Thermally-activated precipitation strengthening

Precipitation strengthening is a key strengthening method for metallic materials. However, the temperature effect on precipitation strengthening is still unclear to date. Based on dislocation theory, a thermally-activated precipitation strengthening model is built by considering the competition between shear and bypass mechanisms. For medium-sized precipitate particles, the thermally-activated shear mechanism dominates the precipitation strengthening, resulting in a plateau region. While, for large or very fine precipitate particles, the thermally-activated bypass mechanism dominates the precipitation strengthening, leading to the strengthening or weakening regions. Moreover, the effects of precipitate phase volume fraction, temperature, shear modulus, strain rate, and mobile dislocation density on precipitation strengthening are also investigated. This study not only provides new insights into precipitation strengthening from the perspective of thermal activation but also offers clear guidance for the design of new materials

General Debiasing for Multimodal Sentiment Analysis

Existing work on Multimodal Sentiment Analysis (MSA) utilizes multimodal information for prediction yet unavoidably suffers from fitting the spurious correlations between multimodal features and sentiment labels. For example, if most videos with a blue background have positive labels in a dataset, the model will rely on such correlations for prediction, while ``blue background'' is not a sentiment-related feature. To address this problem, we define a general debiasing MSA task, which aims to enhance the Out-Of-Distribution (OOD) generalization ability of MSA models by reducing their reliance on spurious correlations. To this end, we propose a general debiasing framework based on Inverse Probability Weighting (IPW), which adaptively assigns small weights to the samples with larger bias i.e., the severer spurious correlations). The key to this debiasing framework is to estimate the bias of each sample, which is achieved by two steps: 1) disentangling the robust features and biased features in each modality, and 2) utilizing the biased features to estimate the bias. Finally, we employ IPW to reduce the effects of large-biased samples, facilitating robust feature learning for sentiment prediction. To examine the model's generalization ability, we keep the original testing sets on two benchmarks and additionally construct multiple unimodal and multimodal OOD testing sets. The empirical results demonstrate the superior generalization ability of our proposed framework. We have released the code and data to facilitate the reproduction

Feasibility study for downscaling seasonal tropical cyclone activity using the NCEP regional spectral model

The potential use of the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) for downscaling seasonal tropical cyclone (TC) activity was analyzed here. The NCEP RSM with horizontal resolution of 50 km, was used to downscale the ECHAM4.5 Atmospheric General Circulation Model (AGCM) simulations forced with observed sea surface temperature (SST) over the western North Pacific. An ensemble of ten runs for June–November 1994 and 1998 was studied. The representation of the TCs is much improved compared to the low-resolution forcing AGCM, but the TCs are not as intense as observed ones, as the RSM horizontal resolution is not sufficiently high. The large-scale fields of the RSM are examined and compared to both the AGCM and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. The large-scale fields of RSM characteristics are in general similar to those of the reanalysis. Various properties of the TCs in the RSM are also examined such as first positions, tracks, accumulated cyclone energy (ACE) and duration. While the RSM does not reproduce the higher number of TCs in 1994 than in 1998, other measures of TC activity (ACE, number of cyclone days) in the RSM are higher in 1994 than in 1998

Review of seasonal climate forecasting for agriculture in sub-Saharan Africa

We review the use and value of seasonal climate forecasting for agriculture in sub-Saharan Africa (SSA), with a view to understanding and exploiting opportunities to realize more of its potential benefits. Interaction between the atmosphere and underlying oceans provides the basis for probabilistic forecasts of climate conditions at a seasonal lead-time, including during cropping seasons in parts of SSA. Regional climate outlook forums (RCOF) and national meteorological services (NMS) have been at the forefront of efforts to provide forecast information for agriculture.A survey showed that African NMS often go well beyond the RCOF process to improve seasonal forecast information and disseminate it to the agricultural sector. Evidence from a combination of understanding of how climatic uncertainty impacts agriculture, model based ex-ante analyses, subjective expressions of demand or value, and the few well-documented evaluations of actual use and resulting benefit suggests that seasonal forecasts may have considerable potential to improve agricultural management and rural livelihoods. However, constraints related to legitimacy, salience, access, understanding, capacity to respond and data scarcity have so far limited the widespread use and benefit from seasonal prediction among smallholder farmers. Those constraints that reflect inadequate information products, policies or institutional process can potentially be overcome. Additional opportunities to benefit rural communities come from expanding the use of seasonal forecast information for coordinating input and credit supply, food crisis management, trade and agricultural insurance. The surge of activity surrounding seasonal forecasting in SSA following the 1997/98 El Niño has waned in recent years, but emerging initiatives, such as the Global Framework for Climate Services and ClimDev-Africa, are poised to reinvigorate support for seasonal forecast information services for agriculture. We conclude with a discussion of institutional and policy changes that we believe will greatly enhance the benefits of seasonal forecasting to agriculture in SSA

A framework for examining climate-driven changes to the seasonality and geographical range of coastal pathogens and harmful algae

AbstractClimate change is expected to alter coastal ecosystems in ways which may have predictable consequences for the seasonality and geographical distribution of human pathogens and harmful algae. Here we demonstrate relatively simple approaches for evaluating the risk of occurrence of pathogenic bacteria in the genus Vibrio and outbreaks of toxin-producing harmful algae in the genus Alexandrium, with estimates of uncertainty, in U.S. coastal waters under future climate change scenarios through the end of the 21st century. One approach forces empirical models of growth, abundance and the probability of occurrence of the pathogens and algae at specific locations in the Chesapeake Bay and Puget Sound with ensembles of statistically downscaled climate model projections to produce first order assessments of changes in seasonality. In all of the case studies examined, the seasonal window of occurrence for Vibrio and Alexandrium broadened, indicating longer annual periods of time when there is increased risk for outbreaks. A second approach uses climate model projections coupled with GIS to identify the potential for geographic range shifts for Vibrio spp. in the coastal waters of Alaska. These two approaches could be applied to other coastal pathogens that have climate sensitive drivers to investigate potential changes to the risk of outbreaks in both time (seasonality) and space (geographical distribution) under future climate change scenarios

Orbital Approximation for the Reduced Bloch Equations: Fermi-Dirac Distribution for Interacting Fermions and Hartree-Fock Equation at Finite Temperature

In this paper, we solve a set of hierarchy equations for the reduced statistical density operator in a grand canonical ensemble for an identical many-body fermion system without or with two-body interaction. We take the single-particle approximation, and obtain an eigen-equation for the single-particle states. For the case of no interaction, it is an eigen-equation for the free particles, and solutions are therefore the plane waves. For the case with two-body interaction, however, it is an equation which is the extension of usual Hartre-Fock equation at zero temperature to the case of any finite temperature. The average occupation number for the single-particle states with mean field interaction is also obtained, which has the same Fermi-Dirac distribution from as that for the free fermion gas. The derivation demonstrates that even for an interacting fermion system, only the lowest $N$ orbitals, where $N$ is the number of particles, are occupied at zero temperature. In addition, their practical applications in such fields as studying the temperature effects on the average structure and electronic spectra for macromolecules are discussed.Comment: Modify the last paragraph regarding the applications of the equations Add reference

Temporal Sentence Grounding in Streaming Videos

This paper aims to tackle a novel task - Temporal Sentence Grounding in Streaming Videos (TSGSV). The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query. Unlike regular videos, streaming videos are acquired continuously from a particular source, and are always desired to be processed on-the-fly in many applications such as surveillance and live-stream analysis. Thus, TSGSV is challenging since it requires the model to infer without future frames and process long historical frames effectively, which is untouched in the early methods. To specifically address the above challenges, we propose two novel methods: (1) a TwinNet structure that enables the model to learn about upcoming events; and (2) a language-guided feature compressor that eliminates redundant visual frames and reinforces the frames that are relevant to the query. We conduct extensive experiments using ActivityNet Captions, TACoS, and MAD datasets. The results demonstrate the superiority of our proposed methods. A systematic ablation study also confirms their effectiveness.Comment: Accepted by ACM MM 202

Decreased Glomerular Filtration Rate Is Associated with Mortality and Cardiovascular Events in Patients with Hypertension: A Prospective Study

BACKGROUND: Few studies reported the associations between decreased glomerular filtration rate (GFR) and mortality, coronary heart disease (CHD), and stroke in hypertensive patients. We aim to assess the associations between GFR and mortality, CHD, and stroke in hypertensive patients and to evaluate whether low GFR can improve the prediction of these outcomes in addition to conventional cardiovascular risk factors. METHODS AND FINDINGS: This is an observational prospective study and 3,711 eligible hypertensive patients aged ≥5 years from rural areas of China were used for the present analysis. The associations between eGFR and outcomes, followed by a median of 4.9 years, were evaluated using Cox proportional hazards models adjusting for other potential confounders. Low eGFR was independently associated with risk of all-cause mortality, cardiovascular mortality, and incident stroke [multivariable adjusted hazard ratios (95% confidence intervals) for eGFR <60 ml/min/1.73 m(2) relative to eGFR ≥90 ml/min/1.73 m(2) were 1.824 (1.047-3.365), 2.371 (1.109-5.068), and 2.493 (1.193-5.212), respectively]. We found no independent association between eGFR and the risk of CHD. For 4-year all-cause and cardiovascular mortality, integrated discrimination improvement (IDI) was positive when eGFR were added to traditional risk factors (1.51%, P = 0.016, and 1.99%, P = 0.017, respectively). For stroke and CHD events, net reclassification improvements (NRI) were 5.9% (P = 0.012) and 1.8% (P = 0.083) for eGFR, respectively. CONCLUSIONS: We have established an inversely independent association between eGFR and all-cause mortality, cardiovascular mortality, and stroke in hypertensive patients in rural areas of China. Further, addition of eGFR significantly improved the prediction of 4-year mortality and stroke over and above that of conventional risk factors. We recommend that eGFR be incorporated into prognostic assessment for patients with hypertension in rural areas of China. LIMITATIONS: We did not have sufficient information on atrial fibrillation to control for the potential covariate. These associations should be further confirmed in future

Associations of trajectories in body roundness index with incident cardiovascular disease: a prospective cohort study in rural China

AimsThe body roundness index (BRI) has good predictive ability for both body fat and visceral adipose tissue. Longitudinal BRI trajectories can reveal the potential dynamic patterns of change over time. This prospective study assessed potential associations between BRI trajectories and incident cardiovascular disease (CVD) in rural regions of Northeast China.MethodsIn total, 13,209 participants (mean age: 49.0 ± 10.3 years, 6,856 [51.9%] male) were enrolled with three repeated times of BRI measurements at baseline (2004–2006), 2008, and 2010, and followed up until 2017 in this prospective study. Using latent mixture model, the BRI trajectories were determined based on the data from baseline, 2008 and 2010. Composite CVD events (myocardial infarction, stroke, and CVD death combined) was the primary endpoint. Cox proportional-hazards models were used to analyze the longitudinal associations between BRI trajectories and incident CVD.ResultsThree distinct BRI trajectories were identified: high-stable (n = 538), moderate-stable (n = 1,542), and low-stable (n = 11,129). In total, 1,382 CVD events were recorded during follow-up. After adjustment for confounders, the moderate-stable and high-stable BRI groups had a higher CVD risk than did the low-stable BRI group, and the HR (95%CI) were 1.346 (1.154, 1.571) and 1.751 (1.398, 2.194), respectively. Similar associations were observed between the trajectories of BRI and the risk of stroke and CVD death. The high-stable group was also significantly and independently associated with CVD, myocardial infarction, stroke, and CVD death in participants aged &lt;50 years.ConclusionBRI trajectory was positively associated with incident CVD, providing a novel possibility for the primary prevention of CVD in rural regions of China