Effects of chordwise, spanwise, and isotropic flexibility on the force generation and propulsive efficiency of flapping wings are elucidated. For a moving body immersed in viscous fluid, different ...types of forces, as a function of the Reynolds number, reduced frequency (k), and Strouhal number (St), acting on the moving body are identified based on a scaling argument. In particular, at the Reynolds number regime of $O(1{0}^{3} \ensuremath{-} 1{0}^{4} )$ and the reduced frequency of $O(1)$, the added mass force, related to the acceleration of the wing, is important. Based on the order of magnitude and energy balance arguments, a relationship between the propulsive force and the maximum relative wing-tip deformation parameter ($\gamma $) is established. The parameter depends on the density ratio, St, k, natural and flapping frequency ratio, and flapping amplitude. The lift generation, and the propulsive efficiency can be deduced by the same scaling procedures. It seems that the maximum propulsive force is obtained when flapping near the resonance, whereas the optimal propulsive efficiency is reached when flapping at about half of the natural frequency; both are supported by the reported studies. The established scaling relationships can offer direct guidance for micro air vehicle design and performance analysis.
Micro air vehicles (MAVs) have the potential to revolutionize our sensing and information gathering capabilities in areas such as environmental monitoring and homeland security. Flapping wings with ...suitable wing kinematics, wing shapes, and flexible structures can enhance lift as well as thrust by exploiting large-scale vortical flow structures under various conditions. However, the scaling invariance of both fluid dynamics and structural dynamics as the size changes is fundamentally difficult. The focus of this review is to assess the recent progress in flapping wing aerodynamics and aeroelasticity. It is realized that a variation of the Reynolds number (wing sizing, flapping frequency, etc.) leads to a change in the leading edge vortex (LEV) and spanwise flow structures, which impacts the aerodynamic force generation. While in classical stationary wing theory, the tip vortices (TiVs) are seen as wasted energy, in flapping flight, they can interact with the LEV to enhance lift without increasing the power requirements. Surrogate modeling techniques can assess the aerodynamic outcomes between two- and three-dimensional wing. The combined effect of the TiVs, the LEV, and jet can improve the aerodynamics of a flapping wing. Regarding aeroelasticity, chordwise flexibility in the forward flight can substantially adjust the projected area normal to the flight trajectory via shape deformation, hence redistributing thrust and lift. Spanwise flexibility in the forward flight creates shape deformation from the wing root to the wing tip resulting in varied phase shift and effective angle of attack distribution along the wing span. Numerous open issues in flapping wing aerodynamics are highlighted.
The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for ...four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.
Based on the known and emerging biology of autoimmune diseases and COVID‐19, it was hypothesised that whilst B‐cell depletion should not necessarily expose people to severe SARS‐CoV‐2‐related issues, ...it may inhibit or blunt the protective immunity following infection and vaccination. This is supported clinically, as the majority of SARS‐CoV‐2 infected, CD20‐depleted people with autoimmunity, have recovered. However, in CD‐20 treated people until naïve B‐cells repopulate, based on B‐cell repopulation‐kinetics and vaccination responses, from published rituximab, and unpublished ocrelizumab (NCT00676715, NCT02545868) trial data shown here suggests that it may be possible to undertake dose‐interruption to maintain inflammatory disease control, whilst allowing effective vaccination against SARS‐CoV‐29, if and when an effective vaccine is available.
Summary
Although most autoimmune diseases are considered to be CD4 T cell‐ or antibody‐mediated, many respond to CD20‐depleting antibodies that have limited influence on CD4 and plasma cells. This includes rituximab, oblinutuzumab and ofatumumab that are used in cancer, rheumatoid arthritis and off‐label in a large number of other autoimmunities and ocrelizumab in multiple sclerosis. Recently, the COVID‐19 pandemic created concerns about immunosuppression in autoimmunity, leading to cessation or a delay in immunotherapy treatments. However, based on the known and emerging biology of autoimmunity and COVID‐19, it was hypothesised that while B cell depletion should not necessarily expose people to severe SARS‐CoV‐2‐related issues, it may inhibit protective immunity following infection and vaccination. As such, drug‐induced B cell subset inhibition, that controls at least some autoimmunities, would not influence innate and CD8 T cell responses, which are central to SARS‐CoV‐2 elimination, nor the hypercoagulation and innate inflammation causing severe morbidity. This is supported clinically, as the majority of SARS‐CoV‐2‐infected, CD20‐depleted people with autoimmunity have recovered. However, protective neutralizing antibody and vaccination responses are predicted to be blunted until naive B cells repopulate, based on B cell repopulation kinetics and vaccination responses, from published rituximab and unpublished ocrelizumab (NCT00676715, NCT02545868) trial data, shown here. This suggests that it may be possible to undertake dose interruption to maintain inflammatory disease control, while allowing effective vaccination against SARS‐CoV‐29, if and when an effective vaccine is available.
5-Fluorouracil (5-FU) is a widely used anticancer drug for the treatment of colorectal cancer (CRC). However, resistance to 5-FU often prevents the success of chemotherapy. Nuclear factor-erythroid ...2-related factor 2 (Nrf2) is a transcriptional regulator and a possible target to overcome 5-FU resistance. The present study examined epigenetic changes associated with Nrf2 induction in a human CRC cell line (SNUC5) resistant to 5-FU (SNUC5/5-FUR). Nrf2 expression, nuclear translocation, and binding to promoter were higher in SNUC5/5-FUR cells than in SNUC5 cells. The activated Nrf2 in SNUC5/5-FUR cells led to an increase in the protein expression and activity of heme oxygenase-1 (HO-1), an Nrf2-regulated gene. SNUC5/5-FUR cells produced a larger amount of reactive oxygen species (ROS) than SNUC5 cells. The siRNA- or shRNA-mediated knockdown of Nrf2 or HO-1 significantly suppressed cancer cell viability and tumor growth in vitro and in vivo, resulting in enhanced 5-FU sensitivity. Methylation-specific (MS) or real-time quantitative MS-PCR data showed hypomethylation of the Nrf2 promoter CpG islands in SNUC5/5-FUR cells compared with SNUC5 cells. Expression of the DNA demethylase ten-eleven translocation (TET) was upregulated in SNUC5/5-FUR cells. ROS generated by 5-FU upregulated TET1 expression and function, whereas antioxidant had the opposite effect. These results suggested that the mechanism underlying the acquisition of 5-FU resistance in CRC involves the upregulation of Nrf2 and HO-1 expression via epigenetic modifications of DNA demethylation.
Given observed initial conditions, how well do coupled atmosphere-ocean models predict precipitation climatology with 1-month lead forecast? And how do the models' biases in climatology in turn ...affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981-2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models' ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian-Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated.
We mimic a flapping wing through a fluid–structure interaction (FSI) framework based upon a generalized lumped-torsional flexibility model. The developed fluid and structural solvers together ...determine the aerodynamic forces, wing deformation and self-propelled motion. A phenomenological solution to the linear single-spring structural dynamics equation is established to help offer insight and validate the computations under the limit of small deformation. The cruising velocity and power requirements are evaluated by varying the flapping Reynolds number (
$20\leqslant Re_{f}\leqslant 100$
), stiffness (represented by frequency ratio,
$1\lesssim \unicodeSTIX{x1D714}^{\ast }\leqslant 10$
) and the ratio of aerodynamic to structural inertia forces (represented by a dimensionless parameter
$\unicodeSTIX{x1D713}$
(
$0.1\leqslant \unicodeSTIX{x1D713}\leqslant 3$
)). For structural inertia dominated flows (
$\unicodeSTIX{x1D713}\ll 1$
), pitching and plunging are shown to always remain in phase (
$\unicodeSTIX{x1D719}\approx 0$
) with the maximum wing deformation occurring at the end of the stroke. When aerodynamics dominates (
$\unicodeSTIX{x1D713}>1$
), a large phase difference is induced (
$\unicodeSTIX{x1D719}\approx \unicodeSTIX{x03C0}/2$
) and the maximum deformation occurs at mid-stroke. Lattice Boltzmann simulations show that there is an optimal
$\unicodeSTIX{x1D714}^{\ast }$
at which cruising velocity is maximized and the location of optimum shifts away from unit frequency ratio (
$\unicodeSTIX{x1D714}^{\ast }=1$
) as
$\unicodeSTIX{x1D713}$
increases. Furthermore, aerodynamics administered deformations exhibit better performance than those governed by structural inertia, quantified in terms of distance travelled per unit work input. Closer examination reveals that although maximum thrust transpires at unit frequency ratio, it is not transformed into the highest cruising velocity. Rather, the maximum velocity occurs at the condition when the relative tip displacement
${\approx}\,0.3$
.
We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980-2004) retrospective forecasts performed by 14 climate model systems ...(7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models' MME for the period of 1981-2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial-temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80-90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model's slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.
The first experimental study is presented of a corrugated wall device that uses wakefields to remove a linear energy correlation in a relativistic electron beam (a "dechirper"). Time-resolved ...measurements of both longitudinal and transverse wakefields of the device are presented and compared with simulations. This study demonstrates the feasibility to employ a dechirper for precise control of the beam phase space in the next generation of free-electron-lasers.
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