By analyzing the behavior of membranes without alcohol as a function of the surfactant concentration it is observed that the higher the concentration of ECA 4360, the shorter the coalescence time, which is a non-expected result. This ef- fect was more pronounced up to approximately 5% w/w Adogen 464. Above such concentration, the coalescence times became closer. These results can be understood considering a similar effect described for alcohol in the literature  . Since the surfactant is an amphiphilic molecule, as it is alcohol, it may increase the mutual solubility of the extractant and the diluent, even though it is not used in the system with this purpose. Therefore, the surfactant would leave the interface together with the extractant, thus decreasing the droplet coales- cence time. However, for extractant concentrations higher than approximately 5% w/w, the surfactant concentration becomes insufficient to improve the solva- tion of the extractant in the diluent, leading to an increased extractant concen- tration at the interface and, as a consequence, the effect of the surfactant con-
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In the standard coalescent, each member of a set of (non- recombining) samples can be thought of as traveling inde- pendently backward in time through the generations. A coalescence event occurs if two samples independently “choose” the same parental allele as their ancestor. The wait- ing time until the next coalescence depends only on the num- ber of remaining samples but, importantly, not on “where” the samples are currently found (i.e., in which individual organisms). However, for diploids with a low frequency of sex, the “where” information is crucial (Bengtsson 2003; Ceplitis 2003; Hartﬁeld et al. 2016). For example, two sam- ples can be the two haplotypes found in a single diploid in- dividual (which we denote as “a paired sample”) or they can each come from different individuals (which we denote as “two unpaired samples”). The two haplotypes within a paired sample do not travel back in time independently, but rather they travel together for as long as reproduction is asexual. Coalescence between them is not possible for all the asexual generations they remain paired (ignoring gene conversion). A sexual event splits a paired sample into two unpaired sam- ples that can then coalesce in a subsequent generation. For this reason, paired samples are expected to have longer av- erage coalescence times than unpaired samples and low sex increases average coalescence time compared to high sex (Balloux et al. 2003; Bengtsson 2003; Ceplitis 2003). How- ever, if the frequency of mitotic gene conversion is high rel- ative to the frequency of sex, then these predictions are reversed (Hartﬁeld et al. 2016). In this case, paired samples can coalesce faster than unpaired samples because each gen- eration the samples are paired provides an opportunity for coalescence via mitotic gene conversion.
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behavior along the chromosome but models additional co- alescence events that make it a closer approximation to the ARG. Speciﬁcally, in the back-in-time formulation of the SMC9, coalescence is allowed between lineages containing either overlapping or adjacent ancestral material. In the se- quential formulation of the pairwise SMC9, this means that not every recombination event necessarily produces a new pairwise coalescence time, since two lineages created by a recombination event can coalesce back together. Figure 1 shows the transitions that are permitted under the back- in-time and sequential formulations of the pairwise ARG, SMC, and SMC9. The sequentially Markov coalescent mod- els have been used in many recently introduced population- genetic, model-based inference procedures, including the pairwise SMC (PSMC) model (Li and Durbin 2011), the multiple SMC (MSMC) model (Schiffels and Durbin 2014), diCal (Sheehan et al. 2013), coalHMM (Hobolth et al. 2007; Dutheil et al. 2009), and ARGWeaver (Rasmussen et al. 2014), and in a study of past human demography based on tracts of identity by state (Harris and Nielsen 2013).
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descendants, and so evidence of the recombination event is lost. By reducing the effective recombination rate, diver- gence between the X and Y is enhanced. We can arrive at the same conclusion by considering the process from the coales- cent perspective. When we sample one gene from an X chro- mosome and one from a Y, with sex-antagonistic selection they are likely also to differ with respect to the allele they are linked to at locus A. To coalesce, the genes have to reside on the same genetic background at both the SDR and locus A, and for that to happen at least two recombination events must occur. That increases the coalescence time and hence the divergence between X and Y in the region between the SDR and locus A. The reduction in the effective recombina- tion rate between X and Y is strongest at neutral sites that are closely linked to locus A. Essentially the same mecha- nism produces a similar pattern of divergence in neutral polymorphisms near loci under local adaptation (Barton and Bengtsson 1986; Guerrero et al. 2012b).
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Finite one-dimensional stepping-stone models have tat). Absolute density-dependent population regulation been analyzed by Maruyama (1970c), Fleming and Su is assumed. Each individual occupies a space of width (1974), and Male´cot (1975). These analyses derive 1/N, from which all other individuals are excluded. The expectations for classical measures such as the covari- structure of the population is a one-dimensional lattice, ance in gene frequencies across demes. Nagylaki and as in the voter model (Holley and Liggett 1975), a Barcilon (1988) have considered probabilities of iden- contact-process model used in many ecological applica- tity in a semiinfinite linear habitat. Maruyama (1971) tions (Durrett and Levin 1994). The distribution of has also derived probabilities of identity for a continu- coalescence times is found using a continuous approxi- ous population on a torus and the rate of decrease in mation. Another way to think of the model is as a step- genetic variability in a finite two-dimensional popula- ping-stone model consisting of N demes, each of size 1. tion (Maruyama 1970d, 1972). Hey (1991) has com- Generations are nonoverlapping. Each individual pared the mean coalescence time for a pair of sequences produces a very large number of gametes, which are sampled from opposite ends of a finite linear stepping dispersed according to a normal distribution centered stone with that of a pair sampled at random from the at the location of the individual and with variance entire population. The result that coalescence times are 2 2
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Coalescence time, including the time interval between the detachment of drop from nozzle tip towards the interface and entire coalescence with it was measured. It was named the first step of coalescence time. Upon completion of the first step of the process, the overall time of subsequent steps was measured separately as partial coalescence time . The sum of these two amounts gave the total coalescence time. Order of experiments was as follows:
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We applied our method to data from 10 of the 179 human genomes that were sequenced at low coverage and phased as part of the 1000 Genomes pilot project. Five of the individuals were Yorubans from Ibadan, Nigeria (YRI) and ﬁve were Utah residents of central European descent (CEU) (1000 Genomes Project Consortium 2010). To minimize potential confounding effects from natural selection, we chose a 3-Mb region on chromosome 1 with no genes and then used the middle 2 Mb for analysis. We used the human reference (version 36) to create a full multiple-sequence alignment of 10 haplotypes (ﬁve diploid individuals) for each of the CEU and YRI populations. Although we ﬁltered out unphased individuals and sites, the ﬁnal sequences are based on low-coverage short read data, so phasing and imputation errors could affect the accuracy of our coalescence time inference. We assumed a per-generation mutation rate of m = 1.25 · 10 28 per site, which is consistent with recent studies of de novo mutation in human trios (Awadalla et al. 2010; Roach et al. 2010; Kong et al. 2012), and a mutation transition matrix estimated from the human and the chimp reference genomes (shown in File S1). For simplicity, we assumed that the per-generation recombination rate r be- tween consecutive bases is constant and equal to m. The gen- eration time was assumed to be 25 years. For a reference population size, we used N ref = 10,000.
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momenta to produce a ﬁnal-state meson or baryon, this can happen at a time scale in which the partons rescatter and generate a thermal medium expanding with a collective radial ﬂow . Initial hard processes between colliding nucleons producing minijet partons provide a dominant contribu- tion to hadron spectra at high transverse momentum.
The classical notion of the coalescence of two droplets of the same radius R is that surface tension drives an initially singular flow. In this Letter we show, using molecular dynamics simulations of coalescing water nano-droplets, that after single or multiple bridges form due to the presence of thermal capillary waves, the bridge growth commences in a thermal regime. Here, the bridges expand linearly in time much faster than the viscous-capillary speed due to collective molecular jumps near the bridge fronts. Transition to the classical hydrodynamic regime only occurs once the bridge radius exceeds a thermal length scale l T ∼
A second form of the transition density depends on the coalescent genealogy of the population. The Kingman coalescent is a death process which counts the number of lineages back in time in a coalescent tree beginning with a finite or infinite number of leaves. The death rates are k 2 , k = 2, 3, . . .. Let L θ (t) be the number of non-mutant lineages at time t back in a coalescent tree, beginning with L θ (0) leaves, which can be finite or infinity. Mutations occur according to a Poisson process of rate θ/2 on the edges of the coalescent tree, so the death rate of non-mutant lineages is k 2
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Considerable research has already been carried out on droplet collision. It is a widely accepted fact that binary droplet collisions exhibit five distinct regimes of outcomes, namely (i) coalescence after minor deformation, (ii) bouncing, (iii) coalescence after substantial deformation, (iv) reflexive separation, and (v) stretching separation. The collision process is usually characterized by three parameters: the Weber number, the impact parameter, and the droplet size ratio. Boundary curves between the regions of possible outcomes in terms of these parameters are proposed by several authors (Ashgriz and Poo, 1990; Brazier-Smith et al., 1972; Estrade et al., 1999). Extensive experimental in- vestigation was conducted and several outcome maps are presented in Qian and Law (1997). Further experimental studies were reviewed by Orme (1997). Detailed description of each collision outcome regime is provided in Section 3 together with the boundary curves which are used in our model.
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The first regime is the so called total coalescence regime and is characterised by very small drops that coalescence without producing any secondary drops or entrapping any bubbles. This regime has been previously described and is Oh number limited. A major change to the classification of the flow regimes involves the splitting of the composed regime into two separate regimes. The composed is split into the primary microbubble formation regime and primary vortex ring regime. In the primary microbubble formation regime an air film becomes entrapped between the impacting drop and the pool which initially prevents coalescence. When the film ruptures numerous microbubbles are formed. This is where the coalescence cascade and Mesler type bubble entrapment occur. The second regime that makes up the old composed regime is the primary vortex ring regime. Here large coherent vortex rings are formed without any significant bubble entrapment or jetting.
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This paper presents a novel application of particle im- age velocimetry to the impact and coalescence of a falling droplet and a sessile droplet. The experimental setup is simple and can be applied to systems with non-matching refractive index. Briefly, these experiments consisted of impacting droplets on to a transparent substrate in or- der to observe the internal dynamics through and from below the substrate. In this way, the differences of re- fractive index do not distort the view, no reconstruc- tion algorithms are required and a clear visualization can be achieved in a two-phase system (air/liquid). In addition, this work combined shadowgraph imaging on a side-view plane with digital image analysis to extract the traditional geometric properties of the coalescence phenomenon such as dynamic contact angles, composite diameters and neck height and width. Droplets 2.4 mm in initial diameter with Newtonian properties were used in these experiments. Experiments were carried out vary- ing the sideways separation between the sessile and the impacting droplet from the axisymmetric drop on drop case up to the point (≈ 4.3 mm) of no coalescence. The experimental results are compared with numerical simu- lations based on the lattice Boltzmann method.
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While the type of loading plays a vital part in the fatigue process, this research concentrates on the study of material properties examined under laboratory conditions. In this case, the d ata come from sinusoidal loading with a well defined maximum, minimum and a constant controlled stress range. Time may thus be represented in terms of number of cycles, which is well defined, and is denoted N. It is clear th at using N as tim e brings with it the implicit assumption th a t the frequency of stressing is unim portant, and in any case can be taken account of. In practice this is a reasonable assumption. Increasing the frequency of the stressing under laboratory conditions allows simulation of loading which would be experienced in real conditions over many years.
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Table 4 also shows estimates of liquid velocity from Eq. (6), using a C value of 0.2 (Santos et al., 2008), intimating the development of a co-current like flow regime for the > 30% gas volume fraction runs with liquid velocities increasing with gas volume fraction, driven by the liquid surrounding and above the leading slugs being accelerated upwards (e.g., Mayor et al. 2008b), in contrast to the quasi-stagnant liquid for the smaller gas fraction experiments. Fig. 6e and 6f show examples of coalescence for the largest gas volume fraction experimental conditions (> 55 % gas volume fraction), again with coalescence being driven by expansion of the trailing slug. There are, in addition, large temporal fluctuations in the ascent velocities of all slugs in the column, due to drainage of fluid down the tube walls following burst events, or a resonant bounding of the experimental apparatus, causing significant
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Side-view shadowgraph pictures of the same experi- ments were analyzed to determine the geometrical char- acteristics of the coalescence process. For small droplet separations, the impacting droplet lands entirely on pre- wetted substrate, and the spreading process is similar to the axisymmetric case, leading to a circular final foot- print. For larger separations, the impacting droplet lands on dry substrate, then spreads into the sessile droplet. In such cases, the growth of the neck height, in particular, highlights the difference between this impact-driven coa- lescence and the coalescence of two static droplets. The neck height initially increases more rapidly in the impact- driven case, as the gap between the droplets is closed by the rapid spreading of the impacting droplet. The neck then becomes difficult to distinguish from the side view, and the height levels off at the height of the fully spread impacting droplet, before becoming more distinct again as the droplet regains its height and coalescence proceeds as in the static droplet case. When the droplet separation is close to the maximum that still results in contact be- tween the droplets, the impacting droplet is fully spread when it meets the sessile droplet and coalescence then proceeds in a very similar way to the case of two static droplets.
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This study has some limitations. First, the study was conducted in a limited number of patients monitored for pulmonary congestion by EVLW. Larger studies are needed for clinical validation. Second, the scoring ana- lyses was performed on single frames, and an implemen- tation of our software to multi-frame analysis is the planned as a next step in order to analyze the entire re- spiratory cycle and minimize operator biases due to frame selection. Third, the computer-aided analysis (QLUSS) was performed in post-processing on single frames previously stored and future implementation on ultrasound machines might allow a real-time analysis. Fourth, QLUSS is not useful in pleural effusion or consolidations.
The peak instantaneous intensities measured in DI water, ethanol and isoamyl alcohol are shown in Table 2. The local ultrasonic field in the XUB25 ultrasonic bath can be described as chaotic with intensities which vary substantially both with position and time. This complicates the comparison of measurements taken across the range of solvents under investigation. As noted earlier in instances where a large number of cavitation bubbles may be generated and bubble shielding effects can occur, see for example Nguyen et al. 16 Therefore, although a broadly similar magnitude of ultrasonic intensity can be inferred from this data, in solvents with a lower cavitation threshold a larger population of bubbles may be generated under
are added to control their stability [28-34]. In a stable emulsion, the interfacial area and free energy of the dispersion phase is decreased . The time required to get the phases separated is considered as the stability of emulsion. The stability depends upon size, size distribution of drops, and viscosity of continuous media and over the dispersed phase, Different emulsion failure process can be represented by some of the instability of emulsion which produced layers separation in the emulsions, the sedimentation/creaming, aggregation or coalescence is the major factors which produce instability in the emulsion process [36-37]. In this study I have to determine the validity of the emulsions and yield stress which is very important for health aspects. And also show the morphology of the emulsions with volume fraction, droplets size droplets distribution, coalescence and stability of emulsions. Stability of the emulsion is directly depending upon droplets size and its distribution.
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Electric fields have long been used to manipulate microdroplets. The following aspects of single and multiple microdroplet dynamics has been studied: droplet transport under electrophoretic and dielectrophoretic forces , droplet deformation and breakup [2,3], electrically enhanced coalescence of droplets [4,5], and partial coalescence of droplets [6,7]. Creating an emulsion is another application of an electric field based microdroplet manipulation. An emulsion is a mixture of two immiscible liquid such as water in oil system. Emulsions are widely used in medicines, detergents, paints, lubricants, and foods [8-11]. Traditional methods for making emulsions involve mechanical and fluid devices, ultrasound and chemical modification by surfactants addition. Mechanical agitation of an emulsification is widely used in many applications for the simplicity despite the inefficient energy consumption. Alternative approaches include a microfluidic device to generate an emulsion by the action of capillary or hydrodynamic forces [12-16] and the use of electric forces [17,18].
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