Summary View Research Articles

Above the Law: From Medieval England to Trump v. the United States

Abstract There is nothing unprecedented about prosecuting Donald Trump. While it’s certainly true that no president has (yet) to be indicted, if we look at to the long stretch of English political-legal history, we find many precedents. Because what happened in England fueled the American Revolution and the Framers’ view of the chief executive. As Richard II and Charles I discovered to their cost, acting as if they were above the law could lead to their deposition and eventual death, and the framers agreed. Thomas Jefferson asserted in A Summary View of the Rights of British America (1774), retained “the powers of punishment or removal” of their rulers. Holding the chief executive, whether a king, a prime minister, or a president is irrelevant, to account for alleged crimes is, as the phrase goes, baked into American constitutional law. But the Supreme Court has ruled otherwise. The president now enjoys the immunity Charles I claimed. We are now at the cusp of something without precedent: an absolutist presidency.

Five decades of policymaking in the EU – background and overview of the current state of employee financial participation

Purpose Opinions drafted by the European Economic and Social Committee (EESC), and reports and studies by the European Parliament and 2014 and 2018 Resolutions on employee financial participation (EFP) emphasised the growing importance of EFP, particularly with respect to small and medium-sized enterprises. Against this background, the commission included the promotion of employee share ownership in its Action Plan to reform European company law and corporate governance and embarked on the 2013/14 Pilot Project. Based on the most recent data on the scope and impact of various EFP schemes in EU companies and the legal and regulatory changes in individual Member States, the aim of this article is to provide an overview of policymaking and the main trends of the dynamics of EFP over the last three decades.Design/methodology/approach We give an overview (1) of the analysis of the most recent rounds of different large-scale cross-country surveys (2015 European Working Conditions Survey, 2021 CRANET [Cranfield Network on International Human Resource Management], 2019 European Company Survey [ECS]) and (2) of the EU policy documents and legislative acts over the last three decades. We provide a tabular overview of the status quo in all 29 countries under consideration as of January 2024 to provide the reader with an Alta vista summary view of all forms of EFP practised.Findings The European Commission’s interest in EFP has grown substantially since the publication of the first PEPPER Report in 1991 and the Council Recommendation on EFP of 27 July 1992. Since then, the European Union has not only extended from 12 Members States to currently 27 but has also faced many complex and urgent challenges. Financial and other crises have endangered prosperity and cohesion on the continent and both, the financial crisis of 2008/09, and the coronavirus disease 2019 (COVID-19) pandemic 2020/21 have left their marks on “Social Europe”.Originality/value The European Commission’s interest in EFP has grown substantially since the publication of the first PEPPER (Promotion of Employee Participation in Profits and Enterprise Results) Report in 1991 and the Council Recommendation on EFP on 27 July 1992. Since then, the European Union has not only extended from 12 Members States to currently 27 but has also faced many complex and urgent challenges. Financial and other crises have endangered prosperity and cohesion on the continent and both, the financial crisis of 2008/09, and the COVID-19 pandemic 2020/21 have left their marks on “Social Europe”.

Narratives from GPT-derived networks of news and a link to financial markets dislocations

AbstractWe introduce a novel framework to study the dynamics of news narratives, by leveraging GPT3.5 advanced text analysis capabilities and graph theory. In particular, we focus on a corpus of economic articles from The Wall Street Journal and dynamically extract the main topics of discussion over time, in a completely systematic and scalable fashion. As a simple application of the suggested approach, we show how the structure of such topics of discussion has a statistically significant relationship with the contemporaneous state of financial markets, which can be used to construct an investment strategy or monitor financial risks. Our work is based on the intrinsic ability of GPT models to track the context of sentences within a document, thanks to which we can accurately extract a ranking of the most important entities discussed within each article, and evaluate their entity-specific sentiments. Then, we create a graph for each week of data, in which nodes are the entities retrieved and edges are built from the co-occurrence of such entities within articles. Graph centrality measures are computed over time to track the most representative keywords of topics of discussion, which result in an accurate summary view of the evolution of economic narratives. Fuzzy community detection is finally used to cluster linked entities into a more detailed representation of topics. Such groups of entities are mapped to the related journal articles, which are in turn summarised to reach a highly nuanced and interpretable view of the topics discussed within each week. Linking the features of these topics to the relevant financial market time series, we find that high fragmentation within our networks’ communities relates to moments of financial markets dislocations (i.e. dates with unusually high volatility across asset classes). This result should thus motivate stronger effort within financial research to move beyond ubiquitous sentiment analysis of news and delve deeper into broader and more holistic studies of textual data.

Emergent invariance and scaling properties in the collective return dynamics of a stock market.

A key metric to determine the performance of a stock in a market is its return over different investment horizons (τ). Several works have observed heavy-tailed behavior in the distributions of returns in different markets, which are observable indicators of underlying complex dynamics. Such prior works study return distributions that are marginalized across the individual stocks in the market, and do not track statistics about the joint distributions of returns conditioned on different stocks, which would be useful for optimizing inter-stock asset allocation strategies. As a step towards this goal, we study emergent phenomena in the distributions of returns as captured by their pairwise correlations. In particular, we consider the pairwise (between stocks i, j) partial correlations of returns with respect to the market mode, ci,j(τ), (thus, correcting for the baseline return behavior of the market), over different time horizons (τ), and discover two novel emergent phenomena: (i) the standardized distributions of the ci,j(τ)'s are observed to be invariant of τ ranging from from 1000min (2.5 days) to 30000min (2.5 months); (ii) the scaling of the standard deviation of ci,j(τ)'s with τ admits good fits to simple model classes such as a power-law τ-λ or stretched exponential function [Formula: see text] (λ, β > 0). Moreover, the parameters governing these fits provide a summary view of market health: for instance, in years marked by unprecedented financial crises-for example 2008 and 2020-values of λ (scaling exponent) are substantially lower. Finally, we demonstrate that the observed emergent behavior cannot be adequately supported by existing generative frameworks such as single- and multi-factor models. We introduce a promising agent-based Vicsek model that closes this gap.

Electronic Health Record Usability When Caring for Children With Medical Complexity.

To evaluate usability of and clinician satisfaction with the electronic health record (EHR) in the context of caring for children with medical complexity (CMC) at a large academic pediatric hospital and to identify key areas for targeted improvements. Cross-sectional study of pediatric faculty and advanced practice providers across several pediatric specialties using an online Research Electronic Data Capture survey. EHR usability was measured with 6 validated questions from the National Usability-Focused Health Information System Scale, and satisfaction with common EHR functionalities was measured with 6 original Likert-scale questions and 3 free-text questions. Results were analyzed with bivariate testing. More than half of providers completed the survey (n = 81, response rate 56%). When asked 6 positively-phrased, validated usability questions, a majority of respondents either agreed or were neutral. Respondents were most dissatisfied with information quality of the summary view and most satisfied with physician communication. Older respondents were less satisfied with EHR usability (P < .01). Focusing on functionalities needed for CMC, the majority of respondents were dissatisfied with the chart review process. More respondents were dissatisfied with order entry (P = .002) and documentation (P = .017) when caring for CMC compared with caring for other patients. The most cited challenges were locating recent patient data, performing an accurate medication reconciliation, and lack of specialized documentation templates. Clinicians are less satisfied with common EHR functionalities when caring for CMC compared with caring for all other patients. Targeted interventions to improve usability and common EHR functionalities for CMC are necessary to improve the user experience.

Retrieving Rare Cases: A Protocol for Searching Complex Medical Cases

This study sought to provide a protocol for searching complex medical cases of grand rounds. A clinical informationist was embedded in gastroenterology grand rounds to use comprehensive search strategies and summarize patients’ information through concept mapping. Our proposed protocol classifies into three categories: (1) The general search strategy, (2) The protocol for searching for evidence about rare diseases, and (3) Identifying other resources more than routine medical databases. This approach represents a novel method beyond previous studies which were focused on usual ward rounds to facilitate evidence-based decision-making by providing and simplifying a comprehensive summary view of complex medical cases.

Deep Learning for Zero-day Malware Detection and Classification: A Survey

Zero-day malware is malware that has never been seen before or is so new that no anti-malware software can catch it. This novelty and the lack of existing mitigation strategies make zero-day malware challenging to detect and defend against. In recent years, deep learning has become the dominant and leading branch of machine learning in various research fields, including malware detection. Considering the significant threat of zero-day malware to cybersecurity and business continuity, it is necessary to identify deep learning techniques that can somehow be effective in detecting or classifying such malware. But so far, such a comprehensive review has not been conducted. In this article, we study deep learning techniques in terms of their ability to detect or classify zero-day malware. Based on our findings, we propose a taxonomy and divide different zero-day resistant, deep malware detection and classification techniques into four main categories: unsupervised, semi-supervised, few-shot, and adversarial resistant. We compare the techniques in each category in terms of various factors, including deep learning architecture, feature encoding, platform, detection or classification functionality, and whether the authors have performed a zero-day evaluation. We also provide a summary view of the reviewed papers and discuss their main characteristics and challenges.

Cdem: A macOS program for discrete element modeling of tectonic structures

Abstract cdem is a macOS document-based application for two-dimensional discrete element modeling of tectonic structures and their associated deformation. Documents encapsulate simulations that can be run and explored simultaneously. A document contains three main views: (1) Set-up view, to define the assembly size, element properties, anisotropy, boundary conditions (type of faulting), overburden stress, erosion, and syn-tectonic sedimentation; (2) Summary view, which displays the details of the model after initialization; and (3) Results view, which displays the geometry of the model while it is running or after the run and allows exploring the model’s evolution in terms of geometry, displacement, strain, or stress. We illustrate the use of the program for assembly calibration and the modeling of contractional and extensional structures without and with syn-tectonic sedimentation. In all these cases, cdem produces realistic incremental and finite deformation. cdem is less powerful than its precursor cdem2D, but it can import and visualize cdem2D results, making the combined use of these two programs a robust suite for mechanically modeling tectonic structures.

Research on Data Mining Models for the Internet of Things

Data mining is a technique or method which is used to extract datasets from different source and the hidden part of applications. Data mining is also used to make a pattern form a large amount of data by which the data will be more accurate and visible to the user. Data mining is used to enable the user to get a summary view of data according to their research. This paper discusses three data mining model of IOT that how data mining model helps IOT in growing the business and how to improve IOT using data mining technique. The future scope of IOT is discussed

Abstract 3163: Ontology guided navigation of somatic variants, mutational signatures, gene expression and histology images for pediatric cancer

Abstract PeCan Knowledgebase on St. Jude Cloud (pecan.stjude.cloud), initially developed as a resource of curated genomic variants of pediatric cancer (PeCan), is now significantly expanded to comprise a hub of interconnected data facets for over 9,000 hematologic (heme), CNS, and non-CNS solid (solid) tumor patient samples from around the world. The new data facets, which include gene expression, mutational signatures, and histology, can be explored alongside our existing variants data facet inspiring new hypothesis generation. Variants shows a genomic landscape view (i.e. oncoprint view) and gene- or genome-level view (i.e. ProteinPaint view). Expression data, generated from normalized RNA-seq of ~2,500 samples, can be explored via interactive 2-dimensional maps, revealing distinct subtypes relevant for patient stratification for precision therapy. Mutational signatures, identified from ~2,000 WGS samples, are presented as a heatmap across subtypes, in addition to a summary view for a user-defined cohort or individual sample for which we also display a mutation profile frequency plot together and identified signatures. Histology enables review of histological slide images and associated clinical notes for ~3,000 solid tumors via a searchable interface. As all samples on PeCan have been mapped to a WHO pediatric cancer classification based ontology, the user can customize the view of each data facet presented in PeCan by selecting a specific cancer subtype. Integrative analysis between the data facets has enabled new insights into pediatric cancer biology as demonstrated in the following two examples. First is the discovery of two potential subtypes of adamantinomatous craniopharyngioma. These were initially identified via expression analysis which revealed two distinct groups that were confirmed by examination of associated histology slide data which revealed delineation by brain invasion. Second is an analysis that links germline and somatic alterations in genes involved in DNA Damage Response with mutational signatures associated with homologous recombination deficiency (HRD). This provided new insights on the applicability of therapies targeting HRD in the pediatric cancer population. These examples demonstrate the potential value of PeCan in advancing clinical diagnosis classifications of pediatric cancer and exploration of new therapeutic opportunities. PeCan is an evolving knowledgebase, as we are continuously expanding the platform and adding data over time to foster scientific discovery for the global research community, with the goal of improving treatments for pediatric cancer. Citation Format: Alexander M. Gout, Stephanie Sandor, Delaram Rahbarinia, Jobin Sunny, James Madson, Lucian Vacaroiu, Wentao Yang, Ben Lansdell, Michael Macias, Samuel W. Brady, David Finkelstein, Victor Pastor, Kevin Benton, Andrew Frantz, Mark R. Wilkinson, Cynthia Cline, Brent A. Orr, Abbas Shirinifard, Elizabeth Stewart, Michael Rusch, Xin Zhou, Michael Dyer, David A. Wheeler, Clay McLeod, Jinghui Zhang. Ontology guided navigation of somatic variants, mutational signatures, gene expression and histology images for pediatric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3163.

The Storied Landscape of Iroquoia: History, Conquest, and Memory in the Native Northeast by Chad L. Anderson

Reviewed by: The Storied Landscape of Iroquoia: History, Conquest, and Memory in the Native Northeast by Chad L. Anderson David L. Preston The Storied Landscape of Iroquoia: History, Conquest, and Memory in the Native Northeast. By Chad L. Anderson. Borderlands and Transcultural Studies. Lincoln: University of Nebraska Press, 2020. 288 pages. Cloth, ebook, pdf. John Mitchell's 1755 Map of the British and French Dominions in North America was so comprehensive and expansive that it remained influential in imperial boundary making for decades to come.1 As a summary view of the British imperial imagination, it drew upon previous cartographic work and expressed Britain's territorial claims to North America from the Mississippi to Newfoundland. Along the crest of the Appalachian Mountains, Mitchell engraved the word Iroquois in letters that stretched from Virginia's frontier northeast toward Montreal and the Saint Lawrence Valley. The Haudenosaunee, as the Six Nations or Iroquois are more accurately known, figured prominently in British imperial ambitions in North America, as they maintained a powerful and independent Indigenous confederation in the eighteenth-century Northeast. Mitchell's rendering captured the eighteenth-century British fiction that their Six Nations allies controlled those designated lands, based upon an equally fictional Haudenosaunee claim of having won them by right of conquest. As Chad L. Anderson makes clear, Iroquoia was a "storied landscape" that remained central in British and American imaginations, even after triumphant revolutionaries had expanded into that region and destroyed much of the Indigenous landscape in the years following the American Revolution. Anderson's The Storied Landscape of Iroquoia traces how early Americans both erased and appropriated the Native past as they imagined the new republic. Ignoring clear evidence of Haudenosaunee towns and agriculture, Americans increasingly portrayed Natives as forest fixtures rather than as skilled and settled farmers. They justified Native dispossession by arguing that American improvements and "progress" would lead to the "inevitable" decline of Native peoples. Echoing familiar themes of classic works by Anthony F. C. Wallace, Laurence M. Hauptman, and Alan Taylor, [End Page 389] the book's greatest value is in how well it captures contested European and American perceptions of the Haudenosaunee past and their meanings for the early republic.2 But in contrast to those authors, who deeply explored Haudenosaunee experiences and perspectives, Anderson focuses almost exclusively on European or American views of the Iroquoian landscape and past.3 Making a compelling case that a close examination of colonizers' ideologies is warranted, Anderson's central contribution is to trace the evolution of Americans' attitudes about the Haudenosaunee lands and landscape, past and present, as they "struggled over the meaning of conquest" (15). Unfolding like a series of focused journal essays, the book first explores the Haudenosaunee world and landscape in the mid-eighteenth century and argues that the "American Revolution marked the turning point in their ability to define the nature of settlement" (11). Anderson underscores that the Haudenosaunee were settlers with ineffable connections to their homelands. Haudenosaunee territories framed by the Saint Lawrence, Champlain, Mohawk, Susquehanna, and Ohio Valleys constituted a built and natural landscape brimming with historical, mythic, and spiritual meanings for the Haudenosaunee. On the eve of the American Revolution, the Haudenosaunee population of around nine thousand prospered in distinct towns and settlements with abundant agriculture. Anderson describes Haudenosaunee lands prior to the revolution as "relatively unknown to outsiders" (8), but his use of "relatively" misses a long and complicated interaction between Haudenosaunee and Euro-American settlers who had competed for land and resources since the early years of the eighteenth century. He claims, for example, that "Europeans did not permanently settle in the lands of the Haudenosaunee prior to the American Revolution" (19) but does not take into account scholarly literature examining how Palatine, Scottish, Dutch, and other European families had been permanently settled—in many cases cheek by jowl—alongside Oneida and Mohawk communities beginning in the 1720s.4 [End Page 390] Indeed, in the early years of the Mohawk Valley's settlement, Europeans initially requested permission of the Haudenosaunee owners to establish their farms. Similarly, French Canadian habitants lived intermixed with Haudenosaunee communities in the Saint Lawrence Valley (an area of Iroquoia that the book...

The Digital Analytic Patient Reviewer (DAPR) for COVID-19 Data Mart Validation.

To provide high-quality data for coronavirus disease 2019 (COVID-19) research, we validated derived COVID-19 clinical indicators and 22 associated machine learning phenotypes, in the Mass General Brigham (MGB) COVID-19 Data Mart. Fifteen reviewers performed a retrospective manual chart review for 150 COVID-19-positive patients in the data mart. To support rapid chart review for a wide range of target data, we offered a natural language processing (NLP)-based chart review tool, the Digital Analytic Patient Reviewer (DAPR). For this work, we designed a dedicated patient summary view and developed new 127 NLP logics to extract COVID-19 relevant medical concepts and target phenotypes. Moreover, we transformed DAPR for research purposes so that patient information is used for an approved research purpose only and enabled fast access to the integrated patient information. Lastly, we performed a survey to evaluate the validation difficulty and usefulness of the DAPR. The concepts for COVID-19-positive cohort, COVID-19 index date, COVID-19-related admission, and the admission date were shown to have high values in all evaluation metrics. However, three phenotypes showed notable performance degradation than the positive predictive value in the prepandemic population. Based on these results, we removed the three phenotypes from our data mart. In the survey about using the tool, participants expressed positive attitudes toward using DAPR for chart review. They assessed that the validation was easy and DAPR helped find relevant information. Some validation difficulties were also discussed. Use of NLP technology in the chart review helped to cope with the challenges of the COVID-19 data validation task and accelerated the process. As a result, we could provide more reliable research data promptly and respond to the COVID-19 crisis. DAPR's benefit can be expanded to other domains. We plan to operationalize it for wider research groups.

Improving Urban Air Quality Monitoring in Delhi, India: Reflections on Low-Cost Air Quality Sensors (LCAQS) and Participatory Engagement

In Delhi, the capital city of India, air pollution has been a perpetual menace to urban sustainability and public health. The present study uses a mixed-method approach to enumerate to the urban authorities: (a) the state of air pollution in the city; (b) systemic flaws in the current monitoring network; (c) potential means to bolster it; and (d) need of a participatory framework for monitoring. Information about Air Quality Index (AQI), obtained from 36 monitoring stations across Delhi is compared between 2021 (20 April–25 May; 2nd year/phase of SARS-CoV-2 lockdown), and the corresponding time periods in 2020 (1st year/phase of lockdown), and 2019 (business-as-usual) using the Mann–Whitney U Test. AQI during the 2021 lockdown (a) appeared statistically more similar ( p &lt; .01) to that of 2019 and (b) exceeded the environmental health safety benchmark for 85% days during the study period (20 April–25 May). However, this only presented a partial glimpse into the air pollution status. It owes to numerous ‘holes’ in the AQI data record (no data and/or insufficient data). Moreover, certain areas in Delhi yet have no monitoring station, or only too few, to yield a ‘representative’ estimate (inadequate spatial coverage). Such shortcomings in the existing monitoring network may deter future research and targeted/informed decision-making for pollution control. To that end, the present research offers a summary view of Low-Cost Air Quality Sensors (LCAQS), to offer the urban sustainability authorities, ‘complementary’ technique to bolster and diversify the existing network. The main advantages and disadvantages of various LCAQS sensor technologies are highlighted while emphasizing on the challenges around various calibration techniques (linear and non-linear). The final section reflects on the integration of science and technology with social dimensions of air quality monitoring and highlights key requirements for (a) community mobilization and (b) stakeholder engagement to forge a participatory systems’ design for LCAQS deployment.

Personality Cults from a Communicative Standpoint

Drawing upon a wide variety of personality cults in religion, culture and politics from Ancient Egypt to our times, the author attempts to present a summary view of this phenomenon from a communicative standpoint. Personality cult is seen as an attribution of universal and eternal socio-cultural significance to certain beings, messages and interaction scenarios in defiance of changes in and diversity of the surrounding reality. The communicative implementation of such a cult involves the suspension of some of the most basic mechanisms of social coordination. Thus, deification of political, cultural or religious leaders eliminates the subordination of individuals to their social roles, whereas canonization severs the ties of certain selected texts with the contexts of their production and reception. Last, but not least, random signaling between the subject of cultic adoration and his or her subordinates runs counter the standard cooperation rules in interaction (‘turn-taking’). Illustrating these points, the article points out at specific communicative pathologies accompanying personality cults and jeopardizing the stability of their socio-cultural environments.

DENOTATION OF DISCOURSE IN HISTORICAL PERSPECTIVE

Background. Over the past thirty years, the concept of “discourse” has been closely integrated into many scientific disciplines, and therefore its determination is complicated. Researchers cannot come to a common opinion regarding this linguistic category. An overview of discourse in a diachronic perspective allows us to explore diverse approaches to its study and identify the most relevant definition of this linguistic term.&#x0D; Purpose. In this paper, an attempt is made to interpret the term discourse by examining it in a diachronic aspect.&#x0D; Materials and methods. The research is based on general scientific methods (generalization, analysis) and a descriptive method.&#x0D; Results. As a result of the analysis of the theoretical material, the authors summarize that there is no generally accepted interpretation of this linguistic category in the linguistic literature. The researchers agree and disagree in some ways, which is reflected in the inconsistency of their opinions. However, the review of scientific papers offered in this study makes it possible to get a summary view of linguists on this issue. Summarizing the data gained, the authors give their interpretation of the concept of “discourse”. Moreover, the authors come to the conclusion that a wide range of scientific applications of the term and the vector of scientific integration that is gaining popularity makes a significant contribution to the development of discourse theory as an interdisciplinary field of research.&#x0D; Practical implications. The results of this study can be applied by researchers of scientific discourse, as well as in the preparation of textbooks on academic writing, the style of scientific text.

P190 Implementation of IBD symptom diary – Case Finnish IBD register

Abstract Background BCB MyHealth application is a digital monitoring system of patient reported outcomes (PROMs) fully integrated and synchronized with the Finnish IBD Register, which delivers information about the patients’ disease and state of health. Our system monitors patients’ symptoms and well-being only at one point. There is a need to monitor patients’ symptoms and well-being more closely between follow-up visits. Therefore, we developed a digital daily self-monitoring symptom diary service, Feeling application, which is suitable for all patients with IBD in everyday practice. In addition, our goal was to create a system that allows IBD-patients to view their own parameters used to monitor treatment. Methods As a part of MyHealth, we developed the Feeling app (Figure 1) with Tampere University Hospital. Project group included gastroenterologists, IBD-nurses, and the hospitals’ senior medical advisor of health technology assessment. The Feeling app is a digital daily self-monitoring symptom diary service intended for IBD-patients. The system supports biometric authentication (Figure 2) and saves responses to IBD Register database. Figure 1. IBD Symptom Diary Figure 2. Biometric authentication Results Feeling app enables continuous home-monitoring of patients with IBD. This symptom diary allows patients to monitor their symptoms and well-being daily. They can see their own answers and how their symptoms and well-being have developed weekly, monthly, or annually. During treatment follow-up, the Feeling app also visualizes lab parameters used to monitor treatment, such as CRP, calprotectin and hemoglobin values, which are derived from the IBD register (Figure 3). In addition, certain endoscopy related parameters, such as SES-CD and Mayo Score are visualized for the patient. Health care professionals (HCPs) can see summary view all the data that the patient has inserted in the Feeling app in IBD register and the data is visualized in real time. Tampere University Hospital started to use the Feeling app in 2021. Figure 3. Summary view Conclusion The Feeling app provides new ways to support patient care and is an efficient tool for long-term data collection. The opportunity of patients to monitor the development of their symptoms and well-being, and to see the lab parameters used to monitor treatment may improve adherence to treatment. With efficient data collection we have increased opportunity to utilize the data for AI activities such as synthetic data and outcomes prediction.

Strategic Background of the Start-Up—Qualitative Analysis

A start-up is a relatively new and attractive entrepreneurial form that is being explored in a broader national economy and industry context. However, there is little knowledge about its strategy, which is mainly represented by the business development strategy. The main goal of the research is to deepen and expand knowledge about the strategic background of start-ups, which is preparation and condition for a development strategy and later a business strategy, too. The partial goals of the research are in-depth and detailed knowledge of the content and novelty of the business idea, the quality of the internal environment of the start-up, the nature of the external environment of the start-up, and the content of the goals. The research sample contains 147 start-ups operating in Slovakia. Each start-up was researched by a member of the research team, who personally recorded the statements of the founder. The research results are based on qualitative analysis and synthesis of statements of the founders of start-ups. The main result of the research is a summary view of the strategic background of the examined start-ups, which expresses the peculiarities of the start-up business making and documents the possibilities and motives of the start-up’s strategizing. The summary of knowledge about the strategic background of the start-up is synthesized into a strategic balance sheet, which expresses the strategic perspective of the start-up, the possibilities of survival, explains the potential failure, and provides a solution to the identified imbalance. The practical use of the results consists of providing a model of the strategic balance, which is the result of field research of real and functioning start-ups. The originality and value of the research lie in the direct collection of qualitative data, immediate knowledge of business reality, and the synthesis of results into a comprehensive and at the same time detailed picture of the strategic background of the start-up.

An Idea of Higher Education Renewal

Beginning with the briefest reference to the state of higher education today, this paper overviews moral and philosophical concepts of and disposition to education in ancient Greece from the works of Plato and Aristotle, takes a summary view of the subjects taught, sums up the subject content of liberal arts and the principles of rhetoric. The author assumes that even if a dedicated return to the classical ideals may never happen in higher education today, a few concrete ideas might be helpful. With reference to concrete works of classical authors, a suggestion is made to stop never-ending reforms in universities, to recover the teaching of such subjects as style in language and literature programmes, to renew the subjects of history, philosophy and logic and to introduce memory-based learning while paying tribute to classical antiquity and regaining local traditions.

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease-specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders EXpanding (T-REX) was created to identify changes in both rare and common cells across human immune monitoring settings. T-REX identified cells with highly similar phenotypes that localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized MHCII tetramer reagents that mark rhinovirus-specific CD4+ cells were left out during analysis and then used to test whether T-REX identified biologically significant cells. T-REX identified rhinovirus-specific CD4+ T cells based on phenotypically homogeneous cells expanding by ≥95% following infection. T-REX successfully identified hotspots of virus-specific T cells by comparing infection (day 7) to either pre-infection (day 0) or post-infection (day 28) samples. Plotting the direction and degree of change for each individual donor provided a useful summary view and revealed patterns of immune system behavior across immune monitoring settings. For example, the magnitude and direction of change in some COVID-19 patients was comparable to blast crisis acute myeloid leukemia patients undergoing a complete response to chemotherapy. Other COVID-19 patients instead displayed an immune trajectory like that seen in rhinovirus infection or checkpoint inhibitor therapy for melanoma. The T-REX algorithm thus rapidly identifies and characterizes mechanistically significant cells and places emerging diseases into a systems immunology context for comparison to well-studied immune changes.

The Structure of the Start-Up Business Model—Qualitative Analysis

The aim of the research is an in-depth and detailed knowledge of the start-up business model, which is structured according to Canvas visualization. The research sample contains 106 start-ups operating in Slovakia. Each start-up was researched by a member of the research team, who personally recorded the statements of the founder. The research results are based on qualitative analysis and synthesis of statements of the founders of start-ups. The main results of the research are a summary view of the business model of the examined start-ups, which expresses the peculiarities of the start-up business making, including priorities within its blocks, and the identification of space for variations in the business model of start-ups. A secondary result of the research is the subjective and objective circumstances of the creation of a business idea, its content, confirmation of its originality, and the peculiarity of the start-up development process. The practical use of the results consists in providing a pattern of the business model and the possibilities of its variation, which are the result of field research of real and functioning start-ups. The originality and value of the research lie in the direct collection of qualitative data, immediate knowledge of business reality, and the synthesis of results into a comprehensive and detailed picture of the start-up business model.