Changes In Gradient Research Articles

Abstract 4132223: Mavacamten in adolescent patients with symptomatic obstructive hypertrophic cardiomyopathy: design of the Phase 3 SCOUT-HCM trial

Background: While most current treatments can improve symptoms in patients with obstructive hypertrophic cardiomyopathy (HCM), they may be poorly tolerated and do not target the underlying pathophysiology. Mavacamten is the first and only cardiac myosin inhibitor approved for the treatment of adults with symptomatic New York Heart Association (NYHA) class II-III obstructive HCM but has not been evaluated in a pediatric age group. SCOUT-HCM (Study of MavaCamten in AdOlescents with Symptomatic ObstrUcTive HCM; NCT06253221) will evaluate the efficacy, safety, and pharmacokinetics of mavacamten in adolescents with symptomatic obstructive HCM. Methods: SCOUT-HCM is a randomized, double-blind, placebo-controlled, international phase 3 clinical trial that will enroll 40 adolescents (age 12 to <18 years) with obstructive HCM ( Figure ). Patients will receive mavacamten or placebo during the first 28 weeks, followed by a 28-week double-blind active treatment period. Inclusion criteria include a diagnosis of HCM with presence of symptoms and left ventricular outflow tract (LVOT) obstruction. Patients with HCM phenocopies, LVEF <50% at rest in the past 6 months, planned escalation in HCM therapy or upcoming intervention (eg, major cardiac surgery) will be excluded. The primary endpoint is change in Valsalva LVOT gradient from baseline to week 28. Key secondary endpoints include other echocardiographic parameters, safety, pharmacokinetics, and exercise capacity. Conclusions: SCOUT-HCM is the first randomized controlled trial evaluating a targeted myosin inhibitor in adolescents with symptomatic obstructive HCM. The results will inform the utility of mavacamten in adolescent patients with symptomatic obstructive HCM.

Constraints on the Projected Tropical Pacific Sea Surface Temperature Warming Pattern by the Tropical North Atlantic Cold SST Bias in CMIP6 Models

AbstractReliable projections of the tropical Pacific sea surface temperature (SST) warming (TPSW) patterns are critically important for exploring the future climate change. However, climate models suffer from long‐standing common biases in simulating the present‐day climate, raising doubts about the model projected TPSW patterns. Here by using outputs from 30 CMIP6 models, we find the projected TPSW patterns are significantly correlated with the simulated present‐day SST in the tropical North Atlantic (TNA), with higher present‐day TNA SSTs tending to project more weakened zonal SST gradients by producing more present‐day low‐level clouds and the resultant positive cloud–shortwave–SST feedbacks over the eastern equatorial Pacific. An emergent constraint using observed TNA SST reveals a consistent El Niño‐like warming pattern in all models with more weakened zonal SST gradient than before in most models, together with a reduction of the inter‐model uncertainty in the zonal SST gradient change by more than 20%.

Research on the prediction of material removal and over-grinding optimization for abrasive flow machining of 3D printed right-angle bends

Abstract Addressing the issue of over-grinding on the outer side of right-angle bends in abrasive flow machining due to the gradient change of abrasive inertia force, a model for predicting material removal and an optimized structure for right-angle bends, both based on abrasive flow machining, are proposed. In this paper, the 3D-printed aluminium alloy right-angle bends are used as experimental objects, and the Carreau-Yasuda equations are fitted for simulation and analysis after rheological testing of the medium used in the test. A predictive model for material removal was developed by integrating simulated channel pressure with machining cycles, and its effectiveness was validated through experiments. Using this predictive model for structural optimization of bends, an unevenly thickened optimized right-angle bend was designed. The machining tests verified the accuracy of the simulation analysis, and the over-grinding region of the right-angle bend appeared at the maximum of the pressure region in the numerical simulation. At a processing pressure of 10 MPa and cycles of 20, 60, and 100, the prediction model resulted in material removal errors of 6.94%, 8.93%, and 13.31% respectively for the outer side of the bend, indicating a good fit of the prediction model. The optimized bend designed according to the predictive model exhibited an 80.37% reduction in overall deviation at the elbow compared to conventional right-angle bends, and a 67.31% reduction in contour deviation at the area most affected by inertia forces, effectively mitigating the issue of over-grinding at the elbow. This research facilitates quantitative control of material removal in abrasive flow machining of right-angle bends and provides theoretical support for non-uniform thickness design in bends.

Evaluation of Secondary Buckling and Ultimate Strength Behaviour According to Boundary Conditions of Curved Plate Subjected to Compressive Load

This paper analyzed the buckling and ultimate strength characteristics of plate members with curvature, which are essentially used in ships and marine structures, through numerical analysis. Major structural members are affected by rotational velocity depending on the rigidity of structures placed around them, and it is very important to check how this affects buckling and ultimate strength. The aspect ratio of the curved plate was adopted as 2.5, 3.0, and 3.5 to reflect the plate thickness range and high-strength steel characteristics actually used. In the case of no curvature, and in the case of curvature, 5 degrees, 10 degrees, 15 degrees, 20 degrees, 30 degrees, and 45 degrees were considered. Under certain thickness and curvature conditions, secondary buckling occurs and the buckling state of the plate changes rapidly. Therefore, the final strength is evaluated lower than in the case where there is no curvature. Buckling and ultimate strength were high in a clamped condition around the curved plate, and there was no specificity in behavior depending on the aspect ratio change. In the four-side simply supported condition, the in-plane stiffness gradient changes depending on the aspect ratio due to the secondary buckling effect, and this characteristic is a phenomenon that is not considered at all in the existing classification method.

Improvement of multiscale decomposition for space-based gravitational wave signal processing technology.

During the process of detecting gravitational waves in space, addressing noise issues caused by terrestrial vibrations, natural environmental changes, and the factors intrinsic to the detectors, this paper proposes a multiscale variational mode adaptive denoising algorithm based on momentum gradient descent. This algorithm integrates momentum factors and multiscale concepts into the variational mode algorithm to resolve the issue of multiple local optima encountered during operation, reduce oscillations in regions with large or unstable gradient changes, and improve convergence speed. Additionally, the algorithm combines the least mean squares algorithm to automatically adjust weights, thereby mitigating the impact of noise, addressing the issue of noise from multiple and random sources, effectively suppressing noise in the gravitational wave signal, and enhancing the quality and reliability of the gravitational wave signal. Experimental results demonstrate that this algorithm performs better than other algorithms in noise suppression, effectively reducing noise in gravitational wave signals and meeting the noise suppression requirements for space-based gravitational wave detection.

Multi-scenario simulation and optimization of habitat quality under karst desertification management

IntroductionInvestigation of the evolutionary trend of habitat quality in karst and rocky desertification zones is crucial for enhancing ecological security and conservation.MethodsAnalysis of land use statistics from the years 2000, 2010, and 2020, changes in habitat quality (HQ) and land use (LULC) between 2000 and 2020 were analyzed using Huize County in Yunnan Province as an example. The InVEST and FLUS models were applied to simulate LULC under different scenarios in 2030 and 2040 and assess changes in spatial gradients of habitat quality at each timepoint and factors influencing them.ResultsThe findings indicated that (1) The predominant land use types are grassland and woodland, experiencing the most significant growth in urbanized areas, the main sources of which are paddy fields and high-cover grassland. (2) The habitat quality between 2000 and 2020 was average and displayed a consistent decline. The spatial distribution pattern indicates low HQ in urban areas, high HQ in the outskirts, low HQ in the south-west, and high HQ in the north-east. In all four scenarios, habitat quality predominantly decreases in urban areas and regions with a dense concentration of built-up land. (3) Habitat quality spatial distribution is primarily affected by the type of land use, with NDVI being the secondary determinant.DiscussionThe ecological environment of Huize County must be restored and safeguarded with a focus on ecological priorities and harmonious development scenarios. This study provides methodological lessons for ecorestoration and policymakers in areas of karstic rocky desertification.

An integrated CFD and machine learning analysis on pilots in-flight thermal comfort and productivity

In the cockpit, minimising the pilots' thermal discomfort due to solar exposure while ensuring clear visibility is essential. This study numerically examined the solar radiation effect on thermal fields of an Airbus A320 cockpit and assessed global and local thermal comfort of three aircrews using the Fanger model and the Equivalent Homogeneous Temperature (EHT) model. The productivity of aircrews based on thermal comfort was further estimated. A total of 27 cases, encompassing a combination of environmental and HVAC parameters were performed. This dataset was used for data analysis, employing an explainable machine, XGBoost, to highlight the significance of each variable on the pilot's thermal satisfaction. Outcomes proved that solar radiation penetrating the cockpit domain facilitated a non-homogeneous temperature distribution and thermal stratification. With strong solar exposure, it was recommended to set cockpit's maximum supply temperature smaller than 19 ∘ C, maintaining RH between 10–20% for appropriate global thermal environment. Aircrew productivity loss was estimated to decline by 2.7% to 5.6% due to solar intensity variation, with pilot being the most affected. Without solar radiation, the local comfort of lower body segments was compromised. Rising solar radiation resulted in significant EHT gradient changes in the upper torso compared to the lower body, highlighting the predominance of radiative heat transfer at the upper level. Analysis via XGBoost revealed that mean radiant temperature had the most substantial impact on thermal satisfaction in the cockpit, underscoring the efficiency of optimising cockpit materials for better absorption and reflection of radiative heat for enhanced thermal environment control.

Aluminum Josephson junction microstructure and electrical properties modified by thermal annealing

Reproducibility of Al/AlOx/Al Josephson junctions is a challenge for scaling up superconducting quantum processors. The frequency uncertainty of the transmon qubits arising from the fabrication process is attributed to deviations in the Josephson junction microstructure and electrical properties. Here, we present a solution for this problem using the post-fabrication Josephson junction thermal annealing process. The developed thermal post-exposure method allows not only to increase the junction resistance by 175%, but also to decrease by 60% with a step of 10% in Rn, which opens up new possibilities for tuning the frequency of qubits. The resistance is shown to be strongly temperature dependent, and is weakly dependent on the holding time. The linear dimensions of the electrodes and the sidewalls contribution to the total JJ area also have a significant impact on the final resistance after annealing. Finally, a theoretical model of the structure modification in a tunnel barrier with changes in oxygen concentration gradient is proposed. The proposed thermal annealing approach can be used to form stable and reproducible tunnel barriers and scalable frequency trimming for widely used fixed-frequency transmon qubits.

Regulatory mechanism of bamboo biochar dosage on cadmium accumulation in Salix psammophila: insights from rhizosphere microbial communities, assembly processes, and interactions

Soil amendments play a pivotal role in regulating rhizosphere microbial communities, which is essential for maintaining robust plant growth under adverse environmental conditions. However, the microbial mechanisms that underlie the impact of biochar on phytoremediation performance remain incompletely understood in the context of different application rates. Here, we compared the phytoremediation performance, rhizosphere microbial community characteristics, and microbial interactions in Salix psammophila across different biochar application rates (1%, 3%, 5%, and 7%) in Cd-contaminated soil. Applying 5% biochar increased plant biomass by 10.02%, root activity by 183.82%, and Cd accumulation by 13.65%. Lower biochar rates (1% and 3%) decreased Cd accumulation in plants by 21.89% and 42.05%, respectively, compared to the control. Rhizosphere soil properties and Cd content, except for nitrogen, showed a gradient change with increasing biochar application rates. This was accompanied by an elevation in the Chao1 index for the bacterial community, although the fungal community remained unaffected in terms of diversity and structure. Null-model analyses indicated that fungal community assembly was mainly driven by ecological drift, explaining its unresponsiveness to biochar application. Applying 1% biochar enhanced microbial network stability while reducing bacterial network complexity. Conversely, 3% biochar application resulted in the lowest microbial network stability. Biochar application, except 3%, reduced the proportion of bacteria-fungi associations, suggesting increased independence between two microbial kingdoms. Random forest and piecewise structural equation models revealed that phytoremediation performance is influenced by microbial network stability, complexity, and bacteria-fungi associations. Fungal complexity and stability, along with bacterial stability, were identified as key predictors of phytoremediation performance. Our findings reveal potential mechanisms by which biochar influences phytoremediation through altering microbial interactions. For long-term microbial stability and cost-effectiveness, a 1% biochar application is recommended for phytoremediation. Conversely, for rapid Cd accumulation in plants, a 5% biochar application is optimal.Graphical

Sensing force gradients with cavity optomechanics while evading backaction

We study force-gradient sensing with a coherently driven mechanical resonator and phase-sensitive detection of motion through the two-tone backaction evading measurement of cavity optomechanics. The response of the optomechanical system, solved by numerical integration of the classical equations of motion, shows an extended region which is monotonic to changes in force gradient. We use Floquet theory to model the fluctuations, which rise only slightly above that of the usual backaction evading measurement in the presence of the mechanical drive. The monotonic response and minimal backaction are advantageous for applications such as atomic force microscopy. Published by the American Physical Society 2024

Thrombus attenuation predicts natural history of hypo-attenuating leaflet thickening after transcatheter aortic valve replacement

Abstract Background Hypo-attenuating leaflet thickening (HALT) after transcatheter aortic valve replacement (TAVR) occurs in up to 25% of patients and is characterized by diverse temporal dynamics. Several studies investigated the natural history of HALT in transcatheter and surgical cohorts, but little is known about the imaging features of persistent thrombus. Purpose To examine the association of quantitative HALT volume and attenuation from computed tomography angiography (CTA) with its natural history. Methods We prospectively examined patients with HALT present on CTA at 30 days after TAVR and who underwent a follow-up CTA at one year. Hypoattenuation affecting motion (HAM) was defined as the presence of HALT with at least moderately reduced (>50%) leaflet motion. HALT was quantified by segmenting the inner volume of the bioprosthetic frame at the level of the leaflets and extracting voxels between a threshold of -200 to 200 HU. Thrombus volume, mean thrombus attenuation and thrombus heterogeneity measured with standard deviation of attenuation were automatically calculated (Figure 1). Results A total of 37 patients (70% men, 71±7 years old) undergoing TAVR with balloon-expandable SAPIEN3 (86%) and self-expanding EVOLUT (14%) valves were evaluated. Hypoattenuation affecting motion (HAM) at 30 days after TAVR was present in 29 (74%) patients. Patients with HAM had higher thrombus volume than patients without reduced leaflet motion (0.40cm3 [IQR 0.16 – 0.61cm3] vs 0.14 [IQR 0.06 – 0.19 cm3], p=0.009) but comparable mean attenuation values (145HU [IQR 141-151HU] vs 123 [IQR 114 – 141HU], p=0.079). Only 3 patients were switched to oral anticoagulation following HALT detection. At one year, HALT resolution was observed in 18/37 (48%) and HAM resolution in 19/29 (65%). No difference in quantitative thrombus features was noted between patients with persistent and resolved HALT. Notably, patients with persistent HAM had higher mean thrombus attenuation (141HU [IQR 123-156HU] vs 123HU [IQR 110 – 138 HU), p=0.045; Figure 2) and thrombus heterogeneity (58HU [IQR 51-63HU] vs 48HU [IQR 41- 54HU], p=0.021) than resolved HAM. Mean thrombus attenuation (area under the curve of 0.732, p=0.044) and thrombus heterogeneity (area under the curve of 0.763, p=0.022) were predictive of HAM resolution at one year. The optimal cutoff values as determined by Youden index was 140HU for mean attenuation and 52HU for heterogeneity. There was an increase in the mean transvalvular gradients between measurements at 30 days and one year in patients with persistent HAM as compared to patients with HAM resolution (Δ3mmHg [IQR -3 – 11mmHg] vs Δ-1mmHg [IQR -4 – 0mmHg], p=0.049). The volume of thrombus at one year was associated with the magnitude of change in transvalvular gradients (β = 10.3, 95% CI 1.6- 19.0, p=0.025). Conclusion Quantitative evaluation of HALT by CTA may aid the identification of patients at risk of persistent thrombus.

GDMol: Generative Double-Masking Self-Supervised Learning for Molecular Property Prediction.

Effective molecular feature representation is crucial for drug property prediction. Recent years have seen increased attention on graph neural networks (GNNs) that are pre-trained using self-supervised learning techniques, aiming to overcome the scarcity of labeled data in molecular property prediction. Traditional GNNs in self-supervised molecular property prediction typically perform a single masking operation on the nodes and edges of the input molecular graph, masking only local information and insufficient for thorough self-supervised training. Hence, we propose a model for molecular property prediction based on generative double-masking self-supervised learning, termed as GDMol. This integrates generative learning into the self-supervised learning framework for latent representation, and applies a second round of masking to these latent representations, enabling the model to better capture global information and semantic knowledge of the molecules for a richer, more informative representation, thereby achieving more accurate and robust molecular property prediction. Our experiments on 5 datasets demonstrated superior performance of GDMol in predicting molecular properties across different domains. Moreover, we used the masking operation to traverse through the gradient changes of each node, the magnitude and sign of which reflect the positive and negative contribution respectively of the local structure in the molecule to the prediction outcome. This in-depth interpretative analysis not only enhances the model's interpretability, but also provides more targeted insights and direction for optimizing drug molecules. In summary, this research offers novel insights on improving molecular property prediction tasks, and paves the way for further research on the application of generative learning and self-supervised learning in the field of chemistry.

Madden Julian Oscillation Moves Faster as the Meridional Moisture Gradient Intensifies in a Warming World

AbstractThe eastward‐moving large‐scale convective system associated with the Madden‐Julian Oscillation (MJO) significantly impact global weather and climate. Recent decades have seen notable changes in the MJO's lifecycle due to non‐uniform tropical ocean warming, with the roles of natural climate variability and anthropogenic influence still requiring quantification. This study examines observed and projected long‐term changes in the MJO phase speed using four twentieth‐century reanalyses and CMIP6 simulations. We find a substantial increase in MJO phase speed in three reanalyses during the twentieth century (0.6–1.2 m s⁻1 century⁻1) and further increase in MJO phase speed during the twenty‐first century (0.3–1.5 m s⁻1 century⁻1), with notable multidecadal fluctuations. We attribute the overall acceleration of the MJO to the global warming‐driven increase in the meridional moisture gradient around the warm pool while attributing the multidecadal variability in the MJO phase speed to changes in the zonal moisture gradient associated with the Pacific Decadal Oscillation.

The Global Atmospheric Energy Cycle in TaiESM1: Present and Future

AbstractThe Lorenz Energy Cycle (LEC) in the Taiwan Earth System Model Version 1 (TaiESM1) historical simulation is calculated and compared with ERA5 to evaluate the model performance from the thermodynamic aspect. The future change of LEC is accessed by comparing the SSP5‐8.5 and historical simulations in TaiESM1. TaiESM1 reasonably simulates the global mean, seasonal cycle, and spatial patterns of the energy reservoirs with larger values in the mean energy components and smaller in the eddy energy components. The energy cycle in TaiESM1 is about 35%–45% stronger than ERA5, except from December to February. The impact of global warming on the LEC is different at the vertical levels. The influence of meridional temperature gradient change is the dominant factor in the intensity of the energy cycle, and the change in static stability only contributes to the lower troposphere. Lifting the tropopause in the tropics increases the meridional temperature gradient and produces more zonal mean potential energy (PM) in the upper troposphere. PM is the primary driver of the LEC and leads to a more active energy cycle in the upper troposphere. As the tropical tropospheric depth increases and the mid‐latitude eddy activities become more active, more (less) energy is stored in the upper (lower) troposphere, and the energy conversion processes tend to become stronger (weaker) in the upper (lower) troposphere.

Projected North Equatorial Current/Countercurrent Towards an El Niño-Like Condition in the Western Pacific under Moderate and Worst-case CO2 Emission Scenarios

Abstract Validating the mean state and historical trends of the North Equatorial Current and Countercurrent (NEC and NECC) in 36 Coupled Model Intercomparison Project (CMIP) phase 5 models and 32 CMIP phase 6 models with those in ocean reanalysis products, this study extracts the most qualified 17 model outputs to explore the projected changes in NEC and NECC in the western Pacific Ocean under scenarios of moderate and worst-case CO2 emissions. NEC and NECC are robustly predicted to have an El Niño-like change, in which the NEC (NECC) tends to intensify with a poleward (equatorward) movement, during the 21st century under both scenarios. Meanwhile, the Kuroshio and Mindanao Current are projected to become weaker. Change in meridional gradient of basin-scale wind stress curl in the tropical Pacific Ocean is the major contributor to the centennial changes in NEC and NECC; however, anomalous wind stress curl dipole on the two sides of NEC off the eastern Philippines is the major factor in controlling the western boundary currents. This study not only represents a step forward in understanding the impact of global warming on the western tropical Pacific surface circulation, but also serves as a reference for downscaled modeling, which can better resolve regional circulation and western boundary currents, for selecting suitable inputs from a large number of CMIP models.

Mitochondrial DNA patterns describe the evolutionary history of the bonnethead shark Sphyrna tiburo (Linneus 1758) complex in the western Atlantic Ocean.

The apparent lack of physical barriers in the marine realm has created the conception that many groups have a constant gene flow. However, changes in ocean circulation patterns, glacial cycles, temperature, and salinity gradients are responsible for vicariant events in many fish species, including sharks. The bonnethead shark, Sphyrna tiburo, is an endangered small coastal shark species. Although considerable efforts have recently been undertaken, little remains known about the possible biogeographic scenario that can explain its actual distribution within the western Atlantic (WA). Here, we used 599 mitochondrial sequences to assess the phylogeographic structure and implement Bayesian phylogenetic analyses to obtain divergence times and reconstruct the ancestral geographic range. This allowed us to infer processes responsible for the diversification of S. tiburo into major divergent lineages. Our results indicated that S. tiburo in the WA represents three independent lineages, with Brazilian samples differentiated into a distinct genetic cluster. The posterior probability of ancestral range analysis indicated that the species likely originated in the northern region (Carolina Province and the southern Gulf of Mexico), where it colonized southward through the uplifting of the Central American Isthmus (CAI). The Northern and Caribbean genetic clusters appear to have arisen from the intensification of the Loop Current, which currently flows northward passing the Yucatan Peninsula, Gulf of Mexico, and east Florida. Following initial colonization, the Northeastern Brazil group differentiated from the Caribbean region due to the sediment and freshwater discharge of the Amazon-Orinoco Plume. Thus, the evolutionary history of the S. tiburo complex can be explained by a combination of dispersal and vicariance events that occurred over the last ~5 million years (MY). We established and confirmed the species and population limits, demonstrating that the Amazon-Orinoco Plume constitutes a significant dispersal barrier for coastal sharks. Finally, we discuss some recommendations for the conservation of the bonnethead shark.

Macroscale Gradient Dysfunction in Alzheimer's Disease: Patterns With Cognition Terms and Gene Expression Profiles.

Macroscale functional gradient techniques provide a continuous coordinate system that extends from unimodal regions to transmodal higher-order networks. However, the alterations of these functional gradients in AD and their correlations with cognitive terms and gene expression profiles remain to be established. In the present study, we directly studied the functional gradients with functional MRI data from seven scanners. We adopted data-driven meta-analytic techniques to unveil AD-associated changes in the functional gradients. The principal primary-to-transmodal gradient was suppressed in AD. Compared to NCs, AD patients exhibited global connectome gradient alterations, including reduced gradient range and gradient variation, increased gradient scores in the somatomotor, ventral attention, and frontoparietal regions, and decreased in the default mode network. More importantly, the Gene Ontology terms of biological processes were significantly enriched in the potassium ion transport and protein-containing complex remodeling. Our compelling evidence provides a new perspective in understanding the connectome alterations in AD.

Comparing MJO Intensity over the Tropical Western Pacific during Mega and Equatorial La Niña Winters

Abstract This study investigated variations in the Madden–Julian oscillation (MJO) behavior between two types of La Niña winters: mega and equatorial La Niñas. Results of this work show that in contrast to mega conditions, accompanied by more abundant intraseasonal column-integrated moisture anomalies over the planetary boundary layer, intensities of intraseasonal outgoing longwave radiation anomalies are stronger over the tropical western Pacific (WP) at MJO phases 5–6 under equatorial conditions. The occurrence of the moisture anomaly change averaged over the tropical WP is supported by a distinct moisture tendency difference. Moisture budget and multiscale interaction diagnoses underscore the pivotal effect of an area-averaged vertical gradient change in low-frequency background moisture in driving such tendency change. Considering notable MJO convection variations, the teleconnections associated with MJO phases 5–6 over East Asia (EA) were also explored, including warmer surface air temperature anomalies and stronger positive geopotential height anomalies at 200 hPa on the intraseasonal time scale under equatorial conditions. Results from a linear baroclinic model demonstrate that such teleconnection changes could be effectively explained by the linear response to the MJO’s diabatic heating anomaly. Roles of mean state and MJO itself variations in the linear response change are also discussed. These findings provide novel insights into MJO activity and offer potential improvements for subseasonal forecasting in EA. Significance Statement The relationship between El Niño–Southern Oscillation (ENSO) and MJO has been extensively explored recently. However, variations in the MJO behavior and its climate effects under mega and equatorial La Niña winters have not been thoroughly investigated. In this work, we utilized reanalysis datasets and an idealized linear baroclinic model to address these questions. We observed more robust and abundant intraseasonal convection activity and planetary boundary layer–integrated moisture anomaly averaged over the tropical WP at MJO phases 5–6 under equatorial conditions than mega conditions, which is closely linked with the vertical gradient change in low-frequency background moisture. Additionally, MJO-related teleconnections also exhibit some changes. This work may provide a new perspective on understanding the relationship between the MJO and ENSO and offer potential improvements for the subseasonal forecast.

A fault diagnosis method for bearings and gears in rotating machinery based on data fusion and transfer learning

Abstract Rotating machinery is a crucial component of industrial equipment, and the fault diagnosis of bearings and gears, as vital elements of rotating machinery, is essential since they often fail under harsh working conditions, leading to significant property losses and serious personal safety problems. However, fault data for gears and bearings are often sparse in actual condition, and it is a challenge to ensure the reliability and stability of fault diagnosis results by extracting the features of a single data. To solve the above problems, this paper proposes a fault diagnosis method that combines Transfer Learning and data fusion techniques. Firstly, in this method, two kinds of fault signals are transformed into Gramian Angular Difference Fields and Recurrence Plot. Next, a U-shaped feature fusion dual discriminator generative adversarial network is used to fuse two-dimensional images from multiple sensor data. Its feature fusion module deeply integrates the features of the two images, thereby solving the impact of single data on the reliability and stability of fault diagnosis. Moreover, open-source datasets are used for Transfer Learning training to tackle the small sample problem. Finally, a decision-level information fusion classifier, the Dual-Branch Dempster-Shafer Classifier (DB-DSC), classifies the fused images. This classifier incorporates an improved soft threshold function and D-S evidence theory to achieve adaptive gradient changes and improve the robustness and accuracy of classification results. The experimental results show the effectiveness and stability of the proposed method, and the generated images get high score in several metrics. The average classification accuracy of the classification network reaches 93% and 92.5% on the two datasets, Therefore, the proposed method exhibits strong fault diagnosis capabilities under the small sample conditions of bearings and gears.

Predicting rapid adaptation in time from adaptation in space: A 30-year field experiment in marine snails

Predicting the outcomes of adaptation is a major goal of evolutionary biology. When temporal changes in the environment mirror spatial gradients, it opens up the potential for predicting the course of adaptive evolution over time based on patterns of spatial genetic and phenotypic variation. We assessed this approach in a 30-year transplant experiment in the intertidal snail Littorina saxatilis . In 1992, snails were transplanted from a predation-dominated environment to one dominated by wave action. On the basis of spatial patterns, we predicted transitions in shell size and morphology, allele frequencies at positions throughout the genome, and chromosomal rearrangement frequencies. Observed changes closely agreed with predictions and transformation was both dramatic and rapid. Hence, adaptation can be predicted from knowledge of the phenotypic and genetic variation among populations.