dataesr/scientific-paragraphs-categorization huggingface dataset:
Underwater Cultural Heritage Preservation Status The acoustic data parameterization that derived from the TargAn software proved highly efficient in the assessment of the submerged archaeological features' preservation status. The assessment analysis of the conical rubble structures showed that the bigger the distance from the modern harbor the better they were preserved. Modern interventions by the port authorities the recent years and after the modernization of the harbour commercial zone have affected their original height and morphology, while some conical rubble structures have been deliberately destroyed to facilitate the navigation towards the entrance of the modern harbor  [6]. Moreover, to enter the modern harbor facilities the vessels occasionally still cross on top of the structures whose original depth, comparing to the ones that are well preserved, should have probably ranged between -3.
Conclusions The present marine geological survey offered valuable data in order to advance the ongoing systematic underwater and coastal archaeological research and open a new interdisciplinary dialogue. This was achieved through the use of a non-intrusive downscale approach for the mapping and detection of the submerged ancient structures which requires the combined use of modern marine geophysics (side-scan sonar, sub-bottom profiler, multibeam echo-sounder), automatic seafloor segmentation software, and photogrammetric implications through the use of ROV. The use of this methodological approach proved successful in identifying geomorphological features (i. e. , faults, sediment thickness, seabed bathymetry). The whole extent of the submerged and semi-buried archaeological site was delimited using the collected acoustic data while automatic seafloor segmentation techniques were used to detect the submerged harbour facilities (conical rubble structures and breakwaters) in detail while revealing a previously unknown underwater area that contains archaeological remains.
The submerged harbor facilities' spatial planning analysis revealed the advanced harbour engineering plan, unique in the Greek world, that offered multiple and controlled passages to the ancient harbours' basins. This strongly indicates that a hydrographic survey preceded the construction of the harbor facilities by the ancient harbour engineers. The parameterization and morphometric analysis (geometric characteristics and depth distribution of the structures, burial depth) of the submerged harbor facilities' (conical rubble structures) acoustic data showed that their use to prevent enemies from entering the harbors (shielding) but also as submerged breakwaters (sheltering) could be two possible functional scenarios. However, this remains to be verified by the study of the morphology and the dating of the conical rubble structures complex by underwater archaeological survey and excavation, as well as wave modelling that will use the current seafloor bathymetry as input.
Acknowledgements We are very grateful to many friends and colleagues for discussions and various help, including  Yuri Demindenko ,  Evgeny Giria ,  Brad Gravina ,  Anton Lada ,  Sergei Lisitsyn  and  Alexander Otcherednoy. Needless  to say, they may or may not agree with our conclusions. We are also thankful to  Jesse Davies  and  Craig Williams  for the help with the illustrations and figures. Ekaterina Petrova  kindly helped with ID'ing some of the sampled bones. We thank the staff of the  Oxford Radiocarbon Accelerator Unit at the University of Oxford  for their support with the chemical preparation and the measurement of the samples. We are also grateful to the three anonymous reviewers for their thoughtful and constructive comments, which helped improve the paper. This paper is a contribution to  Leverhulme Trust  project  RPG-2012-800.
Acknowledgements We are grateful to all the researchers that supported and advised us during this investigation, and in particular  Nicolas Goepfert ,  Véronique Darras ,  Valentine Roux ,  Belkys Gutiérrez ,  Segundo Vásquez ,  Sumru Aricanli ,  Juan Villela ,  Jefrin Ascensio ,  Gianina Comeca  and  Helen Chavarria. This study was carried out as part of  Alicia Espinosa PhD  sponsored.
6 mm yr -1 ). The conventional accelerator mass spectrometry (AMS) 14 C measurements were performed using mollusk shells (Cerastoderma glaucum) on eight control points for GEM3 (Table  1 ) and seven for GEM4 (Table  2 ). Taking into account both the radiocarbon and 210 Pb ex dates, the local 14 C reservoir age in the Ghar El Meleh lagoon was determined. According to the method of  Sabatier et al. (2010) , the evaluation of the modern 14 C reservoir age was conducted by comparing an age obtained from 137 Cs   and 210 Pb data and from geochemical analysis of miningcontaminated lagoonal sediments with an AMS 14 C age of a pre-bomb mollusk shell. According to  Reimer et al. (2013) , the sea surface reservoir age R(t) for the recent shell (Sac A44506) was measured by subtracting the atmospheric 14 C value determined for the historical date 1845 CE (114 ± 8 14 C years) from the measured apparent 14 C ages of the shell (450 ± 30 14 C years; Table  3 ).
Moreover, the highest contents of Ti (> 1400 ppm) and Fe (> 17 500 ppm) are retrieved in sediment from the watershed of the Medjerda (Fig. 7a ). To make our interpretations more vigorous, a tree diagram was generated using the statistical program XL-STAT 2021, which is used as an additional tool to identify and test the statistical link between all the elements and the deposits using both sedimentological data and XRF data of surface sediments in the study area (Fig. 7b ). In the first cluster, the association of the coarse fraction (sand) with the Si is clear, suggesting that the silicone is coming from coarse marine sand inputs. However, the second cluster determines an assembly between the terrigenous elements (Ti, Fe, Sr, and Ca) and fine fractions (silt and sand). This difference in the origin of the terrigenous inputs in Ghar El Meleh lagoon is explained by the fact that, during flood events, finer sediments are coming from the Medjerda watershed, whereas, at the time of marine storms, coarse marine sand inputs are from the barrier.
In coastal environments, the principal component analysis (PCA) was usually performed on the sediment sampled around lagoons in order to characterize the different sources of sediments deposited in the lagoon  (Degeai et al. , 2015; Gaceur et al. , 2017; Affouri et al. , 2017; Khalfaoui et al. , 2019)  and to determine the several end-members related to potential sediment source supplies (Fig. 8 ). We choose the Mn, Ti, Zn, Ba, Rb, Fe, Sr, Ca, and Si elements due to their good detection by the mobile XRF. We established the calculation factors F1 61. 12 % and F2 11. 13 % of the geochemical dataset using the XLSTAT-2016 statistical software. The two first factorial factors represented in the PCA diagram present (Fig. 8 ) 72. 25 % of the entire variance in the dataset. Factor 1 accounts for 61.
Acknowledgements. The authors would like to thank the  Paris Saclay University (French Atomic Energy Commission)  and especially the  Laboratoire de Mesure   14 C (LMC14 ) ARTEMIS at the  CEA  for the 14 C analyses. We are grateful for the projects  MIS-TRALS PALEOMEX , the  PHC-UTIQUE  no. 14G1002 , and the MEDYNA FP7-IRSES 2014-2017 for their financial support. We would also like to thank  Radewane Hout  for his help in the achievement of some figures. Financial support. We are grateful to  Ministry of Higher Education and Scientific research of Tunisia and "Ecole doctorale Sciences Fondamentales de la Facultée des Sciences de Sfax"  for financial support. This work was financially supported by the  French-Tunisian  joint project  PHC-Utique  (Partenariats Hubert Curien no. 14G1002 ). Financial support was also provided by the  ME-DYNA FP7-IRSES 2014-2017.
Code availability. The code used in this paper is available at https://doi. org/10. 5281/zenodo. 5744957 (Kohlia et al. , 2021). Data availability. The survey datasets used in this article are available open-access on Zenodo. Please find the data at https://doi. org/10. 5281/zenodo. 5744957 (Kohila et al. , 2021). Author contributions. BSK has performed the granulometric and geochemical analyses. BSK prepared the paper with contributions from all co-authors (LD, SB, TM, and NK).
Participants and procedure One thousand four persons agreed to participate in the study. Among them, were excluded those reporting missing data and under the age of 18. The final sample was composed of 793 participants (613 women, 178 men and 2 persons who have a gender identity other than male or female) aged between 18 and 77 years old (M = 33. 75, SD = 14. 70). All participants were francophone: 463 were French, 264 were Belgian, 20 were Swiss and 46 had another nationality. Regarding the highest degree completed, one person had no primary education, 253 had a high school degree, 285 had a university short cycle degree (two or three years), 207 had a university long cycle degree (four or five years) and 47 had a doctorate. Finally, 89% had a Facebook account (N = 703), 63% had an Instagram account (N = 502), 38% had a Twitter account (N = 300) and 15% had a TikTok account (N = 121).
An anonymous online survey was created using the Qualtrics Survey Software. Participants were recruited through academic mailing lists from social science, which explains the large proportion of women and academic people in the sample. Before completing the measures, all participants signed an informed consent form and accepted voluntary to take part in this research. Data collection was carried out from 7th April 2020 to 16th April 2020. Measures reported in the present study are part of a larger questionnaire; all data are available in OSF (Open Science Framework) at: https://osf. io/s5mjx/.
Preliminary analyses An exploratory analysis of the data is available in OSF at: https://osf. io/fe4pn/. Four paired samples T-Tests have been also carried out between the overall SNS use before the quarantine measures and during the quarantine measures. Results showed that the overall use have increased during the quarantine for all SNSs, and in particular for TikTok: Facebook (t (702) = 11. 84, p <. 001, d =. 45), Instagram (t (501) = 6. 33, p <. 001, d =. 28), Twitter (t (299) = 4. 02, p <. 001, d =. 23) and TikTok (t (120) = 10. 31, p <. 001, d =. 94). Finally, correlations between overall SNS use during quarantine and motivations to use SNSs are presented in Table  1.
06 for satisfaction with life; p =. 056 for positive affect). In other words, results showed that actively using Twitter was associated with more social support, and that using passively Twitter was associated with less upward social comparison. In addition, social support mediated the relation between using actively Twitter and satisfaction with life, and social comparison mediated the relation between passively using Twitter and negative affect. TikTok. All standardized items loadings were significant (p <. 05) and exceeded. 4, except one item of the social support construct (. 24). The results also revealed that the model fits the data well: χ 2 (227, N = 121) = 227. 034, p >. 05; SRMR =. 084; RMSEA =. 001; CFI = 1. 000; TLI = 1. 000. As shown in Fig  4  and inconsistent with hypothesis 3, direct paths from actively and passively using TikTok to satisfaction with life, positive affect and negative affect were nonsignificant (p >.
ACKNOWLEDGEMENTS This work was supported by the  Malaysian Ministry of Higher Education  under Grant  Fundamental Research Grant Scheme (FRGS)  'Towards a model of concerted and participative food heritage touristic valorization process:  Kelabit indigenous community, Sarawak'  ( FRGS/1/2015/SS06/TAYLOR/03/1 ). We would like to thank the participants from  Kelabit Highlands  for their warm hospitality and for taking the time to share their experiences.
Acknowledgements This research was conducted as part of the  TUBITAK-CNRS  bilateral cooperation with the grant number of 114Y723 during 2015-2017. The researches were further funded by  ECCOREV (CNRS  ( ACIGÖL  project), the  LABEX OT-MED  ( Bilat  project) and by the  ANR  ( MRSEI, ACIGÖL  project). The long coring of Acıgöl (core 3) was funded by  ALKİM Company due  to the Acıgöl Drilling Project signed between  Cahit Helvacı  ( DEU ) and the  ALKİM and SODAS Companies. We are grateful to the companies of ALKİM and SODAS, particularly to the courtesy of their respective owner and  Mr Cihat Kora  who permitted us to access and work on the Acıgöl Core-3. Moreover,  Mr Hüseyin Ünlü , the general director of ALKİM Company during the coring,  Mr. Ünal Arık  director of ALKİM and  Mr. Mahmut Eser , the correspondent of the core is greatly appreciated as well as  Mr.
Acknowledgements This article is the result of work started several years ago and presented in its different stages at universities in Milan, Paris,  Taipei and Tromsø. I would like to thank  Lin Jo-Wang ,  Liu Chang ,  Luther Liu ,  Lu Yaqiao  and  Qiu Yiqin  for comments and data. I am particularly indebted to  Yan Shanshan ,  Zhitang Yang-Drocourt  and  Wei Haley Wei , for their competence, enthusiasm and patience. I also gratefully acknowledge valuable feedback from  Ora Matushansky , Johan.
The search has been run in three electronic databases: Medline (PubMed), Scopus, and PsycINFO with no time limit, in order to ensure that it was as comprehensive as possible (Table  1 ). Studies were selected according to predefined inclusion and exclusion criteria as follows: Inclusion criteria 1. meta-analysis, randomized controlled trial, review, cohort study, open study, descriptive study, expert opinion, concerning conceptualization, and assessment of negative symptoms in subjects with schizophrenia according to the search terms cited in Table  1 ; 2. studies published in English; 3. studies carried out in humans; 4. studies published in journals indexed in Embase or Medline.
SDS has a good inter-rater reliability within research groups, but requires extensive training, the use of different sources of information, and a careful longitudinal clinical evaluation to judge whether the observed negative symptoms are primary or secondary  [14, 32, 34, 36, 38, 44]. The last information is not always available, especially in first episode patients  [14, 34, 36, 44]. To increase the practicability of the DS diagnosis, a proxy  [45] [46] [47]  was developed based on the Brief Psychiatric Rating Scale (BPRS)  [48] , PANSS  [26] , or SANS  [25]. The proxy allows the categorization of a large number of patients included in existing datasets in which the SDS was not used. However, in spite of its good sensitivity and specificity, several concerns on face validity of these measures have been raised  [36, 49].
In clinical trials, as requested by regulatory agencies, in order to evaluate the efficacy of drugs for negative symptoms, other two concepts have been used: "predominant negative symptoms" and "prominent negative symptoms" (Boxes 5 and 6 for criteria). Neither construct included the evaluation of persistence over time of negative symptoms. Box 3. Negative symptoms included in the Schedule for the Deficit Syndrome (SDS): correspondence with the MATRICS domains and assessment procedures  [42]. Three reviews  [4, 14, 36]  analyzed data on "predominant negative symptoms" and only one of these reviews focused on "prominent negative symptoms" too  [36]  (Table  e1 ). These two concepts were also discussed during an international meeting, involving experts in the field, who did not reach an agreement on whether predominant or prominent negative symptoms should be considered in clinical trials  [55]  (Table  e1 ).
18, 19 For this study, we screened Neolithic period human remains from As xıklı Ho ¨yu ¨k (n = 30) and C ¸atalho ¨yu ¨k (n = 60) by shotgun DNA sequencing. Owing to adverse conditions and the antiquity of the material, only n = 8 (26%) and n = 14 (23%) skeletons (all petrous bones), respectively, contained R0. 1% human DNA. These were directly deep sequenced or sequenced after enrichment by whole-genome capture probes, resulting in a total of 22 genomes with 0. 013 to 5. 03 coverage (median = 0. 093 ) (Tables  1  and Z1 ) (tables with the prefix ''Z'' are supplemental data tables, which can be found at Zenodo Data: https://doi. org/10. 5281/zenodo. 4587657). After confirming the authenticity of the data (Figure  S1A  and Table  Z1 ), we combined them with published genomes from Boncuklu Ho ¨yu ¨k (n = 9), Barcın Ho ¨yu ¨k (n = 23), and Tepecik-C ¸iftlik (n = 5)  [20] [21] [22] [23]  (Tables  S1  and Z2 ).
33, 34 Nevertheless, the assemblage of burials within or around domestic structures is expected to carry information about household composition and/or burial practices, and it may shed light on the relative importance of genetic relatedness as an organizing principle within these early Neolithic communities. 4] [5]  The question has remained   Z3 ). The map was created using ArcGIS ProÒ 2. 4. 0 (ArcGIS ProÒ is the intellectual property of Esri and is used herein under license. For more information about EsriÒ software, please visit www. esri. com. Map sources: Esri, USGS, NOAA). (B) Principal components analysis (PCA) plot describing the genetic affinities among ancient populations studied. The genotype of each ancient individual was projected upon the first two PCs calculated using present-day West Eurasians.
The final dataset included a total of 223 pairs of individuals buried within the same sites, who were broadly contemporaneous, and who had sufficient genomic data for reliably inferring genetic relatedness (Tables  S1, S3 , and Z11). Of these, co-burials comprised 32 individuals and 50 pairs, including 2-6 burials associated with the same building or building clusters (i. e. , co-burials). In C ¸atalho ¨yu ¨k and Barcın, co-buried individuals who could be genetically sampled only included subadults. Importantly, all these buildings either had evidence of domestic use (e. g. , hearths) or lacked evidence of systematic non-domestic use (e. g. , use as animal penning), and did not deviate from others of the same layer in terms of structure or elaboration.
A B C D Figure  2. Genetic relatedness estimation among co-buried individuals using genomic data (A) Autosomal kinship coefficients (q) between pairs of individuals calculated using three different software programs. The horizontal black lines indicate expected autosomal q values for first-and second-degree related and unrelated pairs. The high estimates for the As xıklı 128-133 pair may be influenced by inbreeding (STAR Methods). The horizontal colored bars indicate expected q ranges for different degrees of relatedness estimated using simulations with 5,000 SNPs (95% confidence interval). Figure  S4B  presents the same results, where simulations were performed using the same SNP numbers per pair. (B) Autosomal versus X chromosomal kinship coefficients (q) between pairs calculated with NgsRelate.
Thus, as at As xıklı Ho ¨yu ¨k, we could identify close relatives across the majority of individuals (4 out of 5) associated with neighboring building pairs (Figure  2D  and Table  S1 ). The only exception was a perinatal infant (individual ZHAG). Intriguingly, this infant was buried in the same grave with an adult female (individual ZHAF). The infant also shared the woman's mitochondrial haplotype but was closely related to neither the woman nor any other individual studied. Other individuals also lacked close relatives in this dataset.
Data and Code Availability Ancient genome data produced for this study is deposited at the European Nucleotide Archive (ENA) under the accession number PRJEB39316 as BAM files. The computer simulation code used in the study is available at github. com/CompEvoMetu/kinshipsim. Bash scripts and R code used in regular population genetic and statistical analyses are available upon request. The supplemental data tables (identified throughout the text by the prefix Z) are available at Zenodo Data: https://doi. org/10. 5281/zenodo. 4587657.
Evidence on dietary similarity among Neolithic Anatolian households is currently equivocal. A 2015 study reported no dietary differentiation among C ¸atalho ¨yu ¨k co-burials in different buildings. 33 A 2020 study using a wider dataset again from C ¸atalho ¨yu ¨k reported statistically significant differentiation in carbon and nitrogen isotope values among buildings. 34 This same work further reported significant dietary differences among neonates buried in different buildings. Still, possible confounding factors that could influence stable isotope profiles (age and sex for adults, pathological conditions for neonates) were not explicitly controlled for in these analyses and we therefore consider these results as preliminary. There exist additional arguments against the hypothesis that co-burials represent households.
Mitochondrial contamination We calculated mitochondrial DNA (mtDNA) contamination of all samples from As xıklı (n = 8) and C ¸atalho ¨yu ¨k (n = 14) using contamMix (version 1. 0. 10). 142 This method calculates posterior probability of mtDNA contamination using a Bayesian approach. We called a consensus mtDNA sequence for each individual from BAM files using samtools mpileup (version 1. 9)  143  and vcfutils modules. Then, the consensus sequences were added to a set of 311 modern human mtDNA sequences and mapped to these 311 modern human mtDNA sequences. Here, we calculated contamination rates with and without transitions using contamMix. Authenticity was estimated at 3 93% for all 22 libraries (Table  Z1 ). X chromosome contamination X chromosome contamination was estimated for the male individuals from As xıklı (n = 1) and C ¸atalho ¨yu ¨k (n = 4) using ANGSD.
144 e generated a binary chrX BAM file with the following parameters ''-r X:5000000-154900000 -doCounts 1 -iCounts 1 -minMapQ 30 -minQ 30'' for X chromosome positions. Then, we ran the contamination. R script to estimate chrX contamination using Fisher's exact test and the jackknife procedure (Table  Z1 ). Overall evaluation of aDNA authenticity Evaluating the above results together, we confirmed that all n = 22 individuals examined passed at least two of the contamination estimation methods. 108 Given these results, we included all samples in further analyses.
Y chromosome We used the yHaplo program (version 1. 0. 19)  151 to assign Y chromosome haplogroups of one As xıklı and four C ¸atalho ¨yu ¨k male individuals. We genotyped each male individual based on 13,508 ISOGG (International Society of Genetic Genealogy, http://isogg. org, version 11. 04) consortium SNPs, excluding strand-ambiguous SNPs (C/G and A/T) and by randomly choosing one allele for each of 13,508 ISOGG SNPs. We called all single base substitutions using BAM files mapped to hs37d5 and samtools mpileup (version 1. 9)  143  (filtering the sites with a mapping quality and a base quality of lower than 30. We also excluded insertions/deletions and sites that displayed multiple alleles. We observed haplogroup G2a2b in As xıklı33 male individual. Two individuals from C ¸atalho ¨yu ¨k (5357 and 2779) were assigned to haplogroup C1a2 and the remaining two C ¸atalho ¨yu ¨k individuals (1885 and 2033) belonged to haplogroups, G2a2a1 and H3a1, respectively (Table  Z2 ).
Dataset processing Reference SNP datasets We prepared three datasets by merging the ancient genomes generated in this study (n = 22) with published ancient genomes from previous studies (n = 191; Table  Z3 ) and with different datasets of modern-day populations: DS1: The Human Origins SNP Array dataset  25, 139  that includes 594,924 autosomal SNPs (both transitions and transversions) genotyped in 2,730 modern-day individuals from 203 populations. This SNP list was used for PCA and ADMIXTURE analyses. When genotyping using DS1, transitions were included only conditionally (see 'Genotyping' below) to avoid the influence of postmortem damage. DS2: The 1000 Genomes whole genome sequencing dataset (phase 3) 152 comprised of 1,938,919 biallelic autosomal transversion SNPs genotyped in West African Yoruba (YRI) individuals (n = 108) was used to maximize the genetic overlap between ancient samples and reduce the potential effect of post-mortem damage.