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The article presents the history of introduction and application of the tax on excessively increasing wage payments being in force in the years 1982–1995. Basing on source documents, it also analyses the characteristics of this tax and discusses the social and economic situation, together with the legal environment which conditioned the way it was introduced, its shape, functioning, and the infamous end. The author acknowledges that legal faults of this tax, its repressive character, economic ineffectiveness, and the social discontent with its functioning, could be among the important factors that stimulated the Polish political system’s transformation during the late eighties and nineties of the twentieth century.

The problem of international cooperation for sustainable development in the areas of environmental protection, economics, energy and public goods is a well-known scope of research, which can be classified as a classic canon of analysis in this domain. There is an explicit lack of research in the area of security, particularly in those aspects relating to objectives 8 and 16 of Agenda 2030, referring to combating the crime of human trade. The aim of the publication is to analyse the dynamics of international cooperation for the implementation of sustainable principles in the fight against human trafficking, undertaken in the context of the diagnosis of its effects for the implementation of sustainable principles with the use of resources (created and implemented standards), cooperation structures (global international organisations and their Member States) forming a system of international cooperation, the directions of which are determined by security needs. The article shows the evolution of international law in this area, the cooperation of selected international structures and its effects, as well as the dynamics of change resulting from statistics indicating the directions of implementation of objectives 8 and 16 of the sustainable development of the Agenda 2030. To achieve the objective, the assumptions of institutional theory were applied. The analysis was made using historical, comparative methods and analysis of source documents. The analysis presented in the article allows us to conclude that after the adoption of the Agenda 2030, the dynamics of international cooperation in the analysed area has increased, which is reflected in the new impetus given to the implementation of provisions enshrined in international law and required actions undertaken by member states - signatories of the act. Combating the crime of trafficking in human beings takes place within the framework of a diagnosable multifaceted institutional formula expressed in a detailed division of tasks and competences, allowing for coordination at the global level of preventive and operational actions to combat this practice. Global international cooperation for sustainable development in the area of combating trafficking in human beings in the 21st century is implemented in a systemic way and brings results which provide better and better prospects for effective combating of this crime, thus meeting the assumptions and objectives 8 (p. 8.7) and 16 (p. 16.2) of the Agenda 2030.

PURPOSE: The main objective of this paper is to examine the process of forming political and legal tools for counteracting and combating terrorism which has a significant impact on economic growth in the European Union., DESIGN/METHODOLOGY/APPROACH: A mixed research method was used during the research work. To minimize the occurrence of irrelevant results and repetitions, during the systematic review of academic sources the Preferred Reporting Items for Systematic Reviews and MetaAnalysis (PRISMA) method was used. In the case of European Union source documents, the EurLex legal acts database was explored, considering strictly defined criteria. The selected collection of literature and EU source documents was analysed using the Qualitative content analysis method., FINDINGS: EU countries, despite the conflict of interest that often separates them, were able to jointly develop and implement a substantial package of regulations of a political and legal nature, which evolved from ad hoc activities to preventive measures. The areas that currently require special attention include cybersecurity, counteracting the sources of terrorism (radicalization of attitudes), combating social exclusion, proper physical protection of critical infrastructure and public spaces, as well as tightening international cooperation to cut off all sources of financing terrorism., PRACTICAL IMPLICATIONS: The study results seem to be particularly important in the context of developing an optimum and effective tool for the long-term European Union policy in the field of counteracting and combating terrorism phenomenon, which is one of the key factors ensuring the maintenance of a sustainable level of economic growth., ORIGINALITY/VALUE: The study was conducted after the outbreak of the SARS-Cov-2 pandemic, which significantly remodelled the economy and safety environment in European Union countries. The article contains a critical analysis of undertakings performed at the EU forum to counteract and combat the phenomenon of terrorism. The research considers the latest EU legal regulations - the legal status of May 2021., peer-reviewed

Purpose: The aim of the article was to analyse the correlation between financial liquidity and the competitiveness of enterprises from defense industry enterprises. Design/Methodology/Approach: The solutions were developed on the basis of literature analysis, case study, document analysis. As part of the case study were used diagnostic and prognostic sheets, as well as the analysis of source documents. The analysis of financial liquidity was performed using the induction method, which includes examination of details, generalization in the form of conclusions, synthetic evaluation and diagnosis. The time scope of the research covered the period 2015-2018. Four defense companies in the world were selected for the purpose of the research. Findings: The analysis of four enterprises from the defense industry shows connection between the financial situation (measured by liquidity ratios) and the competitiveness of the surveyed companies. The most stable company, one of the leading defense in the world, is Northrop Grumman. In turn, United Aircraft is characterized by a large dispersion of results and negative values of cash flows from operational activities. The article is also an overview of competitiveness, showing the diversity in managing the resources of an economic unit, and indicates practical guidelines for the use of methods and interpretation of the financial liquidity ratios of enterprises. Practical Implications: The results of the research can be used by company managers, both from the defense industry and others, to create mechanisms that increase competitiveness. Originality/Value: The study is a new contribution to research into the competitiveness of defense companies. The aspects of the competitiveness of defense enterprises on the basis of liquidity ratios remained beyond the area of scientific interest., peer-reviewed

Cross-Language Multi-document summarization (CLMDS) process produces a summary generated from multiple documents in which the summary language is different from the source document language. The CLMDS model allows the user to provide query in a particular language (e.g., Tamil) and generates a summary in the same language from different language source documents. The proposed model enables the user to provide a query in Tamil language, generate a summary from multiple English documents, and finally translate the summary into Tamil language. The proposed model makes use of naïve Bayes classifier (NBC) model for the CLMDS. An extensive set of experimentation analysis was performed and the results are investigated under distinct aspects. The resultant experimental values ensured the supremacy of the presented CLMDS model.

This review describes the state of the art on the role of various imaging modalities in pre-operative preparation to transcatheter implantation of biological aortic valve prosthesis, based on the literature data published from 2012 to 2020. One of the key source documents is the consensus of the European Society of Cardiovascular Radiology (ESCR) from 2019, providing the standardized protocols for scanning, measurements and description of the abnormalities identified. The final decision on the procedure of transcatheter aortic valve implantation should be based on the combination of all available diagnostic methods, clinical data and results of imaging by different modalities. Given the most comprehensive information content, the main diagnostic method is computed tomography. The radiologist and the multidisciplinary team should form a single entity, combining clinical and technical knowledge, discussing all the images and conclusions with other team members.

Plagiarism refers to the use of other people’s ideas and information without acknowledging the source. In this research, anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’ written assignments and laboratory reports. The proposed framework collected original documents to identify plagiarized text using natural language processing. Our research proposes a method to detect plagiarism by applying the core concept of text, which is semantic associations of words and their syntactic composition. Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri, and it is stored in a centralized Microsoft database Server. A total of 55,001 data samples were collected from 2015 to 2019. Furthermore, we assimilated data from a university website, specifically from the psau.edu.sa network, and arranged the data into students’ categories. Furthermore, we extracted words from source documents and student documents using the WordNet library. On a benchmark dataset consisting of 785 plagiarized text and 4,716 original text data, a significant accuracy of 90.2% was achieved. Therefore, the proposed framework demonstrated better performance than the other available tools. Many students mentioned that working on assignments using the framework was suitable because they were able to work on the assignments in harmony, as per their timeframe and from different network locations. The framework also recommends procedures that can be used to avoid plagiarism.

The aim of the article is to reflect on linguistic manifestations of ordering information regarding the edition of source documents from the field of law by XIX century scholars dealing with the history of Poland. The work on preserving the printing of Polish monuments in the XIX century was motivated by the desire to document and prove the antiquity of Polish culture and Polish language, the historical significance of the Polish nation in the period of statehood loss. Organizing content in the studied source material is done by choosing materials, selecting them, giving them a chronological order, determining their origin and adding a commentary on linguistic, historical and moral themes. Reflection on the language concerns graphics, the writer’s efficiency, grammar and lexical correctness of the text, the realization of Latin, and exceptionally etymology. The authors of the commentary most often take the floor on the authenticity of the text. Reflections on the language of the document serve as an argument about the originality or inauthenticity of the source. Adjudication about the authenticity of a text and its meaning reflects one of the basic cognitive ideas of this period — ordering the editing of monuments of Polish law. In the discursive strategy of historians, reflections on language have been subordinated to it. Celem artykułu jest refleksja nad językowymi przejawami porządkowania informacji dotyczących edycji dokumentów źródłowych z dziedziny prawa przez XIX-wiecznych uczonych zajmujących się historią Polski. Prace nad utrwaleniem drukiem pomników polszczyzny były w XIX w. motywowane pragnieniem udokumentowania i udowodnienia dawności polskiej kultury i języka polskiego, historycznego znaczenia polskiego narodu w okresie utraty państwowości. Porządkowanie treści w badanym opracowaniu źródłowym następuje poprzez dobór materiałów, selekcję, nadanie im układu chronologicznego, określenie ich pochodzenia oraz opatrzenie komentarzem o tematyce językowej, historycznej, obyczajowej. Refleksja nad językiem dotyczy grafii, sprawności pisarza, poprawności gramatycznej i leksykalnej tekstu, realizacji łaciny, wyjątkowo etymologii. Autorzy komentarza najczęściej zabierają głos w sprawie autentyczności tekstu. Refleksje o języku dokumentu służą jako argument o oryginalności lub nieautentyczności źródła. Orzekanie o autentyczności tekstu i jego znaczeniu odzwierciedla jedną z podstawowych idei poznawczych tego okresu — porządkowania edycji pomników polskiego prawa. W strategii dyskursywnej historyków refleksje nad językiem zostały jej podporządkowane.

BACKGROUND: Guideline recommendations may be affected by flaws in the process, inappropriate panel member selection or conduct, conflicts of interest and other factors. To our knowledge, no validated tool exists to evaluate guideline development from the perspective of those directly involved in the process. Our objective was to develop and validate a universal tool, the PANELVIEW instrument, to assess guideline processes, methods and outcomes from the perspective of the participating guideline panellists and group members. METHODS: We performed a systematic literature search and surveys of guideline groups (identified through contacting international organizations and convenience sampling of working panels) to inform item generation. Subsequent groups of guideline methodologists and panellists reviewed items for face validity and missing items. We used surveys, interviews and expert review for item reduction and phrasing. For reliability assessment and feedback, we tested the PANELVIEW tool in 8 international guideline groups. RESULTS: We surveyed 62 members from 13 guideline panels, contacted 19 organizations and reviewed 20 source documents to generate items. Fifty-three additional key informants provided feedback about phrasing of the items and response options. We reduced the number of items from 95 to 34 across domains that included administration, training, conflict of interest, group dynamics, chairing, evidence synthesis, formulating recommendations and publication. The tool takes about 10 minutes to complete and showed acceptable measurement properties. INTERPRETATION: The PANELVIEW instrument fills a gap by enabling guideline organizations to involve clinicians, patients and other participants in evaluating their guideline processes. The tool can inform quality improvement of existing or new guideline programs, focusing on insight into and transparency of the guideline development process, methods and outcomes.

The issues of calculating losses caused by criminal acts of an economic nature are traditionally debatable in Russian law. This problem is especially acute in industries with specific conditions of financial and economic activity, for example, in the agricultural sector. The paper contains the author’s interpretation of the term "losses" in accordance with the specifics of agricultural production. The proposed method for calculating losses is differentiated according to the objects of criminal offense and is based on the use of primary accounting documents, accounting registers and specialized reporting forms, which have not been previously studied and described in the scientific literature. The paper proposes methods for calculating losses caused by economic crimes in the agricultural sector in conditions of neglect or lack of accounting. The author’s position regarding the inclusion of the amounts of lost profits in the assessment of damage is presented and possible conditions for its recognition are described.

Municipalities voluntarily carry out two main tasks: in the field of sport and recrea-tion and culture. In most communities there are sports clubs, including folk clubs in villages. Community expenditure on physical culture accounts for several percent of the budgeted expendi-ture. The purpose of the article is to answer the question as to whether, despite relatively small expenditure on sport, in relation to other titles, municipalities control the effectiveness of funds spent on this voluntary task. To this end, an analysis of legal acts regulating the possible forms of spending funds on sport in municipalities was conducted. The author also used the knowledge acquired in cooperation with municipalities. Mainly two research methods were used: research of source documents and observation. The study arrives at the following conclusion: municipalities do not assess the efficiency of spending on sport. Such conduct is contrary to the principles of spending public funds. Each expenditure should be purposeful, economical, and effective. The mechanisms of expenditure efficiency assessment proposed by the author are adequate to the organizational solutions adopted in communities for the implementation of tasks in the field of sport and thus forms of financing them. To ensure the effectiveness of the proposed mechanisms, they should be included in the management control system of the community.

PurposeThe purpose of the study is to assess performance of local level planning policies that required new buildings to avoid a specified and rising proportion of projected greenhouse gases (GHGs) from their use; it is calculated based on the approved design and plans for the specific development and through the installation and operation of low and zero-carbon generating technologies (LZCGTs).Design/methodology/approachData were extracted from a random sample of 911 new builds from 403 planning applications and related documents, across five Scottish local planning authorities (LPAs) who adopted GHG reduction policies. The data included GHG reduction, LZCGT installation and performance, use of plan designs to meet GHG reductions and exemptions from the GHG policies. Descriptive statistics using SPSS software, complimented by qualitative responses from questionnaires, helped to explain observed performance.FindingsThe policies performed poorly, at the level of delivering low-hanging fruits, with significant room for improvement. Design-led opportunities in the GHG policies were not actively pursued; most LZCGT installation was exempted from GHG policies and the policies were poor in targeting the relationship between building unit size, GHG emission and reductions.Research limitations/implicationsThe source documents, where the data came from, had varying quality and completeness and some LPAs are over-represented in the data. The study applied limited criteria to evaluate policy performance.Practical implicationsAreas for policymakers to further focus on when exploring how to enhance role and performance of LZCGT are highlighted, including practical suggestions.Originality/valueOne of the few studies assessing policy performance and distilling lessons, from early adopters of GHG policies at local level planning, offer performance benchmarks and raise points of concern for policymakers.

Text summarization is an approach for identifying important information present within text documents. This computational technique aims to generate shorter versions of the source text, by including only the relevant and salient information present within the source text. In this paper, we propose a novel method to summarize a text document by clustering its contents based on latent topics produced using topic modeling techniques and by generating extractive summaries for each of the identified text clusters. All extractive sub-summaries are later combined to generate a summary for any given source document. We utilize the lesser used and challenging WikiHow dataset in our approach to text summarization. This dataset is unlike the commonly used news datasets which are available for text summarization. The well-known news datasets present their most important information in the first few lines of their source texts, which make their summarization a lesser challenging task when compared to summarizing the WikiHow dataset. Contrary to these news datasets, the documents in the WikiHow dataset are written using a generalized approach and have lesser abstractedness and higher compression ratio, thus proposing a greater challenge to generate summaries. A lot of the current state-of-the-art text summarization techniques tend to eliminate important information present in source documents in the favor of brevity. Our proposed technique aims to capture all the varied information present in source documents. Although the dataset proved challenging, after performing extensive tests within our experimental setup, we have discovered that our model produces encouraging ROUGE results and summaries when compared to the other published extractive and abstractive text summarization models., Comment: 10 pages, 13 figures, 3 tables

Niniejszy artykuł porusza tematykę funkcjonowania rynku obligacji komunalnych w Polsce. Analiza obejmuje lata 2012-2018. W opracowaniu zwrócono uwagę również na rolę Catalyst w rozwoju dłużnych papierów wartościowych. Materiałem badawczym w niniejszym artykule są: analiza literatury i aktów prawnych, metoda obserwacji, analiza dokumentów źródłowych oraz metoda dedukcji. Rezultatem rozważań jest określenie obszarów, na które należy zwrócić uwagę w celu wzrostu zainteresowania rynkiem obligacji komunalnych. Przeprowadzona analiza wykazała, iż jednostki samorządu terytorialnego, dokonując emisji długu, przyczyniły się w niewielkim stopniu do rozwoju tego rynku. Również powstanie platformy Catalyst spowodowało nieznaczny wzrost zainteresowania emisją tego rodzaju papierów dłużnych, wyższy udział w finansowaniu zadłużenia w analizowanym okresie miały kredyty i pożyczki

The architecture of the text-reuse detection system consists of three main modules, i.e., source retrieval, text analysis, and knowledge-based postprocessing. Each module plays an important role in the accuracy rate of the detection outputs. Therefore, this research focuses on developing the source retrieval system in cases where the source documents have been obfuscated in different levels. Two steps of term weighting were applied to get such documents. The first was the local-word weighting, which has been applied to the test or reused documents to select query per text segments. The tf-idf term weighting was applied for indexing all documents in the corpus and as the basis for computing cosine similarity between the queries per segment and the documents in the corpus. A two-step filtering technique was applied to get the source document candidates. Using artificial cases of text reuse testing, the system achieves the same rates of precision and recall that are 0.967, while the recall rate for the simulated cases of reused text is 0.66.

The Poznan Guardhouse is, from an artistic point of view, a historic monument of very fine quality. It is easily recognizable due to its location at the centre of tourist routes. It is also frequently visited, and is now the seat of the Museum of the Wielkopolska Uprising 1918–1919 – a branch of the Wielkopolska Museum of the Struggle for Independence. In previous scholarly works, its design and construction have been misattributed to Johann Christian Kamsetezer, an architect of King Stanislaus Augustus. Established attributions of monuments dating from the reign of Stanislaus Augustus have been repeated many times and therefore are long-lived. Nonetheless, many of them have been made without being confirmed on the basis of source documents, or without even taking into consideration the artist’s or the epoch’s specific background. They were based on loose associations, without putting forward any arguments. Sometimes they contributed to whole sequences of attributions arising. One speculation led to another, and they were repeated in print, thereby creating ‘indisputable facts’. The Poznan Guardhouse is a good example of such a train of thought.The idea of building a brick Guardhouse in Poznan evolved in 1784, inspired by matters related to organizing the stationing of troops in Warsaw. The Boni Ordinis Committee supervised the project and Kazimierz Raczynski, the Starosta Generalny of Wielkopolska, was also personally responsible. It was Raczynski who donated funds from his personal property to supplement municipal funds derived from the property tax. He also commissioned the design to Stanislaw Zawadzki, with whom he was personally acquainted and who was also architect to the Royal Army. Major Zawadzki’s competencies included designing all the military construction projects undertaken in towns. The architectural and sculptural solutions used in the building attest to such an attribution, as they had been used previously in the architect’s work. In 1787, the Guardhouse in Poznan was built and adorned with sculptures probably made, according to Zawadzki’s designs, by the Poznan sculptor Augustinus Schops.

With the continuous development of deep learning, pre-trained models have achieved sound effects in the field of natural language processing. However, text summarization research is far from what people want, especially in abstractive summarization. A high-quality summarization system needs to focus on the topic content of the document and the similarity between the summary and the source document. In this paper, we propose a topic information fusion and semantic relevance for text summarization based on Fine-tuning BERT(TIF-SR). Primarily, considering the critical role of topic information in summary generation, we extract topic keywords and fusion them with source documents as part of the input. Secondly, make the summary closer to the source document by calculating the semantic similarity between the generated summary and the source document, the quality of the abstract is improved. The experimental data indicate that the ROUGE index and readability have improved in this model, so these shreds of evidence suggest that the method proposed by our model is sufficient.

Introduction:Audits play a critical role in maintaining the integrity of observational cohort data. While previous work has validated the audit process, sending trained auditors to sites (“travel-audits”) can be costly. We investigate the efficacy of training sites to conduct “self-audits.”Methods:In 2017, eight research groups in the Caribbean, Central, and South America network for HIV Epidemiology each audited a subset of their patient records randomly selected by the data coordinating center at Vanderbilt. Designated investigators at each site compared abstracted research data to the original clinical source documents and captured audit findings electronically. Additionally, two Vanderbilt investigators performed on-site travel-audits at three randomly selected sites (one adult and two pediatric) in late summer 2017.Results:Self- and travel-auditors, respectively, reported that 93% and 92% of 8919 data entries, captured across 28 unique clinical variables on 65 patients, were entered correctly. Across all entries, 8409 (94%) received the same assessment from self- and travel-auditors (7988 correct and 421 incorrect). Of 421 entries mutually assessed as “incorrect,” 304 (82%) were corrected by both self- and travel-auditors and 250 of these (72%) received the same corrections. Reason for changing antiretroviral therapy (ART) regimen, ART end date, viral load value, CD4%, and HIV diagnosis date had the most mismatched corrections.Conclusions:With similar overall error rates, findings suggest that data audits conducted by trained local investigators could provide an alternative to on-site audits by external auditors to ensure continued data quality. However, discrepancies observed between corrections illustrate challenges in determining correct values even with audits.

Disparities of socio-economic development, barriers and limitations and social expectations are the circumstances for new look into city, its model and city space management. For this purpose one makes review of space in various ranges and indicates the changes to be done for improving the conditions of territory functionality. A part of a space stays untouched, not to interfere with its previous development. However, a part of territory needs deploying of revitalization process. Particularly it relates to post-industrial, post-military, post-railway, outlying, bad managed or not managed areas. The consequences of city development are changes in its functional arrangement and pushing out some functions to outlying areas or outside of a city. The goal of this article is to research the renewed problem of post-military areas management. The areas have quality diversified localizations and their transfer is followed in diversified technical and functional conditions. The analysis of revitalized post-military areas for some examples. There have been used the following research methods: literature and source documents analysis, deduction and case study.

Background There is an unmet need for review methods to support priority-setting, policy-making and strategic planning when a wide variety of interventions from differing disciplines may have the potential to impact a health outcome of interest. This article describes a Modular Literature Review, a novel systematic search and review method that employs systematic search strategies together with a hierarchy-based appraisal and synthesis of the resulting evidence. Methods We designed the Modular Review to examine the effects of 43 interventions on a health problem of global significance. Using the PICOS (Population, Intervention, Comparison, Outcome, Study design) framework, we developed a single four-module search template in which population, comparison and outcome modules were the same for each search and the intervention module was different for each of the 43 interventions. A series of literature searches were performed in five databases, followed by screening, extraction and analysis of data. “ES documents”, source documents for effect size (ES) estimates, were systematically identified based on a hierarchy of evidence. The evidence was categorised according to the likely effect on the outcome and presented in a standardised format with quantitative effect estimates, meta-analyses and narrative reporting. We compared the Modular Review to other review methods in health research for its strengths and limitations. Results The Modular Review method was used to review the impact of 46 antenatal interventions on four specified birth outcomes within 12 months. A total of 61,279 records were found; 35,244 were screened by title-abstract. Six thousand two hundred seventy-two full articles were reviewed against the inclusion criteria resulting in 365 eligible articles. Conclusions The Modular Review preserves principles that have traditionally been important to systematic reviews but can address multiple research questions simultaneously. The result is an accessible, reliable answer to the question of “what works?”. Thus, it is a well-suited literature review method to support prioritisation, decisions and planning to implement an agenda for health improvement.

The World Health Organization (WHO) has collected information on policies on sexual, reproductive, maternal, newborn, child and adolescent health (SRMNCAH) over many years. Creating a global survey that works for every country context is a well-recognized challenge. A comprehensive SRMNCAH policy survey was conducted by WHO from August 2018 through May 2019. WHO regional and country offices coordinated with Ministries of Health and/or national institutions who completed the questionnaire. The survey was completed by 150 of 194 WHO Member States using an online platform that allowed for submission of national source documents. A validation of the responses for selected survey questions against content of the national source documents was conducted for 101 countries (67%) for the first time in the administration of the survey. Data validation draws attention to survey questions that may have been misunderstood or where there was a lot of missing data, but varying methods for validating survey responses against source documents and separate analysis of laws from policies and guidelines may have hindered the overall conclusions of this process. The SRMNCAH policy survey both provided a platform for countries to track their progress in adopting WHO recommendations in national SRMNCAH-related legislation, policies, guidelines and strategies and was used to create a global database and searchable document repository. The outputs of the SRMNCAH policy survey are resources whose importance will be enriched through policy dialogues and wide utilization. Lessons learned from the methodology used for this survey can help to improve future updates and inform similar efforts.

The paper outlines procedures necessary for development of advanced teaching materials in a large scale and describes a tool that can help the individual authors to improve the efficiency of the process through a semi-automated conversion of source documents to a form suitable for presentation on web pages. The tool (in its prototype version) has been already tested within a nationwide project.

Extraction of categorised named entities from text is a complex task given the availability of a variety of Named Entity Recognition (NER) models and the unstructured information encoded in different source document formats. Processing the documents to extract text, identifying suitable NER models for a task, and obtaining statistical information is important in data analysis to make informed decisions. This paper presents TNNT, a toolkit that automates the extraction of categorised named entities from unstructured information encoded in source documents, using diverse state-of-the-art Natural Language Processing (NLP) tools and NER models. TNNT integrates 21 different NER models as part of a Knowledge Graph Construction Pipeline (KGCP) that takes a document set as input and processes it based on the defined settings, applying the selected blocks of NER models to output the results. The toolkit generates all results with an integrated summary of the extracted entities, enabling enhanced data analysis to support the KGCP, and also, to aid further NLP tasks., This demo paper will be submitted at K-Cap 2021

A Development Safety Update Report (DSUR) is a comprehensive review of safety information collected during an annual reporting period for an investigational drug. The creation of a DSUR is a resource-intensive process, requiring effective communication among, and collaboration with, various functional stakeholders. To increase the efficiency and cost-effectiveness of generating a DSUR with the use of an electronic authoring platform. This computerized platform auto-populates the DSUR template using available source data. Requirements for the DSUR authoring tool were developed, and available data sources were mapped to respective sections of a company DSUR template. The DSUR authoring tool, mined, scanned, and extracted the relevant data from multiple-input source documents using Natural Language Processing logic. The data were then auto-populated into the template, as required by regulatory guidance ICH-E2F, with different text options based on questions and answers. The time- and cost-savings gained through automation were analyzed for DSURs authored during 2017–2019. The DSUR contains 31 sections (20 main sections and 11 sub-sections), of which 9 were fully automated, 12 were partially automated, and 10 were not automated in this release of the automation tool. Use of the DSUR automation tool resulted in a time-savings of approximately 25% per report, corresponding to a cost saving of US$4550 per report. Deployment of the automation tool reduced the time and cost required to manually produce DSURs, as well as improved the quality, compliance, and consistency of company-prepared DSURs. This tool enhanced the potential of the organization to generate larger volumes of DSURs in a timely manner, without requiring additional resources or compromising quality. This or a similar authoring automation tool could be employed in the future to generate other regulatory submission documents, which also require various source documents and cross-functional contributions.

This paper highlights the System Effectiveness methodology and its role in acquiring and sustaining U.S. military weapons systems from 1958 to 2021. Given the long period covered by this study and the many changes to the acquisition process, it would be reasonable to expect that the methodology would change and adapt, and the study supports this assumption. The study used three qualitative methods: a structured review of the literature related to System Effectiveness, a grounded theory analysis of the structured literature review, and a historiography of the initial grounded theory results. The research identified three epochs, the first two lasting approximately 22 years each. The conclusions are fourfold. First, the role of System Effectiveness today is vastly diminished from its original purpose because original material was not widely accessible to the community of interest during the formative years. Second, analysis of source documents provides insight into how to correct the misconceptions of the past and incorporate System Effectiveness into modern system engineering. Third, the models developed in epoch one may have relevance for today’s problems. The last conclusion is that an integrated research methodology is a valuable tool for making sense of a mass of conflicting information spread out over time. This the most comprehensive research on systems effectiveness ever published. Based on over 500 documents, it is rigorous and innovative and provides the basis for a structured and integrated approach for utilizing System Effectiveness in emerging U.S. defense system acquisition and sustainment challenges.

Health management information systems (HMIS) are a crucial source of timely health statistics and have the potential to improve reporting in low-income countries. However, concerns about data quality have hampered their widespread adoption in research and policy decisions. This article presents results from a data verification study undertaken to gain insights into the quality of HMIS data in Ethiopia. We also provide recommendations for working with HMIS data for research and policy translation. We linked the HMIS to the 2016 Emergency Obstetric and Newborn Care Assessment, a national census of all health facilities that provided maternal and newborn health services in Ethiopia. We compared the number of visits for deliveries and caesarean sections (C-sections) reported in the HMIS in 2015 (January–December) to those found in source documents (paper-based labour and delivery and operating theatre registers) in 2425 facilities across Ethiopia. We found that two-thirds of facilities had ‘good’ HMIS reporting for deliveries (defined as reporting within 10% of source documents) and half had ‘very good’ reporting (within 5% of source documents). Results were similar for reporting on C-section deliveries. We found that good reporting was more common in urban areas (OR: 1.30, 95% CI 1.06 to 1.59), public facilities (OR: 2.95, 95% CI 1.38 to 6.29) and in hospitals compared with health centres (OR: 1.71, 95% CI 1.13 to 2.61). Facilities in the Somali and Afar regions had the lowest odds of good reporting compared with Addis Ababa and were more likely to over-report deliveries in the HMIS. Further work remains to address remaining discrepancies in the Ethiopian HMIS. Nonetheless, our findings corroborate previous data verification exercises in Ethiopia and support greater use and uptake of HMIS data for research and policy decisions (particularly, greater use of HMIS data elements (eg, absolute number of services provided each month) rather than coverage indicators). Increased use of these data, combined with feedback mechanisms, is necessary to maintain data quality.

In abstractive single-document summarization task, generated summaries always suffer from fabricated and less informative content. An intuitive way to alleviate this problem is to merge external semantic knowledge into the model framework. In this paper, we incorporate explicit graphs based on semantic knowledge, including term frequency, discourse information, and entities with their relations, into neural abstractive summarization for the problem. We propose a novel model for abstractive single-document Summarization based on Semantic Knowledge Graphs (SKGSUM), which regards sentences and entities as nodes, captures the relations between units in different textual levels, and focuses on salient content in the source documents to guide the summary generation process. To the best of our knowledge, we are the first to exploit different textual-unit levels explicit graph representations in a unified framework for the neural abstractive summarization task. Results show that our model achieves significant improvements on both XSum and CNN/Daily Mail datasets over some strong baselines. Human evaluations further indicate that our model can generate informative and coherent summaries.

Medical knowledge bases (KBs), distilled from biomedical literature and regulatory actions, are expected to provide high-quality information to facilitate clinical decision making. Entity disambiguation (also referred to as entity linking) is considered as an essential task in unlocking the wealth of such medical KBs. However, existing medical entity disambiguation methods are not adequate due to word discrepancies between the entities in the KB and the text snippets in the source documents. Recently, graph neural networks (GNNs) have proven to be very effective and provide state-of-the-art results for many real-world applications with graph-structured data. In this paper, we introduce ED-GNN based on three representative GNNs (GraphSAGE, R-GCN, and MAGNN) for medical entity disambiguation. We develop two optimization techniques to fine-tune and improve ED-GNN. First, we introduce a novel strategy to represent entities that are mentioned in text snippets as a query graph. Second, we design an effective negative sampling strategy that identifies hard negative samples to improve the model's disambiguation capability. Compared to the best performing state-of-the-art solutions, our ED-GNN offers an average improvement of 7.3% in terms of F1 score on five real-world datasets., To appear in SIGMOD 2021

The aim of the scientific research included in the paper was to show the issue of Polish women and the cultural changes in the Polish People’s Republic in the end of 1980s. These transformations were reflected in women’s magazines, including in «Zwierciadło», being also a platform for disseminating the activities of the only official women’s movement at that time – League of Polish Women among readers. The research studies are new; so far scientific research on the importance of the women’s press on the subject of «Zwierciadło» has been conducted only by the author of this study. The method of press analysis, analysing individual studies of the «Zwierciadło» magazine, and the historical method of analysing source documents and literature on the subject were used in the study. As a result of the study, an image of women achieving professional, social and, thus, personal success, disseminated in «Zwierciadło», was shown. The image also demonstrated some role models for women – what the women’s success which Polish women should strive for can and should look like. «Zwierciadło: Pismo Ligi Kobiet Polskich», a magazine addressed to women, was published in 1982–1990 and promoted the organization and its achievements. The magazine sought to present issues concerning the life of Polish women, their everyday problems, but also successes to be enjoyed by Polish women and women from abroad. The magazine provided examples of women’s careers. Professional work was to be a way to personal success and social advancement. The image of successful women presented in the magazine differed from the possibility to achieve the success by typical magazine’s readers, including League of Polish Women members.

This study was designed to collect data on key issues related to implementation of the digital forms of tax checks, in particular e-audit, Fiscal Services of different countries. The research is focused on three-areas: a) to explore the essence and the structure of Standard Audit File for Tax; b) to learn the international experience of using tax audit files; c) to develop recommendations on the possibility of introducing the most effective methods in national practice.Standard Audit File for Tax (SAF-T) is an electronic file, which contains accurate audit data, exported from the initial accounting system. SAF-T 1.0 consists of four sections: «Header», «Master Files», «General Ledger Entries» and «Source Documents». In version 2.0, 8 subunits were added to the «Master Files» section: «Taxonomies», «UOMT Table», «Analysis Type Table», «Transaction Type Table», «Products», «Physical Stock», «Owners» and «Assets».The experience of the implementation and components of tax audit files of the leading European countries indicate that: a) most countries use the tax audit file in accordance with the recommendations of the OSER (Portugal, Norway, Austria, Lithuania), but there are some that have substantially modified it (Singapore); b) there are different ways to provide data: from pilot projects and voluntary application, to mandatory filing by certain categories or by all taxpayers; c) mainly the fiscal authorities apply the phased implementation of tax audit files in practice (Austria, Lithuania, Norway, etc.).It is established that before introducing SAF-T into national practice, it is worth considering that the standard approach can be neither practical nor desirable because each tax service faces a variety of conditions, the legislative environment, administrative practice and the tax culture of taxpayers.

This article considers document flow in the management system of chain trade companies. Taking into account the specific character of their activities, chain trade companies constantly face the demand for unification of document processing. Volume of document flow in chain companies is significant and rather costly. At the same time it constantly requires optimization in accordance with the transformation of a company’s business processes posed by the changing market. The paper examines arrangements for organizing document flow of chain retailers, defines general components of accounting policies, classifies major documents used in the company’s operating activities. The author also identifies stages of document flow in chain retailing companies starting from the interface of interaction with suppliers up to the interface of interaction with consumers. The results of the study show that while considering document flow as an imparting business process, it is important to take into account the documentation of core and control processes of an enterprise, due to the fact that in the majority of cases documents serve as an input and output of various business processes. In its turn, performance of the entire chain trade company depends on the proper document processing.

The aim of the article is the general characterization of cyberterrorism as a new and constantly evolving form of terrorism. The phenomenon was described in the context of globalization processes and the main definitions of terrorism were cited, followed by the specific factors determining cyberterrorism. The article was based on an analysis of source documents – legislation on terrorism prevention and cyberspace protection. Definitions review was performed. The results of earlier research related to the topic of work are quoted. It has been assessed that in the future the threat of cyber-attacks will be a challenge for states and international organizations. The development of modern technologies and the creation of computerized societies is a factor that provides new areas of action for terrorists. Potential targets of attacks are varied and difficult to protect. Preventive actions should be characterized by a comprehensive approach to the problem and systemic, long-term action in the international sphere.

Because of M*A*S*H and other popular portrayals, helicopter evacuation of casualties has been closely linked to the Korean War. We sought to investigate their role in military medicine during this conflict.This study incorporated a thorough review of the original source documents dating to the Korean War that are housed in the National Archives, the Military History Institute, and other repositories.Medical evacuation helicopters entered the war late, after the United Nations forces had suffered the majority of their casualties. There were relatively few helicopters in the country, and a combination of mechanical and personnel issues kept many grounded. Technological constraints limited their efficacy. Military policy forbade rescues from the front lines, and interhospital transfers comprised a significant percentage of their missions.Helicopters did not appreciably decrease the average time from wounding to surgical care, nor did they evacuate a statistically significant number of casualties, and ultimately, they had minimal effect on military medicine. However, the war did provide helicopters the opportunity to prove themselves conceptually, leading to their widespread usage in Vietnam, in later conflicts, and ultimately in civilian health care systems.

The land and building cadastre is the register significantly affecting the activities of the state. One of the cornerstones of its functioning are the cadastral data entered by an administrative employee basing on the source documents. The aim of this article is to present the problem of data incorrectness and types of errors occurring. The method of verification and the obtained results are discussed. The paper focuses on the importance of the technology used, the experience gained and knowledge of regulations that are both valid and no longer in force. The analysis was made on the basis of verifications carried out in 2015 and 2016, in the cadastral data base of the city of Katowice.

Background Care for patients with thyroid nodules is complex and multidisciplinary, and research demonstrates variation in care. The objective was to develop clinical guidelines and quality metrics to reduce unwarranted variation and improve quality. Methods Multidisciplinary expert consensus and modified Delphi approach. Source documents were workflow algorithms from Kaiser Permanente Northern California and Cancer Care of Ontario based on the 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer. Results A consensus-based, unified preoperative, perioperative, and postoperative workflow was developed for North American use. Twenty-one panelists achieved consensus on 16 statements about workflow-embedded process and outcomes metrics addressing safety, access, appropriateness, efficiency, effectiveness, and patient centeredness of care. Conclusion A panel of Canadian and United States experts achieved consensus on workflows and quality metric statements to help reduce unwarranted variation in care, improving overall quality of care for patients diagnosed with thyroid nodules.

Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intelligence and robotic process automation to automate processing of adverse event reports. The pilot paradigm was used to simultaneously test proposed solutions of three commercial vendors. The result confirmed the feasibility of using artificial intelligence–based technology to support extraction from adverse event source documents and evaluation of case validity. In addition, the pilot demonstrated viability of the use of safety database data fields as a surrogate for otherwise time‐consuming and costly direct annotation of source documents. Finally, the evaluation and scoring method used in the pilot was able to differentiate vendor capabilities and identify the best candidate to move into the discovery phase.

Word embeddings are increasingly being used as a tool to study word associations in specific corpora. However, it is unclear whether such embeddings reflect enduring properties of language or if they are sensitive to inconsequential variations in the source documents. We find that nearest-neighbor distances are highly sensitive to small changes in the training corpus for a variety of algorithms. For all methods, including specific documents in the training set can result in substantial variations. We show that these effects are more prominent for smaller training corpora. We recommend that users never rely on single embedding models for distance calculations, but rather average over multiple bootstrap samples, especially for small corpora.

Query focused summarization (QFS) models aim to generate summaries from source documents that can answer the given query. Most previous work on QFS only considers the query relevance criterion when producing the summary. However, studying the effect of answer relevance in the summary generating process is also important. In this paper, we propose QFS-BART, a model that incorporates the explicit answer relevance of the source documents given the query via a question answering model, to generate coherent and answer-related summaries. Furthermore, our model can take advantage of large pre-trained models which improve the summarization performance significantly. Empirical results on the Debatepedia dataset show that the proposed model achieves the new state-of-the-art performance., The two authors contribute equally. Accepted as a short paper in Findings of ACL 2021

Overview In the current work, we build upon a small body of literature that delineates cross-cutting factors, or processes, of evidence-based alcohol or other drug (AOD) therapies. Here, we discuss Psychoeducation. We define psychoeducation as a brief process of therapy focused on the communication of varied aspects of disease- and/or treatment-related information. Method The authors conducted a literature review and qualitative content analysis to derive a set of principles and practices of psychoeducation. The review used source documents (i.e., literature reviews, therapy manuals, and government-issued practice guidelines) and videos (i.e., therapy demonstration videos), and we performed analyses in NVIVO. Results The review identified nine principles and 21 practices. Together, the principles suggest that psychoeducation in evidence-based addictions therapies can be characterized as a collaborative approach to teaching, education, or other provision of information. The term collaborative denotes a shift in emphasis from compliance to a more egalitarian partnership focused on meeting individual health needs. Specific practices included ways to transition to psychoeducation (e.g., provide rationale and promote expectancy), teaching methods in psychoeducation (e.g., use plain language), tailoring content in psychoeducation (e.g., to learning style, to cultural worldview), and methods for facilitating a dialogue about the information (i.e., five question types), for facilitating understanding and retention of the information (e.g., tailor to individual needs, use of varied teaching modalities), and how to end psychoeducation and engage in related goal-setting, where applicable. Conclusions We frame psychoeducation as a collaborative approach to teaching where client engagement, understanding, and utilization of the information provided is the central goal. We offer a novel resource with pragmatic value to trainees, providers, and clinical supervisors who do not consider themselves aligned with a single evidence-based modality but who may benefit from training and proficiency assessment in core, behavioral health counseling competencies.

ive summarization is useful in providing a summary or a digest of news or other web texts and enhancing users reading experience, especially when they are reading on small displays such as mobile phones. However, existing encoder-decoder summarization models have difficulty learning the latent alignment between source documents and summaries because of their vast disparity in length. In this paper, we propose a extractor-abstractor framework in which the keyword-based extractor selects a few sets of salient sentences from the input document and then the abstractor paraphrases these sets of sentences in parallel, which are more aligned to the summary, to generate the final summary. The new extractor and abstractor are pretrained from a set of “pseudo summaries” extracted by specially designed heuristics, and then further trained together in a reinforcement learning framework. The results show that the proposed model generates high-quality summaries with faster training speed and less training memory footprint, and outperforms the state-of-the-art models on CNN/Daily Mail, Webis-TLDR-17, Webis-Snippet-20, WikiHow and DUC-2002 datasets.

Text summarization is a procedure of extracting the meaning details from source documents. Multi-document summarization is an automated task where the necessary details are extracted using several input documents. Diverse techniques were presented on the generation of the summary from single or many documents. Single and multiple document summarization techniques pose several issues because they might comprise of maximum repetitive information compared to the single document. To resolve this issue, this study develops a novel improved cuckoo search optimization algorithm (ICSA) for multi-document summarization. For improving the optimization abilities of the CS technique, the orthogonal concepts and simulated annealing (SA) are included to raise the exploitation searching capability. The presented ICSA model involves distinct sub-processes namely preprocessing, input, and summary representation. The main aim is to summarize the representation task involves the creation of a document summary including the meaning data. Through the optimal sentence choosing task using the ICSA model, the required sentences defining the summary are selected. An extensive experimental validation process was carried out on the DUC 2006 and 2007 datasets and the efficiency is examined in terms of distinct aspects.

Introduction This is a comprehensive history of the International Society for Sexual Medicine (ISSM) and its founding organizations regarding the publications, including the journals and the publication committee, and the communication tools of the organization since its inception. Objectives The object of this review is to provide a detailed and comprehensive history of the publication and communication tools of the ISSM and the people who have participated in production of these efforts. Methods Recorded Publication Committee minutes, filed letters, the various journals themselves, printed News bulletins, and Publishers reports to the society served as source documents to produce this history. The author has participated in many of the journal establishments and has kept an extensive personnel file of the events related in this history. All written history has not only relied on personal memories of these events but have been verified from the stored personal files. Printed and website stored journal and News bulletin have served as source material for this history. Also, Power Point presentations by the editors of the journals at the Publication Committee meetings have served as source material. Finally, annual, and semi-annual reports of the Publishers presented at Publication Committee meetings of the ISSM are source material. Results After extensive review of the historical material listed in the Methods section of this abstract, this comprehensive history of the communication efforts of this society has provided a rich and dynamic historical document for this society. Conclusion This extensive, detailed, and comprehensive history of the communication tools of this society help us to record and remember the events and the people involved in this process. Sharing scientific information and information regarding the life of the International Society for Sexual Medicine have been an important function of this society from early. Lewis RW. Comprehensive History of the International Society for Sexual Medicine–Journals and Communication. Sex Med Rev 2021;9:542–567.

Feature models (FM) are a valuable resource in the analysis of software product lines (SPL). They provide a visual abstraction of the variation points in a family of related software products. FMs can be manually created by domain experts or extracted (semi-) automatically from textual documents such as product descriptions or requirements specifications. Nevertheless, there is no way to measure the accuracy of a FM with respect to the information described in the source documents. This paper proposes a method to quantify and visualize whether the elements in a FM (features and relationships) conform to the information available in a set of specification documents. Both the correctness (choice of representative elements) and completeness (no missing elements) of the FM are considered. Designers can use this feedback to fix defects in the FM or to detect incomplete or inconsistent information in the source documents.

ive text summarization aims at compressing the information of a long source document into a rephrased, condensed summary. Despite advances in modeling techniques, abstractive summarization models still suffer from several key challenges: (i) layout bias: they overfit to the style of training corpora; (ii) limited abstractiveness: they are optimized to copying n-grams from the source rather than generating novel abstractive summaries; (iii) lack of transparency: they are not interpretable. In this work, we propose a framework based on document-level structure induction for summarization to address these challenges. To this end, we propose incorporating latent and explicit dependencies across sentences in the source document into end-to-end single-document summarization models. Our framework complements standard encoder-decoder summarization models by augmenting them with rich structure-aware document representations based on implicitly learned (latent) structures and externally-derived linguistic (explicit) structures. We show that our summarization framework, trained on the CNN/DM dataset, improves the coverage of content in the source documents, generates more abstractive summaries by generating more novel n-grams, and incorporates interpretable sentence-level structures, while performing on par with standard baselines.

In our modern society, almost all events, processes, and decisions in a corporation are documented by internal written communication, legal filings, or business and financial news. The valuable knowledge in such collections is not directly accessible by computers as they mostly consist of unstructured text. This chapter provides an overview of corpora commonly used in research and highlights related work and state-of-the-art approaches to extract and represent financial entities and relations.The second part of this chapter considers applications based on knowledge graphs of automatically extracted facts. Traditional information retrieval systems typically require the user to have prior knowledge of the data. Suitable visualization techniques can overcome this requirement and enable users to explore large sets of documents. Furthermore, data mining techniques can be used to enrich or filter knowledge graphs. This information can augment source documents and guide exploration processes. Systems for document exploration are tailored to specific tasks, such as investigative work in audits or legal discovery, monitoring compliance, or providing information in a retrieval system to support decisions.

ive multi-document summarisation (MDS) remains a challenging task. Part of the problem is the question as to how to preserve a document’s polarity in the summary. We propose an opinion polarity attention model for MDS, which incorporates a polarity estimator based on a BERT-GRU sentiment analysis network. It captures the impact of opinions expressed in the source documents and integrates it in the attention mechanism. Experimental results using a state-of-the-art MDS approach and a common benchmark test collection demonstrate that this model has a measurable positive effect using a range of metrics.

Web document summarization is a very important function for knowledge management when documents are very huge and dynamic. This helps the document readers to easily read and understand. In general, summarization is done based on the extraction of sentences from the retrieved documents and assembled with the needed proposition. Text content plays a major role in the Web, and extraction of text content is a challenging task. Recently, one of the problems that arise with the rapid growth of the Web and general information availability (sometimes referred to as an information overloading) is the increased need for effective and powerful text summarization. In this paper, a system is built for automatic text summarization from the source documents which is retrieved from the Web. The proposed method considers the ontology approach to extract the text summary according to query terms, which are existing in the ontology graph based on their depth. Also, attributes are used to improve the semantic representation of a sentence’s information from contents.

Purpose: The purpose of this article is to assess whether having a creditworthiness assessment from more than one credit rating agency by issuers of green debt instruments affects the number of issues and the average amount issued. This objective was achieved through the process of analysis of the ratings assigned by the rating agencies. Methodology: Due to the complexity of the data, mixed research methods were used such as observation, analysis, and inference. The study used data from Refinitiv Eikon. The credit ratings for the issuers, announced on the issue date, have been analyzed. The analysis covered debt instruments issued in all currencies in the years 2010-2020. The empirical research was carried out using the observation method, the analysis of source documents, and the method of deduction. Findings: In the analyzed period only 44.22% of issuers had credit ratings. The results of the conducted research indicate that the number of green debt instruments and the average issue amount were affected by the number of ratings given to the issuer. Because the largest number of green debt instruments and the highest average issue amount was held by green debt issuers with three ratings, there is a need for an additional creditworthiness assessment. Practical implications: The conclusions of this study can be used in the process of obtaining financing from capital markets on green projects. The content of the article concerns the conclusions from the analysis of the credit ratings of the issuers of green debt instruments. Originality/Value: The theoretical and empirical literature does not provide guidance on the impact of the issuer's credit rating on the success of issuing debt instruments, in particular green ones., peer-reviewed

Text summarization is the process of generating the condensed view of the text by selecting useful and relevant information from the original source documents. It is a sub-topic of natural language Processing. Text summarization is a technique for understanding the aim of any document, to visualize large text document within short duration. Summarization provides flexibility and convenience. Business leaders, analyst, and researchers must undergo huge number of documents on a day-to-day basis to stay ahead, and an oversized portion of their time is spent just deciding what document has relevancy and what is not. By finding out important and relevant sentences and creating summaries, it is possible to quickly check whether or not a document is worth reading. In this paper, we propose to design automatic text summarizer to summarize the multiple text documents. The input to the system is the multiple sources of news articles. Important sentences from the source document are selected and arranged in the destination documents or the summarized documents. This is called as the extraction technique in automatic text summarization. Here, one document visited is being processed, and its summary is generated using extraction technique through which a weighted graph is constructed using language processing.

Summaries are expected to relay the most amount of information in the least amount of words. Summary assessment tools such as Rouge, METEOR, and BLEU fail to explain the factual consistency of summaries with source documents and also disregard the synonymy between expressions. Information-coverage is a measure of the amount of important information retained in the summary. We propose ICE and ICE-T metrics that employ pre-trained word embeddings, Part-Of-Speech or POS-based keyword extraction, cosine-similarity, source length, and target length, for gauging the information-coverage in automatically shaped abstracts. We propose five POS-based keyword sampling techniques (NN, NN-VB, NN-JJ, NN-VB-JJ, and NN-VB-JJ-CD) for efficient retrieval of predominant information from the source text. Experiments show that: (1) ICE very strongly correlates with human-judgments w.r.t NN-VB-JJ-CD sampling (Pearson (0.989), Spearman rank (0.987) and Kendall rank (0.919)); and NN-VB-JJ sampling (Pearson (0.978), Spearman rank (0.979) and Kendall rank (0.899)) (2) ICE-T strongly correlates with human-judgments w.r.t NN-VB-JJ-CD sampling (Pearson (0.904), Spearman rank (0.846) and Kendall rank (0.702)); and NN-VB-JJ sampling (Pearson (0.877) and Spearman rank (0.832)). ICE and ICE-T are reliable information-coverage estimation tools as they equate eminently with human evaluations compared to Rouge (Rouge-1, Rouge-2, Rouge-L, Rouge-WE), and BLEU.