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The real-time multivariate Madden–Julian oscillation (MJO) (RMM) index has now been widely applied as a standard in operational subseasonal prediction and monitoring. Its calculation procedures involve the extraction of major intraseasonal variability (ISV) by subtracting the prior 120-day mean. However, this study uncovers that such a real-time strategy artificially creates unwanted low-frequency variability (LFVartificial) that might cause nonnegligible influences on the RMM amplitude and phase. Compared to the real LFV, the LFVartificial explains more (∼70% in boreal summer) of the residual LFV (LFVresidual) in the RMM index. It occupies 33% of all days that the LFVresidual explains more than one-half of total RMM amplitude, 19% that the LFV contribution exceeds ISV, and 10% that the LFVartificial-associated RMM amplitude surpasses 0.8. The RMM-defined “MJO” is obscured by the LFVresidual in such a way that the eastward-propagating mode is stronger and bigger with a slower phase speed, as compared with the “true” MJO derived from the 20–100-day filtered data. The interference effects of LFVresidual on the MJO might be particularly strong when the background state is changing rapidly with time. However, these issues can be well avoided when one chooses to remove the centered 120-day mean, as evidenced by the largely reduced three percentages (17%, 8%, and 1%) mentioned above in the so-derived index. These results give us a reminder that more attention should be paid to monitoring or predicting an MJO using the RMM index in a rapidly changing low-frequency background or in the boreal summer. Significance Statement The real-time multivariate MJO (RMM) index has been widely applied in the monitoring and prediction of the MJO, the major tropical intraseasonal variability influencing global weather and climate. Using observational analysis, we reveal that there exist such scenarios (∼16%) when large-amplitude RMM indices do not represent a strong MJO, mainly due to the obscuring effect of residual, while largely artificial, low-frequency variability introduced by the RMM calculation procedures. This finding is of great significance as it informs the research community that serious caution should be given when relating large RMM amplitude to the MJO, especially in a condition when the low-frequency background state is rapidly changing with time or in the boreal summer.

The Madden–Julian oscillation (MJO) is the dominant intraseasonal wave phenomenon influencing extreme weather and climate worldwide. Realistic simulations and accurate predictions of MJO genesis are the cornerstones for successfully monitoring, forecasting, and managing meteorological disasters 3–4 weeks in advance. Nevertheless, the genesis processes and emerging precursor signals of an eastward-propagating MJO event remain largely uncertain. Here, we find that the MJO genesis processes observed in the past four decades exhibit remarkable diversity with different seasonality and can be classified objectively into four types, namely, a novel downstream origin from the westward-propagating intraseasonal oscillation (WPISO; 20.4%), localized breeding from the Indian Ocean suppressed convection (IOSC; 15.4%), an upstream succession of the preceding weakly dispersive (WD; 25.9%), and strongly dispersive (SD; 38.3%) MJO. These four types are associated with different oceanic background states, characterized by central Pacific cooling, southern Maritime Continent warming, eastern Pacific cooling, and central Pacific warming for the WPISO, IOSC, WD, and SD types, respectively. The SD type is also favored during the easterly phase of the stratospheric quasi-biennial oscillation. Diverse convective initiations possibly imply various kinds of propagations of MJO. The subseasonal reforecasts indicate robustly distinct prediction skills for the diverse MJO genesis. A window of opportunity for skillful week 3–4 prediction probably opens with the aid of the WPISO-type MJO precursor, which has increased the predictability of primary MJO onset by 1 week. These findings suggest that the diversified MJO genesis can be skillfully foreseen by monitoring unique precursor signals and can also serve as benchmarks for evaluating contemporary models’ modeling and predicting capabilities.

The boreal summer intraseasonal oscillation (BSISO) is a major source of subseasonal predictability of the East Asian summer monsoon. However, modeling and prediction of the BSISO remain major challenges partly due to an incomplete understanding of its eastward propagation. Our moisture budget analysis suggests that western Pacific (WPAC) premoistening leading the eastward-propagating (EP) BSISO is mainly attributed to the horizontal moisture advection with two centers in the lower and middle troposphere, respectively. The lower-tropospheric center is rooted in the linear moisture advection by flows from both the mean state and BSISO, while the middle-tropospheric center is induced by the nonlinear eddy moistening effect from the suppressed activity of synoptic tropical depression (TD) disturbances. The vertical profile of WPAC premoistening is significantly modulated by El Niño–Southern Oscillation (ENSO), with the premoistening being enhanced in the lower troposphere and weakened in the middle troposphere during an El Niño summer, and vice versa in a La Niña summer. During an El Niño summer, the nonlinear eddy moistening effect is weakened in the middle troposphere due to less southwest–northeast tilt of the TD, while the linear moisture advection is enhanced in the lower troposphere due to strengthened background cross-equatorial flows and moisture gradients. These results suggest an urgent need to improve the simulation fidelity of the BSISO’s scale interactions with synoptic and interannual variabilities in climate models. Significance Statement In this work, we use statistical analysis to explore multiscale interactions of BSISO with synoptic and interannual variabilities using observations and reanalysis data. Our key finding shows that the ENSO significantly modulates the premoistening process of the BSISO over the WPAC. In an El Niño summer, the WPAC nonlinear eddy moistening effect leading the BSISO is weakened in the midtroposphere due to smaller southwest–northeast tilt of the TD, while the linear moistening effect is enhanced in the lower troposphere due to enhanced background cross-equatorial flow and moisture gradient. These results offer new metrics for validating climate models and for projecting BSISO’s future change under different global warming scenarios.

A set of cloud-permitting-scale numerical simulations during January–February 2018 is used to examine the diurnal cycle (DC) of precipitation and near-surface variables (e.g., 2 m temperature, 10 m wind and convergence) over the Indo-Pacific Maritime Continent under the impacts of shore-orthogonal ambient winds (SOAWs). It is found that the DC of these variables and their variabilities of daily maxima, minima, and diurnal amplitudes vary over land, sea, and coastal regions. Among all variables, the DC of precipitation has the highest linear correlation with near-surface convergence (near-surface temperature) over coastal (noncoastal) regions. The correlations among the DCs of precipitation, wind, and heating are greater over the ocean than over land. Sine curves can model accurately the DCs of most variables over the ocean, but not over land. SOAWs act to influence the DC mainly by affecting the diurnal amplitude of the considered variables, with DC being stronger under more strengthened offshore SOAWs, though variable dependence and regional variability exist. Composite analysis over Sumatra reveals that under weak SOAWs, shallow clouds are dominant and cause a pre-moistening effect, supporting shallow-to-deep convection transition. A sea breeze circulation (SBC) with return flow aloft can develop rapidly. Cold pools are better able to trigger new updrafts and contribute to the upscale growth and inland migration of deep convection. In addition, warm gravity waves can propagate upward throughout the troposphere, thereby supporting a strong DC. In contrast, under strong SOAWs, both shallow and middle-high clouds prevail and persist throughout the day. The evolution of moistening and SBC is reduced, leading to weak variation in vertical motion and rainwater confined to the boundary layer. Large-scale winds, moisture, and convection are discussed to interpret how strong SOAWs affect the DC of Sumatra.

Endocrine resistance is a crucial challenge in estrogen receptor alpha (ERα)-positive breast cancer (BCa) therapy. Aberrant alteration in modulation of E2/ERα signaling pathway has emerged as the putative contributor for endocrine resistance in BCa. Thus, identification the efficient ERα cofactor remains necessary for finding a potential therapeutic target for endocrine resistance. Herein, we have demonstrated that Myb like, SWIRM and MPN domains 1 (MYSM1) as a histone deubiquitinase is a novel ERα co-activator with establishedDrosophilaexperimental model. Our results showed that MYSM1 participated in up-regulation of ERα action via histone and non-histone deubiquitination. We provided the evidence to show that MYSM1 was involved in maintenance of ERα stability via ERα deubiquitination. Furthermore, silencing MYSM1 induced enhancement of histone H2A ubiquitination as well as reduction of histone H3K4me3 and H3Ac levels atcisregulatory elements on promoter of ERα-regulated gene. In addition, MYSM1 depletion attenuated cell proliferation/growth in BCa-derived cell lines and xenograft models. Knockdown of MYSM1 increased the sensitivity of antiestrogen agents in BCa cells. MYSM1 was highly expressed in clinical BCa samples, especially in aromatase inhibitor (AI) non-responsive tissues. These findings clarify the molecular mechanism of MYSM1 as an epigenetic modifier in regulation of ERα action and provide a potential therapeutic target for endocrine resistance in BCa.

Introduction: Arteriovenous fistula (AVF) nonmaturation is associated with postoperative fibrosis and an increase in lysyl oxidase (LOX) expression. Objective: The purpose of this study was to determine whether unidirectional periadventitial delivery of β-aminoproprionitrile (BAPN) using bilayer poly lactic-co-glycolic acid nanofiber scaffolds is a feasible approach to reduce AVF fibrosis and encourage adaptive vascular remodeling. Methods: AVFs were created in thirty Sprague Dawley rats (200-350 g) of both sexes by an end-to-side anastomosis of the epigastric vein to the femoral artery. BAPN-loaded (b-BAPN) (n=10) or vehicle (b-VEH) (n=10) scaffolds (5 mm x 5 mm) were wrapped around the juxta-anastomotic zone of the epigastric vein immediately after anastomosis. AVFs without treatment were used as an additional control (n=10). Changes in lumen diameter were followed-up weekly using ultrasound. Flow was calculated using the pulse-wave velocity and lumen diameter. AVFs were collected at 21 days for histomorphometric analysis and to assess fibrosis. Results: b-BAPN significantly increased dilation of AVFs at day 14 (185.9%) compared to b-VEH (135.5%; p=0.0006) and control AVFs (113.6%; p2 vs. 95,580 μm 2 ; p=0.0048). While there was no difference in intimal growth (p=0.5460), b-BAPN significantly reduced luminal occlusion with respect to control AVFs (0.0611 vs. 0.2067; p=0.0002). Finally, b-BAPN (49.48%) significantly reduced the fibrosis percent area compared to b-VEH (72.14%; p=0.0016) and control AVFs (74.5%; p=0.0007). Conclusion: Periadventitial LOX inhibition prevents AVF postoperative fibrosis and promotes adaptive vascular remodeling.

In order to address the problem of low ability of intelligent medical auxiliary diagnosis (IMAD), an IMAD based on improved decision tree is proposed. Firstly, the constraint parameter model of IMAD is constructed. Secondly, according to the physiological indexes of IMAD, the independent variables and dependent variables of auxiliary diagnosis are constructed, the quantitative recurrent analysis of IMAD is carried out by using regression analysis method, the data analysis model of IMAD is constructed, and the adaptive classification and recognition of IMAD are carried out. Finally, the attribute feature quantity of IMAD with pathological characteristics is extracted, and the improved decision tree model is used to realize intelligent medical auxiliary, assist in the optimal decision of diagnosis, and realize the effective classification and recognition of pathological characteristics. The results show that this method has better decision-making ability and better classification performance for IMAD, which improves the intelligence and accuracy of intelligent medical auxiliary diagnosis.

A high-resolution (3–8 km) regional oceanic general circulation model is utilized to understand the sea surface temperature (SST) variability of Ningaloo Niño in the southeast Indian Ocean (SEIO). The model reproduces eight Ningaloo Niño events with good fidelity and reveals complicated spatial structures. Mesoscale noises are seen in the warming signature and confirmed by satellite microwave SST data. Model experiments are carried out to quantitatively evaluate the effects of key processes. The results reveal that the surface turbulent heat flux (primarily latent heat flux) is the most important process (contribution > 68%) in driving and damping the SST warming for most events, while the roles of the Indonesian Throughflow (~15%) and local wind forcing are secondary. A suitable air temperature warming is essential to reproducing the reduced surface latent heat loss during the growth of SST warming (~66%), whereas the effect of the increased air humidity is negligibly small (1%). The established SST warming in the mature phase causes increased latent heat loss that initiates the decay of warming. A 20-member ensemble simulation is performed for the 2010/11 super Ningaloo Niño, which confirms the strong influence of ocean internal processes in the redistribution of SST warming signatures. Oceanic eddies can dramatically modulate the magnitudes of local SST warming, particularly in offshore areas where the “signal-to-noise” ratio is low, raising a caution for evaluating the predictability of Ningaloo Niño and its environmental consequences.

Although the moisture feedback has been well known to be essential in the Madden–Julian Oscillation (MJO) dynamics, whether its pre-moistening effect plays a key role in exciting the onset of primary MJO events, as has been confirmed in the successive initiation, remains elusive. In this study, using a hybrid coupled climate model that has a good fidelity in simulating the intraseasonal variability, we develop a new framework of methodology to investigate the nonlinear excitation of primary MJO event, of which the key achievement is the successful implementation of the conditional nonlinear optimal perturbation (CNOP). In an application of this new framework, the CNOP-type moisture perturbations are calculated for the pre-chosen non-MJO reference states and generally favor a moistening in the equatorial region while drying in the poleward. Comparisons of the model simulation with observation give credibility to the existence of moisture signals several weeks before some primary MJO events. A suite of numerical experiments confirms that the CNOPs of moisture can contribute to the excitation and propagation of strong primary MJO events while random perturbations cannot. The moisture budget analysis further reveals the central importance of the horizontal moisture advection, especially the nonlinearly upscaled moisture transports associated with the high-frequency disturbances on the quasi-3–4-day and 6–8-day synoptic time scales, in supporting the nonlinear excitation of the primary MJO events. The subgrid-scale processes of evaporation, condensation and eddy transport of moisture are found to be critical for the pre-moistening effect in the boundary layer as well. This study directly supports the vital importance of the moisture perturbations, which are characterized by a particular pattern concentrated at low levels, to the nonlinear growth and propagation of the primary MJO events.

This study investigates modulation of El Niño–Southern Oscillation (ENSO) on the Madden–Julian oscillation (MJO) propagation during boreal winter. Results show that the spatiotemporal evolution of MJO manifests as a fast equatorially symmetric propagation from the Indian Ocean to the equatorial western Pacific (EWP) during El Niño, whereas the MJO during La Niña is very slow and tends to frequently “detour” via the southern Maritime Continent (MC). The westward group velocity of the MJO is also more significant during El Niño. Based on the dynamics-oriented diagnostics, it is found that, during El Niño, the much stronger leading suppressed convection over the EWP excites a significant front Walker cell, which further triggers a larger Kelvin wave easterly wind anomaly and premoistening and heating effects to the east. However, the equatorial Rossby wave to the west tends to decouple with the MJO convection. Both effects can result in fast MJO propagation. The opposite holds during La Niña. A column-integrated moisture budget analysis reveals that the sea surface temperature anomaly driving both the eastward and equatorward gradients of the low-frequency moisture anomaly during El Niño, as opposed to the westward and poleward gradients during La Niña, induces moist advection over the equatorial eastern MC–EWP region due to the intraseasonal wind anomaly and therefore enhances the zonal asymmetry of the moisture tendency, supporting fast propagation. The role of nonlinear advection by synoptic-scale Kelvin waves is also nonnegligible in distinguishing fast and slow MJO modes. This study emphasizes the crucial roles of dynamical wave feedback and moisture–convection feedback in modulating the MJO propagation by ENSO.

To address the problem of high failure rate and low accuracy in computed tomography (CT) image edge segmentation, we proposed a CT sequence image edge segmentation optimization algorithm using improved convolution neural network. Firstly, the pattern clustering algorithm is applied to cluster the pixels with relationship in the CT sequence image space to extract the edge information of the real CT image; secondly, Euclidean distance is used to calculate similarity and measure similarity, according to the measurement results, convolution neural network (CNN) hierarchical optimization is carried out to improve the convergence ability of CNN; finally, the pixel classification of CT sequence images is carried out, and the edge segmentation of CT sequence images is optimized according to the classification results. The results show that the overall recognition rate of this method is at a high level. The training time is obviously reduced when the training times exceed 12 times, the recall rate is always about 90%, and the accuracy of image segmentation is high, which solves the problem of large failure rate and low accuracy.

Despite the great importance of interactions between moisture, clouds, radiation, and convection in the Madden-Julian Oscillation, their role in the boreal summer intraseasonal oscillation (BSISO) has not been well established. This study investigates the moisture variation of a BSISO during its rapid redevelopment over the eastern Maritime Continent through a cloud-permitting-scale numerical simulation. It is found that moisture variation depends closely on the evolution of clouds and precipitation. Total moisture budget analysis reveals that the deepening and strengthening (lessening) of humidity before (after) the BSISO deep convection are attributed largely to zonal advection. In addition, the column moistening/drying is mostly in phase with the humidity and is related to the maintenance of BSISO.An objective cloud-type classification method and a weak temperature gradient approximation are used to further understand the column moistening/drying. Results indicate that elevated stratiform clouds play a significant role in moistening the lower troposphere through cloud water evaporation. Decreases in deep convection condensation and re-evaporation of deep stratiform precipitation induce moistening during the development and after the decay of BSISO deep convection, respectively. Meanwhile, anomalous longwave radiative heating appears first in the lower troposphere during the developing stage of BSISO, further strengthens via the increase of deep stratiform clouds, and eventually deepens with elevated stratiform clouds. Accordingly, anomalous moistening largely in phase with the humidity of BSISO toward its suppressed stage is induced via compensated ascent. Owing to the anomalous decrease in the ratio of vertical moisture and potential temperature gradients, the cloud-radiation effect is further enhanced in the convective phase of BSISO.

Westerly Wind Events (WWEs) over the tropical Pacific are characterized by their spatiotemporal diversity and classified into six types based on their different locations and durations. Various types of WWEs exhibit quite different characteristics in terms of their amplitudes. The long events with a 10–30-day duration are stronger than the short events with a 6–10-day duration, and the maximum amplitudes of the Central-Pacific (C) type and Eastern-Pacific (E) type of long events are larger than the Western-Pacific (W) type of long ones. The evolutions of these six types of WWEs are also quite different. The W-type short and long events and the C-type long events show a distinct eastward propagation, whereas the C-type short events and the E-type short and long events have no apparent propagation direction. We demonstrate that such a difference in the eastward propagation of WWEs can be significantly associated with the Madden-Julian Oscillation (MJO). The W-type events are more influenced heavily by the MJO, as indicated by their more distinct eastward propagation patterns, than the two other types of WWEs. In addition to the MJO, the convectively coupled Kelvin waves are also associated with the WWEs, especially for the short events.

The Madden-Julian Oscillation (MJO) is a dominant intraseasonal variability originating in the tropics and influencing global weather and climate. Despite this dominance, we still lack reliable precursor signals triggering nonlinear initiation of primary MJO events. Here for the first time, we deal with this question from the point of view of nonlinearity, with successful implementation of conditional nonlinear optimal perturbation (CNOP). Our results show that relative to random perturbations, CNOPs of moisture have the most potential to trigger the strongest primary MJO events more than 15-20 days in advance from the given non-MJO reference states. The CNOPs manifest as a moist equator and aggregate in the lower troposphere, with stronger signals over the western Indian Ocean than over the eastern one. These CNOPs can also capture the observational moist precursor conditions of primary MJO events. This work also implies the necessity of utilizing nonlinear optimal moist initialization in subseasonal predictions. Plain Language Summary As a dominant intraseasonal (20-90 days) variability prevailing in the tropics, the Madden-Julian Oscillation (MJO) casts significant impacts on global weather and climate. However, we still lack reliable precursor signals for MJOs initiating over the western Indian Ocean, especially for primary events, that is, those without an immediately preceding MJO event. Here for the first time, we deal with this topic from the point of view of nonlinearity, with the successful implementation of conditional nonlinear optimal perturbation (CNOP). In particular, we find that our CNOPs can identify the optimal precursors of primary MJO initiation. We examined four non-MJO reference states, selected based on both circulation- and convection-based MJO indices. Although different reference states produce different CNOPs, all tend to manifest as a moist equator and aggregate in the lower troposphere, with stronger signals over the western Indian Ocean than over the eastern Indian Ocean. These CNOP-type moist precursor conditions are also found preceding the onset of observed primary events. We find that, relative to random perturbations, CNOPs of moisture have the most potential to trigger the strongest MJO event more than 15-20 days in advance. This work implies the necessity of utilizing nonlinear optimal moist initialization to improve subseasonal (15-60 days) predictions.

Objective: The aim of this study was to measure the expression of PD-L1, CD1a (a marker for immature dendritic cells), and CD83 (a marker for mature dendritic cells) and further examine the associations of PD-L1, CD83, and CD1a with overall survival (OS) in triple-negative breast carcinoma patients. Methods: PD-L1, CD1a, and CD83 expression in breast carcinoma tissues and CD83 expression in lymph node tissues were examined by immunohistochemistry and tissue microarray in 159 patients. Patients were classified into the low, medium, and high PD-L1, CD1a, and CD83 levels. Pearson χ2 test was used to analyze the correlations between PD-L1, CD1a, and CD83. The Kaplan-Meier method was used to calculate the OS. Multivariate analysis was used to identify determinants of 3- and 5-year OS. Results: 25.1, 25.8, and 49.1% of the patients had low, medium, and high PD-L1 levels, respectively. PD-L1 levels significantly correlated with CD1a (r = 0.30409, p < 0.001) and CD83 levels (r = 0.6146, p < 0.001) in breast carcinoma tissue, as well as CD83 levels (r = 0.17508, p = 0.027) in lymph node. The median OS was 83 months (range 12–106), and the 3- and 5-year OS rates were 94.97% (95% CI 91.57–98.37) and 86.79% (95% CI 81.53–92.06), respectively. Moreover, patients with high median CD1a levels had a significantly lower 5-year OS rate (75.6%) than those with low median CD1a levels (93.5%, p = 0.038). Conclusion: PD-L1, CD1a, and CD83 are variably expressed in triple-negative breast carcinoma tissues, and PD-L1 expression correlates with CD1a and CD83. Higher CD1a levels correlate with PD-L1 expression and predict worse OS in triple-negative breast carcinoma.

Background The arteriovenous fistula (AVF) is the preferred hemodialysis access for end-stage renal disease (ESRD) patients. Yet, establishment of a functional AVF presents a challenge, even for the most experienced surgeons, since postoperative stenosis frequently occludes the AVF. Stenosis results from the loss of compliance in fibrotic areas of the fistula which turns intimal hyperplasia into an occlusive feature. Fibrotic remodeling depends on deposition and crosslinking of collagen by lysyl oxidase (LOX), an enzyme that catalyzes the deamination of lysine and hydroxylysine residues, facilitating intra/intermolecular covalent bonds. We postulate that pharmacological inhibition of lysyl oxidase (LOX) increases postoperative venous compliance and prevents stenosis in a rat AVF model. Methods LOX gene expression and vascular localization were assayed in rat AVFs and human pre-access veins, respectively. Collagen crosslinking was measured in humans AVFs that matured or failed, and in rat AVFs treated with β-aminopropionitrile (BAPN), an irreversible LOX inhibitor. BAPN was either injected systemically or delivered locally around rat AVFs using nanofiber scaffolds. The major endpoints were AVF blood flow, wall fibrosis, collagen crosslinking, and vascular distensibility. Results Non-maturation of human AVFs was associated with higher LOX deposition in pre-access veins (N=20, P=0.029), and increased trivalent crosslinks (N=18, P=0.027) in human AVF tissues. Systemic and local inhibition of LOX increased AVF distensibility, while reducing wall fibrosis and collagen crosslinking in rat fistulas. Conclusions Our results demonstrate that BAPN-mediated inhibition of LOX significantly improves vascular remodeling in experimental fistulas.

The traditional CT image segmentation algorithm is easy to ignore image contour initialization, which leads to the problem of long time consuming and low accuracy. A superpixel mesh CT image improved segmentation algorithm using active contour was proposed. CT image superpixel gridding was carried out first; secondly, on the basis of gridding, the region growth criterion was improved by superpixel processing, the region growth graph was established, the image edge salient graph was calculated based on the growth graph, and the target edge was obtained as the initial contour; finally, the Mumford-Shah model in the active contour model was improved; the energy functional was constructed based on the improved model and transformed into the symbol distance function. The results show that the proposed algorithm takes less time to mesh superpixels, the accuracy of image edge calculation is high, the correct classification coefficient is as high as 0.9, and the accuracy of CT image segmentation is always higher than 90%, which has superiority.

The mechanisms contributing to the excellent mechanical properties of the ultrafine-grained (UFG) Fe-23 wt.%Mn alloy processed by heavy ausforming are unraveled based on detailed characterization analysis and modelling. The UFG microstructure is fully austenitic after the heavy ausforming step involving a 90% rolling reduction; while the material quenched from the coarse-grained (CG) austenite consists of epsilon (e)-martensite and austenite. The UFG Fe23Mn alloy shows a high strain-hardening capacity which leads to a much higher true uniform elongation (0.33) and true tensile strength (1330 MPa) than the CG counterpart (0.17 and 950 MPa, respectively). The high ductility of the heavily-ausformed microstructure with no subsequent annealing step contradicts the general trend of UFG alloys produced by severe plastic deformation. In addition, a ductile fracture mode with improved resistance to damage initiation in the UFG microstructure contrasts with the brittleness of the CG counterpart. Therefore, the UFG Fe23Mn alloy exhibits a high combination of strength, resistance to plastic localization and resistance to cracking. This superior mechanical performance is attributed to the gradual deformation-induced e-martensitic transformation and to the large plastic co-deformation of the UFG e-martensite, in which twinning is suppressed at the expense of the activation of non-basal slip. A mean-field micromechanical model is used to analyze the contribution of the phase transformation to plasticity, and to further rationalize the mechanical response of the UFG e-martensite. This finding provides new insight into the effects of microstructural scale on the mechanical behavior of this class of transformation-induced plasticity (TRIP)-assisted alloys.

Ningaloo Niño – the interannually occurring warming episode in the southeast Indian Ocean (SEIO) – has strong signatures in ocean temperature and circulation and exerts profound impacts on regional climate and marine biosystems. Analysis of observational data and eddy-resolving regional ocean model simulations reveals that the Ningaloo Niño/Niña can also induce pronounced variability in ocean salinity, causing large-scale sea surface salinity (SSS) freshening of 0.15–0.20 psu in the SEIO during its warm phase. Model experiments are performed to understand the underlying processes. This SSS freshening is mutually caused by the increased local precipitation (~68%) and enhanced fresh-water transport of the Indonesian Throughflow (ITF; ~28%) during Ningaloo Niño events. The effects of other processes, such as local winds and evaporation, are secondary (~18%). The ITF enhances the southward fresh-water advection near the eastern boundary, which is critical in causing the strong freshening (> 0.20 psu) near the Western Australian coast. Owing to the strong modulation effect of the ITF, SSS near the coast bears a higher correlation with the El Niño-Southern Oscillation (0.57, 0.77, and 0.70 with Niño-3, Niño-4, and Niño-3.4 indices, respectively) than sea surface temperature (-0.27, -0.42, and -0.35) during 1993-2016. Yet, an idealized model experiment with artificial damping for salinity anomaly indicates that ocean salinity has limited impact on ocean near-surface stratification and thus minimal feedback effect on the warming of Ningaloo Niño.