dataesr/scientific-paragraphs-categorization huggingface dataset:
The resulting corrected matrix was used for dimensionality reduction by principal component analysis (prcomp, stats), tSNE (Rtsne, Rtsne, v0. 15) and UMAP (umap, umap, v0. 2. 7. 0). To identify cell type clusters, we used graph-based community detection using the Louvain algorithm implemented by the functions buildSNNGraph and cluster_louvain of the package igraph (v1. 2. 10). Cell type labels were defined by label transfer from the ImmGenData dataset (celldex R package, v1. 6. 0) using the SingleR R package (v1. 10. 0). Doublets were identified and excluded using the scDoubletFinder package (v1. 15. 4). Single-nucleus RNA sequencing: sample preparation, library preparation and sequencing Nuclei isolation was performed as described previously  20  , with the following modifications. ~20mg pulverised frozen liver tissue was dounced ten times with pestle A and ten times with pestle B (Sigma # 8938) in 1ml hypotonic lysis buffer solution B containing 10 mg/ml BSA (Sigma # 126609).
Sample demultiplexing and alignment For handling the demultiplexing and subsequent downstream alignment and read-counting of sci-RNA-seq3 data, we designed a custom Snakemake 21 workflow termed sci-rocket which has been made publicly-available under the MIT licence. (https://github. com/odomlab2/sci-rocket). Raw sequencing data (binary base calls) were converted to paired-end read sequences using bcl2fastq (v2. 20. 0. 422) with the PCR index #1 and PCR index #2 sequences added within the read-name using the following parameters: After sample-demultiplexing, remaining adapter sequences and low-quality bases (≥Q15) were trimmed using fastp (v0. 23. 4)  22. Read-pairs with mates containing fewer than 10 nucleotides after trimming were discarded. Alignment of trimmed reads was performed against GRCm39 (M31) with GENCODE (v31) annotations  23  using STARSolo (v2.
7. 10b)  24  with the following parameters: In addition, indexes of BAM files were generated using sambamba (v1. 0)  25. Briefly, this generated sparse matrices containing the UMI counts for each gene per cellular barcode. For each gene, we counted the total set of UMI of all intronic, exonic and UTR-overlapping reads based on GENCODE (v31) annotation. Reads mapping to multiple genes (multi-mappers) were counted using the Expectation-Maximization (EM) algorithm available within STARSolo. After visual inspection of the sample-wise knee-plots with the STARSolo-designated UMI threshold to distinguish ambient RNA from true cell, we opted to adopt these UMI-thresholds as-is.
Differential expression testing Differential expression analysis of single-cell and single-nucleus RNA-Seq data was performed as a pseud-bulk per individual mouse and using the DESeq2 package  29. To this end, raw read counts for each library were summed up, and genes with fewer than 10 reads per sample were excluded as lowly expressed. Then DESeq2 (v1. 36. 0) was used to compute size factors (estimateSizeFactors function) and to detect differentially expressed genes between XY and XX genotypes with default parameters (DESeq function), separately for the two gonadal groups. Genes were considered differentially expressed at an FDR of 10% (Benjamini-Hochberg correction). To decrease the multiple testing burden, we only test genes on the X-chromosome in this analysis. The single-nucleus RNA-Seq dataset was analyzed in the same way, but separating individual cell types.
Whole-Genome Sequencing: data processing and analysis For the whole genome sequencing data, reads were first trimmed to using Trim Galore and cutadapt (https://github. com/FelixKrueger/TrimGalore) using the options trim_galore --paired --three_prime_clip_R1 1 --three_prime_clip_R2 1 --fastqc --cores 8 --stringency 3. Next, reads were aligned to a GRCm39 in which all SNP positions between C57B6 and CAST/EiJ strains are N-masked (see also Single-cell RNA sequencing: data processing and analysis) using bowtie2 with default options  30. PCR duplicates were deduplicated when they mapped to the exact same positions using the samtools programs collate, fixmate, sort and markup. Finally, for the F1 mouse samples, reads mapping to the C57B6 or CAST/EiJ genomes were assigned to either parental haplotype (or unassigned) using SNPsplit  31.
Acknowledgements We thank all members of the  Odom and Heard labs , the  DKFZ Central Animal Laboratory and Next Generation Sequencing core  facilities. We thank  Arthur Arnold  for discussion and feedback on the manuscript as well as for providing tissue samples and support. This research was financially supported by core funding from the  Helmholtz Association  (to DTO) and EMBL (to EH), a grant from the  European Research Council  ( 788937  to DTO), a grant from the  Wilhelm Sander Stiftung  (to DTO and EH), a  DKFZ   Postdoctoral Fellowship  (to JPC) and state funds approved by the  State Parliament of Baden-Württemberg  for the  Innovation Campus Health + Life Science Alliance Heidelberg Mannheim  (to JvR).
Introduction: An innovative and community-based intervention is implemented in the Guiana Shield to eliminate malaria among people involved in artisanal and small-scale gold mining. The intervention is possible in the field thanks to community health workers (CHWs) who are previously trained to master all intervention's procedures, including training gold miners to treat themselves for malaria. This article describes thus a training-of-trainers (ToT) program for CHWs, as well as the method and results of its evaluation in terms of quality and effectiveness. Methods: A mixed-method case study was implemented in two steps and based on knowledge survey, satisfaction test, observations and semistructured interviews. Quantitative and qualitative data were triangulated. Results: The project team's previous experience and the Guiana Shield countries' commitment to the WHO E-2025 initiative were identified as levers for the quality of the ToT training, while the complexity of the project context was a challenge.
The malakit was composed of self-testing kits with rapid diagnostic tests (RDTs) and self-treatment kits in case of malaria This strategy was evaluated as effective and acceptable by the community, and has been scaled up in Suriname  (16) (17) (18). Started in 2023, another intervention's evaluation study -Curema -expands the foundations of the Malakit project to also include the radical cure of Plasmodium vivax  (19, 20). Curema intervention consists of two modules offered at inclusion sites located in Brazil and Suriname, in resting and logistical places across the border in French Guiana, regularly frequented by people involved in ASGM in French Guiana: the "malakit" module and the "radical cure" module. The latter aims to prevent relapses and thus reduce the number of human hosts capable of transmitting the parasite; asymptomatic individuals at risk of carrying P.
vivax hypnozoites are offered presumptive treatment with chloroquine and aminoquinolines. The intervention is made possible by CHWs, specifically recruited for the Curema project, and working in pairs on the field at the inclusion sites. As part of the Curema project, CHWs are responsible for enrolling participants and providing health education to participants followed by individual training during the inclusion process (Figure  1 ). Furthermore, they carry out collective outreach activities on malaria in the community. Before the launch of the project, the CHWs participated in a training program which enabled them to take part in a bidirectional working space, to master health research procedures, to present information effectively, to lead activities that reinforce participants' learning, and to collaborate on the design of.
Design and development of the training program With the aim of making CHWs able to master all the procedures and tasks they need to carry out, the Curema training program was designed using a training-of-trainers (ToT) model with two components: an initial training and an on-the-job training (Figure  2 ). Adult learning principles were applied to design the training program focusing on practice-based activities to be appropriate for CHWs' needs and to give them the opportunity to practice  (28). To be more effective, and to reach all of the audience, varied activities and methods were implemented mobilizing cognitive, affective, psychomotor learning principles, and the visual, auditory and kinesthetic (VAK) learning model  (29) (30) (31). Moreover, the training program was tailored and centered on CHWs.
Therefore, the training program was conducted in Portuguese using learning tools targeting on an audience with a low level of scholarity. All partners and organizations involved in the Curema project participated in the training program, increasing contributions from all staff and from professionals with different experiences and expertise. Trainers used a horizontal approach to make CHWs feel respected and to make the learning environment safe and supportive. To be more responsive to the needs of the CHWs and the community in the field, a bidirectional approach was used, and CHWs were asked to collaborate in the design of operating tools. The initial training component took place in Paramaribo, Suriname, jointly by the entire team of CHWs both from Suriname and Brazil. Considering the type and number of topics to be addressed, the initial training was developed for three-weeks to allow enough time to ensure an effective knowledge transfer, an exhaustive practice of skills and new procedures, an appropriate adaptation of tools, and a good team and capacity building.
Methods The design of the training evaluation consisted of a mixed-method case study, executed in two steps as shown in Figure  2. Firstly, during the initial training in Paramaribo developed in a classroom environment, and secondly during the on-the-job training during the launch of the intervention on inclusion sites. First step is nurture by quantitative and qualitative methods, while second step correspond to qualitative method. The quantitative component provided computable data on satisfaction, knowledge improvement and practice, while the qualitative component enabled giving context and an in-depth explanation of the quantitative results. Data were collected through knowledge surveys, a satisfaction test, observations, and semi-structured interviews, and analyzed as follows (Table  2 ): The analysis was conducted using a theoretical framework conceptualized for the evaluation of training programs for the control of infectious diseases in cross-border contexts, by the Centre for Infectious Disease Control, National Institute for Public Health of Health of The Netherlands and The EU Healthy Gateways Joint Action  (24).
Ethics Curema protocol was approved by the ethics committees of the countries involved in the project (Brazil: CONEP:5,507,241 and Suriname: CMWO05/22). The evaluation of quality and effectiveness of CHWs' training program is part of the secondary objectives of the Curema protocol. According to the article R1121-1 of the French Public Health Code, the regulatory classification of this evaluation is a "research not involving the human being" (outside the scope of the Loi Jardé or RNIPH) because it "aims to evaluate the methods of practice of healthcare health professionals or teaching practices in the field of health"  (35). A collective oral information was reached out and participants' non-opposition was collected. For semi-structured interviews, consent was requested. The evaluation was conducted in accordance with the principles of the Declaration of Helsinki.
CHWs profile A total of 20 CHWs were invited for the training program, 14 from Suriname employer-organizations and 6 from Brazil employer-organization. The characteristics of the trainees are summarized in Table  3. The majority were women over 40, with Portuguese as their mother tongue. (38). On the other hand, the complexity of Curema project also influenced the training because of a large number of interacting components that are sometimes difficult to align in order to make possible the training program development  (39). In fact, Curema is an international project which means several organizational levels, country-specific features for implementation on the field, communication in different foreign languages depending on the actors, logistical issues linked to differences in bureaucracy and regulatory requirements between countries  (40).
Limits of our study The evaluation was carried out by researchers previously involved in the design, development, and implementation of the training. Despite this could lead to attribution bias, several data sources -both quantitative and qualitative -were used for the evaluation, enabling data triangulation and increasing internal validity. The Kirkpatrick's theoretical framework used recommends to assess effectiveness at 4 levels: reaction, learning, behavior, and system. The higher the impact in terms of effectiveness, the better the achieved the final training outcome  (24). Nevertheless, the assessment at the system level is more challenging and we were unable to evaluate it. A further evaluation of learning transfer to the community at the end of the intervention could be realized by the post-intervention cross-sectional survey and would be very useful.
Training design: a crucial step Developing a high-quality training program demands careful considerations of the learning methods and modules to be designed. We designed the training program on a ToT model based on adult-learning principles. Consequently, the training program contained ample interactive sessions including group discussions, role plays, practical activities, and simulations. This methodology is considered more effective in comparison to traditional teaching approaches, especially among CHWs with poor level of scholarity  (9, 41). Despite complexities, we can affirm that the quality of the training was good and met the needs for the implementation of the Curema intervention in the field. The significant increase in pre-post scores obtained at the knowledge survey suggests the achievement of theorical concepts.
shown training program or recruitment adaptations due to outside forces or made to improve feasibility or engagement  (45, 46). A review by Stirman et al. identified most common reasons intervention adaptation were to address language, cultural differences, literacy, or situational constraints  (47). In our experience, we can argue that adaptive aptitude, embedded in a community-based approach, may have enabled our intervention to be more appropriate, effective, and sustainable by fostering the bidirectional transfer of knowledge, the empowerment of CHWs as a central actor of the intervention, and their engagement in the Curema project. To be appropriate, trainings of the CHWs should take place in their work environment to practice in a real-life situation  (48, 49). Our quantitative and qualitative results suggested that, although many simulations were carried out during the initial training, real practice in the field during on-the-job training permitted CHWs to improve mastery of procedures and to appropriately perform participants' inclusions and education activities regarding malaria.
In this study, we focus on Northwest Iran and exploit a dataset of Rayleigh-wave group-velocity measurements obtained from ambient noise cross-correlations and earthquakes. We build group-velocity maps using the recently developed SOLA Backus-Gilbert linear tomographic scheme as well as the more traditional Fast-marching Surface-wave Tomography method. The SOLA approach produces robust, unbiased local averages of group velocities with detailed information on their local resolution and uncertainty; however, it does not as yet allow ray-path updates in the inversion process. The Fast-marching method, on the other hand, does allow ray-path updates, although it does not provide information on the resolution and uncertainties of the resulting models (at least not without great computational cost) and may suffer from bias due to model regularisation.
, 2017; Zaroli, 2019; Latallerie et al. , 2022). The SOLA method not only produces full resolution and uncertainty information for tomographic models, it also constrains the models to be unbiased, and allows users direct control on the trade-off between resolution and uncertainty. In this study, we apply the SOLA tomographic inversion of  Zaroli (2016)  to Northwest Iran to construct maps of Rayleigh-wave group-velocities, using a dataset of Rayleigh-wave dispersion measurements obtained both from earthquakes and from seismic noise crosscorrelations. We compare the resulting tomographic images with those obtained using the same dataset and parameterisation but applying the Fast-marching surface-wave tomography method of  Rawlinson and Sambridge (2005). We focus on how each method performs in cases of strong vs.
Data Processing and Measurement We measured Rayleigh-wave group velocity dispersion curves on both earthquake recordings and ambient seismic noise cross-correlations in Northwest Iran. We used 55 broad-band and mid-band stations (see Fig. 1b  and Table  S1 ): 32 operated by the Iranian Seismological Center (IRSC, affiliated with the Institute of Geophysics, University of Tehran) and 23 belonging to the International Institute of Earthquake Engineering and Seismology (IIEES, operated by the Iranian National Broadband Seismological Center).
We then visualised the waveforms and retained those with clear dispersed surface-waves. An example is shown in Fig. 2a. We also collected continuous, vertical seismic records dating between January 2013 and December 2015 from 19 of the 55 available broad-band stations. Several of the broadband stations in the IRSC and IIEES networks were deployed after 2015 or at the end of 2014, so did not produce enough continuous data for our study. Moreover, some stations recorded part of the time as short-period stations and part of the time as broadband stations (instrument updates over the network). In some cases, we had insufficient coincident recording between two stations to cross-correlate and produce stable surface waves. We followed the procedures of  Bensen et al. (2007) ,  Lin et al. (2008), and Poli et al.
Tomographic Methods We inverted the group-velocity measurements shown in Fig. 6  to produce maps of group velocities at periods of 10, 20, 30, and 50 s using two different tomographic methods: the Fast-marching surface-wave tomography method of  Rawlinson and Sambridge (2005)  and the SOLA Backus-Gilbert method of  Zaroli (2016)  and  Zaroli et al. (2017). For detailed explanations of the two methods, we refer the reader to these publications. However, since the main objectives of this study are to compare the two methods using an identical dataset and explore their respective advantages and disadvantages, we present below an overview of how each method ad-dresses the forward and inverse aspects of the tomographic problem.
Implementation Details We used the Fast-marching Surface-wave Tomography (FMST) package developed by  Rawlinson and Sambridge (2005)  and the SOLA Backus-Gilbert code developed by  Zaroli (2016)  and  Zaroli et al. (2017)  and adapted to surface-wave tomography by  Latallerie et al. (2022). We parameterised the slowness space in cells of 0. 25 • in latitude and longitude. For the Fast-marching method we selected the values of the damping and smoothing factors of the subspace inversion by examining the trade-offs between data residual and model variance as shown in Fig. 7a, b  (often called L-curves): the chosen values were 5 for the damping factor and 30 for the smoothing factor, each located near the elbow of its L-curve. For the SOLA tomographic method we chose the tar-  get kernels for each cell to be circles whose radii depended on the logarithm of the path density  (Zaroli et al.
, 2017; Latallerie et al. , 2022) : (6) r(ρ) = r max -(r max -r min ) log(ρ -ρ min ) log(ρ max -ρ min ) , where r is the target kernel radius, constrained to lie between r min and r max , and ρ is the path density (sum of the columns of G) whose minimum and maximum values are ρ min and ρ max. We chose r min = 50 km and r max = 250 km, based on the dominant wavelengths and path lengths within the dataset. The path densities and target kernel radii are shown in Fig. 8. We selected the value of the trade-off parameter η between resolution and uncertainty of the SOLA inversion by examining the trade-offs between the average resolution length and the average model uncertainties as shown in Fig. 7c. Fig. S3  of the Supplementary materials show tomographic models, uncertainty maps, and resolution lengths obtained using a range of η values.
Results Figure  10  shows Rayleigh-wave sensitivity kernels as a function of depth at various periods. Figures  11, 12 , 13, and 14 show the group-velocity maps we obtained from our combined noise correlation and earthquake dataset using Fast-marching and SOLA tomographic approaches for periods of 10, 20, 30 and 50 s respectively. The figures also show the SOLA resolution lengths and uncertainties for each period.
Discussion We have constructed a dataset of fundamental mode group-velocity measurements from noise correlations and local/regional earthquakes in Northwest Iran and inverted them with two different techniques -Fastmarching and SOLA Backus-Gilbert -to obtain the group-velocity maps shown in Figs. 11 to 14. In the previous section, we attempted to compare the groupvelocity maps produced by the two techniques to known geological features in the region seen by previous studies. Comparisons between tomographic images are notoriously difficult to make as their resolution and uncertainties differ. In our case, we know the resolution and uncertainties of the SOLA group-velocity map, but not those of the Fast-marching one. We have inferred several smearing artefacts and possible local bias in the Fast-marching maps by singling out regions with poor coverage where there is a convergence of paths, notably in the South Caspian Basin (g and h in Fig.
Conclusion We have assembled a data-set of group-velocity measurements from ambient noise cross-correlations and earthquakes that cover Northwest Iran. Using this dataset, we have produced group-velocity maps using two tomographic techniques: the Fast-marching method of  Rawlinson and Sambridge (2005)  and the SOLA Backus-Gilbert approach of  Zaroli (2016). We have compared them with each other and with known geological features in the region. Thanks to the resolution and uncertainty information provided by the SOLA inversion, we were able to single out robust features of the tomographic maps -for example the high velocities at short period (shallow depth) shown in the Sanandaj-Sirjan Zone and their contrast with the slower velocities of the Zagros Fold and Thrust Belt  (Figs 15 and 16). We were also able to show that the SOLA method allows us to minimise artefacts caused by poor coverage and identify any ones that do remain.
Acknowledgements The authors thank anonymous reviewers for their insightful comments that helped improve the manuscript, as well as the handling editor  Suzan van der Lee. We would like to express our gratitude to  Franck Latallerie  who shared generously his experience in working with the  SOLA Backus-Gilbert  code. We wish to thank  Ramin Movaghari  ( Southern University of Science and Technology, China ) and  Taghi Shirzad  ( Institute of Geophysics, Polish Academy of Sciences, Poland ) for their useful comments and suggestions during the signal processing part of this work. Christophe Zaroli  acknowledges the  High-Performance Computing Center of the University of Strasbourg  for supporting this work by providing scientific support and access to computing resources.