dataesr/scientific-paragraphs-categorization huggingface dataset:
They are sufficient for the basic work carried out here to present the main concepts taken into account by this new language. However, it would be wise in further work, to better study organizations with administrative processes to improve these models. -The expressiveness of LSAWfP has been analysed on basic routings and its applicability has been established on some examples of processes among which, the one described in this paper. Since LSAWfP also has a solid mathematical foundation, we have no doubt about its applicability in practice. However, it is essential to evaluate it in the modelling of larger processes in terms of number of actors, tasks, events, distribution (geographical distribution), etc. to definitively validate it.
Ongoing Work on LSAWfP There is still a lot of work to be done to refine our models and achieve our goal of producing a complete workflow management infrastructure (a complete and solid workflow language, tools to assist in the design and validation of processes, a workflow execution environment, etc. ). In this section, we present some of the work being currently done on LSAWfP. LSAWfP and workflow patterns: one avenue we are currently exploring is that of measuring the expressiveness of LSAWfP in relation to workflow patterns  [39]. This will allow us to characterize precisely the class of processes (beyond administrative processes) that this language can facilitate the modelling. To conduct this study, it is necessary to study in detail the different workflow patterns proposed in  [39] , then find examples of processes highlighting these patterns and finally, find out how LSAWfP can help to model these processes.
Conclusion In this paper, we have proposed a new workflow language called LSAWfP which allows, through a simple grammar-based formalism, to specify administrative business processes. Like any traditional workflow language, LSAWfP allows to specify basic flows (sequential, parallel, alternative and iterative) that are generally found in workflow models; particularly, it focuses on the modelling of each of the process scenarios using an artifact. Moreover, LSAWfP allows to model the main characteristics of business processes (their lifecycle, their informational and their organizational aspects); it also allows to address certain security aspects of administrative workflows. In fact, LSAWfP allows the.
Background: Hereditary Hemorrhagic Telangiectasia (HHT) is an autosomal dominant disorder characterized by multiple telangiectases and caused by germline disease-causing variants in the ENG (HHT1), ACVRL1 (HHT2) and, to a lesser extent MADH4 and GDF2, which encode proteins involved in the TGF-β/BMP9 signaling pathway. Common visceral complications of HHT are caused by pulmonary, cerebral, or hepatic arteriovenous malformations (HAVMs). There is large intrafamilial variability in the severity of visceral involvement, suggesting a role for modifier genes. The objective of the present study was to investigate the potential role of ENG, ACVRL1, and of other candidate genes belonging to the same biological pathway in the development of HAVMs. Methods: We selected 354 patients from the French HHT patient database who had one disease causing variant in either ENG or ACVRL1 and who underwent hepatic exploration.
We first compared the distribution of the different types of variants with the occurrence of HAVMs. Then, we genotyped 51 Tag-SNPs from the Hap Map database located in 8 genes that encode proteins belonging to the TGF-β/BMP9 pathway (ACVRL1, ENG, GDF2, MADH4, SMAD1, SMAD5, TGFB1, TGFBR1), as well as in two additional candidate genes (PTPN14 and ADAM17). We addressed the question of a possible genetic association with the occurrence of HAVMs. Results: The proportion of patients with germline ACVRL1 variants and the proportion of women were significantly higher in HHT patients with HAVMs. In the HHT2 group, HAVMs were more frequent in patients with truncating variants. Six SNPs (3 in ACVRL1, 1 in ENG, 1 in SMAD5, and 1 in ADAM17) were significantly associated with HAVMs. After correction for multiple testing, only one remained significantly associated (rs2277383).
Patients This is an non-interventional study including DNA from 354 patients with a diagnosis of HHT confirmed by molecular genetics (107 with ENG disease-causing variants and 247 with ACVRL1 disease-causing variants) and who benefited from systematic hepatic evaluation by ultrasound Doppler (n = 247), contrast abnominal CT (n = 51), or both exams (n = 56). The patients were collected through the three laboratories involved in HHT genetic diagnosis in France: Lyon (n = 248), Paris (n = 91), and Poitiers (n = 15). The number of patients with MADH4 disease-causing variants was too low (< 30) for statistical analyses. Patients had given written consent for the study of genetic factors involved in HHT according to the French bioethics law. Genetic and clinical data have been collected in the French HHT patient database (CIROCO) from 2005 to 2013.
SNP selection and genotyping As potential candidate modifier genes for HHT, we selected ACVRL1, ENG and MADH4, the ligands (BMP9/GDF2 and TGFB1) and the receptor of the TGF-β signaling pathway (TGFBR1), and two main transcription factors implicated in the TGF-β signaling pathway (SMAD1 and SMAD5). Fortyeight Tag-SNPs from the HapMap project were chosen using Haploview V4. 1 software (https://www. broadinstitute. org/ haploview/haploview)  [19]. All SNPs with a maximum r2 value of 0. 8 (pairwise tagging approach) and a minor allele frequency (MAF) of at least 5% in CEU HapMap individuals (https://ftp. ncbi. nlm. nih. gov/hapmap/genotypes/2010-05_pha-seIII/hapmap_format/polymorphic/) were selected: ACVRL1 (rs7956340, rs11169953, rs11169954, rs1150051, rs2277383, rs706819, rs2293092), ENG (rs10987759, rs4836585, rs16930129, rs10121110, rs2005129, rs11792480, rs17557600, rs3739817, rs10819309, rs10987746, rs1330684), GDF2 (rs3758496, rs12252199, rs9971293, rs9421799), MADH4 (rs10502913, rs948588, rs12458752), SMAD1 (rs6537355, rs959641, rs2118438, rs714195, rs1016792, rs13120142, rs12505085), SMAD5 (rs5008734, rs746994, rs746993, rs17749249), TGFB1 (rs2241715, rs4803455, rs8110090, rs11466338, rs11466345), and TGFBR1 (rs10988705, rs10819638, rs6478974, rs10739778, rs10512263, rs928180, rs10733710).
Analysis of clinical variables The effect of clinical variables (sex, age at hepatic screening, type of pathogenic variant, gene responsible for HHT) on the phenotype (groups 1, 2, and 3) was tested with two sided Cochran-Armitage trend tests (R package DescTools) for qualitative data or one-way analysis of variance for quantitative data. The proportion of missense variant in HHT1 and HHT2 was compared with Pearson Chi-Squared test. Some patients being related, the independence assumption may not exactly be met so the effect of these variables was confirmed in multivariate mixed-effect logistic regression models. In addition, when the type of variant is studied, there might be a bias due a founder mutation  [24]  that was found in 55 HHT2 patients. Analyses were thus performed both with and without these 55 patients.
Distribution of the ACVRL1 and ENG disease-causing variants On a total of 107 HHT1 patients, 44 (41. 1%) had hepatic involvement, including 10 individuals of group 3. There were 247 HHT2 patients: 187 (75. 7%) had hepatic disease including 83 of group 3. The proportion of HHT2 patients increased significantly according to the severity of HAVM (Table  1  and p < 10 -5 in the mixed logistic model). The distribution of the types of disease-causing variants for ACVRL1 (HHT2) and ENG (HHT1) was different: the proportion of missense was higher in the ACVR L1 group (Table  2 , all patients: p < 0. 0002, founder mutation bias removed: p < 1,7 × 10 -8 ) in accordance with data from the international mutation database (http:// arup. utah. edu/database/HHT). In the HHT2 group, the proportion of truncating variants increased with the severity of liver involvement.
This means that one should refrain from feeling comfortable with the imposition of technological innovations that inevitably call for specific and often rigid logics of interaction among the different market actors  (Melacini et al. , 2018). Equally, the data show how important it is to understand the operationalisation of the technologically driven service in real-life conditions where both proprietary (eretailers; local authorities etc. ) technological platforms (hardware and software) are mingled with open source applications (Google map, weather apps). Regarding the time constraint in particular, contrary to expectation of further distress, the data show e-delivery contractors outstanding adaptation and that TBMP in effect acts as a motivator that positively influence these independent workers' behaviours and broader collective solutions towards more sustainable and valuable e-delivery within the sociospatialised ULMD  (de Souza et al.
38 million hectares, which corresponded to production of 5. 0 million tons. The seven regions selected account for more than 75% of that production. We approached the empirical analysis of the contractual agreements in the Italian durum wheat chain using a two-step method. First, a direct survey was carried out to collect information on the supply chain organization and the use of contractual agreements at farm level in the period 2015-2016. In particular, we asked farmers how they regulated their production and sale of durum wheat, and why they chose to sign or not sign a written contract. For this purpose, a questionnaire 1 was submitted to a sample of 300 durum wheat farms belonging to the Italian Farm Accountancy Data Network (FADN) database. 2 Seven Italian regions were selected for distribution of the questionnaire: Emilia-Romagna, Abruzzi, Marche, Campania, Tuscany, Apulia and Sicily.
3 The sample accounted for about 25% of the FADN durum wheat population in these regions. The farms were selected taking into account the province where they were located, the degree of specialization in durum wheat growing and size classes of durum wheat hectares. The sample included farms above two hectares, highly differentiated by size and production specialization. The farm size under durum wheat varied from just over one hectare to more than 500 hectares (Table  1 ). Thirty-nine companies out of 300 did not respond to answer the questionnaire and the final panel size was 261 respondents. Data on contracts were collected by professional subjects in face-to-face interviews with farmers using a questionnaire, which was organized in four sections: i) General information about socio-demographic characteristics (age, education) and farm characteristics (total hectares in production, total hectares in durum wheat, product quantity, etc.
Limitations and Future Research Directions Although by offering a large-scale cross-country investigation of the relationship of age and perceived employability and covering two levels of analysis for its predictors (i. e. , individual and country level), our study makes an important contribution to the literature, it is also subject to a range of limitations that are common to statistical surveys across many countries  (Bryman, 2016). Our first limitation concerns the measurement of our variables. Measuring HRDPs demands recall from our respondents as we asked them to report the HRDPs in which they have taken part over the course of their careers. It is not possible to fully rule out a positive bias and over-recall of the HRDPs the respondents were involved in during their career. Future research should ideally involve multi-source data from employees and their employers/supervisors that can provide an objective measure of HRDPs.
paper therefore makes two critical contributions. First, we consider the role of organizational initiatives in shaping how individuals construe their perceptions of external employability (Forrier & Sels, 2003). In doing so, our study goes beyond the dominant individual perspective on employability, which has nevertheless been criticized more than once (Clarke, 2018; Forrier et al. , 2018; McQuaid & Lindsay, 2005). Second, we examine whether the proposed negative relationship between age and perceived external employability is universal across country contexts. We leverage a large crosscountry dataset, thus moving employability research away from single-country or fewcountry studies (Froehlich, Beausaert, & Segers, 2016) toward international comparisons and contribute to the scarce body of multi-level research that simultaneously considers contextual factors at different levels when studying employability.
Survey The survey was given to employees working in Indian organizations that use high technology in their operations. The organizations use big data analytics as part of their decision-making procedure and these capabilities are developed in-house. The data was collected for the year 2018 using an online questionnaire for respondents from diverse fields. We used the 5-point Likert Scale for our questionnaire (1-strongly disagree, 2-disagree, 3-neutral, 4-agree, and 5-strongly agree)  (Dwivedi et al. , 2013; Kim et al. , 2009; Hair et al. , 2013). To confirm the validity, reliability and appropriateness of the questionnaire, it was pre-tested by 20 respondents. The weblink of the questionnaire was distributed to approximately 1100 respondents, of which we received data from 290 respondents.
After evaluating and examining all 290 responses, a total of 209 (19% response rate) completely filled-out and usable responses were considered for the study. The data was standardized and there were no cases of missing data, zero variance or rank-related problems. Respondents from a broad agerange from 20-60 years and with diverse academic qualifications were considered for this study. Each segment of respondents from different age groups represents a different decisionmaking position, which creates a possibility of flexibility for the system; details are given in Table  1  below. Fifty percent (104) of the total 209 respondents belonged to the 20-30-yearold group and the lowest number of respondents were from the 41-60 age range. With regard to educational qualification, 61% (128) of the 209 respondents were post-graduates, whereas only 2% (5) of respondents held a PhD.
Introduction Firms are increasingly turning to loyalty programs (LPs) to manage customer relationships. Such programs help firms identify the most valuable customers, improve customer retention, and enhance the efficiency of marketing communications. Customers also often benefit because participating in these programs allows access to customized products and services, relevant promotions, and enable more personalized and efficient interactions with the firm. This paper takes these positive features as given and focuses on often overlooked societal consequences of LPs. The goal of this paper is to show how researchers and practitioners can enhance both research and practice by viewing the LP/big data union through a societal lens. We propose a framework to enable academics and practitioners to consider carefully the societal impact of an LP's design and its management.
As a result, LPs trigger (1) privacy concerns related to the collection and usage of finegrained, identifiable data on consumers, (2) inequality concerns related to the design of the program where consumers can or cannot enter/benefit, and (3) sustainability concerns related to the usage of rewards. So, the inherent link between LPs and big data naturally links LPs to a variety of societal issues that makes this marketing instrument a worthwhile focus for the application of the societal lens. Still, we consider it worthwhile to expand the framework to consider other societal facets, other big data era consequences that impact privacy, inequality, and sustainability, or on how new datasets such as biometrics, social media text, and social network information are changing LPs' societal impact.
Born in the 1960s, the LCA study presents four stages: the first and most important is the definition of the context and the functional unit (function of the product and definition of its environment to set the boundaries of the study ), then the inventory of all the elements constituting the product, the evaluation of the impacts and finally the interpretation of the results. Software were designed to move from the inventory of all the constituent elements of the product to the associated environmental impacts, such as SimaPro, and are linked to widely supplied databases such as Ecoinvent or Idemat  [13]  which are valid especially for industrialized countries. The quantified impacts are the resources consumed and the emissions to air, water and soil. Figure  2 , from the Innomat training  [14] , presents the environmental impacts of LCA in intermediate ("midpoint"), final and unique indicators which aggregate the previous ones.
This evaluation is shown schematically in the diagram in Figure  3. Data is collected via operational reports or surveys and then compared to target values to normalize the results, so all indicators are quantitative even if they deal with quality. The choice of indicators is important because they must be clearly defined, simple to understand and apply, transparent and fair. However, Ilskog warns about his method which cannot cover all the diversity of contexts by itself, it is necessary to add specific indicators to certain projects, it should rather be seen as a tool for decision-makers, a discussion support allowing to understand the impacts of an electrification project on the sustainable development of a community. This multi-criteria assessment, like many others, assesses an energy access system after it has been used in relation to consumers.
These include principally what are called the 'price' effect, and the 'income' effect. 4 The main source of data for investigating the aggregate employment impact of adopting robots are the figures on robot installations collected by the International Federation of Robotics (IFR) since the 1990 at the industry-and country-levels. 5 Key contributions using this data covering European nations are the studies by  Dauth et al. (2017)  for regions in Germany, and  Graetz and Michaels (2018)  for 14 EU-member countries, Korea, the United States and Austria. Dauth et al. (2017)  identify significant direct negative effects of robot adoption on employment in German manufacturing between 1993 and 2014, accounting for almost a quarter of the decline in manufacturing jobs over this period. This negative impact however is fully compensated for by increases in employment in service sectors implying that there are important income effects compensating for the loss of jobs due to robots in adopting industries.
The authors use a human intelligence crowdsourcing platform, CrowdFlower, to derive what they refer to as suitability for machine learning (SML) scores at the task level. They consider the 18,156 tasks for 964 occupations in the O*NET database and map them into 2,056 direct work activities that are shared across occupations. The SML scores are based on a rubric that is designed to capture the extent to which the work activity is well-structured in the sense that there is a clear mapping between inputs or actions and outputs that can be learnt by the machine with sufficient data. If there are difficulties in measuring this relation, as is the case for unstructured social interaction or much complex cognitive work, then the work activity receives a low SML score. Brynjolfsson et al. (2018)  find in general that there is considerable variability across occupations in the susceptibility of their component tasks to automation with only a few having high SML scores for all tasks implying that automation technologies are unlikely to result in the elimination of entire occupations.
Nowadays, the problem of the model's applicability domain (AD) definition is an active research topic in chemoinformatics. Although many various AD definitions for the models predicting properties of molecules (Quantitative Structure-Activity/Property Relationship (QSAR/QSPR) models) were described in the literature, no one for chemical reactions (Quantitative Reaction-Property Relationships (QRPR)) has been reported to date. The point is that a chemical reaction is a much more complex object than an individual molecule, and its yield, thermodynamic and kinetic characteristics depend not only on the structures of reactants and products but also on experimental conditions. The QRPR models' performance largely depends on the way that chemical transformation is encoded. In this study, various AD definition methods extensively used in QSAR/QSPR studies of individual molecules, as well as several novel approaches suggested in this work for reactions, were benchmarked on several reaction datasets.
The percentage of X-inliers in test data is the coverage of the model. At one extreme, all objects are considered as X-inliers and therefore a model can universally be applied to any test object with the same reliability. In this case, the coverage is 100%. This, obviously, contradicts the theory and practice of applying QSAR/QSPR models, which in the general case cannot be considered universal laws of nature. At the opposite extreme, only the training data are considered as X-inliers, while all other objects are considered as X-outliers. Therefore, the coverage is 0%. Such models are obviously useless in practice because they cannot be used to predict the properties of new objects. Therefore, AD for QSAR/QSPR models that are useful in practice should be between these two extremes. In this article, we find optimal AD definitions by maximizing certain AD performance metrics.
Its positive values indicate the improvement in the property prediction within AD. If no reactions are left inside or outside AD, then OIR is considered equal to 0; (iii) The Outliers Criterion metric shows how well AD definition detects Y-outliers. First, property prediction errors are estimated in cross-validation for all reactions in a dataset. The reactions for which the absolute prediction error is higher than 3× RMSE are identified as Y-outliers, while the rest are considered as Y-inliers. Y-outliers (poorly predicted) that are predicted by AD definition as X-outliers (outside AD) are called true outliers (TO), while Y-inliers predicted by AD definition as X-inliers (within AD) are called true inliers (TI). False outliers (FO) are Y-inliers that are wrongly predicted by the AD definition as X-outliers, while false inliers (FI) are Y-outliers that are wrongly predicted by the AD definition as X-inliers.
We have found in the initial stages of the study that ∆R 2 _AD and AUC_AD are not suitable objective functions for optimizing thresholds and hyperparameters of AD definition models, because they often lead either to very small coverage with high accuracy (when only a few points very similar to training examples are left within AD) or, vice versa, high coverage and low accuracy (because a very small number of excluded examples can only slightly improve the accuracy of the whole dataset). The ∆R 2 _AD and AUC_AD metrics appear not to be able to distinguish between these two modes. Since the resulting AD models selected using these metrics had very different coverage, their comparison was difficult. For this reason, we refused to use these metrics to benchmark different AD definition models.