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The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis’ thermal optimum at 21.7°C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1–27.3°C and 23.6–27.9°C (95% CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum. 

Abstract During 2013–16 and 2018–22, marine heatwaves (MHWs) occurred in the North Pacific, exhibiting similar extensive coverage, lengthy duration, and significant intensity but with different warming centers. The warming center of the 2013–16 event was in the Gulf of Alaska (GOA), while the 2018–22 event had warming centers in both the GOA and the coast of Japan (COJ). Our observational analysis indicates that these two events can be considered as two MHW variants induced by a basinwide MHW conditioning mode in the North Pacific. Both variants were driven thermodynamically by atmospheric wave trains propagating from the tropical Pacific to the North Pacific, within the conditioning mode. The origin and propagating path of these wave trains play a crucial role in determining the specific type of MHW variant. When a stronger wave train originates from the tropical central (western) Pacific, it leads to the GOA (COJ) variant. The cross-basin nature of the wave trains enables the two MHW variants to be accompanied by a tripolar pattern of sea surface temperature anomalies in the North Atlantic but with opposite phases. The association of these two MHW variants with the Atlantic Ocean also manifests in the decadal variations of their occurrence. Both variants tend to occur more frequently during the positive phase of the Atlantic multidecadal oscillation but less so during the negative phase. This study underscores the importance of cross-basin associations between the North Pacific and North Atlantic in shaping the dynamics of North Pacific MHWs. 

Abstract The interaction of airflow with complex terrain has the potential to significantly amplify extreme precipitation events and modify the structure and intensity of precipitating cloud systems. However, understanding and forecasting such events is challenging, in part due to the scarcity of direct in situ measurements. Doppler radar can provide the capability to monitor extreme rainfall events over land, but our understanding of airflow modulated by orographic interactions remains limited. The SAMURAI software is a three-dimensional variational data assimilation (3DVAR) technique that uses the finite element approach to retrieve kinematic and thermodynamic fields. The analysis has high fidelity to observations when retrieving flows over a flat surface, but the capability of imposing topography as a boundary constraint is not previously implemented. Here, we implement the immersed boundary method (IBM) as pseudo-observations at their native coordinates in SAMURAI to represent the topographic forcing and surface impermeability. In this technique, neither data interpolation onto a Cartesian grid nor explicit physical constraint integration during the cost function minimization is needed. Furthermore, the physical constraints are treated as pseudo-observations, offering the flexibility to adjust the strength of the boundary condition. A series of observing simulation sensitivity experiments (OSSEs) using a full-physics model and radar emulator simulating rainfall from Typhoon Chanthu (2021) over Taiwan are conducted to evaluate the retrieval accuracy and parameter settings. The OSSE results show that the strength of the IBM constraints can impact the overall wind retrievals. Analysis from real radar observations further demonstrates that the improved retrieval technique can advance scientific analyses for the underlying dynamics of orographic precipitation using radar observations. 

SAGE3 is software to augment the cyberinfrastructure-enhanced research and education enterprise by supporting data-intensive collaboration across a wide range of display devices from high-resolution display walls to laptops. This paper provides insight into SAGE3’s implementation, which significantly improves on prior generations of SAGE by leveraging emerging advancements in Web technologies and Artificial Intelligence. We also provide an overview of new usage patterns that we observed with SAGE3. 

SAGE3 is software to augment the cyberinfrastructure-enhanced research and education enterprise by supporting data-intensive collaboration across a wide range of display devices from high-resolution display walls to laptops. This paper provides insight into SAGE3’s implementation, which significantly improves on prior generations of SAGE by leveraging emerging advancements in Web technologies and Artificial Intelligence. We also provide an overview of new usage patterns that we observed with SAGE3. 

SAGE3 is software to augment the cyberinfrastructure-enhanced research and education enterprise by supporting data-intensive collaboration across a wide range of display devices from high-resolution display walls to laptops. This paper provides insight into SAGE3’s implementation, which significantly improves on prior generations of SAGE by leveraging emerging advancements in Web technologies and Artificial Intelligence. We also provide an overview of new usage patterns that we observed with SAGE3. 

Abstract Adsorption-induced deformation is a change in geometrical dimensions of an adsorbent material caused by gas or liquid adsorption on its surface. This phenomenon is universal and sensitive to adsorbent properties, which makes its prediction a challenging task. However, the pure academic interest is complemented by its importance in a number of engineering applications with porous materials characterization among them. Similar to classical adsorption-based characterization methods, the deformation-based ones rely on the quality of the underlying theoretical framework. This fact stimulates the recent development of qualitative and quantitative models toward the more detailed description of a solid material, e.g. account of non-convex and corrugated pores, calculations of adsorption stress in realistic three-dimension solid structures, the extension of the existing models to new geometries, etc. The present review focuses on the theoretical description of adsorption-induced deformation in micro and mesoporous materials. We are aiming to cover recent theoretical works describing the deformation of both ordered and disordered porous bodies.