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High- and medium-entropy alloys are considered as new and promising material candidates for extreme service conditions. Due to the high strength and significant work-hardening under cold-forming conditions, the hot bulk-forming process is often used for raw billets of high-entropy alloys, which requires a thorough understanding of the hot flow behavior of new material and finite-element simulations of processing. In this paper, first, the hot compression tests of NbTiVZr 0.5 medium-entropy alloy were carried out, and the flow stress–strain curves of NbTiVZr 0.5 alloy at different temperatures 800–1000 °C and strain rates 0.001–0.1 /s were obtained, which enables the feasibility of hot bulk-forming such a new material to be evaluated. EBSD grain morphology and grain size under typical conditions were characterized to provide quantitative microscopic variables. Using the determined macro- and micro-values, a physical-mechanism-based constitutive model of NbTiVZr 0.5 medium-entropy alloy was established considering the dynamic recrystallization and adiabatic heating effects, particularly in hot bulk-forming. The hot flow behavior under different deformation conditions was accurately predicted with good agreement with experimentation. The calculated R -value of 0.93 further demonstrates the accuracy of the predicted results.

We utilize a global warming level (GWL) lens to evaluate global and regional patterns of agricultural impacts as global surface temperature increases, providing a unique perspective on the experience of stakeholders with continued warming in the 21st century. We analyze crop productivity outputs from 11 crop models simulating 5 climate models under 3 emissions scenarios across 4 crops within the AgMIP/ISIMIP Phase 3 ensemble. We categorize regional productivity changes (without adaptation) into 9 characteristic climate change response patterns, identifying consistent increases and decreases as well as non‐linear (peak or dip) responses indicative of inflection points reversing trends as GWLs increase. Many maize regions and pockets of wheat, rice and soybean show peak decrease patterns where initial increases may lull stakeholders into complacency or maladaptation before productivity shifts to losses at higher GWLs. Although the GWL perspective has proven useful in connecting diverse climate models and emissions scenarios, we identify multiple pitfalls that recommend proceeding with caution when applying this approach to climate impacts. Chief among these is that carbon dioxide (CO2) concentrations at any GWL depend on a climate model's transient climate response (TCR). Higher CO2 concentrations generally benefit crop productivity, so this leads to more pessimistic agricultural projections for so‐called “hot” models and can skew multi‐model ensemble results as models with high TCR are disproportionately likely to reach higher GWLs. While there are strong connections between many climatic impact‐drivers and GWLs, vulnerability and exposure components of food system risk are strongly dependent on development pathways. Plain Language Summary This study uses the latest ensemble of crop and climate models with a framework to identify cropping systems and regions where non‐linear aspects of agricultural system response to climate change could lead to complacency or maladaptation. Results will help readers understand the different experiences and contextual adaptation needs for food systems in the coming decades. This framework could be widely applied across all impacts sectors. Analysis also highlights that climate models with particularly strong climate sensitivity lead more pessimistic projections by crop impacts, underscoring the need for special care in the use of climate model ensembles for impact assessments. Key Points Climate change response patterns show regional farming systems where initial positive changes give way to long‐term detrimental impacts Regional and species‐dependent patterns of agricultural impacts on benchmark global warming levels prioritize risk management strategies Climate models with high climate sensitivity have less CO2 benefit on a given global warming level (GWL) and are over‐represented in ensembles of higher GWLs

Studying the nonlinear photoresponse of different materials, including III-V semiconductors, two-dimensional materials and many others, is attracting burgeoning interest in the terahertz (THz) field. Especially, developing field-effect transistor (FET)-based THz detectors with preferred nonlinear plasma-wave mechanisms in terms of high sensitivity, compactness and low cost is a high priority for advancing performance imaging or communication systems in daily life. However, as THz detectors continue to shrink in size, the impact of the hot-electron effect on device performance is impossible to ignore, and the physical process of THz conversion remains elusive. To reveal the underlying microscopic mechanisms, we have implemented drift-diffusion/hydrodynamic models via a self-consistent finite-element solution to understand the dynamics of carriers at the channel and the device structure dependence. By considering the hot-electron effect and doping dependence in our model, the competitive behavior between the nonlinear rectification and hot electron-induced photothermoelectric effect is clearly presented, and it is found that the optimized source doping concentrations can be utilized to reduce the hot-electron effect on the devices. Our results not only provide guidance for further device optimization but can also be extended to other novel electronic systems for studying THz nonlinear rectification.

Recent, large fires in the western United States have rekindled debates about fire management and the role of natural fire regimes in the resilience of terrestrial ecosystems. This real-world experience parallels debates involving abstract models of forest fires, a central metaphor in complex systems theory. Both real and modeled fire-prone landscapes exhibit roughly power law statistics in fire size versus frequency. Here, we examine historical fire catalogs and a detailed fire simulation model; both are in agreement with a highly optimized tolerance model. Highly optimized tolerance suggests robustness tradeoffs underlie resilience in different fire-prone ecosystems. Understanding these mechanisms may provide new insights into the structure of ecological systems and be key in evaluating fire management strategies and sensitivities to climate change.

Titanium alloy is widely applied in aerospace, medical, shipping and other fields due to its high specific strength and low density. The purpose of this study was to analyze the formability of Ti6Al4V alloys at elevated temperatures. An accurate constitutive model is the basic condition for accurately simulating the plastic forming of materials, and it is an important basis for optimizing the parameters of the hot forging forming process. In this study, the optimization algorithm was used to accurately identify the high-temperature constitutive model parameters of Ti6Al4V titanium alloy, and the hot working diagram was established to optimize the hot forming process parameters. The optimal forming conditions of Ti6Al4V titanium alloy are given. Ti6Al4V alloy was subjected to high-temperature compression tests at 800–1000 °C and at strain rates of 0.01–5 s−1 on a Gleeble-1500D thermal/mechanical simulation machine. Each parameter of the Hansel–Spittel constitutive model was taken as an independent variable, and the accumulated error between the stress calculated by the constitutive model and the stress obtained by experimentation was used as an objective function. Based on response surface methodology, an inverse optimization method for identifying the parameters of the high-temperature constitutive model of Ti6Al4V alloy is proposed in this paper. An orthogonal test design was adopted to obtain sample point data, and a third-order response surface approximate model was established. The genetic algorithm (GA) was applied to reversely optimize the parameters of the constitutive model. To verify the accuracy of the optimized constitutive model, the average absolute relative error (AARE) and correlation coefficient (R) were used to evaluate the reliability of optimized constitutive model. The R value of the model was 0.999, and the AARE value was 0.048, respectively, indicating that the established high-temperature constitutive model for Ti6Al4V alloy has good calculation accuracy. The flow stress behavior of the material could be accurately delineated. Meanwhile, in order to study the formability of Ti6Al4V alloy, the hot processing map of the alloy, based on a dynamic material model, was established in this paper. The optimum hot working domains of the Ti6Al4V alloy were determined within 840–920 °C/0.01–0.049 s−1 and 940–980 °C/0.11–1.65 s−1; the hot processing map was verified in combination with the microstructure, and the fine and equiaxed grains and a large amount of β phase could be found at 850 °C/0.01 s−1.

There is evidence that warming leads to greater evapotranspiration and surface drying, thus contributing to increasing intensity and duration of drought and implying that mitigation would reduce water stresses. However, understanding the overall impact of climate change mitigation on water resources requires accounting for the second part of the equation, i.e., the impact of mitigation-induced changes in water demands from human activities. By using integrated, high-resolution models of human and natural system processes to understand potential synergies and/or constraints within the climate–energy–water nexus, we show that in the United States, over the course of the 21st century and under one set of consistent socioeconomics, the reductions in water stress from slower rates of climate change resulting from emission mitigation are overwhelmed by the increased water stress from the emissions mitigation itself. The finding that the human dimension outpaces the benefits from mitigating climate change is contradictory to the general perception that climate change mitigation improves water conditions. This research shows the potential for unintended and negative consequences of climate change mitigation.

A hot spell is an extreme weather event with one or more consecutive days with daily maximum temperature exceeding a certain threshold of high temperature. Statistical modeling of summer hot spells in China during 1960–2005 and their simulations in the historical experiment of the Coupled Model Intercomparison Project Phase 5 (CMIP5) are investigated in this study. A technique called the hot spell model (HSM), introduced by Furrer et al. (Clim Res 43:191–205, 2010 ) for modeling hot spells by extending the point process approach to extreme value theory, is applied. Specifically, the frequency of summer hot spells is modeled by a Poisson distribution, their intensity is modeled by a generalized Pareto distribution, and their duration is modeled by a geometric distribution. Results show that the HSM permits realistic modeling of summer hot spells in China. Trends in the frequency, duration, and intensity of hot spells were estimated based on the HSM for the observed period from 1960 to 2005. Furthermore, the performance in simulating hot spell characteristics and trends from the CMIP5 historical run were assessed based on the HSM. Climate models with good performance were selected to conduct an ensemble projection of hot spell intensity, frequency, and duration and their trends in future decades.

Heterologous prime-boost settings with a protein vaccine and the viral vector vesicular stomatitis virus, both expressing tumor-associated antigens (KISIMA-TAA and VSV-GP-TAA), have been previously shown to generate potent antitumor immunity. In the cold TC-1 model (HPV antigen) and the immune-infiltrate MC-38 model (Adpgk, Reps1 and Rpl18 neo-antigens), we further investigated pivotal immune cells that educate CD8+ T cells. Heterologous prime-boost vaccination induced a superior antitumor response characterized by the increase in number and functionality of antigen-specific CD8+ T cells, recruitment of cross-presenting dendritic cells, and polarization of CD4+ T cells towards an antitumor Th1 phenotype within the tumor and tumor-draining lymph nodes, turning the cold TC-1 tumor into a hot, inflamed tumor. In the inflamed MC-38 tumor model, treatment combination markedly prolonged the overall survival of mice. Treatment with multi-epitope vaccines also induced high frequencies of multiple antigen specificities in the periphery and in the tumor. Prime-boost treatment reduced tumor-infiltrating regulatory CD4+ T cells whilst increasing cross-presenting dendritic cells in tumor-draining lymph nodes. In conclusion, heterologous prime-boost vaccination possesses the ability to induce a potent anti-tumor response in both immune-excluded and immune-infiltrated mouse tumor models. Additionally, this study highlights the design of a multi-epitope vaccine for cancer immunotherapy.

The correction of directional effects on satellite-retrieved land surface temperature (LST) is of high relevance for a proper interpretation of spatial and temporal features contained in LST fields. This study presents a methodology to correct such directional effects in an operational setting. This methodology relies on parametric models, which are computationally efficient and require few input information, making them particularly appropriate for operational use. The models are calibrated with LST data collocated in time and space from MODIS (Aqua and Terra) and SEVIRI (Meteosat), for an area covering the entire SEVIRI disk and encompassing the full year of 2011. Past studies showed that such models are prone to overfitting, especially when there are discrepancies between the LSTs that are not related to the viewing geometry (e.g., emissivity, atmospheric correction). To reduce such effects, pixels with similar characteristics are first grouped by means of a cluster analysis. The models’ calibration is then performed on each one of the selected clusters. The derived coefficients reflect the expected impact of vegetation and topography on the anisotropy of LST. Furthermore, when tested with independent data, the calibrated models are shown to maintain the capability of representing the angular dependency of the differences between LST derived from polar-orbiter (MODIS) and geostationary (Meteosat, GOES and Himawari) satellites. The methodology presented here is currently being used to estimate the deviation of LST products with respect to what would be obtained for a reference view angle (e.g., nadir), therefore contributing to the harmonization of LST products.

Background Evaluating healthcare information systems, such as the Electronic Health Records (EHR), is both challenging and essential, especially in resource-limited countries. This study aims to psychometrically develop and validate an instrument (questionnaire) to assess the factors influencing the successful adoption of the EHR system by healthcare professionals in Moroccan university hospitals. Methods The questionnaire validation process occurred in two main stages. Initially, data collected from a pilot sample of 164 participants underwent analysis using exploratory factor analysis (EFA) to evaluate the validity and reliability of the retained factor structure. Subsequently, the validity of the overall measurement model was confirmed using confirmatory factor analysis (CFA) in a sample of 368 healthcare professionals. Results The structure of the modified HOT-fit model, comprising seven constructs (System Quality, Information Quality, Information technology Service Quality, User Satisfaction, Organization, Environment, and Clinical Performance), was confirmed through confirmatory factor analysis. Absolute, incremental, and parsimonious fit indices all indicated an appropriate level of acceptability, affirming the robustness of the measurement model. Additionally, the instrument demonstrated adequate reliability and convergent validity, with composite reliability values ranging from 0.75 to 0.89 and average variance extracted (AVE) values ranging from 0.51 to 0.63. Furthermore, the square roots of AVE values exceeded the correlations between different pairs of constructs, and the heterotrait-monotrait ratio of correlations (HTMT) was below 0.85, confirming suitable discriminant validity. Conclusions The resulting instrument, due to its rigorous development and validation process, can serve as a reliable and valid tool for assessing the success of information technologies in similar contexts.