PCK is seen as the transformation of content knowledge and pedagogical knowledge into a different type of knowledge that is used to develop and carry out teaching strategies. To gain more insight into the extent to which PCK is content specific, the PCK about more topics or concepts should be compared. However, researchers have rarely compared teachers’ concrete PCK about more than one topic. To examine the content dependency of PCK, we captured the PCK of sixteen experienced Dutch history teachers about two historical contexts (i.e. topics) using interviews and Content Representation questionnaires. Analysis reveals that all history teachers’ PCK about the two contexts overlaps, although the degree of overlap differs. Teachers with relatively more overlap are driven by their overarching subject related goals and less by the historical context they teach. We discuss the significance of these outcomes for the role of teaching orientation as a part of PCK.
PURPOSE: The purpose of this study was to gain insight into how low back pain (LBP) patients conceptualize the construct of expectations regarding treatment.METHODS: This study was nested within a mixed-method randomized clinical trial comparing three primary care interventions for LBP. A total of 77 participants with LBP lasting longer than 6 weeks were included; semi-structured interviews were conducted querying patients about their expectations for treatment. Also factors influencing their expectations were explored. Interviews were administered following enrollment into the study, but prior to study treatment. Two researchers independently conducted a content analysis using NVIVO 9 software.RESULTS: LBP patients' expectations could be categorized in two main domains: outcome and process expectations, each with subdomains. Patients expressed expectations in all subdomains both as values (what they hoped) and probabilities (what they thought was likely). In multiple subdomains, there were differences in the nature (positive vs. negative) and frequency of value and probability expectations. Participants reported that multiple factors influenced their expectations of which past experience with treatment appeared to be of major influence on probability expectations.CONCLUSION AND RECOMMENDATIONS: This study showed that LBP patients' expectations for treatment are multifaceted. Current measurement instruments do not cover all domains and subdomains of expectations. Therefore, we recommend the development of new or improved measures that make a distinction between value and probability expectations and assess process and/or outcome expectations covering multiple subdomains. Some of the influencing factors found in this study may be useful targets for altering patients' treatment expectations and improving health outcomes.
AIM: The purpose of this study was to describe how nurses apply the components of family nursing conversations in their home healthcare practice.METHOD: A qualitative content analysis with a deductive approach was conducted. Home healthcare nurses conducted family nursing conversations with families from their practice. Families were selected based on three nursing diagnoses: risk of caregiver role strain, caregiver role strain or interrupted family processes. Nurses audio-recorded each conversation and completed a written reflection form afterwards. Transcripts of the audio-recorded conversations were analysed in Atlas.ti 8.0 to come to descriptions of how nurses applied each component. Nurses' reflections on their application were integrated in the descriptions.RESULTS: A total of 17 conversations were audio-recorded. The application of each component was described as well as nurses' reflections on their application. Nurses altered or omitted components due to their clinical judgment of families' needs in specific situations, due to needs for adjustment of components in the transfer from theory to practice or due to limited skill or self-confidence.CONCLUSION: All of the components were applied in a cohesive manner. Nurses' application of the components demonstrates that clinical judgment is important in applying them. Further training or experience may be required to optimise nurses' skill and self-confidence in applying the components. This study demonstrates the applicability of the family nursing conversations components in home health care, allowing exploration of the working mechanisms and benefits of family nursing conversations for families involved in long-term caregiving in future studies.
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Carboxylated cellulose is an important product on the market, and one of the most well-known examples is carboxymethylcellulose (CMC). However, CMC is prepared by modification of cellulose with the extremely hazardous compound monochloracetic acid. In this project, we want to make a carboxylated cellulose that is a functional equivalent for CMC using a greener process with renewable raw materials derived from levulinic acid. Processes to achieve cellulose with a low and a high carboxylation degree will be designed.
The research, supported by our partners, sets out to understand the drivers and barriers to sustainable logistics in port operations using a case study of drone package delivery at Rotterdam Port. Beyond the technical challenges of drone technology as an upcoming technology, it needs to be clarified how drones can operate within a port ecosystem and how they could contribute to sustainable logistics. KRVE (boatmen association), supported by other stakeholders of Rotterdam port, approached our school to conduct exploratory research. Rotterdam Port is the busiest port in Europe in terms of container volume. Thirty thousand vessels enter the port yearly, all needing various services, including deliveries. Around 120 packages/day are delivered to ships/offices onshore using small boats, cars, or trucks. Deliveries can take hours, although the distance to the receiver is close via the air. Around 80% of the packages are up to 20kg, with a maximum of 50kg. Typical content includes documents, spare parts, and samples for chemical analysis. Delivery of packages using drones has advantages compared with traditional transport methods: 1. It can save time, which is critical to port operators and ship owners trying to reduce mooring costs. 2. It can increase logistic efficiency by streamlining operations. 3. It can reduce carbon emissions by limiting the use of diesel engines, boats, cars, and trucks. 4. It can reduce potential accidents involving people in dangerous environments. The research will highlight whether drones can create value (economic, environmental, social) for logistics in port operations. The research output links to key national logistic agenda topics such as a circular economy with the development of innovative logistic ecosystems, energy transition with the reduction of carbon emissions, societal earning potential where new technology can stimulate the economy, digitalization, key enabling technology for lean operations, and opportunities for innovative business models.
The project aim is to improve collusion resistance of real-world content delivery systems. The research will address the following topics: • Dynamic tracing. Improve the Laarhoven et al. dynamic tracing constructions [1,2] [A11,A19]. Modify the tally based decoder [A1,A3] to make use of dynamic side information. • Defense against multi-channel attacks. Colluders can easily spread the usage of their content access keys over multiple channels, thus making tracing more difficult. These attack scenarios have hardly been studied. Our aim is to reach the same level of understanding as in the single-channel case, i.e. to know the location of the saddlepoint and to derive good accusation scores. Preferably we want to tackle multi-channel dynamic tracing. • Watermarking layer. The watermarking layer (how to embed secret information into content) and the coding layer (what symbols to embed) are mostly treated independently. By using soft decoding techniques and exploiting the “nuts and bolts” of the embedding technique as an extra engineering degree of freedom, one should be able to improve collusion resistance. • Machine Learning. Finding a score function against unknown attacks is difficult. For non-binary decisions there exists no optimal procedure like Neyman-Pearson scoring. We want to investigate if machine learning can yield a reliable way to classify users as attacker or innocent. • Attacker cost/benefit analysis. For the various use cases (static versus dynamic, single-channel versus multi-channel) we will devise economic models and use these to determine the range of operational parameters where the attackers have a financial benefit. For the first three topics we have a fairly accurate idea how they can be achieved, based on work done in the CREST project, which was headed by the main applicant. Neural Networks (NNs) have enjoyed great success in recognizing patterns, particularly Convolutional NNs in image recognition. Recurrent NNs ("LSTM networks") are successfully applied in translation tasks. We plan to combine these two approaches, inspired by traditional score functions, to study whether they can lead to improved tracing. An often-overlooked reality is that large-scale piracy runs as a for-profit business. Thus countermeasures need not be perfect, as long as they increase the attack cost enough to make piracy unattractive. In the field of collusion resistance, this cost analysis has never been performed yet; even a simple model will be valuable to understand which countermeasures are effective.
