dataesr/scientific-paragraphs-categorization huggingface dataset:
Images were used for data capture in 13 of the tools we evaluated (nine research and four consumer-based tools), either by automatically coding food intakes, passively capturing food intake throughout the day, as a method of recording intakes, or as a memory prompt. Digital images were also used to facilitate portion size estimation in over half of the tools we evaluated (53%; 19 research tools and four consumer tools). Uses ranged from automatic estimation of food volumes from digital images  [14] [15] [16] 30]  to visualization of different portion sizes to improve portion-size reporting  [20, 26, 40, 42, 45, 46, 52, 59, 81, 83, 84, 87]. Validation studies were much more commonly reported for dietary assessment tools in the research setting than for those targeted to consumers. There was very good agreement between many of these tools and their reference method, a conclusion also drawn in another previous review  [112].
g. standardized portions, household measures, absolute values, automatic estimation of food volume? -Were there features to add missing items or to custom recipes? -Were data exported to another devices? -Did the tool provide feedback or allow users to set goals for self-monitoring? -Which type of dietary information was included in the output files, e. g. , total energy, macro/micronutrients (and which ones), food groups consumed, meal occasions, time of intake? Step 5 Report on the design, pretest, and validation of the tool -How was the ease of use or user friendliness assessed? -How was the user feedback/acceptability assessed? -How long did it take to complete an assessment (average and range)? -How was the tool validated, and against what method? Was a gold standard method used to report on the magnitude of measurement error? In addition, the definition of the specific purpose of a tool implies the identification of the population characteristics, e.
Acknowledgments: The authors, members of the  ILSI Expert Group  involved in this research, wish to thank  Jonathon M. Taberner  ( Leeds University ) for his assistance in the initial literature search, setting up the spreadsheet for the data extraction, and contributing to the scoring of the first 24 tools. We also wish to thank  Mariah L. Tabar , international student at UniLaSalle in 2016, for her additional literature search. In addition, we thank the  ILSI Europe Dietary Intake  and  Exposure Task Force , as well as task force manager  Nevena Hristozova , for their support.
2012 Health and Technology; Australia Food groups consumed Adults and adolescents Smartphone App images; dietitian identifies foods and Healthy Eating, but not integrated into 2670 Not specified and 2016; Pollard et al. 2016 mobile food food groups tool [21-23] record Compl-Eat Netherlands Dietary intake Adults and adolescents from 16 years Web-based Interviewer-assisted or self-administered 24-h recall based on Dutch Food Composition Database 2000 Close to 30 min Meijboom et al. 2017 [24] DAP Diet Assess and Plan Serbia, Balkan region Diet and physical activity All ages Web-based, PC 24-h recalls, food frequency questionnaires (FFQ), food propensity; dietitian enters data Serbian and Balkan regional food composition databases 1450 Serbian and 1600 Balkan foods and recipes 9 15-30 min Gurinovic et al.
, 2015; Kupek et al. 2016 [78,79] WebDASC Web-Based Dietary Assessment Software for Denmark Dietary Intake Children Web-based 24-h recall Danish National Survey of Diet and Physical Activity (DANSDA) 1300 Average of 15 min (after first day) Biltoft-Jensen et al. 2012 and 2013; Andersen et al. 2015 [80-82] Children Nutrition Data Web-FFQ Quebec, Canada Dietary intake Adults Web-based FFQ System for Research and the Canadian 136 45 min Labonte et al. 2012 [83] Nutrient File WebFR Norwegian National Medin et al. 2015, Web-based Food Norway Dietary Intake Children Web-based 24-h recall Survey database 550 Not specified 2016, and 2017 Record (NORKOST) [84-86] Zambia Tablet-based 24h recall Tool Zambia Dietary intake Children Tablet Interviewer-assisted 24-h recall HarvestPlus and Zambia food comp tables Not specified Not specified Caswell et al.
2014 and 2016 [94,95] FoodLog for dietary data collection as part of DialBetics program Japan, Korea Diabetes management and diet, physical activity Adults Smartphone App Food record from images, text; system calculates energy, macro-nutrients National food database: Dietary Reference Intakes, Japan (2010) 2191 Average of 35 min Aizawa K. et al. 2014; Waki et al. 2012 and 2015 [96-98] GoCARB EU Diabetes management and diet Adults Smartphone App Food record based on meal images for carbohydrate intake estimates USDA Nutrient Database for Standard Reference 5000 ~1 min per image Rhyner et al. 2016; Bally et al. 2017 [99,100] IDQC Internet Based Diet and Lifestyle Questionnaire China Diet and physical activity Adults and adolescents Web-based FFQ Food Nutrition Calculator (Beijing) 135 30-40 min Du et al.
Methods In this prospective pilot study, all the participants belonged to the "Prospective Assessment of Dysarthria and Other Dopaminergic and Non Dopaminergic Axial Signs in PD" cohort (PRO-DYGI-PARK; ClinicalTrials. gov: NCT 02627664) and were included during an inclusion visit between September 2011 and December 2012. All of the patients (i) met the UK Brain Bank criteria  [15] , (ii) had a Hoehn and Yahr score below 3  [16] , and (iii) had been diagnosed and included early in the course of PD (i. e. a disease duration of less than 5 years, as determined by the onset of the first motor symptoms reported by the patient). None of the patients suffered from a concomitant respiratory disease. Likewise, patients with an ear, nose or throat disease (a tumor, an infection or a functional disorder of the vocal cords) or severe cognitive disturbance (as defined by a Mini-Mental State Examination score of less than 24 out of 30  [17] ) were excluded.
e. the 5 th percentile). The PFT was performed at the inclusion visit (V1) for both groups and then two years later (V2) for the PD group only. The neuropsychological examination included the Montreal Cognitive Assessment  [23]. Quantitative variables were expressed as the mean ± SD (for normally distributed variables) or the median [interquartile range]. Qualitative variables were expressed as the number (percentage). The normality of the data distribution was assessed using histograms and the Shapiro-Wilk test. A bivariate analysis was performed using Student's t test for quantitative variables (or a Mann-Whitney U test for non-normally distributed variables) and a chi-squared test for categorical variables (or Fisher's exact test if the expected cell frequency was <5). An analysis of covariance was used to assess changes over time in clinical parameters for PD patients with or without inspiratory muscle weakness.
Changes over time at V2 The changes over time in clinical features and PFT data between V1 and V2 are summarized in Table  4. With the exception of the UPDRS part I score (p = 0. 096), the MIP (p = 0. 055) and the SNIP (p = 0. 056), all clinical parameters had significantly worsened after two years of follow-up. The LEDD was significantly higher (p<0. 0001), and the FEV1/FVC was significantly lower (p = 0. 002). The correlation between the LEDD and changes in FEV1/FVC was not statistically significant (p = 0. 55). Patients with a higher LEDD tended to have higher MIP (p = 0. 02, r = 0. 37) and SNIP (p = 0. 05, r = 0. 53) values-greater respiratory muscle strength, in other words.
9 ± 1. 7 years. Furthermore, the drug-naïve patients and the treated patients (at V1) did not differ with regard to the PFT data in general and inspiratory muscle weakness in particular, and the LEDD and PFT results were not correlated. Hence, one can suppose that ventilatory dysfunction is part of the pathophysiological process, rather than an effect of treatment with dopaminergic medications. However, these results need to be confirmed in a larger population. In agreement with other reports  [29, 30] , our patients' mean UPDRS III scores worsened by 2. 1% over two years. The LEDD also increased, and FEV1/FVC decreased significantly. We cannot rule out a role of age in these changes, although there is a lack of detailed data on this topic in the literature. When considering inspiratory muscle strength, the changes over time in MIP and SNIP were non-significant.
Development and planning of health care services requires robust health information systems to define the burden of disease, inform policy development, and identify opportunities to improve service provision. The global coverage of kidney disease health information systems has not been well reported, despite their potential to enhance care. As part of the Global Kidney Health Atlas, a cross-sectional survey conducted by the International Society of Nephrology, data were collected from 117 United Nations member states on the coverage and scope of kidney disease health information systems and surveillance practices. Dialysis and transplant registries were more common in high-income countries. Few countries reported having nondialysis chronic kidney disease and acute kidney injury registries.
Recruitment for nondialysis CKD and AKI registries will need to encompass patients managed in primary health care, general medical, and critical care settings. Estimation of disease prevalence and the collection of longitudinal data concerning patient outcomes are challenging due to the migratory nature of some populations, and the lack of a national census affects the adequacy of the reference population. Also, health information systems rely on the systematic identification of individuals; however, the feasibility of using identifiers will vary by local custom. Establishing a health information system requires adequate numbers of trained  personnel, including data collectors, coders, and analysts, as well as suitable data processing facilities for data storage and security. 10 Complex and lengthy questionnaires may limit participation.
Currently, the burden of nondialysis CKD and AKI is difficult to estimate, which inhibits optimal allocation of finances and health resources to manage these highly prevalent conditions. Because de novo creation of registries requires substantial investment of resources, consideration should be given to the inclusion of patients with nondialysis CKD and AKI into existing registries with infrastructure already in place. Because it is impractical to include all individuals in such registries, focus should initially be on inclusion of those with advanced disease. The ability of nondialysis CKD and AKI health information systems to accurately estimate disease burden and outcome will be reliant on the availability of appropriate population-based screening procedures. It is likely that in the future it will be possible to monitor a broad range of medical conditions using registries that collect data inexpensively from electronic medical records and administrative datasets.
32 For example, both nondialysis CKD and AKI are ideal computable phenotypes. 33 To reduce the burden and cost of registry data collection, registry  development will need to evolve to ensure that data items are reliably captured within, and easily extracted from, these routinely collected electronic datasets. Incorporation of patient-reported outcome measures to existing health information systems in order to enhance understanding of patient experiences should be considered. 34 System design that enables easy comparisons between and within regions warrants consideration. 35 To this end, the NephroQUEST project was launched by the ERA-EDTA Registry with the aim of developing a consensus on the selection of quality of care indicators recorded in participating European national registries and to standardize data collection and dissemination.
36 At the same time, international comparison of registry data between diverse nations may not be appropriate because of differences in patient selection and health service provision. 37 Novel use of health information system data is occurring in the field of clinical research and study design. In addition to use in cohort studies, registry data may be utilized for cluster-randomized studies nested within an ongoing registry, and for studies that link the registry database with other data sources. This is the most comprehensive report of the global coverage of health information systems for kidney disease. Its key strengths lie in its use of a validated survey, based on the WHO health system building blocks, as well as its inclusion of respondents from 117 countries, with representation from all ISN regions and World Bank income groups.
Methods The GKHA Project was a cross-sectional survey conducted by the ISN. All United Nations member states were invited to participate, with a specific focus on 130 countries with ISN-affiliated societies. The online questionnaire was distributed through the ISN's 10 regional boards (Africa, East and Central Europe, Latin America, Middle East, North America, North and East Asia, Oceania and Southeast Asia, newly independent states [NIS] and Russia, South Asia, and Western Europe). For the purpose of analysis, countries were grouped by World Bank country classification of 2014 and ISN region (Supplementary Tables  S1  and S2 ). A comprehensive description of the sampling approach, development and validation of the survey, data handling, and statistical analysis is available elsewhere. 38, 39 s part of the survey, countries were asked to provide data on the local availability of health information systems for dialysis, transplant, nondialysis CKD and AKI.
ACKNOWLEDGMENTS We thank  Drs. Marcello Tonelli  and  Valerie Luyckx  for their contributions to the project and manuscript,  Sandrine Damster , Research Project Manager at the  International Society of Nephrology (ISN) , and  Alberta Kidney Disease Network (AKDN)  staff ( Ghennete Houston ,  Sue Szigety , and  Sophanny Tiv)  for their support with the organization and conduct of the survey and project management. We thank the  ISN  staff ( Louise Fox  and  Luca Segantini ) for their support. We thank the executive committee of the ISN, the  ISN regional leadership , and the leaders of the ISN Affiliate Societies at regional and country levels for their support toward the success of this initiative.
Background: Due to the increase in the number of people with dementia, relatives often provide in-home care. This care constitutes a cornerstone of the healthcare system, and maintaining these caregivers' well-being is therefore of paramount importance. Although respite interventions are generally considered an effective support system, they tend to be underutilized. The aim of this integrative literature review is to highlight the factors that promote and impede the use of respite interventions. Methods: Searches were conducted on the PubMed and CINAHL databases for studies of respite interventions from 1980 to 2016, and they yielded 51 articles of relevance. Results: Analysis of these articles revealed modifiable and immutable factors that influence the use of respite. The most cited topic categories in the literature were attributes of respite services and workload managed by caregivers, which is characterized by the onset of burden.
The search for relevant documents was carried out using PubMed and CINAHL databases. The MESH terms were "caregivers," "Alzheimer," "dementia," and "respite. " The various terms were combined using Boolean operators to obtain a search equation (Additional file 1). Two researchers carried out the article selection and analysis stages to ensure cross-checking and controls. Using the results in the various databases, we performed the first selection by restricting the languages; then we perused the titles and abstracts while using the criteria for inclusion and noninclusion. Elimination of duplicates was performed at the same time. Reading of the full articles then allowed for evaluation of the scientific studies' methodological quality and the final selection.
Data extraction strategy After the article selection, a descriptive and analytical reading was carried out, and a summary table of the selected articles was generated. The analysis of the studies was carried out according to the principles recommended by Miles, Huberman, and Saldaña (  2014 ). An encoding using the MAXQDA 12 software analysis tool allowed for a regrouping of subthemes in a pattern group and determination of the theme categories  [36]. The data was coded in two stages. During the first coding cycle, codes that represented symbolic descriptive or deductive information were assigned. These codes were allocated to large parts of the participants' statements, and they promoted the grouping of data segments. Then a second coding cycle promoted the identification of "pattern codes" to group these summaries into a smaller number of thematic categories.
Synthesis The results regarding the factors promoting and impeding the use of respite interventions were identified and regrouped into three categories: in connection with the respite interventions, with caregivers, and/or with the person with dementia. Several themes and subthemes emerged from these three categories (see Fig. 2 ). To guide activities for caregivers, the theme categories were classified based on two broad factors, namely changeable factors and immutable factors. The changeable factors are defined as elements that can be subject to an action. By contrast, the immutable factors are unchangeable elements (see Table  1 ). With the software MAXQDA 12, the occurrence of themes and studies' quotes were calculated from the codification. In Table  1 , the immutable factors are represented by elements on which the actions of health professional, decision makers, and politicians have little influence.
Acknowledgements We want to thank  Julian Santiago-Prowald  ( ESA ) and  Vicente Gomez Molinero  (formerly at Airbus D&S) for fruitful discussions. Authors acknowledge the support of the  European Space Agency  under contract " Sonic Crystals For Noise Reduction At The Launch Pad" ,  ESA ITT 1-7094  ( ITI ) and the 441-2015  Co-Sponsored PhD "Acoustic Reduction Methods for the Launch Pad ". The work was supported by  Spanish Ministry of Economy and Innovation (MINECO)  and  European Union FEDER  through project  FIS2015-65998-C2-2  and by project  AICO/2016/060  by  Consellería de Educación, Investigación ,  Cultura y Deporte de la Generalitat Valenciana. LJSC gratefully acknowledge the support of PAID-01-14 at  Universitat Politècnica de València.
Patients and data collection We collected data between 30 April and 7 May 2017 within two camps (names omitted for security reasons) hosting displaced people from, respectively, Mosul East (largely reconquered by end January 2017) and Mosul West (more recent arrivals), where fighting persisted until July. Patients were seen by Médecins Sans Frontières outpatient clinics serving the camps. Given security constraints, heavy clinical workload and the need for rapid information for modelling, we asked a female and male medical doctor seeing patients of their same gender to sequentially recruit a fixed sample of 16 study participants, with a balanced gender ratio. Patients were eligible if aged ≥18y, diagnosed with hypertension, diabetes mellitus and/or chronic kidney disease before 2014, not presenting with signs, symptoms or a diagnosis of psychological trauma, and able in the clinician's opinion to answer questions without experiencing distress.
Patients were recruited from only two sites displaced patients elsewhere may have had a different care experience. Generally, patients from Mosul West would have experienced a more prolonged and severe siege, with extensive damage to health services due to dense urban layout and a change in military tactics. The use of physicians to both provide care for and interview patients may have affected how patients reported services, particularly their current care. Self-reporting itself may also introduce bias due to challenges with recall. The study only collected data from patients with diabetes or hypertension; while this may have reflected convenience of recruitment, it is likely that these NCDs were the most prevalent among presenting patients. It seems likely that disruption of services and drug supply would have affected other NCDs in a similar way, though patients with other conditions, e.
Here we estimate how well experts' subjective confidence in their understanding of the graphs aligns with their objective understanding. Attendees of the United Nations Framework Conference in Marrakesh, 2016 (COP22) answered questions on three graphs from the health chapter. This allowed us to gather data on how relevant audiences understand these graphs. The presented results should be considered pilot since our sample of COP22 attendees constitutes a relevant, but not representative sample of the entire audience of the IPCC reports. A lay-sample without particular interest or expertise in climate change answered the same questions for comparison, namely Heidelberg university mathematics students. They contrasted with the climate experts in that mathematics students (i) likely possess less top-down knowledge on climate change and health; but (ii) are likely to be highly numerate, and more used to reason with complex graphs.
Discussion Decisions in the context of climate change and health need to be based on the best scientific evidence available in order to be most effective. Since the human health impacts of climate change generate a large and increasing number of scientific publications per year, however, it would be close to impossible to keep track. The IPCC regularly provides a unified scientific signal to communicate policy-relevant evidence. Here we assessed objective and subjective understanding of health chapter graphs in attendees of the COP22 and a sample of mathematics students. Evidence on how these graphs are interpreted seems necessary, both because large variation was found in how decision-makers interpret climate data in previous research  [23] , and because appropriate development of data visualizations is fundamental to guide adaptation decisions.
First, the "surrounding" nature of the trajectory was analyzed, to investigate whether it was perceived to be surrounding or not. A binomial set of data (1 if the trajectory was perceived to surround subjects/ 0 if not) was analyzed here using a mixed effects logistic regression. Then, the relevant continuous parameters were analyzed via a linear mixed effects analysis followed by a Tukey's post hoc test. All the statistical analyses were conducted using R  [41]  with lme4 package  [42]. For all the results presented in the next section, visual inspection of residual plots did not reveal any obvious deviations from homoscedasticity or normality. P-values were obtained by likelihood ratio tests testing the full model with the effect in question against the model without the effect in question.
All interviews and focus groups were recorded and fully transcribed. The data was managed (coding, categorization), processed (analysis, validity) and interpreted according to the standard thematic content analysis protocol  (Miles & Huberman, 2003 [16] ). This was followed by manual grouping and counting within a framework for analysis with the following dimensions: process applicability (terminology, formalization, tools, remote coordination); patients and parents involvement (roles, time spent, obstacles); French national and regional coordination (roles, nature of support, mechanisms for incorporation); process adoption (perceived benefits and costs, working atmosphere, engagement, acquisitions); and effects (operation, working practices, cooperation with partners). Only results on the dimension regarding patient and parent involvement during the pilot PHARE-M training year are reported in this article.