Acid/base titrations of pico- and femtoliter microsamples have been performed previously using a diffusional microburet (DMB) for reagent delivery in a simple droplet-heptane system (Gratzl, M.; Yi, C. Anal. Chem. 1993, 65, 2085-2088). The lowest delivery rate achieved with a DMB was about 6 fmol/s, which would correspond to about a 1 microL/year volumetric flow rate with a hypothetical equivalent mechanical delivery scheme (Yi, C.; Gratzl, M. Anal. Chem. 1994, 66, 1976-1982). In this work, the feasibility of complexometric titrations in microscopic samples is explored. Stability of pH in the microdroplets required for different determinations and the effects of DMB shank geometry on titration characteristics are also studied. Diffusional microtitrations of Fe(III), Zn(II), and Cu(II) have been performed with EDTA. Xylenol orange and Eriochrome Black T provide clear color changes at the end point of the respective titrations, despite the microscopic size of the samples (between 16 and 1570 pL, corresponding to diameters between 30 and 144 microns). Random errors of the determinations relative to full scale were 6.6% for Fe(III), 5.8% for Cu(II), and 7.9% for Zn(II). The pH required for EDTA titrations of the individual metal ions stays stable in the acidic range. This makes the microscopic titration of a number of metal ions, such as Fe(III), Fe(II), Cu(II), and Pb(II), feasible in a simple droplet-heptane system without any modification. With a higher density of strongly alkaline buffer droplets (about 100 droplets/mm2) sprayed on the bottom of the Petri dish, or by flushing N2 above the heptane, the microscopic samples can also be kept alkaline despite ambient CO2 present. In this way, Zn(II) can also be titrated in microdroplets, requiring a pH around 10. This work renders it possible to perform a variety of complexometric titrations and other chemical manipulations in microdroplets even if they need to be kept alkaline. Similar titrations in single biological cells to assess intracellular buffer capacities of different metal ions, such as Ca(II) and Mg(II), are underway.

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The performance of TCP over wireless links could degrade due to handoff, high bit error rate and long roundtrip delay on the air interface. The conventional Radio Link Protocol uses fixed channel coding and ARQ to mitigate impairment over wireless channels. Adaptive channel coding with the use of punctured convolutional codes has been proposed for its ability to adapt to channel quality and maintain a high level of system throughput. In this paper, we study TCP over adaptive RLP based on estimated channel condition. We consider a Markov channel model and evaluate the performance of TCP with adaptive RLP in such environment. We also evaluate the existing channel quality measurement in wireless systems and propose a methodology to update RLP channel coding schemes based on filtered channel measurement. We use simulation to calculate the throughput of TCP system and determine the effectiveness of adaptive channel coding with respect to different fading rates.

The data volume and computation task of MIMO radar is huge; a very high-speed computation is necessary for its real-time processing. In this paper, we mainly study the time division MIMO radar signal processing flow, propose an improved MIMO radar signal processing algorithm, raising the MIMO radar algorithm processing speed combined with the previous algorithms, and, on this basis, a parallel simulation system for the MIMO radar based on the CPU/GPU architecture is proposed. The outer layer of the framework is coarse-grained with OpenMP for acceleration on the CPU, and the inner layer of fine-grained data processing is accelerated on the GPU. Its performance is significantly faster than the serial computing equipment, and satisfactory acceleration effects have been achieved in the CPU/GPU architecture simulation. The experimental results show that the MIMO radar parallel simulation system with CPU/GPU architecture greatly improves the computing power of the CPU-based method. Compared with the serial sequential CPU method, GPU simulation achieves a speedup of 130 times. In addition, the MIMO radar signal processing parallel simulation system based on the CPU/GPU architecture has a performance improvement of 13%, compared to the GPU-only method.