dataesr/scientific-paragraphs-categorization huggingface dataset:
53), p. 53). Not surprisingly, the SMP data fit very well with Kington's daily sea level pressure (SLP) fields. Figure  7  shows SMP pressure data reduced to sea level (using Eq. 6) plotted onto Kington's maps. By 24 December, a depression had arrived from the northwest and soon developed an intense centre that  had moved over the English Channel within days. As the low expanded, all sites recorded a drop in pressure, with Middelburg and Mannheim at 984 and 986. 2 hPa respectively. On 2-3 January, another frontal system arrived in from the Atlantic, pushing against a large high-pressure system centred over Scandinavia, creating a strong pressure gradient over the North Sea that blew gusts of Arctic air over Denmark, Germany, and the Low Countries. According to SMP measurements, the tight gradient ranged from 1000.
Indeed, keeping the usual degree of uncertainty associated with early instrumental measurements in mind, the temperature and pressure SMP data restored in this study are in usable condition. Their overall quality is good, likely due to the SMP's insistence on the use and free dispatch of stan-dardised, comparable instruments. Nevertheless, the series are not free of errors (some more than others). A number of SMP temperature series occasionally showed evidence of the instrument being badly exposed, either indoors or in the sunlight. Some of the pressure series needed to be homogenised, and this could not be done for the Russian data. Nevertheless, the level of consistency among the SMP pressure records is remarkable if compared to similar pan-European datasets for the early instrumental period.
In  Brugnara et al. (2015) , for instance, additional corrections of up to 10 hPa were necessary before synoptic maps for the 1810s could be drawn. Suspicious values were flagged with the C3S QC software, thereby providing an indication of the kind of problem at hand. The SEF files in the database furnish the necessary metadata pertaining to each measurement so that future users of this database can take the specific uncertainties of a given series into account when evaluating any results. Finally, the two examples of extreme weather illustrated the usefulness of the instrumental data recovered in this study. When paired with narrative sources and atmospheric dynamical information, the SMP data can provide in situ, quantitative knowledge about the weather during these extreme events. The daily timescale of these measurement series is particularly important, as the series allow a detailed understanding of the progression and development of the event.
Conclusions The precise correction of pre-industrial meteorological data remains a challenge for climate research; they typically suffer from a lack of uniform procedures and protocols for their recording, meaning that the effort involved to recover, correct, and study them is much greater. These reasons make the data collected by the Societas Meteorologica Palatina even more valuable: their insistence on precise standardised instruments and emphasis on coordinating observations to a common plan mean that historical climatologists and data rescuers can use the database presented in this study with more confidence. We presented a dataset that aims to uncover the historical weather data from the SMP, thereby filling a perceived gap in the research on the rescue of early instrumental observations.
An assessment of the data availability in the Ephemerides revealed that the coverage and resolution vary significantly depending on the year, station, and parameter in question. Our inventory could be enriched and improved by focusing on https://doi. org/10. 5194/cp-17-2361-2021 Clim. Past, 17, 2361-2379, 2021 specific stations or other variables, such as air moisture and rainfall. Additionally, 37 temperature and pressure records were digitised, converted, quality-controlled, homogenised where needed, and formatted into an accessible and standard American Standard Code for Information Interchange (ASCII) format. Their quality is generally quite good in comparison to other early instrumental datasets, although specific uncertainties associated with some of the measurements generate a need for locating and exploring further details regarding the individual stations.
Two case studies highlighted the usefulness of the data when compared with existing research and historical documentary sources. These records have a number of different possible applications for climate research, including their assimilation in reanalysis datasets for use in regional dynamical downscaling studies and their use in the statistical reconstruction of daily fields over Europe with the analogue method. Their usefulness may depend on the specific goals of the study being undertaken, including which focus area and variables are of interest. The potential here is large not only for climate science but for historians as well. The generated time series are of sufficient quality to allow historians to inspect the impact of specific periods of extreme weather on historical events. The weather information uncovered here could be used to study social developments that might have depended on day-to-day weather, or indeed on health and agriculture.
Acknowledgements. This work was supported by the  Swiss National Science Foundation  (project  WeaR , grant no. 188701 ), the  European Research Council (ERC) , and the  European Union 's  Horizon 2020 Research and Innovation programme  (grant no. 787574 ;  PALAEO-RA). Sylvie Jourdain 's work was carried out within the  ANR CHEdaR  project (grant no. ANR-09-CEP-002 ). The work of  Aleksandra Pospieszyńska  and  Rajmund Przybylak  was conducted within the  NCN  project (grant no. DEC-2020/37/B/ST10/00710 ). Financial support. This research has been supported by the  Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung  (grant no. 188701 ), the  H2020 European Research Council  (grant no. 787574 ), the  ANR   CHEdaR  project (grant no. ANR-09-CEP-002 ), and the  NCN  project (no.
Code and data availability. The inventory, data, and relevant code related to this article are available in the Supplement. In addition, the data have been submitted to the Copernicus Climate Change Service Global Land and Marine Observations Database (C3S GLAMOD; https://cds. climate. copernicus. eu, GLAMOD, 2021). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/cp-17-2361-2021-supplement.
This paper presents a complete hybrid numerical methodology for the efficient design and optimization of large-scale Transmit-Array (TA) antennas for modern telecommunication applications. There are four main components to the proposed work and methodology: 1) the implementation through Python scripts of a hybrid scheme based on the Friis analytical formula for linking gain and phase of the primary source and elementary cells of the studied transmit-array ; 2) the implementation of a Particle Swarm Optimizer (PSO) for efficient characterization of the optimal phase distribution on the in-plane lens maximizing the gain of the antenna and minimizing the side-lobe levels for multiple fed TA antennas; 3) the implementation of a full-wave Finite element and Interconnecting domain decomposition (FETI) for the final analysis of the TA radiating performance; 4) the design, optimization, fabrication and proof of concept of an X band transmit-array including the focal source.
This work presents the main functionalities of the hybrid Python/CST tool associated with phase compensation PSO, FETI implementation for transmit-arrays and as an application of this numerical strategy, a new compact unit-cell operating in the X-band (thickness of 3. 2 mm) able to easily generate Phase Rotations (PR) necessary for TAs with phase compensation on the aperture. The proposed unit-cell is a completely symmetric design including a metallic via interconnecting two identical square patches (including a circular hole in the center and a microstrip line) by crossing through a ground plane. A particle swarm optimization (PSO) routine is proposed as a way to quickly optimize the phase distribution of the transmit-array unit-cells. The optimization routine is tested through multiple sources and focal ratios, demonstrating a reduction of over 50% of the volume occupied by the antenna, while keeping a high gain (19.
This work also fails to detail how the phase distribution is optimized for the multiple feed case. The electromagnetic simulation of such large TA antennas is a challenging problem to be solved through Full Wave simulations, since the problem is not periodic and there are no symmetry planes to reduce the size of the problem. In addition, the small size of the unit-cells compared to the wavelength of the incident wave requires a highly detailed mesh for good accuracy. Although it is possible to obtain the antenna performance characteristics through commercially available software such as ANSYS-HFSS  [12]  and CST Microwave Studio  [13] , the memory resources and especially the time required for the simulation are highly prohibitive to the design phase of these antennas. For instance in  [14] , using FEKO's Method of Moments (MoM), a full wave simulation of a 30×30 reflect-array (analogous problem to a TA) in the Ka band takes about 27 hours of CPU time and 29.
e. the coupling i) through the metallic via and directly ii) through the hole (slot) in the ground plane. One of the originalities of the proposed design is the internal feeding of the patch antenna compared to a standard patch excitation technique and the good mastery and comprehension of the impedance matching as explained in section V. The different impedances can be given by the EM simulation softwares (Z ant ,Z line and Z via ). This unit-cell can be modelled as illustrated in Figure  2. The PSO optimization routine is tested through multiple FIGURE  1 : Transmit-array working principle (courtesy of  [16] ) sources and focal ratios, demonstrating a reduction of over 50% of the volume occupied by the antenna, while keeping a high gain (≥ 19. 5) dBi and overall good performance. The first part of this paper will describe the hybrid analytical tool and the PSO optimizer for rapid design and optimization of TAs including the search for the optimal source.
II. HYBRID ANALYTICAL/FULL-WAVE TOOL In order to allow fast simulation of TA antennas, thus making parametric studies possible, a hybrid tool was developed to perform accurate simulations in under 0. 5 seconds. This hybrid tool was proposed at first by  [1]  and developed as a MATLAB routine, and in our work is retrofitted with an object-oriented strategy coded in Python to efficiently design transmit-arrays and obtain their performance during parametric studies. The methodology used in this tool is based on the Friis formula for linking gain and phase of the primary source and the elementary cells characterized initially with full wave simulation tools. In the simulations, the feed is considered to be well suited at the frequency of interest, so no mismatch is considered at this point. The power injected (and therefore radiated) by the feed is noted as P 1.
The simplicity of this method allows for easy adaptation of the routine, therefore making it capable of being applied to multiple transmit-array configurations with very little effort. Furthermore, it does not require differentiability (nor the approximation of derivatives) and it has the natural capacity to avoid local minima by its random movements. Inspired by other array synthesis problems (  [20] ,  [18]  and  [17] ), an optimization module was developed. The goal was to maximize the axis gain, and keep the SLL under a determined threshold level SLL min , thus the cost function was defined as: f (x) = -Gain(θ = 0 • ) + Π(SLL) (13) Π(SLL) = 0 if SLL ≤ SLL min γ|SLL -SLL min | else (14) Where Π(SLL) is a penalty function only applied if the SLL is over the threshold level, with the penalty able to be controlled through the γ parameter.
IV. FETI-2LM FINAL ANALYSIS The final analysis of TA radiating performance can be performed with exact full wave methods. One of the most successful frequency domain computational methods for electromagnetic simulations  [22]  of antennas or microwave circuit engineering applications is the Finite Element Method (FEM). For computationally challenging TA applications especially, the FEM method requires the solution of problems with billions of unknowns. They are of course very difficult to solve with a single computational domain using commercial software such as CST Microwave Studio  [13]  or HFSS  [12] , especially when the problems of interest involve multi-scale geometries, with very small details compared to the wavelength. This is the case for X band or Ka-band transmit-array applications.
As presented previously in section II, it is first necessary, using commercial software such as CST Microwave Studio  [13] , to obtain the gain and phase diagrams of the primary source (making it possible to determine the distribution of the electric field illuminating the array on the primary source side) as well as the unit-cell (allowing evaluation of the radiation performance of the transmit-array). The principle of a transmit-array is to associate with each unit-cell a phase gradient which then allows, once the array has been configured, a zenithal beam angle θ 0 to be obtained when the feed is at the central position (x=0, y=0). Each unit-cell of the TA has been designed to provide a phase correction Φ lens (x, y) at position (x,y) and defined by equation (  2 ). As a result and for the central position of the horn source, the phase at the output of the transmit-array is given by equation (  3 ).
Measurements show that a beam scanning from -22. 5 • to +25 • is achieved with 3 dB scan loss. Table  3  shows the elapsed time of the different phases of the simulation methodology. The simulation time using CST, Hybrid tool and PSO routine are obtained on a standard PC with 1 Intel(R) Xeon(R) CPU E5-1603 @2. 8GHz processor. The FACTOPO simulation used 1153 Intel Xeon 2680v4 core processors. The simulation times demonstrate clearly the efficiency of the hybrid code for fast design of transmitarrays.
Afterwards it is simulated using CST Microwave Studio and the results show a maximal gain of 6 dBi. To properly place the sources, a 2×2 array is designed using coaxial feeding and microstrip lines. The use of patches makes the feeding of the source much easier. A single 50 Ω coaxial cable is required to feed the structure and the power division is realized through power dividers with the microstrip lines, thus making the design simpler, cheaper and lighter. To analyse correctly the Figure  21 , note that it presents the radiation pattern of four patch antennas taking into account the large distance between them (about 5 λ). So, it is not the radiation pattern of an array antenna composed by four elements. It is worth mentioning that the simulations realized with the hybrid code include (in this case) 4 objects of the "primary source" or "feed" type.
Accepted Article Those with mildly elevated liver tests were included as controls if their transient elastography was less than 6 kPa. Cases were defined by 1) clinically evident portal hypertension or decompensated cirrhosis (e. g. , ascites, esophageal varices), 2) Fibroscan stiffness >22kPa if AST <100 IU/L/>32kPa if AST 100-200 IU/L/exclude if AST >200 IU/L, or 3) liver histology (Metavir score of F4) on a previously-performed liver biopsy. Those with other causes of liver disease (e. g. viral hepatitis, hemochromatosis) or with HIV were excluded as described in detail previously  (11). DNA was obtained from blood samples and genotyped on Global Screening Array v1. 0 (Illumina. , 5200 Illumina Way, San Diego, CA 92122). Genotype data were reviewed using the steps detailed in the Supplemental texts.
In brief, using a GWAS data cleaning pipeline, genotyped SNPs were filtered for call rate, violation of the Hardy-Weinberg equilibrium (HWE) and minor allele frequency (MAF). Samples were checked for genotyping rate, sex, relatedness, and European genetic ancestry. PLINK was used to check for discordance between reported and genetic sex, sample relationship was calculated using --genome command and using Pi-hat value, we removed one sample from each pair of related individuals down to second-degree relatives. Genetic ancestry was determined using SNPRelate package using 1000 Genomes Project as reference. Additional genotypes were imputed using the Michigan Imputation Server  (12). Additional details on GWAS data cleaning is available in the Supplement Texts under 'Genetic Data Cleaning' section.
Laboratory of Neurogenetics (LNG) cohort Genotype and phenotype data from 860 heavy-drinking subjects who had given consent as part of two NIH screening/natural history protocols (98-AA-009; 05-AA-0121) were provided by the Laboratory for Neurogenetics (LNG) at the National Institutes on Alcohol Abuse and Alcoholism (NIAAA, Rockville, MD, USA) as additional heavy drinking controls. Participants.
Accepted Article were required to have alcohol consumption of ≥80 grams per day (males) and ≥50 grams per day (females) and excluded if they had a serious medical condition requiring ongoing treatment, including liver disease. Genotype data (Illumina OmniExpress Bead Chip) were cleaned and imputed using the same pipeline used for GenomALC. After filtering, 235 participants meeting the inclusion criteria were included as controls.
GWAS in UK Biobank data The data were analyzed with FaST-LMM (  14 ), a mixed model method that computes a kinship matrix to adjust for relatedness/population stratification and infers any missing genotypes at a SNP based on the genotypes of other samples at that SNP. Cases (231) and drinking controls (8,364) that had all the clinical covariates (age, sex, type 2 diabetes mellitus (T2DM) status, BMI, and current daily alcohol intake (in grams)) were included in a GWAS that mirrored the primary analysis performed in GenomALC cohort. To mirror the GenomALC conditional analysis in the UK Biobank data, cases and drinking controls used above were re-analyzed with.
Gene Ontology based enrichment analysis resultsNumber of known genes in GO (number of genes with annotated function in Gene Ontology database), Number of genes in the list (number of genes from the input list (also see Supplementary Table10) that have the same annotated function from Gene Ontology), Expected (expected number of genes in the list from a random set of genes with same size as input list), +/-(increase/decrease in enrichment), Raw P value (Fisher's exact test based p-value), FDR (false discovery rate, adjusted p-value after random permutation).
Study overview First, a generic partial budget model for the estimation of disease costs was conceptualised and data needs identi ed based on knowledge of the effects of livestock schistosomiasis and variables commonly used in impact studies of livestock disease. Subsequently, protocols were developed for a cross-sectional interview-based survey and focus group discussions with farmers covering questions on knowledge, occurrence and manifestations of livestock schistosomiasis, herd and production data as well as management of livestock and disease. The data collected were analysed and used to develop and parameterise speci c production and partial budget models for the two sites and to de ne scenarios in line with local production and management practices. Secondary data and expert opinion were collated to complement the primary data where needed.
Data collection and analysis From the twelve villages selected from Barkedji and the Lac de Guiers regions, eight of them had participated previously in the ZELS project and four villages (two in each region) were newly recruited. For the cross-sectional survey, questions were encoded in Open Data Kit (ODK) mobile data collection software. The questionnaire covered the following topics: demographics, production and management practices (including disease management and selling of animals and products), impact of livestock deaths on livelihood, prevention behaviour in people and animals, knowledge of disease in humans and livestock, signs of the disease in livestock and equity tool; most questions were closed and a few were open. The full survey questionnaire details are available upon request from the corresponding author(s).
Each survey participant was also asked to complete a table about the number of animals owned per species, age group (young, adult), sex, and breed (local, exotic or cross-bred). The survey was translated from English to French and administered by local enumerators following a training session with the researchers leading the eld work. Farmers who participated in the survey were also invited to participate in focus group discussions (FGDs) to gather data on general signs of animal disease, signs of schistosomiasis in livestock, selling and buying of animals, milk and meat, feed and medicine including prices. All group activities were facilitated by a local enumerator with one person acting as note-taker; the language used was Wolof. The full question guide can be found in supplementary information 1.
Summary notes were generated, and the discussions were recorded in full. The recordings were transcribed and then translated by the Senegalese research collaborators into English. Data were collected in August and September 2019. Upon completion of the survey, data were downloaded from ODK and stored as an Excel le on a safe RVC drive. The tables on livestock numbers were collected as hard copies and manually added to the Excel le using the identi er code given to each participant. The translated transcripts of the FGDs were sent to the research team based at the RVC for storage and analysis.
Data cleaning and analysis Survey data were checked for completeness and cleaned which entailed mainly harmonisation of spelling in open question elds. Answers available in French in the open comment elds were translated to English by the authors and professional translators. Data on the demographics of respondents, knowledge on schistosomiasis and economic impact of the disease were analysed. Microsoft Excel was used to calculate summary statistics and to visualize the data. For uncertain variables (e. g. those with skewed distribution, inconsistent or too few responses) probability distributions were assigned to the input variables. The open questions were read in detail in the search of information that would be relevant for the conceptualisation of the economic models including the de nition of scenarios; relevant information was extracted as summary statements.
For example, some respondents stated that sick animals in the herd will lose value and condition and explained a need to replace them with new ones; this informed the replacement strategy used in building the models. Data about why livestock were kept, milking animals with schistosomiasis, which animals are sold and bought were extracted from individual interviews. All FGDs were analysed for questions on daily feed quantity and type of feed consumed by animals, cost of feed, farmers selling sick animals or not and questions on whether animals with schistosomiasis sell differently. Common topics were identi ed across responses for the FGDs and interviews which were used to inform the structure of the partial budget model and the input variables.