dataesr/scientific-paragraphs-categorization huggingface dataset:
Other future perspectives are to include questionnaires for Quality of Life research since research on this important subject is largely lacking, especially data on end-stage disease symptoms and the associated specific needs for palliative and end-of-life care  [18]. The collection of conventional MR-imaging data in the Imaging Repository, will in the future be expanded to multimodality MR-imaging and other advanced imaging techniques such as PET. The data also might be useful for educational purposes (e-learning) in an aim to improve diagnostics of these tumors. To conclude, with the collaborative efforts of professionals treating children with DIPG, patient/parent organizations, legal advisors, experts in the field of information technology and imaging experts, an international research-infrastructure was successfully set up, which led to the development and initiation of the SIOPE DIPG Registry.
With already 694 patients registered, this Registry stimulates collaborative preclinical and clinical research efforts. The first study using data from both the SIOPE 1 World Health Organisation (WHO) International Classification of Diseases (ICD). and International Registry is already in its final stages. The existence of the International DIPG Registry, surveying similar data as the SIOPE DIPG Registry, allows for external cross-validation of data, generating robust data on the DIPG patient population. Big data analysis of the Registry's data will potentially lead to the discovery of patterns that pave the way to the identification of effective therapies towards a cure for patients suffering from DIPG. The methodology used for the SIOPE DIPG Registry will, most likely, be easily translatable to other pediatric cancer registries, as almost all of these are orphan diseases that could benefit from international registration and collaboration in research.
Compliance with ethical standards Conflict of interest The authors declare that they have no conflict of interest. Informed consent If required, a SIOPE Network member informed parents (and patients), after which he/she provided the Patient Information Form and requested for informed consent. Research involving human participants All data in the SIOPE DIPG Registry has been retrieved from the participating hospital upon local Medical Ethical Committee and IRB approval. The SIOPE DIPG Registry project is being performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http:// creativecommons.
First, to detect genes with a mutational bias, we compared the expected number of mutations acquired per gene under a neutral model of evolution with that observed in the CC17 population (Fig. 2 ). From this analysis, we found that a total of 152 genes accumulated significantly more mutations than expected (P Ͻ 0. 05,   S2 ). (B) Venn diagram depicting the proportion of genes with a significant mutational signature across CC17, CC1, CC19, and CC23. (C) Functional classification of the 152 significant genes in CC17, based on the eggNOG database  (24). Fold change corresponds to the proportional difference in the number of genes among those with a mutational bias compared to the COH1 coding sequences (in parentheses). Statistical significance was assessed with a Fisher exact test. *, P Ͻ 0. 05; **, P Ͻ 0.
However, we found that the most promising candidates for a GBS vaccine (4), such as the capsule, the pilus, and Rib, are frequent targets of evolution. Therefore, this high level of adaptability will need to be carefully considered in the development of preventive strategies against GBS colonization. msystems. asm. org 12 a minimum of a five-strain gap between them, based on the phylogeny. Genes with a mutational bias in the CC17 population were classified into functional categories by using the eggNOG database v4. 5  (62). We then used a Fisher exact test to assess the statistical significance of the functions affected in relation to their overall proportion in the COH1 reference strain. For dN/dS calculations, the observed spectrum of nonsynonymous (N) and synonymous (S) mutations per gene was normalized by the expected N/S ratio obtained through simulation of all possible nucleotide substitutions in each reference genome.
Values of Ͼ1 are indicative of positive selection, and statistical significance was assessed with the binomial test. Variants associated with the available metadata (Table  S1 ) were extracted with VCFtools (63). Mutations were classified as carriage or disease related on the basis of whether they were exclusively present in CC17 isolates collected either from infected individuals or from asymptomatic carriers. This involved removing mutations that arose in ancestral lineages common to both carriage and disease strains. Subsequently, for each locus of the genome of COH1, the total number of mutations classified into each clinical state was calculated. To investigate the genes most differentially mutated, a linear model of correlation was built between carriage and disease mutation frequencies, and the outlier genes were detected with a Bonferroni-adjusted outlier test.
ACKNOWLEDGMENTS We thank  Laurence Ma  for her help in performing the Illumina sequencing, and the  CIP  for providing some of the isolates used in this study. We also thank  Arnaud Firon ,  Shaynoor Dramsi , and  Carmen Buchrieser  for useful feedback and discussions. This work was supported by  a project of ANR LabEx IBEID  and  ANR-13-PRTS-0006-04. A. A. is a scholar in the  Pasteur-Paris University (PPU) International Ph. D. program and received a stipend from  ANR Labex IBEID. Sequencing was performed at the  Pasteur Genopole , a member of  France Génomique  ( ANR10-IBNS-09-08 ).
Background: The number of clinical trials including older patients, and particularly patients with cognitive impairment, is increasing. While statutory provisions exist to make sure that the capacity to consent is assessed systematically for each patient, many gray areas remain with regard to how this assessment is made or should be made in the routine practice of clinical research. Objectives: The aim of this review was to draw up an inventory of assessment tools evaluating older patients' capacity to consent specifically applicable to clinical research, which could be used in routine practice. Methods: Two authors independently searched PubMed, Cochrane, and Google Scholar databases between November 2015 and January 2016. The search was actualized in April 2017. We used keywords (MeSH terms and text words) referring to informed consent, capacity to consent, consent for research, research ethics, cognitive impairment, vulnerable older patients, and assessment tools.
Methods Two authors (TG and OLS) independently consulted PubMed (Medline), Google Scholar, and the Cochrane databases in search for original articles describing tools for the assessment of DC. Existing literature reviews on the topic were also considered as additional information. The initial search was conducted between November 2015 and January 2016 and was actualized in April 2017. The inclusion criteria were based on the tools themselves. To be included, the references had to make a description of tests specifically designed for assessing patients' DC, with a report of the methods for assessing validity and/or reliability (either from the original report or from other studies evaluating the same test). Second, a mention of applicability to research and to older people with cognitive impairment was sought.
Different search strategies were performed using in priority keywords from the MeSH thesaurus: "informed consent", "decision making", "neuro-cognitive disorders", "aged", "adult clinical protocols", and "research subjects". However, the following additional keywords completed the search strategy: "Alzheimer", "dementia", "protocol inclusion", "ethics", "consent for research", "consent to research", "inclusion in clinical trials", "competency", "capacity to consent", "understanding", and "neuro-psychological evaluation". No language or publication date limit was set. The article selection was based on titles, abstracts, and finally full text for relevant articles. Additional results were also retrieved from the bibliography of existing reviews. Second, the same two authors independently conducted the data extraction and the selection of suitable tests or tools for assessing patients' CR.
Results The flow diagram in Figure  1  summarizes the number of articles accepted and rejected during the selection procedure. The search of the computerized databases identified a total of 226 articles. In the end, a total of 19 publications were identified as relevant to our research on instruments assessing DC for patients with cognitive disorders (Figure  1 ). ] [32] [33] [34] [35]  Thirty-eight instruments assessing DC were identified. However, the vast majority of existing tests were developed to assess the capacity of patients to consent to medical treatment and not for research purpose. For this particular context, 14 assessment tools were identified, the majority of which were initially developed or validated in psychiatric populations. 30, 32, 34 The main characteristics of each test are summarized in Table  1.
d. Smart Card Smart card is a technology that using Near Field Communication (NFC) as a media for transferring data such as information, balance, etc. Regarding to the payment system, this smart card is used to store e-money in a card. For thus who don't know, NFC system is a shortrange wireless technology that enables interactivity between electronic devices  [12]. There is some available smartcard that already implement in Indonesia such as BNI Tapcash, Mandiri e-money, BCA Flazz, BRI Brizzi, etc. This smartcard can be used as a payment system that already implemented in some public transportation like Transjakarta, Kereta Rel Listrik (KRL). Deploying payment system with NFC system as the replacement of money or ticket based paper, offers important benefits such as significantly reduced revenue collection costs, enhanced customer satisfaction as well as improved services and operational efficiency  [13].
The QR code will generated the user's necessary data such as user's name, the balance of the money in the internet account, and the payment deducted  [21]. We choose to make this because e-wallet is more simple, efficient and minimalize the usage of cash paper in the public. This system is also attracting more people to use the public transportation because this proposed system adopted incentive systems, where someone use public transportation, they will get the point. The more user using public transportation the more benefit they will get. The usage of e-wallet is very efficient because it needs only smartphone with camera to scan the QR Codes. The user only need to install the application, sign up to get the points or sign in as a guest for temporary use, top up the wallet and its ready to use.
iers. org). However, GNSS (Global Navigation Satellite System) data (tracking mainly GPS satellites) have dominated since the inception of the IGS in 1994. This is strikingly evident in Fig. 10  of Altamimi et al. [2] , who describe the combination methods and results for the ITRF2014 (International Terrestrial Reference Frame 2014). The ITRF multi-technique combination is the basis for the definitive IERS PM time series. A study by Ray et al. [3]  had already demonstrated that GPS-based PM from the IGS totally dominates over VLBI (very long baseline interferometry) results in rigorous combinations due to the "relatively dense and uniform global network coverage, high precision, continuous daily sampling, and homogeneity" of the former. Note that since the formal uncertainty of geodetic PM estimates scales as the inverse square-root of the number of observing stations, the IGS is hugely advantaged by using vastly more continuous tracking sites than any other method.
Consequently, the IGS PM formal errors have ranged between 5 and 10 mas since ~2000. So an evaluation of the accuracy of modern PM measurements must focus on the IGS products, which is the task of this report. As is already well known for other GPS-derived products, particularly terrestrial positions and velocities, systematic effects invariably overwhelm white or thermal data noise propagated from the observations into formal errors by the parameter covariances; see Ref. [4]  for a recent summary. The systematic errors can be decomposed into three categories: long-term biases, which are most difficult to detect if independent observations of similar accuracy are not available; various periodic variations mainly at periods of annual (1. 0 cycle per year or cpy), GPS draconitic (1. 04 cpy) plus its higher harmonics (N*1.
The x p and y p parameter partials are simple diurnal sine waves whose amplitude and phase depend only on the location of individual ground stations and the size of the a priori PM error. As a consequence, the quality of PM estimates depends mostly on the extent of global coverage by ground stations and their number. Idiosyncratic motions of particular stations, for whatever reason, can be overcome by sheer numbers of stations, in large measure. This is the major strength of the IGS, which routinely includes data from >400 stations since 2002 and has formal PM uncertainties of about 5 mas (0. 15 mm of equatorial rotation). In passing it is worth noting that data integration periods less than 24 h yield progressively poorer quality PM results as the observability is inherently reduced, thereby subjecting the PM estimates to increasing levels of systematic biases.
It is not feasible to estimate PM geometrically with data intervals much less than a day, in sharp contrast with the near-instantaneous capabilities of gyroscopic methods. Claims of doing so always rely on constraints on the geodetic estimates, such as continuity between consecutive segments over 24 h or longer. But such procedures invariably cause smoothing and signal distortion, even up to several times the Nyquist segmentation period (Ray J, Analysis effects in IGS polar motion estimates, 2008; at IGS Analysis Center Coordinator website acc. igs. org/erp-index. html). With this perspective, it is clear that any unrelated effect that introduces a diurnal sinusoidal signal into the relative ground-sky relationship is likely to bias PM estimates. GPS satellites form a particularly inopportune celestial framework in this respect because their orbital period is very close to 12 sidereal hours and their ground tracks repeat about every sidereal day.
The alignment process itself is necessary because GNSS data processing does not realize a reliable Earth center-ofmass frame, requiring the spurious AC origin offsets be removed by a Helmert transformation. That transformation itself is imperfect due to non-zero correlations among translation and rotation terms caused by non-ideal network distributions coupled with the fact that the stations forming each AC frame do not move exactly linearly. Annual position variations are largest (apart from occasional discontinuities caused by equipment changes, earthquakes, and other episodic events that have been modeled separately) and those would be listed as the next most important component of AC frame alignment errors were it not that  [2]  recognized this possibility and therefore they empirically adjusted seasonal terms for all stations in ITRF2014.
0 and that the last IGS data used to construct that frame was until 2009. 5. Realistic horizontal IGb08 station velocity uncertainties are probably at least 0. 2 mm/yr. So by late 2016 we see typical WRMS horizontal scatters for IGb08 core stations, compared to recent weekly IGS frames, at the level of ~5 mm. Considering that only about 50e55 core reference frame station survive, there could be an additional rotational uncertainty of ~22 mas simply due to frame aging. Obviously, this purely procedural error could be strongly mitigated or eliminated by modifying the processing steps to permit more frequent frame updates while still preserving a stable secular ITRF datum. Various proposals to do this have been considered in the past but none adopted so far. For only a few very demanding users might this be a practical issue.
down to the formal error level, owing to the longer-term character of the predominant frame alignment errors as well as annual and draconitic variations being the main periodic contributors. So the conclusion by MacMillan  [35]  that PM precision from the continuous VLBI campaign CONT14 is comparable to the IGS based on just two weeks of data is not sound. The fact that the standard deviation (not WRMS, as stated) is about 30 mas for the (CONT14 e IGS) PM differences over that short period is insufficient. Among other things, ignoring the mean PM differences, as  [35]  seems to have done, also ignores potentially significant reference frame inconsistencies. There is no reason to imagine that the far sparser VLBI network suffers any less from reference frame misalignments than does the IGS.
For several decades, satellite-based microwave sensors have provided valuable soil moisture monitoring in various surface conditions. We have first developed a modeled aerosol optical depth (AOD) dataset by utilizing Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Global Land Data Assimilation System (GLDAS) soil moisture datasets in order to estimate dust outbreaks over desert areas of East Asia. Moderate Resolution Imaging Spectroradiometer-(MODIS-) based AOD products were used as reference datasets to validate the modeled AOD (MA). The SMOS-based MA (SMOS-MA) dataset showed good correspondence with observed AOD (-value: 0. 56) compared to AMSR2and GLDAS-based MA datasets, and it overestimated AOD compared to observed AOD. The AMSR2-based MA dataset was found to underestimate AOD, and it showed a relatively low -value (0.
Many of the mineral dust source regions in East Asia are located in large bare deserts, and therefore, the surface wind speed and soil moisture (SM) are considered to be the primary factors that control interannual variation in the frequency of dust outbreaks  [15, 17]. Various studies were previously conducted using wind tunnel experiments in laboratories or in fields to examine the effect of SM on wind erosion  [18] [19] [20] [21] [22] [23]. However, most of these studies were not able to fully reflect largescale dust outbreak phenomena under natural conditions. In order to overcome this challenge, the synergetic use of remote sensing datasets and global assimilated datasets is invaluable. This enables global-scale dust emission studies to be conducted beyond observatory-scale dust research  [24, 25].
In recent years, many efforts have been made to identify dust source regions and to detect dust events based on satellite remote sensing techniques  [10, [26] [27] [28] [29] [30] [31] [32] [33] [34]. However, the previous studies hardly explain the conditions in the dust source regions that produce dust outbreaks because most analyses are based on data obtained from visible and infrared sensed datasets which have limitations under cloudy and dusty weather conditions. Thus, this study investigates dust outbreak phenomena using microwavebased satellite remote sensing techniques to estimate the surface conditions (i. e. , surface SM) when dust events occur. Several studies have investigated surface SM from satellite-based microwave instruments  [35] [36] [37] [38] [39]. Satellitebased SM measurements were required during the initial states of weather forecasting and climate modeling over vast scales  [40] [41] [42] [43].
The AMSR2, a follow-up microwave sensor to the AMSR for Earth Observing System (AMSR-E), is a passive microwave instrument that has been providing global nearsurface SM data since its launch in May 2012. The AMSR2 SM product has been widely validated by many studies  [41, 52, 53]. The present study uses SMOS-and AMSR2-derived SM measurements and the Global Land Assimilation Dataset System (GLDAS) to investigate dust outbreaks over the desert regions of East Asia. The relationships among the SM, wind speed, and aerosol optical depth (AOD) are utilized to estimate dust outbreak phenomena. The main objectives of this study are  (1)  to estimate the modeled AOD (hereafter MA) datasets based on different SM and GLDAS wind speed datasets, (2) to validate MAs with the observed MODIS-AOD products and short-term trend analysis, and (3) to analyze the spatial distribution of MA products and observed AOD datasets in different seasons.
Datasets and Study Areas In this study, the erosivity factor (i. e. , wind speed), erodibility factors (i. e. , soil properties, sand fractions, and SM), surface conditions (i. e. , surface temperature), and precipitation were considered in order to analyze the effect of SM on dust outbreaks over deserts in East Asia. The US Department of Agriculture (USDA) topsoil texture classification was used with the Harmonized World Soil Database (HWSD) to define the desert regions and to obtain information on the land and the atmosphere over the land. The SM contents were retrieved from SMOS and AMSR2; SM, wind speed (WS), surface temperature, and precipitation datasets from GLDAS were utilized for generating MA products. Atmospheric properties were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Aqua satellite (Refer to the following sections for further details regarding those datasets).
Land Cover and Land Properties Dataset. Land cover and land properties datasets are used in this study to identify dust source regions and investigate dust outbreak conditions. The land cover dataset is obtained from Biosphere Atmosphere Transfer Scheme (BATS). BATS landform categories were created by Dickinson et al. [54]  and modified by Olson  [55]  to support land-atmosphere modeling. Similarly, the land properties dataset is obtained from the Harmonized World Soil Database (HWSD), which is a raster database that contains more than 16,000 different soil mapping units at a spatial resolution of 1 km × 1 km. This database combines regional and national updates of soil information worldwide. It consists of 221 million grid cells and is contained within the 1 : 5,000,000 scale FAO-UNESCO Soil Map of the World.
In particular, the HWSD has been applied in dust research to identify dust sources and investigate dust outbreak conditions ∘ E 125 ∘ E 130 ∘ E 115 ∘ E 100 ∘ E 85 ∘ E 80 ∘ E 75 ∘ E 110 ∘ E 90 ∘ E 105 ∘ E 95 ∘ E [1] Taklimakan Desert  [3]  Kumtag and Qaidam Basin Desert  [2]  Gurbantunggut Desert  [4]  Badain Jaran, Tengger, Ulan Buh, and Hobq Desert  [6]  Horqin Desert  [5]  Hunshandake Desert  [7]  Gobi Desert Figure  1 : The East Asia sand fractions were retrieved according to the Harmonized World Soil Database (HWSD). All of the identified desert regions were recognized as the most famous dust sources around the world. Well-known desert regions (#1 to #6) are classified as sand by the USDA classification and exhibit a sand fraction that is greater than 80%. as well as in several other research fields  [56] [57] [58] [59].
Originally, both of these algorithms utilized a simple radiative transfer model  [69]. Moreover, LPRM provides AMSR2 SM retrievals for both C-and X-band microwave frequencies, whereas the JAXA algorithm provides SM retrievals only for the Xband. The LPRM algorithm, however, is expected to be more accurate, which enables the retrievals of the SM and vegetation optical depth, simultaneously, from horizontal and vertical polarized   measurements  [70]. The AMSR2 SM products used in this study were cross-validated with the AMSR-E slow rotation dataset (http://global. jaxa. jp/ press/2015/12/20151207 amsr-e. html). In this study, we only utilized the LPRM X-band SM dataset for conciseness, because SM from the C1-and C2-bands showed almost the same temporal patterns as the SM from the X-band over the study area.