dataesr/scientific-paragraphs-categorization huggingface dataset:
The moderating role of perceived usefulness H4 predicts that perceived usefulness will moderate the relationship between guanxi and relationship performance. In the SME client dataset, our findings reveal that perceived usefulness negatively moderates the relationship between guanxi and relationship performance (coeff/se = -0. 111/0. 037, p =. 003; CL LL = [-0. 184, -0. 038]), as shown in Fig. 4 , suggesting the perceived usefulness of AI-assisted smart loan services weakens the relationship between guanxi and relationship performance. In other words, the performance of relationally-based business relationships between banks and their SME clients can be diminished when the transactional mechanism of AI-assisted smart loan services is adopted. However, the banker dataset shows the opposite results.
Limitations and directions for future research Our study has several limitations that future studies could examine further. First, we focused on relationship performance; therefore, future research could include secondary data to measure transactional indicators, such as growth in loan amounts, market share, and profitability. Second, we used a Chinese sample that particularly emphasises the value of guanxi and the appreciation of interpersonal interactions, inter-firm connections, and mutual obligations in building B2B relationships. Therefore, we encourage future researchers to adopt the relationship marketing theory to examine the impact of AI technology on transactional governance relationships. Third, we utilised the Chinese banking industry to examine the impact of guanxi on relationship performance because "bad loans granted to good friends" is a common occurrence in this sector  (Selmier II, 2013, p.
736). Researchers could also examine the impact of AI technology on guanxi in other service sectors. Finally, we collected cross-sectional survey data to test our research hypotheses, so it would be worthwhile for future researchers to collect longitudinal data or employ a qualitative approach to gain more insight. I would try my best to help out the bank's representative when he/she is in need because he/she is a friend of mine. 0. 74 I would consider whether the feelings of the bank's reprehensive would be hurt before I made an important decision. 0. 78 I would try my best to help out the bank's representative when he/she is in need because he/she is a friend of mine. 0. 82 I feel a sense of obligation to the bank's representative for doing him/her a favour. 0. 79 I think that "calling in" favours is part of doing business with the bank's representative.
3 Sample collection Two hundred thirty-eight (238) crocodilian teeth were collected from 16 units of the Shungura Fm aged between ca. 2. 97 Ma and ca. 1. 14 Ma (Tables  1  and S2 , Fig. 2 ). The specimens were purposely collected for destructive analysis during the OGRE field missions in 2013 and 2016. All teeth with a minimum size of 1 cm in height were exhaustively collected (rounded and pointed) from a large part of the Shungura series, each sample corresponding to a single locality (or part of a locality). This sampling strategy allows for exploring the signal yielded by crocodilian teeth in units documenting major environmental transitions. Units K-4 and L-3 did not yield rounded teeth, and no pointed teeth were present in unit L-9. The analyses presented were preferentially conducted on pointed teeth, to build a comparable dataset along the series, as they are most likely to be from piscivorous crocodilians and are particularly linked to aquatic environments.
Results The isotopic composition of crocodilian enamel phosphate and the resulting estimated δ 18 Ow are summarised in Table  1  (full dataset in Table  S2 ) and displayed in Figs. 4  and 8. δ 18 Op values range between 15. 1 ‰ and 22. 9 ‰, while δ 18 Oc values range between -8. 2 ‰ and 1. 2 ‰. The δ 18 Op is not statistically different between round and pointed teeth (ANOVA: F = 1. 136, df= 8, p = 0. 342) (Fig. 4 ). From B-10 to C-8, F-2, G-27/G-28, H-4/H-5, and K-4, the range of δ 18 Op values is greater than 2. 3 ‰; while in the other units F-1, G-3 to G-24, and L-2 to L-9, the range of δ 18 Op values does not or barely exceeds this variation. Minimal δ 18 Op values increase from 15. 3 ‰ in B-10 (2. 97 Ma) to 18. 6 ‰ in L-9 (ca. 1. 14 Ma) (R²=0. 49), corresponding to an increase in δ 18 Ow values from -6.
). This new dataset highlights a large increase in δ 18 Ow values, between 5. 3 ‰ and 6. 4 ‰, from the Pliocene to the present, consistent with other studies in eastern Africa  (Hailemichael et al. , 2002; Levin et al. , 2004). This increase is likely to have resulted from the migration of convergence zones of low air streams affecting the distribution of the monsoons affecting the δ 18 Ow in addition to the resulting scarcity of rainfalls over the Ethiopian Dome. The data point to a main shift in δ 18 Ow between 1. 84 Ma and ca. 1. 34 Ma, slightly later than suggested by studies on paleosols  (Levin et al. , 2011). Contrary to some conclusions based on terrestrial proxies, the δ 18 Op of crocodilian teeth does highlight any major change affecting aquatic environments, rather pointing to the stability of these environments between 2.
97 Ma and ca. 2. 57 Ma. Crocodilian teeth are also abundant in continental series and widely distributed across the globe, notably in the Neogene strata of Africa. Although adapted in the context of the Shungura Fm, the proposed interpretation model can be generalized to comparable paleontological and archaeological sites, especially in other sites in the Turkana Depression but will require sampling as detailed as that done by OGRE in the Shungura Fm. For optimal use of this approach, particularly along a stratigraphic sequence, it is necessary to ensure that temperature changes are limited and do not significantly affect the body temperature of crocodilians. For the same purpose, it is necessary to compare the same taxa throughout the sequence to avoid interspecific variation. Better control of the potential phylogeny-dependent variation of δ 18 Op in the present dataset would benefit from a study on the systematics and temporal distribution of the different crocodilian taxa in the Shungura Fm.
Acknowledgements The authors are indebted to all the people who contributed to the fieldwork in the Shungura Formation as part of the  Omo Group Research Expedition (OGRE , PI:  Jean-Renaud Boisserie ). OGRE corresponding fieldwork seasons were funded notably by the  UMR 7262 PALEVOPRIM (CNRS and University of Poitiers) , the  French Ministry of Europe and Foreign Affairs , the  CNRS (SEEG Shungura) , the  French National Agency for Research , the  Fyssen Foundation , and were logistically supported by the  UAR 3137 CFEE  ( CNRS  and  Ministry of Europe and Foreign Affairs). Fieldwork, sampling material exportation, and destructive analyses of fossil remains were authorized by the  Ethiopian Heritage Authority  (previously ARCCH) within the framework of the OGRE research permit, and greatly facilitated by its staff members.
Acknowledgements The authors thank the 27 members of the panel of experts. SU acknowledges nancial support from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  857287. Sergio Uribe  is member of the BMC Oral Health Editorial Board Authors' contribution RM: Participated in the conception and design of the study, acquisition of data, analysis, and interpretation of data; as well as drafting of the manuscript and its critical revision, and approval of the nal version. SU: Participated in the conception and design of the study, acquisition of data, analysis, and interpretation of data; as well as drafting of the manuscript and its critical revision, and approval of the nal version. RC: Participated in the conception and design of the study, and interpretation of data; as well as drafting of the manuscript and its critical revision, and approval of the nal version.
2010 ) are higher than today, with an estimate of -6. 1 ‰. The δ 13 Cdiet can in turn provide the mean annual precipitation (MAP) with the equation from Kohn The δ 18 OCo3(V-PDB) was converted into δ 18 OCo3(V-SMOW) using the equation from  Coplen et al. (1983) : δ O V-SMOW 18 =1. 03091×δ O V -PDB 18 +30. 91 This was used to calculate the δ 18 Oprecipitation and the mean annual temperature (MAT) detailed as follows. No reliable equation to estimate the δ 18 Oprecipitation based on the δ 18 Oenamel of rhinoceros is available in the literature. Tütken et al. (2006)  tentatively established one, based on a dataset of extant rhinoceros (including zoo specimens) and using converted phosphates values obtained from the carbonates ones. The MATs obtained with this equation are consistently 2-4°C higher (MH pers.
2013; Steuer et al. 2014). The mesowear values observed for P. minutum (mostly 1 or 2) are consistent with browsing but also overlap with mixed-feeding, whereas that for M. paulhiacense (2, 3 and 4) point towards mixed-feeding or grazing  (Rivals et al. 2017). However, a C4-grazing is unlikely based on the isotopic signal (Figure  3 ), the age and the situation of Ulm-Westtangente (C4 scarce or absent in the early Miocene of Germany; Strömberg, 2011). Fewer differences were noted in the microwear pattern of both species (Table  6 ). The slight differences in DMT are rather consistent with the mesowear, and points towards browsing in P. minutum (high values of Asfc correlated with browsing;  Scott et al. 2006) , and mixed-feeding in M. paulhiacense. Outlier in the stable isotope dataset: weaning signal? One tooth of M.
The majority of samples from the LHS plot within the range of ruminant adipose fat (n = 11; 63%), followed by dairy fats (n = 6; 32%). Samples LHS-36-37 originate from the same vessel. Sample LHS-10 falls just outside the ± 1σ standard deviation of the ruminant milk range, possibly representing a mixture of ruminant adipose and milk fats. Within the Mzonjani facies, only one sample, LHS-27, plots in the non-ruminant adipose range (n = 1; 5%). As no modern reference database from sub-Saharan Africa is available, results are compared using the globally applicable Δ 13 C-values (δ 13 C 18:0 -δ 13 C 16:0 ) plotted against δ 13 C 16:0. This allows good comparison of lipids which derive from either mixed C 3 and C 4 or pure C 3 /C 4 sources  (Dunne et al. , 2012). In general, the δ 13 C values of fatty acids reflect the animal diet, including the C 3 and C 4 composition of their respective diets, hence the biosynthetic pathway within organisms  (Stott et al.
The LHS samples are currently under further investigation using an acidified methanol extraction method to examine the vessels that have shown negligible residue, involving further compound-specific isotope analysis and undertaking a general plant and fish marker screening applied to all samples to check for the presence of long-chain ω-(o-alkylphenyl)alkanoic acids (APAAs). The obtained ORA data from LHS confirms the presence of ruminant and non-ruminant carcass fats as well as ruminant dairy fats. It is hence likely that most ruminant adipose samples represent the processing of Ovis/Capra species and domestic cattle (Bos taurus), with possible evidence of yet unknown wild ruminants among the bovid size classes I-III, such as antelopes. Two Mzonjani (LHS-08, LHS-03) and three of the Doornkop samples (LHS-13, LHS-36-37), each representing two vessels, plot within the ± 1σ standard deviation of ruminant dairy.
At the current stage of research, the origin of the non-ruminant fat cannot be examined in further detail. When comparing the vessel profiles of the LHS sherds with the identified lipid contents in this study, no correlation could be observed as suggested by ethnographic observation  (Fowler, 2006). Consequently, ethnographic studies, which focus on the correlation of use and typology e. g. (Fowler, 2006; Huffman, 1972) , should be applied with caution to EIA pottery. However, there seems to be a tendency for ruminant processing in vessels with decoration motif modes D1, D3, and D5 during the Doornkop occupation. In general, larger datasets from lipid residue analysis, especially GC-C-IRMS data, are needed to better evaluate correlations between vessel shape, size, decoration and the use of ceramic vessels.
Conclusion Despite the intense research on early farming societies in southern Africa, conducted over the past decades, little is known about the use, content or purpose of certain vessel types. Our study demonstrates that ORA is a useful method to test assumptions based on ethnoarchaeological and typological approaches. LHS provided the earliest evidence for the processing of dairy products by early farmers in southern Africa. Due to a high percentage of Bantu-speaking people with a lactase deficiency, it is highly likely that the dairy evidence represents secondary milk products, such as sour milk and curds of milk, rather than the consumption of fresh milk. Furthermore, the obtained ORA data from LHS confirms the processing of ruminant carcass fats within both occupation facies, likely representing domestic animal fats, as well as the processing of wild non-ruminant carcass fats within the earlier Mzonjani facies.
Acknowledgements We are grateful to SAHRIS (PermitID: 2830) and  Philipp Hine  for issuing the permit as well as  Thembi Russel  for providing the permit and access to the samples in the Archaeology collection, GAES, at the  University of the Witwatersrand. We are further grateful to  Stephan Woodborne  and  Moshabi Silidi  at  iThemba LABS (Braamfontein, Johannesburg ) for providing help and a workspace for sampling the sherds. We would also like to thank  J. P. Celliers , Director of the  Lydenburg Museum , who arranged access to the site and provided the duiker reference sample and the editorial team from  Southern African Humanities  for reprint permission.
Data Preparation We collected regional death and population counts for 21 European countries by age and sex from the national statistical offices, Eurostat, and the Human Mortality Database  [36]. Since these data show varying age classes, we harmonised them into single-age intervals up to 95+ for all spatial units  [37]. The lowest number of age groups in our input data is sixteen (for Slovakia) and the largest age group that we ungrouped into single ages is fourteen (for Germany, deaths at age 1 to 14). To ensure consistency in area size when selecting spatial units among the 21 countries, we relied on mostly Nomenclature of Territorial Units for Statistics (NUTS) 3 (Czechia, Denmark, France, Italy, Luxembourg, Slovakia, Spain, Sweden) and NUTS 2 levels (Austria, Belgium, Hungary, Iceland, Netherlands, Norway, Portugal, Switzerland, Slovenia, England, Wales).
As exceptions, we used NUTS 1 for Ireland, Northern Ireland, and Scotland; and, for Germany, a national classification ("Raumordnungsregionen"). Minor adjustments were required due to territorial changes over time and data availability issues (see online supplementary Appendix A, Table  1  for details). In total, we analysed 561 harmonised spatial units containing populations ranging from 40,000 (Bornholm, Denmark) to 6,760,000 (Madrid, Spain). Finally, we verified the data quality by comparing our regional data (aggregated at the national level) with those available in the Human Mortality Database. The differences between age-specific death rates calculated from the two data sources are almost nil for ages below 90, and very small for ages upper this limit. Thus, summary measures such as life expectancy at birth correspond to each other.
0. 3  [39]. To identify any spatial clustering of losses of life expectancy, we rely on the Getis-Ord Gi* statistic  [40] , which allows us to locate hot and cold spots, that is, neighbouring areas of high concentration of spatial units with either large or small loss of life expectancy. In practice, Gi* is calculated for all estimated losses of life expectancy in our dataset, and the resultant z-scores and p-values are evaluated within a defined neighbourhood. Here, we used the contiguity edges corners definition of neighbourhood, which specifically considers neighbours to be units that share a boundary, share a node, or overlap. To be a statistically significant hot spot, p. 6 a spatial unit should not only have a high value but also be surrounded by other units with high values. The local sum for a given unit and its neighbours is evaluated against the sum of all spatial units.
Strengths and Limitations This study is the first to use a large set of small territorial units to provide estimates of loss of life expectancy during the COVID-19 pandemic in 2020. The contiguity of the regions investigated has allowed us to accurately identify geographic clusters of elevated mortality. This approach is novel because most previous studies have focused primarily on single-country regions or on regions in various countries with no common borders. Contrary to many other studies on COVID-19-related deaths, we estimated losses of life expectancy using official mortality data routinely collected by vital registration systems, which are less sensitive to reporting delays and misclassification. To verify that each country's sums of its regional data were consistent for all ages, we verified them with data from the Human Mortality Database.
Data and Methods Data for this analysis come from Continuity and Change in Contraceptive Use (CCCU) Study, which was administered online to a national sample of women aged 18-39. To best capture women at risk of pregnancy, the sample only included women who ever had vaginal sex with a man, were not pregnant, and who herself or whose main male sexual partner had not been sterilized. In late 2012, 11,365 women were invited to participate; 6,658 (59 percent) answered the four screening items; 4,634 were eligible and completed the survey. A subsequent survey was conducted with the same women six months later, and 69 percent participated. Women who dropped out were younger (average age 28 rather than 29 among those who participated), less educated (32 percent had a college degree compared to 46 percent among those who stayed), less often White (57 percent vs.
Change in employment status was described using categories: "more work" (transitioning from no job to part-or full-time; or from part-time to full-time) and "less work" (transitioning from a part-or full-time job into unemployment; or from full-time to part-time). The survey did not assess whether women who were not employed had been laid off, were on leave, or were not working by choice. Our analyses also include the baseline characteristics of age, race/ethnicity, education, parity, and the age of the youngest child in the household. Sample distributions of all variables are provided in Table  1. Values are reported at each wave for time variant and at baseline for time invariant ones. We analyzed the data using descriptive statistics and multinomial regression. Firstly, independent variables were tabulated against the two outcome variables.
Acknowledgments The authors would like to thank participants of PAA 2015 Session 120: Fertility Intentions: Causes and Consequences for their comments on an earlier version of the paper. Heini Väisänen  conducted the statistical analysis and wrote the first versions of 'Data and Methods' and 'Results' sections. Rachel K. Jones  is the principal investigator in the research project that collected these data. She wrote the first version of the 'Introduction' section.
There was no conflict of interest. Heini Väisänen  was funded by the  Economic and Social Research Council  [Grant number  ES/J00070/1 ]. The Continuity and Change in Contraceptive Use Study, on which this analysis was based, was supported by  The JPB Foundation. Author Contributions: Both authors contributed to the 'Discussion' section and edited all the sections of the study after putting together the first version of the manuscript. review board of the Guttmacher Institute. The data used in this study will be made publicly available through the  Guttmacher Institute's Center for Population Research Innovation and Dissemination  (http://www. guttmacher. org/popcenter/),tentatively in early 2017.
MATHEMATICAL METHODS Species interactions: Intraspecies parameters across the models are positive-defined and generated with Log-normal distributions with standard deviation of the logarithm σ = 0. 05 (Fig. 2A ,B, 3 top) and σ = 0. 8 (3 bottom, see SI II. F. 1). Interaction matrices A and B of dimension N × N have intraspecies diagonal vectors and Bii. Diagonal and off-diagonal terms are generated from different Log-normal distributions (see SI I). Singlelayer matrices encompassing both positive and negative interactions are generated from Gaussian distributions (see SI III). We explore the effect of varying the mean (Fig. 2A ,B, 3), standard deviation (Fig. 2C ) and connectivity (see SI II. F. 3) of interspecies interactions. Numerical simulations: Numerical simulations are described in detail in SI I and python codes are available at https://github.
ACKNOWLEDGEMENTS The authors thank the members of the  BioDICée team at ISEM  and the members of the  Institut Natura e Teoria en Pireneus (INTP)  for discussions and support throughout the project. G. A. -G. thanks  L. Arola ,  I. Lajaaiti ,  B. Pichon  and  R. Solé  for insight and feedback and  A. Vives  and  J. Leigh  for support on graphical design. Special thanks to  J. G. Cole  and  B. Parham  for inspiration. G. A. -G. was supported by a  2022 postdoctoral fellowship  of the  Fundación Ramón Areces. S. K. was supported by the grant  ANR-18-CE02-0010-01  of the  French National Research Agency ANR  (project  EcoNet ).
Training group VS control group We first focused on the overall (i. e. , irrespective of schooling and living environment) potential training effect among Himba participants by contrasting performance in the training and control group before and after the intervention. For each participant, we calculated the average proportion of correct responses for conflict, no-conflict, and neutral problems, in the pre-and post-intervention blocks. We analysed the data using a Linear Mixed-Effects Model (LMM) on average conflict, noconflict and neutral accuracies with block (pre-VS post-intervention) and group (training VS control) as fixed factors and participants as random effect intercept. We tested the fixed-effects using the Kenward-Roger method that has been shown sufficiently conservative and robust for small sample sizes  (Luke, 2017).
Formal education and living environment effect on training performance Next, we explored the impact of formal education and living environment on the training effect. We analysed the data using a LMM on average conflict items of the trained participants with block (pre-VS post-intervention), formal education (school VS no school) or living environment (town VS village) as fixed factors and participants as random effect intercept. We tested the fixed effects using the Kenward-Roger method. Bayes Factor analysis was used to evaluate the evidence for null effects. Regarding formal education, most reasoners failed to solve conflict problems before the intervention whether they went to school (n = 36, M = 2. 08%, SEM = 1. 17) or not (n = 38, M = 3. 95%, SEM = 2. 10). Both groups improved after the intervention, main effect of block: F(1,72) = 80.