dataesr/scientific-paragraphs-categorization huggingface dataset:
Each coping style was entered separately for analysis. The relationship between the profiles and the caregiver's familial position was estimated using a three-step latent class regression model with the Lanza method for categorical distal variables  (Asparouhov & Muth en, 2014; Lanza et al. , 2013). To rule out the possibility that the association between class membership and familial position could only be explained by age, a logistic regression model was developed, with age and class membership as the independent variables and familial position as the dependent variable. Finally, to test whether the duration of illness differs among classes, an analysis of variance (ANOVA) was performed with class membership as the independent variable and duration of illness as the dependent variable. All statistical analyses were performed using the IBM-SPSS 25 and Mplus version 8 software.
Sociodemographic data A total of 181 family caregivers of PWS participated in this study. Among them, 120 were siblings and 61 were parents (see Table  1 ). The majority of participants were female (70. 49% parents and 81. 67% siblings) and were caring for a male (74. 41% parents and 86. 67% siblings). In general, sibling caregivers were younger than parent caregivers (t ¼ À13. 91; p < 0. 001). Siblings were on average 37 years old (SD ¼ 13. 71 years) and parents 60 years old (SD ¼ 7. 73 years) but they are caring for an older PWS than their parent (M age of the PWS in the sibling sample ¼ 37. 69 years old; SD ¼ 11. 97; M age of the PWS in the parent sample ¼ 32. 13 years old; SD ¼ 10. 70). The duration of the relative's illness was longer in the sibling sample than in the parent sample (t ¼ 2.
This paper describes a project aimed at digitizing and openly sharing the natural history collections (AMUNATCOLL) of the Faculty of Biology at Adam Mickiewicz University in Poznań (Poland). The result of this project is a database (including 2. 2 million records) of plant, fungal and animal specimens, which is available online via the AMUNATCOLL portal and on the Global Biodiversity Information Facility website. This article presents selected aspects of the "life cycle" of this project, with a particular focus on its preparatory phase.
Introduction Biological specimens are widely known and longestablished in systematic and taxonomic studies  (Lane 1996) , and they provide a basis for the repeatability or reinterpretation of the preserved aspects of various phenotypes. Each specimen constitutes evidence of biodiversity and a documentation of a particular species that is present in a particular place at a particular time  (Hilton et al. 2021). Natural History Collections (NHCs) are a part of the foundation of global biological sciences research and education infrastructure. Biodiversity col-lections are more than shelves of preserved specimens; they also contain tissue and gene samples, parasites that are associated with a specimen and environmental data captured during specimen collection, including audio and video recordings and field notes (Gropp 2018).
2022a ). However, activities undertaken in 2015 resulted in the acquisition of significant funding for a project entitled the AMU Nature Collections -Online (AMUNATCOLL), which involved digitizing and sharing the nature data resources of the FBAMU. Separate articles included in this BRC volume present the main concepts and components of the AMUNATCOLL IT system: the metadata structure, the database and the operational procedures  (Lawenda et al. 2022) , the portal and the mobile application and the graphical interface  (Nowak et al. 2022). This paper aims to provide an outline of the assumptions, workflow and main results of the AMUNATCOLL project, with a focus on the substantive and organizational problems associated with the process of digitizing NHCs.
Identification of resources based on an inventory of the natural collections The inventory of the NHCs proved to be a very intensive process, despite the fact that these collections had been deposited in a common space since 2004 and systematically catalogued for an analogue system featuring a local database. The task of producing an inventory of natural specimens is laborious because it must reflect not only the richness and diversity of the organisms but also the manner in which they are collected, described, stored and preserved. It was agreed that 54 collections of plants, fungi and animals as well as 12 specialist and iconographic collections would be digitized. It was estimated that these collections would result in a digital database containing approximately two million unique records that would reflect the biodiversity of many places worldwide.
Identification of the target group and recognition of the expectations of potential users of the information system to be designed Biodiversity has been a fundamental subject of scientific research since the term was first defined  (Arthur 1916). During the second half of the twentieth century, due to constantly increasing anthropogenic threats, biodiversity became an important topic of discussion in increasingly broad social, economic and political contexts  (CBD 1992; MEA 2005). Assuming that the digital NHC database has an important role to play in this respect, an analysis of its potential users was conducted. As a result, five core target groups were defined, the requirements of these groups were identified and their numbers were estimated. The first group consists of scientists and PhD students from 43 public research institutions, including 24 universities and 19 research institutes associated with the Polish Academy of Sciences.
These individuals are key recipients of the project outcomes. These people will use digital data primarily for the purposes of research and teaching. Some of these people will contribute new scientific information to the database and correct the biodiversity knowledge resources that have been made available. The estimation of the first group was difficult because the number of professionals who use such databases worldwide is unknown. It is difficult to estimate the number of institutions in which they are employed even approximately. The second group is composed of representatives of nearly three thousand state and local government units at various levels. In Poland, this group includes employees from 23 national parks, 16 landscape parks, 16 provincial offices, 16 marshals' offices, 314 district authority offices and 2,478 city and municipal offices.
The fourth group comprises educational institutions of all levels and specializations, of which there are approximately 21,500 in Poland. Analysing the needs of teachers and students in terms of access to biodiversity knowledge, it was concluded that the sharing of information resources related to the natural collections and tools for their analysis should have a positive impact on their awareness and activity in the context of nature conservation. The fifth group includes NGOs and all members of the public with an interest in biodiversity and natural history museums. The numbers of this group are the most difficult to estimate, but this group is also potentially the largest and most diverse in terms of requirements for the database. The conclusions that can be drawn from this identification of the NHCs and the target groups were important for the digitization process, the construction of the database and the organization of the information system.
Planning for the digitization of the collection The digitization of NHCs involves converting spe cimen data from analogue form to digital signals  (Nelson et al. 2018). The following digitization techniques are planned to be used for the AMUNATCOLL project: (1) transcribing the text data from sample labels and other sample-related documents into digital records of those labels and documents; (2) translating the physical specimens into digital, two-dimensional images of these specimens (taking images from light microscopes, stereo microscopes, scanning microscopes, speciali zed scanners and CANON full-matrix cameras); (3) converting analogue photos as well as audio and video recordings to digital recordings; (4) converting textual descriptions of locations into geographical coordinates and creating a digital layer of points to represent specimens; and (5) converting biodiversity data from other sources (e.
Development of an IT system concept and selection of a partner IT institution Many systems on the internet are related to the presentation of biodiversity information. They differ in terms of their purposes and in the scope of functionality that they offer to their users. As a part of the work involved in determining the functional scope of the implemented interfaces, we investigated the experiences of renowned scientific institutions and IT databases, with a particular emphasis on online databases, which are among the tools most frequently employed by scientific users. Detailed results of a comparative analysis of the most important websites and portals of this type are presented in a separate article  (Nowak et al. 2022). Although the conclusions of this ana lysis were very informative, the decision was made to proceed with the development of our own IT system.
Project goals, objectives and timetable The strategic goal of the AMUNATCOLL project was to make the digital data associated with the NHCs of the FBAMU completely open and available online. The following specific objectives were prerequisites for the achievement of this goal: (1) the development of a standardized set of metadata to record the unique values of the FBAMU's NHCs in a manner that would be compatible with international standards; (2) the development of a digital database for the NHCs of the FBAMU; (3) the creation of an information system to ensure interoperability, communication with other databases, the possibility of developing applications and facilitating multidimensional data analysis, including the spatial dimension; (4) the provision of the appropriate hardware and software infrastructure as well as the organizational facilities necessary to guarantee the sustainability and further development of the system within the scope of the resources of the Project Partners; and (5) equipping the project's scientific team with the competences necessary to digitize other biological resources with the aim of carrying out similar projects using other datasets.
Thirty-six months were allotted to the entire package of goals and objectives. Using the experience de veloped during the initial phase of the project, a key output indicator of 2 million records, i. e. , digitized specimens of algae, plants, fungi and animals, was established. The specific output indicator was set at 960 TB. This size was intended to guarantee secure storage of the digitized text data and space-intensive image data. For tasks that were crucial to the success of the project, strict deadlines for achieving certain milestones were planned (Table  1 ). It was assumed that quantitative indicators (e. g. , the number of digitized objects) would be monitored systematically and reported on a monthly and quarterly frequency. Two supporting tasks were also defined: (1) the provision of training in the use of the database to potential users and (2) the dissemination of information regarding the project through promotional activities.
Equipment This project featured high requirements regarding the standards for the digitization process and the storage of the results of digitization. The digitization process, in addition to its requirement of procedures to allow many people to work smoothly simultaneously, required topclass devices that could cope with such a heavy load. In addition, a key to success was the correct selection of equipment for the scanned materials, i. e. , equipment that could ensure precision and display scientifically important features. Taking these assumptions into account, the following equipment was selected: • Scanner Zeutschel OS 14000 TT -used for scanning herbarium sheets, this machine allows two sheets to be scanned simultaneously and subsequently divided into two files in the graphics program; • Light microscope OLYMPUS BX 51 and BX 53, DP74 camera and CS software (cellSens Dimension) -this set of hardware and software allows photos to be taken using a light microscope for solid and unstable microscopic slides.
The large resolution of this equipment allows objects smaller than 1 mm to be photographed; • Stereoscopic microscope OLYMPUS SZX16, DP74 camera and CS (cellSens Dimension) software -this equipment allows pictures of preserved or living animals and plant diasporas up to 3 cm. in size to be taken. Four positions were used mainly for photographing spiders, molluscs, crustaceans, twigs and insects. The available magnification (from 7 to 110 times) allows the details of the morphological structure of arthropods (Arthropoda) and molluscs (Mollusca) to be photographed; • Scanning microscope Zeiss EVO 40 -this equipment allows pictures of preparations that have been sprayed with gold to be taken. In this way, it is possible to photograph morphological details under high magnification. The Nature Collection has an extensive collection of scanning photos, mainly of mites (Acari); • CANON full-frame cameras -these came ras were used to take photographs of collected specimens using a shadowless table and lenses of various lengths (ranging from wide angle lenses to telephoto and macro lenses).
These cameras are used to photograph large objects (e. g. , stuffed birds, fish, corals) and macro objects (e. g. , snail shells, insects). In addition to digitization equipment, project partners also provided numerous ICT systems for the storage and processing of large amounts of material produced by the digitization process. The most important servers are enumerated below: • Production and development servers -used for hosting the portal and accompanying services; • Specimen and observation databases -hosted on servers that maintain the databases used by the portal and the mobile application; • Monitoring server -this server ensures the continuity of the system's operation and the security of the data stored, which are crucial tasks due to the need to access the data and the services offered.
Furthermore, the following data storage systems were established and made available based on the requirements of AMUNATCOLL: • Data buffer -a system based on Seafile software that allows data to be saved and stored following the digitization process but prior to actual importation to the database (120 TB); • Disk matrix -space on matrix disks allows source data and processed data to be processed and stored alongside their copies safely ma nner following importation to the database. This solution is composed of two Ceph-based storages containing 360 TB of space each (local and geographic copy) as well as 120 TB of tape system. In addition to computer devices, the most significant aspect of the geotagging process was the development of a resource based on geographic information used to support this task (Nowak et al.
A group of a dozen IT specialists included developers who were responsible for (1) developing the metadata structure; (2) implementing the database repository with the required converters; (3) preparing the portal and the mobile application; (4) integrating the AMUNATCOLL and GBIF systems; (5) supplying the maps and specimen locations; and (6) conducting internal security audits of the produced software. The project was supervised by a project lead appointed by the AMU Rector. This individual was primarily responsible for (1) achieving the project's goals and indicators as well as developing and updating any plans for the project, (2) receiving a group of tasks, (3) maintaining the project's documentation, (4) reporting on the project's status and progress; (5) promoting the project and dealing with the media, and (  6 ) organizing legal and administrative consultations.
A key element of the digitization process is the validation of and development of a quality control system for the work of the participants throughout the process. Once the appropriate level and pace of digitization was achieved, it was possible to direct a team of IT specialists and coordinators to work on the database structure and the basic interfaces, namely, the portal and the mobile application. Based on the general assumptions made during the project preparation stage, solutions that are currently available to all interested parties were developed. It should be noted that future users, who represent different target groups, had a significant influence on the final design of the portal and the mobile application. These individuals participated in specially organized presentations and workshops to test new versions of the tools that were to be implemented in the AMUNATCOLL IT system.
Functioning of the AMUNATCOLL IT system The result of the project is a functioning AMUNAT-COLL IT system that consists of a database containing more than 2. 2 million records and interfaces that make those records available online. The digital data on the NHCs, which are deposited at the FBAMU, are openly available through the project's portal  (Amunatcoll. Portal 2022) , the mobile app (Amunatcoll. Mobile app 2022) and the Global Biodiversity Information Facility website (Amunatcoll at Gbif 2022) (Fig. 5 ). The portal provides a rich set of tools for data analysis and results presentation in both graphical and cartographic form. The mobile application is designed to facilitate field studies of flora, fauna and natural habitats  (Nowak et al. 2022). The AMUNATCOLL IT system operates on the basis of the SEPP (Scientific, Educational, Public, and Practical use model) model that was developed as part of this project  (Jackowiak et al.
2022b). Based on the experience gained while completing the project, new solutions for geotagging were proposed  (Nowak et al. 2021). The scientific benefits of these solutions are illustrated by the visitation and download data that are available through the GBIF. During the first few months after project completion, the AMUNAT-COLL database was visited more than 9000 times, and the data thus obtained were cited approximately 20 times. The AMUNATCOLL IT system was also tested as part of a citizen science project aimed at documenting an invasive species (Ambrosia artemisiifolia) in the Poznań area  (Grewling et al. 2022). The portal and the mobile app have already been used several times in the context of academic classes in Poland, France, the Czech Republic and Madagascar (Nowak M. M. , oral information).
Conclusions AMUNATCOLL is an interdisciplinary project that requires close cooperation between teams working in the fields of biology and computer science. As in every project in the context of IT, work on AMUNATCOLL began with careful analysis, design and implementation of all the most important modules and functions of the ICT system, which were anticipated in the funding application and the feasibility study. First, work on the AMUNATCOLL project included the creation of a set of metadata pertaining to various aspects of the correct taxonomic description of the specimens as well as the requirements of the target groups. On this basis, the structure of the database was designed to facilitate the storage of taxonomic, iconographic, organizational and technical information. The process of data preparation and importation was supported by numerous application and logistics solutions, which allowed us to streamline the entire process to improve our ability to process a large number of records over a relatively short period of time.
Acknowledgements. This work has been supported by the  AMUNATCOLL  project and has been partly funded by the  European Union and Ministry of Digital Affairs  from the  European Regional Development Fund  as part of the  Digital Poland Operational Program  under grant agreement number:  POPC. 02. 03. 01-00-0043/18. This paper expresses the opinions of the authors and not necessarily those of the  European Commission and Ministry of Digital Affairs. The European Commission and Ministry of Digital Affairs are not liable for any use that may be made of the information contained in this paper.
Search Strategy An electronic search was conducted up to 14 February 2022 in the following databases: Medline, PICO (Patient, Intervention, Comparison, Outcome), Cochrane Database of Systematic Reviews, Scopus, and Clinical Trials Register. The references listed in each retrieved article were manually searched. The MeSH terms were: (probiotics) OR (synbiotics) AND (surgery) AND (colorectal). Selected publication languages were: English, French.
Data Extraction The titles and abstracts of all the identified reviews were screened by two independent assessors (JV, KS) against the inclusion and exclusion criteria. Any disagreement was resolved by consensus. The full texts of relevant RCTs were assessed independently. The selection/exclusion process is summarised in a PRISMA 2020 flow diagram  [18]. We extracted a dataset from each included RCT: first author, year of publication, country, number of patients, formulation (prob or synb), pre-and/or postoperative, strains, main outcomes, competing interests of the authors, and comments. Overall infectious complications and surgical site infections (SSIs including both deep abdominal infections and wound (skin or under the skin) infections) were considered as the primary outcomes. Anastomotic leaks, wound infections, urinary infections, pulmonary infections were the secondary outcomes.
Data Synthesis and Statistical Analysis This meta-analysis was performed combining the results of the reported risk ratio in the selected studies. Binary outcomes data from these studies were extracted when available. The analysis calculated the random effects estimates risk ratio (RR) for each outcome listed above. The inverse variance weighting was used for pooling. The iterative Paule-Mandel method was used to estimate between-study variance  [21]. Heterogeneity between studies was explored using Cochran's Q statistic, Higgin's and Thompson's percentage of variability I 2 statistic to estimate the percentage of total variation across studies arising from heterogeneity rather than chance  [22]. Heterogeneity was rated low, moderate, or substantial when the value of I 2 was less than 25%, 50%, or greater than or equal to 75%, respectively.
Indeed, the study in this article reviews the effects of prolonged use on cognition as well as research on a mental state based on adaptive interfaces and different classes of metrics for mental fatigue detection. Literature authored in English was selected based on the relevance to the topic and its scientific rigor. As a result of this, the list of effects of mental fatigue on cognition in Section 2, possible and implemented adaptations in Section 3, and the set of metrics for mental fatigue detection in Section 4 is not exhaustive. The principal search engine used for the literature review was Google Scholar. In addition, the ACM (www. acm. org) and IEEE (www. ieee. org) databases were searched. Although no hard inclusion and exclusion criteria were defined, articles that were not peer reviewed were generally avoided.
In particular, their localization to ER-mitochondria contacts was higher compared with when expressed individually (Figure  1H ). Also, the co-localization of co-overexpressed ORP5 and ORP8 was comparable with the co-localization of the endogenous proteins, as revealed by the high Pearson's correlation coefficient, which, in both cases, was close to 1 (Figure  1F ). These data indicate that co-expression of ORP5 and ORP8 mimics the physiological localization of these proteins as a complex, when the expression level of one of the two proteins is not highly enriched compared with the other. To further quantify ORP5 and ORP8 co-localization and interaction at ER-mitochondria contact sites in co-overexpression and endogenous conditions, we used Duolink-Proximity Ligation Assay (PLA) coupled with staining of mitochondria (MitoTracker) and confocal microscopy.