dataesr/scientific-paragraphs-categorization huggingface dataset:
Further to the north, this channel bifurcates into two smaller channels of 100-150 m wide (see Figure  2 ). At the edge of these now buried channels, the top of the point bar deposits were characterized by high concentrations of micro-charcoal pointing towards deliberate firing activity along the banks of the river. Immediately on top of the charcoal, fine-grained sediment points to the infilling of an abandoned channel. At two locations, these micro-charcoal concentrations were used for AMS 14  A more detailed coring dataset and ER profiling was made across the contemporary desert edge around the village of Dayral Barshā. Our results indicate that the location of the transition from desert to Nile floodplain did not change much over the last few thousand years, however, the morphology of this transition did change enormously.
25 The ideal scenario would be to take one site at a time and understand the individual internal dynamics of particular situations, 26 but in the northern Delta, however, the situation is still at an early stage, as this paper will show. el-Khanziri as Pachnemounis from an inscription found there and discussed the identification of sites, provinces and Nile branches. Further survey work by Pascale Ballet and Thomas von der Way 28 and then by the Egypt Exploration Society has shown that the archaeological prospects for the northern Delta are good, in the sense that there are many extant sites worth scientific study. The sites have been under threat since the end of the nineteenth century, however, as many have been levelled or built over (see figure  1 ). Out of 153 "sites" logged by the EES Delta Survey database, that is places designated the name "kom" or "tell" 29 in the areas of Kafr el-Sheikh, Hamul, Biyala and Sidi Salem, 29 % have been levelled, 22 % have been built upon, 28 % mostly in the Hamul/ Biyala area have not been researched, leaving only 21 % with useful scientific data.
There is often too little information until a survey visit is made to a "kom" or "tell" to be certain that it was an older settlement. 30 The sites were collected from the EES database and allocated a status according to whether they had been investigated. After counting, the numbers in each category (leveled, built over, investigated, not investigated), the percentages were calculated. 31 miKHail, 2014. It is possible that an agrarian development of the north Delta began in the Ptolemaic period similar to the settlement "boom" in the west Delta and Fayum during the Ptolemaic period, 32 but there is a limited amount of evidence due, in part, to the relative lack of archaeological work in the Delta in general and a specific lack of documentary material. Where papyri have survived, as at Thmouis in the eastern Delta they have been able to provide precise details about specific periods, in this case the second century A.
Conclusion A stark photograph of the monastery of Saint Damiana around 1903, shows the building standing in a salt-mud flat, with nothing else around it. 85 Flat expanses of water with labyrinthine reed beds of modern Lake Burullus (see figure  7 ), hiding the remnants of ancient sites evoke a desolate marsh environment prone to human interference and natural stress. Much survives worth archaeological investigation but the prioritisation of that work is difficult due to the nature of the sites involved and modern agricultural and urban pressures. Classification of sites and zones of sites as urban, self-sufficient "monasteries"/farmsteads, military/ customs outposts, industrial/warehousing, small scale farms and fisheries shows the diversity of production and activity of the north. The work discussed here presents a small, perhaps imperfect dataset, but set against the framing story of the natural fluvial landscape and from the wider Eastern Mediterranean and North African perspective, it is worth teasing out the strong regional character and cultural context of life in the unique, north Egyptian Delta.
Acknowledgements For consultation I am obliged to  Daniel Stanley  ( Smithsonian Institution, Washington ),  Jürgen Wunderlich  ( University of Frankfort ) and  Penelope Wilson  ( University of Durham ). All mistakes, however, are mine. My thanks also go to the editors of this publication. For the ilustrations, if not specified especially, I am indebted to  Nicola Math ,  Marian Negrete-Martinez  and  Silvia Prell.
Acknowledgements Pierre Zignani , engineer of research at the  CNRS  and chief of the architectural and topographical unit of the USR 3172 of the  CNRS at Karnak , very kindly provided us with a map of the layout of the area from Karnak to Luxor temples, from the cartographic fund of CFEETK. The  SCA  ( Mansour Boraik  and his successors on the site) offered all facilities to conduct the enquiries on the spot. The  Franco Egyptian Centre , through the kindness of its director,  Christophe Thiers , for the  CNRS laboratory , provided us with the very valuable data of its rich archival documentation. Alban-Brice Pimpaud had the kindness to share with us information on the relative levelling in the surroundings of Karnak. Angus Graham would like to thank all those who have contributed to the augering and geophysical programme at  Karnak  ( 2002-09 ) as part of the  Karnak Landand Waterscapes Survey (KLaWS)  especially his co-director Judith Bunbury, and since 2011 all the team of the  Theban Harbours and Waterscapes Survey (THaWS)  and all their colleagues and friends at Karnak who have generously collaborated with them since 2002.
Acknowledgments The authors would like to thank staff members from the  Centre of Archaeological Sciences  as well as the many Geography students and scholars from  KU Leuven  that contributed to this study through field work:  Véronique De Laet ,  Koen D'Haen ,  Bert Dusar ,  David Kaniewski ,  Robin Jolley ,  An Steegen ,  Johan Schuermans ,  Wim Van Dessel ,  Jenny Segers ,  Marlon Pareijn ,  Pieter Van Turnhout ,  Jozefien Hermy ,  Jan Duhayon ,  Iris Deliever ,  Maarten Van Loo  and  Matthias Vanmaercke. The second author received funding from  KU Leuven  through a PhD-scholarship from the  Interfaculty Council for Development Cooperation (IRO). The research fits within the  APLADYN  project funded by the  STEREO II-program of the Belgian Science Policy -project  SR/00/132 , two projects funded by the  Fund for Scientific Research-Flanders  ( FWO: G.
Acknowledgements The research here reported upon was made possible by a  Johannes-Gutenberg research fellowship  at the  Johannes-Gutenberg-Universität Mainz  and by several project grants: the  APLADYN  project funded by the  STEREO II-program of the Belgian Science Policy -project  SR/00/132 , the project  Spatial analysis of the cemeteries of Dayr al-Barshā (Middle Egypt). A Study  of the cultural and environmental context of an archaeological site ( FWO  project  G. 0277. 06 ), Settlement patterns in the greater Dayr al-Barshā region. An archaeological investigation of population dynamics in the northeastern Hare nome  ( FWO  project  G. 0A94. 14 ), and  From Khemenu  to Tjerty. Towards a physical and social geography of a region in pharaonic  Middle Egypt  ( KU Leuven  project  OT/13/042 ).
Acknowledgements I would like to thank  Harco Willems  and  Jan-Michael Dahms  for their invitation to take part in the conference and their patience. I also acknowledge the support of  Jeffrey Spencer  and the  Egypt Exploration Society's Delta Survey  project,  Roger Dickinson  for assistance with the maps and  Dimitrios Grigoropoulos ,  Rebecca Bradshaw ,  Fatma Keshk  and  Hind Ramadan , as well as the  Ministry of State for Antiquities in Egypt and Kafr el-Sheikh office under Gamal Selim  and  Dr Mohamed  abd el Rifaat.
Characteristics of the CMOST microsimulation model We developed a new microsimulation model for CRC, focusing on the natural history as observed by endoscopy on a macroscopic and histological level. The model has been implemented in Matlab as the program Colon Modeling Open Simulation Tool (CMOST). In our model, colorectal cancer may develop either through adenomatous precursors detected by colonoscopy or in a non-adenomatous pathway. Once an adenoma has been transformed into cancer, it can be detected in an asymptomatic state during diagnostic examinations such as endoscopy or when it becomes symptomatic (Fig. 1 ). The pseudocode illustrating how our CMOST microsimulation program works is given in Table  1. In our model, an adenoma develops within one of 13 colon segments (Fig. 2 ). This location remains constant for the lifetime of a lesion affecting both rate of progression as well as accessibility and detection by endoscopic methods such as rectosigmoidoscopy and colonoscopy.
Automated parameter calibration CMOST supports automated calibration of model parameters to meet epidemiological benchmarks regarding the natural history of colorectal cancer. To calibrate our model to the US American population, we used published age-and sex-specific adenoma prevalence rates as benchmarks  [18, [49] [50] [51]. Carcinoma incidence and mortality, as well as separate colon and rectum cancer incidence rates, are modeled according to data from the Surveillance Epidemiology and End Results (SEER) database for 2005-2009  [52]. The stage distributions of symptomatic and asymptomatic cancers also follow published analyses  [11, 53]. Altogether we used 105 benchmarking data points covering various quantities predicted by the model for parameter estimation. A full list of all benchmarks is provided in Additional file 1: Table  S1.
Implementation of CMOST Details of all features of CMOST can be found in the accompanying manual. The software is available under a GNU general public license and can be downloaded at https://gitlab. com/cmostmodel/CMOST. CMOST has been implemented in Matlab®. Time critical calculations were implemented using the Coder module of Matlab, resulting in a 20x improvement in performance. All functionality of CMOST is available via several intuitive graphical user interfaces. All relevant parameters, including values for all variables describing the natural history, specifications for CRC screening, and a screening plan, can be saved and loaded as a settings file. CMOST can be run on a desktop computer and we provide basic support in the form of scripts for running it on LINUX compute clusters. CMOST produces the following output files after each calculation: i) a Matlab data file with the raw computation results, which can be used for further calculations in Matlab; ii) several PDF files containing plots of all relevant variables that describe the prevalence and distribution of adenomas, advanced adenomas, and CRC, relative to the benchmarks used; iii) an Excel file with a summary of the CMOST simulation run.
The accurate determination of the optimal age for reduction in incidence, mortality, or cost per life year gained required calculations on population sizes of up to 10 million. The calculations are repeated for each condition, e. g. , the year of recommended screening colonoscopy. Each of these cases is, in principle, a single processor job. However, in order to effectively handle the memory available on each processor, the calculation on the population of 10 million was subdivided into calculations with 100,000 individuals on a high-performance LINUX computer cluster.
Additional advancements of our model and its implementation include calibration against results of a recently published endoscopic screening trial, which had not been possible at the time of the development of previous models. The transparency of benchmarking and automated calibration of CMOST parameters will facilitate further improvements to the model. Repeated convergence to the same set of parameters for different initial parameter guesses suggests a well-defined optimum in parameter space of CMOST. We believe that many aspects of the CMOST implementation will benefit future users of the tool. CMOST can be run using a graphical user interface, which allows adjustment of all relevant parameters. Time critical routines are accelerated using the coder option of Matlab, with a 20x improvement in performance.
A simulation of 100,000 individuals implemented in Matlab R2015 and executed on a 2. 5 GHz processor, uses 1 GB RAM and typically finishes in less than 1 min. In addition, CMOST supports usage of a high-performance compute cluster for either the simulation of large populations or detailed explorations. There is no agreement as to what level of detail is necessary for a CRC microsimulation to be both accurate and practical. We attempted to implement CMOST as a detailed microsimulation. For instance, 13 different locations of a lesion within the colon are supported and many details of CRC pathogenesis and screening can be adjusted according to these locations. Since the true value (or probability distribution) of adenoma dwell times is unknown, we calibrated versions of CMOST with median dwell times of 8, 13, and 19 years (CMOST8, CMOST13, CMOST19).
Acknowledgements The authors would like to thank  Stephan R. Vavricka ,  Christine Manser ,  Luc Biedermann ,  Patric Urfer ,  Roger Wanner , and  Urs Marbet  for stimulating discussions, and help with thorough literature research. We would like to thank  Martin Fox, BSSE Basel  and the management of the Brutus and Euler computer clusters at  ETH Zurich  for technical support.
, 2011). The binding of TDP-43 is also enriched in 3 0 UTRs, and it can regulate APA of its own transcript  (Ratti and Buratti, 2016; Tollervey et al. , 2011) , indicating a possible role for regulating APA of other transcripts. We identified poly(A) sites regulated by TDP-43 in HEK293 cells by 3 0 mRNA sequencing and defined TDP-43 binding sites with individual nucleotide crosslinking and immunoprecipitation (iCLIP). To perform 3 0 end data analysis, we developed expressRNA, a modular bioinformatics research platform that manages data and inter-connects recently developed (expressRNA. apa module, RNAmotifs2) and existing (STAR, DEXSeq) analysis software. The expressRNA. apa module identifies the sites where cleavage and polyadenylation takes place (poly(A) sites), marks and annotates the differentially regulated poly(A) sites, and visualizes binding patterns of RBPs around these sites.
The resulting RNA maps defined the binding positions The expressRNA platform performs analyses of alternative polyadenylation datasets and can include external alternative splicing datasets. The identified or provided regulated features (poly(A) sites, alternative exons) are then combined with RNA protein binding information (iCLIP). Motif analysis is performed with the RNAmotifs2 platform. The results are presented with RNA maps that elucidate position-dependent regulatory mechanisms. where TDP-43 can enhance or repress multiple types of poly(A) sites, and we validated its direct action with a minigene reporter. We demonstrated that the role of TDP-43 can be replaced in this minigene by TIA1, another known splicing regulator, if UG-rich motifs are replaced by UA-rich motifs. To identify enriched clusters of diverse regulatory motifs around the regulated exons or poly(A) sites, we extended and upgraded RNA motifs  (Cereda et al.
Identification and Validation of Poly(A) Sites with expressRNA To study how TDP-43 regulates APA, RNA was isolated from six independent TDP-43 knockdown (KD) and control HEK293 cells. The 3 0 ends of mRNAs were amplified with the QuantSeq Rev 3 0 mRNA sequencing (mRNA-seq) library prep kit (Lexogen), which uses a poly(T) primer to reverse transcribe the mRNAs. The library was sequenced with HiSeq, producing 60-nt single-end reads and 10-nt index reads. For data analysis, we developed the expressRNA web application and analysis platform (Figures  1  and S1B ). The first step of expressRNA is to process and map the 3 0 mRNA-seq data to the genome, classify the sites where cleavage and polyadenylation takes place (poly(A) sites), and identify the differentially regulated poly(A) sites. We first aligned the reads to the hg19 reference genome with STAR  (Dobin et al.
, 2013) , allowing soft clipping from both 5 0 and 3 0 end. Of the total 52. 96 million reads, 54. 83% aligned uniquely to the human genome (Table  S1 ). To construct the database of identified poly(A) sites, we considered sequence data from all experiments as one dataset. Some of the aligned reads were soft-clipped due to the sequencing running into the poly(A) tail or imperfect primer annealing (Figure  S2A ). Since the longest 3 0 UTR isoforms are in some cases not fully annotated, we added 5 kb of the intergenic region downstream of each gene. If two genes are closer than 10 kb, only the region up to the middle was added. We found that alternative positions of cleavage and polyadenylation can be clustered in close proximity of a dominant poly(A) site, with most variation occurring within 5 nt of the dominant site, indicating that the cleavage position is not always precise and can vary by a few nucleotides (Figure  S2B ).
This produced an atlas of 30,213 putative poly(A) sites. QuantSeq relies on annealing a poly(T) primer to the poly(A) tail of mRNAs to identify the 3 0 end of the mRNAs. However, as has been shown previously, poly(T) primers often also anneal to internal A-rich sites in mRNAs  (Derti et al. , 2012). Therefore, poly(A) sites with A-tracts in the vicinity  [-10. 10]  were first filtered out. The poly(A) sites were further classified into three classes by using the software poly(A)R  (Akhtar et al. , 2010) , which evaluates the presence of preceding PAS. This identified 17,102 PASstrong, 2,599 PAS-weak, and 10,513 PAS-less sites (Table  S4 ). We examined the nucleotide composition, the efficiency of cleavage, and the level of overlap with two past studies  (Derti et al. , 2012; Gruber et al. , 2012) , which confirms that the PASstrong and PAS-weak sites are the most reliable and efficiently used sites.
Classification and broad identification of poly(A) sites in HEK293 cells has been achieved earlier by a comprehensive analysis of 3 0 end targeted sequencing datasets  (Gruber et al. , 2016). In contrast, the aim of our study is not to further characterize newly identified sites, but rather to use a stringent filtering approach to examine the regulatory patterns at the functional poly(A) sites. We therefore focused only on the PAS-strong and PAS-weak sites, which identified a total of 19,701 poly(A) sites, 16,599 sites were annotated to genes (Ensembl v. 74). To ensure robust analysis, poly(A) sites with less than ten read counts in either control or KD experiments were further filtered out, resulting in 16,221 poly(A) sites. We then identified the poly(A) site in each gene that contained the highest read count, which we consider as the ''major poly(A) site.
Validation of the Poly(A) Sites Comparisons of our 15,113 sites to the published poly(A) database in human tissues  (Derti et al. , 2012)  and HEK293 cells  (Gruber et al. , 2012)  demonstrates that the majority of sites over-lap at nucleotide precision (Figure  2D ). Allowing for up to a 10-nt spacing, approximately 70% of our sites overlap with the sites in  Derti et al. (2012)  and 65% with the previously defined sites in HEK293 cells from  Gruber et al. (2012)  (Figure  2D ). The overlapping sites have the characteristic nucleotide signature of A-rich PAS upstream of the cleavage site, which is followed by T-rich sequences, in agreement with past studies  (Sheets et al. , 1990 ) (Figure  S2F ). A larger number of poly(A) sites were identified in HEK293 cells by a previous study due to the use of milder filtering criteria  (Gruber et al.
RNAmotifs2 Allows Unbiased Discovery of the Regulatory RNA Maps To understand whether the RNA map of APA regulation by TDP-43 can be discovered without any knowledge of its binding specificity, we upgraded our RNAmotifs software  (Cereda et al. , 2014)  so that it could assess regulated poly(A) sites, in addition to alternative exons. Moreover, while the original RNAmotifs could only identify clusters of highly similar motifs around alternative exons, the version (named RNAmotifs2) can identify clusters of diverse motifs enriched around groups of exons or poly(A) sites. This can assess the potential for multiple RBPs to combinatorially regulate pre-mRNA processing. We applied RNAmotifs2 to analysis of the same-exon class of poly(A) sites regulated by TDP-43. The enrichment of the detected significant motif clusters (Fisher's exact test, p < 0.
DISCUSSION In this study, we developed several tools to examine how cis-acting elements recruit RBPs to regulate splicing and APA in a transcriptome-wide manner (Figure  S7 ). We developed expressRNA, a platform that processes 3 0 mRNA sequencing data, classifies the sites where cleavage and polyadenylation takes place (poly(A) sites), and identifies the differentially regulated poly(A) sites. We also integrated the expressRNA platform with an upgraded RNAmotifs2 software to identify enrichment of combinatorial motif clusters around regulated exons or poly(A) sites. We used the motifs and the iCLIP data to define high-resolution RNA maps of APA regulation by TDP-43. This showed that TDP-43 can directly regulate both proximal and distal poly(A) sites of same-exon or skipped classes (Figure  7 , Table  S6 , p value <0.
For the initial step of this kit, oligodT priming, including Illumina-compatible linker sequences, was carried out. The second strand synthesis was followed by purification with magnetic beads. Barcodes were introduced during the PCR amplification step as standard external barcodes. Single-end sequencing (60 nt) was performed on a Illumina GA-2 with a Rapid Run flow-cell. This kit makes use of a custom sequencing primer that anneals to a linker sequence previously introduced in the oligo(dT) priming step for reverse transcription. The obtained reads are strand specific. expressRNA We developed two independent research platforms, expressRNA for computational analysis of post-transcriptional modifications including analysis of 3 0 end sequence data (expressRNA. apa) and RNAmotifs2 for clustered motif analysis (see RNAmotifs2).
The web application part of expressRNA (jQuery and JavaScript) allows the exploration of combined analysis results over an interactive web interface (Figure  1 ). expressRNA supports several open-source and commercial 3 0 end sequencing protocols (Lexogen forward/reverse, 3P-seq, pA-seq, PolyAseq). The platform is modular and scalable and runs on desktop computers for small sequence samples and on multi-core machines for large datasets. It provides a complete analytical framework incorporating several tools for reads alignment, genome annotation, calling of differentially polyadenylated genes, and integration of RNA-protein binding (iCLIP) datasets (Figure  S1 ). We established an online server (http://expressrna. org/paper) to provide interactive browsing of results presented in this publication.
Processing the 3 0 End Sequencing Data We processed each of the 12 experimental datasets (Table  S1 ) by aligning the reads to the reference human genome (hg19) using STAR aligner  (Dobin et al. , 2013)  with default parameters. Tagging only one position per alignment (the first 5 0 aligned nucleotide), we constructed the database of genome-wide polyadenylation events (Figure  2A ). Since internal priming (annealing to the genomic sequence instead of the poly(A) tail) is a major problem in 3 0 end sequencing protocols, we checked the genomic sequence in the region  [-10. 10]  surrounding the polyadenylation events and filtered out alignments containing stretches of six consecutive A or with 70% A coverage in any 10-nt sub-window in this region. Published studies indicate that auxiliary RNA motifs tend to be enriched in the region approximately up to 75 nt upstream (URE) and 50 nt downstream (DRE) of each cleavage site  (Beaudoing et al.