Oscillations of a gas pocket on a liquid-covered solid surface

The dynamic response of a gas bubble entrapped in a cavity on the surface of a submerged solid subject to an acoustic field is investigated in the linear approximation. We derive semi-analytical expressions for the resonance frequency, damping and interface shape of the bubble. For the liquid phase, we consider two limit cases: potential flow and unsteady Stokes flow. The oscillation frequency and interface shape are found to depend on two dimensionless parameters: the ratio of the gas stiffness to the surface tension stiffness, and the Ohnesorge number, representing the relative importance of viscous forces. We perform a parametric study and show, among others, that an increase in the gas pressure or a decrease in the surface tension leads to an increase in the resonance frequency until an asymptotic value is reached

Marginal Release Under Local Differential Privacy

Many analysis and machine learning tasks require the availability of marginal statistics on multidimensional datasets while providing strong privacy guarantees for the data subjects. Applications for these statistics range from finding correlations in the data to fitting sophisticated prediction models. In this paper, we provide a set of algorithms for materializing marginal statistics under the strong model of local differential privacy. We prove the first tight theoretical bounds on the accuracy of marginals compiled under each approach, perform empirical evaluation to confirm these bounds, and evaluate them for tasks such as modeling and correlation testing. Our results show that releasing information based on (local) Fourier transformations of the input is preferable to alternatives based directly on (local) marginals

Minimizing Flow Time in the Wireless Gathering Problem

We address the problem of efficient data gathering in a wireless network through multi-hop communication. We focus on the objective of minimizing the maximum flow time of a data packet. We prove that no polynomial time algorithm for this problem can have approximation ratio less than \Omega(m^{1/3) when $m$ packets have to be transmitted, unless $P = NP$. We then use resource augmentation to assess the performance of a FIFO-like strategy. We prove that this strategy is 5-speed optimal, i.e., its cost remains within the optimal cost if we allow the algorithm to transmit data at a speed 5 times higher than that of the optimal solution we compare to

CD4+ T-cell responses to Epstein-Barr virus (EBV) latent-cycle antigens and the recognition of EBV-transformed lymphoblastoid cell lines

There is considerable interest in the potential of Epstein-Barr virus (EBV) latent antigen-specific CD4$^+$ T cells to act as direct effectors controlling EBV-induced B lymphoproliferations. Such activity would require direct CD4$^+$ T-cell recognition of latently infected cells through epitopes derived from endogenously expressed viral proteins and presented on the target cell surface in association with HLA class II molecules. It is therefore important to know how often these conditions are met. Here we provide CD4$^+$ epitope maps for four EBV nuclear antigens, EBNA1, -2, -3A, and -3C, and establish CD4$^+$ T-cell clones against 12 representative epitopes. For each epitope we identify the relevant HLA class II restricting allele and determine the efficiency with which epitope-specific effectors recognize the autologous EBV-transformed B-lymphoblastoid cell line (LCL). The level of recognition measured by gamma interferon release was consistent among clones to the same epitope but varied between epitopes, with values ranging from 0 to 35% of the maximum seen against the epitope peptide-loaded LCL. These epitope-specific differences, also apparent in short-term cytotoxicity and longer-term outgrowth assays on LCL targets, did not relate to the identity of the source antigen and could not be explained by the different functional avidities of the CD4$^+$ clones; rather, they appeared to reflect different levels of epitope display at the LCL surface. Thus, while CD4$^+$ T-cell responses are detectable against many epitopes in EBV latent proteins, only a minority of these responses are likely to have therapeutic potential as effectors directly recognizing latently infected target cells

The effects of age on associations between markers of HIV progression and markers of metabolic function including albumin, haemoglobin and lipid concentrations.

OBJECTIVES: We investigated whether age modified associations between markers of HIV progression, CD4 T lymphocyte count and HIV RNA viral load (VL), and the following markers of metabolic function: albumin, haemoglobin, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC). METHODS: A retrospective analysis of data from the United Kingdom Collaborative HIV Cohort was carried out. Analyses were limited to antiretroviral-naïve subjects to focus on the impact of HIV disease itself. A total of 16670 subjects were included in the analysis. Multilevel linear regression models assessed associations between CD4 count/VL and each of the outcomes. Statistical tests for interactions assessed whether associations differed among age groups. RESULTS: After adjustment for gender and ethnicity, there was evidence that lower CD4 count and higher VL were associated with lower TC, LDL-C, haemoglobin and albumin concentrations but higher triglyceride concentrations. Age modified associations between CD4 count and albumin (P 50 years, a 50 cells/μL lower CD4 count correlated with a 2.4 [95% confidence interval (CI) 1.7-3.0], 3.6 (95% CI 3.2-4.0) and 5.1 (95% CI 4.0-6.1) g/L lower haemoglobin concentration and a 0.09 (95% CI 0.07-0.11), 0.12 (95% CI 0.11-0.13) and 0.16 (95% CI 0.13-0.19) g/L lower albumin concentration, respectively. CONCLUSIONS: We present evidence that age modifies associations between CD4 count and plasma albumin and haemoglobin levels. A given reduction in CD4 count was associated with a greater reduction in haemoglobin and albumin concentrations among older people living with HIV. These findings increase our understanding of how the metabolic impact of HIV is influenced by age

Efficiency and accuracy of GPU-parallelized Fourier spectral methods for solving phase-field models

Phase-field models are widely employed to simulate microstructure evolution during processes such as solidification or heat treatment. The resulting partial differential equations, often strongly coupled together, may be solved by a broad range of numerical methods, but this often results in a high computational cost, which calls for advanced numerical methods to accelerate their resolution. Here, we quantitatively test the efficiency and accuracy of semi-implicit Fourier spectral-based methods, implemented in Python programming language and parallelized on a graphics processing unit (GPU), for solving a phase-field model coupling Cahn-Hilliard and Allen-Cahn equations. We compare computational performance and accuracy with a standard explicit finite difference (FD) implementation with similar GPU parallelization on the same hardware. For a similar spatial discretization, the semi-implicit Fourier spectral (FS) solvers outperform the FD resolution as soon as the time step can be taken 5 to 6 times higher than afforded for the stability of the FD scheme. The accuracy of the FS methods also remains excellent even for coarse grids, while that of FD deteriorates significantly. Therefore, for an equivalent level of accuracy, semi-implicit FS methods severely outperform explicit FD, by up to 4 orders of magnitude, as they allow much coarser spatial and temporal discretization

Most significant changes experienced by farmers from adopting rainforestation farming

The Visayas State University (VSU) developed the rainforestation farming (RF) system to replace the more destructive forms of kaingin or slash-and-burn practices commonly practiced by farmers and provide them with a stable and higher income. VSU disseminated the technology through training and establishment of demonstration farms coupled with various extension materials. The most important changes experienced by farmers from adopting RF were increase in income, greater social skills, improvement of their water and air conditions, and enhancement of biodiversity in their rainforestation farms

Optimising finishing pig delivery weight : participatory decision problem analysis

The seemingly straightforward question of optimal pig delivery weight is more complex than meets the eye. Despite abundant research insights, the industry continues to request additional applied scientific decision support on the delivery weight problem. The current objective is to investigate whether and how the complex decision of delivery weight can be reshaped (reframed) into a more tangible and comprehensible system of factors that matter for making the right decision. We used a participatory decision problem analysis, which resulted in modelling blueprints that incorporate factors prioritised by stakeholders for determining optimal delivery weights. How to efficiently organise such a 'problem reframing process' is case-specific: it depends on the objective, the initial problem understanding by the stakeholders, and their learning potential. Efficient co-learning is a prerequisite for successful participatory problem analysis. Our study reveals that the first step in such a process of 'problem reframing' should therefore be to answer the question of how to effectively organise co-learning among stakeholders and researchers, instead of starting with a correct and detailed representation of the problem. Useful guidelines for participatory problem reframing processes are (1) providing sufficient participatory learning steps, (2) having few and clearly defined objectives per learning step, (3) providing adapted learning tools per step, (4) establishing a common language and (5) deliberately choosing stakeholders based on prior knowledge of the problem or its context, potential motivation or incentives to be part of the participatory process step and potential role in up-scaling the co-learning process to a larger group of beneficiaries