3-D inkjet printed solid oxide electrochemical reactors III. cylindrical pillared electrode microstructures

Inkjet printing is a scalable technique that can fabricate customised three-dimensional microstructures, reproducibly, accurately, and with high material utilisation, by printing multiple layers sequentially onto previously printed layers, to produce architectures tailored in this case to electrochemical reactors. Printable yttria-stabilised zirconia (YSZ) and lanthanum strontium manganite (LSM) inks were formulated to enable fabrication of solid oxide electrochemical reactors (SOERs): H2O-H2 | Ni(O)-YSZ | YSZ | YSZ pillars | LSM | O2. Of the geometries studied, equi-sized, hexagonally-arranged cylindrical pillars were predicted to produce the largest ratio of interfacial to geometric (cross-sectional) areas. However, this neglects effects of potential and current density distributions that constrain up-scaling to more modest factors. Hence, using kinetic parameter values from the literature, finite element computational simulations of the pillared SOER in (H2 - O2) fuel cell mode predicted peak power densities of 0.11 W cm−2 at 800 °C, whereas its counterpart with only a planar electrolyte layer produced only 0.05 W cm−2; i.e. the pillars were predicted to enhance peak power densities by ca. 2.3. Arrays of several thousand YSZ cylindrical pillars were printed, with post-sintering diameter, height, and spacing of 25, 95 and 63 μm, respectively. LSM was inkjet-printed onto the pillars, and sintered subsequently, to produce contiguous films ca. 4 μm thick. In (H2 - O2) fuel cell mode at 725, 770, and 795 °C, these reactors produced peak power densities of 0.09, 0.21, 0.30 W cm−2, respectively, 3–6 times greater than the performance of ‘benchmark’ Ni(O)-YSZ | YSZ | LSM reactors inkjet-printed with planar cathodes operating under the same conditions, thereby demonstrating the benefit of inkjet printing as a fabrication technique for SOERs

Predicting optimal geometries of 3D-printed solid oxide electrochemical reactors

Solid oxide electrochemical reactors (SOERs) may be operated in fuel cell (SOFC) or electrolyser (SOE) modes, at temperatures > 800 K, depending on electrolyte and electrode materials. In electrolyser mode, current densities of ≥ ca. 104 A m−2 are achievable at potential differences ideally at the thermoneutral values of 1.285 V for steam splitting or 1.46 V for CO2 splitting at 750 °C. As for large scale chemical processes in general, such reactors are required to be energy efficient, economic, of scalable design and fabrication, and durable ideally over ≥ ca. 10 years. Increasing densities of electrode | electrolyte interfacial areas (and electrode | electrolyte | pore triple phase boundaries) of solid oxide fuel cells or electrolysers offers one means of increasing performance, reproducibility, durability and potentially decreasing cost. Three-dimensional structuring of those interfaces can be achieved by 3D printing, but modelling is required to optimise geometries. Using kinetic parameter values from the literature, COMSOL Multiphysics® finite element software was used to predict effects of 3D geometries, increasing interfacial to geometric area ratios, on SOER performances for YSZ ((ZrO2)0.92(Y2O3)0.08) oxide ion conducting electrolyte and Ni-YSZ electrode based cells, relative to corresponding planar structures with < 10 μm thick planar YSZ electrolyte. For the negative electrode, electrolyte and electrode layers were inkjet printed on Ni(O)-YSZ substrate precursors, then sintered. For the positive electrode, porous lanthanum strontium manganite (LSM: La0.8Sr0.2MnO3-δ) was brush-coated over the (gas-tight) YSZ, then sintered to produce complete SOERs: H2O-H2 | Ni(O)-YSZ | YSZ-YSZ pillars | YSZ-LSM | LSM | O2. Results are reported showing that, in the case of solid YSZ pillars, despite interfacial electrode | electrolyte areas being up scaled by factors of 10–150 depending on height (10–150 μm), current densities were predicted to increase by only ca. 1.14 in electrolysis mode and peak power densities were predicted to increase by ca. 1.93 in fuel cell mode. This was due to increased ionic current path length along the pillars, increasing ohmic potential losses relative to faradaic impedances; as expected, such predictions depend strongly on electrode kinetic parameter values. After sintering the porous Ni(O)-YSZ pillars and their subsequent reduction with H2 to nickel, they were assumed to constitute equipotential surfaces, depending on current collector design. Predicted current densities were up to 1011 mA cm−2, far greater than in solid YSZ pillars, ultimately limited by reactant or product mass transport through porous pillars of increasing height

Population-Wide Emergence of Antiviral Resistance during Pandemic Influenza

Background: The emergence of neuraminidase inhibitor resistance has raised concerns about the prudent use of antiviral drugs in response to the next influenza pandemic. While resistant strains may initially emerge with compromised viral fitness, mutations that largely compensate for this impaired fitness can arise. Understanding the extent to which these mutations affect the spread of disease in the population can have important implications for developing pandemic plans. Methodology/Principal Findings: By employing a deterministic mathematical model, we investigate possible scenarios for the emergence of population-wide resistance in the presence of antiviral drugs. The results show that if the treatment level (the fraction of clinical infections which receives treatment) is maintained constant during the course of the outbreak, there is an optimal level that minimizes the final size of the pandemic. However, aggressive treatment above the optimal level can substantially promote the spread of highly transmissible resistant mutants and increase the total number of infections. We demonstrate that resistant outbreaks can occur more readily when the spread of disease is further delayed by applying other curtailing measures, even if treatment levels are kept modest. However, by changing treatment levels over the course of the pandemic, it is possible to reduce the final size of the pandemic below the minimum achieved at the optimal constant level. This reduction can occur with low treatment levels during the early stages of the pandemic, followed by a sharp increase in drug-use before the virus becomes widely spread. Conclusions/Significance: Our findings suggest that an adaptive antiviral strategy with conservative initial treatment levels, followed by a timely increase in the scale of drug-use, can minimize the final size of a pandemic while preventing large outbreaks of resistant infections

The Influence of Fat Suppression Technique on Diffusion-weighted (DW) MRI in Lung Cancer

Purpose: To qualitatively and quantitatively investigate the effect of common vendor-related sequence variations in fat suppression techniques on the diagnostic performance of free-breathing DW protocols for lung imaging.Methods: 8 patients with malignant lung lesions were scanned in free breathing using two diffusion-weighted (DW) protocols with different fat suppression techniques: DWA used short-tau inversion recovery (STIR), and DWB used Spectral Adiabatic Inversion Recovery (SPAIR). Both techniques were obtained at two time points, between 1 hour and 1 week apart. Image quality was assessed using a 5-point scoring system. The number of lesions visible within lung, mediastinum and at thoracic inlet on the DW (b=800 s/mm2) images was compared. Signal-to-noise ratios (SNR) were calculated for lesions and para-spinal muscle. Repeatability of ADC values of the lesions was estimated for both protocols together and separately.Results: There was a signal void at the thoracic inlet in all patients with DWB but not with DWA. DWA images were rated significantly better than DWB images overall quality domains. (Cohens κ = 1). Although 8 more upper mediastinal/thoracic inlet lymph nodes were detected with DWA than DWB, this did not reach statistical significance (p = 0.23). Tumour ADC values were not significantly different between protocols (p=0.93), their ADC reproducibility was satisfactory (CoV=7.7%) and repeatability of each protocol separately was comparable (CoVDWA=3.7% (95% CI 2.5 7.1%) and CoVDWB=4.6% (95% CI 3.18.8%)).Conclusion: In a free-breathing DW-MRI protocol for lung, STIR fat suppression produced images of better diagnostic quality than SPAIR, while maintaining comparable SNR and providing repeatable quantitative ADC acceptable for use in a multicentre trial setting

Thalamic inputs to dorsomedial striatum are involved in inhibitory control: evidence from the five-choice serial reaction time task in rats

Rationale Corticostriatal circuits are widely implicated in the top-down control of attention including inhibitory control and behavioural flexibility. However, recent neurophysiological evidence also suggests a role for thalamic inputs to striatum in behaviours related to salient, reward-paired cues. Objectives Here, we used designer receptors exclusively activated by designer drugs (DREADDs) to investigate the role of parafascicular (Pf) thalamic inputs to the dorsomedial striatum (DMS) using the five-choice serial reaction time task (5CSRTT) in rats. Methods The 5CSRTT requires sustained attention in order to detect spatially and temporally distributed visual cues and provides measures of inhibitory control related to impulsivity (premature responses) and compulsivity (perseverative responses). Rats underwent bilateral Pf injections of the DREADD vector, AAV2-CaMKIIa-HA-hM4D(Gi)-IRES-mCitrine. The DREADD agonist, clozapine N-oxide (CNO; 1 μl bilateral; 3 μM) or vehicle, was injected into DMS 1 h before behavioural testing. Task parameters were manipulated to increase attention load or reduce stimulus predictability respectively. Results We found that inhibition of the Pf-DMS projection significantly increased perseverative responses when stimulus predictability was reduced but had no effect on premature responses or response accuracy, even under increased attentional load. Control experiments showed no effects on locomotor activity in an open field. Conclusions These results complement previous lesion work in which the DMS and orbitofrontal cortex were similarly implicated in perseverative responses and suggest a specific role for thalamostriatal inputs in inhibitory control

Antigenic Diversity, Transmission Mechanisms, and the Evolution of Pathogens

Pathogens have evolved diverse strategies to maximize their transmission fitness. Here we investigate these strategies for directly transmitted pathogens using mathematical models of disease pathogenesis and transmission, modeling fitness as a function of within- and between-host pathogen dynamics. The within-host model includes realistic constraints on pathogen replication via resource depletion and cross-immunity between pathogen strains. We find three distinct types of infection emerge as maxima in the fitness landscape, each characterized by particular within-host dynamics, host population contact network structure, and transmission mode. These three infection types are associated with distinct non-overlapping ranges of levels of antigenic diversity, and well-defined patterns of within-host dynamics and between-host transmissibility. Fitness, quantified by the basic reproduction number, also falls within distinct ranges for each infection type. Every type is optimal for certain contact structures over a range of contact rates. Sexually transmitted infections and childhood diseases are identified as exemplar types for low and high contact rates, respectively. This work generates a plausible mechanistic hypothesis for the observed tradeoff between pathogen transmissibility and antigenic diversity, and shows how different classes of pathogens arise evolutionarily as fitness optima for different contact network structures and host contact rates

DeepReg: a deep learning toolkit for medical image registration

Image fusion is a fundamental task in medical image analysis and computer-assisted intervention. Medical image registration, computational algorithms that align different images together (Hill et al., 2001), has in recent years turned the research attention towards deep learning. Indeed, the representation ability to learn from population data with deep neural networks has opened new possibilities for improving registration generalisability by mitigating difficulties in designing hand-engineered image features and similarity measures for many realworld clinical applications (Fu et al., 2020; Haskins et al., 2020). In addition, its fast inference can substantially accelerate registration execution for time-critical tasks. DeepReg is a Python package using TensorFlow (Abadi et al., 2015) that implements multiple registration algorithms and a set of predefined dataset loaders, supporting both labelledand unlabelled data. DeepReg also provides command-line tool options that enable basic and advanced functionalities for model training, prediction and image warping. These implementations, together with their documentation, tutorials and demos, aim to simplify workflows for prototyping and developing novel methodology, utilising latest development and accessing quality research advances. DeepReg is unit tested and a set of customised contributor guidelines are provided to facilitate community contributions. A submission to the MICCAI Educational Challenge has utilised the DeepReg code and demos to explore the link between classical algorithms and deep-learning-based methods (Montana Brown et al., 2020), while a recently published research work investigated temporal changes in prostate cancer imaging, by using a longitudinal registration adapted from the DeepReg code (Yang et al., 2020)

Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus

BACKGROUND: Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease. METHODS: We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium(R) HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes. RESULTS: Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy. CONCLUSION: This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy

Exploring C semantics and pointer provenance

The semantics of pointers and memory objects in C has been a vexed question for many years. C values cannot be treated as either purely abstract or purely concrete entities: the language exposes their representations, but compiler optimisations rely on analyses that reason about provenance and initialisation status, not just runtime representations. The ISO WG14 standard leaves much of this unclear, and in some respects differs with de facto standard usage - which itself is difficult to investigate. In this paper we explore the possible source-language semantics for memory objects and pointers, in ISO C and in C as it is used and implemented in practice, focussing especially on pointer provenance. We aim to, as far as possible, reconcile the ISO C standard, mainstream compiler behaviour, and the semantics relied on by the corpus of existing C code. We present two coherent proposals, tracking provenance via integers and not; both address many design questions. We highlight some pros and cons and open questions, and illustrate the discussion with a library of test cases. We make our semantics executable as a test oracle, integrating it with the Cerberus semantics for much of the rest of C, which we have made substantially more complete and robust, and equipped with a web-interface GUI. This allows us to experimentally assess our proposals on those test cases. To assess their viability with respect to larger bodies of C code, we analyse the changes required and the resulting behaviour for a port of FreeBSD to CHERI, a research architecture supporting hardware capabilities, which (roughly speaking) traps on the memory safety violations which our proposals deem undefined behaviour. We also develop a new runtime instrumentation tool to detect possible provenance violations in normal C code, and apply it to some of the SPEC benchmarks. We compare our proposal with a source-language variant of the twin-allocation LLVM semantics proposal of Lee et al. Finally, we describe ongoing interactions with WG14, exploring how our proposals could be incorporated into the ISO standard

Super-A-polynomials for Twist Knots

We conjecture formulae of the colored superpolynomials for a class of twist knots $K_p$ where p denotes the number of full twists. The validity of the formulae is checked by applying differentials and taking special limits. Using the formulae, we compute both the classical and quantum super-A-polynomial for the twist knots with small values of p. The results support the categorified versions of the generalized volume conjecture and the quantum volume conjecture. Furthermore, we obtain the evidence that the Q-deformed A-polynomials can be identified with the augmentation polynomials of knot contact homology in the case of the twist knots.Comment: 22+16 pages, 16 tables and 5 figures; with a Maple program by Xinyu Sun and a Mathematica notebook in the ancillary files linked on the right; v2 change in appendix B, typos corrected and references added; v3 change in section 3.3; v4 corrections in Ooguri-Vafa polynomials and quantum super-A-polynomials for 7_2 and 8_1 are adde