Use of 3D-printed mixers in laboratory reactor design for modelling of heterogeneous catalytic converters

A method for identifying radial concentration maldistribution in synthetic catalyst activity test (SCAT) benches, is presented, where spatially resolved concentration measurements are not available. The developed methodology was successfully tested for an injection-based SCAT. To resolve the radial concentration maldistribution a static mixer was designed, 3D-printed and inserted upstream the test sample. The methodology could also prove the effectiveness of the mixer, which did not only resolve the concentration maldistribution but also avoided causing reaction disturbances. The resulting increased axial dispersion from the turbulence created by the static mixer was evaluated using a 3D CFD model in Ansys Fluent 19. The axial dispersion of the injection-based SCAT bench was compared to a premixed SCAT bench through classical Aris-Taylor calculations. The results from the axial dispersion calculations show that the injection-based design with the use of a static mixer is far superior to the premixed design – both with regards to pulse broadening but also time delay. This is highly desirable for modelling studies towards zero emission exhaust aftertreatment

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

The sites and mechanisms of postoperative insulin resistance

The Sites and Mechanisms of Postoperative InsulinResistance by Jonas Nygren, M.D. Departments of Surgery and Endocrinology and Diabetes, Karolinska Hospital and Institute, SE-171 76, Stockholm, Sweden In Sweden with nine million inhabitants, 450,000 operations(outpatients excluded) are performed every year resulting in2,250,000 treatment days in hospital. Surgical operations are part ofthe treatment for 44% of all patients admitted to hospital careoccupying 24% of all hospital beds. The majority of these patientsundergo an elective surgical procedure. Therefore, it is important toreduce the side effects of surgery, such as the catabolic response. Insulin is a key anabolic hormone which regulates not only themetabolism of glucose, but also the metabolism of fat and protein.Insulin resistance is a main feature of the catabolic response tosurgery and other trauma. However, the sites and mechanisms of thepostoperative insulin resistance remain to be clearly defined.Furthermore, it is not known whether changes in postoperative insulinsensitivity have any impact on patient outcome. Therefore, insulinsensitivity and glucose kinetics ([6,6,2H2]-D-glucose) weredetermined using hyperinsulinemic, normoglycemic clamps and indirectcalorimetry, before and after elective surgery in patients undergoingabdominal surgery (n = 18) or total hip replacement (n = 13). Thepatients were undergoing surgery after the traditional overnight fast(n = 17) or in a carbohydrate fed state. The carbohydrate fed statewas achieved by infusions of glucose and insulin 3-4 hours before andduring surgery (n = 7) or by intake of a carbohydrate drink (400 ml,50 g carbohydrates) 2-3 hours before surgery (n = 7). Glucose infusion rates required to maintain normoglycemia duringclamps (M-value) were reduced after surgery in the overnight fastedpatients, indicating the development of postoperative insulinresistance. Endogenous glucose production was moderately increasedafter surgery. The suppressibility of endogenous glucose productionby insulin was preserved postoperatively. Thus, most of the reductionin insulin sensitivity after surgery was due to a defect in glucosedisposal. Since postoperatively, a similar reduction in both glucoseoxidation and nonoxidative glucose disposal was observed, a defect inglucose transport probably underlies a decrease in insulinsensitivity. Energy expenditure increased after surgery and fatoxidation rates were less suppressed by insulin infusions. Onlymoderate changes were found in glucagon and cortisol levels ahersurgery. To single out the effects of surgery from the effects of thecommon perioperative treatment with bed rest and hypocaloricnutntion, insulin sensitivity was measured in healthy subjects (n =6), before and after a 24 hour period of hypocaloric nutrition and/orbed rest. Insulin sensitivity was reduced after 24 hours hypocaloncnutrition alone while the same period of immobilization had noeffect. One group of patients was treated with infusions of insulin andglucose before and during total hip replacement and compared tocontrols. In the insulin and glucose treated patients, insulinsensitivity remained unaffected immediately after surgery whileinsulin sensitivity was reduced in the control patients, undergoingthe same operation after an ovemight fast. A more convenient way to administer carbohydrates would be as abeverage instead of an intravenous infusion. To test the possibilityof administrating carbohydrates orally before the operation, gastricemptying of an isoosmolar carbohydrate rich drink (400 ml, 12%carbohydrates) was detenmined using gamma camera technique (99Tcm).Despite increased anxiety preoperatively, gastric emptying of thedrink was completed 90 minutes after intake in patients in themorning of surgery. When the carbohydrate drink was given to patients2-3 hours before elective colorectal surgery, postoperative insulinsensitivity was markedly improved as compared to patients undergoingsimilar surgical procedures after an overnight fast. Multiple regression analysis showed that 72% of the variability inthe relative reduction in insulin sensitivity after electiveabdominal surgery could be predicted by the duration of surgery (p =0.0002) and the carbohyd rate access preoperatively (p = 0.0005).Furthermore, the length of hospital stay was related to the degree ofpostoperative insulin resistance (relative change in M-valuespostoperatively vs hospital stay in postoperative days, r = -0.60, p= 0.018). In addition, 64% of the vanability in hospital stay was predicted bythe type of surgery (hip or abdominal) (p = 0.0001), duration ofsurgery (p = 0.010) and whether the patients were fasted orcarbohydrate fed before surgery (p = 0.004). Thus, carbohydratefeeding seems to be a better preparation than overnight fastingbefore surgery by improving postoperative insulin sensitivity andpatient recovery following elective surgery. Key words: Surgery, Insulin resistance, Glucosemetabolism, Glucose clamping technique, Gastric emptying,Immobilization, Preoperative fasting, ICF-I, Hospital stay, Stableisotopes ISBN 91-628-2695-6 Stockholm 199

Bayesian Neural Networks for Forecasting Restaurant Table Bookings

 In the restaurant business, the amount of bookings and guests on a given day will vary greatly depending on multiple factors, both internal and external. Examples of internal factors may be events held at the restaurant such as parties, quiz nights or special offers. External factors may be things such as time of year, holidays, weather or sports events taking place in the area near the restaurant. Being able to predict the number of guests that are going to attend on any given day is very valuable to any restaurant owner as it lets them plan the amount of food and drinks to order and to schedule enough staff. This thesis aims to explore the possibilities of forecasting the number of restaurant bookings based on time of year and month in order to find patterns, both within a month and seasonal patterns across an entire year. To do so, a Bayesian neural network will be employed, learning patterns from previous booking data. Despite a limited number of factors, the results point in a positive direction towards further exploring the possibility of using such a network to forecast the number of restaurant bookings. By adding additional information and factors when making a forecast, this method could prove very useful for restaurant owners in the future by exploiting patterns in previous booking data

Bayesian Neural Networks for Forecasting Restaurant Table Bookings

 In the restaurant business, the amount of bookings and guests on a given day will vary greatly depending on multiple factors, both internal and external. Examples of internal factors may be events held at the restaurant such as parties, quiz nights or special offers. External factors may be things such as time of year, holidays, weather or sports events taking place in the area near the restaurant. Being able to predict the number of guests that are going to attend on any given day is very valuable to any restaurant owner as it lets them plan the amount of food and drinks to order and to schedule enough staff. This thesis aims to explore the possibilities of forecasting the number of restaurant bookings based on time of year and month in order to find patterns, both within a month and seasonal patterns across an entire year. To do so, a Bayesian neural network will be employed, learning patterns from previous booking data. Despite a limited number of factors, the results point in a positive direction towards further exploring the possibility of using such a network to forecast the number of restaurant bookings. By adding additional information and factors when making a forecast, this method could prove very useful for restaurant owners in the future by exploiting patterns in previous booking data