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The plasma potential measured by cylindrical and planar Langmuir probes has been shown to differ from the plasma potential measured by emissive probes in the neighborhood of the presheath near a negatively biased electrode immersed in a weakly collisional low temperature argon plasma. There are two principal results demonstrated in this paper. First, while it is well known that Langmuir probes cannot reliably measure plasma potentials inside of sheaths, results presented here demonstrate that the problem persists in presheaths, the quasineutral plasma bordering sheaths. It is known that emissive probes analyzed in the limit of zero emission accurately measure the plasma potential in the sheath. It is now clear that they are the only known electrostatic probe technique able to measure the plasma potential accurately throughout the presheath. Second, it is shown that the difference between potential measurements made by Langmuir probes and emissive probes in the body of the plasma, farther than a presheath distance from the boundary, is not proportional to Te, as has been previously claimed. 

Dependent security labels (security labels that depend on program states) in various forms have been introduced to express rich information flow policies. They are shown to be essential in the verification of real-world software and hardware systems such as conference management systems, Android Apps, a MIPS processor and a TrustZone-like architecture. However, most work assumes that all (complex) labels are provided manually, which can both be error-prone and time-consuming. In this paper, we tackle the problem of automatic label inference for static information flow analyses with dependent security labels. In particular, we propose the first general framework to facilitate the design and validation (in terms of soundness and/or completeness) of inference algorithms. The framework models label inference as constraint solving and offers guidelines for sound and/or complete constraint solving. Under the framework, we propose novel constraint solving algorithms that are both sound and complete. Evaluation result on sets of constraints generated from secure and insecure variants of a MIPS processor suggests that the novel algorithms improve the performance of an existing algorithm by orders of magnitude and offers better scalability. 

Abstract Therapeutic antibodies, due to their high affinity and specificity toward their biological targets, may demonstrate reduced harmful side effects compared with traditional drug moieties. While most of the as‐yet clinically approved antibody therapeutics have targeted extracellular or membrane‐bound domains, the ability to target intracellular antigens with antibodies opens up tremendous opportunities for imaging, diagnosis, and therapeutic applications. Generally, delivery concerns have limited the ability to target intracellular antigens, as many antibodies cannot easily cross the cell membrane due to their size and surface chemistry. Delivery platforms have been explored to address this issue, including physical methods, fusion protein/peptide techniques, and synthetic carrier‐based systems. This review summarizes the progress of carrier‐based intracellular antibody delivery systems employing synthetic lipids, polymers, and inorganic nanomaterials. Antibodies targeting various epitopes have been loaded through adsorption, conjugation, or physical encapsulation strategies. Successful intracellular deliveries have been demonstrated largely through fluorescence imaging using dye‐labeled antibody cargos. Specific synthetic delivery platforms have great potential for ex vivo and in vivo therapeutic applications. Challenges and opportunities are further discussed for material scientists to explore in this research area.