the remaining low frequency sub-sequences and one residual. Finally, the prediction results of each sub series are combined to obtain the final prediction results. To verify the accuracy and stability of the model, four wind speed data sets form Inner Mongolia, China, are used to test the proposed methods. Five models are established in four practical cases and their performances are compared with the performances of the proposed model. The results in this paper show the following: (1) the EMD method can improve the wind speed prediction performance when it is combined with LSTM; (2) after decomposition, LSTM is suitable for predicting high complexity subsequences and the ARIMA is suitable for effectively predicting low complexity subsequences based on the different sample entropies; and (3) the root mean squared errors (RMSEs) of the hybrid model on the four wind speed data sets are 0.4163, 0.2085, 0.1613, and 0.2790, respectively, which are basically lower than those of the five models compared. Therefore, it is feasible to apply the hybrid model to wind speed prediction.
The application of photovoltaic-thermoelectric (PV-TE) combined power generation system in greenhouse is an effective way to solve the problems of high energy consumption and high pollution. In order ...to improve the efficiency of the PV-TE system, maximum power point tracking (MPPT) control is required. Aiming at the shortcomings of the traditional incremental conductance (INC) method, which is fixed in step size, a hyperbolic tangent-type adaptive variable step length INC method is proposed. The method takes advantage of the monotonically increasing and the fast changing speed of the hyperbolic tangent function, so that the step length can be adjusted rapidly and adaptively according to the change of external environmental conditions such as light intensity. The simulation results show that the proposed method can rapidly track the maximum power point when the illumination intensity changes drastically, and meanwhile it has smaller steady-state error and can realize MPPT control well.
The π^{0} pole constitutes the lowest-lying singularity of the hadronic light-by-light (HLBL) tensor, and thus, it provides the leading contribution in a dispersive approach to HLBL scattering in the ...anomalous magnetic moment of the muon (g-2)_{μ}. It is unambiguously defined in terms of the doubly virtual pion transition form factor, which in principle, can be accessed in its entirety by experiment. We demonstrate that, in the absence of a direct measurement, the full spacelike doubly virtual form factor can be reconstructed very accurately based on existing data for e^{+}e^{-}→3π, e^{+}e^{-}→e^{+}e^{-}π^{0}, and the π^{0}→γγ decay width. We derive a representation that incorporates all the low-lying singularities of the form factor, matches correctly onto the asymptotic behavior expected from perturbative QCD, and is suitable for the evaluation of the (g-2)_{μ} loop integral. The resulting value, a_{μ}^{π^{0}-pole}=62.6_{-2.5}^{+3.0}×10^{-11}, for the first time, represents a complete data-driven determination of the pion-pole contribution with fully controlled uncertainty estimates. In particular, we show that already improved singly virtual measurements alone would allow one to further reduce the uncertainty in a_{μ}^{π^{0}-pole}.
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Nanoemulsions are used in the food, cosmetics, personal care and pharmaceutical industries to provide desirable optical, textural, stability, and delivery characteristics. In many ...industrial applications, it is desirable to formulate nanoemulsions using natural ingredients so as to develop label-friendly products. Rhamnolipids are biosurfactants isolated from certain microorganisms using fermentation processes. They are glycolipids that have a polar head consisting of rhamnose units and a non-polar tail consisting of a hydrocarbon chain. In this study, the interfacial characteristics of this natural surfactant at medium chain triglyceride (MCT) oil-water interfaces were characterized, and its ability to form nanoemulsions was compared to that of another natural surfactant (quillaja saponins). The influence of rhamnolipid concentration, homogenization pressure, and oil type on the mean droplet diameter of emulsions produced by microfluidization was determined. Rhamnolipids were highly effective at forming small droplets (d32<0.15μm) at low surfactant-to-oil ratios (SOR<1:10) for MCT oil. Rhamnolipids could also be used to form small droplets using long chain triglyceride oils, such as corn and fish oil. Rhamnolipid-coated droplets were stable to aggregation over a range of pH values (5–9), salt concentrations (<100mM NaCl) and temperatures (20–90°C). However, droplet aggregation was observed at highly acidic (pH 2–4) and high ionic strength (200–500mM NaCl) conditions. These effects were attributed to a reduction in electrostatic repulsion at low pH and high salt levels. Rhamnolipid-coated droplets had a high negative charge at neutral pH that decreased in magnitude with decreasing pH. These results indicate that rhamnolipids are effective natural surfactants that may be able to replace synthetic surfactants in certain commercial applications.
Consumer concern about human and environmental health is encouraging food manufacturers to use more natural and sustainable food ingredients. In particular, there is interest in replacing synthetic ...ingredients with natural ones, and in replacing animal-based ingredients with plant-based ones. This article provides a review of the various types of natural emulsifiers with potential application in the food industry, including phospholipids, biosurfactants, proteins, polysaccharides, and natural colloidal particles. Increased utilization of natural emulsifiers in food products may lead to a healthier and more sustainable food supply. However, more research is needed to identify, isolate, and characterize new sources of commercially viable natural emulsifiers suitable for food use.
Recent developments in the area of plant‐based hydrogels are introduced, especially those derived from wood as a widely available, multiscale, and hierarchical source of nanomaterials, as well as ...other cell wall elements. With water being fundamental in a hydrogel, water interactions, hydration, and swelling, all critically important in designing, processing, and achieving the desired properties of sustainable and functional hydrogels, are highlighted. A plant, by itself, is a form of a hydrogel, at least at given states of development, and for this reason phenomena such as fluid transport, diffusion, capillarity, and ionic effects are examined. These aspects are highly relevant not only to plants, especially lignified tissues, but also to the porous structures produced after removal of water (foams, sponges, cryogels, xerogels, and aerogels). Thus, a useful source of critical and comprehensive information is provided regarding the synthesis of hydrogels from plant materials (and especially wood nanostructures), and about the role of water, not only for processing but for developing hydrogel properties and uses.
Inspired from nature, wood‐based and man‐made hydrogels are produced taking advantage of the properties and structure of elements present in the cell walls of plants, including (nano)celluloses. They endow new materials with features that include directionality, hierarchy, responsiveness, and function, all of which are associated to the composition and morphology of the building blocks.
Emulsions are utilized in the food, pharmaceutical, and personal care industries to provide specific physicochemical properties and functional attributes. In many applications, it is desirable to use ...natural ingredients to formulate emulsions to create “label-friendly” products. In this study, the impact of three polysaccharide-based emulsifiers on the formation and stability of oil-in-water emulsions prepared using high-pressure microfluidization were compared: gum arabic, corn fiber gum, and beet pectin. The surface activities of these emulsifiers were characterized using interfacial tension measurements. The influence of emulsifier type, concentration, and homogenization pressure on the efficiency of emulsion formation was examined. The impact of oil type (medium chain triglycerides, corn oil, fish oil, and lemon oil) on the ability of the different emulsifiers to form emulsions was also investigated. The stability of the emulsions was monitored during storage at ambient temperature. Emulsions could be produced using all three polysaccharide-based emulsifiers, with the mean particle diameter decreasing with increasing emulsifier concentration and homogenization pressure. Gum arabic and beet pectin were more effective emulsifiers than corn fiber gum, with a lower amount of emulsifier required and smaller droplets being produced. This effect was attributed to a greater reduction in interfacial tension and stronger adsorption leading to more efficient droplet disruption and less re-coalescence within the homogenizer for gum arabic and beet pectin. Emulsions prepared using corn fiber gum were susceptible to flocculation and coalescence. This study provides valuable information for choosing polysaccharide-based emulsifiers for utilization in food and beverage industries.
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•Emulsions were prepared by high-pressure microfluidization.•Droplet size decreased with emulsifier level and homogenization pressure.•Beet pectin produced smaller droplets than gum arabic and corn fiber gum.•Corn fiber gum emulsions creamed due to large droplets & depletion flocculation.
Nanoemulsions are utilized within the food, pharmaceutical, and personal care industries because of their unique physicochemical properties and functional attributes: high optical clarity; prolonged ...stability; and, enhanced bioavailability. For many applications, it is desirable to utilize natural ingredients to formulate nanoemulsions so as to create “label-friendly” products. In this study, we compared the effectiveness of a number of natural emulsifiers at fabricating corn oil-in-water nanoemulsions using dual-channel microfluidization. These emulsifiers were either amphiphilic biopolymers (whey protein and gum arabic) or biosurfactants (quillaja saponin and soy lecithin). Differences in the surface activities of these emulsifiers were characterized using interfacial tension measurements. The influence of emulsifier type, concentration, and homogenization pressure on the efficiency of nanoemulsion formation was examined. The long-term stability of the fabricated nanoemulsions was also monitored during storage at ambient temperature. For all of the natural emulsifiers, nanoemulsions could be produced by dual-channel microfluidization, with the mean particle diameter decreasing with increasing emulsifier concentration and homogenization pressure. Whey protein isolate and quillaja saponin were more effective at forming nanoemulsions containing fine droplets than gum arabic and soy lecithin, with a lower amount of emulsifier required and smaller droplets being produced. This effect was attributed to faster emulsifier adsorption and a greater reduction in interfacial tension leading to more efficient droplet disruption within the homogenizer for saponins and whey proteins. This study highlights the potential of dual-channel microfluidization for efficiently producing label-friendly nanoemulsions from natural emulsifiers.
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•Dual-channel microfluidization could be used to efficiently produce nanoemulsions.•Nanoemulsions (d < 200 nm) could be prepared from most natural emulsifiers.•Droplet size decreased with homogenization pressure and emulsifier level.•Whey protein and saponin were more effective than gum arabic and lecithin.
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