dataesr/scientific-paragraphs-categorization huggingface dataset:
Based on Step 2, only Austrian fiber manufacturing uses the environmentally friendly manufacturing technology, which provides much lower amounts of non-renewable energy use (NREU) than the normal technology in the other locations. We also consider cost and CO 2 e from electricity used in wastewater treatment that are calculated based on the study of Yin et al. [53]. Distance and delivery time between locations for assigned transportation mode are obtained from Searates. com, a logistics provider's website. Trucking is used for domestic transportation in China and between factories and ports for international transportation by ship, as well as international transportation between Germany, Italy, Poland, and Lithuania. International transportation between the other locations uses shipping. More manufacturing data are in Tables A1-A8 in Appendix A.
Moreover, users may use our approach to find a set of low cost and CO 2 e supply chains and select a final supply chain from them with qualitative criteria and approach. Another limitation is the difficulty of data collection, though this can be lowered by choosing only one or two main suppliers per each supply stage with a limited number of potential locations. Governments can help overcome the difficulty by having a database providing all cost and emission factor data, such as electricity emission factors, import taxes, and prices of industrial water, electricity, waste collection and treatment, in order to support research and practices on sustainable supply network design, potentially resulting in industrial and sustainability improvement. The purpose of showing the model application is to demonstrate how to use the model with real data in practice, as well as the model's potential to reveal the lowest or optimized cost and CO 2 e supply chains, their most important factors, and possible local and global risks that impact the lowest cost and CO 2 e supply chains.
Adverse events Adverse events are, according to the definitions, any unfavourable or unintended event affecting patients on study. In cases of prolongation of hospitalisation, death or significant clinical sequelae, these events are defined as serious adverse events (SAEs), the occurrence of which the study sponsor (Assistance Publique -Hôpitaux de Paris, APHP) and the Data Safety Monitoring Board (DSMB) will be informed at short notice. During protocol treatment, all deaths, all SAEs that are life-threatening and any unexpected SAE must be reported to APHP using the SAE web form within 48 hours of the initial observation of the event. Safety aspects of the study are closely assessed by the DSMB, which receives non-blinded data. Moreover, the first relapse of INS has been included as SAE to allow monitoring by the DSMB of any major discrepancy between the treatment groups.
Open access Ethics and dissemination study was approved by the ethics committee (Comité de Protection des Personnes) of Ouest I on 24 April 2018 and authorised by the French drug regulatory agency (Agence Nationale de Sécurité du Médicament et des Produits de Santé-EudraCT n°2017-000826-36) on 17 May 2018. A manuscript with the results of the primary study and the secondary aims will be published in a peerreviewed journal.
Acknowledgements The sponsor was  Assistance Publique -Hôpitaux de Paris (Clinical Research and Innovation Department , a non-profit public organisation), supervising all the public hospitals in the Paris area. collection, management, analysis and interpretation of data; writing of the report and the decision to submit the report for publication is the responsibility of  Assistance Publique -Hôpitaux de Paris , the study sponsor. Funding The RITUXIVIG trial is funded by a grant from  Programme Hospitalier de Recherche Clinique -PHRC 2016 (Ministry of Health ). Competing interests None declared. commissioned; externally peer reviewed.
History ENIGMA was launched in December 2009 to help 'break the logjam' in genetic studies of the brain. At the time, most neuroimaging genetics studies were assessing historically candidate genetic variations, mostly in very small samples of a few tens to hundreds of participants (e. g. , COMT, 5-HTTLPR, BDNF). These studies typically reported 'candidate gene' effects that did not replicate when tested in independent cohorts  [19] [20] [21]. It became apparent that very large numbers of genetic loci contributed to variation in complex neurological or psychiatric traits, including imaging-derived brain measureseach with a very small effect size-and only a few genetic loci accounted for more than 1% of the variance in any complex brain condition or measure  22. Thus, scientists began to recognize the need to pool multiple datasets worldwide to perform better-powered studies of these traits.
g. , individuals with 22q11DS exhibiting psychotic symptoms) or when a specific method is being developed, and computational power or expertise is available at only a few sites; here the data transferred usually include unidentifiable derived imaging metrics (e. g. , hippocampal volume) and demographic or clinical information (age at scan, sex, diagnostic status, etc. ); however, this form of analysis may limit participation and requires individual data transfer agreements with participating sites. We note, because of these required agreements with potentially clinically sensitive patient information, and the project-specific design of the 'centralized' approaches, ENIGMA does not curate a database for repeated or open access, and each cohort PI approves of each project for which they contribute data.
c In complementary work on rare variants by the ENIGMA-CNV Working Group, Sønderby and colleagues (2018) examined effects of the 16p11. 2 distal CNV that predisposes to psychiatric conditions including autism spectrum disorder and schizophrenia. ENIGMA (including the 16p11. 2 European Consortium) and deCODE datasets were combined to discover negative dose-response associations with copy number on intracranial volume and regional caudate, pallidum and putamen volumes-suggesting a neuropathological pattern that may underlie the neurodevelopmental syndromes. The agreement across datasets is apparent in the Forest plots for each brain region. [Data adapted, with permission from the authors and publishers]. growth or atrophy, and performs GWAS to find genetic markers that may influence these rates of change.
ENIGMA disorder-based neuroimaging studies ENIGMA-schizophrenia The Schizophrenia WG was formed in 2012, and has since analyzed data from 39 cohorts worldwide and has identified case-control differences in brain morphometry  1, 54, 55  and WM microstructure  56, 57  , on an unprecedented scale. ENIGMA-Schizophrenia was the first working group to publish large-scale analyses of disease, in two seminal papers on case-control differences in brain morphometry based on the largest samples to date. Van Erp and ENIGMA colleagues  54  first reported that patients with SCZ (N = 2028 patients) had smaller hippocampus (Cohen's d = -0. 46), amygdala (d = -0. 31), thalamus (d = -0. 31), nucleus accumbens (d = -0. 25), total intracranial volumes (d = -0. 12), and larger pallidum (d = 0. 21) and lateral ventricle volumes (d = 0.
ENIGMA's Diffusion MRI working group, launched in 2012 with protocols for diffusion tensor imaging (DTI), published a series of papers on the heritability and reproducibility of DTI measures derived with a protocol based on tract-based spatial statistics  [64] [65] [66]. Over ten of ENIGMA's working groups have since used this protocol to rank effect sizes for DTI metrics across key WM tracts. Kelly et al. reported on widespread WM abnormalities in schizophrenia, pooling data from 2359 healthy controls and 1963 patients with SCZ from 29 independent international studies  56. Significant reductions in fractional anisotropy (FA) in patients with SCZ were widespread across major WM fasciculi. While effect sizes varied by tract and included significant reductions in the anterior corona radiata (d = 0.
In ADHD, however, the amygdala, caudate and putamen, and nucleus accumbens all show deficits, as does ICV (ventricular data is not included here for ADHD, as it was not measured in the ADHD study). A web portal, the ENIGMA Viewer, provides access to these summary statistics from ENIGMA's published studies of psychiatric and neurological disorders (http:// enigma-viewer. org/About_the_projects. html). b Independent work by the Japanese Consortium, COCORO, found a very similar set of effect sizes for group differences in subcortical volumes between schizophrenia patients and matched controls. [Data adapted, with permission of the authors and publishers, from Kelly et al. 56  , van Velzen et al. 67  , and Villalón-Reina et al. 17  ; a key to the tract names appears in the original papers; some tracts (i.
26 to -0. 57). Moreover, these differences in gray matter morphometry observed in MDD do not involve abnormal asymmetry, as shown in a joint study by the Laterality and the MDD WGs involving 2540 MDD individuals and 4230 controls, from 32 datasets  71. A follow-up analysis on a subset of these aforementioned data found that the brain MRIs of adult patients with MDD (18-75 years old) appeared, on average, 1. 08 years older than those of controls (d = 0. 14)  72. This 'brain age' estimate was based on a machine learning algorithm trained to predict chronological age from morphometric data from 2188 controls across 19 cohorts and subsequently applied to hold-out data from 2126 healthy controls and 2675 people with MDD. The largest brain aging effects were observed in antidepressant users (+1.
ENIGMA-PGC Post-Traumatic Stress Disorder In partnership with the PGC, ENIGMA launched a WG on PTSD that has analyzed neuroimaging and clinical data from 1868 individuals (including 794 patients with PTSD) from 16 cohorts. In this first ENIGMA-PTSD study, Logue and colleagues found that patients with current PTSD had smaller hippocampal volumes (d = -0. 17) compared to trauma-exposed controls  4. Childhood trauma predicted smaller hippocampal volume (d = -0. 17) independent of diagnosis. In a subsequent study, the WG found that cortical thickness in 3378 individuals (including 1309 patients with PTSD) was lower in PTSD in the orbitofrontal cortex, cingulate cortex, precuneus, insula, and lateral parietal cortices. In addition, a DTI meta-analysis of 3057 individuals (including 1405 patients with PTSD) from 25 cohorts found alterations in WM organization in the tapetum, a structure that connects the left and right hippocampus  76.
ENIGMA-Obsessive-Compulsive Disorder The ENIGMA's OCD WG grew out of a previously established consortium (the OCD Brain Imaging Consortium, or OBIC)  87  , and has published the largest studies to date of brain structure in adult and pediatric OCD, using both meta-and mega-analytic approaches  6, 88. The first study analyzed MRI scans from 1830 patients diagnosed with OCD and 1759 controls across 35 cohorts from 26 sites worldwide  88. Unmedicated pediatric OCD patients demonstrated larger thalamic volumes, while the pallidum was enlarged in adult OCD patients with disease onset at childhood. Adult OCD patients also had significantly smaller hippocampal volumes (d = -0. 13), with stronger effects in medicated patients with adult-onset OCD compared to healthy controls (d = -0. 29). A cortical study included data from 1905 patients diagnosed with OCD and 1760 healthy controls across 38 cohorts from 27 sites worldwide.
To assess whether the anatomical differences could be used to create a neuroimaging biomarker for OCD, a machine learning analysis of the cortical and subcortical data was performed with 2304 OCD patients and 2068 controls. Classification performance across ten different machine and deep learning approaches was poor. With site-stratified cross-validation, the ROC-AUC ranged between 0. 57 and 0. 62. The performance dropped to chance level when leave-one-site-out cross-validation was used, with classification performance between 0. 51 and 0. 54. This indicates that these anatomical brain features do not provide a biomarker for OCD. But when patients were stratified according to whether they had used medication, classification performance improved remarkably. Medicated OCD patients and controls could then be distinguished with 0.
73, unmedicated OCD and controls with 0. 61, and medicated and unmedicated OCD patients with 0. 86 ROC-AUC. These multivariate results therefore mirror the univariate results, and highlight that medication use is associated with large differences in brain anatomy  89. The OCD WG, in conjunction with the Laterality WG, studied brain asymmetry in OCD using 16 pediatric datasets (501 patients with OCD and 439 healthy controls), and 30 adult datasets (1777 patients and 1654 controls)  90. In the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward in patients compared to controls; d = 0. 19) and the pallidum (less leftward in patients compared to controls; d = -0. 21). No asymmetry differences were found in the adult datasets.
Overall, patients with ASD showed altered morphometry in the cognitive and affective associated-regions of the striatum, frontal cortex, and temporal cortex. The ASD group worked together with the Laterality group to produce the largest ever study of brain asymmetry in ASD, involving 1774 patients and 1809 controls, from 54 datasets  97. Generally, subtle but widespread reductions of cortical thickness asymmetries were present in patients with ASD compared to controls, as well as volume asymmetry of the putamen, and surface area asymmetry of the MOFC (the strongest effect had Cohen's d = -0. 16). Altered lateralized neurodevelopment may, therefore, be a feature of ASD, affecting widespread cortical regions with diverse functions.
ENIGMA-22q11. 2 Deletion Syndrome 22q11DS is associated with a 20-fold increased risk for psychosis, and an elevated risk for developmental neuropsychiatric disorders such as ASD. 22q11DS provides a 'genetics-first' framework to study the brain markers underlying complex psychiatric phenotypes. The ENIGMA-22q11DS working group analyzed the largest dataset to date of brain images from patients with 22q11DS from 10 cohorts including 466 individuals with 22q11DS and 374 matched controls. Compared to controls, 22q11DS individuals showed overall thicker cortical gray matter (left/right hemispheres: Cohen's d = 0. 61/0. 65), but pervasive reductions in cortical area (left/right hemispheres: d = -1. 01/ -1. 02), with specific anatomic patterns. Machine learning methods were applied to the cortical thickness and area measures to achieve a high accuracy (sensitivity 94.
ENIGMA-Copy Number Variations This WG was set up to examine the effect of rare CNVs, risk factors for a variety of neuropsychiatric disorders, on brain structure. Due to their low prevalence  102, 103  , their effects on the brain have been hard to establish. Sønderby and colleagues focused on the 16p11. 2 distal CNV that predisposes to psychiatric conditions including ASD and schizophrenia. ENIGMA (including the 16p11. 2 European Consortium) and deCODE datasets were combined to compare subcortical brain volumes of carriers of 15 16p11. 2 distal deletion and 18 duplication to 7714 noncarriers which led to the discovery of negative doseresponse associations with copy number on intracranial volume and regional accumbens, caudate, pallidum and putamen volumes-suggesting a neuropathological pattern that may underlie the neurodevelopmental syndromes  53.
A further study  100  including the UK Biobank assessed the association of the 15q11. 2 CNV with cognition and cortical and subcortical morphology in more than 45,000 individuals from 38 datasets (203 individuals with a 15q11. 2 deletion, 45,247 non-carriers, and 306 duplication carriers). The authors found a clear pattern of widespread poorer cognitive performance, smaller surface area and thicker cortices for deletion carriers compared to non-carriers and duplication carriers, particularly across the frontal lobe, anterior cingulate and pre/postcentral gyri. The pattern of results fits well with known molecular functions of the genes in the 15q11 region and suggests involvement of these genes in neuronal plasticity and cortical development. Thus, the results from ENIGMA-CNV have shown that several CNVs cause abnormal brain patterns and inform on genetically determined variation in brain development and their relation to neurodevelopmental disorders.
ENIGMA-Brain Injury ENIGMA's Brain Injury WG  111  combines data from 72 centers, and is organized into ten separate subgroups that focus on (1) acute mild traumatic brain injury (TBI), (2) adult moderate/severe TBI 112 , (3) pediatric moderate/ severe TBI  113, 114  , (4) military-related brain injury  [115] [116] [117] [118]  , (5) sports-related concussion 119 , (6) intimate partner violence 120 , (7) MR spectroscopy 121 , (8) arterial spin labeling, (9) resting state fMRI, and (10) cognitive endpoints. These groups have recently started-up compared to other ENIGMA WGs, but are rapidly expanding in membership and focus. In addition to meta-and megaanalyses of relevant existing datasets, the Brain Injury WGs endeavor to further extend efforts to promote increased consistency in prospective data collection, both in terms of imaging data and associated cognitive outcome data.
ENIGMA-Stroke Recovery The ENIGMA-Stroke recovery WG has addressed a major gap in stroke research relating to the large-scale definition of lesion masks. Researchers in this WG have released a public archive of 304 T1-weighted MRIs with manually segmented stroke lesion masks  126  (https://www. icpsr. umich. edu/icpsrweb/ADDEP/studies/36684), and developed open-source software  127  and analyses specific for scalable  128  , reproducible lesion analyses (https:// github. com/npnl/PALS). In addition to this major methodological contribution they have analyzed data from 629 participants from 22 sites worldwide to identify reliable predictors of motor function after stroke  129, 130. They found that motor-related subcortical volumes in the basal ganglia and thalamus are positively associated with poststroke motor performance, and depend on impairment severity, time since stroke, and lesion laterality.
ENIGMA-methods focused working groups The ENIGMA Consortium functions as a driving force for the development, validation and implementation of novel methods to address the complexities of analyses of large imaging datasets and to derive more mechanistic insights into the processes that underpin variation in brain organization in health and disease. To achieve this, ENIGMA has dedicated WGs focused on the development of more innovative pipelines for data analyses to be applied for various dataset worldwide. The ENIGMA Diffusion MRI WG on DTI is one of the most longstanding. DTI offers information on microstructural abnormalities that are not detectable on standard anatomical MRI. As mentioned earlier, this WG has published a series of papers on the heritability and reproducibility of DTI measures derived with a custom protocol based on tract-based spatial statistics  64, 134.
The impact of ENIGMA The ENIGMA Consortium has been a driving force in the field of neuroscience by making substantial contributions to the science of brain variation and shaping the working practices of the field at various levels. In reflecting on the key achievements, three areas stand out: Promoting robustness and reproducibility ENIGMA's "big data" approach to neuroimaging addresses directly the reproducibility challenges that plague many areas of biomedical science-including neuroscience  [146] [147] [148]. Neuroimaging has received considerable scrutiny regarding the reliability of published findings, given the literature replete with studies based on small samples and seemingly unlimited methodological freedom  149, 150. Many other approaches also aim to tackle this reproducibility crisis, by building data repositories that can be accessed for replication  [151] [152] [153]  ; yet ENIGMA offers an opportunity to collaborate with teams of diverse experts irrespective of whether or not any data is shared.
In one recent study by ENIGMA's Laterality group, the authors examined brain asymmetry in 99 MRI datasets worldwide (from N = 17,141 people) and found that, as expected, the reproducibility of findings increased with the effect size and sample size, in a setting that was free from publication bias (data available at: http://conxz. net/neurohemi/)  18, 154. For example, for effect sizes of d ≥ 0. 6, the reproducibility rate was higher than 90% even when including the datasets with sample sizes as low as 15, while it was impossible to obtain 70% reproducibility for small effects of d < 0. 2, even with a relatively large minimum sample size threshold of 500. The unprecedented size of the datasets analyzed across ENIGMA boosts statistical power to detect the effects of disease and their moderators  73, 155.
Through data sharing, investigators can now identify patterns of brain abnormalities that consistently characterize disorders or clinical syndromes, while assessing their reproducibility across continents. This is exemplified by the close match between the schizophrenia findings by ENIGMA  54, 60  and independent work by the Japanese Consortium, COCORO  58  and a recent Norwegian study of 16 cohorts by Alnaes  59. In all three studies, schizophrenia patients showed enlargement of the lateral ventricles, pallidum, putamen, and caudate, and volume reduction in the hippocampus, amygdala, thalamus and accumbens, with a strong agreement in the magnitude and rank order of effects from highest to least group difference. Similarly, a recent GWAS study of the UK Biobank dataset  156  was able to replicate the majority of the genetic loci discovered by ENIGMA in two separate GWAS of subcortical volumes  24, 25.
Thus, the international, multi-site nature of ENIGMA studies likely promotes representative findings that are widely generalizable. Meanwhile, the larger and more diverse samples are valuable resources for understanding the heterogeneity across different studies, and may provide new insights into the reproducibility issue faced by the neuroimaging community. Moreover, ENIGMA offers a platform for investigators to converge on methods for sharing and analyzing data acceptable to the community. ENIGMA also offers new opportunities to change the landscape for how data can be used. In current research practices, a great resource of data remains largely untapped that is often known as "long-tail" data: data sets collected in individual laboratories that accumulate over many years and funding cycles  157.
Much valuable data remains dormant (and unpublished) due to a lack of personnel and time to analyze it, and this is going to increase with studies including larger samples than before. Efforts through ENIGMA to leverage 'dormant' data in labs throughout the world have at least three important advantages. First, data sharing increases the scope of the science, enhancing opportunities for analyses not otherwise possible with small sample sizes. Second, data sharing naturally engages scientists from distinct disciplinesa crucial step for advancing the clinical neurosciences  158. A final benefit that is sometimes overlooked in global scientific collaborations is their power to build and enhance diplomatic relations and transcend political conflicts between nations  159. With representation from 43 countries-some of which have minimal diplomatic tiescollaborations are not only constructive in terms of collective problem solving, but they also build connections between high income countries and the poorest nations across the globe and to build capacity in the latter  159.