Background & aims: Optimal nutritional support during the acute phase of critical illness remains controversial. We hypothesized that patients with low skeletal muscle area and -density may specifically benefit from early high protein intake. Aim of the present study was to determine the association between early protein intake (day 2–4) and mortality in critically ill intensive care unit (ICU) patients with normal skeletal muscle area, low skeletal muscle area, or combined low skeletal muscle area and -density. Methods: Retrospective database study in mechanically ventilated, adult critically ill patients with an abdominal CT-scan suitable for skeletal muscle assessment around ICU admission, admitted from January 2004 to January 2016 (n = 739). Patients received protocolized nutrition with protein target 1.2–1.5 g/kg/day. Skeletal muscle area and -density were assessed on abdominal CT-scans at the 3rd lumbar vertebra level using previously defined cut-offs. Results: Of 739 included patients (mean age 58 years, 483 male (65%), APACHE II score 23), 294 (40%) were admitted with normal skeletal muscle area and 445 (60%) with low skeletal muscle area. Two hundred (45% of the low skeletal muscle area group) had combined low skeletal muscle area and -density. In the normal skeletal muscle area group, no significant associations were found. In the low skeletal muscle area group, higher early protein intake was associated with lower 60-day mortality (adjusted hazard ratio (HR) per 0.1 g/kg/day 0.82, 95%CI 0.73–0.94) and lower 6-month mortality (HR 0.88, 95%CI 0.79–0.98). Similar associations were found in the combined low skeletal muscle area and -density subgroup (HR 0.76, 95%CI 0.64–0.90 for 60-day mortality and HR 0.80, 95%CI 0.68–0.93 for 6-month mortality). Conclusions: Early high protein intake is associated with lower mortality in critically ill patients with low skeletal muscle area and -density, but not in patients with normal skeletal muscle area on admission. These findings may be a further step to personalized nutrition, although randomized studies are needed to assess causality.
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In this report, the details of an investigation into the e ect of the low induction wind turbines on the Levelised Cost of Electricity (LCoE) in a 1GW o shore wind farm is outlined. The 10 MW INNWIND.EU conventional wind turbine and its low induction variant, the 10 MW AVATAR wind turbine, are considered in a variety of 10x10 layout configurations. The Annual Energy Production (AEP) and cost of electrical infrastructure were determined using two in-house ECN software tools, namely FarmFlow and EEFarm II. Combining this information with a generalised cost model, the LCoE from these layouts were determined. The optimum LCoE for the AVATAR wind farm was determined to be 92.15 e/MWh while for the INNWIND.EU wind farm it was 93.85 e/MWh. Although the low induction wind farm o ered a marginally lower LCoE, it should not be considered as definitive due to simple nature of the cost model used. The results do indicate that the AVATAR wind farms require less space to achieve this similar cost performace, with a higher optimal wind farm power density (WFPD) of 3.7 MW/km2 compared to 3 MW/km2 for the INNWIND.EU based wind farm.
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The purpose of this paper is to propose a research by design strategy, focusing on the generation of innovative climate adaptation solutions by utilizing the Design Thinking Process. The proposed strategy has been developed and tested in a research and design studio, which took place in 2020 at a Master of Architecture degree program in the Netherlands. The studios focused on the sparsely populated, high flood risk region of the Lake District, UK. The Lake District faces urgent climate change challenges that demand effective solutions. On the other hand, the area is a UNESCO heritage site, characterized by massive tourism and tending towards museumification (sic). Three indicative design research projects were selected to illustrate the proposed research by design strategy. The results reveal that this strategy facilitates the iterative research by design process and hence offers a systematic approach to convert the threats of climate change into opportunities by unraveling the potentials of the study area. The findings lay the groundwork for more systematic studies on research by design as an effective strategy for climate change adaptation design. Beyond the local case, the results contribute to the critical theories on climate adaptation design and research by design methodologies.
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Background & aims: Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements. Methods: This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle. Results: 110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle. Conclusions: Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density. Trial registration: ClinicalTrials.gov (NCT02555670).
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Amsterdam faces the challenge of accommodating 50,000 to 90,000 new homes in the next five to ten years. That is equivalent to 10% of the city’s current total housing stock. The new homes have to be built within the existing urban fabric. This will entail high densities and the construction of new ‘un-Dutch’ typologies with high-rise residential buildings. Densification is currently accelerating in many Western cities and high-rise living environments are gaining ground as today’s typology. Yet these new typologies come with potentially serious risks to the liveability of cities in general and those new environments in particular (Asgarzadeh et al. 2012; Lindal and Hartig 2013; Gifford 2007). Urban designers and (landscape) architects are challenged to prevent and soften the negative impact that is often associated with extremely densified environments. This entails mitigating contradictive demands: to create high-density capacity andshape streetscapes that relate to a human scale. Designers might resort to the large body of applied design solutions and theories, yet these tend to be derived from more traditional urban fabrics of low-density developments (for example: e.g. Sennett 2018; Haas 2008; Jacobs 1993; Banerjee and Southworth 1990; Alexander et.al. 1977; Jacobs 1961).Therefore, the question of the research project Sensing Streetscape is if the classical design solutions are without any alterations, applicable in these new high density settings and able to create streetscapes with a human scale. A combination of emerging technologies and principles from both worlds; neuroscience and architecture offer the opportunity to investigate this question in-depth as a relation between the designed and the visually perceived streetscape.
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BACKGROUND: Muscle quantity at intensive care unit (ICU) admission has been independently associated with mortality. In addition to quantity, muscle quality may be important for survival. Muscle quality is influenced by fatty infiltration or myosteatosis, which can be assessed on computed tomography (CT) scans by analysing skeletal muscle density (SMD) and the amount of intermuscular adipose tissue (IMAT). We investigated whether CT-derived low skeletal muscle quality at ICU admission is independently associated with 6-month mortality and other clinical outcomes.METHODS: This retrospective study included 491 mechanically ventilated critically ill adult patients with a CT scan of the abdomen made 1 day before to 4 days after ICU admission. Cox regression analysis was used to determine the association between SMD or IMAT and 6-month mortality, with adjustments for Acute Physiological, Age, and Chronic Health Evaluation (APACHE) II score, body mass index (BMI), and skeletal muscle area. Logistic and linear regression analyses were used for other clinical outcomes.RESULTS: Mean APACHE II score was 24 ± 8 and 6-month mortality was 35.6%. Non-survivors had a lower SMD (25.1 vs. 31.4 Hounsfield Units (HU); p < 0.001), and more IMAT (17.1 vs. 13.3 cm(2); p = 0.004). Higher SMD was associated with a lower 6-month mortality (hazard ratio (HR) per 10 HU, 0.640; 95% confidence interval (CI), 0.552-0.742; p < 0.001), and also after correction for APACHE II score, BMI, and skeletal muscle area (HR, 0.774; 95% CI, 0.643-0.931; p = 0.006). Higher IMAT was not significantly associated with higher 6-month mortality after adjustment for confounders. A 10 HU increase in SMD was associated with a 14% shorter hospital length of stay.CONCLUSIONS: Low skeletal muscle quality at ICU admission, as assessed by CT-derived skeletal muscle density, is independently associated with higher 6-month mortality in mechanically ventilated patients. Thus, muscle quality as well as muscle quantity are prognostic factors in the ICU.TRIAL REGISTRATION: Retrospectively registered (initial release on 06/23/2016) at ClinicalTrials.gov: NCT02817646 .
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Poster en begeleidende audio uit de guided tour van het Open Atelier van CoE Groen op 7 december 2023 over het project RhoC bulkdichtheidsmeter. De bulkdichtheid van de bodem wordt steeds belangrijker als bodemparameter. De bulkdichtheid kun je alleen meten door ongestoorde ringmonsters te nemen op verschillende dieptes in een profielkuil en deze in het lab te analyseren. Dit is specialistisch en tijdrovend werk. Een andere meting die wel snel is en vaak wordt gebruikt om verdichte grondlagen op te sporen, is met een penetrometer. Deze meet niet de bulkdichtheid maar de indringingsweerstand van de grond. Dit is niet om te rekenen naar bulkdichtheid en de indringingsweerstand is bovendien zeer gevoelig voor natte en droge omstandigheden, waardoor de metingen soms onbetrouwbaar zijn. Als mogelijke oplossing voor deze uitdaging om de bulkdichtheid te meten, wordt een sensor ontwikkeld die de bodembulkdichtheid van een volledig bodemprofiel meet.
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This report focuses on the feasibility of the power-to-ammonia concept. Power-to-ammonia uses produced excess renewable electricity to electrolyze water, and then to react the obtained hydrogen with nitrogen, which is obtained through air separation, to produce ammonia. This process may be used as a “balancing load” to consume excess electricity on the grid and maintain grid stability. The product, ammonia, plays the role of a chemical storage option for excess renewable energy. This excess energy in the form of ammonia can be stored for long periods of time using mature technologies and an existing global infrastructure, and can further be used either as a fuel or a chemical commodity. Ammonia has a higher energy density than hydrogen; it is easier to store and transport than hydrogen, and it is much easier to liquefy than methane, and offers an energy chain with low carbon emissions.The objective of this study is to analyze technical, institutional and economic aspects of power-to-ammonia and the usage of ammonia as a flexible energy carrier.
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Background & aims: Accurate diagnosis of sarcopenia requires evaluation of muscle quality, which refers to the amount of fat infiltration in muscle tissue. In this study, we aim to investigate whether we can independently predict mortality risk in transcatheter aortic valve implantation (TAVI) patients, using automatic deep learning algorithms to assess muscle quality on procedural computed tomography (CT) scans. Methods: This study included 1199 patients with severe aortic stenosis who underwent transcatheter aortic valve implantation (TAVI) between January 2010 and January 2020. A procedural CT scan was performed as part of the preprocedural-TAVI evaluation, and the scans were analyzed using deep-learning-based software to automatically determine skeletal muscle density (SMD) and intermuscular adipose tissue (IMAT). The association of SMD and IMAT with all-cause mortality was analyzed using a Cox regression model, adjusted for other known mortality predictors, including muscle mass. Results: The mean age of the participants was 80 ± 7 years, 53% were female. The median observation time was 1084 days, and the overall mortality rate was 39%. We found that the lowest tertile of muscle quality, as determined by SMD, was associated with an increased risk of mortality (HR 1.40 [95%CI: 1.15–1.70], p < 0.01). Similarly, low muscle quality as defined by high IMAT in the lowest tertile was also associated with increased mortality risk (HR 1.24 [95%CI: 1.01–1.52], p = 0.04). Conclusions: Our findings suggest that deep learning-assessed low muscle quality, as indicated by fat infiltration in muscle tissue, is a practical, useful and independent predictor of mortality after TAVI.
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Energy policies are vital tools used by countries to regulate economic and social development as well as guarantee national security. To address the problems of fragmented policy objectives, conflicting tools, and overlapping initiatives, the internal logic and evolutionary trends of energy policies must be explored using the policy content. This study uses 38,277 energy policies as a database and summarizes the four energy policy objectives: clean, low-carbon, safe, and efficient. Using the TextCNN model to classify and deconstruct policies, the LDA + Word2vec theme conceptualization and similarity calculations were compared with the EISMD evolution framework to determine the energy policy theme evolution path. Results indicate that the density of energy policies has increased. Policies have become more comprehensive, barriers between objectives have gradually been broken, and low-carbon objectives have been strengthened. The evolution types are more diversified, evolution paths are more complicated, and the evolution types are often related to technology, industry, and market maturity. Traditional energy themes evolve through inheritance and merger; emerging technology and industry themes evolve through innovation, inheritance, and splitting. Moreover, this study provides a replicable analytical framework for the study of policy evolution in other sectors and evidence for optimizing energy policy design
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