dataesr/scientific-paragraphs-categorization huggingface dataset:
Zheng et al. (2006)  developed a dataset covering 63 stations across the North China Plain and the middle and lower reaches of the Yangtze Plain and reconstructed a drought-flood index series spanning from 137 BCE to 1469 CE. Adamson and Nash (  2014 ) also adopted a five-point index series when reconstructing monsoon precipitation in western India (Fig. 4 ). Where data quality allowed, indices were derived for individual "monsoon months" (May/June, July, August, and September/October) and summed to produce an index value for each entire monsoon season. Where monthly level indices could not be constructed, indices pertaining to the whole monsoon were generated directly from narrative evidence. The five-point index was chosen to correspond to the terminology currently used by the Indian Meteorological Department for their seasonal forecasts (from "deficient" to "excess" rainfall) and regular reports of rainfall conditions (a four-point scale from "scanty" to "excess", with a fifth category "heavy" added by the authors).
Indices of wind direction and velocity If carefully contextualised, information in written records of oceanic weather -especially ships' logbooks and accounts of naval voyages -can be quantified and entered into databases. The Climatological Database for the World's Oceans (CLI-WOC; Fig. 10 ), for example, quantified nearly 300 000 logbooks from 1750 to 1850 CE, and their data are now among 456 million marine reports within the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) (García-  Herrera et al. , 2005b; Koek and Konnen, 2005; García-Herrera et al. , 2006). By using such datasets or by creating databases of their own, scholars have reconstructed aspects of past climate at sea, in many cases verifying or extending reconstructions compiled by scientists using other means. High-resolution reconstructions of regional trends in the frequency of winds from different directions, for example, reveal broadscale atmospheric circulation changes associated with stratovolcanic eruptions, ENSO, the North Atlantic Oscillation (NAO), or the monsoons of the Northern and Southern hemispheres (e.
Climate index development in Australia Australian efforts have largely been based on the Pfister approach (Sect. 8. 1) and regional-scale historical climatology investigations in southern Africa (Sect. 8. 3), although instrumental and documentary sources have been analysed separately. Fenby and Gergis (2013)  and  Gergis and Ashcroft (2013)  converted documentary and instrumental data into a three-point scale of wet, normal, and drought conditions. Historical data availability along with high spatial variability and known non-linearities in Australian rainfall meant that wet and dry conditions were assessed differently. Years were classified as "normal" if they failed to reach either wet or dry criteria. To avoid introducing errors or biases in the record, years with missing data were marked as missing, rather than given a value of zero.
Months of above-average rainfall in coastal New South Wales were identified using the annual rainfall summaries of  Russell (1877) , as this was the only source with consistent yearly information about rainfall events and impacts. Along with specific reports of good rainfall, monthly classifications of wet conditions were also based on accounts of flooding, abundant crops, excellent pasture, and the occurrence of insect plagues  (Fenby and Gergis, 2013). Six months of high rainfall were required for a year (May-April) to be defined as wet. Combining the documentary-based indices with an instrumentally derived index enabled the development of a single index of wet and dry conditions for eastern New South Wales from 1788 to 2008 CE. Each year of the instrumental rainfall datasets -the nine-station network for the Sydney region (1832-1860 CE) and a larger 45-station network representing the wider southeastern Australian region -was assigned an index value of wet (1), normal (0), or dry (-1) based on normalised precipitation anomalies.
, 2014a; Nash et al. , 2016). Calibration and verification of indices in Australia (Fig. 12 ) have been conducted using overlapping and largely independent instrumental data products, similar to approaches used in African reconstructions. In an example of good practice for future studies, independent high-resolution palaeoclimate reconstructions and records of water availability, such as lake levels, were also used for verification  (Gergis and Ashcroft, 2013). Disagreements between these different sources were examined closely and often attributed to spatial variability in individual sources. For example, the 1820s in southeastern Australia were identified as wetter than average in a regional palaeoclimate reconstruction  (Gergis et al. , 2012) , but drier than average in a documentary-derived index and in historical information about water levels in Lake George, New South Wales  (Gergis and Ashcroft, 2013).
This was put down to geographical differences between the datasets -the palaeoclimate reconstruction was biased towards rainfall variability in southern parts of southeastern Australia whereas the lake records and documentary index represented the east. It is a long-standing best practice in marine historical climatology to verify weather observations by comparing different kinds of documentary evidence or alternative different examples of the same evidence (e. g. multiple logbooks in the same fleet). Despite the very real challenges of interpreting measurements even in logbooks, there are indications that reconstructions that use these sources are reliable. There appears to be a high consistency and homogeneity both within wind measurements derived entirely from ships' logbooks, and between such measurements and data obtained   2012 ) is also plotted as anomalies (mm) relative to a 1900-1988 base period.
Note that 1841, 1844, 1846, and 1859 have been classified as wet, in accordance with a rainfall index derived from observations in the Sydney region (blue). Adapted from  Gergis and Ashcroft (2013). from diverse sources that register the marine climate. Therefore, researchers have linked documentary weather observations in, for example, the CLIWOC database, with datasets that homogenise and synthesise evidence from both textual and natural proxies, such as the National Oceanic and Atmospheric Administration's International Comprehensive Ocean-Atmosphere Data Set (ICOADS)  (Jones and Salmon, 2005; Barriopedro et al. , 2014).
The second form of uncertainty relates specifically to index-based climate reconstruction. Where uncertainties can be quantified (either formally with statistics or less formally by comparison with other reconstructions), index-based reconstructions can be made fully comparable to natural proxybased quantitative reconstructions. One example of this approach is the central Europe temperature series by  Dobrovolný et al. (2010) , the only documentary series used as part of the PAGES 2k Consortium (2013) continent-by-continent temperature reconstruction. Calibrated temperature series from China, including  Zhang (1980)  and R. S. Wang and Wang (1990) , are also incorporated into the PAGES 2k Consortium (2017) community-sourced database of temperaturesensitive proxy records. This review has shown that there are multiple approaches globally to the development and application of indices for historical climate reconstruction.
3 and 8. 2; MdRP, FR, and SW of Sects. 5 and 8. 4; LA and JG of Sects 6 and 8. 5; and DD of Sects. 7 and 8. 6. Competing interests. The authors declare that they have no conflict of interest. Special issue statement. This article is part of the special issue "International methods and comparisons in climate reconstruction and impacts from archives of societies". It is not associated with a conference. Acknowledgements. The authors would like to thank PAGES (Past Global Changes) for supporting the CRIAS working group meetings in Bern (2018) and Leipzig (2019) that led to the conception and subsequent development of this publication, and Lina Lerch (Leipzig) for help with Japanese climate-historical sources. Financial support. The meetings that underpinned this article were supported by PAGES (Past Global Changes).
Background: Polychlorinated biphenyls (PCBs) are a large family of man-made organic, ubiquitous, and persistent contaminants with endocrine-disrupting properties. PCBs have been associated with numerous adverse health effects and were classified as carcinogenic to humans, but their long-term impact on mortality risk in the general population is unknown. Objective: To conduct a systematic review and meta-analysis in order to assess whether background exposure levels of PCBs increase all-cause and cancer-and cardiovascular-specific mortality risk in the general population. Methods: We searched the Pubmed, Web of Science, Cochrane Library, and Embase databases for eligible studies up to 1st of January, 2021. We included cohort and nested-case control studies comparing the lowest vs. the highest background exposure level of PCBs in the general population and reporting data for all-cause mortality and/or cancer-/cardiovascular-specific mortality.
Search strategy We searched the PubMed, Embase, Web of Science, and Cochrane Review databases for eligible studies from inception to 1 st January, 2021 with the main keywords representative of the exposure and the outcomes identified in our PECO statement: (dioxin or dioxins or PCB or PCBs or Polychlorinated biphenyls or TCDD or Tetrachlorodibenzodioxin or 2,3,7,8-Tetrachlorodibenzo-p-dioxin or Tetrachlorodibenzo-p-dioxin) AND (mortality or death or cancer mortality or cardiovascular mortality) AND (cohort or case-control or longitudinal or follow-up) (Supplementary Methods). This meta-analysis was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines (Supplementary Methods)  (Moher et al.
Data extraction The following data were extracted from each study by two investigators (TF and FRM): publication date, study design, country, period of exposure measurement, type of biological sample, number of participants and number of deaths, sex ratio, age of the participants, length of follow-up, doses when available, and risk estimate (HR or OR) and 95% confidence intervals (95%CIs) (Supplementary Table  S1 ). When considered appropriate, authors were contacted directly to gather unpublished data. The most fully adjusted risk estimate reflecting the greatest control of potential confounders was extracted and considered for the meta-analysis.
Quality of studies Quality assessment was conducted for studies included in the metaanalysis using the NTP/OHAT Risk of Bias Rating Tool for human and animal studies (NTP/OHAT (National Toxicology Program/Office of Health Assessment Translation),  2015; Rooney et al. , 2014). This tool evaluates each study based on a set of 7 risk-of-bias questions: -Confounding bias [Key item]: Did the study design or analysis (stratification, regression, matching, inverse probability weighing, etc. ) account for important confounding and modifying variables? -Selection bias: Did selection of study participants result in appropriate comparison groups? -Attrition/exclusion bias: Were outcome data incomplete due to attrition or exclusion from analysis? -Detection bias [Key item]: Can we be confident in the exposure characterization? -Detection bias [Key item]: Can we be confident in the outcome assessment? -Selective reporting bias: Were all measured outcomes reported? -Conflict of interest: Was the study free of support from a company, study author, or other entity having a financial interest in any of the treatments studied? Reviewers chose between low-and high-risk of bias options based on a 4-point scale (definitely low, probably low, probably high, or definitely high risk of bias) for each question.
We then assessed the relationship between PCB exposure and cause-specific mortality risk for cancer and cardiovascular diseases. HRs or RRs were treated as equivalent measures of mortality risk. A Summary Relative Risk (SRR) was calculated using a random-effects model with inverse variance weighting, known as the DerSimonian-Laird method  (DerSimonian and Laird, 1986). Significance was checked by a Z-test (p < 0. 05 was considered statistically significant). An absolute risk difference (RD) was calculated from the two largest Swedish cohorts (n = 69,498 participants with 16,776 deaths) using a baseline mortality (BR) risk of 24. 1% with the following formula: RD = BR×(RR-1). Usually, the most common approach for performing meta-analysis is the frequentist approach, which provides point estimates using observed data and confidence intervals indicating the estimate variability, but there is an implicit postulate implying that there is a singular true value of the parameter.
5), and µNormal (1,1) with a smaller variance  and τ Half-Cauchy (0,0. 5 ). The Half-Cauchy distribution has heavy tails, which ensures to give very high values of τ while assuming that lower values are more likely. The Bayesian approach was conducted using the R package "brms"  (Bürkner, 2017). Subgroup analyses following the frequentist approach were further conducted to explore the source of heterogeneity according to the biological matrix of exposure, the presence of comorbidity at baseline, and according to the country. Additionally, we tested the exclusion of articles based on populations with disease cases diagnosed before study inclusion. Finally, we performed an influence analysis to detect potential studies with a large influence on the overall meta-analysis estimate by omitting one study at a time  (Viechtbauer and Cheung, 2010).
Literature search After searching the PubMed, Web of Science, Embase, and Cochrane library databases, 2,132 results were identified, among which 634 duplicates and 1,498 articles not meeting the inclusion criteria were excluded. Based on title and abstract screening, 18 articles concerning PCB and mortality in the general population were included for further consideration. Two articles about foetal death  (Mendola et al. , 1995; Toft et al. , 2010)  were excluded, leading to 16 articles for the narrative review. Eight articles based on overlapping populations  (Ali et al. , 2016; Fry and Power, 2017; Hong et al. , 2012; Høyer et al. , 2002; Kim et al. , 2017; Lee et al. , 2014; Lin et al. , 2012; Roswall et al. , 2018a)  were excluded (Supplementary Table  S2 ). Finally, the present meta-analysis included 8 studies  (Donat-Vargas et al.
For outcome assessment, mortality and cause of death were confirmed using a combination of national registers, clinical records, and autopsy records, leading to a low risk of bias. Additionally, all studies reported no evidence of missing outcome data and incomplete follow-up. For selection bias, studies were rated as "probably low risk of bias" since these studies conducted in prospective cohorts: exposed/non-exposed groups were recruited from the same eligible population, with the same method of ascertainment and inclusion/exclusion criteria and independently from health status. All studies were funded through public funds and no author reported a conflict of interest. Overall, all studies were categorized in Tier 1 (n = 6) or Tier 2 (n = 2), indicating a probably low risk of bias.
This approach has been successfully applied theoretically and experimentally in sandboxes with an analysis of temporal drawdown curves in response to constant-rate pumping  (Mao et al. , 2013b; Zhao et al. 2015). However to date a real field case application following this method has not been presented. Therefore further recommendations have been provided for adapting such process in real applications in  Mao et al. (2013a)  and  Zhao et al. (2015). The major concerns in its application remains effect of noise on the data and the necessity to assess a sufficient amount of information on both the saturated flows (rather horizontal) and the unsaturated flows (rather vertical) in the dataset. Oscillatory pumping tests can improve the quality of hydraulic data and thus the characterization of unconfined aquifers, including the effect of the marginal capillary zone.
sin. π π   = -     (7) where A h is the oscillating response amplitude (m) and P h is the oscillating response phase lag to the signal source (°). These oscillatory parts can be extracted from the head responses through a Fast Fourier Transform (FFT) directly in terms of timeless amplitudes ( A h ) and phases ( P h ). configurations are presented in Table  1  and were chosen mainly according to the UNsaturated SOil hydraulic DAtabase (UNSODA) in  Leij et al. (1996)  and to previous works in the unconfined aquifers literature. 25 % magnitude hysteresis effect in the unsaturated zone, based on the recommendations in  Kool and Parker (1987). Figure  3  presents the differences between our simulated sand and loam soils in terms of unsaturated flows (i. e. effective saturation profiles, water content curves and hysteresis effects on the responses in the saturated zone).
Homogeneous cases applications Inversions have been performed with oscillatory responses generated in homogeneous loams or sands (using property values presented in Table  1 ). For this generation we applied an injection/extraction rate aiming to generate similar pressure amplitudes (10 cm) at the perturbation point in both type of soil (i. e. A Q = 1 mL/s in loam and A Q = 10 mL/s in sand). The generated responses have been noised (2% added noise) for the imaging applications. The hydraulic properties were optimized within two blocks (one 'superficial' block between 0 and 65 cm depth and one 'deep' block between 65 and 100 cm depth). Thus, in our inversions the number of property values to be inverted was m = 6 (2 distributed values for each property) for a dataset composed of n = 7 amplitude/phase responses couples.
It is, in fact, necessary to generate a movement of the saturated/unsaturated interface, in order to generate vertical flows, mainly with a source close to this interface, or at this interface directly (such as tide periodic sources). Mao et al. (2013a)  provided several conditions on the dataset to perform accurate hydraulic tomography of unconfined aquifers. In particular they recommend to measure fluxes in addition to pressure data and to couple different type of data in order to better characterize the heterogeneity of the medium. Ideally, the different data should also identify flow processes in the saturated and the unsaturated zone separately. Coupling geophysical data, allowing to image water content variations in the soil and heterogeneity contrasts, could greatly improve the imaging results.
our zoned inversions the number of property values to be inverted was m = 12 (4 zoned values for each property) for a dataset composed of n = 45 amplitude/phase responses couples (15 responses obtained for each perturbation). We considered a diagonal covariance matrix for C with a 0. 01 variance on each property value. We have tested different combinations of responses generated with lower or higher periods of oscillation (5, 15 or 30 min) in terms of imaging efficiency, and for different heterogeneity configurations (3/4 sand, 3/4 loam and half sand/half loam). The best imaging results obtained are presented in Figure11.
For our zoned inversions the number of property values to be inverted was m = 12 (4 zoned values for each property) for a dataset composed of n = 45 amplitude/phase responses couples (15 responses obtained for each perturbation). We considered a diagonal covariance matrix for C with a 0. 01 variance on each property value. We have tested different combinations of responses generated with lower or higher periods of oscillation (5, 15 or 30 min) in terms of imaging efficiency, and for different heterogeneity configurations (3/4 sand, 3/4 loam and half sand/half loam). The best imaging results obtained are presented in Figure11.
Literature review Many previous studies have assessed the environmental and operational efficiency of oil & gas companies. Using the Data Envelopment Analysis (DEA),  Thompson et al. (1992)  studied the efficiency of 45 independent oil & gas companies during the period 1980-1986, equipped with the principles of assurance region. They show that the efficiency measures had different characteristics during the period 1980-1982 compared to the period  1983 -1986. Sueyoshi and Goto (2012b)  proposed a nonradial DEA model including unified output for desirable and undesirable production unification. This DEA model is reformulated for the environmental evaluation. They applied the model to a dataset including international oil companies (IOC) and national oil companies (NOC) and compared the efficiency between the two groups.
The results showed that in terms of environmental efficiency, IOCs outperform NOCs, while NOCs outperform IOCs in terms of operational efficiency. Using the dataset including IOC and NOC,  Sueyoshi and Goto (2012a)  measured the returns to scale of oil companies and damage to scale. The authors proposed two alternative strategies for oil companies to reduce the CO2 emissions related to their operations. In order to measure two types efficiency, Sueyoshi and Wang (2014) adopted a DEA models for a sample of integrated and independent oil companies in U. S. The GHG emissions adopted as an undesirable output. Their results affirmed that integrated companies outperformed independent companies following their longer supply chain. Their results revealed that the longer supply chain system enhanced company sustainability.
However, the deterministic parametric approach has been proposed by some research as an alternative methodology  (Du et al. , 2016a; De Clercq et al. , 2019)  to overcome the above-mentioned limitations. Among research that adopted the SFA method for the production efficiency evaluation, the current methods developed by  Battese and Coelli (1995)  make it possible to overestimate the term of inefficiency, which leads to a distortion between the estimated efficiency results and the actual situations. However,  Greene (2004 Greene ( , 2005a,b) ,b)  focused on the heterogeneity impact on the efficiency measurement. Greene (2004)  studied the health care service efficiency of 191 countries using the World Health Organization panel dataset, and showed that it is interesting to distinguish between inefficiency and heterogeneity.
Data and statistical description The data used in this research comprises 45 oil & gas companies in the US energy sector. All of them were included in the Thomson Financial Database for the time period 2000-2018. This research adopts one desirable output, two inputs, and one undesirable output for the true fixed effect model application (see Table  1 ). The undesirable output is the amount of CO2 emissions from the production and exploration sectors. This study evaluates the environmental efficiency using CO2 emissions as an undesirable output, and the operational efficiency using the operational revenue as a desirable output. This paper adopts the number of employees and the operating expenses as the indicators of labor and capital inputs, respectively (see Table  1 ). The operational revenue is used as the desirable output index, the undesirable output is the amount of CO2 emissions  (Mrabet and Jarboui, 2017).