| 1. |
- Tapia-Ruiz, Nuria, et al.
(author)
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2021 roadmap for sodium-ion batteries
- 2021
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In: Journal of Physics. - : Institute of Physics Publishing (IOPP). - 2515-7655. ; 3:3
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Journal article (peer-reviewed)abstract
- Increasing concerns regarding the sustainability of lithium sources, due to their limited availability and consequent expected price increase, have raised awareness of the importance of developing alternative energy-storage candidates that can sustain the ever-growing energy demand. Furthermore, limitations on the availability of the transition metals used in the manufacturing of cathode materials, together with questionable mining practices, are driving development towards more sustainable elements. Given the uniformly high abundance and cost-effectiveness of sodium, as well as its very suitable redox potential (close to that of lithium), sodium-ion battery technology offers tremendous potential to be a counterpart to lithium-ion batteries (LIBs) in different application scenarios, such as stationary energy storage and low-cost vehicles. This potential is reflected by the major investments that are being made by industry in a wide variety of markets and in diverse material combinations. Despite the associated advantages of being a drop-in replacement for LIBs, there are remarkable differences in the physicochemical properties between sodium and lithium that give rise to different behaviours, for example, different coordination preferences in compounds, desolvation energies, or solubility of the solid-electrolyte interphase inorganic salt components. This demands a more detailed study of the underlying physical and chemical processes occurring in sodium-ion batteries and allows great scope for groundbreaking advances in the field, from lab-scale to scale-up. This roadmap provides an extensive review by experts in academia and industry of the current state of the art in 2021 and the different research directions and strategies currently underway to improve the performance of sodium-ion batteries. The aim is to provide an opinion with respect to the current challenges and opportunities, from the fundamental properties to the practical applications of this technology.
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| 2. |
- Demmelmaier, Ingrid, 1960-, et al.
(author)
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Does exercise intensity matter for fatigue during (neo-)adjuvant cancer treatment? The Phys-Can randomized clinical trial
- 2021
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In: Scandinavian Journal of Medicine and Science in Sports. - : Wiley. - 0905-7188 .- 1600-0838. ; 31:5, s. 1144-1159
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Journal article (peer-reviewed)abstract
- Exercise during cancer treatment improves cancer-related fatigue (CRF), but the importance of exercise intensity for CRF is unclear. We compared the effects of high- vs low-to-moderate-intensity exercise with or without additional behavior change support (BCS) on CRF in patients undergoing (neo-)adjuvant cancer treatment. This was a multicenter, 2x2 factorial design randomized controlled trial (Clinical Trials NCT02473003) in Sweden. Participants recently diagnosed with breast (n = 457), prostate (n = 97) or colorectal (n = 23) cancer undergoing (neo-)adjuvant treatment were randomized to high intensity (n = 144), low-to-moderate intensity (n = 144), high intensity with BCS (n = 144) or low-to-moderate intensity with BCS (n = 145). The 6-month exercise intervention included supervised resistance training and home-based endurance training. CRF was assessed by Multidimensional Fatigue Inventory (MFI, five subscales score range 4-20), and Functional Assessment of Chronic Illness Therapy-Fatigue scale (FACIT-F, score range 0-52). Multiple linear regression for main factorial effects was performed according to intention-to-treat, with post-intervention CRF as primary endpoint. Overall, 577 participants (mean age 58.7 years) were randomized. Participants randomized to high- vs low-to-moderate-intensity exercise had lower physical fatigue (MFI Physical Fatigue subscale; mean difference −1.05 [95% CI: −1.85, −0.25]), but the difference was not clinically important (ie <2). We found no differences in other CRF dimensions and no effect of additional BCS. There were few minor adverse events. For CRF, patients undergoing (neo-)adjuvant treatment for breast, prostate or colorectal cancer can safely exercise at high- or low-to-moderate intensity, according to their own preferences. Additional BCS does not provide extra benefit for CRF in supervised, well-controlled exercise interventions.
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| 3. |
- Johansson, L. Ronnie M., et al.
(author)
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Bridging the gap between information need and information acquisition
- 2004
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In: Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004. - Stockholm. - 917056115X ; , s. 1202-1209
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Conference paper (peer-reviewed)abstract
- In this article, we address the rarely discussed problem of connecting high-level information (e.g., aggregated states and enemy intentions) to information acquisition. Our approach is to partition the transition of information need to sensor management into a set of comprehensible entities (information types and functions), which we present in a framework. The framework is stepwise (sequential) and first translates actual information (from the data and information fusion process) to information need. The information need is mapped to the task space by a task management function which performs prioritization with respect to information need. A further step includes projection of tasks to service space by an allocation scheme, and finally services give orders to resources. In the terminology of the framework, we discuss the extension of a previous study (that involved plan recognition) with a sensor management function.
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| 4. |
- Suzic, Robert, et al.
(author)
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Realization of a bridge between high-level information need and sensor management using a common DBN
- 2004
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In: PROCEEDINGS OF THE 2004 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IRI-2004). - NEW YORK : IEEE. ; , s. 606-611
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Conference paper (peer-reviewed)abstract
- In a decision support system for military decision makers a plan recognition process provides estimates Of enemy plans. To respond to a changing and uncertain environment the plan recognition process requires timely and relevant information. We address the rarely discussed, yet crucial, issue of connecting the information needs of plan recognition to management of sensors. We have previously presented a framework for this purpose and here we give details of an implementation and provide some results. In our implementation both plan recognition, sensor management and the functions that connect them utilize the a priori knowledge stored in a Dynamic Bayesian Network.
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