Explore the vast range of titles available.

Accurate computational identification of B-cell epitopes is crucial for the development of vaccines, therapies, and diagnostic tools. However, current structure-based prediction methods face limitations due to the dependency on experimentally solved structures. Here, we introduce DiscoTope-3.0, a markedly improved B-cell epitope prediction tool that innovatively employs inverse folding structure representations and a positive-unlabelled learning strategy, and is adapted for both solved and predicted structures. Our tool demonstrates a considerable improvement in performance over existing methods, accurately predicting linear and conformational epitopes across multiple independent datasets. Most notably, DiscoTope-3.0 maintains high predictive performance across solved, relaxed and predicted structures, alleviating the need for experimental structures and extending the general applicability of accurate B-cell epitope prediction by 3 orders of magnitude. DiscoTope-3.0 is made widely accessible on two web servers, processing over 100 structures per submission, and as a downloadable package. In addition, the servers interface with RCSB and AlphaFoldDB, facilitating large-scale prediction across over 200 million cataloged proteins. DiscoTope-3.0 is available at: https://services.healthtech.dtu.dk/service.php?DiscoTope-3.0 .

The second version of Chinese Academy of Sciences Earth System Model (CAS‐ESM 2) is described with emphasis on the development process, strength and weakness, and climate sensitivities in simulations of the Coupled Model Intercomparison Project (CMIP6) DECK experiments. CAS‐ESM 2 was built as a numerical model to simulate both the physical climate system as well as atmospheric chemistry and carbon cycle. It is a newcomer in the international modeling community to provide sufficiently independent solutions of climate simulations from those of other models. Performances of the model in simulating the basic states of the radiation budget of the atmosphere and ocean, precipitation, circulations, variabilities, and the twentieth century warming are presented. Model biases and their possible causes are discussed. Strength includes horizontal heat transport in the atmosphere and oceans, vertical profile of the Atlantic Meridional Overturning Circulation; weakness includes the double intertropical convergence zone (ITCZ) and stronger amplitude of the El Niño–Southern Oscillation (ENSO) that are also common in many other models. The simulated the twentieth century warming shares a similar discrepancy with observations as in several other models—less warming in the 1920s and stronger cooling in the 1960s than in observation—at the time when there was a steep increase of anthropogenic aerosols. As a result, the twentieth century warming is about 60% of the observed warming despite that the model simulated a similar slope of warming trend after 1980 to observation. The model has an equilibrium climate sensitivity of 3.4 K with a positive cloud feedback from the shortwave radiation. Plain Language Summary This paper describes the second version of Chinese Academy of Sciences Earth System Model (CAS‐ESM 2) along with simulation results from the Coupled Model Intercomparison Project (CMIP6) DECK experiments. Performances of the model in simulating the radiation budget of the atmosphere and ocean, precipitation, circulations, variabilities, and the twentieth century warming are presented. The simulated the twentieth century warming shares a similar discrepancy with observations as in several other models—less warming in the 1920s and stronger cooling in the 1960s than in observation—at the time when there was a steep increase of anthropogenic aerosols. As a result, the twentieth century warming is about 60% of the observed warming despite that the model simulated a similar slope of warming trend after 1980 to observation. Key Points The second version of Chinese Academy of Sciences Earth System Model (CAS‐ESM 2) is described Strength and weakness of the model simulations from the CMIP6 DECK experiments are described along possible causes The model has an equilibrium climate sensitivity of 3.4 K with a positive cloud feedback from the shortwave radiation

Protein language models (pLMs) can offer deep insights into evolutionary and structural properties of proteins. While larger models, such as the 15 billion parameter model ESM-2, promise to capture more complex patterns in sequence space, they also present practical challenges due to their high dimensionality and high computational cost. We systematically evaluated the performance of various ESM-style models across multiple biological datasets to assess the impact of model size on transfer learning via feature extraction. Surprisingly, we found that larger models do not necessarily outperform smaller ones, in particular when data is limited. Medium-sized models, such as ESM-2 650M and ESM C 600M, demonstrated consistently good performance, falling only slightly behind their larger counterparts—ESM-2 15B and ESM C 6B—despite being many times smaller. Additionally, we compared various methods of compressing embeddings prior to transfer learning, and we found that mean embeddings consistently outperformed other compression methods. In summary, ESM C 600M with mean embeddings offers an optimal balance between performance and efficiency, making it a practical and scalable choice for transfer learning in realistic biological applications.

Quantification of dust aerosols in Earth System Models (ESMs) has important implications for water cycle and biogeochemistry studies. This study examines the global life cycle and direct radiative effects (DREs) of dust in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1), and the impact of increasing model resolution both horizontally and vertically. The default 1° E3SMv1 captures the spatial and temporal variability in the observed dust aerosol optical depth (DAOD) reasonably well, but overpredicts dust absorption in the shortwave (SW). Simulations underestimate the dust vertical and long-range transport, compared with the satellite dust extinction profiles. After updating dust refractive indices and correcting for a bias in partitioning size-segregated emissions, both SW cooling and longwave (LW) warming of dust simulated by E3SMv1 are increased and agree better with other recent studies. The estimated net dust DRE of −0.42 Wm−2 represents a stronger cooling effect than the observationally based estimate −0.2 Wm−2 (−0.48 to +0.2), due to a smaller LW warming. Constrained by a global mean DAOD, model sensitivity studies of increasing horizontal and vertical resolution show strong influences on the simulated global dust burden and lifetime primarily through the change of dust dry deposition rate; there are also remarkable differences in simulated spatial distributions of DAOD, DRE, and deposition fluxes. Thus, constraining the global DAOD is insufficient for accurate representation of dust climate effects, especially in transitioning to higher- or variable-resolution ESMs. Better observational constraints of dust vertical profiles, dry deposition, size, and LW properties are needed.

In current research, emotions in language use situations are often examined only at their starting and ending points, akin to observing the beginning and end of a wave, while neglecting their complex fluctuations in between. To fully comprehend the dynamics of emotions in language use situations, it is essential to delve into their intricate unfolding throughout their progression. This is particularly critical in the context of Second Language Acquisition (SLA), where emotional dynamics can significantly influence learning outcomes and proficiency. Drawing on existing empirical research and theories, we propose a novel interpretation rooted in complex dynamic systems theory (CDST) to elucidate the dynamic nature of emotions in language use situations. Furthermore, we suggest methodologies for capturing the complete dynamics of emotional and language behaviours, including an analysis of their dynamic interrelationships. By embracing a dynamic perspective, we can advance our understanding of interplay between emotions and language behaviours from epistemological theory to methodology and analysis, paving the way for future research in this field.

Barrier coverage is a fundamental issue in wireless sensor networks (WSNs). Most existing works have developed centralized algorithms and applied the Boolean Sensing Model (BSM). However, the critical characteristics of sensors and environmental conditions have been neglected, which leads to the problem that the developed mechanisms are not practical, and their performance shows a large difference in real applications. On the other hand, the centralized algorithms also lack scalability and flexibility when the topologies of WSNs are dynamically changed. Based on the Elfes Sensing Model (ESM), this paper proposes a distributed Joint Surveillance Quality and Energy Conservation mechanism (JSQE), which aims to satisfy the requirements of the desired surveillance quality and minimize the number of working sensors. The proposed JSQE first evaluates the sensing probability of each sensor and identifies the location of the weakest surveillance quality. Then, the JSQE further schedules the sensor with the maximum contribution to the bottleneck location to improve the overall surveillance quality. Extensive experiment results show that our proposed JSQE outperforms the existing studies in terms of surveillance quality, the number of working sensors, and the efficiency and fairness of surveillance quality. In particular, the JSQE improves the surveillance quality by 15% and reduces the number of awake sensors by 22% compared with the relevant TOBA.

Engagement has been recognized as one of the most important factors of learning and achievement in academic settings. Research on engagement has been gearing toward a “person-in-context” orientation, where both personal characteristics and contextual features in relation to students’ engagement are considered. This orientation allows a more in-depth understanding of how a person embedded within a context engages in a task, and it pays particular attention to the interactions between the person and contextual features. Engagement in context is situational, longitudinal, and multi-dimensional. This in-situ orientation requires a research methodology that is embedded in and responsive to the context where learning occurs. In this paper, we provide a conceptual synthesis of research on academic engagement in proposing a framework of engagement in context. We introduce the affordances of Experience Sampling Methodology (ESM) and provide a review of current technologies in supporting ESM. In addition, we provide example cases of examining engagement using ESM and technology. In these cases, we discuss details about how ESM combines with technologies and statistical approaches in providing insights to educational research, theory, and practice.

The dust emission parameterization in the Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) is described with emphasis on the implementation process and simulations of global dust cycle and East Asia dust event statistics. The parameterization is based on the scheme of Shao (2004; http://doi.org/10.1029/2003JD004372) which considers two major dust emission mechanisms, namely, saltation bombardment and aggregation disintegration. Shao (2004; http://doi.org/10.1029/2003JD004372) scheme was well tested against field observations and has been widely used in regional dust modeling. Here this scheme is implemented into a global climate model for the first time and thus provides an independent solution for simulating global dust emissions. With this scheme, CAS‐ESM2 reasonably simulates the main dust emission regions in the Earth and reproduces the observations of dust deposition flux and surface dust concentrations at most stations. Compared to the synoptic records of dust events, the model also captures the general patterns and seasonal variations of dust activities in East Asia. However, the model underestimates the frequency of strong dust events (instantaneous surface dust concentrations >1,000 μg m−3) due to the weaker surface winds simulated by the model. The model tends to simulate much weaker and longer‐lasting dust events in Eastern Sources (35–49°N, 94–126.5°E) of northern China, suggesting the weaker and slower‐moving synoptic weather systems associated with dust events in the model. Overall CAS‐ESM2 performs well in simulating the key aspects of global dust distribution and East Asian dust events, yet some biases remain to be improved. Plain Language Summary Dust emitted from the bare soil is an important aerosol type, and dust cycle links the various components of Earth System including atmosphere, land, and oceans. Therefore, dust emission is an essential part of Earth system. In this study, we develop a dust emission module for Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) to simulate the global dust emission. The module incorporates advanced mechanisms of dust emission physics. The results show that with this module, CAS‐ESM2 reproduces well the global distribution of dust aerosol. We also evaluate the model's ability in simulating the individual dust events in terms of dust event frequency, intensity, and duration. We find that the model can reproduce the key regions of dust emission and the highest frequency of dust event in spring in East Asia. However, because the model underestimates surface wind speeds, it simulates weaker and longer‐lasting dust events. Overall CAS‐ESM2 provides a new and promising solution to simulate global dust emission, although there are still some biases for further improvements. Key Points Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) with a physically based dust emission scheme provides a new and promising solution to simulate global dust emissions CAS‐ESM2 captures the main global dust emission regions and reproduces observed dust depositions and surface dust concentrations The weaker dust events are compensated by overestimated dust event frequency and duration to produce reasonable means in East Asia