The polymeric conformational effect on capacitive deionization performance of graphene oxide/polypyrrole composite electrode

Exploitation of novel faradic materials is an alternative implementation for solving the problem of poor specific electrosorption capacity that conventional carbon materials are encountered in capacitive deionization. Particularly, composite electrode is just a suitable choice because of its potentially high ion-storage ability. Herein, a cyclic voltammetric treatment method with different low limit of potential window was used to manipulate the polymeric conformation and doping level of graphene oxide/polypyrrole (GO/PPy) composite electrode. Based on it, the effect of polymeric structure on the electrosorption performance was systematically studied. When the low limit of potential window is shifted negatively enough, the irreversible polymeric conformational shrinks of GO/PPy are promoted, which not only hinders the insertion process of ions, but also decreases the doping level of polymer due to the intensive interchain-action produced by more entangled polymeric chain. Thus, the number of intercalated ions should decrease, which is expressed by electrochemical impedance spectroscopy (EIS) results and is proportional to the electrosorption capacity of GO/PPy composite electrode in membrane capacitive deionization (MCDI) process. Our work suggests that the less packing density, higher doping level and more charge delocalization on PPy backbone in electrode are beneficial to enhance its capacitive deionization performance

A systematic approach to the formulation of anti-onychomycotic nail patches

Nail patches have a potential role as drug carriers for the topical treatment of nail diseases such as onychomycosis, a common condition. O ur aim was therefore to develop a systematic and novel appr oach to the formulat ion of a simple drug -in-adhesive ungual patch. Twelve pressure -sensitive adhesives (PSAs), four backing membranes, two release liners and three drugs were screened for pharmaceutical and mechanical properties . From this initial screeni ng, two PSAs, two drugs, one backing membrane and one release liner were selected for further investigation. Patches were prepared by solvent -casting and characterised. The patches had good uniformity of thickness and of drug content, and showed minimal drug crystallisation during six month s of storage. Meanwhile, the d rug stability in the patch upon storage and patch adhesion to the nail was influenced by the nature of the drug, the PSA and the backing membrane . The reported methodology paves the way for a systematic formulation of ungual nail patches to add to the armamentarium of nail medicines . Further , from this work, the best patch formulation has been identified

Learning to complete object shapes for object-level mapping in dynamic scenes

In this paper, we propose a novel object-level mapping system that can simultaneously segment, track, and reconstruct objects in dynamic scenes. It can further predict and complete their full geometries by conditioning on reconstructions from depth inputs and a category-level shape prior with the aim that completed object geometry leads to better object reconstruction and tracking accuracy. For each incoming RGB-D frame, we perform instance segmentation to detect objects and build data associations between the detection and the existing object maps. A new object map will be created for each unmatched detection. For each matched object, we jointly optimise its pose and latent geometry representations using geometric residual and differential rendering residual towards its shape prior and completed geometry. Our approach shows better tracking and reconstruction performance compared to methods using traditional volumetric mapping or learned shape prior approaches. We evaluate its effectiveness by quantitatively and qualitatively testing it in both synthetic and real-world sequences

Absolute Quantification of Uric Acid in Human Urine Using Surface Enhanced Raman Scattering with the Standard Addition Method.

High levels of uric acid in urine and serum can be indicative of hypertension and the pregnancy related condition, preeclampsia. We have developed a simple, cost-effective, portable surface enhanced Raman scattering (SERS) approach for the routine analysis of uric acid at clinically relevant levels in urine patient samples. This approach, combined with the standard addition method (SAM), allows for the absolute quantification of uric acid directly in a complex matrix such as that from human urine. Results are highly comparable and in very good agreement with HPLC results, with an average <9% difference in predictions between the two analytical approaches across all samples analyzed, with SERS demonstrating a 60-fold reduction in acquisition time compared with HPLC. For the first time, clinical prepreeclampsia patient samples have been used for quantitative uric acid detection using a simple, rapid colloidal SERS approach without the need for complex data analysis

Learning Optimal Deep Projection of 18^{18}F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes

Several diseases of parkinsonian syndromes present similar symptoms at early stage and no objective widely used diagnostic methods have been approved until now. Positron emission tomography (PET) with $^{18}$F-FDG was shown to be able to assess early neuronal dysfunction of synucleinopathies and tauopathies. Tensor factorization (TF) based approaches have been applied to identify characteristic metabolic patterns for differential diagnosis. However, these conventional dimension-reduction strategies assume linear or multi-linear relationships inside data, and are therefore insufficient to distinguish nonlinear metabolic differences between various parkinsonian syndromes. In this paper, we propose a Deep Projection Neural Network (DPNN) to identify characteristic metabolic pattern for early differential diagnosis of parkinsonian syndromes. We draw our inspiration from the existing TF methods. The network consists of a (i) compression part: which uses a deep network to learn optimal 2D projections of 3D scans, and a (ii) classification part: which maps the 2D projections to labels. The compression part can be pre-trained using surplus unlabelled datasets. Also, as the classification part operates on these 2D projections, it can be trained end-to-end effectively with limited labelled data, in contrast to 3D approaches. We show that DPNN is more effective in comparison to existing state-of-the-art and plausible baselines.Comment: 8 pages, 3 figures, conference, MICCAI DLMIA, 201

Regulation of mitochondrial biogenesis in erythropoiesis by mTORC1-mediated protein translation.

Advances in genomic profiling present new challenges of explaining how changes in DNA and RNA are translated into proteins linking genotype to phenotype. Here we compare the genome-scale proteomic and transcriptomic changes in human primary haematopoietic stem/progenitor cells and erythroid progenitors, and uncover pathways related to mitochondrial biogenesis enhanced through post-transcriptional regulation. Mitochondrial factors including TFAM and PHB2 are selectively regulated through protein translation during erythroid specification. Depletion of TFAM in erythroid cells alters intracellular metabolism, leading to elevated histone acetylation, deregulated gene expression, and defective mitochondria and erythropoiesis. Mechanistically, mTORC1 signalling is enhanced to promote translation of mitochondria-associated transcripts through TOP-like motifs. Genetic and pharmacological perturbation of mitochondria or mTORC1 specifically impairs erythropoiesis in vitro and in vivo. Our studies support a mechanism for post-transcriptional control of erythroid mitochondria and may have direct relevance to haematologic defects associated with mitochondrial diseases and ageing

A thermal simulation process based on electrical modeling for complex interconnect, packaging, and 3DI structures

To reduce the product development time and achieve first-pass silicon success, fast and accurate estimation of very-large-scale integration (VLSI) interconnect, packaging and 3DI (3D integrated circuits) thermal profiles has become important. Present commercial thermal analysis tools are incapable of handling very complex structures and have integration difficulties with existing design flows. Many analytical thermal models, which could provide fast estimates, are either too specific or oversimplified. This paper highlights a methodology, which exploits electrical resistance solvers for thermal simulation, to allow acquisition of thermal profiles of complex structures with good accuracy and reasonable computation cost. Moreover, a novel accurate closed-form thermal model is developed. The model allows an isotropic or anisotropic equivalent medium to replace the noncritical back-end-of-line (BEOL) regions so that the simulation complexity is dramatically reduced. Using these techniques, this paper introduces the thermal modeling of practical complex VLSI structures to facilitate thermal guideline generation. It also demonstrates the benefits of the proposed anisotropic equivalent medium approximation for real VLSI structures in terms of the accuracy and computational cost. © 2006 IEEE.published_or_final_versio

Automating Deductive Verification for Weak-Memory Programs

Writing correct programs for weak memory models such as the C11 memory model is challenging because of the weak consistency guarantees these models provide. The first program logics for the verification of such programs have recently been proposed, but their usage has been limited thus far to manual proofs. Automating proofs in these logics via first-order solvers is non-trivial, due to reasoning features such as higher-order assertions, modalities and rich permission resources. In this paper, we provide the first implementation of a weak memory program logic using existing deductive verification tools. We tackle three recent program logics: Relaxed Separation Logic and two forms of Fenced Separation Logic, and show how these can be encoded using the Viper verification infrastructure. In doing so, we illustrate several novel encoding techniques which could be employed for other logics. Our work is implemented, and has been evaluated on examples from existing papers as well as the Facebook open-source Folly library.Comment: Extended version of TACAS 2018 publicatio