dataesr/scientific-paragraphs-categorization huggingface dataset:
A Hybrid Modeling Method Based on Expert Control and Deep Neural Network for Temperature Prediction of Molten Steel in LF Zi-cheng XIN,  1)  Jiang-shan ZHANG,  1)  Jin ZHENG,  2)  Yu JIN  2)  and Qing LIU 1) * 1) State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing, 100083 China. 2) Tangshan Branch, Hebei Iron and Steel Co. , Ltd. , Tangshan, Hebei, 063000 China. (Received on June 2, 2021; accepted on November 16, 2021; J-STAGE Advance published date: January 8, 2022)   The temperature control of molten steel in ladle furnace (LF) has a critical impact on steelmaking production. In this work, production data were collected from a steelmaking plant and a hybrid model based on expert control and deep neural network (DNN) was established to predict the molten steel temperature in LF.
In this study, a hybrid model based on the expert control and the DNN algorithm was established to predict the temperature of molten steel in LF. The original production data collected from a steelmaking plant in China were preprocessed to delete outliers, and then the correlation analysis between the input and output variables was carried out. Moreover, the hybrid model was evaluated and compared with other models by using different evaluation indexes. It is expected to establish a more accurate and applicatory hybrid model to predict the temperature of molten steel in LF.
Data Cleansing The production data of LF refining process were collected  from a steelmaking plant in China. The original data were processed by using boxplot. 31, 32) The boxplot consists of five statistics, including lower quartile (Q 1 ), median (Q 2 ), upper quartile (Q 3 ), Q 1 -1. 5IQR, and Q 3 + 1. 5IQR. The interquartile range (IQR) is defined as Q 3 -Q 1. In boxplot, the outlier data took values below Q 1 -1. 5IQR or above Q 3 + 1. 5IQR, as shown in Fig. 5. Boxplot is a widely used method to detect outliers in sample data. The advantage of boxplot is that it is not influenced by outliers, so it can describe the discrete distribution of data in a relatively stable way, and it is also conducive to data cleansing. In this study, the original data were processed using boxplot, and the outliers below Q 1 -1.
5IQR and beyond Q 3 + 1. 5IQR were eliminated to realize the data cleaning. The outliers distribution of original data were shown after the original data was normalized, as shown in Fig. 6. There are 2 000 groups of production data in total, as the data were obtained based on the boxplot and production operation rules. The data distribution of a single variable and the descriptive statistics for all input and output vari-ables of the prediction models are showed in Fig. 7  and Table  4. The range of the turnover cycle of ladle and the refining time was 28-90 min and 18-55 min, respectively. The value of weight for molten steel ranged from 150 000 to 158 260 kg. The value of starting temperature ranged from 1 518 to 1 603°C. The range of the heating duration time was 155-1 256 s. The range of the argon consumption was from 15 000 to 48 000 NL.
05 between T 1 and turnover cycle of ladle; the p-value is greater than 0. 05 between T 1 and weight of molten steel. Taken together, these results indicated that the relationship between starting temperature of molten steel, refining time, heating duration time, argon consumption and T 1 reach very significant correlation, and the relationship between turnover cycle of ladle and T 1 reach significant correlation. However, there is no significant correlation between T 1 and weight of molten steel. ] 34)  Meanwhile, the initial energy of molten steel is determined by the weight of molten steel. Thus, the weight of molten steel was considered when the hybrid model was established. L2 In order to improve the accuracy and accelerate the convergence of model, the data processed by using the boxplot and production operation rules were normalized.
Comparison of the DNN Model with Other Models Based on the Pearson correlation analysis, the relationship tends to be linear between the T 1 and a part of input parameters, such as turnover cycle of ladle, starting temperature of molten steel, refining time, heating duration time, argon consumption respectively. However, there is a nonlinear feature between the weight of molten steel and the T 1 , which indicated that there are complex relationships (hybrid linear and nonlinear relationship) between input variables and output variables. Meanwhile, in the actual production, the weighing system has an error of more than 10 kg or even 100 kg; for example, the hopper weighing error is ± 10 kg and the crown block weighing error is ± 600 kg. In addition, the production datasets inevitably even contain fault data, abnormal data, or missing data, which led to the potential noisy data in the production dataset even after preprocessing.
Therefore, on the premise of ensuring the computational accuracy of DNN model, the improvement of computational efficiency should also be considered. 40) (3) Engineering application problem. On the one hand, LF refining is a complicated physical and chemical process at high temperature, and there is a very complex nonlinear relationship between different variables. The complex process cannot be described completely and accurately by using the DNN model. Meanwhile, the expert control should be adjusted and optimized in real time to improve the hit ratio of the hybrid model, according to the change of the production condition, such as the change of the alloy and slag making materials supplier. On the other hand, in the actual production, the original production datasets inevitably contain fault data, abnormal data, and missing data, which will affect the calculation accuracy of the hybrid model.
We have a copy of this work from the collection of the Jesuit library in Beijing, with frequent annotations in the handwriting of Verbiest, 66 who mentions Argoli's table in his own later account of the 'restoration of European astronomy' in 1668-9. 67 It is highly significant that this text has inked horizontal marks next to the entry rows for the ephemeris data for 27 and 28 December 1668, the first two dates for which Verbiest had to make shadow predictions. Since Argoli provides ready-made computations of solar longitudes, using these tables would have spared Verbiest a considerable amount of labour and uncertainty. Even if he did not use them as the basis of the predictions he submitted, a cross-check with Argoli's tables would still have given him valuable reassurance that he had not made any gross error in his calculations.
Methods In this systematic analysis, we expanded our global RSV disease burden dataset by obtaining new data from an updated search for papers published between Jan 1, 2017, and Dec 31, 2020, from MEDLINE, Embase, Global Health, CINAHL, Web of Science, LILACS, OpenGrey, CNKI, Wanfang, and ChongqingVIP. We also included unpublished data from RSV GEN collaborators. Eligible studies reported data for children aged 0-60 months with RSV as primary infection with acute lower respiratory infection in community settings, or acute lower respiratory infection necessitating hospital admission; reported data for at least 12 consecutive months, except for in-hospital case fatality ratio (CFR) or for where RSV seasonality is well-defined; and reported incidence rate, hospital admission rate, RSV positive proportion in acute lower respiratory infection hospital admission, or in-hospital CFR.
Added value of this study We substantially expanded our global RSV burden dataset by including 113 new studies from the literature review update and new unpublished data from 51 studies shared through RSV GEN. With these data and improved methods, we have now been able to estimate RSV morbidity and mortality burden for hospital settings and overall, and focus on narrower infant age groups that are targeted by RSV prophylactics in development. With data on RSV community mortality, we estimated the overall RSV mortality burden in different age groups-one death was attributable to RSV in every 50 deaths in children aged 0-60 months and in every 28 deaths in children aged 28 days to 6 months. For every RSV-associated acute lower respiratory infection in-hospital death, there were approximately three deaths attributable to RSV in the community.
Implications of all the available evidence By incorporating the latest RSV community mortality data, we provide robust estimates of global and regional burden of RSVrelated mortality. Our findings, together with other existing RSV disease burden estimates, provide a comprehensive global overview of RSV morbidity and mortality burden in infants and young children. With many RSV prophylactic products in the pipeline, our estimates by narrower age bands provide important baseline information to the introduction, prioritisation, and evaluation of these products. Further evidence is warranted to understand the implications of the potential age-shifts in peak RSV burden to older age after administration of RSV prophylactics to infants younger than 6 months. efficacy among healthy preterm infants in a phase 2b trial, 7 reduced medically-attended RSV lower respiratory tract infections in healthy late-preterm and term infants in its phase 3 trial (NCT03979313).
8 Moreover, two maternal vaccine candidates aimed to protect infants through transplacental transfer of vaccine-induced maternal antibodies (RSV MAT [GlaxoSmithKline; NCT04605159] and RSVpreF [Pfizer; NCT04424316]), and one monoclonal antibody (MK-1654 [MSD; NCT04767373]) have initiated recruitment for the phase 3 clinical trials, and are expected to complete in the next 3-5 years. In this study, we aim to estimate RSV-associated acute lower respiratory infection morbidity and mortality in 2019 at global, regional, and national levels in children aged 0-60 months, with a primary focus on narrower infant age groups that are targeted by RSV prophylactics under development, and on overall mortality.
Unpublished RSV data Previously, we established the Respiratory Virus Global Epidemiology Network (RSV GEN) to collect unpublished data (including re-analysis of published data), applying common case definitions and approaches to data analysis, yielding unpublished data from over 70 individual study sites. 3 For this study, we continued to encourage existing members of RSV GEN to contribute new RSV data while inviting other investigators with eligible RSV data to join this collaborative network. This resulted in novel unpublished data from 51 study sites to supplement published data and data included in our previous estimates (appendix pp 9-11).
For RSV-associated acute lower respiratory infection incidence, we also estimated country-specific RSVassociated acute lower respiratory infection incidence rate and episodes in children aged 0-60 months in 137 LMICs using a risk-factor based model similar to previous work (appendix pp 13-14). 3 For RSV-associated acute lower respiratory infection hospital admission, we validated the estimates with independent data by applying the metaestimates of RSV positive proportion among acute lower respiratory infection hospital admissions (through GLMM) in our study to the external sources of acute lower respiratory infection hospital admission estimates (appendix p 19 and p 42). 14, 15  We obtained meta-estimates of in-hospital CFR for RSV-associated acute lower respiratory infection hospital admission by region (UNICEF country development status and World Bank Income classification) and age band using GLMM.
Results In addition to the 317 studies included in the previous review, 3 we identified and included 113 new eligible studies from the literature review update and included new unpublished data from 51 studies from RSV GEN collaborators. This brought the total number of studies included in the present analysis to 481. Among the 481 studies, 140 contributed to the estimate of RSVassociated acute lower respiratory infection incidence or hospitalisation rate; 339 contributed to the estimate of RSV-positive proportion among acute lower respiratory infection hospital admission; 147 contributed to the estimate of RSV-associated in-hospital deaths; and 15 studies contributed to the estimate of RSV overall deaths (appendix pp 20-23). Study-level characteristics are presented in the appendix (pp 24-31).
Number of episodes were were rounded to the nearest 1000. RSV=respiratory syncytial virus. UR=uncertainty range. *Global estimates were obtained by summing the numbers of developing and industrialised countries for each of the 1000 samples in the Monte Carlo simulation. †The point estimates and uncertainty range estimates are not necessarily equal to the sum of the estimates by finer age bands; this is because the studies that contributed to different age-group-specific estimates were different. ‡Data in parentheses indicate the number of studies with imputed data; comparisons between estimates using imputed data and not using imputed data are presented in the appendix (p 44).
Discussion In this study, we expanded our existing global RSV disease burden dataset by including 113 new eligible studies from the literature review update and new unpublished data from 51 studies shared through RSV GEN. We estimated that globally in 2019, there were 33•0 million RSV-associated acute lower respiratory infection episodes, 3•6 million RSV-associated acute lower respiratory infection hospital admissions, and 26 300 RSV-associated acute lower respiratory infection in-hospital deaths in children aged 0-60 months. In infants aged 0-6 months, there were 6•6 million RSV-associated acute lower respiratory infection episodes, 1•4 million RSV-associated acute lower respiratory  infection hospital admissions, and 13 300 RSV-associated acute lower respiratory infection in-hospital deaths.
Because of the expanded dataset, we could observe a larger gap in RSV disease burden between LMICs and high-income countries in children aged 0-6 months than in children aged 0-60 months. The disproportionately high RSV burden in the younger age groups in LMICs warrants more extensive community case management and effective and affordable immunisation programmes. The gap is even larger when it comes to hospital admission, reflecting the fact that access and availability to hospital care is still limited in LMICs. Despite higher incidence in the community, the RSV-associated acute lower respiratory infection hospital admission rate in LMICs was similar to that in high-income countries for children aged 0-60 months, and for children aged 0-6 months, astonishingly, the hospital admission rate in LMICs was consistently lower than that in high-income countries.
It is unknown how the COVID-19 pandemic could affect RSV disease burden in the long term. Our estimates could serve as a reference for understanding RSV epidemiology in the context of the ongoing COVID-19 pandemic. Despite these limitations, our revised estimates are based on a substantially expanded dataset (including the community mortality data) and improved methodology. For the first time, we managed to break down the population of children aged 0-6 months into narrower age bands for both morbidity and mortality estimates that are essential for estimating the impact of RSV prophylactics. These estimates should provide a comprehensive global overview of RSV morbidity and mortality burden in infants and young children. With the numerous RSV prophylactic products in the pipeline, our estimates provide an important baseline profile of RSV disease burden for evaluating their potential clinical impact and cost-effectiveness of public health programmes.
Data are n, incidence rate per 1000 children per year (UR), or n (UR). RSV=respiratory syncytial virus. UR=uncertainty range. *Global estimates were obtained by summing the numbers of developing and industrialised countries for each of the 1000 samples in the Monte Carlo simulation. †The point estimates and uncertainty range estimates are not necessarily equal to the sum of the estimates by finer age bands; this is because the studies that contributed to different age-group-specific estimates were different. ‡Data in parentheses indicate the number of studies with imputed data; comparisons between estimates using imputed data and not using imputed data are presented in the appendix (p 44).
The SiW-ECAL prototype Within the R&D program for the SiW-ECAL, we distinguish two main versions of the prototypes: the physics prototype, and the technological prototype. The physics prototype was the first to be developed and provided a proof-of-concept for PF calorimetry  [2, 9, 3, 4, 5, 6] , where the electronic components were placed outside the interaction region, used an external trigger system, and had no constraints on the power consumption. After this successful first iteration, the following years have been devoted to the technological prototype to address engineering challenges at ILD, such as electronic components inside the detector, implementing power pulsing, achieving required compactness, among others. In this work, we present preliminary results using data recorded with the technological prototype in 2017.
METHODS A retrospective monocentric study was conducted at the University Hospital of Tours, France, which is a reference centre for vascular malformations. Inclusion criteria were extracranial AVM confirmed by magnetic resonance imaging (MRI) and treatment with a systemic beta-blocker between January 2012 and May 2020, as well as consent for data collection. Exclusion criteria were: intracerebral AVMs and patients who received beta-blockers for an indication other than the AVM. All data were extracted from patients' medical records (demographic data, data on the AVM and beta-blockers, imaging). Patients were followed-up at consultation or contacted by telephone to collect self-reported outcomes. The primary endpoint was the patient's overall perception of treatment efficacy on a numerical scale from -100 to +100 (-100 being a harmful treatment and +100 being a high efficacy of the treatment).
Venetoclax (VEN) in combination with low-dose cytarabine (LDAC) is FDA-approved for the treatment of unfit patients with newly diagnosed AML ineligible for intensive chemotherapy, based on a response rate of 54% (complete remission with or without blood count recovery [CR/CRi]) in the original phase Ib/ II study. 1  The VIALE-C phase 3 study (ClinicalTrials. gov Identifier: NCT03069352), compared VEN vs placebo (PBO) in combination with LDAC in 211 patients with untreated AML ineligible for intensive chemotherapy. 2, 3 The primary overall survival (OS) endpoint was event-driven and did not show a significant benefit in favor of VEN + LDAC after a median follow-up time of 12 months. 2 This initial analysis was associated with substantial early censoring of patients with <6 months follow-up.
Study setting This is an international hospital-based study in the UK, Netherlands and Denmark (and planned to open in Belgium and Sweden). Potential candidates are identified in the endoscopy suite following (i) investigation of new bowel symptoms, (ii) personal bowel surveillance or (iii) bowel screening and are referred to a colorectal surgeon or the colorectal cancer multidisciplinary team (MDT), where eligibility is confirmed following review of clinical data (Table1).
Recruitment STAR-TREC is a hospital-based study. Candidates will generally be identified in the endoscopy suite following referral (i) for the investigation of new bowel symptoms, (ii) as part of a personal bowel surveillance programme or (iii) through national bowel screening. Subjects will then be referred to either a colorectal surgeon or the colorectal cancer MDT meeting. Recruiting trial sites are likely to act as 'regional hubs' for the early rectal cancer service. They will specialize in organ-saving techniques while being able to provide standard (radical surgery) treatment. Following informed consent, which will be conducted by medically qualified individuals in accordance with good clinical practice standards, confirmation of eligibility and trial entry will be conducted using electronic remote data capture.
TA B L E 1 STAR-TREC trial registration data Elective irradiation of lateral or presacral lymph nodes cranial to or above the mesorectal volume is thus not indicated. This results in a significant reduction of the irradiated target volume and is expected to result in less toxicity  [22, 23]. Detailed radiotherapy guidelines and an international quality assurance programme are employed to ensure high quality radiotherapy delivery. Timing of response assessment is calculated from the start of radiotherapy treatment, rather than on completion, to improve comparison of tumour regression between SCRT and CRT.
Other dichotomized outcomes will be analysed similarly. HRQoL (and continuous outcomes) will be analysed using hierarchical repeated measures models to model each patient's trajectory through time, to account for the multiple data points per patient. Analysis of toxicity will evaluate the rate of major treatmentrelated complications in each group. Secondary analyses will incorporate the partially randomized standard surgery comparator. This partially randomized TME surgery reference group will provide data relating to the incidence of major treatment-related toxicity and HRQoL following TME surgery for early-stage rectal cancer, without the use of radiotherapy. Although the non-randomized analysis means that conclusions must be treated with extra caution, this analysis will provide valuable additional information for patients with early-stage rectal cancer who are balancing the risks and benefits of different treatment strategies.
| Data analysis To obtain the GPGI satisfaction scores of residents, we calculated at the respondent level (j) the sum of each constituent's (i) weighted performance scaled to 100 as follows: We analysed the data at two levels. First, we used all 1350 responses (i. e. including constituents with null impact on respondents HWB), and second, we analysed only impacted constituents (343 responses). We tested differences on the continuous variables 'relative importance' and 'GPGI' using the nonparametric Dunn test for unbalanced sample sizes  (Dinno, 2017). Additionally, the categorical variable 'impact' was classified as positive for all responses indicating 'Improved a little' and 'Improved a lot' and negative for all responses indicating 'A lot worse' and 'A little worse'. We used R to conduct all analyses (R Development Core Team, 2020).
Research in context Evidence before this study We identified a recent systematic review and meta-analysis of oesophageal squamous cell carcinoma (ESCC) risk factors in Africa from studies published until March 31, 2019, and updated it to June 20, 2021, by searching the Embase, PubMed, and Ovid databases using the search term "*esophag* AND (cancer OR carcinoma OR malignan*) AND (Africa OR [list of individual African countries])" and screening for studies assessing alcohol as a risk factor. The meta-analysis estimated a pooled odds ratio (OR) of 2•28 for alcohol consumption associated with ESCC risk. This OR was generated using eight estimates from six studies, four of which were in South Africa. Individual estimates showed a high degree of heterogeneity (ORs 0•90-5•24; I² of 92•1%) and the exposure definition was not consistent between studies.
Added value of this study This three-country case-control study presents data from a harmonised comprehensive alcohol assessment that was sensitive to the multitude of traditional and commercial beverages consumed in each country's setting. These data were used to derive multiple alcohol exposure metrics. This approach has yielded both intracountry and intercountry positive associations for several alcohol exposure metrics, including ever drinking, daily number of drinks, estimated ethanol intake, and type of drinker (high vs low alcohol-byvolume [ABV] drinks), apart from men in Malawi for whom there was no positive association. These findings show that alcohol consumption contributes to the risk of ESCC in the east African high-incidence corridor, which was a factor previously downplayed because of inconsistent and uncompelling findings.