In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
Aims and objectives. The Forensic Early Warning Signs of Aggression Inventory (FESAI) was developed to assist nurses and patients in identifying early warning signs and constructing individual early detection plans (EDP) for the prevention of aggressive incidents. The aims of this research were as follows: First, to study the prevalence of early warning signs of aggression, measured with the FESAI, in a sample of forensic patients, and second, to explore whether there are any types of warning signs typical of diagnostic subgroups or offender subgroups. Background. Reconstructing patients’ changes in behaviour prior to aggressive incidents may contribute to identify early warning signs specific to the individual patient. The EDP comprises an early intervention strategy suggested by the patient and approved by the nurses. Implementation of EDP may enhance efficient risk assessment and management. Design. An explorative design was used to review existing records and to monitor frequencies of early warning signs. Methods. Early detection plans of 171 patients from two forensic hospital wards were examined. Frequency distributions were estimated by recording the early warning signs on the FESAI. Rank order correlation analyses were conducted to compare diagnostic subgroups and offender subgroups concerning types and frequencies of warning signs. Results. The FESAI categories with the highest frequency rank were the following: (1) anger, (2) social withdrawal, (3) superficial contact and (4) non-aggressive antisocial behaviour. There were no significant differences between subgroups of patients concerning the ranks of the four categories of early warning signs. Conclusion. The results suggest that the FESAI covers very well the wide variety of occurred warning signs reported in the EDPs. No group profiles of warning signs were found to be specific to diagnosis or offence type. Relevance to clinical practice. Applying the FESAI to develop individual EDPs appears to be a promising approach to enhance risk assessment and management.
Purpose: This study examined the effects of a giant (4×3 m) exercising board game intervention on ambulatory physical activity (PA) and a broader array of physical and psychological outcomes among nursing home residents. Materials and methods: A quasi-experimental longitudinal study was carried out in two comparable nursing homes. Ten participants (aged 82.5±6.3 and comprising 6 women) meeting the inclusion criteria took part in the 1-month intervention in one nursing home, whereas 11 participants (aged 89.9±3.1 with 8 women) were assigned to the control group in the other nursing home. The giant exercising board game required participants to per-form strength, flexibility, balance and endurance activities. The assistance provided by an exercising specialist decreased gradually during the intervention in an autonomy-oriented approach based on the self-determination theory. The following were assessed at baseline, after the intervention and after a follow-up period of 3 months: PA (steps/day and energy expenditure/day with ActiGraph), cognitive status (mini mental state examination), quality of life (EuroQol 5-dimensions), motivation for PA (Behavioral Regulation in Exercise Questionnaire-2), gait and balance (Tinetti and Short Physical Performance Battery), functional mobility (timed up and go), and the muscular isometric strength of the lower limb muscles. Results and conclusion: In the intervention group, PA increased from 2,921 steps/day at baseline to 3,358 steps/day after the intervention (+14.9%, P=0.04) and 4,083 steps/day (+39.8%, P=0.03) after 3 months. Energy expenditure/day also increased after the intervention (+110 kcal/day, +6.3%, P=0.01) and after 3 months (+219 kcal/day, +12.3%, P=0.02). Quality of life (P<0.05), balance and gait (P<0.05), and strength of the ankle (P<0.05) were also improved after 3 months. Such improvements were not observed in the control group. The preliminary results are promising but further investigation is required to confirm and evaluate the long-term effectiveness of PA interventions in nursing homes.
The continuous monitoring of health indicators in biofluids such as sweat, saliva, blood, and urine has great potential for preventive medicine. Techniques that continuously monitor biomarkers still remain a major technological challenge. Recently, a concept of dynamic biosensing was published that is based on mediator particles. Such mediator particles exhibit rapid switching between a bound and unbound state during interaction with a probing structure to which they are connected through a molecular tether (like a balloon on a string). Although the concept of using mediator particles for dynamics biosensing is very promising, the used detection method is not a viable solution as it is not miniaturizable. We propose to use a photonic ring resonator (RR) or Mach-Zender interferometer (MZI) as the probing structure in combination with a highly miniaturizable readout scheme. In this project, we perform preliminary experiments to prove that this photonic approach can be used for the detection of the mediator particles tethered to the photonic waveguide. To bridge the gap with the practical application by health professionals, we will enrich the envisioned solution through OnePlanet's OpenEd program. OpenEd aims to share technology and innovations (e.g. prototypes) with educational institutes (MBO, HBO) that want to further innovate their courses or work methods, such that current and future professionals are well prepared to work with new (digital) technologies. By presenting our use-case as a 'challenge' to teachers, students and practitioners, OpenEd also allows enriching the use-case by involving (future) health professionals that can provide feedback on - or further investigation of - the practical application of our new technology from the health professional's perspective.
The building industry is a major target for resource-efficiency developments, which are crucial in European Union’s roadmaps. Using renewable materials impacts the sustainability of buildings and is set as urgent target in current architectural practice. The building industry needs renewable materials positively impacting the CO2 footprint without drawbacks. The use of wood and timber as renewable construction materials has potentials, but also drawbacks because trees need long time to grow; producing timber generates considerable waste; and the process from trees to applications in buildings requires transportation and CO2 emission. This research generates new scientific knowledge and a feasibility study for a new wood-like bio-material - made of cellulose and lignin from (local) residual biomass via i.e. 3D printing - suitable for applications in the building industry. It contributes to a sustainable built environment as it transforms waste from different sectors into a local resource to produce a low carbon-footprint bio-material for the construction sector. Through testing, the project will study the material properties of samples of raw and 3D printed material, correlating different material recipes that combine lignin and cellulose and different 3D printing production parameters. It will map the material properties with the requirements of the construction industry for different building products, indicating potentials and limits of the proposed bio-material. The project will produce new knowledge on the material properties, a preliminary production concept and an overview of potentials and limits for application in the built environment. The outcome will be used by industry to achieve a marketable new bio-material; as well as in further scientific academic research.
