In situ observation of synthesized nanoparticles in ultra-dilute aerosols via X-ray scattering

In-air epitaxy of nanostructures (Aerotaxy) has recently emerged as a viable route for fast, large-scale production. In this study, we use small-angle X-ray scattering to perform direct in-flight characterizations of the first step of this process, i.e., the engineered formation of Au and Pt aerosol nanoparticles by spark generation in a flow of N₂ gas. This represents a particular challenge for characterization because the particle density can be extremely low in controlled production. The particles produced are examined during production at operational pressures close to atmospheric conditions and exhibit a lognormal size distribution ranging from 5–100 nm. The Au and Pt particle production and detection are compared. We observe and characterize the nanoparticles at different stages of synthesis and extract the corresponding dominant physical properties, including the average particle diameter and sphericity, as influenced by particle sintering and the presence of aggregates. We observe highly sorted and sintered spherical Au nanoparticles at ultra-dilute concentrations (< 5 × 10⁵ particles/cm³) corresponding to a volume fraction below 3 × 10^–10, which is orders of magnitude below that of previously measured aerosols. We independently confirm an average particle radius of 25 nm via Guinier and Kratky plot analysis. Our study indicates that with high-intensity synchrotron beams and careful consideration of background removal, size and shape information can be obtained for extremely low particle concentrations with industrially relevant narrow size distributions.

     

Enhanced Multi-attribute Combinative Double Auction (EMCDA) for Resource Allocation in Cloud Computing

Wireless Personal Communications - Cloud computing is a growing technology where lot of heterogeneous resources are available and large amount of requests are submitted by the customers...     

Evaluation of the degree of rate control via automatic differentiation

The degree of rate control (DRC) quantitatively identifies the kinetically relevant (sometimes known as rate-limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, for example, with finite differences (FDs). Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this study, we demonstrate the use of automatic differentiation (AD) in the evaluation of the DRC. AD libraries are increasingly available through modern machine learning frameworks. Compared with the FDs, AD provides solutions with higher accuracy with lower computational cost. We demonstrate applications in steady-state and transient kinetics. Furthermore, we illustrate a hybrid local-global sensitivity analysis method, the distributed evaluation of local sensitivity analysis, to assess the importance of kinetic parameters over an uncertain space. This method also benefits from AD to obtain high-quality results efficiently.     

A Light Weight Secure Communication Scheme for Wireless Sensor Networks

Wireless Personal Communications - The majority of security systems for wireless sensor networks are based on symmetric encryption. The main open issue for these approaches concerns the...     

The generalized discrete ‐centroid problem

The ‐centroid problem or leader–follower problem is generalized considering different customer choice rules where a customer may use facilities belonging to different firms, if the difference in travel distance (or time) is small enough. Assuming essential goods, some particular customer choice rules are analyzed. Linear programming formulations for the generalized ‐medianoid and ‐centroid problems are presented and an exact solution approach is applied. Some computational examples are included.     

Neutrophils in Tuberculosis: Cell Biology,Cellular Networking and Multitasking in Host Defense

Neutrophils readily infiltrate infection foci, phagocytose and usually destroy microbes. In tuberculosis (TB), a chronic pulmonary infection caused by Mycobacterium tuberculosis (Mtb), neutrophils harbor bacilli, are abundant in tissue lesions, and their abundances in blood correlate with poor disease outcomes in patients. The biology of these innate immune cells in TB is complex. Neutrophils have been assigned host-beneficial as well as deleterious roles. The short lifespan of neutrophils purified from blood poses challenges to cell biology studies, leaving intracellular biological processes and the precise consequences of Mtb–neutrophil interactions ill-defined. The phenotypic heterogeneity of neutrophils, and their propensity to engage in cellular cross-talk and to exert various functions during homeostasis and disease, have recently been reported, and such observations are newly emerging in TB. Here, we review the interactions of neutrophils with Mtb, including subcellular events and cell fate upon infection, and summarize the cross-talks between neutrophils and lung-residing and -recruited cells. We highlight the roles of neutrophils in TB pathophysiology, discussing recent findings from distinct models of pulmonary TB, and emphasize technical advances that could facilitate the discovery of novel neutrophil-related disease mechanisms and enrich our knowledge of TB pathogenesis.     

Computational modelling of water flow inside laboratory Knelson concentrator bowl

Enhanced gravity concentrators such as Knelson concentrator (KC) are extensively used in the mineral processing industry. The complexities of KC bowl geometry and variation of feed characteristics have forced process engineers to design empirically new units using laboratory and pilot-scale Knelson concentrators. However, numerical modelling methods such as computational fluid dynamics (CFD) and discrete element method (DEM) provide a better insight of flow behaviour of fluid and particulate solid phases inside these processing units. This article reports findings of CFD simulations for single-phase water flow inside the laboratory KC. An available standard 7.5-cm laboratory KC bowl was numerically simulated using realisable k-ε turbulence model to resolve the turbulence dispersion of existing transitional flow regime. The effects of relative centrifugal force (RCF) intensity and bed fluidisation water flow rate on the water velocity and pressure distributions were studied. Simulations confirmed the swirling flow pattern governing inside the bowl. The results revealed that the impact of RCF intensity on the water field values is greater than that of bed fluidisation water flow rate. Both velocity and pressure variations inside the bowl rings followed a linear trend.