Individuals suffering from long-term cognitive impairments following COVID-19 engage in a wide range of activities throughout their cognitive rehabilitation journey. This journey may include diagnostic assessments, therapeutic interventions, administrative coordination, and self-managed rehabilitation tasks. To effectively support and enhance such multifaceted rehabilitation processes, a digiphysical approach – which integrates digital and physical components – offers a promising solution. This article presents a process-oriented prototype based on the digiphysical approach, designed to bridge clinical and administrative tasks while combining digital and physical interventions. The article also reports findings from an initial evaluation of the prototype conducted with key rehabilitation professionals as respondents. Furthermore, five reusable solution patterns for implementing digiphysical rehabilitation are presented. These patterns are intended to be applicable not only in the studied context but also to support other care providers and organizations aiming to develop or enhance digiphysical rehabilitation services.

Custom CRISPR screens are powerful tools for rapid, hypothesis-driven discovery, but their design is often complex and time-consuming. Green Listed v2.0 simplifies this process with an intuitive workflow for designing custom CRISPR spacer libraries and supports downstream analysis for all users, irrespective of their computational experience. The web application features a user-friendly graphical interface freely accessible at https://greenlisted.cmm.se. Version 2.0 includes significant upgrades to the original 2016 version that were implemented based on user feedback. This includes a new gene synonym tool, expanded library options, optimized output lists, performance improvements, and linked scripts for the rational design of custom CRISPR screen gene sets.

The vast and growing web of rules and regulations that govern modern organisations is increasingly difficult to comprehend and manage. One technique for understanding and managing rules among stakeholders is enterprise modelling of organisational rules. However, rule models are usually flat, lacking hierarchical structure that allows for effective abstraction and reduced complexity. The aim of this paper is to examine the different aspects of hierarchy among organisational rules. A model pattern is proposed, based on the main constructs rule description, norm hierarchy, scope, and citation. The model pattern is demonstrated by instantiating it in a concrete case, the European Union’s General Data Protection Regulation (GDPR), using Wikibase Cloud to structure the data and Kumu.io to visualise it.

Human rights groups of all sizes and specializations gather evidence of human rights violations. Those with sufficient resources commonly use dedicated databases to manage the intricate web of sources, events, and analyses that build a strong case. However, developing databases for the needs of each organization remains a challenge. Effective database design requires a data model, which functions as a blueprint for how the data is structured and related. A most basic example of what a data model can specify is that a human rights violation is committed by at least one perpetrator, and that the perpetrator’s attributes, such as name or date of birth, should be recorded. A data model that is shared and generic reduces the need to reinvent the wheel since its design can be reused for several databases. In the information systems field, such shared models are called ontologies. Despite the critical nature of the matter, no ontology for human rights violations documentation exists. The present note, therefore, will present the design of the first ontology of this kind. It was developed in association with the human rights group HURIDOCS, which specializes in information management. The requirements elicitation included unstructured interviews with HURIDOCS, document analysis of human rights manuals, and a survey with practitioners. The resulting ontology, named OntoRights, is freely available online with an open license. The evaluation of OntoRights suggests that OntoRights could be highly useful for case databases.

Health care is a complex domain containing large amounts of data, including clinical and administrative data. Furthermore, the domain includes advanced decision-making utilising the collected data. Various IT systems based on AI technologies, such as machine learning, have been promoted as a way to improve both the quality and efficiency of health care. So far, the focus has been on supporting quite narrow and data-intensive activities carried out by a single actor, such as interpreting X-ray images and performing triage. However, providing health care for a single patient can involve a comprehensive process with numerous actors, ranging from home care and primary care to specialist care. In this paper, we examine how existing AI solutions can support a complex care process involving several collaborating actors. We base the examination on a health care case from Swedish elderly care. The case is used to identify multiple problem areas, which are then compared to existing AI solutions

The nature of modern organizations needs to be increasingly adaptive, since they are dealing with a constant demand to respond to stimuli derived from the dynamic environments they operate in. Changing their capabilities is a common response, and this makes capability management a vital aspect of organizational survivability. To date, there are no approaches specifically designed to address this specific situation. KYKLOS and Compass are two interlinked approaches of different complexity, a DSML and a canvas, developed to support capability change. As recently developed methods, they lacked formal demonstration and evaluation; therefore, the goal of this article is to present the demonstration and evaluation of the two approaches by their stakeholders, in particular, business and modeling experts. A case study in a Swedish company in the ERP system consulting domain that is undergoing changes in its sales and consulting capabilities related to evolving customer requirements has been used to demonstrate and evaluate the two approaches. The process consisted of two evaluation cycles. The first cycle concerned KYKLOS and used two categories of evaluators, the business experts and the modeling experts. While the modeling experts evaluated positively the method, the business experts had difficulties associated with its ease of use and adoption. This resulted in the development of Compass, which was evaluated by business experts during the second evaluation cycle. Compass was evaluated more positively in terms of the difficult aspects, but the challenge is ongoing and motivates further future research.

Patients with long-term cognitive impairments following COVID-19 face significant challenges in their rehabilitation, which involves essential therapeutic procedures, administrative tasks, diagnostic tests, and self-assessments. "Digiphysical" methods, combining digital and physical healthcare interventions, offer promising solutions to enhance these rehabilitation processes. In this paper, we present a newly developed digital rehabilitation prototype based on the digiphysical approach. The prototype is designed to integrate digital and physical interventions, streamline clinical and administrative tasks, support the entire rehabilitation process, and facilitate self-directed rehabilitation. It addresses the rehabilitation needs from both the patients' and the rehabilitation personnel's perspectives. In this paper, we present the results of an initial evaluation of the prototype conducted with key rehabilitation professionals.

Health- and social care are complex domains, requiring the collaboration of several professions and several care provider organizations within and between the domains. In this paper, we describe the collaboration between care providers in the Stockholm County and the municipality of Stockholm, highlighting how the information is exchanged, which IT system that supports the exchange, and legal prerequisites for the collaboration. We identify several problems in current practices, including the lack of system integration, and the underutilization of existing digital solutions. We also suggest several solutions aimed at improving the technical infrastructure for digital collaboration. These include the integration of IT systems, simplification of access to essential information, and the adoption of modern APIs to facilitate better communication among healthcare providers. We also present legal issues for the collaboration and how they can be addressed.

Zero-trust security involves designing, coding, and deploying applications, assuming that threats may exist both inside and outside the application environment. Developing applications using a zero-trust design is complex since it requires internal development teams to understand and apply zero-trust principles throughout the development process. This is especially crucial for microservice architectures, where many independent teams develop services. However, enforcing and teaching security principles may lead to a formal process, focusing on documentation and auditing rather than agile development. In this paper, we describe a pragmatic use of a modeling tool that is tied to a knowledge repository and contains means for team communication. The tool supports a systemic way of developing zero-trust architectures, catering to both programming needs and the desire to improve the overall development process. The paper concludes with lessons learned from a bank case study where the tool has been developed and utilised for microservices development.