The as-fabricated sample exhibited epitaxial growth columnar dendrites along the building direction with discrepant secondary arm spacing due to heat accumulation. A lot of fine γ′ particles with an average size of 81 nm and MC carbides were observed in the interdendritic region. Elemental segregation and γ–γ′ eutectic reaction were analyzed in detail and some MC carbides were confirmed in the reaction L + MC→γ + γ′. After standard heat treatment, bimodal distribution of γ′ phases, including coarse γ′ particles  and fine γ′ particles , was observed. The mechanism of microstructural evolution, phase formation, as well as cracking mechanisms were discussed. Microhardness and tensile tests were carried out to investigate the mechanical performance. The results show that both the as-fabricated and heat-treated samples exhibited a higher tensile strength but a slightly lower ductility compared with cast parts.The IN738LC Ni-based superalloy strengthened by the coherent γ′-Ni Nowadays, additive manufacturing (AM) is a promising technology to repair and fabricate functional metallic materials. AM is able to manufacture complex components by virtue of stacking material layer by layer, reducing the machining process over conventional or wrought parts, such as turbine discs and blades ,2,3,4. P3 precipitates, is one of the most employed blade materials and has been widely used in land-based and aero gas turbine engines. The IN738LC superalloy has a very excellent high-temperature strength, creep rupture strength and hot corrosion resistance and thus can work at elevated temperatures up to 980 °C [IN738LC Ni-based superalloy, strengthened by the ordered, coherent γ′-Nio 980 °C . Variouso 980 °C . Nb, Ti,o 980 °C . IN738LCo 980 °C ,14,15. Ao 980 °C ,17,18. 23C6 carbides, M2B borides, and Ni-Zr intermetallic compounds are found in grain boundaries and the interdendritic region [Several laser additive manufacturing technologies have been recently used to form IN738LC components, such as laser consolidated (LC) , laser sc region ,22. Howec region . TherefoAlmost all the previous research about AM of IN738LC focuses on laser additive manufacturing technologies ,19,20. IAs shown in Commercial IN738LC powder  with an average size of 71 μm was used in the present study. During the PPAAM of IN738LC thin wall components, the depositing direction was kept constant along the positive X-axis, while the building direction was kept positive along the Z-axis, and the Z-increment between layers was maintained at 1.5 mm. After 12 layers were deposited, a IN738LC thin wall free of macrocracks with dimensions of 100 mm × 8 mm × 18 mm (thickness of 8 mm) was successfully fabricated, as can be seen in 2H5OH + 20 mL HCl + 5 g FeCl3, while electrolytic etching in a solution of 12 mL H3PO4 + 40 mL HNO3 + 48 mL H2SO4 at 6 V for 4–6 s was used for FEI NOVA NANOSEM scanning electron microscope (SEM) observation, equipped with an energy-dispersive X-ray spectrometer (EDS) and an Oxford electron backscattered diffraction (EBSD). XRD was performed by using Cu Kα radiation (λ = 0.15425 nm) and the diffraction profile ranged from 25° to 105° with an angle step of 0.01°. Microstructural examination was also carried out with a TECNAL G2 transmission electron microscope (TEM). The size and volume fraction of the γ′ particles were acquired by ImageJ software. The microhardness of samples was measured with an HXZ-1000 micro Vickers hardness tester and the load was set to 200 g with a dwell time of 15 s. Tensile samples were machined according to our previous work [Samples were cut on the transverse sections (y-z plane) along the build direction by electrical discharge machining (EDM) for microstructural characterization and XRD examinations. Specimens used for Olympus optical microscope (OM) observation were etched for 15–30 s with a solution of 100 mL Cous work . Tensileλ is the SDA spacing, ε is the cooling rate, and ck and n is the constant. Using the values of ck = 518.39 and n = −0.592, as determined by other researchers for Ni-based superalloys [Optical micrographs of the as-fabricated (AF) samples and heat-treated (HT) samples are shown in eralloys , the cooGrain orientation and growth in AF and HT samples are investigated in detail by EBSD. max)(hkl) were calculated and are summarized in The results of the XRD investigation of IN738LC powder, AF, and HT samples are summarized in k is the equilibrium distribution coefficient, L is the diffusion distance. Considering a constant solute diffusivity and negligible solid-state diffusion, the term In the IN738LC superalloy, the elements Co, Cr, Mo, W, and Ta are generally added in the γ matrix to play an important role in the solid solution strengthening, and elements Cr, Mo, Ti and Nb can also achieve the solid solution strengthening of the γ′ phases. The distribution of various alloying elements can not only significantly affect the microstructure, but also have a strong impact on the properties. Solute redistribution during weld pool solidification is an important phenomenon which should be researched to analyze the elemental distribution. According to the solute redistribution model established by Bower et al. , the solequation (4)Cs=kCk > 1 can gather in the dendritic core, while the elements Nb, Mo, Ta, Ti and Zr can be more easily segregated in the interdendritic region, which is responsible for the precipitation and distribution of MC carbides.In the present study, the cooling rate during PPAAM ranges from 216–571 K/s, and such a high cooling rate can undoubtedly suppress the solute back diffusion to some extent. Hence, it is appropriate to use Equation (4) to evaluate the distribution coefficients. At the initial stage of solidification, k < 1 keep on segregating during the whole solidification process. At the final stage, the enrichment of Al and Ti in the interdendritic region could lead to a eutectic reaction, L→γ + γ′, when the temperature cools down to the eutectic temperature. Another thing that should be mentioned is that MC carbides are also reported to be able to participate in eutectic reactions [During solidification in the PPAAM of IN738LC, the γ matrix (dendrite) forms at the initial stage. Then, with the elements Nb, Mo, Ta and Ti segregating in the interdendritic region, MC carbides start the formation of liquid. In the next stage, the formation of γ′ begins. It is noted that elements with eactions ,34. Accoeactions , when thThe IN738LC superalloy is known to be metastable at high temperatures and is always accompanied by changes in the size, morphology, and distribution of γ′ phases. After standard heat treatment in the present study, IN738LC samples show a bimodal γ′ particle distribution and a dispersed distribution of MC carbides, as can be seen in γ matrix . The cohγ matrix ,41.During heat treatment, the γ′ phase normally evolves, following four stages: nucleation, growth, coarsening and dissolution. According to the theory of solid phase precipitation, both isothermal precipitation and continuous precipitation are mainly controlled by two vital factors: the capability of solute atom migration and the activation energy required for nucleation . In FiguOne common defect in most AM technologies of the IN738LC superalloy is undoubtedly micro-cracks. equation :(6)γgb=Gn θ > θm . ObviousTensile tests at room temperature were also carried out to investigate the mechanical performance of AF and HT samples. Ultimate tensile strength (UTS), yield strength (YS) and elongation (EL) are summarized in In the present study, an IN738LC thin wall free from macro-cracks is successfully fabricated by PPAAM, the microstructure and mechanical performance of AF and HT samples are investigated in detail and the primary conclusions can be summarized as follows.The AF samples exhibit epitaxially growing columnar dendrites along the building direction with different SDA spacing. Because of the heat accumulation during PPAAM, the SDA spacing of the bottom, middle, and top region is found to be 12.1 μm, 16.2 μm, and 21.5 μm, respectively. The grain morphology also changes from columnar dendrites to cellular dendrites and equiaxial dendrites due to the variational thermal gradient (G) and grain growth rate (R), which can result in constitutional undercooling.k < 1, such as Nb, Mo, Ta, and Ti, are easy to segregate in the interdendritic region, which could lead to a eutectic reaction, L→γ + γ′, at the final stage of solidification. Moreover, some MC carbides are confirmed in the reaction L + MC→γ + γ′.The precipitates of AF samples mainly consist of MC carbides rich in Nb, Ti and Ta, fine spherical γ′ particles with an average size of 81 nm, accounting for about 35 vol.%, and some γ–γ′ eutectics with irregular shapes. Elements with a partition coefficient After standard heat treatment, the HT sample shows a bimodal γ′ particle distribution. The coarse γ′ particles with a mean size of 385 nm account for about 42 vol.%, while the fine γ′ particles with a mean size of 42 nm account for about 25 vol.%. Both spherical and cuboidal γ′ particles are observed and nonuniformly distributed due to the elemental segregation. The morphology evolution is ascribed to the virtually double “aging” treatments.Crack formation tends to occur along high-angle grain boundaries (HAGB) with the misorientation exceeding 15°, at which point dendritic coalescence undercooling occurs Both AF and HT samples exhibit higher UTS and YS, but slightly lower ductility compared with cast parts. A further study, adjusting the heat treatment to acquire a more appropriate size and distribution of γ′ phases, may further improve the mechanical performance of IN738LC samples fabricated by PPAAM.


We aimed to understand which abiotic and spatial variables influence ant β-diversity and identify which processes may drive ant β-diversity patterns in Mediterranean drylands by measuring the percentage of variation in ant taxonomic and functional β-diversity explained by local environmental, regional climatic and spatial variables. We found that taxonomic and functional replacement (βrepl) primarily drove patterns in overall β-diversity (βtot). Variation partitioning analysis showed that respectively 16.8%, 12.9% and 21.6% of taxonomic βtot, βrepl and βrich variation were mainly explained by local environmental variables. Local environmental variables were also the main determinants of functional β-diversity, explaining 20.4%, 17.9% and 23.2% of βtot, βrepl and βrich variation, respectively. Findings suggest that niche-based processes drive changes in ant β-diversity, as local environmental variables may act as environmental filters on species and trait composition. While we found that local environmental variables were important predictors of ant β-diversity, further analysis should address the contribution of other mechanisms, e.g. competitive exclusion and resource partitioning, on ant β-diversity.The decomposition of beta-diversity (β-diversity) into its replacement (β To asses changes in diversity across different communities along climatic gradients, researchers rely on beta diversity (β-diversity), which is defined as the difference in species composition between two or more communities2. Recently, a framework was developed to assess the contribution of the two components of total β-diversity (differences in species richness and composition between sites), namely: (1) species replacement (i.e. differences in diversity due to species replacement) and (2) species richness differences (i.e. differences in numbers of species present)4. However, taxonomic β-diversity alone may not fully elucidate the underlying processes regulating community assemblages5. To overcome this issue, a functional trait approach has been applied to the β-diversity concept (e.g.6). The functional approach to β-diversity by Carvalho et al.3 follows a similar rationale to the one used in the taxonomical approach and total functional β-diversity (βtot) can be decomposed into two components: (1) trait value replacement (βrepl) and, (2) trait value richness .Measurements of biological diversity and its responses to environmental changes are key issues in ecologyversus niche-based), as we can see from its recent generalized application [e.g.8]. If neutral-based processes are dominant, community composition is the result of random associations of species and their functional traits. As a result, β-diversity is expected to increase as the distance between sites increases (across space) while it would remain constant across environmental gradients9. Niche-based processes include biotic and abiotic filters, which have similar effects on community composition and are therefore difficult to disentangle10. For example, under abiotic filtering, environmental conditions may exclude some species and limit some trait establishment and persistence by selecting for or against species and ecological strategies11. As a result, with abiotic filters, β-diversity is expected to be constant across space and increase along an environmental gradient, with communities in the same environmental conditions sharing similar traits12. In the extreme tails of environmental gradients, we expect that environmental differences match biological differences, while in areas with similar environmental conditions, low species and trait differences are expected. Instead, under similar environmental conditions, biotic filters, such as competitive exclusion, may lead to a higher dissimilarity of traits13.Using multiple approaches and exploring the components of taxonomic and functional β-diversity in tandem, allows us to more completely understand ecological mechanisms regulating diversity. Combining taxonomic and functional β-diversity increases our understanding of community patterns and their regulatory processes , indicating the presence of species with similar combinations of traits6. For example, different regions sharing similar environmental conditions may have high species dissimilarity and low functional β-diversity5. Therefore, high functional diversity may result either from the replacement of functionally different species, indicating abiotic filtering, or from the loss/gain of functional strategies, which may be related to a different intensity of the niche-based processes14.Niche-based processes may lead to high dissimilarity in both taxonomic and functional β-diversity between two extreme ends of a gradient16. Ant communities are shaped by abiotic, namely small-spatial scale  environmental factors, such as plant composition, vegetation structure, soil characteristics and productivity18 and large-scale  climate variables, such as temperature and precipitation20 and biotic interactions, e.g. competitive exclusion. Furthermore, the role of ants in drylands together with their potential as ecological indicators20, makes this a key taxon to be monitored in response to environmental changes. Ant β-diversity has been assessed for different ecosystems21, although these studies focused on elevational gradients23. However, to our knowledge, previous studies along aridity gradients have either measured the link between aridity and ant species diversity or functional traits, but not taxonomic and functional β-diversity (e.g.18). Given that Mediterranean drylands are particularly vulnerable to aridity increase24, they offer an interesting context in which to assess the processes governing ant diversity and community assemblages along climatic environmental gradients.Ants represent a key group to examine functional and taxonomic diversity because they are diverse, abundant, and have an essential role as ecosystem engineers, especially in drylands where they are often associated with important ecological functions 9). We specifically addressed the two following questions: (1) which components (βrepl and βrich) drive ant taxonomic and functional βtot? and (2) which abiotic factors explain variation in taxonomic and functional β-diversity and how can they help us to infer on the ecological processes driving taxonomic and functional β-diversity along climatic environmental gradients? Based on previous studies25 we expected a higher contribution of the βrepl, over the βrich component, to ant βtot, and that along climatic environmental gradients, niche-based processes play the most important role in structuring ant communities.Our goals were to analyze how ant taxonomic and functional β-diversity change along climatic environmental gradients and to identify which components (replacement or richness differences) contribute most to overall β-diversity. Furthermore, we evaluated the contribution of local environmental, regional climatic and spatial variables as determinants of ant β-diversity variation. To do that, we performed variation partition analysis, which has been used to disentangle the influence of the selected variables on community changes and to understand whether niche- or neutral-based processes drive β-diversity  accounted for most species (6 species), followed by the genus Camponotus (Mayr 1861) (4 species) and Aphaenogaster , Messor  and Tapinoma  . Five ant species , Cataglyphis hispanica , Formica subrufa , Messor barbarus  and Temnothorax nylanderi  were widespread in the study area, occurring in more than 20 sites, eight species occurred in between 10 and 20 sampling sites, while most species (S = 23) were restricted to less than 10 sites.In total, we collected 36 ant species representing three sub-families . The richest sub-family was Myrmicinae, which accounted for 20 species, followed by Formicinae with 12 species .The fourth-corner analysis found a marginally significant trait-environmental relationship (p = 0.09), suggesting that the traits explain some of the variation in the responses of species to environmental gradients Figure . In parttot was 0.616 (± 0.128), and mean Tβrepl and mean Tβrich were 0.427 (± 0.197) and 0.189 (± 0.145), respectively. For functional β-diversity, mean pairwise dissimilarity (± standard deviation) for Fβtot was 0.488 (± 0.118), 0.317 (± 0.169) for Fβrepl and 0.170 (± 0.123) for Fβrich. When we used less traits and a different trait coding , mean pairwise dissimilarity for functional β-diversity was similar despite being slightly lower. In particular, we found that with decreasing number of ant functional traits, namely 7 and 4 traits, and using the original coding, mean pairwise dissimilarity was slightly lower for βtot, βrepl and βrich . When we measured ant functional β-diversity using 11, 7 and 4 traits and a different coding for qualitative traits (fuzzy coding), we found similar results, with Fβrepl rather than Fβrich mainly contributing to overall Fβtot  for Tβtot model explained 20.7% of the variation along the climatic gradient by the following factors: (1) pure local (13.2%), (2) pure climatic (2.8%) and (3) pure spatial (0%)  pure local (13.4%), (2) pure climatic (3.1%) and (3) pure spatial (2%). Regarding Tβrich, the forward selection procedure selected local, climatic and spatial variables, which together account for 22.2% of the variation explained. Tβrich was explained by: (1) pure local (14.2%), (2) pure climatic (0%) and (3) pure spatial (1.3%) variables.The Tβfactors:  pure loctot showed in general similar patterns of those found for Tβtot  respectively, which appears to be common across a wide range of taxa, including ants27. Species and trait value replacement components playing a major role in generating the observed ant β-diversity patterns and the trait-environment associations, suggest that functionally unique species are replaced as environmental differences between sampling sites increase. Taxonomic and functional β-diversity components shared similar sets of variables explaining β-diversity variation, e.g. vegetation structure, productivity and aridity. Furthermore, the higher contribution of the βrepl component to βtot, in both taxonomic and functional anlayses, combined with the larger contribution of local environmental and regional climatic factors as determinants of β-diversity agree with previous findings in a similar environment29 and may corroborate the hypothesis that niche-based processes drive ant β-diversity in this Mediterranean dryland.We found that both Tβ30, and may indicate that different environmental variables act as abiotic filters on ant taxonomic and functional β-diversity. In particular, in drylands the role of local environmental and regional climatic variables in explaining variation in ant species and trait composition has been highlighted25. However, while these authors25 found no relationship between ant β-diversity and habitat structure , our results show that local environmental factors, such as habitat structure, productivity and soil characteristics were the major determinants structuring variation in ant β-diversity. Furthermore, we found that some ant functional traits were associated to those environmental variables and changed along the gradients. For example, ants with a seed-based diet increased in sites with a higher plant height, epigeic ants (nesting above ground) increased in sites with more herbaceous biomass, while in shrubby sites (high relative cover of woody plant species) ants with large body size decreased.The contribution of different environmental factors to changes in taxonomic and functional β-diversity has been shown in other important invertebrate groups as well22, aridity, temperature and precipitation seasonality shaped ant functional structure and β-diversity. However, the contribution of regional climatic variables was low and mainly through shared effects with local environmental factors, as for the Tβrich and Fβrich components, and spatial variables, e.g. Tβrepl and Fβrepl components. The shared effects between local environmental and regional climatic variables suggest that these two sets of factors are connected and interact with each other. As found recently along the same aridity gradient, climatic variables, such as aridity, summer precipitation and winter temperature directly influence vegetation structure and productivity31. Instead, the shared effects between regional climatic and spatial factors, and also local environmental and spatial factors, indicate that ant β-diversity variation is explained by spatially structured environmental and climatic variables as well, although percentages were low.In our study, regional climatic variables explained some changes in ant taxonomic and functional β-diversity: as found by other studies10. In concert, these results suggest that the occurrence of different environmental conditions through space may have selected species with unique functional strategies10, leading to taxonomically and functionally distinct communities11. Apart from abiotic filters, competitive exclusion and resource partitioning may drive ant beta diversity patterns too10. However, quantifying and disentangling the contribution of these different filters on β-diversity brings many challenges, as they often covary and create very similar patterns in biodiversity10. Furthermore, measuring competitive exclusion in the field is quite difficult (e.g.32) although it should be addressed in a future study. Thus, we acknowledge that abiotic and biotic filters may act synergistically on ant β-diversity in drylands, and while we found that local environmental variables were associated to some ant functional traits and explained some of the variation in ant β-diversity, we cannot exclude that part of the patterns observed may be a result of resource partitioning and competitive exclusion too10.While these results narrow down the abiotic factors shaping ant beta-diversity in drylands and point to niche-based processes driving changes in ant taxonomic and functional β-diversity, identifying which ecological mechanism among the niche-based processes is responsible for the observed pattern remains difficult33, our findings emphasize that neutral-based processes play only a secondary role in shaping ant β-diversity. We provide two explanations for the observed spatial effect on ant β-diversity in our study gradient. First, the spatial component may represent biotic interactions at local scale and other unmeasured variables that show a spatial distribution, as environmental variables are often spatially structured35. Second, the influence of spatial variables on β-diversity suggests that neutral-based processes may also have an influence on ant β-diversity in drylands. Neutral-based processes drive diversity when a community is primarily influenced by the neighbouring community and the dispersal rate of species in its immediate surroundings 35. Neutral-based processes are usually found to be stronger at small spatial scales, given that biotic conditions may change quickly at small-scales, while as the spatial scale increases, environmental differences accumulate, matching a shift in biotic conditions36.Spatial variables also explained some of the variation in ant taxonomic and functional β-diversity, although for all components the contribution was low. Similar to another study4, while bringing many advantages, also comes with some pitfalls8. Functional β-diversity based on Carvalho’s et al.3 approach allows to distinguish between differences in assemblages due to true replacement of functional traits or due to loss/gains of functional traits, and neither species replacement is overestimated nor species richness is underestimated4. However, Cardoso’s et al.4 method produces a functional space with a lower quality, as the functional distances between species generated from the functional dendrogram37 seem to differ more from the initial dissimilarity matrix than those created in a functional ordination38, and the two functional β-diversity components seem not to be independent from one another8. Third, the present study had temporal and spatial limitations, specifically a low temporal span with sampling being limited to one of the yearly peak of ant activity and a short length of the gradient, restricted to southwestern Iberia and including only two aridity classes. An expansion of the gradient in space and time, e.g. through the inclusion of additional aridity classes and repeated sampling over more years, might be needed to reinforce our findings.Lastly, we would like to stress out three important aspects of this study. First, our analysis revealed that the local, climatic and spatial variables only explained a low percentage of the total variation and just identified some of the drivers shaping ant taxonomic and functional β-diversity in drylands. Second, we acknowledge that the approach we follow29) addressing the need to include abiotic explanatory variables acting at different scales, and biotic factors to assess changes in ant β-diversity. Moreover, we highlighted the importance of combining multiple diversity approaches to understand changes in ant β-diversity. Based on our results, we suggested that niche-based processes, including abiotic and biotic filters, may shape ant β-diversity in Mediterranean drylands. This result is timely and important, given that we need to improve our understanding of ant diversity patterns in drylands39 and that ants more so than other key groups are predicted to respond in a highly sensitive way to increased aridity and higher temperatures40. Indeed, the expansion of anthropogenic influence and climatic changes in dryland area, as well as changes in temperature and precipitation amount and patterns in the Mediterranean region41 may lead to a rearrangement of the environmental factors influencing ant β-diversity, which may, in turn, accelerate the observed ant species and trait value replacement, or even shift the relative contribution of each component to the total β-diversity.Concluding, in the present study, we provide evidence that environmental variables explain part of ant β-diversity in Mediterranean drylands, which is mostly driven by species and trait replacement. Regarding local environmental and regional climatic variables, this study supports previous studies (e.g.Quercus ilex) woodland known as the Montado. The site understory is characterized by shrubs of the genera, Cistus and Lavandula (among others). The Montado supports sustainable anthropogenic activities, such as low-intensity grazing and cork harvest, in addition to woodland biodiversity42.This study was carried out along an aridity gradient in the drylands of the southwestern Iberian Peninsula. The study area is a low density holm oak 44. Along the aridity gradient, high levels of AI equate to low aridity, while low levels of AI represent high aridity. The sampling area includes semi-arid to dry sub-humid aridity classes with AI ranging between 0.42 and 0.54. The vegetation of the sampling sites has been the subject of past studies (e.g.45) and was unimpacted by common local environmental disturbances such as heavy grazing, recent agricultural activities and past fires.Our sampling design was composed of a total of 30 sampling sites and was stratified to the aridity index (AI)46. We deployed 10 pitfall traps per sampling site, which consisted of 50 ml Falcon tubes, filled with 10% diluited ethylene glycol and a few drops of liquid detergent to reduce surface tension. Pitfall traps were arranged in a circle, with a diameter of 10 m. Pitfall traps were spaced at 5 m apart each along the circumference of the circle and left in the field for 5 days. Samples were collected and transported to the laboratory, where ants were sorted and identified to species47 using a stereomicroscope.Ants were sampled between May and June 2017, which coincides with one of the peaks in ant activity during the yearGlobalAnts 48.Traits were selected according to their ecological importance (Table 20). Environmental and climatic variables were divided into two categories: local environmental factors, which included variables measured directly in the field at a scale of < 50 m, and regional climatic factors, which included variables retrieved from the global aridity database44 and the WorldClim database49 at a scale of > 1000 m.Several environmental variables were selected based on their presumed influence on ant traits and species community composition . Mean plant height, dry herbaceous biomass, species richness, and relative cover of woody plant species describe habitat structure and environmental heterogeneity, whereas the NDVI is used as a proxy for vegetation productivityAlong a 20 m transect, we measured maximum plant height and soil cover type every 50 cm, by holding a rod perpendicular to the soil surface and recording maximum plant height and soil cover touching the rod , at 50 m buffer around each sampling site and at a 10 m of spatial resolution 44. The other regional climatic variables . The mean value per sampling site was extracted for each climatic variable. These variables were divided into two groups, related to temperature and precipitation respectively, and were correlated among each other within each group  in package mvabund within R56.We performed a fourth-corner analysis to assess the relationship between ant functional traits and local environmental and regional climatic variables. This technique analyses three matrices simultaneously, namely of ant species (sites by species incidence), ant functional traits (species by traits) and environmental variables , to test the significance of all pairwise combinations of functional traits and explanatory variablesbeta in the BAT package in R57. In this method the functional representation is based on functional clustering trees rather than on a functional ordination, and total species variation  is decomposed into variation through species replacement (Tβrepl) and variation due to species richness differences (Tβrich). Similarly, total functional β-diversity  is decomposed in β replacement (Fβrepl), which corresponds to variation due to trait value replacement, and β richness (Fβrich), which accounts for variation due to trait value loss/gain (Fβrich).To calculate taxonomic and functional β-diversity we first built a site per species matrix and a species per trait matrix. The site per species matrix contained presence-absence data for ant species at each site, whereas the species per trait matrix was based on mean trait value for a specific trait for a specific species. Taxonomic β-diversity was computed using the site per species matrix, while functional β-diversity was computed using the dissimilarity between species, obtained from the species per trait data, and the site per species data. The Jaccard index was used to compute β-diversity, which varies between 0 and 1. To compute taxonomic and functional β-diversity, based on pairwise dissimilarity between sites, we used function 38, to evaluate the sensibility of the results on functional β-diversity, we decided to use different sets of ant functional traits through reductions in the number of traits, combined with the original coding of the species per trait matrix or with a different trait coding. In the original trait coding, traits with a fuzzy coding only included behaviour, nesting preference, colour, mound presence and foraging strategy, instead in the different coding trait matrix, fuzzy coding was applied to all qualitative traits. We assessed mean pairwise dissimilarity for functional beta-diversity using: (a) a lower number of traits, namely 7 traits  and 4 traits , and the original species per trait matrix, and (b) 11, 7 and 4 traits, with fuzzy coding applied to all qualitative traits.Following Maire et al.58. The method of the variation partitioning allows us to partition β-diversity variation among local environmental, regional climatic and spatial variables as well as to assess how much of the variation in β-diversity remains unexplained34. To represent the spatial relationships among sites we used distance-based Moran’s eigenvector maps (dbMEM)59, using function dbmem of package adespatial in R60. Compared to the original principal coordinates of neighbour matrices method, identifying the eigenvectors modelling positive spatial correlation that are used in most ecological studies is easier with the dbMEM method59. Briefly, this analysis consists in constructing a matrix of geographic distances among sampling sites, upon which a principal coordinate analysis is performed to obtain eigenvectors that are then used as spatial explanatory variables in the variation partitioning analysis. The eigenvectors represent spatial relationships between the sites, describing wide- and small-scale variation. The first dbMEM vectors describe large scale variation, whereas later dbMEM vectors represent small scale variation.To assess the influence of local environmental, regional climatic and spatial factors on taxonomic and on functional β-diversity, we conducted a variation partition procedure based on redundancy analysis61, to create more parsimonious sets of explanatory variables. These were selected from the group of variables from which highly correlated variables had already been excluded . Negative values of adjusted R2 correspond to less variation being explained than by random explanatory variables and can thus be interpreted as zero34. We performed the variation partitioning analysis using package vegan in R63.For each β-diversity component, we analyzed the total accounted for and unaccounted for variation; the variation explained individually by pure local environmental, pure regional climatic, and pure spatial effects, and by spatially structured environmental effects . In some cases, the sum of pure and shared effects did not equal to the total variation explained; this can happen when an effect has a negative adjusted RSupplementary Information


We regret any confusion or inconvenience this error may have caused.In Table 2 of the article “Community Pharmacists’ Contributions to Disease Management During the COVID-19 Pandemic,” data for the row labeled “Hispanic or Latino” were reversed. That row should read Percentage of US Population, 16.6; Percentage of COVID-19 Deaths, 27.7. The article was corrected on July 30, 2020, and appears online at


Results: For all three tobacco products, there was significantly more agreement with the cognition “I would smoke if my best friend offered” among tobacco users (used one or more tobacco products) than among non-users. For e-cigarettes and waterpipes, there was significantly more agreement with the cognition “It would be easy to quit these products” than was reported by non-users. Polytobacco users (three tobacco products) endorsed the cognitions scale  significantly more than non-users for cigarettes and e-cigarettes. Furthermore, waterpipe users, polytobacco users, dual users and single users all endorsed the combined cognitions scales more strongly than non-users. Conclusions: Efforts to prevent polytobacco use should ensure that young adults have the necessary self-efficacy to resist peer pressure and provide them with clear information about the health risks associated with using alternative tobacco products.Background: Polytobacco use is common among young adults. The purpose of the present study was to investigate a number of cognitions related to the use of three tobacco products  among young adults. Methods: Participants ( In most regions of the world, cigarette use continues to have a high prevalence among young adults ,2,3. FurE-cigarettes, and other alternative nicotine and tobacco products (ANTP), such as waterpipes , have become increasingly attractive to young adults ,6. A subPolytobacco use, which is the concurrent use of alternative nicotine products and cigarettes, has been found to be more prevalent among young adults (18–25 years) than in older adults (26–34 years) ,10,11. PPrevious studies have investigated the relationship that tobacco product use has with tobacco-related perceptions and attitudes among young adults . IndividMore research into the cognitions related to polytobacco use among young adults is needed in order to better understand this increasing phenomenon and to help develop effective prevention programs, especially for emerging ANTPs, such as waterpipes. The present study set out to investigate a number of cognitions surrounding the use of cigarettes, e-cigarettes and waterpipes among young adults.The study design was based upon previous polytobacco research . A conveParticipants reported their sex, age and ethnicity.Current tobacco use was assessed using the question “How frequently have you smoked cigarettes/e-cigarettes/waterpipes during the past 30 days?”. For each tobacco product, the response options were: “never”, “occasionally”, “once a week”, “more than once a week, but not every day”, and “every day”. Participants who reported “never” using tobacco were classified as “non-users” and those who answered “occasionally”, “once a week”, “more than a week, but not every day” or “every day” were classified as “current users”. Furthermore, those who reported the use of one tobacco product were classified as “single product users”, those who reported the use of two products were classified as “dual users” and those who reported using three products were classified as “poly users” .The cognitions associated with tobacco use were based upon previous research in this area . The queIn order to construct the tobacco use cognitions scales (TUCS), the cognitions were dichotomized into “would not endorse” (definitely no and probably no), rated 0, or “would endorse” (definitely yes and probably yes), rated 1 . FollowiChi-square tests were used to compare percentages, while t-tests and ANOVAs were used to compare means. Effect sizes were computed using the phi coefficient, Cohen’s d and eta squared. All analyses were performed using SPSS v23 manufactured by IBM Corp. .n = 475; 59.4%) and had a mean age of 21.8 (SD = 1.7). Most participants identified themselves as Turkish (60.6%), followed by Greek, Greek Cypriot or Turkish Cypriot (21.8%), other European (5.3%) and other ethnicity (12.4%).The majority of the participants were female (2(2)= 9.8; p = 0.002; Φ = 0.11) and e-cigarette use  = 11.9; p = 0.001; Φ = 0.12), but no significant differences were found for waterpipe use  = 4; p = 0.55). With regard to age and ethnicity, current cigarette users were older  and were more likely to be Turkish = 2.2; p = 0.007; Φ = 0.12), than non-users, but no differences were observed for e-cigarette or waterpipe use. Among those who had used tobacco in the last 30 days, women were less likely than men to report cigarette , with cigarette use in the past 30 days being the most common (56.9%), followed by waterpipes (47.2%) and e-cigarettes (29.7%). Among current users, 30% were classified as single users, 22.7% as dual users and 19.1% were classified as polytobacco users.The majority of participants were tobacco products users , there was significantly more agreement with the cognition “I would smoke if my best friend offered” among current users (used one or more tobacco product) than among non-users . All thrCurrent cigarette users  endorsed the cognition “the product helps people relieve stress” significantly more than non-users. Furthermore, dual or poly users endorsed the cognition “the product makes young people feel more comfortable” significantly more than non-users. In addition, single and poly waterpipe users endorsed the cognition “The product helps people relieve stress” significantly more than non-users and dual users.There were statistically significant differences in the tobacco use cognitions scales (TUCS) by polytobacco use status . For cigThe present research found that the cognition “I would smoke if my best friend offered” was strongly associated with tobacco product use  and polytobacco use among young adults, in agreement with previous research on adolescents . MoreoveFor e-cigarette and waterpipe use, the cognition “It would be easy to quit” was related to use of these products and to polytobacco use, as previously found among adolescents . In contThe cognitions “The product helps people relieve stress” and “The product makes young people feel more comfortable” were both associated with traditional cigarette use. Moreover, relieving stress was also associated with single and poly users for waterpipe use. Previous research has found that questions measuring affect regulation, such as boredom reduction, were predictive of polytobacco use among young adults . FurtherConsistent with previous studies  , our finPrevious research has considered young adults to be particularly inclined to use waterpipes and has reported the need for public health messages to prevent the initiation and progression of waterpipe use ,28,29. FThe present study has several limitations. Firstly, as this was a cross-sectional survey, only associations between the variables can be reported. Secondly, only two alternative nicotine products were investigated (e-cigarettes and waterpipes), so it is not possible to make conclusions about other alternative nicotine products. The study also used a convenience sample of university students that may not be representative of all young adults in Turkey and Cyprus. Furthermore, all measures relied on self-reported behaviour, which may be vulnerable to a number of potential biases, such as social desirability bias. The present study also has a number of strengths. Firstly, the present study was conducted in a population that differs substantially from those normally used to research health-related behaviours. Furthermore, the present study provides new information about the cognitions associated with polytobacco use in this novel population. In addition, the present study provided more information about the cognitions associated with waterpipe use. Another innovative element of the present study was the creation of a tobacco use cognitions scale. Interventions to prevent polytobacco use should focus on ensuring that young adults have the necessary self-efficacy to resist peer pressure. These interventions must also provide clear and complete information about the health risks associated with these alternative tobacco products. Future prevention campaigns must also be designed to take into consideration these cognitions about waterpipes, cigarettes and e-cigarettes. Future research is also needed to understand the transitions between products, as well as the cognitions associated with the maintenance of tobacco product use.


The ability to quickly identify fearful faces is important for the activation of defense mechanisms that allow an individual to deal with potential emergencies. This study examined the relationship between frontal electroencephalography (EEG) alpha asymmetry and the processing of congruent and incongruent fearful faces among female participants using event-related potentials (ERPs). Behavioral results showed that individuals with more left frontal EEG alpha asymmetry had shorter response times than individuals with more right frontal EEG alpha asymmetry during the cue-target task. ERP results indicated that, for individuals with more left frontal EEG alpha asymmetry, enhanced N1 reflected more rapid processing of emotional faces in the early stage, and enhanced P3 indicated that these individuals directed more attentional and motivational resources to the evaluation of emotional faces in the late stage. For individuals with more right frontal EEG alpha asymmetry, enhanced N2 indicated that these individuals experienced more conflict for incongruent fearful faces in the late stage. The present findings suggest that frontal EEG alpha asymmetry during resting conditions can reflect individual differences in the processing of congruent and incongruent fearful faces. Investigation of the factors that underlie individual differences in the evaluation of emotional stimuli continues to be a central focus in the field of affective neuroscience. Fear expression as the fundamental emotional face stimuli plays an important role in human survival and adaptation . The abiFrontal EEG alpha asymmetry reflects differences in activation of the alpha frequency band  of the left and right frontal cortices; there is an inverse relationship between activity within the alpha range and cortical processing . ResearcEvent-related potentials (ERPs) have high temporal resolution and can be used to study the unfolding of emotional processing. A large number of studies have investigated the time course of neural activity underlying the processing of fearful faces using ERPs. Findings indicate that fearful faces elicit a larger P1 , a largeIn addition, emotional processing is different between women and men. Studies have shown that compared with men, women are more accurate and faster in identifying emotional stimuli , have moGiven the above, the current study aimed to examine the relationship between frontal EEG alpha asymmetry and the processing of congruent and incongruent fearful faces among female participants using ERP markers. In this study, participants first completed a 2 min resting task and then completed a cue-target task. For the purposes of this study, we were interested in early processing components  and late processing components  as they relate to the processing of congruent and incongruent fearful faces. Previous studies have indicated that frontal EEG alpha asymmetry during resting conditions can be considered as a neural index of emotional regulation , 2017. R∗ Power software was used to calculate the sample size in order to achieve a power of 0.85 at an α level 0.05 with an effect size of 0.30. The output of G ∗ Power software indicated that a sample size of 52 was required. As such, 56 healthy female undergraduate students  were paid to participate in this study. All participants self-reported that they were right-handed with normal or corrected-to-normal vision and had no neurological or psychological disorders. All participants completed the Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI), and all participants were suitable for the experiment because their scores on the BDI and BAI were within the normal range. All participants gave their written informed consent, and the study was approved by the local ethics committee of Ningbo University.G The BDI is a 21-item self-report measure designed to assess depression . The ChiF = 596.49, p < 0.001] and arousal   Participants were asked to complete a 2 min resting task, in which recording of resting EEG was obtained; the 2 min resting task included 1 min eyes open (O) and 1 min eyes closed (C). Two sequences were used, O–C–C–O and C–O–O–C; the presentation of these sequences was balanced between the subjects. (2) Participants were asked to complete the cue-target task, which was a modified version of the task used by E-prime 2.0 software was used to present the 2 min resting task and the cue-target task. All stimuli were presented in the center of a 17-inch LCD screen .Electroencephalography data were recorded using a NeuroScan recorder with a NuAmps amplifier. The electrode cap contained 40 Ag/AgCl electrodes, which were positioned according to the International 10–20 system. EEG signals were acquired by a DC model with a sampling rate of 1,000 Hz and a bandwidth of 100 Hz. Vertical and horizontal electrooculograms (EOGs) were recorded; the left mastoid electrode served as the reference. The impedance of all electrodes was kept under 5 kΩ.n = 56). Offline analysis of EEG signals was re-referenced to the Cz electrode1 and was filtered using a 30 Hz bandwidth (24 dB/octave slope). Power spectra were derived by fast Fourier transform with a Hamming window  for the 2-min resting task. For consistency with previous research (L − R)/(L + R)] × 100. Positive values indicate higher alpha activity in the left compared to the right hemisphere.Electroencephalography asymmetry measures were taken from the 2-min resting task. Neuroscan 4.3 software was used to analyze the EEG data. According to previous studies , all datresearch , we focuThe offline analysis of EEG signals was re-referenced to the mean of the left and right mastoids and was filtered using a 0.05- to 30-Hz bandwidth (24 dB/octave slope). Vertical and horizontal EOGs were filtered out according to the computation rule commonly used in ERP studies . The artAccording to a median split of frontal EEG alpha asymmetry scores during the 2-min resting task , individIn this section, we first report the behavioral results. Then, the ERP results are reported. For the sake of brevity, the statistical effects that did not reach significance are omitted.Before statistical analysis, the no-response trials were removed. Then, subjects were divided into two groups (IRA and ILA) based on a median split of baseline asymmetry. F = 16.81, p < 0.001, η2 = 0.237, indicating that the accuracy rate for the word “fear” was higher than for the word “neutral.” The main effect of expression type was significant, F = 55.19, p < 0.001, η2 = 0.505, indicating that the accuracy rate for fear faces was lower than for neutral faces. The interaction effect of prime cue × expression type was significant, F = 33.94, p < 0.001, η2 = 0.386. The simple effect analysis of prime cue × expression type showed that the accuracy rate for fear faces when the prime cue was the word “fear” was higher than that when the prime cue was the word “neutral” (p < 0.001), whereas there was no significant difference between neutral faces when the prime cue was the word “fear” and when the prime cue was the word “neutral” (p = 0.068).For the accuracy rates, the main effect of the prime cue was significant, F = 54.50, p < 0.001, η2 = 0.502, indicating that reaction times to the word “fear” were shorter than to the word “neutral.” The main effect of group was significant, F = 4.39, p = 0.041, η2 = 0.075, indicating that the reaction times of the ILA group were shorter than those of the IRA group. The interaction effect of prime cue × expression type was significant, F = 13.67, p = 0.001, η2 = 0.202. The simple effect analysis of prime cue × expression type showed that when the prime cue was the word “neutral,” the reaction times for fear faces were longer than neutral faces (p = 0.003), whereas there was no significant difference between fear faces and neutral faces when the prime cue was the word “fear” (p = 0.256).For response times, the main effect of the prime cue was significant, F = 4.85, p = 0.032, η2 = 0.082, indicating that ILA had larger N1 amplitudes than IRA.For N1, the main effect of group was significant, F = 11.29, p = 0.001, η2 = 0.173, indicating that fear faces induced larger P2 amplitudes than neutral faces.For P2, the main effect of expression type was significant, F = 25.55, p < 0.001, η2 = 0.321, indicating that fear faces induced smaller N2 amplitudes than neutral faces. The main effect of electrode was significant, F = 67.88, p < 0.001, η2 = 0.557, indicating that the anterior region induced greater N2 amplitudes than the posterior region. The interaction effect of prime cue × expression type was significant, F = 10.36, p = 0.002, η2 = 0.161. The interaction effect of prime cue × electrode was significant, F = 5.37, p = 0.024, η2 = 0.090. The interaction effect of prime cue × electrode × group was significant, F = 5.61, p = 0.021, η2 = 0.094. The interaction effect of prime cue × expression type × group × electrode was significant, F = 5.41, p = 0.024, η2 = 0.091. The simple effect analysis of prime cue × expression type × electrode × group showed that for IRA, fear faces when the prime cue was the word “neutral” induced greater N2 amplitudes than when the prime cue was the word “fear” (p’s < 0.05). However, there were no significant differences for ILA (p’s > 0.05).For N2, the main effect of expression type was significant, F = 12.69, p = 0.001, η2 = 0.190, indicating that fear faces induced greater P3 amplitudes than neutral faces. The main effect of group was significant, F = 4.68, p = 0.035, η2 = 0.080, indicating that ILA had greater P3 amplitudes than IRA. The interaction effect of prime cue × expression type was significant, F = 5.61, p = 0.021, η2 = 0.094. The interaction effect of prime cue × electrode × group was significant, F = 4.99, p = 0.030, η2 = 0.085. The interaction effect of prime cue × expression type × electrode × group was significant, F = 4.11, p = 0.048, η2 = 0.071. The simple effect analysis of prime cue × expression type × electrode × group showed that fear faces induced greater P3 amplitudes when the prime cue was the word “fear” than when the prime cue was the word “neutral” for the IRA group only (p’s < 0.05). However, there were no significant differences in the ILA group (p’s > 0.05). Another simple effect analysis method showed that the ILA group had a larger P3 than the IRA group for the word “neutral,” regardless of whether it was followed by fear faces or neutral faces, and for the word “fear” followed by neutral faces (p’s < 0.05). However, there was no significant difference between ILA and IRA for the word “fear” followed by fear faces (p > 0.05).For P3, the main effect of expression type was significant, The present study examined whether frontal EEG alpha asymmetry during resting conditions is related to the processing of congruent and incongruent fearful faces among female participants. Behaviorally, we found that the IRA group had longer reaction times than the ILA group during the cue-target task. The ERP results showed that there was a modulating effect of frontal EEG alpha asymmetry on congruent and incongruent fearful faces in N1, N2, and P3 time intervals.The behavioral results showed that the accuracy of fearful faces when the prime cue word was “fear” was higher than when the prime cue word was “neutral.” These results indicated that fearful faces processing was influenced by anticipation that congruent prime cue had higher accuracy than incongruent prime cue for fearful faces. Some studies have shown “negative bias” for the processing of emotional information, in which negative stimuli are often quicker to attract attention and priority in mental processing . In the The ERP results indicated that ILA had larger N1 amplitudes than IRA. Previous studies have shown that N1 is associated with early perceptual processing . N1 servFurther, fearful faces, when the prime cue word was “neutral,” induced greater N2 amplitudes than when the prime cue word was “fear,” among the IRA group only. Previous studies have shown that the N2 component is related to conflict monitoring. For example, N2 is sensitive to the degree of conflict between response alternatives in the flanker task . TherefoIn addition, the ILA group exhibited larger P3 amplitudes than the IRA group for the word “neutral,” regardless of whether it was followed by fear faces or neutral faces, and for the word “fear” when followed by neutral faces. In studies using emotional stimuli, P3 has been summarized as reflecting the allocation of limited resources toward motivationally salient environment stimuli, in which motivationally relevant stimuli  naturally and automatically arouse and direct attentional and motivational resources . AccordiThe present study suggests that frontal EEG alpha asymmetry during resting conditions is associated with the processing of congruent and incongruent fearful faces. The neuro-laterality models of affect and psychopathology assume that the left and right frontal cortical hemispheres are differentially involved in processes modulating affective responses to emotional challenges . It has A potential limitation of the present study is that it is unclear how frontal EEG alpha asymmetry during resting conditions relates to the processing of congruent and incongruent fearful faces. A previous study found that fear emotion induced by fear stimuli increased activation of the frontal cortex. With the increased frontal cortical activity, there was a downward trend in amygdala activation . Future The present study suggests a relationship between frontal EEG alpha asymmetry and the processing of congruent and incongruent fearful faces. In this study, ILA quickly processed the emotional faces in the early stage and directed more attentional and motivational resources to the evaluation of the emotional faces in the late stage, while IRA experienced more conflict for incongruent fearful faces in the late stage and longer reaction times during the cue-target task. Therefore, frontal EEG alpha asymmetry during resting conditions can reflect individual differences in the processing of congruent and incongruent fearful faces.The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by the Ethic Committee at the Department of Psychology, Ningbo University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.Both authors developed the ideas and wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


ABA− of non-overlapping brief tones, A and B, is a valued paradigm for studying auditory stream formation and the cocktail party problem. The stimulus is “heard” either as a galloping pattern (integration) or as two interleaved streams (segregation); the initial percept is typically integration then followed by spontaneous alternations between segregation and integration, each being dominant for a few seconds. The probability of segregation grows over seconds, from near-zero to a steady value, defining the buildup function, BUF. Its stationary level increases with the difference in tone frequencies, DF, and the BUF rises faster. Percept durations have DF-dependent means and are gamma-like distributed. Behavioral and computational studies usually characterize triplet streaming either during alternations or during buildup. Here, our experimental design and modeling encompass both. We propose a pseudo-neuromechanistic model that incorporates spiking activity in primary auditory cortex, A1, as input and resolves perception along two network-layers downstream of A1. Our model is straightforward and intuitive. It describes the noisy accumulation of evidence against the current percept which generates switches when reaching a threshold. Accumulation can saturate either above or below threshold; if below, the switching dynamics resemble noise-induced transitions from an attractor state. Our model accounts quantitatively for three key features of data: the BUFs, mean durations, and normalized dominance duration distributions, at various DF values. It describes perceptual alternations without competition per se, and underscores that treating triplets in the sequence independently and averaging across trials, as implemented in earlier widely cited studies, is inadequate.A repeating triplet-sequence  ABA− of non-overlapping brief pure tones, A and B, frequency-separated, is a valued stimulus. Studies typically focus on one of two behavioral phases: the early  buildup of segregation from the default integration or later spontaneous alternations (bistability) between seconds-long integration and segregation percepts. Our experiments and modeling encompass both. Our novel, data-driven, evidence-accumulation model accounts for key features of the observations, taking as input recorded spiking activity from primary auditory cortex . Our results underscore that assessing individual triplets independently and averaging across trials, as in some earlier studies, is inadequate . Further, we identify fresh parallels between evidence accumulation and competition as potential dynamic processes for choice in the brain.Segregation of auditory objects (auditory streaming) is widely studied using ambiguous stimuli. A sequence of repeating triplets  A and B pure tones have been widely used in studying segregation of distinct objects in an auditory scene (auditory streaming), in human psychophysics  = T-(T-Tf)λn and variance Var[Xn] = σ2(1 − λn2)/(1 − λ2). In particular, at the nth triplet during integration, the mean and variance of xS (xI) that accumulated evidence against (for) the percept were E[xS] = Ea, Var[xS] = Va, E[xI] = Ef, Var[xI] = Vf wherep = 1 − pseg;DF. Then at the nth triplet during segregation they were E[xI] = Ea, Var[xI] = Va, E[xS] = Ef, Var[xS] = Vf with Ea, Va, Ef, Vf defined as above but computed with p = pseg;DF. Given that 3 times the standard deviation from the mean accounts for 99.73% of values in a normal distribution, if σa was too small the accumulators could cross the threshold 1 only with very small probabillity. From the calculation above, a lower bound for σa in the model was estimated at σa > σa,min with pM was the maximum of pseg;DF and 1 − pseg;DF for all DF = 3, 5, 7. For example, if Ta = 0.9 then a necessary condition for switching was σa > 0.022.Our EVA model features accumulation that could saturate, given that target-against d by Eqs  and 7)..Ta was a λ = 1-p . Therefoσa the accumulators in the EVA model could not cross threshold 1 -plane, alternations between percepts occurred and the dominant durations were distributed according to: normal distributions at σa small . The range for σa that led to gamma-like distributions varied slightly with Nsl with the biggest difference being identified at Nsl = 1; see As explained in the previous section, for small ge  in the ABA− sequence and for each semitone difference DF = 3, 5, 7; see section Input Layer and mt,DF at A-tone selective neurons in A1 during presentation of tones A, B and A in ABA− were extracted from [t ≤ 20 in the sequence and for each DF = 1, 3, 6, 9; See scatter points in [mDF1, measured at the first triplet to some level mt,DF and the corresponding exponential curve  defined by DF = 1, 3, 6, 9 at any fixed t.Parameter mean values B-tones of any pool of A-tone selective IL neuronal units, as well as the standard error to the mean, were computed from simulation of Poisson processes with parameter mt,DF while varying Nin  of the stimulus  dx = γadt+ σadWt with positive drift rate γa, noise amplitude σa, Gaussian white noise dWt, and decision threshold θ = 1. In this DDM, the likelihood of first-passage at time t follows an inverse Gaussian distribution [γa, variance CV but converges to a normal distribution as σa decreased in relation to drift rate γa [σa chosen in a restricted parameter range, given fixed targets Ta and Tf . Outside this range, percept durations followed either normal distributions  or exponential distributions . However, the accumulation process in the EVA model is different than in the DDM for several reasons: To gain some intuition about the accumulation process in our EVA model and about the timing of switch events, we considered an approximation of the stochastic ribution  with den rate γa . To someS1 FigDF = 3 and B: DF = 7. They are obtained from numerical simulations of the EVA model  and compared to those derived from behavioral data .Distributions of normalized phase durations are shown for A: (TIF)Click here for additional data file.S2 FigDF = 3 and 220 out of 675 for DF = 7, the first percept is segregation . During a cycle, the suppressed unit accumulates evidence against the current percept until it reaches the switching threshold. Then, a perceptual switch occurs and accumulators are reset to the same value. In the noise free case, the accumulators stabilize to their corresponding target values and there are no alternations. Such trajectories are depicted by dashed lines.In only a few trials, 103 out of 675 for (TIF)Click here for additional data file.S3 FigNsl = 1 (e.g. for subsequent durations). A two-parameter response diagram of the dependence of μ and α on target-against Ta and noise strength σa is shown for DF = 5 and varying Nsl for A: first percepts and B: subsequent percepts. All parameters are chosen as described in Methods, except for Nsl . For comparison, see Nsl = 20 at DF = 5. Red diamonds correspond to same parameter choices as in Nsl = 20, as well. The heat map represents the ratio μ/μexp between model-generated μ and mean duration μexp from the behavioral data. Regions of no alternations (na) are colored in gray. Mean durations are much longer than their experimental counterparts μexp (region in warm colors), much shorter than μexp (region in cool colors), or close to μexp . The distributions of normalized percept durations are characterized by three distinct regions: for small σa the distributions are normal ; for large σa the distributions are exponential ; for intermediate values σa the distributions are gamma-like with shape close to that found experimentally . As in Nsl = 1 this intersection is empty for both subsequent percepts I and S .Some important differences occur, however, at (TIF)Click here for additional data file.S4 Figmt;DF (scatter points) at A-tone selective neurons in A1 during tone B were extracted from [DF = 1 (blue), 3 (green), 6 (red), 9 (cyan), based on 10 s (20 triplets) long trials. The mean spike counts decrease exponentially and stabilize within a few seconds . The algorithm generates spike counts during B-tone by using Poisson processes of means mt;DF, and then average them over Nin neuronal units. The average values of the mean spike counts, including asymptotic values (written in parenthesis) at each DF, and the standard error to the mean (SEM) are computed over 675 trials. Lower panel: The signal detection algorithm constructs neurometric functions using numerical data from all Nin neuronal units. Parameters Nin and Cth are chosen to yield SEM similar to those observed in the spike count data [DF = 1, 3, 6, 9. The best approximation is obtained for Nin = 30, Cth = 4.64. Note: Statistics of percept durations were not reported in [DF = 1, 3, 6, 9.For comparison, see Micheyl et al (2005) . Upper p(TIF)Click here for additional data file.S5 Figα of gamma distributions are shown for A: Experimental data; B: EVA model with optimized values for target-against . On the other hand, gamma-fit shape values α are comparable to those from panels A and B. This is not surprising given that α depends mostly on the noise-level σa, as shown in For comparison, mean durations and shape parameter (TIF)Click here for additional data file.


Previous studies have reported that verbal sounds are associated—non-arbitrarily—with specific meanings , including visual forms of information such as facial expressions; however, it remains unclear how mouth shapes used to utter each vowel create our semantic impressions. We asked 81 Japanese participants to evaluate mouth shapes associated with five Japanese vowels by using 10 five-item semantic differential scales. The results reveal that the physical characteristics of the facial expressions (mouth shapes) induced specific evaluations. For example, the mouth shape made to voice the vowel “a” was the one with the biggest, widest, and highest facial components compared to other mouth shapes, and people perceived words containing that vowel sound as bigger. The mouth shapes used to pronounce the vowel “i” were perceived as more likable than the other four vowels. These findings indicate that the mouth shapes producing vowels imply specific meanings. Our study provides clues about the meaning of verbal sounds and what the facial expressions in communication represent to the perceiver. According to a famous Japanese proverb, “names and natures do often agree.” Consistent with this proverb, verbal sounds often agree with specific representations. If people listen to the meaningless sounds of “bouba” or “baluma,” they imagine a circular and expansive shape. When participants judged which figure is “bouba” when presented a pointy figure and a round figure, the most participants selected the round figure as “bouba” ,2,3. VowFacial display is a tool well known to humans, and it facilitates our social communication; in successful communication, perceivers usually try to understand targets’ internal states by focusing on what they are saying as well as what they are expressing through their facial configurations . In factTo understand how perceivers receive information from facial expressions, a specific assumption may be helpful: perceivers make inferences about each facial action separately, not holistically; that is, one’s physical facial action components  instead of a whole face may have an impact on perceivers’ inferences about others’ facial expressions. Indeed, Durán et al. showed in their meta-analysis on the coherence between facial expressions and emotional experiences that prototypical whole facial patterns were not coherent with the emotional experiences of the expressers, whereas there was a small coherence between their emotional experiences and individual facial components . MoreoveWhen people pronounce words referring to smallness , these words are usually associated with and pronounced in high acoustic frequency, whereas words referring to largeness  are usually associated with low acoustic frequency . Thus, sHowever, these prior studies investigating mouth shapes made to produce vowels failed to evaluate what perceivers infer about mouth shapes when expressers produce all five vowels, so there is little literature available on the evaluation of the perception of each facial component. In social situations such as a casual conversation with another person, we interpret body language and verbal information simultaneously , and vowTo elucidate the relationships between specific facial expressions and perceived information, we conducted an exploratory investigation to evaluate what each vowel mouth shape stands for. The current study explored Japanese participants’ responses toward their visual recognition of mouth shapes made by expressers when pronouncing five Japanese vowels . We assumed participants would have associative memories between the mouth shapes and the vowels. We focused on the Japanese language and Japanese native speakers as the target language and sample, respectively, because Japanese includes numerous sound-symbolic words, which indicate non-arbitrary associations between verbal sounds and sensory-motor/emotional features . A dictiM = 19.86 years, SD = 10.74) with normal or corrected-to-normal vision took part in the current study. Informed consent was obtained from each participant before the investigation. After a lecture on introductory psychology, all participants received a QR code to perform the experimental task voluntarily. All tasks were performed with a smartphone. This study was approved by the Ethics Committee of the Graduate School of Education, Hiroshima University, and was conducted in accordance with the Declaration of Helsinki . Participants did not receive any remuneration for their participation.Eighty-one Japanese participants . All participants were given a link to the experiment so that they were able to perform it during their own personal time. After completing and providing informed consent via Qualtrics, participants were asked to evaluate each image by 10 semantic differential scales, which comprised a block . All fivTo compare evaluations among the lower facial configurations voicing a vowel, we conducted one-way within-subjects ANOVA tests for the effect of the vowels . If there was a significant effect, we further analyzed pairwise comparisons using Shaffer’s modified sequentially rejective Bonferroni procedure, and this was performed for all 10 adjectives (Q1–Q10). All analysis was performed by R (3.6.1)r = 0.57), while preference and unfamiliarity had negative correlations (r = −0.43). The meaning of these pairs appears to be similar, so they make sense when taken together. As for preference and familiarity, the more familiar a shape, the more it will be preferred. Results for each mouth shape are separately reported below.First, the relationships among adjectives (the dependent variables) were examined. F = 25.69, p < 0.001, partial η2 = 0.24). The mouth shape made to voice the vowel “a” was significantly bigger than other configurations (ts(80) > 4.92, ps < 0.001), and the mouth shape made to voice the vowel “e” was also significantly bigger than the other two vowels: “i” and “u” (ts(80) > 4.43, ps < 0.002).F = 1.21, p = 0.31, partial η2 = 0.02). There was no difference in perception about distance for each facial configuration.The results indicate a significant effect of facial configurations  = 22.73, p < 0.001, partial η2 = 0.22). The mouth shape made to voice the vowel “i” was significantly thinner than other configurations (ts(80) > 6.50, ps < 0.001).The results indicate a significant effect of facial configurations  = 31.86, p < 0.001, partial η2 = 0.29). Consistent with the evaluation of size on Q1, which correlated highly with this item (r = 0.54), the mouth shapes made to voice the vowels “a” and “e” were significantly wider than other configurations (ts(80) > 2.98, ps < 0.02), while “a” was wider than “e” (t(80) = 5.13, ps < 0.001).The results indicate a significant effect of facial configurations  = 7.97, p < 0.001, partial η2 = 0.09). The mouth shape taken to voice the vowel “i” was significantly lighter than the mouth shapes voicing “u,” “e” or “o” (ts(80) > 3.73, ps < 0.005).The results indicate a significant effect of facial configuration  = 5.11, p < 0.001, partial η2 = 0.06). The mouth shape made to voice the vowel “a” was significantly higher than the other vowels: “i,” “u” and “e” (ts(80) > 3.02, ps < 0.02). Additionally, the mouth shape made to voice the vowel “o” was also significantly higher than that of “u” (t(80) = 2.83, ps = 0.04). Other comparisons were not significant (ps = ns).F = 24.84, p < 0.001, partial η2 = 0.24). The mouth shapes made to voice the vowel “i” and “e” were shallower than other configurations (ts(80) > 4.33, ps < 0.001), while “i” was shallower than “e” (t(80) = 2.76, ps < 0.03).The results indicate a significant effect of facial configurations  = 11.26, p < 0.001, partial η2 = 0.12). As ts(80) > 4.28, ps < 0.001).The results indicate a significant effect of facial configurations  = 15.86, p < 0.001, partial η2 = 0.17). The mouth shape made to voice the vowel “o” significantly provided more arousal than other configurations (ts(80) > 3.99, ps < 0.001). Furthermore, the mouth shape made to voice the vowel “i” significantly provided less arousal than any other configurations (ts(80) > 2.75, ps < 0.03).The results indicate a significant effect of facial configurations  = 6.52, p < 0.001, partial η2 = 0.08). The mouth shape made to voice the vowel “i” was more familiar than other shapes (ts(80) > 2.76, ps < 0.05), except for “a” as t(80) = 1.31, p = 0.77). Additionally, the mouth shape made to voice the vowel “a” was more familiar than the shape made to voice the vowel “o” (t(80) = 2.99, p = 0.02). Other comparisons were not significant (ps = ns).The results indicate a significant effect of facial configurations  . We beliThe mouth shape made to pronounce the vowel “i” was perceived as thinner, lighter, and shallower than other mouth shapes. Although a previous finding reported that the mouth shape of “i” was the widest compared to other vowels , the parFurthermore, the mouth shape made to pronounce the vowel “o” was perceived as higher and deeper, producing arousal and unfamiliarity in this study. A previous linguistic study identified that the secondary sound symbolism of the vowel “o” was associated with semantic features such as “modest, unremarkable, unnoticeable, shabby, indistinct, or unsophisticated” . Given tThis study provided relevant evidence, yet there were several limitations. First, the five-item semantic differential scales assessed seven physical and only three psychological features ; thus, it provided far less information on the psychological state of the sample when compared to several other psychological scales used to assess psychological representations. Therefore, additional studies should be conducted using diverse rating scales, including those with constructs such as competence, attraction, and disgust.Second, it could be clearly seen in the visual stimuli that there was only one mouth used in the examples, and it was a man’s. Thus, it is difficult to generalize our results, and future studies need to identify these same evaluations regarding stimuli using mouths with female and non-binary gender markers. Additionally, the results of this study were based on samples of Japanese native speakers. Thus, future data collection from samples of other populational groups or remote cultures could prove very meaningful for facial expression research, which could corroborate our research and increase the relevance of our findings.Third, although our findings are consistent with relationships between words with vowels including high second formants and size ,5,6, we Finally, although we examined the subjective evaluations of the mouth shapes to pronounce vowels, the actual words included multiple vowels. In Japanese sound-symbolic words, a linguist suggests that the functions of the first vowels are different from those of the second vowels . For insThe results show that participants made several inferences in accordance with the physical characteristics of each mouth shape taken to utter each vowel. This was consistent with previous findings of sound-symbolic effects related to vowels and their meanings ,5. Furth


To analyze the oral health-related impact profile in patients treated with three different types of dental prosthesis in student courses.n = 70), removable (n = 61), or telescopic dental prostheses (n = 20) in clinical student courses of two German universities from October 2018 to October 2019. All patients completed three standardized German versions of the Oral Health Impact Profile (OHIP-G49/53) before prosthetic treatment (T0), at control after 1 week (T1), and after 3 months (T2), divided into five dimensions: (a) appearance, (b) oral function, (c) psychosocial impact, (d) linguistic limitations, and (e) orofacial pain. Data were analyzed with Kolmogorov–Smirnov, Wilcoxon signed-rank, Kruskal–Wallis, Mann–Whitney, and Cronbach’s alpha tests.This prospective bicenter clinical trial was conducted with 151 patients being treated with fixed (p ≤ 0.014), linguistic limitations (p ≤ 0.016), and appearance (p ≤ 0.003). No significant differences were found between fixed and telescopic dental prostheses (p ≥ 0.104) or between removable  and telescopic dental prostheses (p ≥ 0.100). Within T1–T2, a significant improvement in orofacial pain could be determined (p = 0.007).Within T0–T1 and T0–T2, greater improvements were determined for removable compared with fixed dental prostheses for the dimensions’ oral function (Restorations presented an improvement in oral health-related quality of life. Removable dental prostheses showed better improvement than fixed ones in various dimensions.Knowledge about the influence of oral health-related quality of life on the three different types of prosthesis used in student courses can be of decisive help in dental consultations. Overall quality of life (QoL) depends crucially on the oral health-related quality of life (OHRQoL) . The indIn general, an OHIP questionnaire represents a subjective evaluation of individual oral health and, in some cases, of patients’ expectations, feelings, and satisfaction with regard to a prosthetic restoration , 10, 16.The scientific literature generally shows an improvement in oral health-related impact profile through prosthetic restorations, although this appears to depend on the restoration type . In two There is no change in patients’ oral health-related impact profile after prosthetic restoration in a student course in relation to specific questions and the dimensions.There are no differences in patients’ oral health-related impact profile between prosthetic type after prosthetic treatment within a student course.To the best of the authors’ knowledge, there has been no comparable study of the oral health-related impact profile of patients who have been prosthetically restored with three different types of dental prosthesis in student courses and comparison between them. The hypotheses of the present study state that:The present prospective bicenter clinical trial was conducted in two prosthetic dentistry departments in Germany. The ethics committees of both universities approved the study . In advance, written informed consent was obtained from all patients participating. A Consort flow diagram is presented in Fig. n = 75; Würzburg n = 76); they were treated with fixed (n = 70), removable (n = 61), or telescopic (n = 20) dental prostheses  in both centers from October 2018 to October 2019. Fixed dental prostheses included crowns and fixed dental prostheses, removable dental prostheses included partial dental prostheses with clasps and complete dental prostheses, and telescopic dental prostheses were fabricated with friction telescopes. The following inclusion criteria were defined:All patients completed a total of three standardized German versions of the Oral Health Impact Profile (OHIP-G49/53). Patients who were treated with removable dental prostheses completed the entire questionnaire with all 53 questions. Patients with fixed dental prostheses completed only 49 questions, as the last three questions are only for removable dental prostheses. Only patients who completed all three questionnaires were included in the study.The first questionnaire (T0) was completed as a baseline questionnaire before the start of the prosthetic treatment. The second questionnaire (T1) was completed after definitive insertion of the dental prosthesis, at the follow-up appointment approximately 1 week after insertion, and the third questionnaire (T3) was completed after 3 months of use. In the OHIP-G49/53 questionnaire used, patients had five options to answer the questions, and answers were therefore numbered 1 (never) to 5 (very often). All data were recorded in an Excel sheet.The OHIP-G49/53 questionnaires used were divided by the authors into five dimensions according to Liebermann et al. : (a) appThe individual difference values for the three investigation periods  and the corresponding dimensions were evaluated separately. The individual replies at times T0, T1, and T2 were considered. If the patient gave the same answer of value 0–5, the question was defined with the value 0; if the patient gave a positive or negative answer in the following questionnaire, a − or + was defined with the corresponding number, such as + 1 or − 3 .U tests using the grouped medians. Cronbach’s alpha test was performed as an additional reliability analysis to secure the compilation of all questions to the various dimensions. A power analysis was performed for all subgroups with the software G*Power 3.1 . Data were analyzed with the SPSS version 25.0 , and the level of significance was set at p = 0.017.The normal distribution was tested by Kolmogorov–Smirnov test. Significant differences in the questionnaires with respect to investigation times and dimensions were analyzed with Wilcoxon’s signed rank for matched pairs, Kruskal–Wallis, and Mann–Whitney The mean age of the patients was 64.7 ± 10.51 years.Among the questions, 94.9% and among the dimensions 82.2% of the values did not show a normal distribution. Consequently, non-parametric tests were subsequently used.The Cronbach’s alpha test revealed values between 0.738 (linguistic limitations) and 0.966  within the five dimensions.For question 3/10 (appearance) and question 1 , the greatest improvement was observed between T0 and T1 (median 0.971) and for question 1 also between T0 and T2 (median 1.304), followed by question 46  between T0 and T1 (median 0.923) and question 51  between T0 and T1 (median 0.909).The power analysis showed a power of over 90% for the individual subgroups of the different restoration types and dimensions for fixed restorations and removable dental prostheses, with the exception of the dimension of oral pain for removable dental prostheses (39%). For the restoration type of telescopic dental prostheses, the power ranged between 41 and 77%.p = 0.012; oral function p = 0.029) and between T0 and T2 . No significant difference could be found between investigation times T1 and T2  ; no significant differences were found between the other investigation times (p ≥ 0.067)  Fig..Fig. 4Bop = 0.012). The other investigation times did not show any differences (p ≥ 0.537)   Fig. .Fig. 6Bop = 0.012), “linguistic limitations” (p = 0.016), and “appearance” (p = 0.003)  presented no changes  or between removable and telescopic dental prostheses (p ≥ 0.100).Within the investigation period T0–T1, significantly greater improvements were found for removable as compared with fixed restorations for the dimensions “oral function” p = 0.01, “lingui p = 0.00  Figs. . All othes Figs.  and 6. Ip = 0.014), “linguistic limitations” (p = 0.002), and “appearance” (p = 0.001)  presented no changes  or between removable and telescopic dental prostheses (p ≥ 0.158).Within the investigation period T0–T2, significantly greater improvements were found for removable dental prostheses compared with fixed ones for “oral function” (1) Figs. , and 4. es Figs.  and 6. Ip = 0.007) could only be found for the dimension “orofacial pain”; all others showed no significant differences (p ≥ 0.100)  Fig. .The first hypothesis of the present study, which stated that there is no change in patients’ oral health-related impact profile after prosthetic treatment in a clinical student course in relation to specific questions and dimensions, can be rejected. Patients showed partly significant improvements in oral health-related impact profile after prosthetic treatment in a student course. In addition, significant differences were shown between the types of dental prosthesis in terms of oral health-related impact profile. Consequently, the second hypothesis can also be rejected. The specific differences are discussed below.The OHIP-G49 for fixed and OHIP-G53 for removable dental prostheses were used in the present study to analyze five different dimensions with corresponding questions. In particular, the important dimension “appearance” is not considered in the shorter OHIP versions , 15. SinRegarding fixed restorations, the present results showed a significantly lower increase in the OHRQoL in patients with fixed restorations than in those with removable dental prostheses for the dimensions “oral function,” “linguistic limitations,” and “appearance” at both T1 and T2 in relation to the baseline values, but the initial situation is decisive in this context. Most of the patients who received fixed restorations had no previous prosthetic restoration. The improvement of the value therefore seems to be lower. In contrast, the improvement of the OHRQoL with new removable dental prostheses in patients who had no prosthetic restoration before or new removable dental prostheses that probably have a better fit seem obvious. As in the present study, the prosthetic treatment with fixed restorations showed an improvement in OHRQoL in the scientific literature and data from other studies analyzing single-tooth restorations or multiple-unit fixed dental prostheses –21.Nevertheless, all restoration types showed an improvement as already described in literature . Within The same results were measured for the dimension “oral function.” In particular, question 51, which is specifically for removable dental prostheses, including telescopic restorations, and asks whether patients feel that their dental prosthesis has not fitted properly in the last 7 days, showed the greatest improvements. This can be explained by the fact that this is probably one of the main reasons for prosthetic treatment with new removable dental prostheses.A significant improvement in “linguistic limitations,” on the other hand, could only be found between T0 and T2 and was not already apparent at T1. Patients, especially those newly treated with removable dental prostheses with possibly palatal coverage, need time to get used to the linguistic function, which is underlined by the present results , 24. ConIn addition, a delayed improvement in the dimension of “orofacial pain” was only observed at investigation time T2 in relation to the data obtained at the follow-up appointment directly after insertion, regardless of the restoration type. This could also be due to the time required for any tissue or muscular structures to facilitate a specific impairment. Within this dimension, the greatest improvements for patients seem to have been achieved in the area of dry mouth.In the study of Jenei et al., the type of dental prosthesis showed no significant impact on the overall OHIP score . HoweverViola et al. found that the scores improved in patients treated with complete dental prostheses . In geneRegarding telescopic dental prostheses, there seemed to be no difference in oral health-related impact profile when patients were treated with telescopic dental prostheses compared with removable dental prostheses or fixed restorations. The literature also showed an improvement of the oral health-related impact profile, also for different telescope types , 30. HowA limitation of the present study is the long time period between T1 and T2, which was about 3 months. A measurement of the results after 1 month could have highlighted the faster improvement of the dimensions “orofacial pain” and “linguistic limitations”. Consequently, it cannot clearly be concluded how long a patient needs for an improvement. In other studies, different follow-up times were selected, but these partly correspond to the present study. The examination times are usually before the actual prosthetic treatment as a baseline value, directly after the insertion at the check-up date, and after 1 month , 12, 15,Significant improvements in oral health-related impact profile after fitting of dental prostheses were found between investigation times T0 and T1 and T0 and T2 for the dimensions “appearance” and “oral function,” independent of the restoration type.The dimension “linguistic limitations” showed a delayed improvement in oral health-related impact profile between T0 and T2, and the dimension “orofacial pain” showed the same between T1 and T2, independent of dental prosthesis type.For removable dental prostheses, a significantly greater improvement in oral health-related impact profile was found for the dimensions “oral function,” “linguistic limitations,” and “appearance” in contrast to fixed dental prostheses between T0 and T1, as well as between T0 and T2 and for “orofacial pain” from T1 to T2. However, the individual initial situations must also be taken into account.Within the limitations of the present study, the following conclusions can be drawn:


In this article, we created a new dataset comprising 10 ensembles for severe rainfall simulations at a high spatial resolution  in Egypt using the Weather Research and Forecast model Version 3.8 (WRF 3.8). The vertical grid had over 41 levels, extending from the surface to 10 hPa. The defined domain, a Lambert conformal conic projection, started from 24°E to 36°E. The ensembles were generated using 10 different microphysics schemes within the WRF 3.8. The severe rainfall event occurred between October 26 and 29, 2016. Final analysis data from National Center for Environmental Predictions were used for the initial and boundary conditions every 6 h at a spatial resolution of 1° × 1°. The geographical static input data, such as land use, albedo, and terrain height, were interpolated and prepared using a geogrid program in the WRF preprocessing system. This dataset is the first of its kind. It is addressing a need for this type of high resolution data over Egypt using physically- based numerical weather prediction models. Specifications table•Egypt lacks high-resolution meteorological datasets especially the precipitation. This dataset contains 10 ensembles generated using different numerical simulations from the WRF model for a heavy rainfall event that occurred in Egypt on October 26, 2016, at hourly intervals. This dataset is considered to be unique and critical.•This high-resolution (10 km) dataset was generated using the WRF 3.8, which consistently represents the physical processes in the atmosphere and the interaction with land surface. This dataset features three-dimensional information, which is unlike the few existing and available datasets for specific locations.•These 10 ensembles can be used to differentiate artificial intelligence algorithms in the classification and identification of precipitation and temperature patterns for heavy rainfall events.•This dataset can be used to determine the correlation among different meteorological datasets. Other statistical models can also be used to analyze other impacts.•This dataset is especially useful for flagship pilot studies within the Coordinated Regional Downscaling Experiment (CORDEX) framework which is part of World Climate Research Programme (WCRP). This flagship pilot study is interested in simulating short-term heavy rainfall events using regional climate models in “weather-like” mode in different domains •This dataset can be processed and visualized easily using both Climate Data Operator (CDO) and Ncview software respectively.1The dataset was divided into 10 directories, each representing an ensemble generated using a different microphysics scheme. The directory naming convention is WRF_microphysics_scheme_xyz, where “xyz” represents the used scheme. For example, WRF_microphysics scheme_ Kessler represents an ensemble whose WRF simulation utilized the Kessler microphysics scheme.Each directory features four NetCDF files. Each file contains data for a single day (24 h), consisting of 14 variables (see Specification Table) measured in three dimensions on an hourly basis. The file naming convention is EGYPT_WRF_3_8_xyz_dd_mm_yyyy.nc, where “xyz” represents the scheme used, “dd” is the date, “mm” is the month, and “yyyy” is the year. For example, EGYPT_WRF_3_8_ Kessler_25_10_2016.nc would refer an ensemble that utilized the Kessler microphysics scheme on October 25, 2016.22.12 (10 km × 10 km). The vertical grid has over 41 levels, extending from the surface up to 10 hPa. The static geographical fields, such as terrain height, soil properties, vegetation fraction, land use, and albedo, were interpolated and preprocessed using the geogrid program in the WRF preprocessing system (WPS). Final analysis data from National Center for Environmental Predictions were used for the initial and boundary conditions every 6 h at a spatial resolution of 1° × 1° The boundary and initial conditions were interpolated based on the model domain using the ungrib and metgrid programs in the WPS.WRF 3.8 2.2https://github.com/wrf-model/WRF).The 10 ensembles were generated using 10 different microphysics schemes within WRF 3.8: Kessler, Purdue–Lin, WRF Single-Moment-Microphysics 3-class, WRF Single-Moment-Microphysics 5-class, Eta Ferrier, WRF Single-Moment-Microphysics 6-class, Goddard, Thompson, Milbrandt–Yau Double Moment, and Morrison Double Moment. It used RRTMG longwave and shortwave models and the Unified Noah Land Surface model. The Yonsei University planetary boundary scheme and the MM5- similarity scheme were also used, in addition to the Grell 3D Ensemble (a cumulus scheme). The severe rainfall event occurred between October 26 and 29, 2016. The precipitation data of the 10 ensembles were compared to the Tropical Rainfall Measuring Mission's satellite data as presented in The authors have no conflicts of interest to report.