EFFECTIVE CLEARANCE AND DIFFERENTIAL GAPPING IMPACT ON SEAL FLUTTER MODELLING AND VALIDATION

This paper presents an update of the model derived by Corral and Vega (2018, “Conceptual Flutter Analysis of Labyrinth Seal Using Analytical Models. Part I - Theoretical Support”, ASME J. of Turbomach., 140 (12), pp. 121006) for labyrinth seal flutter stability, providing a method of accounting for the effect of dissimilar gaps. The original CV model was intended as a conceptual model for understanding the effect of different parameters on the seal stability comprehensively, providing qualitative trends for seal flutter stability. However, the quantitative evaluation of seal flutter, and the comparison of the CV model with detailed unsteady numerical simulations or experimental data, require including additional physics. The kinetic energy generated in the inlet gap is not dissipated entirely in the inter-fin cavity of straight-through labyrinth seals, and part is recovered in the downstream knife. This mechanism needs to be retained in the model. It is concluded that when the theoretical gaps are identical, the impact of the recovery factor on the seal stability can be high. The sensitivity of the seal stability to large changes in the outlet to inlet gap ratio is high as well. It is concluded that fin variations due to rubbing or wearing inducing inlet gaps more open than the exit gaps lead to an additional loss of stability concerning the case of identical gaps. The agreement between the updated model and 3D linearized Navier-Stokes simulations is excellent when the model is informed with data coming from steady RANS simulations of the seal.

The GET pathway serves to activate Atg32-mediated mitophagy by ER targeting of the Ppg1-Far complex

Mitophagy removes defective or superfluous mitochondria via selective autophagy. In yeast, the pro-mitophagic protein Atg32 localizes to the mitochondrial surface and interacts with the scaffold protein Atg11 to promote degradation of mitochondria. Although Atg32-Atg11 interactions are thought to be stabilized by Atg32 phosphorylation, how this posttranslational modification is regulated remains obscure. Here we show that cells lacking the guided entry of tail-anchored proteins (GET) pathway exhibit reduced Atg32 phosphorylation and Atg32-Atg11 interactions, which can be rescued by additional loss of the ER-resident Ppg1-Far complex, a multi-subunit phosphatase negatively acting in mitophagy. In GET-deficient cells, Ppg1-Far is predominantly localized to mitochondria. An artificial ER anchoring of Ppg1-Far in GET-deficient cells significantly ameliorates defects in Atg32-Atg11 interactions and mitophagy. Moreover, disruption of GET and Msp1, an AAA-ATPase that extracts non-mitochondrial proteins localized to the mitochondrial surface, elicits synthetic defects in mitophagy. Collectively, we propose that the GET pathway mediates ER targeting of Ppg1-Far, thereby preventing dysregulated suppression of mitophagy activation.

Can Right Whales Out-Swim Climate Change? Can We?

The article by Meyer-Gutbrod and colleagues in this issue demonstrates that the endangered North Atlantic right whale’s preferred prey has declined as the Northwest Atlantic has warmed. Right whales are now spending more time foraging in historically colder habitats, but they are producing fewer calves. The low calf production could reflect a delay between the decline in the potential productivity of their traditional habitats and its increase in their new habitats. This delay would result in a “climate deficit” in their fitness. Right whales must also learn to forage successfully in their new habitats, creating an additional loss of fitness termed an “adaptation deficit.” Humans will also face unavoidable climate deficits, but we have more options for minimizing adaptation deficits.

Stacked sparse autoencoders that preserve the local and global feature structures for fault detection

Although the model based on an autoencoder (AE) exhibits strong feature extraction capability without data labeling, such model is less likely to consider the structural distribution of the original data and the extracted feature is uninterpretable. In this study, a new stacked sparse AE (SSAE) based on the preservation of local and global feature structures is proposed for fault detection. Two additional loss terms are included in the loss function of SSAE to retain the local and global structures of the original data. The preservation of the local feature considers the nearest neighbor of data in space, while that of the global feature considers the variance information of data. The final feature is not only a deep representation of data, but it also retains structural information as much as possible. The proposed model demonstrates remarkable detection performance in case studies of a numerical process and the Tennessee Eastman process.

Development and Evaluation of a Method for Automated Detection of Spreading Depolarizations in the Injured Human Brain

Background Spreading depolarizations (SDs) occur in some 60% of patients receiving intensive care following severe traumatic brain injury and often occur at a higher incidence following serious subarachnoid hemorrhage and malignant hemisphere stroke (MHS); they are independently associated with worse clinical outcome. Detection of SDs to guide clinical management, as is now being advocated, currently requires continuous and skilled monitoring of the electrocorticogram (ECoG), frequently extending over many days. Methods We developed and evaluated in two clinical intensive care units (ICU) a software routine capable of detecting SDs both in real time at the bedside and retrospectively and also capable of displaying patterns of their occurrence with time. We tested this prototype software in 91 data files, each of approximately 24 h, from 18 patients, and the results were compared with those of manual assessment (“ground truth”) by an experienced assessor blind to the software outputs. Results The software successfully detected SDs in real time at the bedside, including in patients with clusters of SDs. Counts of SDs by software (dependent variable) were compared with ground truth by the investigator (independent) using linear regression. The slope of the regression was 0.7855 (95% confidence interval 0.7149–0.8561); a slope value of 1.0 lies outside the 95% confidence interval of the slope, representing significant undersensitivity of 79%. R2 was 0.8415. Conclusions Despite significant undersensitivity, there was no additional loss of sensitivity at high SD counts, thus ensuring that dense clusters of depolarizations of particular pathogenic potential can be detected by software and depicted to clinicians in real time and also be archived.

Effective Clearance And Differential Gapping Impact on Seal Flutter Modelling and Validation

This paper presents an update of the model derived by Corral and Vega (2018, “Conceptual Flutter Analysis of Labyrinth Seal Using Analytical Models. Part I - Theoretical Support”, ASME J. of Turbomach., 140 (12), pp. 121006) for labyrinth seal flutter stability, providing a method of accounting for the effect of dissimilar gaps. The original CV model was intended as a conceptual model for understanding the effect of different geometric parameters on the seal stability comprehensively, providing qualitative trends for seal flutter stability. However, the quantitative evaluation of seal flutter, and the comparison of the CV model with detailed unsteady numerical simulations or experimental data, require including additional physics. The kinetic energy generated in the inlet gap is not dissipated entirely in the inter-fin cavity of straight-through labyrinth seals, and part is recovered in the downstream knife. This mechanism needs to be retained in the seal flutter model. It is concluded that when the theoretical gaps are identical, the impact of the recovery factor on the seal stability can be high. The sensitivity of the seal stability to large changes in the outlet to inlet gap ratio is high as well. It is concluded that fin variations due to rubbing or wearing inducing inlet gaps more open than the exit gaps lead to an additional loss of stability concerning the case of identical gaps. The agreement between the updated model and 3D linearized Navier-Stokes simulations is excellent when the model is informed with data coming from steady RANS simulations of the seal.

Driving plasmonic nanoantennas at perfect impedance matching using generalized coherent perfect absorption

Coherent perfect absorption (CPA) describes the absence of all outgoing modes from a lossy resonator, driven by lossless incoming modes. Here, we show that for nanoresonators that also exhibit radiative losses, e.g., plasmonic nanoantennas, a generalized version of CPA (gCPA) can be applied. In gCPA outgoing modes are suppressed only for a subset of (guided plasmonic) modes while other (radiative) modes are treated as additional loss channels - a situation typically referred to as perfect impedance matching. Here we make use of gCPA to show how to achieve perfect impedance matching between a single nanowire plasmonic waveguide and a plasmonic nanoantenna. Antennas with both radiant and subradiant characteristics are considered. We further demonstrate potential applications in background-free sensing.

A Video Captioning Method Based on Multi-Representation Switching for Sustainable Computing

Video captioning is a problem that generates a natural language sentence as a video’s description. A video description includes not only words that express the objects in the video but also words that express the relationships between the objects, or grammatically necessary words. To reflect this characteristic explicitly using a deep learning model, we propose a multi-representation switching method. The proposed method consists of three components: entity extraction, motion extraction, and textual feature extraction. The proposed multi-representation switching method makes it possible for the three components to extract important information for a given video and description pair efficiently. In experiments conducted on the Microsoft Research Video Description dataset, the proposed method recorded scores that exceeded the performance of most existing video captioning methods. This result was achieved without any preprocessing based on computer vision and natural language processing, nor any additional loss function. Consequently, the proposed method has a high generality that can be extended to various domains in terms of sustainable computing.

Miscanthus Sinensis is as Efficient as Miscanthus × Giganteus for Nitrogen Recycling in Spite of Smaller N Fluxes

Nitrogen (N) recycling is a key mechanism to ensure the sustainability of miscanthus production with no or small fertiliser inputs, but little is known on the subject in miscanthus species other than the most cultivated Miscanthus × giganteus. This field experiment on Miscanthus × giganteus and Miscanthus sinensis quantified plant biomass and N stock dynamics during two years. Endogenous net N fluxes, calculated by the difference in plant N content throughout time, were higher in Miscanthus × giganteus than in Miscanthus sinensis. Indeed, 79 kg N ha-1 and 105 to 197 kg N ha-1 were remobilized during spring and autumn respectively for Miscanthus × giganteus, as opposed to 13 to 25 kg N ha-1 and 46 to 128 kg N ha-1 for Miscanthus sinensis. However, their N recycling efficiency, defined as the ratio between N remobilisation fluxes and the maximum above-ground N content, did not differ significantly. It ranged from 8 to 27% for spring remobilisation and from 63 to 74% and 24 to 38% for autumn remobilization calculated on above-ground and below-ground N respectively. Exogenous N, the main source of N to constitute maximum plant N content for all genotypes, was provided by fertilisation (22 to 24%) and organic matter mineralisation or other sources (43 to 59%). During winter, 50 to 56% of plant N content was lost. Abscised leaves constituted an additional loss of 6 to 12%. Our results show that Miscanthus sinensis is as efficient as Miscanthus × giganteus and as performant as other perennial species concerning N functioning.

Switching off microcavity polariton condensate near the exceptional point

Gain and loss modulation are ubiquitous in nature. An exceptional point arises when both the eigenvectors and eigenvalues coalesce, which in a physical system can be achieved by engineering the gain and loss coefficients, leading to a wide variety of counter-intuitive phenomena. In this work we demonstrate the existence of an exceptional point in an exciton polariton condensate in a double-well potential. Remarkably, near the exceptional point, the polariton condensate localized in one potential well can be switched off by an additional optical excitation in the other well with very low (far below threshold) laser power which surprisingly induces additional loss into the system. Increasing the power of the additional laser leads to a situation in which gain dominates in both wells again, such that the polaritons re-condense with almost the same density in the two potential wells. Our results offer a simple way to optically manipulate the polariton condensation process in a double-well potential structure. Extending such configuration to complex potential well lattices offers exciting prospects to explore high-order exceptional points and non-Hermitian topological photonics in a non-equilibrium many-body system.