Wetting morphologies on randomly oriented fibers

We characterize the different morphologies adopted by a drop of liquid placed on two randomly oriented fibers, which is a first step toward understanding the wetting of fibrous networks. The present work reviews previous modeling for parallel and touching crossed fibers and extends it to an arbitrary orientation of the fibers characterized by the tilting angle and the minimum spacing distance. Depending on the volume of liquid, the spacing distance between fibers and the angle between the fibers, we highlight that the liquid can adopt three different equilibrium morphologies: (1) a column morphology in which the liquid spreads between the fibers, (2) a mixed morphology where a drop grows at one end of the column or (3) a single drop located at the node. We capture the different morphologies observed using an analytical model that predicts the equilibrium configuration of the liquid based on the geometry of the fibers and the volume of liquid

Knots modify the coil–stretch transition in linear DNA polymers

We perform single-molecule DNA experiments to investigate the relaxation dynamics of knotted polymers and examine the steady-state behavior of knotted polymers in elongational fields. The occurrence of a knot reduces the relaxation time of a molecule and leads to a shift in the molecule's coil-stretch transition to larger strain rates. We measure chain extension and extension fluctuations as a function of strain rate for unknotted and knotted molecules. The curves for knotted molecules can be collapsed onto the unknotted curves by defining an effective Weissenberg number based on the measured knotted relaxation time in the low extension regime, or a relaxation time based on Rouse/Zimm scaling theories in the high extension regime. Because a knot reduces a molecule's relaxation time, we observe that knot untying near the coil-stretch transition can result in dramatic changes in the molecule's conformation. For example, a knotted molecule at a given strain rate can experience a stretch-coil transition, followed by a coil-stretch transition, after the knot partially or fully unties.National Science Foundation (U.S.) (Grant CBET-1602406

Automated Electrokinetic Stretcher for Manipulating Nanomaterials

In this work, we present an automated platform for trapping and stretching individual micro- and nanoscale objects in solution using electrokinetic forces. The platform can trap objects at the stagnation point of a planar elongational electrokinetic field for long time scales, as demonstrated by the trapping of ~100 nanometer polystyrene beads and DNA molecules for minutes, with a standard deviation in displacement from the trap center < 1 micrometer. This capability enables the stretching of deformable nanoscale objects in a high-throughput fashion, as illustrated by the stretching of more than 400 DNA molecules within ~4 hours. The flexibility of the electrokinetic stretcher opens up numerous possibilities for contact-free manipulation, with size-based sorting of DNA molecules performed as an example. The platform described provides an automated, high-throughput method to track and manipulate objects for real-time studies of micro- and nanoscale systems.Comment: 9 pages, 7 figure

Constructing Custom Thermodynamics Using Deep Learning

One of the most exciting applications of AI is automated scientific discovery based on previously amassed data, coupled with restrictions provided by the known physical principles, including symmetries and conservation laws. Such automated hypothesis creation and verification can assist scientists in studying complex phenomena, where traditional physical intuition may fail. Of particular importance are complex dynamic systems where their time evolution is strongly influenced by varying external parameters. In this paper we develop a platform based on a generalised Onsager principle to learn macroscopic dynamical descriptions of arbitrary stochastic dissipative systems directly from observations of their microscopic trajectories. We focus on systems whose complexity and sheer sizes render complete microscopic description impractical, and constructing theoretical macroscopic models requires extensive domain knowledge or trial-and-error. Our machine learning approach addresses this by simultaneously constructing reduced thermodynamic coordinates and interpreting the dynamics on these coordinates. We demonstrate our method by studying theoretically and validating experimentally, the stretching of long polymer chains in an externally applied field. Specifically, we learn three interpretable thermodynamic coordinates and build a dynamical landscape of polymer stretching, including (1) the identification of stable and transition states and (2) the control of the stretching rate. We further demonstrate the universality of our approach by applying it to an unrelated problem in a different domain: constructing macroscopic dynamics for spatial epidemics, showing that our method addresses wide scientific and technological applications

The role of depression, anxiety and illness characteristics on risky sexual behaviour among people with HIV

Background: People living with HIV (PLHIV) have a longer lifespan with treatment and continue to be sexually active. To date, the extent of risky sexual behaviour among local PLHIV and its associated factors were undetermined. Objective: To examine the role of depression, anxiety and illness characteristics on risky sexual behaviour among PLHIV attending care in a Malaysian tertiary reference hospital (N= 406). Methods: It was a cross-sectional study. Subjects were recruited by systematic random sampling. Risky sexual behaviour was determined by using the modified National Youth Risk Behaviour Survey. PHQ-9 and GAD-7 were used to measure the depressive and anxiety symptoms, respectively. Chi-square test was used to examine the association between the variables. Multiple logistic regression was used to examine the predictors of the study. A p value of less than 0.05 was considered significant and odds ratio was used as the measure of risk association. Results: Our study showed that 29.3% had risky sexual behaviour. Meanwhile, 21.9% and 26.4% had depressive and anxiety symptoms, respectively. Risky sexual behaviour was significantly associated with age, religion, education level, duration of HIV diagnosis, depressive and anxiety symptoms. From multivariate logistic regression, duration of HIV diagnosis and anxiety symptoms significantly predicted risky sexual behaviour. Conclusion: This study highlights that a substantial number of PLHIV had risky sexual behaviour and psychological symptoms. It is important for psychological interventions that reduce risky sexual behaviour among PLHIV who attend treatment, especially during the early phase

Mechanical tuning of the evaporation rate of liquid on crossed fibers

We investigate experimentally the drying of a small volume of perfectly wetting liquid on two crossed fibers. We characterize the drying dynamics for the three liquid morphologies that are encountered in this geometry: drop, column and a mixed morphology, in which a drop and a column coexist. For each morphology, we rationalize our findings with theoretical models that capture the drying kinetics. We find that the evaporation rate depends significantly on the liquid morphology and that the drying of liquid column is faster than the evaporation of the drop and the mixed morphology for a given liquid volume. Finally, we illustrate that shearing a network of fibers reduces the angle between them, changes the morphology towards the column state, and so enhances the drying rate of a volatile liquid deposited on it

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong