dataesr/scientific-paragraphs-categorization huggingface dataset:
Prediction weights were previously computed based on expression in the dorsolateral prefrontal cortex of ROS/MAP participants with AD, MCI, or healthy controls as obtained from the AMP-AD RNAseq Harmonization Study  [44, 45] , and processed by Bellenguez et al. [46]  We chose this dataset as it includes a relatively large number of samples of a relevant tissue in a population similar to the current study. Prediction quality of GRIN2D was sufficient in this dataset, based on significant variance explained as estimated with cross-validation (5. 2%, p = 3. 6 × 10 -8 ). In total, weights for 13,420 transcripts with nominally significant heritability estimates were available. We next associated the predicted transcripts with non-AD synaptic functioning (PC5) and consequently computed the posterior inclusion probability (PIP), resulting in a credible gene set.
Multiple testing adjustment To strike a balance between reliable inference and power, we present our findings as primary, secondary, and tertiary results. The primary analyses in this study were the GWAS in the full dataset independent of sex. For SNPbased tests, we apply the conventional genome-wide association threshold of p < 5 × 10 -8 , and for gene-based tests, we used Bonferroni's method to adjust for 19,511 genes resulting in a threshold of p < 2. 3 × 10 -6 , as recommended by FUMA. The sex-specific analyses present additional tests of related (and non-independent) hypotheses, and, thus should be regarded as secondary.
CSF biomarker PCs Analogous to our previous study  [3] , the six AD CSF biomarkers tested here could be combined into five consistent components across datasets and analytical subsamples. The PC structure was very similar across the EMIF-AD and ADNI datasets (Additional file 1: Table  S5 ); therefore, all subsequent PC analyses were based on a combined discovery sample to maximize sample size and reduce study heterogeneity. In this study, we extended our analyses to examine whether the CSF biomarker PCs' loadings, their mean levels, or associations with latent AD differ by sex. Generally, PC loadings were consistent across males and females (Table  1 ). NfL loaded 0. 06 higher on tau pathology/degeneration in females when compared to males (0. 25 vs 0. 19). A similar pattern was observed for pTau, which loaded 0.
This comparison revealed that in all but one (i. e. , rs12670437) analyses the statistical support of our top GWAS findings was highly comparable, suggesting that the choice of statistical model for the meta-analyses does not appreciably change our top GWAS findings. functioning and markers in the GRIN2D region. These analyses yielded independent support of the involvement of GRIN2D in AD in many but not all analyses. First, our original GWAS was performed in two independent datasets (EMIF-AD and ADNI) and we note that the GRIN2D signal is quite consistent in both datasets (both in terms of effect size and statistical support; Additional file 1: Table  S9a ). Second, TWAS analyses combining large eQTL (i. e. , brain from ROS/ MAP) and GWAS summary statistics on AD risk and related brain phenotypes, support our conclusion of a relevant association signal in the GRIN2D region and suggest that the molecular effects may be mediated by affecting the expression on GRIN2D (see section " Functional characterization and related phenotypes", Additional file 1: Table  S10 ).
Third, while analyses in the Knight-ADRC dataset revealed no strong association signals between markers in GRIN2D and PC5 (Additional file 1: Table  S9b ), we note that three out of seven top GRIN2D SNPs from our primary analyses (i. e. , all showing P < 1 × 10 -5 in our GWAS) were not available in the Knight-ADRC data and could hence not be tested. Although these (and other) top markers were lacking, we were able to assess local heritability metrics in this region and observed evidence that the remaining markers explain a significant portion of PC5 variance (6. 3%, p = 0. 0002) in the Knight-ADRC data (Additional file 1: Table  S4 ). Furthermore, inspection of all available 228 SNPs in the Knight-ADRC dataset in the general GRIN2D region (i. e. , within the 100-kb interval from chr19: 48,365,921-48,465,818) revealed the strongest association between exons 7 and 12 of the GRIN2D gene, but no other gene in the region (best SNP: rs74459994; P-value = 1.
Comparison to rare variant results In contrast to our previous work based on WES-derived rare variants in a subset of the EMIF-AD dataset analyzed here  [3] , we found no evidence for an association between the analogous CSF biomarker components and common variants in the genes previously highlighted (i. e. , IFFO1, DTNB, NLRC3, SLC22A10, GABBR2, and CASZ). Similarly, combining common SNP effects in gene-based tests did not reveal any significant associations at these loci either (Table  4 ). Together, these results suggest that common variants (MAF ≥ 0. 01) do not appreciably contribute to the rare variant association signals identified earlier by our group.
Besides implying the GRIN2D locus in synaptic functioning, the current study also provides further insights into how other known AD loci may affect disease risk. This was made possible by our multivariate approach which allowed for the quantification and disentanglement of different mediator mechanisms. Specifically, in the mediation analyses, we observed two CSF biomarker profiles associated with AD, which are determined by two different gene sets. The first profile (PC1 and PC2) is characterized by decreased amyloid and increased tau, as well as increased Ng and YKL-40 levels, but not NfL. This component was most strongly associated with SNPs in the APOEregion, in particular the well-known AD risk variant ε4. Our data suggest that the association with this variant may increase AD risk by being a catalyst for amyloid deposition or as inhibitor of amyloid clearance, represented here by the Aβ pathology PC.
Given prior knowledge of the non-specificity of NfL with respect to AD pathogenesis  [6] , we interpret this pattern to represent an independent non-AD-specific neurodegenerative pathway for dementias in general. Genetically, our results suggest that this pathway is not determined by variants in the APOE locus, but instead by variants in TMEM106B and potentially CHI3L1. TMEM106B affects neuronal loss  [54]  and has been convincingly associated with risk for at least two forms of dementias, i. e. , fronto-temporal dementia (FTD)  [54]  and AD  [13, 42, 55]. Here, the lead variant for TMEM106B is rs2302634, which is in perfect LD (r 2 = 1) with the lead variant from our recently published NfLspecific GWAS in the same two datasets (i. e. , rs7797705)  [13]. Both variants are in either perfect (r 2 = 1) or nearperfect (r 2 = 0.
An alternative-and often times equally plausible-interpretation is that the uncovered SNPs affect AD symptoms independently of biomarker levels and that the component associations observed here actually reflect a consequence of AD pathogenesis. While the specificity of the mediation results using certain PCs but not others generally supports the assumed causal directions, longitudinal studies, e. g. , on MCI conversion, are needed to confirm the findings of this arm of our project. Fifth, we note that one of our lead signals, i. e. , the association between the non-AD synaptic functioning PC (mainly driven by Ng levels) and variants in GRIN2D, only showed strong evidence for association in two out of three CSF biomarker datasets. While additional analyses (e. g. , TWAS using several AD-relevant phenotypes, local heritability estimates) generally support the GRIN2D association, this signal should be considered preliminary until assessed in additional datasets of sufficient size.
Availability of data and materials In accordance with EU law and participant privacy, clinical individual-level data from EMIF-AD is not available publicly, but can be obtained via EMIF-AD (https:// emif-catal ogue. eu; http:// www. emif. eu/ about/ emif-ad)  [70]. Registered users can download ADNI data from http:// adni. loni. usc. edu/  [71]. The results published here are in part based on data obtained from the AD Knowledge Portal (https:// adkno wledg eport al. org)  [72]. ROS/MAP predicted gene expression weights can be obtained from https:// doi. org/ 10. 5281/ zenodo. 57459 27  [73]. Analysis code can be found at https:// github. com/ aneum ann-scien ce/ com-mon_ varia nts_ csf_ bioma rkers  [74]. Summary statistics for all GWAS analyses are available for download at URL: https:// doi.
For 4C, we used two different viewpoints from the 5′ part of MNX1 (Supplementary Table  2 ) and identified two predominant interacting regions on chr6, one covering the MYB locus and one covering part of the adjacent AHI1 gene (Fig. 1C  and data not shown). Conversely, reciprocal 4C with the interacting region of MYB as viewpoint (Supplementary Table  2 ) indicated predominant enrichment at MNX1 and the vicinal NOM1 gene (Fig. 1D ). We did not observe, however, reciprocal interaction between the prominent interacting AHI1-exon 20 region (Supplementary Table  2 ) and the MNX1 locus (data not shown). Thus, our reciprocal 4C data indicated chromatin interaction between MNX1 and MYB in GDM-1 and supported our hypothesis of enhancer hijacking as the cause of MNX1 activation. To identify potential enhancers which might be responsible for MNX1 activation in GDM-1, we performed Antibody-guided chromatin tagmentation (ACT) followed by sequencing (ACTseq) to map histone 3 enhancer marks acetylation of lysine 27 (H3K27ac) and mono-methylation of lysine 4 (H3K4me1).
Thus, we suspect that E1 is essential for GDM-1 survival, potentially in regulating MNX1 as a putative oncogene or as a regulator of MYB function. Future experiments with a tagged version on MNX1 might help to overcome this limitation. Taken together, our data supports the notion of an enhancer hijacking event by which TF MNX1 is ectopically activated in the AML cell line GDM-1, and we propose a hematopoietic enhancer, E1, located in AHI1, as being responsible for MNX1 activation. Binding of MNX1 to this enhancer suggests a feedback loop by which MNX1 perpetuates its own expression together with hematopoietic, immunomodulatory and leukemogenic TFs. Our findings in GDM-1 generate a new mechanistic basis to explain the ectopic expression of MNX1 as, for example, seen in t(7;12) pediatric AML  [6, 12].
ACKNOWLEDGEMENTS We thank  Dr. Peter Krijger  from the  University Medical Center Utrecht  for his excellent advice in the use of the pipe4C software. Furthermore, we thank the  Genomics and Proteomics Core Facility  and the Omics IT and Data Management Core Facility of the  DKFZ Heidelberg  for their excellent support in DNA and RNA sequencing and analyses. JH and MH were supported by the  German-Israeli Helmholtz International Research School: Cancer-TRAX  ( HIRS-0003 ), a grant from the  Helmholtz Association's Initiative and Networking Fund. The work was supported in part by the  Helmholtz International Graduate School (AR, MH)  and in part by the  Deutsche Forschungsgemeinschaft (DFG)  funded  Sonderforschungsbereich SFB 1074 (CP, AR) , the  José Carreras Foundation (CP, ES)  and  FOR2674  (CP, AG, DBL).
910 in 2021) and is getting closer to the record (2. 66) from 2019. The fiveyear IF increased to 2. 423 (from 2. 074 last year), which is the highest score in the history of SoSyM. Furthermore, the h-5 Google Scholar ranking places SoSyM at #14 among all conferences and journals related to software engineering and programming languages. Further rankings can be found at https://www. sosym. org/. Over the past year, SoSyM received 374 submissions-a slight decrease when compared to the 420 in 2021, which was the largest number of submissions in SoSyM history. The number of downloads continued to increase over the last 5 years. At the end of 2022, there were 273,171 downloaded SoSyM articles during the calendar year  (compared to 197. 730 in 2021). The acceptance rate in 2022 was atypically high at 37.
Editorial Dear members and readers, JAVMA was first published almost 150 years ago, in 1877, and AJVR over 80 years ago, in 1940. Currently, much of the AVMA's journal content, particularly the historical content before 2000, is unavailable to most members and researchers. For those fortunate enough to be affiliated with a major academic institution that maintains and preserves the backfile content of JAVMA and AJVR in its stacks, this valuable historical data may still be accessible. Many other readers are out of luck. Librarians have long wrestled with how best to fulfill requests for single articles pertinent to a historian's or veterinary scholar's work. Indeed, the University of Pennsylvania has received on average 1 request for an archived article per day for the past 6 years. Retrieving and scanning each article is a laborious task, and one that costs considerable staff time and overhead.
Initially, Erin Eldermire, formerly of the Cornell University Veterinary Library, joined the task force until she left that role in December 2022, to be replaced by Margaret J. Lindem, University of Pennsylvania; Erik Fausak, University of California-Davis; and Howard Rodriguez-Mori, Texas Tech University. The critical need to digitize the AVMA print journals, both for easier access and for preservation, has been discussed within the library community for Meeting monthly, our team has strategically worked through the challenges of inventorying the back issues: we've researched the accessibility of existing digital archives of the journals maintained by HathiTrust and the Internet Archive as well as indexing by CABi and the National Library of Medicine, explored the availability of external funding through foundations, mapped out the cost to convert content to PDF and then create necessary metadata in XML format, and drawn up financial models that might work for librarians and individuals.
To find an archived manuscript, you can visit https://www. hathitrust. org/. It's great news that much of our archival content is available to you and librarians, but this is not an optimal outcome for our journals because if you search in PubMed and find a pre-2000 JAVMA or AJVR manuscript that you would like to read, your search engine results will not link out to the article. You would need to go to HathiTrust and perform a search for that manuscript and download it there. To prioritize what content to digitize, our librarians researched recent requests received for AVMA articles with publication dates before 2000. The data clearly indicate a sharp decrease in requests from materials earlier than the 1970s, with 4 or fewer requests per year (depending on the library) for articles from 1960 or earlier.
2005). As a GGOS technique, GNSS contributes to the determination of the polar motion rate and provides a global coverage for the establishment and maintenance of the ITRF  (Boucher et al. 2015; Altamimi et al. 2016). The concept of the Global Positioning System (GPS) emerged when it was realized in the early 1980s that the measurement of the phase of radio-waves with a decimeter wavelength could result, over a sufficient acquisition time, in a millimeter-level relative positional accuracy between ground-fixed GPS receivers located on the surface of the Earth. At this level of precision, the "static Earth" of the surveyors became the "dynamic Earth" of geophysicists, with also a flow of data for meteorology and ionosphere studies. Today, we have four operational global constellations of positioning satellites: GPS (USA), GLO-NASS (Russia),  Galileo (Europe)  and BDS (China), with the word GNSS attached to them, and also two regional augmented constellations: QZSS (Japan) and NavIC (India), generally referred as Regional Navigation Satellite System (RNSS).
Accurate millimeter-to centimeter-level absolute positionings are now possible in real-time or near real-time for a single station, thanks to highly precise models of the GNSS satellite orbits, the drift of clocks, signal propagation delays, hardware biases and tidal effects. This is the so-called Precise Point Positioning mode, or PPP mode. The development, since 1994, of the International GNSS Service (IGS) infrastructure, with its online databases, is the backbone of these achievements  (Teunissen and Montenbruck 2017). The concept of the single-receiver (stand-alone) PPP mode, based on the monitoring of large networks of static GNSS "reference" stations, was introduced  (Héroux and Kouba 1995; Zumberge et al. 1997) , as a way to alleviate differential positioning between two GNSS stations, only one of which is considered as a "reference".
3, in order to give a thorough review of each error source in the observation equation. Various errors form the error budget of GNSS and are relevant for their origins. In Sect. 4, reviews of each error source are performed in separate subsections. Besides individual error sources, the impact of correlations between them and also the time correlations on PPP data processing are addressed in Sect. 5. Finally, a summary and an outlook are given in Sect. 6.
To enable the virtual synchronization of the whole constellation of onboard clocks, the time offsets of each individual satellite clocks from the ground system time, as well as their linear frequency drift rates are provided as ancillary data in broadcast ephemeris (Jaduszliwer and Camparo 2021). In the absence of true values, precise clock products generated by IGS/MGEX are usually adopted as references. The expected accuracy of the precise products is generally considered to be at least one order of magnitude better than that of the broadcast ephemeris. The statistics of average broadcast-minus-precise clock correction values were computed based on a dataset in 2013/2014 by  Montenbruck et al. (2015a). RMSs of clock differences ranged from 0. 3 to 1. 1 m in equivalent light-distances for GPS, 1.
9 m for GLONASS, 1. 6 m for Galileo and 0. 8 m for BDS-2 MEO/IGSO. With respect to precise clock products generated by Deutsches Zentrum für Luft-und Raumfahrt (indicated by DLR), the RMS was improved from 1. 11 to 0. 30 m for Galileo during the period of 2014-2016  (Steigenberger and Montenbruck 2017) , which is mainly due to the introduction of H-maser clocks and more frequent ephemeris uploads. For BDS-3, an overall satellite clock precision with STD of 0. 54 m based on a dataset collected in the first half of 2019 was reported by  Shi et al. (2020)  w. r. t. precise clock products of Wuhan University (indicated by WUM).
Different from IRI, the GIM has a higher time resolution (depending on the sample interval of GNSS observables) but only produces global VTEC values over a thin layer representing the ionosphere (generally located between 300 and 450 km above the Earth's surface). Since 1998, the IGS has started to provide daily GIM products, and there are seven Ionosphere Associate Analysis Centers (IAACs) computing independently with different approaches and datasets  (Hernández-Pajares et al. 2009). Results between these centers showed good consistency during one solar cycle  (Roma-dollase et al. 2018). As the most commonly used ionosphere correction products, the IGS GIMs have typically errors of 10-20% of the RMS with respect to TEC derived from The satellite altimeter mission named after the ocean TOPography EXperiment (TOPEX)  (Orús et al.
2019). The choice of elevation cutoff in ZTD estimation is also an important parameter, as well as the elevation-dependent weighting function applied in GNSS data processing. Based on a dataset spanning over 14 years, (  16 ) Four kinds of elevation-dependent weighting functions used for GNSS LS processing were investigated by  Hadas et al. (2020). They found that the differences in estimated ZTD between these weighting functions are usually below the 5 mm level but can exceed 10 mm during the initialization period when the PPP solution is converging. The mapping function is usually written in the form of a continuous fraction in such a way it has a value of 1 when the elevation angle is zenithal. a, b and c are coefficients currently estimated either from climatological data. e. g. , the Isobaric Mapping Function (IMF) and the Global Mapping Function (GMF)  (Niell 2000; Boehm et al.
atx and igs08. atx cannot be compared directly since there is a significant scale difference (about -1 ppb) between ITRF2005/IGS05 and ITRF2008/IGS08  (Rebischung et al. 2012). However, by ignoring scale-related biases, the accuracy of the satellite antenna PCOs is at centimeter-level  (Schmid et al. 2016). The antenna PCCs of Galileo satellites were firstly included in igs08. atx in 2015 by adopting the models from  Montenbruck et al. (2014)  and  Steigenberger et al. (2015). Subsequently, more accurate PCOs of Galileo satellites were estimated  (Steigenberger et al. 2016) , as well as the PCCs of BDS-2 IGSO/MEO within ITRF2008  (Dilssner et al. 2014; Guo et al. 2016; Huang et al. 2018 ). However, the differences among these estimated PCOs can reach up to decimeters according to the selected datasets, independent software and different applied models.
2020). To avoid Fig. 9  Phase wind-up transmitter/receiver geometry the drawback of separated antennas, a single dual-polarized LHCP/RHCP antenna was used  (Manandhar et al. 2004 ). Good performances on mitigating multipath effect by distinguishing NLOS signals from direct signals were shown both in simulation and in real GNSS datasets, e. g. ,  (Brenneman et al. 2007; Izadpanah et al. 2008; Groves et al. 2010; Jiang and Groves 2014). But the requirement for calibration of such a dual-polarization antenna and knowledge of antenna orientation restrict its applications  (Jiang and Groves 2014). Advanced signal processing techniques in GNSS receivers were also investigated to resist multipath. Before going into details of these advancements, to have a better understanding of how multipath affects the received signal, let us give an overview of the signal tracking in a GNSS receiver first.
Albeit these parameterbased techniques outperform nEML, common problems exist, such as significant hardware cost and model fidelity (i. e. , the performance can be poor when the signal is under-/overestimated). Some of them are even sensitive to the selected parameters  (Hurskainen et al. 2008). It should be noted that all these above-mentioned signal processing techniques are effective against medium-to-long delay multipath but are ineffective against the multipath signals arriving with a short delay (i. e. , less than 0. 1 chip). In fact, short-and medium-delay multipath are predominant in many environments  (Teunissen and Montenbruck 2017). The A-Posteriori Multipath Estimation (APME) is therefore proposed to cope with the short-delay multipath  (Sleewaegen and Boon 2001) , based on the property of the signal amplitude measurements that they are highly correlated with the multipath error in code phase measurement, especially for short-delay multipath  (Sleewaegen 1997).
Improvement of short-delay multipath rejection up to 50% w. r. t. the nEML and the SC in high signalto-multipath power ratio case was reported, see  (Sleewaegen and Boon 2001) , but deteriorations were introduced for medium-to-long delay multipath. Similarly, a slope-based multipath estimation technique was also developed to mitigate the short-delay, and the simulation result shows that it has the best overall performance when compared to the nEML and HRC in short-delay multipath cases  (Bhuiyan et al. 2010). Until now, one may notice Fig. 10  The diagram of multipath at a GNSS receiver that the above techniques implemented in the receiver all focus on the code multipath mitigation, but actually, the carrier phase multipath mitigation has been studied with the same methods as well. Another commonly adopted method for mitigating multipath is analyzing the time evolution of GNSS measurements.