Colloidal swarms can settle faster than isolated particles

Colloid sedimentation has played a seminal role in the development of statistical physics thanks to the celebrated experiments by Perrin, which gave a concrete demonstration of molecular reality. Recently, the investigation of sedimentation equilibrium has provided valuable information on a wide class of systems, ranging from simple colloids to active particles and biological fluids [1]. Yet, many aspects of the sedimentation kinetics deserve to be further investigated. Here we present some rather surprising results concerning the effect of interactions on particle settling [2]. Usually, the settling velocity of a colloidal suspension decreases with concentration: this well-known effect is called “hindered’’ settling. By experimenting on model colloids in which depletion forces can carefully be tuned, we conversely show that attractive interactions consistently “promote particle settling, so much that, close to a phase-separation line, the sedimentation velocity of a moderately concentrated dispersion can even exceed its single-particle value. At larger particle volume fraction , however, hydrodynamic hindrance eventually takes over. Hence, v() actually displays a non-monotonic trend that may threaten the stability of the settling front to thermal perturbations. By discussing a representative case, we show that these results are relevant to the investigation of protein weak association effects by ultracentrifugation. References. [1] R. Piazza, Reports of Progress in Physics, 2014, 77, 056602. [2] E. Lattuada, S. Buzzaccaro, R. Piazza, Phys. Rev. Lett. 2016, 116, 03830

Hyperbranched DNA clusters

Taking advantage of the base-pairing specificity and tunability of DNA interactions, we investigate the spontaneous formation of hyperbranched clusters starting from purposely designed DNA tetravalent nanostar monomers, encoding in their four sticky-ends the desired binding rules. Specifically, we combine molecular dynamics simulations and Dynamic Light Scattering experiments to follow the aggregation process of the DNA nanostars at different concentrations and temperatures. At odd with the Flory-Stockmayer predictions, we find that, even when all possible bonds are formed, the system does not reach percolation due to the presence of intracluster bonds. We present an extension of the Flory-Stockmayer theory that properly describes the numerical and the experimental results.Comment: The Supplementary Information is included in the pdf fil

Tardive dyskinesia and DRD2, DRD3, DRD4, 5-HT2A variants in schizophrenia: an association study with repeated assessment.

We performed an association study between four candidate genes, DRD2, DRD3, DRD4 and 5-HT2A for the presence of tardive dyskinesia (TD) on 84 patients with residual schizophrenia. The sample was evaluated again for the presence of TD after an interval of 3 years. The first group did not exhibit TD in either observation ( n =34) while in the second group of patients exhibited TD in at least one of the observations ( n =20+18). The clinical and socio-demographic characteristics were not significantly different between the two groups; the genetic analysis revealed a significant correlation between the C/C genotype of 5-HT2A and TD ( p =0.017). An association trend was observed between the 'short' variant of DRD4 and TD ( p =0.022). We did not observe any significant association for the DRD2 and DRD3 polymorphisms

Colloidal Swarms Can Settle Faster than Isolated Particles: Enhanced Sedimentation near Phase Separation

By experimenting on model colloids where depletion forces can be carefully tuned and quantified, we show that attractive interactions consistently “promote” particle settling, so much that the sedimentation velocity of a moderately concentrated dispersion can even exceed its single-particle value. At larger particle volume fraction ϕ, however, hydrodynamic hindrance eventually takes over. Hence, v(ϕ) actually displays a nonmonotonic trend that may threaten the stability of the settling front to thermal perturbations. Finally, by discussing a representative case, we show that these results are relevant to the investigation of protein association effects by ultracentrifugation

A new method for the determination of very small Γ γ

We present a new method for the measurement of very small Γγ partial width that is important for the synthesis of elements in astrophysics. The method is based on the simultaneous detection of scattered beam, residual nucleus and decay γ rays. This method is optimized for the use of the CHIMERA detector at LNS. Experimental details are described

Adherence issues related to sublingual immunotherapy as perceived by allergists

Objectives: Sublingual immunotherapy (SLIT) is a viable alternative to subcutaneous immunotherapy to treat allergic rhinitis and asthma, and is widely used in clinical practice in many European countries. The clinical efficacy of SLIT has been established in a number of clinical trials and meta-analyses. However, because SLIT is self-administered by patients without medical supervision, the degree of patient adherence with treatment is still a concern. The objective of this study was to evaluate the perception by allergists of issues related to SLIT adherence. Methods: We performed a questionnaire-based survey of 296 Italian allergists, based on the adherence issues known from previous studies. The perception of importance of each item was assessed by a VAS scale ranging from 0 to 10. Results: Patient perception of clinical efficacy was considered the most important factor (ranked 1 by 54% of allergists), followed by the possibility of reimbursement (ranked 1 by 34%), and by the absence of side effects (ranked 1 by 21%). Patient education, regular follow-up, and ease of use of SLIT were ranked first by less than 20% of allergists. Conclusion: These findings indicate that clinical efficacy, cost, and side effects are perceived as the major issues influencing patient adherence to SLIT, and that further improvement of adherence is likely to be achieved by improving the patient information provided by prescribers. © 2010 Scurati et al, publisher and licensee Dove Medical Press Ltd

Thermophoresis in self-associating systems: probing poloxamer micellization by opto-thermal excitation

Due to its exquisite sensitivity to interfacial properties, thermophoresis, i.e., particle motion driven by thermal gradients, can provide novel, exclusive, and often surprising information on the structural properties of colloidal or macromolecular fluids and on particle/solvent interactions at the nanoscale. Here, by using an all-optical thermal excitation technique, thermal lensing, we show that thermophoresis can be profitably exploited to investigate the self-association of an amphiphilic block copolymer, poloxamer P407, which takes place above a concentration-dependent critical micellization temperature (cmt). In particular we show that, around and above the cmt, the direction of the poloxamer thermophoretic motion displays a remarkable double sign inversion, which is fully correlated with a peak in the thermal expansivity of the solution marking the progressive dehydration of the propylene oxide groups of P407 and their incorporation into the micellar core. This rather puzzling behaviour of the thermophoretic mobility and of the Soret coefficient in the P407 micellization region can tentatively be explained by properly taking into account the temperature-dependent balance between micellized and nonassociated poloxamer chains

Compressive yield stress of depletion gels from stationary centrifugation profiles

We have investigated the stationary sedimentation profiles of colloidal gels obtained by an arrested phase-separation process driven by depletion forces, which have been compressed either by natural gravity or by a centrifugal acceleration ranging between 6g and 2300g. Our measurements show that the gel rheological properties display a drastic change when the gel particle volume fraction exceeds a value øc, which barely depends on the strength of the interparticle attractive forces that consolidate the network. In particular, the gel compressive yield stress , which increases as for , displays a diverging behaviour for , with an asymptotic value that is close to the random close packing value for hard spheres. The evidence we obtained suggests that basically coincides with the liquid (colloid-rich) branch of the metastable coexistence curve, rather than with the lower (and Ï-dependent) values expected for an attractive glass line penetrating inside the coexistence region

Optimal Resource Allocation of Cloud-Based Spark Applications

Nowadays, the big data paradigm is consolidating its central position in the industry, as well as in society at large. Lots of applications, across disparate domains, operate on huge amounts of data and offer great advantages both for business and research. According to analysts, cloud computing adoption is steadily increasing to support big data analyses and Spark is expected to take a prominent market position for the next decade. As big data applications gain more and more importance over time and given the dynamic nature of cloud resources, it is fundamental to develop an intelligent resource management system to provide Quality of Service guarantees to end-users. This paper presents a set of run-time optimization-based resource management policies for advanced big data analytics. Users submit Spark applications characterized by a priority and by a hard or soft deadline. Optimization policies address two scenarios: i) identification of the minimum capacity to run a Spark application within the deadline; ii) re-balance of the cloud resources in case of heavy load, minimising the weighted soft deadline application tardiness. The solution relies on an initial non-linear programming model formulation and a search space exploration based on simulation-optimization procedures. Spark application execution times are estimated by relying on a gamut of techniques, including machine learning, approximated analyses, and simulation. The benefits of the approach are evaluated on Microsoft Azure HDInsight and on a private cloud cluster based on POWER8 by considering the TPC-DS industry benchmark and SparkBench. The results obtained in the first scenario demonstrate that the percentage error of the prediction of the optimal resource usage with respect to system measurement and exhaustive search is the range 4%-29% while literature-based techniques present an average error in the range 6%-63%. Moreover, in the second scenario, the proposed algorithms can address complex problems like computing the optimal redistribution of resources among tens of applications in less than a minute with an error of 8% on average. On the same considered tests, literature-based approaches obtain an average error of about 57%