dataesr/scientific-paragraphs-categorization huggingface dataset:
, n denotes a set of individual 100(1 -γ)% HPD credible intervals for each component of the vector M t , with γ chosen so that P({M t } ∈ R) = 1 -α. Since the posterior distribution for the vector M t is approximately multivariate normal with known mean vector and known covariance matrix, by trial and error, one can obtain a simultaneous 100(1 -α)% HPD credible band for the vector {M t , t = 1,. , n}, by computing, for every individual component of the vector, a 100(1 -γ)% HPD credible interval, varying γ till the overall probability is 1 -α. α = … ∈ = -. P M t n R ({ , 1, , } ) 1 t Actually this can also be obtained using the function excursions. simconf available in the R package excursions  37. Considering the fact that the linear trend was not significant and considering the cyclic nature of M t , above calculations were reported for the first 52 weeks, rather than for the full period.
Data sources We will search the following databases from inception to May 2019 to identify studies: the Cochrane Central Register of Controlled Trials (CENTRAL), the Cochrane IBD Group Specialized Trials Register, MEDLINE, EMBASE, and Chinese Biomedical medicine (CBM). The search strategies will be customized for each database and we will use recommended Cochrane search string for the identification of RCTs. Detailed search strategy could be found in the appendix, http://links. lww. com/MD/D112.
Study selection We use ENDNOTE X7 literature management software to screen and manage citations yield from electronic databases. Pilot tests will be performed for literature screening and data extraction, and remarks will be made to ensure high inter-rater reliability among the reviewers. Study eligibility will be assessed in 2 stages. First, pairs of reviewers will independently examine the titles and abstracts in ENDNOTE to identify related studies. Then, each full text article from the screening stage will be obtained and evaluated. Excluded trials and the reasons will be recorded and any disagreement will be resolved through discussion or consultation with an independent third adjudicator. The criteria of including studies are as follows: 1) Adults and children with a diagnosis of IBS based on diagnostic criteria including Rome I, Rome II or Rome III or Rome IV will be included.
Data extraction Data abstraction will be completed by independent pairs of reviewers after pilot-testing of the data extraction form. Interventions were coded independently by a clinician and a methodologist using a pre-established coding. Included interventions were classified into the following 2 categories: pharmacological interventions and non-pharmacological interventions. Furthermore, 2 independent reviewers will extract the data of interest. All the discrepancies will be resolved through discussion or a third reviewer. The following descriptive data from eligible studies will be abstracted: country of origin, year of publication, disease course, interventions, treatment schema and doses, number of participants, patient characteristics, background therapies, outcomes measurement or monitoring, length of follow-up, definition and data of primary outcome.
Assessment of risk of bias of included studies Two reviewers will evaluate the risk of bias of the selected RCTs according to the criteria and technique proposed in the Cochrane Handbook V. 5. 2. 0,  [37]  which includes random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), incomplete outcome data (attrition bias), selective reporting (reporting bias) and other bias. Each study will be assigned a level of risk of bias (high risk, unclear risk, low risk) for each item. Any disagreement will be resolved through discussion or consultation with an independent third adjudicator.
[37] Publication bias will be examined using Begg and Egger funnel plot method when applicable. [38, 39] n addition, the contour-enhanced funnel plot will be obtained as an aid to distinguish asymmetry due to publication bias. [40] 7. 3. Network meta-analysis. We will perform Bayesian NMAs with the package 'gemtc' V. 0. 8. 1 of R-3. 3. 2 software  [41]  to compare the effects of different prophylactic agents. The Markov Chains Monte Carlo sampler will be used to generate samples. A total of 5000 simulations for each chain will be set as the 'burn-in' period. Then, posterior summaries will be based on 100,000 subsequent simulations. Model convergence will be assessed using the Brooks-Gelman-Rubin plots method. [42]  Global heterogeneity will be assessed on the bias of the magnitude of heterogeneity variance parameter (I 2 or t 2 ) estimated from the NMA models using the mtc anohe command of the 'gemtc' package.
Inbreeding coefficients were calculated using the Cholesky factors of the relationship matrix (see details in  Boichard, 2002; Meuwissen & Luo, 1992)  as implemented in program meuw. f of PEDIG. The kinship coefficient is a measure of relatedness that represents the probability that two alleles at the same locus, one sampled at random from each individual, are identical by descent. Kinship coefficients were computed, in order to obtain a kinship coefficient matrix, by generating a "progeny" for each pair of sampled individuals and computing its inbreeding coefficient with Meuwissen's method  (Meuwissen & Luo, 1992)  as implemented in program par3. f of PEDIG.
| Spatial distance The location of the display site of each recorded male was recorded on the field in decimal degrees using a GPS (GPSmap 276C, Garmin, accuracy <15 m). Coordinates were then projected under GIS software (Esri ArcGis; coordinate system UTM zone 30N) in order to obtain coordinates in UTM metric unity. Euclidean distances between points of display sites were then calculated in order to obtain a spatial distance matrix using Access software with the following formula: where X and Y are UTM projected coordinates in meters of points A and B.
| Repeatability of the 11 acoustic parameters We analyzed the repeatability of each acoustic parameter of the 36 captive males and its confidence interval based on 1,000 parametric bootstraps as implemented in the rptR package of R  (Stoffel, Nakagawa, & Schielzeth, 2017). The statistical significance of the repeatability of each parameter was tested by a likelihood ratio test comparing the model fit of a model including the male ID random grouping factor and one excluding it.
We propose a way to model topic-based implicit interactions among Twitter users. Our model relies on grouping Twitter hashtags, in a given context, into themes/topics and then using the multiplex network model to construct a thematic multiplex where each layer corresponds to a topic/theme, and users within a layer are connected if and only if they used the same hashtag. We show, by testing our model on a real-world Twitter dataset, that applying multiplex community detection on the thematic multiplex can reveal new types of communities that were not observed before using the traditional ways of modeling Twitter interactions.
, 2014). To the best of our knowledge, no previous work has addressed extracting network-like information from the content generated by users on social media platforms for community detection tasks. Much of Twitter contemporary interactions happen in the form of conversations in many-to-many polyadic spaces defined by hashtags  (Bruns and Burgess, 2011). In this type of interactions, Twitter users are not necessarily retweeting, replying to, or mentioning each other but engaging directly with specific issues. This suggests that analyzing Twitter data by considering only the direct interactions among users (i. e. , following/follower, retweet, and mention networks) is still far from providing a complete picture of Twitter-based interactions. In this paper, we address this gap by proposing an innovative way to model topic-driven interactions of Twitter users using the multiplex network model  (Dickison et al.
, 2016). We test our model, the thematic multiplex, on a real-world dataset capturing the Twitter interactions of the Danish politicians during the parliamentary elections of 2015. We show that detecting communities on the thematic multiplex can reveal different dynamics than those observed by analyzing only explicit interactions. For example, we observed, using thematic multiplex community detection, that while some themes/topics were discussed by almost all the parties within the month leading to the election day, left and right-wing parties, at the same time, have also focused on themes that were politically closer to their traditional ideologies. The rest of this paper is organized as follows. In section 2 we introduce the thematic multiplex and the thematic multiplex community detection.
The DkPol Dataset The data we use to test our model is collected during the month leading to the 2015 Danish parliamentary election. Starting from a list of all the Danish politicians running for the parliament who also had a Twitter account, we collected all the tweets written during the 30 days leading to the election. The initial dataset was formed by 490 politicians distributed across 10 parties, 5,985 original tweets, 633 replies, and 3,993 retweets. Together with their Twitter activity, we noted also the political affiliation of the 490 politicians. Given the complexity of the Danish multi-party system, the parties have also been grouped into two main coalitions existing at the time: Red Block, currently at the opposition, and the Blue block, currently in government 1. In order to use the hashtag contained in the tweets to build a thematic multiplex, some initial data cleaning was necessary.
Experimental Settings Given the DkPol dataset, we constructed a twelve-layer thematic multiplex (layer per theme/topic). A topic/theme with k hashtags is interpreted as k cliques in the correspondent layer (a clique per hashtag) among all the users who used the same hashtag. We first show that detecting communities on the thematic multiplex reveals communities that are largely different from those detected using the traditional ways of modeling twitter  As to the selection of the community detection method for our multiplex networks in this paper, we chose a modularitymaximization based community detection method, Generalized Louvain  (Jutla et al. , 2017)  for this task. The reason is that we consider, by assumption, our networks to be undirected networks and our initial focus is on analyzing the communities resulted by the structural features of the network rather than the information flow.
DISCUSSION A clear difference has been shown when analyzing the communities on the thematic multiplex versus those detected on a multiplex constituted of the following/follower, retweet, and reply layers. This strongly suggests that community detection on the thematic multiplex reveals different dynamics than those observed using traditional ways of modeling twitter interactions. This is not to say that the thematic multiplex can substitute the traditional ways of modeling Twitter activities, but just to shed a light on different dynamics that can be observed using this way of modeling. Applying longitudinal community detection on the thematic multiplex network obtained from Twitter data allowed us to observe several interesting dynamics. Given that the dataset captured the interactions among Danish politicians during the month leading the parliamentary elections of 2015, we were able to capture the interest of a political party (or coalition) in specific issues, regardless of the fact that the issue produced an explicit interaction with other users through retweets or replies.
An example are two of the hashtags in our collection: #engangvarjegflygtning (translated: one day I was a migrant) and #dajegvar12 (translate: when I was twelve). In both cases an emotional hashtag is used to discuss specific issues, the refugee crisis with the first and children policies with the latter. The connection between the topic and the hashtag is not explicit, and while both hashtags are clearly topical hashtags (thus referring to a specific topic or event and suggesting the desire of the user to participate to an ongoing larger conversation Bruns and Moe, 2014) they also contain an emotional layer that, as well as the specific topic, is hard to understand if taken out of the specific cultural and societal context. A future iteration on this work should consider testing the thematic multiplex on other datasets.
An important extension should also consider the scalability problem with large scale datasets. The main complexity of this model comes from the greedy approach of connecting the user with his imagined audience via a clique. This means that by using a hashtag for only one time, a user is adding to the model a number of edges equals to the number of all other users who used the same hashtag. While a naive approach to minimize the size of these cliques could be to apply a threshold on the number times a user should use a hashtag before being part of the clique, we still think that further research should be carried out to find other alternatives for the clique concept in the thematic multiplex without any loose in the information. Even though the idea of using hashtags to gather communications of users that are not otherwise connected (e.
g. , not following each other) was originally introduced by Twitter, many other platforms such as Facebook and Instagram have adopted this idea in various ways. Thus, we suggest that this model should not be limited to Twitter data as it could be easily applied to other hashtag-based communicative contexts (e. g. , Instagram) as well as to other conceptually similar digital contexts (e. g. , participation in Facebook pages). On a separate note, we would like to mention the fact the resulted communities may largely depend on the chosen community detection method. Indeed, weather or not the thematic communities will be significantly different among different community detection methods can be a research question on its own and we think that answering this question is out of the scope of this paper.
CONCLUSION In this paper we propose an innovative model, the thematic multiplex, to model topic-driven interactions on Twitter. The thematic multiplex is a multi-layer network where each layer corresponds to a different topic, and users (nodes) within a layer will be connected via a clique if and only if they used the same hashtag. We explain the motivation behind the thematic multiplex which is the fact that it considers implicit interactions among users on Twitter that are usually neglected in other models. We construct the thematic multiplex of a real-world Twitter dataset describing the Twitter interactions among the danish politicians during the parliamentary elections of 2015. We show that applying multiplex community detection on the thematic multiplex allows us to observe different dynamics than those we would observe on other models.
Acknowledgements This work was funded by the  UK Skyrmion Project ,  EPSRC Programme Grant  ( EP/N032128/1 ), and the  OpenDreamKit Horizon 2020 European Research   Infrastructures  project (# 676541 ). X-ray holography was carried out using the COMET instrument [44] at the  SEXTANS Beamline ,  Synchrotron SOLEIL , proposal ID: 20170252. All the data from the micromagnetic simulations performed in this study can be reproduced from the repository given in ref. [45].
Background. Oligometastatic stage IV non-small lung cancer (NSCLC) patients have a 5-year overall survival of 30% versus 4% to 6% in historical cohorts of stage IV NSCLC patients. We reviewed data and patterns of care of patients affected by oligometastatic NSCLC in our center between 2001 and 2017. Methods. We retrospectively reviewed clinical and pathological files of all patients with lung cancer and synchronous isolated adrenal or brain metastases, or both, treated by locally ablative treatments (surgery or radiotherapy, or both) of both primary cancer and distant metastasis. Statistical analysis was performed to assess the effect on overall survival of patient-and tumor-related characteristics and therapeutic approaches. Overall survival was assessed by the Kaplan-Meier method. Survival rates were compared by log-rank test.
Collected Data Patients' characteristics, treatment procedures, and shortterm outcomes were collected using a standardized case report form. We collected use of induction chemotherapy, type of resection, histologic type, main diameter of tumor, and presence of lymphovascular emboli or perineural spreading. The presence of vascular or lymphatic tumor emboli was assessed by standard hematoxylin and eosin staining on samples from tumor and adjacent nontumoral lung tissue and defined as the presence of aggregates of tumor cells inside vascular or lymphatic microvessels. Tumor stage was reattributed according to the TNM Classification of Malignant Tumours, 8th Edition. Patients were defined as active, former, or never smokers according to tobacco consumption in the 6 weeks preceding treatment of the primary tumor.
Data Analysis, Follow-Up, and Statistical Analysis Data processing and analysis were performed with IBM SPSS Statistics 21. 0 software (IBM, Armonk, NY). Results are expressed as the percentage for qualitative parameters and mean AE SD or median (range) for normally and nonnormally distributed quantitative variables. Follow-up information was obtained by telephone interview with patients, relatives (in case of deceased patients), and referring physicians. Municipality registers were checked to confirm information on vital status. Patient overall survival was assessed by the Kaplan-Meier method, using date of treatment of the primary tumor as time 0. End follow-up was September 30, 2017. Survival rates were compared by log-rank test. Variables significantly associated with survival at univariate analysis were entered in a Cox multivariate analysis to assess their independent character.
In a number of previous works, we have performed a detailed EXAFS characterization of both Pt-  [16, 19, 34]  and Pd-  [23, 46]  functionalized metal-organic frameworks. However, the structure of the possible intermediates which may be present during the activation of functionalized UiO-67 samples remained unclear due to the high complexity of EXAFS analysis for multicomponent systems. In this work, we apply multivariate curve resolution alternating least squares (MCR-ALS) approach  [47] [48] [49]  to XANES spectra  [50] [51] [52] [53] [54] [55] [56] [57]  collected in situ during different treatment procedures at Pd K-and Pt L 3 -edges, which allowed us to extract from the huge experimental datasets the spectra corresponding to pure species and obtain their evolution along the activation procedure.
Materials and Methods Functionalization of UiO-67 by palladium and platinum was achieved via substitution of 10% standard bpdc linkers by MCl 2 bpydc (M = Pd, Pt) using the pre-made linker synthesis (PMLS) approach  [16]. The synthesis procedure have been described in our previous works for both Pd  [23]  and Pt  [19]. Experimental Pt L 3 -edge X-ray absorption data was collected at BM01B beamline  [58]  (now moved to BM31 port) of ESRF. The sample was loaded inside a capillary connected to a remotely controlled gas panel. The 4 temperature was controlled by a gas blower mounted below the capillary and calibrated using a thermocouple. In such environment, the samples were heated from room temperature (RT) to 300 °C with the ramp of 5 °C/min in pure He, 3%H 2 /He, and 10%H 2 /He. The photon energy was scanned from 11.
35 to 12. 42 keV by Si(111) double crystal monochromator operated in continuous scanning mode, which allowed collecting one spectrum in 4 minutes (i. e. one spectrum every 20 °C). Experimental Pd K-edge spectra presented in this paper were collected during three subsequent beamtimes. The first set of data was acquired at BM23 beamline  [59]  of ESRF. A pelletized sample was held in a microtomo cell  [60]  and was activated in a flow of 5% H 2 /He (50 mL/min). The step-by-step mode of the monochromator allowed to collect one spectrum from 24. 1 to 25. 1 keV every 40 °C of ramp. The second set of data was collected in a capillary at BM01B beamline using the similar sample environment as described above for Pt L 3 -edge measurements. For the experiment, performed at BM23 beamline double-crystal fixed-exit Si(111) monochromator was employed.
All spectra at both Pt L 3 -and Pd K-edges were collected in transmission mode with simultaneous measurements of Pt or Pd foils for energy calibration  [61]. The mass flow controllers were adjusted to send ca. 1 mL/min of the total flux per each 2 mg of catalyst. X-ray powder diffraction (XRPD) data for both Pt-and Pd-functionalized samples were collected in situ quasisimultaneously with X-ray absorption data during the experiment at BM01B to monitor the stability of UiO-67 crystal structure. The optic hutch of the beamline is equipped with a double set of monochromators and mirrors that allows a plug-and-play switch between X-ray absorption and diffraction set-ups in less than one minute  [62, 63]. The photon wavelength λ = 0. 51353(1) was selected by Si(111) channel-cut monochromator. The scattered signal was registered by Dexela CMOS flat plate detector in the 2θ-range from 2 to 32°.
The LaB 6 and Si NIST references were measured to calibrate the geometrical parameters of the setup. The 2D patterns were integrated in PyFAI  [64]  and refined in Jana2006 code  [65]. See Supporting Information for the XRPD data. [47] [48] [49]  using the normalized X-ray absorption spectra. In this approach, XANES spectra are represented by matrix D of size m×n, where m is the number of spectra in the dataset and n is the number of energy points. This matrix is decomposed as D = CS T + E, where C with size m×k is the concentration profiles of k pure components from matrix S(n×k), and E(m×n) is the error matrix. The energy ranges were limited to 11. 4 -11. 8 and 24. 2 -24. 6 keV for Pt L 3 -and Pd K-edges, respectively. The optimal number of components was chosen based on a logarithmic plot of the explained variance as function of the component's number obtained during principle component analysis (PCA)  [66] [67] [68] [69] [70].
XANES analysis was performed in MCR-ALS code The spectra extracted from the experimental datasets were compared with theoretically calculated relativistic XANES spectra obtained in the accelerated version of FDMNES code  [39, 40, 71]  within a full potential finite difference method (cluster radius R = 7 Å). Atomic models used for XANES calculation were initially optimized in VASP 5. 3 code  [72] [73] [74]  with PBE exchange-correlation potential  [75]. Initial structures were taken from the crystallographic data for UiO-67-Pd  [23]. Then, only single linker was left and was located in the center of cubic cell with a = 20 Å. The whole series of the optimized atomic structures is described in Section 3 and includes the initial MCl 2 bpydc linker (M = Pd, Pt) and its modifications (e. g. removal of Cl-ligands, substitution of Cl-ligands by hydrogen, detachment of metal from the linker and formation of metal nanoparticles).
At the first step, PCA is performed to determine the number of statistically relevant components in the whole experimental dataset. For Pt L 3 -edge, the three series of data collected during the activation in 0, 3 and 10% H 2 /He were analyzed simultaneously. The 5 most relevant abstract components determined by PCA are shown in Figure  2a-e. Each subsequent component is characterized by a decreasing amplitude which is finally getting close to the noise level at the 5 th component (part e). The variance explained by each of the component plotted in a logarithmic scale also reveals a characteristic change in the slope at the n = 4. This means that the four independent components should be used to reproduce the whole experimental dataset, while the improvement of reconstruction by addition of more than 4 components is negligible.