Ultrafast Near‐Infrared Light‐Triggered Intracellular Uncaging to Probe Cell Signaling

The possibility of regulating cell signaling with high spatial and temporal resolution within individual cells and complex cellular networks has important implications in biomedicine. This article demonstrates a general strategy that uses near‐infrared tissue‐penetrating laser pulses to uncage biomolecules from plasmonic gold‐coated liposomes, i.e., plasmonic liposomes, to activate cell signaling in a nonthermal, ultrafast, and highly controllable fashion. Near‐infrared picosecond laser pulse induces transient nanobubbles around plasmonic liposomes. The mechanical force generated from the collapse of nanobubbles rapidly ejects encapsulated compound within 0.1 ms. This article shows that single pulse irradiation triggers the rapid intracellular uncaging of calcein from plasmonic liposomes inside endolysosomes. The uncaged calcein then evenly distributes over the entire cytosol and nucleus. Furthermore, this article demonstrates the ability to trigger calcium signaling in both an immortalized cell line and primary dorsal root ganglion neurons by intracellular uncaging of inositol triphosphate (IP₃), an endogenous cell calcium signaling second messenger. Compared with other uncaging techniques, this ultrafast near‐infrared light‐driven molecular uncaging method is easily adaptable to deliver a wide range of bioactive molecules with an ultrafast optical switch, enabling new possibilities to investigate signaling pathways within individual cells and cellular networks.     

Superparamagnetic bimetallic iron-palladium nanoalloy: synthesis and characterization

Iron-palladium nanoalloy in the particle size range of 15-30?nm is synthesized by the relatively low temperature thermal decomposition of coprecipitated [Fe(Bipy)(3)]Cl(2) and [Pd(Bipy)(3)]Cl(2) in an inert ambient of dry argon gas. The silvery black Fe-Pd alloy nanoparticles are air-stable and have been characterized by EDX-RF, XRD, AFM, TEM, magnetometry, (57)Fe M?ssbauer and impedance spectroscopy. This Fe-Pd nanoalloy is in single phase and contains iron sites having up to 11 nearest-neighboring atoms. It is superparamagnetic in nature with high magnetic susceptibility, low coercivity and hyperfine field.     

A novel method for optimal coordination of directional overcurrent relays considering their available discrete settings and several operation characteristics

For optimal coordination of directional overcurrent relay we propose to consider operation characteristics, pickup current and time multiplier setting of relays as optimization parameters. Each parameter is optimized independently with the aid of linear formulation of the coordination problem. First, optimal discrete values of pickup current are selected. Second, adequate operation time characteristics of relays are selected. Third, optimal discrete values of time multiplier setting are determined. The proposed method is tested on two networks: an 8-bus system and the IEEE 30-bus system. Its performances are evaluated and compared with those of the linear and nonlinear programming techniques.     

Microstructural and chemical variation of TiO2 electrodes in DSSCs after ethanol vapour treatment

TiO₂ based dye-sensitized solar cells (DSSCs) have great potential to solve many energy challenges, however, their low energy conversion rate is still a barrier for further applications. Ethanol vapour post-treatment can improve the DSSC's conversion efficiency without changing its architecture, and a stable 2–3% improvement was found in our experiments. Microstructural and chemical factors were investigated using scanning electron microscopy and analytical electron microscopy on treated and untreated electrodes. The vapour treatment improved the porosity and surface-to-volume ratio of the TiO₂ particles, decreased electron transport loss between TiO₂ and fluorine doped tin oxide, and increased hydroxyl sites on the TiO₂ particle's surface. The modification therefore enhanced the dye uptake and dye–TiO₂ coupling, and it reduced the energy loss during the carrier transfer.     

Single step hydrothermal synthesis of 3D urchin like structures of AACH and aluminum oxide with thin nano-spikes

3D urchins like ammonium aluminum carbonate hydroxide (AACH) nanostructures with nano-spikes of dia. 20–30 nm were synthesized by a simple, single step hydrothermal technique by using aluminum nitrate and urea as precursor materials. It was found that morphology of the produced structure strongly depends upon the urea concentration. With increasing the amount of urea, the AACH particles having embedded rods like surface features transformed into 3D urchins. The added urea decomposed during hydrothermal treatment and increased the pH of the solution, which affected the morphology of the produced nanostructures. SEM, XRD, FTIR and TGA were employed to characterize the produced structures. On heating, the volatile ingredients of AACH were removed, leaving behind the alumina urchins.     

Energy analysis and modeling of a solar assisted house heating system with a heat pump and an underground energy storage tank

An analytical model is presented and analyzed to predict the long term performance of a solar assisted house heating system with a heat pump and an underground spherical thermal energy storage tank. The system under investigation consists of a house, a heat pump, solar collectors and a storage tank. The present analytical model is based on a proper coupling of the individual energy models for the house, the heat pump, useful solar energy gain, and the transient heat transfer problem for the thermal energy storage tank. The transient heat transfer problem outside the energy storage tank is solved using a similarity transformation and Duhamel’s superposition principle. A computer code based on the present model is used to compute the performance parameters for the system under investigation. Results from the present study indicate that an operational time span of 5–7 years will be necessary before the system under investigation can attain an annually periodic operating condition. Results also indicate a decrease in the annually minimum value of the storage tank temperature with a decrease in the energy storage tank size and/or solar collector area.     

Leveraging parallel computing in multibody dynamics

At a time when sequential computing is limited to marginal year-to-year gains in speed, multi- and many-core architectures provide teraflop-grade performance to cost-conscious users. The ongoing shift to parallel computing spurs new research into solution methods that emphasize algorithmic concurrency. It also provides an opportunity to revisit complex real-life applications whose solutions have been until recently infeasible due to prohibitively heavy computational burdens. This paper concentrates on the use of commodity parallel computing in the field of multibody dynamics by illustrating how many-body frictional-contact dynamics, fluid–solid interaction analysis, and proximity computation have benefited from parallel computing. Preliminary results are encouraging and show one to two orders of magnitude reductions in simulation times. A set of open questions and final remarks round up the contribution.     

A scalable parallel method for large collision detection problems

This paper discusses a parallel collision detection algorithm. Implemented using software executed on ubiquitous Graphics Processing Unit (GPU) cards, the algorithm demonstrates two orders of magnitude speedup over a state-of-the art sequential implementation when handling multimillion object collision detection tasks. GPUs are composed of many (on the order of hundreds) scalar processors that can simultaneously execute an operation; this strength is leveraged in the proposed algorithm, which combines the use of multiple CPU cores with multiple GPUs. The software implementation of the algorithm can be used to detect collisions between five million objects in less than two seconds and was used to detect 1.4 billion contact events in less than 40 seconds. A spherical padding approach is used to represent surface geometries as large collections of spheres when dealing with collision detection between bodies with complex geometries. The proposed methodology is expected to be relevant in computational mechanics with applications in granular flow dynamics and smoothed particle hydrodynamics (SPH), where the number of contact events ranges from millions to billions.     

A Load Balanced Task Scheduling Heuristic for Large-Scale Computing Systems

Optimal task allocation in Large-Scale Computing Systems (LSCSs) that endeavors to balance the load across limited computing resources is considered an NP-hard problem. MinMin algorithm is one of the most widely used heuristic for scheduling tasks on limited computing resources. The MinMin minimizes makespan compared to other algorithms, such as Heterogeneous Earliest Finish Time (HEFT), duplication based algorithms, and clustering algorithms. However, MinMin results in unbalanced utilization of resources especially when majority of tasks have lower computational requirements. In this work we consider a computational model where each machine has certain bounded capacity to execute a predefined number of tasks simultaneously. Based on aforementioned model, a task scheduling heuristic Extended High to Low Load (ExH2LL) is proposed that attempts to balance the workload across the available computing resources while improving the resource utilization and reducing the makespan. ExH2LL dynamically identifies task-to-machine assignment considering the existing load on all machines. We compare ExH2LL with MinMin, H2LL, Improved MinMin Task Scheduling (IMMTS), Load Balanced MaxMin (LBM), and M-Level Suffrage-Based Scheduling Algorithm (MSSA). Simulation results show that ExH2LL outperforms the compared heuristics with respect to makespan and resource utilization. Moreover, we formally model and verify the working of ExH2LL using High Level Petri Nets, Satisfiability Modulo Theories Library, and Z3 Solver.