Tools for Assessing Climate Impacts on Fish and Wildlife

Climate change is already affecting many fish and wildlife populations. Managing these populations requires an understanding of the nature, magnitude, and distribution of current and future climate impacts. Scientists and managers have at their disposal a wide array of models for projecting climate impacts that can be used to build such an understanding. Here, we provide a broad overview of the types of models available for forecasting the effects of climate change on key processes that affect fish and wildlife habitat (hydrology, fire, and vegetation), as well as on individual species distributions and populations. We present a framework for how climate-impacts modeling can be used to address management concerns, providing examples of model-based assessments of climate impacts on salmon populations in the Pacific Northwest, fire regimes in the boreal region of Canada, prairies and savannas in the Willamette Valley-Puget Sound Trough-Georgia Basin ecoregion, and marten Martes americana populations in the northeastern United States and southeastern Canada. We also highlight some key limitations of these models and discuss how such limitations should be managed. We conclude with a general discussion of how these models can be integrated into fish and wildlife management

ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

This article presents the ReMashed system that recommends learning content from emerging information of a Mash-Up Personal Learning Environment. ReMashed offers advice to find most suitable learning content for individual competence development of lifelong learners. The ReMashed system was initially designed to offer navigational support to lifelong learners in informal learning settings. In this article we want to discuss its ability to be used also in formal learning settings. For this purpose, we discuss the use of two different recommendation approaches for formal and informal learning within ReMashed

ReMashed – Recommendations for Mash-Up Personal Learning Environments

Drachsler, H., Pecceu, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed - Recommendations for Mash-Up Personal Learning Environments. In U. Cress, V. Dimitrova & M. Specht (Eds.), Learning in the Synergy of Multiple Disciplines. Proceedings of the Fourth European Conference on Technology-Enhanced Learning (EC-TEL 2009) (pp. 788-793). September, 29 - October, 2, 2009, Nice, France. Lecture Notes in Computer Science Vol. 5794. Berlin: Springer-Verlag.The following article presents a Mash-Up Personal Learning Environment called ReMashed that recommends learning resources from emerging information of a Learning Network. In ReMashed learners can specify certain Web2.0 services and combine them in a Mash-Up Personal Learning Environment. Learners can rate information from an emerging amount of Web2.0 information of a Learning Network and train a recommender system for their particular needs. ReMashed therefore has three main objectives: 1. to provide a recommender system for Mash-up Personal Learning Environments to learners, 2. to offer an environment for testing new recommendation approaches and methods for researchers, and 3. to create informal user-generated content data sets that are needed to evaluate new recommendation algorithms for learners in informal Learning Networks.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. In F. Wild, M. Kalz, M. Palmér & D. Müller (Eds.), Proceedings of 2nd Workshop Mash-Up Personal Learning Envrionments (MUPPLE'09). Workshop in conjunction with 4th European Conference on Technology Enhanced Learning (EC-TEL 2009): Synergy of Disciplines (pp. 23-30). September, 29, 2009, Nice, France: CEUR workshop proceedings, http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-506 .This article presents the ReMashed system that recommends learning content from emerging information of a Mash-Up Personal Learning Environment. ReMashed offers advice to find most suitable learning content for individual competence development of lifelong learners. The ReMashed system was initially designed to offer navigational support to lifelong learners in informal learning settings. In this article we want to discuss its ability to be used also in formal learning settings. For this purpose, we discuss the use of two different recommendation approaches for formal and informal learning within ReMashed.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

ReMashed 1.0

The license for this software is the BSD License owned by TENcompetence Foundation. Please find further license information in the package.ReMashed is a Web 2.0 Mash-up environment that allows learners to personalize information of a community to their preferences. ReMashed can be used by communities to share their Web 2.0 information and further personalize the shared information to personal preferences. ReMashed uses a recommender technology called collaborative filtering to generate recommendations. It works by matching together users with similar opinions about different resources. Each member of the system has a 'neighborhood' of other like-minded users. Ratings and Tags from these neighbors are used to create personalized recommendations. At the moment a tag and a rating based recommendation technique is applied. The ReMashed system is written in Zend PHP, it takes advantage of the Model-View-Controller’ concept and is therefore fully object based. The recommender system builds on top of the Duine prediction engine or alternatively on self designed recommendation algorithms.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Cardiorespiratory monitoring with a wireless and nonadhesive belt measuring diaphragm activity in preterm and term infants:A multicenter non-inferiority study

Introduction: We determined if the heart rate (HR) monitoring performance of a wireless and nonadhesive belt is non-inferior compared to standard electrocardiography (ECG). Secondary objective was to explore the belt's respiratory rate (RR) monitoring performance compared to chest impedance (CI). Method: In this multicenter non-inferiority trial, preterm and term infants were simultaneously monitored with the belt and conventional ECG/CI for 24 h. HR monitoring performance was estimated with the HR difference and ability to detect cardiac events compared to the ECG, and the incidence of HR-data loss per second. These estimations were statistically compared to prespecified margins to confirm equivalence/non-inferiority. Exploratory RR analyses estimated the RR trend difference and ability to detect apnea/tachypnea compared to CI, and the incidence of RR-data loss per second. Results: Thirty-nine infants were included. HR monitoring with the belt was non-inferior to the ECG with a mean HR difference of 0.03 beats per minute (bpm) (standard error [SE] = 0.02) (95% limits of agreement [LoA]: [−5 to 5] bpm) (p &lt; 0.001). Second, sensitivity and positive predictive value (PPV) for cardiac event detection were 94.0% (SE = 0.5%) and 92.6% (SE = 0.6%), respectively (p ≤ 0.001). Third, the incidence of HR-data loss was 2.1% (SE = 0.4%) per second (p &lt; 0.05). The exploratory analyses of RR showed moderate trend agreement with a mean RR-difference of 3.7 breaths/min (SE = 0.8) (LoA: [−12 to 19] breaths/min), but low sensitivities and PPV's for apnea/tachypnea detection. The incidence of RR-data loss was 2.2% (SE = 0.4%) per second. Conclusion: The nonadhesive, wireless belt showed non-inferior HR monitoring and a moderate agreement in RR trend compared to ECG/CI. Future research on apnea/tachypnea detection is required.</p

Multicentre paired non-inferiority study of the cardiorespiratory monitoring performance of the wireless and non-adhesive Bambi® belt measuring diaphragm activity in neonates: Study protocol

Introduction Cardiorespiratory monitoring is used in the neonatal intensive care unit (NICU) to assess the clinical status of newborn infants and detect critical deteriorations in cardiorespiratory function. Currently, heart rate (HR) is monitored by electrocardiography (ECG) and respiration by chest impedance (CI). Disadvantages of current monitoring techniques are usage of wired adhesive electrodes which may damage the skin and hinder care. The Bambi® belt is a wireless and non-adhesive alternative that enables cardiorespiratory monitoring by measuring electrical activity of the diaphragm via transcutaneous electromyography. A previous study showed feasibility of the Bambi® belt and this study compares the belt performance to ECG and CI. Methods and analysis This multicentre non-inferiority paired study will be performed in the NICU of the Máxima Medical Center (MMC) in Veldhoven and the Emma Children's Hospital, Amsterdam University Medical Centre (AmsterdamUMC) in Amsterdam, The Netherlands. 39 infants in different postmenstrual age groups (minimally 10 infants32 weeks) will be recruited. These infants will be monitored with the Bambi® belt in addition to standard ECG and CI for 24 hours. The primary outcome is the HR, studied with three criteria: (1) the limits of agreement of the HR measurements in terms of the second-to-second difference in the HR between the belt and standard ECG, (2) the detection of cardiac events consisting of bradycardia and tachycardia and (3) the quality of HR-monitoring. The secondary outcome is the respiratory rate (RR), studied with the criteria (1) agreement in RR-trend monitoring, (2) apnoea and tachypnoea detection and (3) reliable registrations. Ethics and dissemination This protocol was approved by the Medical Ethical Committee of the MMC and the Central Committee for Human Research. The MMC started patient recruitment in July and the AmsterdamUMC in August 2021. The results will be presented at conferences and published in peer-reviewed journals