dataesr/scientific-paragraphs-categorization huggingface dataset:
Research methods The research study reported here was prompted by the construction of a new 3,000 m 2 training and research building at the CESI campus in Nanterre, Paris (the "Nanterre 2 CESI project"). The construction of the 4-storey building, which comprised teaching and research spaces and a high-tech "living lab" (for BIM, virtual reality displays, etc. ) was planned for a 12-month period (between 5 May 2018, and 31 May 2019). An image of the new building (Nanterre 2) and the existing (Nanterre 1) building is shown in Figure  2. CESI, as client, specified the use of BIM for the design and construction of the Nanterre 2 building. Apart from its intrinsic commitment to the use of the latest available technologies, CESI also wanted the project as a case study that provided data for teaching and research programmes in digital construction.
Software tools used As illustrated in Figure  3 , Navisworks (55% of respondents) and Synchro Pro (25%) were the most widely used BIM 4D products. The former was considered relatively easy to use, and functions such as operation control, conflict analysis, construction sequencing, and coordination between disciplines, were commended. However, respondents reported the need for considerable efforts in manipulating both the BIM model and the planning documents to combine their respective contents. Respondents who used Synchro Pro appreciated its functionality in integrating the planning process (with some reservations) but found the software rather difficult to learn.
Implementation strategies and methods The survey revealed two main strategies for engaging with 4D BIM for construction project planning. The first is for a company to proceed "in-house" by selecting its preferred 4D software and acquiring a license, then to build its capability through training. The second is to outsource its 4D planning to a subcontractor specializing in the process. Irrespective of the strategy adopted, two different methodological approaches to 4D implementation were in evidence. These generally related to the choice of software tool. The first is that described by  Hardin and McCool (Hardin and McCool, 2015)  and relies on the use of the Navisworks "TimeLiner" module. The linking of digital objects (in the 3D BIM model) to their corresponding project tasks (in the construction schedule) can in theory be done automatically, but only if appropriate 4D parameters have been correctly created and entered in the original digital model.
In confirmation of the literature (see above, Section 2. 3), if this has not been done, or if the available 3D design model(s) were incompatible in terms of their LoDs (or any other way) with the detail needed for a working 4D model, then the inevitable manual process is considerably more time-consuming. The second method is based on the use of Synchro Pro software and was developed by the iBIM team at Vinci Construction company, France. It involves 1) remodelling and restructuring the original 3D model into elemental objects that relate to the methods of construction (this could involve "splitting" or "joining" objects); 2) creating a task for each in the schedule; and then 3) linking each elementary object to its corresponding task. This results in a 4D schedule with a very high granularity, since each object in the original 3D model can be split into multiple 4D BIM objects (or joined into composites) according to the requirements of the onsite construction schedule.
This generates collaboration problems within the project and adds further obstacles to the ability to derive full benefits from BIM. The practical requirement for the CESI BIM team to undertake the implementation of 4D BIM planning on the Nanterre 2 project (as described in Section 3. 1) presented an opportunity to develop a workflow that addressed these concerns. The aim was to produce an approach to 4D BIM implementation that could enable creating a construction schedule of maximum functionality with minimum extra effort expended in data exchange. From a theoretical viewpoint, this approach includes and explains how the client should express, in a SMART way, their 4D BIM objectives and enables a four-step process for an efficient and practical implementation of 4D BIM. The CESI 4DBIM process, presented in the next section, describes and formalises the implementation of the 4D BIM use case between project actors, including the definition and selection of workflows and software required to its implementation, and enables four subprocesses, namely: 1) a clear expression of the 4D BIM objectives; 2) the identification of information requirements and relevant workflows to achieve these objectives; 3) the implementation of a project schedule; and 4) BIM model production to suit the 4D BIM use case.
The synthesis of all this information will make it possible to propose a first solution that will then be integrated into the 4D BIM use case and using visualisation, then be validated or amended. Step 3. 4: These steps require both a knowledge of traditional planning and 4D BIM based planning tools. The appropriate parties (e. g. , the contractor's BIM Manager) is asked to verify that the BIM models have been modified according to the required granularity of the project construction schedule. For the Nanterre 2 project, the initial schedule already included links between tasks. It therefore remained to determine a 4D parameter to be created so as to link the schedule to the BIM models to optimise its precision and facilitate the 4D process. Since the BIM model was created using Autodesk Revit software, a straightforward solution was to assign a text parameter "BIM_WBS" to all BIM model objects followed by the exact name of the individual planning task to which each must be linked.
11 In this trial, the safety profile was also less favorable for LEV than for lamotrigine, including higher rates of psychiatric disorders in patients treated with LEV (30%) than in patients with lamotrigine (13%). In brain tumor patients, especially in the context of chemoradiotherapy, the tolerability of LEV may be further reduced. We hypothesized that there is some overlap of the toxicity profile of temozolomide-based chemoradiotherapy and LEV in patients with glioblastoma. 5] [16] [17]  Temozolomide has a moderate emetogenic potential  18  while antiemetic properties were suggested for LEV. 19 Fatigue is a major burden for patients with brain tumors  20  and also represents a common adverse event of LEV. 21 ] [24]  Here we characterized the incidence of hematologic adverse events, nausea or emesis, fatigue, and psychiatric adverse events in patients with glioblastoma receiving combined chemoradiotherapy treated with LEV with or without other AED or treated with any other AED alone or in combination and compared to no AED use, analyzing a pooled patient cohort of the EORTC Brain tumor Group's clinical trial database.
Patient Cohort We performed a retrospective analysis of individual patient data (n = 2476) of four randomized clinical trials in patients with newly diagnosed glioblastoma: CENTRIC (Clinicaltrials. gov number NCT00689221),  25  CORE (Clinicaltrials. gov number NCT00813943),  26  AVAglio (Clinicaltrials. gov number NCT00943826)  27  and ACT-IV (Clinicaltrials. gov number NCT01480479)  28  [see Figure  1  for the Consolidated standards of reporting trials (CONSORT) diagram]. Approval for trial participation was obtained for all sites by their institutional review boards, and informed consent was available for all patients. In CENTRIC, CORE, and AVAglio, patients were enrolled prior to the start of standard radiotherapy with concomitant temozolomide, while ACT-IV enrolled patients after completing standard radiotherapy with concomitant temozolomide, i.
e. prior to the maintenance phase of treatment. Therefore, for analysis of adverse events during concomitant treatment, only data of the trials CENTRIC, CORE, and AVAglio were included while for the period of maintenance treatment, data of all trials were included from patients who started maintenance in the absence of tumor progression. Data on lymphocyte counts were not available in AVAglio, and therefore for analysis of lymphopenia, the dataset S (small) including the trials CENTRIC, CORE, and ACT-IV was used, i. e. without the patients of AVAglio, while for all other analysis the dataset L (large) including all four trials was used.
In these analyses, time to first grade 3 or 4 adverse event were assessed separately for thrombocytopenia, neutropenia, and lymphopenia, and time to first adverse event of any grade separately for anemia, nausea or emesis, fatigue, and psychiatric adverse events. Stratified by trial, the Aalen-Johansen estimator  30, 31  was used to obtain the cumulative incidence function, and the association of the use of AED with the incidence of adverse events was estimated by the Fine and Gray model. 32 Both for the analyses for the concomitant phase and for the maintenance phase, data were adjusted for covariables as indicated. On adjusted analyses, in general, data were used for those patients with all covariables available. However, for patients who did not have information available on the methylation status of the O6-methylguanine-DNA-methyltransferase (MGMT) promotor which was not mandatory in AVAglio and ACT-IV (Supplementary Tables  S2  and S3 ), we decided not to exclude them from adjusted analysis.
Interaction of the adjusted variables with AED use was assessed if there was an indication of a possible interaction. In order to account for the assessment of AED use with the variables of interest at two time points, i. e. concomitant phase and maintenance phase, the overall significance level of 5% was split into 2 (2. 5% for the concomitant phase analysis and 2. 5% for the maintenance phase analysis) and the corresponding 97. 5% confidence intervals reported for all the analyses. SAS version 9. 4 (SAS Institute Inc. , Cary, NC, USA) was used for all analyses.
We next explored whether any changes in AED use on the individual patient level or resolvement of adverse events were related to the observation that use of LEV was associated with psychiatric adverse events during concomitant, but not during maintenance treatment. To assess this, we performed subgroup analyses in the patient cohort of CENTRIC, CORE, and AVAglio during maintenance treatment since no data for concomitant treatment were available for ACT-IV. First, we confirmed that LEV was not associated with psychiatric adverse during maintenance treatment in this subcohort, too, both in unadjusted and adjusted analyses (P =. 427 and P =. 656). To assess the association of psychiatric adverse events on the individual patient level during concomitant and maintenance treatment, data from 1314 patients included in the maintenance phase of CENTRIC, CORE and AVAglio were available.
All values are expressed with a minimum and a maximum deviation of 0. 5 and 3. 5%, respectively. Analysis for the commercial acylglyceride mixtures by 1 H NMR A known amount of each MDGs was diluted with 700 μL of CDCl 3 , mixed and then transferred to a 5-mm NMR tube. The 1D 1 H NMR experiment was acquired on a Bruker Avance 500 spectrometer (Bruker Biospin) equipped with a dual 1 H-13 C TCI cryoprobe at 25 • C. A conventional NMR pulse sequence with a relaxation delay of 6. 54 s, a flip angle of 30 • and an acquisition time of 5. 46 s was used. NMR data were processed using the Topspin 4. 08 software (Bruker Biospin) with one level of zero-filling and Fourier transformation after multiplying FIDs by an exponential line-broadening function of 0. 3 Hz. Phase adjustment and polynomial baseline correction were done manually on each spectrum.
Analytical database An analytical database was constructed for each commercial AG mixtures by integrating the GC results: FA levels: C6:0; C8:0; C10:0; C12:0; C14:0; C15:0; C16:0; C16:1; C17:0; C17:1; C18:0; C18:1; C18:2; C18:3; C20:0; C20:1; C22:0; C22:1; C24:0; saturated FAs; monounsaturated FAs; polyunsaturated FAs and trans FAs. From these raw GC data, specific analytical parameters were calculated: intermediate FAs (6 to 10C); long-chain FAs (12 to 22C) and very long-chain FAs (>22C). 1 H NMR data were introduced for the determination of the amount of the different AGs and their isomers: TGs; 1,2-DGs; 1,3-DGs; 1-MGs; 2-MGs. Specific ratios were calculated from the raw GC data: unsaturated/ saturated FAs; monounsaturated/saturated FAs; monounsaturated/ polyunsaturated FAs; FAs polyunsaturated/saturated; long-chain/ intermediate FAs; very long/long-chain FAs; long chain/intermediate FAs; intermediate/long-chain FAs; intermediate/very long-chain FAs; long-chain/very long-chain FAs.
Chemometrics and statistical analysis All data obtained in this study were normalized by dividing each variable by the greatest value of the column. The QSPR study by ANNs was carried out in MATLAB R2020b (MathWorks) with the deep learning toolbox V. 14. 1. An ANN was constructed with 64 input neurons, connected to each of the 64 analytical parameters and one output neuron connected to the G' value measured for the 5 concentrations of each of the 13 commercial AGs. Feedforward backpropagation was used as a learning algorithm, with a sigmoid transfer function. No hidden layer was used to extract, after 25 learning cycles, the weight attributed by the ANNs to each of the 64 analytical parameters. Multiple linear regression models were built in MATLAB R2020b, with the statistics and machine learning toolbox V.
12. 0, using the key analytical parameters identified by the ANNs. For each model, the coefficient of determination (R2), the root-mean-square error (RMS) and the p-value from Fisher's test were calculated from the normalized values. Principal component analysis (PCA) works by using combinations of variables to describe the variance of a matrix by projecting it on different components. Eigenvectors represent each variable in a correlation matrix for all components, and the commercial AGs can be plotted on the corresponding score plot. PCAs were performed in MATLAB R2020b, with the statistics and machine learning toolbox V. 12. 0, using the key analytical parameters identified by the ANNs as variables for each concentration in commercial AGs mixtures to construct the components. From all the components of the correlation matrices, 3 were included in the analyses to perform classification of the 13 commercial AGs mixtures and 3D plots were defined to represent the correlation score for all concentrations used in the gelation process.
Analytical database First of all, the 13 commercial AGs mixtures composed of 11 known oleogelators and 2 negative controls (C8-C10 where no gelation occurs) were analyzed by GC and 1 H NMR to identify and quantify each lipid classes. With this information, a structural database was built with 64 analytical parameters (Table  S1 , supplementary data). To construct Table  S1 , we selected the analytical parameters suitable for describing the structure of AGs mixtures, grouped into 4 families: the lipid class of FAs, the composition of FAs, the amount of TGs and the different isomers of DGs and MGs and the ratios calculated between these different structural descriptors. The ratios calculated allow a relative comparison of the commercial AGs mixtures and any unknown minor impurities are not taken into account for the QSPR study, which may, in this case, ignore them  (Cherkasov et al.
, 2020)  with certain types of MGs for which macroscopic observations showed the presence of a residual liquid oil phase in the structured sunflower oil. This observation highlights the complexity of the systems and the importance of the mixing effects, which are still difficult to study. QSPR by ANNs To study the contribution to gelation of all the identified parameters, we used the analytical database (Table  S1 , supplementary data) as input descriptors of the AGs mixtures in a QSPR study. The first step was done by analyzing the weights assigned by ANNs to each analytical parameter in relation to the storage modulus (G ′ ) of the rapeseed oil media formulated with AGs mixtures and measured by stress-controlled rheology. Table  2  presents the results of the G ′ measurements for the 13 AGs mixtures studied, based on their concentration in rapeseed oil.
1. All statistical results are presented in Table  S4. For the fitting validation, all MLRs give R-squared models in the 0. 733-0. 963 range for n = 13 samples and p = 4 or 5 independent analytical parameters. The p-value is below the 5% confidence interval for all MLRs, in the 2. 9. 10 -2 -8. 6. 10 -6 range. For cross-validation, R-squared for the calculated G ′ vs experimental regressions are in the 0. 702-0. 963 range and the RMS errors are in the 0. 003-0. 029 range. All these data provide validation of all the linear regression parameters according to the statistical criteria for our experimental space. It should be noted that the low number of commercial AGs makes it impossible to evaluate external cross-validation using different test and regression datasets. These models can therefore only be used for the analysis of the interactions of the variables corresponding to the analytical parameters  (Gramatica, 2013; Konovalov et al.
Acknowledgments The authors gratefully acknowledge the  Nouvelle-Aquitaine Regional Council , the  Délégation Régionale à la Recherche et à la Technologie (DRRT Nouvelle Aquitaine)  and the  Agence Nationale pour la Recherche Technologique (ANRT)  for their financial support LCP contract # 186182. The authors would also like to thank  Franck Dejean  from  ITERG (Pessac, France ) for his helpful support on the GC analysis.
The phosphatidylinositol-3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway is frequently activated in HER2-negative breast cancer and may play a role in taxane resistance. The phase IB/II TAKTIC trial (NCT01980277) has shown that combining a dual AKT and p70 ribosomal protein S6 kinase (p70S6K) inhibitor (LY2780301) taken orally with weekly paclitaxel in HER2-negative advanced breast cancer is feasible, with preliminary evidence of efficacy. We wanted to explore whether circulating tumor DNA (ctDNA) may be a surrogate marker of treatment efficacy in this setting. Serial plasma samples were collected and cell-free DNA was sequenced using low-coverage whole-genome sequencing, and analysis was completed with droplet digital polymerase chain reaction (PCR) for some patients with driver mutations.
Patients' selection and study design All patients analyzed in this work were included in the TAKTIC-IPC 2012-008 study (N°EUDRACT 2013-000585-12, NCT01980277) and gave their consent for participating to ancillary studies. TAKTIC was a twostep trial. The phase IB aimed to determine the recommended phase II dose (RP2D) of LY2780301 in combination with paclitaxel for patients with locally advanced or metastatic HER2-negative breast cancer. Phase II focused on patients in the first-line setting and aimed to estimate the best ORR of this combination in the overall population and in patients with activation of the PI3K/AKT/S6 pathway. Details of inclusion criteria, treatment regimen, and clinical results can be found elsewhere  [11]. Details of tumor genomic analysis can also be found in the article related to the main clinical endpoints of the TAKTIC trial.
49, generating readings of 2*75 base pairs (bp). We then determined the cfDNA fraction from tumor cells (TF, tumor fraction) for each timepoint. Reads were aligned with the human reference genome (hg19) using BWA software (v. 0. 7. 15-r1140). Alignment was then processed to remove the duplicate sequences with the PICARD software (v. 2. 9. 2). A wig file containing the number of reads for regular intervals of 50 000 bp was generated with the READCOUNTER software. Finally, TF evaluation was obtained using the ICHORCNA software (v. 0. 3. 2, Broad Institute, Cambridge, MA, USA). All LC-WGS experiments were performed in simplicate. For each sample, the genomic profile was established. To identify recurrent copy number alterations, we used the Genomic Identification of Significant Targets in Cancer (GISTIC) 2.
The statistical analyses were carried out using SAS v. 9. 4 (SAS Institute, Cary, NC, USA) with a nominal level of statistical significance (two-tailed) set to 0. 05. and R (v. 3. 5. 1; http://www. cran. r-project. org/). This study was conducted in compliance with the Reporting recommendations for tumor marker prognostic studies (REMARK) criteria  [26] , see Table  S1. NGS, aCGH, and LC-WGS sequencing data are available in Tables S2-S4.
Ethics considerations As required by the French regulation, the study protocol was approved by both an Ethics Committee (Comit e de Protection des Personnes Sud M editerran ee I) and the French Agency Health authority (ANSM) and was registered as required (N°EUDRACT 2013-000585-12, NCT01980277). Patients were enrolled after signature on a written informed consent. All procedures were done in accordance with the 2008 Helsinki Declaration.
Acknowledgements We thank the  Institut Paoli-Calmettes Biobank  (the IPC/ CRCM/UMR 1068  Tumour Bank , that operates under authorization #AC-2007-33 granted by the  French Ministry of Research  ( Minist ere de la Recherche et de l'Enseignement Sup erieur ) for samples storage and extraction of tumor DNAs. This study was conducted under the sponsorship of the  Institut Paoli-Calmettes  and was funded by the  French National Cancer Institute  ( INCa , grant number  INCa-ARC_6440 ), the  Caritative Fondation ARC (Association pour la Recherche sur le Cancer) , and  CIC  ( CICp 1409 ). LY2780301 was provided by  Lilly (Indianapolis, IN). The funding source was not involved in the study design, in the collection, analysis, and interpretation of data, in the writing of the report or in the decision to submit the article for publication.
Conflict of interest A. G. declares nonfinancial support from Novartis. R. S. declares research grants from EISAI and Astra-Zeneca; advisory board for Roche, GSK, and Novartis; nonfinancial support (travel, accommodation and meeting registration fees) was from Pfizer, Roche, GSK, BMS, and AstraZeneca. The other authors declare no conflicts of interest.
Presentation of the case CHU-X is made up of three hospitals with significant activity (+3,000 beds and +14,000 employees). It is well ranked among French hospitals. The origin of its tolerance of error policy comes from the 2010 introduction of a no-punishment charter to encourage staff to report their errors. Meanwhile, CHU-X implemented software (KaliWeb) that sought to facilitate AE reports to the Quality and Risk Management Division (DQGR). Some of them were serious enough to impact public opinion: the death of a patient by strangulation after being restrained with a sheet (2008), the amputation of a woman's four limbs after contracting a nosocomial infection during an abortion (2011), the removal of a patient's uterus following vaginal delivery (against the couple's wishes) of a stillborn baby (2018), etc.
Data collection and analysis Between October 2018 and April 2019, we interviewed 26 people from a variety of backgrounds (see Table  1 ), alternating between intentional sampling and the snowball technique  (Patton, 2002). First, CHU-X's Quality and Risk Management Director put us into contact with three colleagues from the Quality and Performance Department and the Public Health Cluster, as well as with two care directors. Then, we asked these people to guide us to as many CHU-X units as possible, taking care to contrast the units studied. Once we met them, certain healthcare managers from the six selected departments put us in touch with people working within their care units. Finally, we directly contacted several people to whom respondents spontaneously referred during our interviews (e.