dataesr/scientific-paragraphs-categorization huggingface dataset:
The study of the relationships between the inter-individual variability of morphological features and that of fiber bundles or functional areas could probably contribute to the interpretation of the differences observed between the endocasts of ancient species. The largest current database, UKbiobank, which will soon include 100,000 brain images but also an exhaustive map of the genome for each subject  [11] , and the progress of paleogenomics  [12] , now make it possible to study the impact of genes inherited from our ancestors on our brain structures  [13, 14]. There are now also very large databases on brain development  [15, 16] , which will allow studies associating ontogeny and phylogeny. Finally, there is a major interest in the neuroimaging of non-human primates, which should also create synergies between neuroimaging and paleoanthropology  [17] [18] [19].
The substantial requirements of neuroimaging research have led to the design of robust and automatic methodologies for brain morphology analysis. In spite of an abundance of proposed methodologies, Darwinian-style pressure has selected a small number of software packages (SPM, Freesurfer, FSL) that are sufficiently simple to be used by more than a thousand research teams using MRI in one way or another. This de facto standardization of the analysis of brain anatomy has largely contributed to the success of the field and is linked to the emergence of a paradigm a la Kuhn that is difficult to escape without loss of credibility. The software is based on a powerful idea: "let's align brains with a template brain before comparing them". Voxel-Based-Morphometry (SPM, FSL), born in the 1990s, encompasses methods that practice this alignment in 3D ("non-linear warping")  [31].
They include approaches that work point-by-point but also ROI-by-ROI, with the ROI also being defined in the template space. VBM is a versatile technique that can be used for the cortex and for subcortical structures. The feature to be compared across subjects is a kind of grey or white matter density supposed to be a proxy for local tissue volume. A specific branch is dedicated to asymmetry studies, which usually involve the use of a specific symmetric template. The tools used in this area have generated much discussion  [32, 33]. The main issue lies in the fact that there is no clear ideal alignment across brains with varying morphologies (Figure  1 ), particularly with respect to the cortical folding that is supposed to be partially printed in endocasts  [34]. abundance of proposed methodologies, Darwinian-style pressure has selected a small number of software packages (SPM, Freesurfer, FSL) that are sufficiently simple to be used by more than a thousand research teams using MRI in one way or another.
These aspects are particularly important as the original fossils are housed all over the (ancient) world. Nevertheless, progress is still expected in the way we share the imaging datasets. Among technical limitations are those related to the size of the datasets and the necessary informatics environment to manage the analyses. The resolution is now potentially very high, allowing very precise analyses. Fortunately, computers and software have also progressed. In addition, paleoanthropologists could rely on the massive computational infrastructures that are currently emerging to support neuroscience research. For example, the virtual models of endocasts scattered all over the world could be gathered on Ebrains (https://ebrains. eu/, accessed on 11 October 2021), the platform resulting from the European flagship Human Brain Project, and give rise to synergies with other communities.
These aspects are particularly important as the original fossils are housed all over the (ancient) world. Nevertheless, progress is still expected in the way we share the imaging datasets. Among technical limitations are those related to the size of the datasets and the necessary informatics environment to manage the analyses. The resolution is now potentially very high, allowing very precise analyses. Fortunately, computers and software have also progressed. In addition, paleoanthropologists could rely on the massive computational infrastructures that are currently emerging to support neuroscience research. For example, the virtual models of endocasts scattered all over the world could be gathered on Ebrains (https://ebrains. eu/), the platform resulting from the European flagship Human Brain Pro- In fact, the main concern in "virtual anthropology" is probably an unexpected aspect.
A few pioneer studies have considered this problem  [4, 44]. Moreover, it is necessary to develop new tools for the automatic and reliable determination of the endocranial sulci  [45]. In the context of the PaleoBRAIN project, financed by the ANR, we are conducting a direct investigation of the correlation between the shape of the brain and that of the intracranial cast within a sample of modern humans using MRI (for Magnetic Resonance Imaging) acquisitions, including some with a specific sequence that allows the characterization of bone tissues. The comparison of morphometric data and anatomical traits between the brain and the endocast will be performed using state-of-the-art quantification methodologies. But our large dataset could probably also be used to refine the methodology dedicated to the sulcus detection in the endocast.
Current methodologies use differential geometry to detect sulci as ravine or crest lines  [4, 44]. A key component in the design of such robust detectors is the amount of local smoothing performed before detection, which is usually tuned to the scale of the features to be detected. The T1-weighted MRI of our dataset can be used to define the ground truth using the sulci detected by the Brain VISA software. Subsequently, the optimal smoothing can be estimated using an inverse problem framework. Thanks to the large dataset, we can probably afford to include the estimation of regularized spatial variations of the optimal amount of smoothing, which may help to achieve a more consistent sulcus detection throughout the endocast. This could help to overcome some of the weaknesses observed in the superior part of the brain [4].
In this context, there is little information available about variations in the global size of the different lobes and their relationship with each other between hominin species. In a previous study  [28] , we demonstrated clear differences in brain organization when considering the relative contribution of the different lobes to the surface of the complete endocast. Asian H. erectus specimens show a significantly smaller relative size of the parietal and temporal lobes than all other samples of the genus Homo. This field of research could benefit from the recent revival of interest in the study of the laws of allometry that govern the relative variations of the various cerebral structures, linked to the large databases of modern brain images  [49]. approaches are justified by the complex nature of the material.
Indeed, gyri and sulci are difficult to identify on the endocast (Figure  4 ). In this context, there is little information available about variations in the global size of the different lobes and their relationship with each other between hominin species. In a previous study  [28] , we demonstrated clear differences in brain organization when considering the relative contribution of the different lobes to the surface of the complete endocast. Asian H. erectus specimens show a significantly smaller relative size of the parietal and temporal lobes than all other samples of the genus Homo. This field of research could benefit from the recent revival of interest in the study of the laws of allometry that govern the relative variations of the various cerebral structures, linked to the large databases of modern brain images  [49].
Funding: This research received funding from the  Agence National de la Recherche  ( ANR-20-CE27-0009-01 ) to AB and from the  European Union 's  Horizon 2020 Research and Innovation Programme  under Grant Agreement No. 945539  ( HBP SGA3 ), from the  FRM   DIC20161236445 , from the  ANR IFOPASUBA and FOLDDICO , and from the  Blaise Pascal Chair of Region Ile de France and Université Paris Saclay  to  W. Hopkins.
All six-month-olds are equally likely to be given the infant vaccine series. The model is calibrated to country-level, age-specific HBsAg+ prevalence data and HBeAg+/ HBsAg+ prevalence data in pregnant women, obtained from the Polaris Observatory and from other sources  (Ott et al. , 2012a; Ott et al. , 2012b) , as well as to HBV-related cirrhosis and liver cancer death rates, obtained from the Global Burden of Disease Results Tool website (Institute for Health  Metrics and Evaluation, 2019). The calibrated model parameters include the risk of horizontal transmission to susceptible one to five year-olds and the risk of vertical transmission from HBsAg+ HBeAg-mothers to their infants. Calibration is performed by the Approximate Bayesian Computation Sequential Monte Carlo algorithm  (Toni et al.
, 2009). Other data sources include demographic data (female and male population sizes of one-year age groups, migration, female fertility rates of five-year age groups, sex ratio of infants, female and male life expectancy of five-year age groups, female and male mortality rates of five-year age groups) from the United Nations World Population Prospects (UNWPP) 2019 Revision and infant and BD vaccine coverage data from the WHO/UNICEF Estimates of National Immunization Coverage (WUENIC) and Gavi, the Vaccine Alliance. Uncertainty in model estimates are due to uncertainties in the prevalence data that are used in the model calibration, as well as uncertainties in historical coverage data, vaccine efficacies and the number of individuals on antiviral treatment. The model structure is regularly updated to reflect the latest understanding of the natural history of HBV.
Liver cirrhosis and hepatocellular carcinoma account for the majority of hepatitis B deaths worldwide. The age-specific liver cirrhosis mortality rates were derived from mortality statistics from the United States and Taiwan (China). The age-specific hepatocellular carcinoma incidence was derived by fitting a polynomial function to data from populations with high HBV prevalence, including Alaska Natives, China, the Gambia and Taiwan (China). Given the low survival rates of hepatocellular carcinoma, the death rate of hepatocellular carcinoma was assumed to be the same as the incidence. The rates were adjusted by the prevalence of HBeAg in each country: populations who were HBeAg positive had six times higher the risk of developing hepatocellular carcinoma. The background all-cause mortality rates were from the life table published in the United Nations World Population Prospects.
, 2019b. For Pneumococcal, efficacy against all serotypes of pneumococcal disease (vaccine type and non-vaccine type) was based on a global meta-analysis by  Lucero et al. , 2004. UNIVAC is not a transmission dynamic model, and thus excludes indirect effects (both positive and negative). This is likely to lead to substantial under-estimates of impact in some countries, particularly for Hib vaccine. More detailed validation against real-world post-introduction evidence of impact is needed. However, the available data in many of the countries included in this desk-based analysis are insufficient to allow validation of modelled estimates (against real-world estimates of post-introduction vaccine impact) and/or parameterisation of a country-specific transmission dynamic model. As such, there is a good deal of uncertainty in the predicted estimates for many countries.
It has been validated against published studies using HPV vaccine economic models set in LMICs  (Jit et al. , 2014). It was also endorsed by the WHO's expert advisory committee, the Immunization and Vaccines Implementation Research Advisory Committee (IVIR-AC) to provide a conservative estimate of the cost effectiveness of vaccinating girls prior to sexual debut. The Excel-based version of the model and documentation are publicly accessible at http://primetool. org/ for use by country programme managers and planners to facilitate country-specific decision-making in LMICs. The R package of the model (prime) has additional functionality such as multiple cohorts and probabilistic sensitivity analysis and is available at https://github. com/lshtmvimc/prime (copy archived at swh:1:rev:0da13630968de0863f38294a1c234c5947baf97e); Abbas and Hadley, 2021.
It can be used for research, global analyses and to generate the vaccine impact estimates used by VIMC. Data inputs include country and age-specific cervical cancer incidence, prevalence, and mortality among females. The model estimates vaccination impact in terms of reduction in age-dependent incidence of cervical cancer and mortality in direct proportion to vaccine efficacy against HPV 16/18, vaccine coverage, and HPV type distribution. It assumes that vaccinating girls prior to infection with HPV types 16 and 18 fully protects them from developing cervical cancer caused by HPV 16 and 18, in accordance with vaccine trials  (Schiller et al. , 2012). The model assumes a two-dose schedule with perfect timeliness at the target ages given in the coverage estimates. Herd effects are not considered meaning that the vaccine impact estimates produced are conservative, although the model can be used in conjunction with transmission dynamic models to project indirect effects.
, 2019). The population is also stratified by age with weekly age classes up to age 3 years, and annual age classes thereafter up to 100 years. The force of infection is calculated by combining an age-dependent social contact matrix from the POLYMOD study  (Mossong et al. , 2008) , demographic distribution for each country, and an estimated probability of transmission per contact. The probability of transmission per contact is then estimated from the basic reproduction number of measles using the principal eigenvalue method. Vaccination is incorporated as a pulse function and can be delivered to any age or range of ages and in either routine or through supplementary immunisation activities (SIAs) or campaigns. The ability of SIAs to reach children who miss routine vaccination is determined using analyses of Demographic and Health Survey (DHS) data  (Portnoy et al.
We assume that both carriers and ill individuals are infectious and can transmit the bacteria to susceptible individuals. The model captures the key features of meningococcal epidemiology, including seasonality, which is implemented by forcing the transmission rate, the extent of which varies stochastically every year. Since only a small proportion of infected individuals develop the invasive disease, diseaseinduced deaths are not included in the model. From each compartment, there is a natural death rate from all causes. Carriage prevalence and disease incidence vary with age, and the model parameterised these distributions using a dataset from  Campagne et al. , 1999 ; the case:carrier ratio consequently varies with age. The duration of 'natural immunity' is an important driver of disease dynamics in the absence of vaccination but good data on this parameter is lacking; instead, prior estimates are used  (Irving et al.
Japanese Encephalitis -National University of Singapore This deterministic dynamic model uses a basic catalytic model for the force of infection (FOI), in which individuals become infected and are then immune. Vaccination is modelled as a removal of susceptibles from the susceptible class. As humans are dead-end hosts for Japanese encephalitis (JE), infection comes from animal reservoirs via mosquitoes. This simple model successfully captures the natural history and transmission dynamics of JE. A systematic review of all published studies and publicly available JE surveillance data was undertaken to collate a dataset of age-stratified case data. The FOI model is fit to age-stratified national surveillance data that were publicly available and data identified via this systematic review of agestratified JE case data  (Quan et al.
, 2020). Data from a total of 10 countries and 17 studies was used, which gave estimates of a wide range of force of infection parameters, as expected for the wide geographical locations. The model is fit in a Bayesian framework using RStan. This gave FOI estimates for all locations in which data is available. For areas in which data was not available we extrapolated from areas in which it was, using the WHO groupings of transmission intensity  (Campbell et al. , 2011). In order to generate uncertainty in the case burden estimates, all model parameters were sampled from the posterior distributions of the parameter estimates. The symptomatic rate was sampled from uniform distribution (0Á002, 0Á004) SAGE Working Group on Japanese encephalitis  (World Health Organization, 2014) , the proportion of these symptomatic cases that died was from uniform distribution (0Á2, 0Á3) and the force of infection from the relevant posterior estimate from the age-stratified case data described above.
JE burden (including cases, deaths, and DALYs) was then estimated from the number of JEV infections. Key sources of uncertainty in our model are the spatial variation in JEV transmission intensity and the proportion of JEV infections that result in either a severe case or death. To identify the areas suitable for sustained JEV transmission, and the size of the population living in at-risk areas, a spatial analysis of the risk factors associated with JEV was conducted. Potential JEV-endemic areas were identified using large-scale spatiotemporal datasets related to suitable climate conditions for the vector species, suitable habitat conditions for the vector, and the presence of potential zoonotic hosts. Transmission was assumed to occur only in areas occupied by the primary vector, Culex tritaeniorhynchus  (Longbottom et al.
, 2017) , or where the annual minimum temperature exceeded 20˚C and annual precipitation exceeded 150 cm. Suitable habitat conditions included areas with rice cultivation or nearby wetlands  (Gumma, 2011). Within these suitable areas, people were considered at risk of infection if the density of domestic pigs or fowl exceeded two per km (with uncertainty represented by varying the animal threshold from 0 to 10 per km)  (Robinson et al. , 2014). Risk maps were validated using seroprevalence and surveillance data. Next, the FOI in each country was estimated from age-specific incidence data using a catalytic model. FOI represents the per-capita rate at which susceptible individuals are infected. Age-specific incidence data was obtained from a literature search, restricted to studies conducted in areas with no history of vaccination (or prior to documented vaccination) to simplify the estimation process.
For several countries where no age-specific incidence data was available, FOI estimates were drawn from the posterior estimate of a neighbouring country. FOI estimates for each study were estimated using a maximum likelihood approach, using the observed numbers of JE cases per age class in each year. Study-specific FOI values were estimated using a Bayesian framework via a Markov chain Monte Carlo (MCMC) approach implemented in the software package STAN. The probability of asymptomatic infection and the case fatality ratio for symptomatic infections were assumed to be independent of the FOI. The annual number of JEV infections for a given study area were then calculated from the FOI estimate and the size of the at-risk population. In the absence of vaccination, the number of infections in age class was calculated by multiplying the age-specific probability of infection by the number of at-risk individuals in the age class.
Variables considered for inclusion were: under five mortality rates (World Bank, 2021), gross domestic product (GDP) per capita (World Bank, 2021), total GDP (World Bank, 2021), region, sub-region, birthrate (World Population Prospects, 2019), life expectancy (World Population Prospects, 2019), and percent of the population living in a rural setting  (World Bank, 2021). The linear regression model was fit using a training (80%) and validation (20%) data set, with the optimal model for each country being selected to optimize the correlation accuracy and the mean absolute percent error (MAPE). The basic reproduction number was calculated by dividing the life expectancy for each country (World Bank, 2021) by the fitted average age of severe infection. To account for uncertainty, we generated 200 parameter sets by uniformly sampling from the published range of vaccine immunogenicity and the 95% confidence interval of the regression models estimated mean age of infection for each country.
Contact is described using the following matrix of 'Who Acquires Infection From Whom': b 1 0:7b 2 0:7b 2 b 2 The effective contact rate differs between <13 and !13 year olds, with its relative size based on contact survey data  (Mossong et al. , 2008). b 1 and b 2 are calculated from the average force of infection in <13 and !13 year olds, estimated from age-stratified rubella seroprevalence data, which had been collected before rubella containing vaccine (RCV) was introduced  (Vynnycky et al. , 2016b). Seroprevalence data were available for 28 countries (see  Vynnycky et al. , 2019). For countries lacking seroprevalence data, we used data from countries in the same WHO region  (Vynnycky et al. , 2016b; Vynnycky et al. , 2019). Confidence intervals (CI) on the force of infection were calculated using 1000 bootstrap-derived-seroprevalence datasets  (Vynnycky et al.
A generalised linear model, based on environmental covariates, is informed by presence/absence of yellow fever reports between 1984 and 2019 at province level. Reports of yellow fever are based on outbreak reports published by the WHO and on cases reported in the Yellow Fever Surveillance Database (YFSD) managed by WHO-AFRO, to which 21 countries in West and Central Africa contribute, and reports from the Brazilian Ministry of Health as well as  PAHO (World Health Organization, 2021a , World Health Organization, 2021b). The environmental covariates were revisited since the initial 2014 model version and now include substantially updated datasets. Covariates include nonhuman primate species occurrence, vector occurrence, temperature, land cover type and altitude  (Fick and Hijmans, 2017; Kraemer et al.
VIMC is jointly funded by  Gavi , the  Vaccine Alliance , and the  Bill and Melinda Gates Foundation (BMGF)  (BMGF grant number:  OPP1157270 / INV-009125 ). Funding from  Gavi  is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper:  Imperial College London, London School of Hygiene and Tropical Medicine , ). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the  UK Medical Research Council and Department for International Development , which supported aspects of VIMC's work (MRC grant number:  MR/R015600/1 ). JHH acknowledges funding from  National Science Foundation Graduate Research Fellowship ;  Richard and Peggy Notebaert Premier Fellowship  from the  University of Notre Dame.