Ketamiini ja kallonsisäinen paine : todellinen ongelma vai paljon melua tyhjästä

Ketamiinin käyttö ensihoidossa on lisääntynyt, sillä se ei lamaa hengitystä eikä verenkiertoa. Ketamiini saattaa kuitenkin nostaa kallonsisäistä painetta. Onko ketamiini turvallinen lääke ensihoidossa aivotapahtumapotilaita hoidettaessa? Kannattaako teho-osastolla aivotapahtumapotilaita lääkitä ketamiinilla?</p

Operatiivinen taloussuunnittelu ja -ohjaus taksialan pienyrittäjien tukena

Taksilain muuttuessa vuonna 2018, taksialan pienyrittäjät ovat joutuneet aivan uudenlaiseen markkinakilpailuympäristöön, mikä on myös tuonut kysymysmerkkejä taksiyrittäjien liiketoiminnan taloudelliselle puolelle. Tämän uuden tilanteen vaikutus taksiyrittäjille, on myös tuonut mahdollisuuden tilitoimistoille erikoistua taksiyrittäjien tarpeiden tukemiseen. Opinnäytetyössä tarkasteltiin taksialan pienyrittäjien käsitystä operatiivisen liiketoimintansa taloudellisesta puolesta. Tutkimuksen kohteena olivat Pirkanmaalaiset taksialan pienyrittäjät ja heidän näkemyksensä aiheesta. Tutkimuksen tarkoituksena oli selvittää, millaista operatiivista taloussuunnittelua ja -ohjausta kannattaisi tarjota taksialan pienyrittäjille, heidän liiketoimintansa tueksi. Tavoitteena oli tuottaa myös selvitys, millainen taloudellinen vaikutus eri tuotannontekijöillä on taksialan pienyrittäjien liiketoimintaan, sekä miten operatiivisen taloussuunnittelun ja -ohjauksen laskelmia ja tunnuslukuja kannattaisi hyödyntää, heidän liiketoimintansa operatiivisen ohjauksen tukena. Opinnäytetyö tehtiin laadullisella tutkimusotteella, missä aineistonkeruumenetelmänä toimi teemahaastattelut. Tutkimuksessa haastateltiin kuutta Pirkanmaalaista taksialan pienyrittäjää, joista puolet olivat yhden auton taksiyrittäjiä ja toiset puolet useamman auton taksiyrittäjiä. Tutkimuksen haastattelut tehtiin maaliskuussa 2021. Teemahaastattelujen tuloksia lähdettiin analysoimaan ja tulkitsemaan, tiivistämällä ja teemoittelemalla. Tutkimuksessa saatiin selville, miten eri tuotannontekijät vaikuttavat taksialan pienyrittäjien liiketoimintaan, sekä mitkä tunnusluvut ja laskelmat ovat keskeisimpiä taksialalla, ja miten niitä hyödynnetään, sekä millaisia operatiivisen taloussuunnittelun ja -ohjauksen tarpeita taksialan pienyrittäjillä ilmenee. Tutkimuksen perusteella tehtiin selvitys, mitä olisi hyvä sisällyttää operatiiviseen taloussuunnitteluun ja -ohjaukseen taksialan pienyrittäjiä varten, mikä tukisi heidän liiketoimintaansa paremmin. Selvityksestä ilmeni eri tunnuslukujen ja laskelmien hyödyllisyys, millä voidaan suunnitella ja ohjata operatiivista liiketoimintaa oikeaan suuntaan. Tunnusluvut ja laskelmat liittyivät enimmäkseen liiketoiminnan kannattavuuteen, hinnoitteluun ja investointeihin, sekä maksuvalmiuteen. Taksiyrittäjät näkivät myös tilitoimiston tarjoamalle tuelle kiinnostusta, tämän aiheen osalta

Developing Social Impact Evaluation Methods for Research : viewpoints on commercialization and sustainability

The social contributions of research activities have become more and more important in the rapidly changing innovation environment. Despite the fact that industrial commercialization of research results constitutes one of the most essential drivers for innovation and competitiveness, most generally used social impact evaluation criteria do not include clear metrics involving research commercialization possibilities. In a similar manner, principles regarding sustainable development have been largely omitted from the impact criteria. This paper considers the "broader impacts criteria" (BIC) model developed for social impact evaluation in the National Science Foundation in United States. We propose extensions to the BIC criteria related to commercialization and sustainable development viewpoints on impact evaluation. This paper also considers a newly introduced extension to BIC, called "inclusion-immediacy criteria" (IIC). Based on it, we propose an extended version of the model that aims to additionally evaluate the impact of research from a commercialization point of view.© Authors 2021. The Technology Innovation Management Review is published under a Creative Commons Attribution 3.0 License.fi=vertaisarvioitu|en=peerReviewed

Modeling the effect of composition and temperature on the conductivity of synthetic copper electrorefining electrolyte

The physico-chemical properties of the copper electrolyte significantly affect the energy consumption of the electrorefining process and the quality of the cathode product. Favorable conditions for electrorefining processes are typically achieved by keeping both the electrolyte conductivity and diffusion coefficient of Cu(II) high, while ensuring low electrolyte viscosity. In this work the conductivity of the copper electrorefining electrolyte was investigated as a function of temperature (50–70 ˚C) and concentrations of copper (Cu(II), 40–60 g/L), nickel (Ni(II), 0–20 g/L), arsenic (As(III), 0–30 g/L) and sulfuric acid (160–220 g/L). In total 165 different combinations of these factors were studied. The results were treated using factorial analysis, and as a result, four electrolyte conductivity models were built up. Models were constructed both with and without arsenic as the presence of As(III) appeared to cause non-linearity in some factor effects and thus impacted the conductivity in more complex ways than previously detailed in literature. In all models the combined effect of factors was shown to be minor when compared to the effect of single factors. Conductivity was shown to increase when copper, nickel and arsenic concentrations were decreased and increase with increased temperature and acidity. Moreover, the arsenic concentration was shown to decrease the level of conductivity more than previously suggested in the literature.Peer reviewe

Machine learning model predicts short-term mortality among prehospital patients : A prospective development study from Finland

Aim: To show whether adding blood glucose to the National Early Warning Score (NEWS) parameters in a machine learning model predicts 30-day mortality more precisely than the standard NEWS in a prehospital setting. Methods: In this study, vital sign data prospectively collected from 3632 unselected prehospital patients in June 2015 were used to compare the standard NEWS to random forest models for predicting 30-day mortality. The NEWS parameters and blood glucose levels were used to develop the random forest models. Predictive performance on an unknown patient population was estimated with a ten-fold stratified cross-validation method. Results: All NEWS parameters and blood glucose levels were reported in 2853 (79%) eligible patients. Within 30 days after contact with ambulance staff, 97 (3.4%) of the analysed patients had died. The area under the receiver operating characteristic curve for the 30-day mortality of the evaluated models was 0.682 (95% confidence interval [CI], 0.6190.744) for the standard NEWS, 0.735 (95% CI, 0.6790.787) for the random forest-trained NEWS parameters only and 0.758 (95% CI, 0.7050.807) for the random forest-trained NEWS parameters and blood glucose. The models predicted secondary outcomes similarly, but adding blood glucose into the random forest model slightly improved its performance in predicting short-term mortality. Conclusions: Among unselected prehospital patients, a machine learning model including blood glucose and NEWS parameters had a fair performance in predicting 30-day mortality.publishedVersionPeer reviewe

Diffusion coefficient of cupric ion in a copper electrorefining electrolyte containing nickel and arsenic

Diffusion and convection are the main modes of mass transport that occur during copper electrorefining. Diffusion determines the rate of copper transfer across the diffusion layer, which in turn, affects the dissolution of the anode and deposition on the cathode. The diffusion coefficient of cupric ion (D Cu(II) ) is a typical property that can be defined from the limiting current density (j lim ) values. In this work, the limiting current densities were measured for 24 different synthetic copper electrolytes over a temperature range of 50–70 °C using a rotating disc electrode (RDE). From this data, a model for j lim and the corresponding models for D Cu(II) were constructed using Levich (Model L), Koutecký-Levich (Model K) and mixed-control Newman equations (Model M). The models for j lim and D Cu(II) were designed, refined and analyzed using the modeling and design tool MODDE, with the temperature, copper, nickel, arsenic and sulfuric acid concentrations as variables. Results from this research show for the first time that an increase in arsenic concentration has a reciprocal effect on the D Cu(II) under copper electrorefining conditions. Furthermore, the models were validated with 11 industrial electrorefining electrolyteswith known compositions. Model L (D Cu(II) based on Levich equation) was shown to provide the highest correlation with the industrial solutions when compared to the other models (Model K and M) considered and previously published diffusion coefficient models. Overall, this work provides an explanation for the previously observed data variances in the literature, investigates for the first time the combined effect of parameters on D Cu(II) value in industrial copper electrolysis and clarifies the effect of arsenic on the D Cu(II) of copper electrorefining electrolytes.Peer reviewe

Viscosity and density models for copper electrorefining electrolytes

Viscosity and density are highly important physicochemical properties of copper electrolyte since they affect the purity of cathode copper and energy consumption [1, 2] affecting the mass and heat transfer conditions in the cell [3]. Increasing viscosity and density decreases the rate in which the anode slime falls to the bottom of the cell [4, 5] and lowers the diffusion coefficient of cupric ion (DCu2+) [6]. Decreasing the falling rate of anode slime increases movement of the slime to other directions than downward [4, 5]. If the anode slime ends up on the cathode, the impurities could entrap into coating [4]. Due to that the aim is to keep the viscosity and density sufficiently low [4]. According to the studies of Price and Davenport [3], Subbaiah and Das [2], Devochkin et al. [7] as well as Jarjoura et al. [8] increasing the concentration of copper, nickel and sulfuric acid increases both viscosity and density, while temperature decreases these properties. In addition, Price and Davenport [1] researched the effect of impurities arsenic and iron as well as Subbaiah and Das [2] the effect of iron, manganese and cobalt. All of these researchers found that those impurities increased both viscosity and density. The density and kinematic viscosity of copper electrorefming electrolytes have not been extensively researched under electrorefming conditions. The kinematic viscosity is also an important factor in the equation defining DCu2+ using a rotating disc electrode technique [6]. The errors in the viscosity values cause significant error to DCu2+. Thus, this work introduces mathematical models for the density and kinematic viscosity. The kinematic viscosity of the test electrolytes was measured with a Ubbelohde capillary viscometer from Schott-Gerate GmbH and the density with a glass tube oscillator DMA 40 Digital Density Meter from Anton Paar K. G. The temperature (50, 60, 70 degrees C) and electrolyte composition were used as variables. The composition variables investigated were copper (40, 50, 60 g/dm(3)), nickel (0, 10, 20 g/dm(3)) and sulfuric acid (130, 145, 160 g/dm(3)) in all models, and additionally the effect of arsenic acid for the viscosity was studied (0, 15, 30 g/dm(3)). The electrolytes used in these tests were prepared from CuSO4-5H(2)O (99-100 %), NiSO(4 center dot)7H(2)O (99-100 %), H2SO4 (95-97 %) and arsenic acid (containing As 151700 mg/dm(3), Bi 6.2 mg/dm(3), Se 0.07 mg/dm(3), Te 18.6 mg/dm(3), Ag 0.2 mg/dm(3), Cu 4794 mg/dm(3), Ni 1688 mg/dm(3), Pb 28.62 mg/dm(3) and Sb 3954 mg/dm(3)). The results were normalized using known water values for viscosity as well as water and air values for the density. Based on these results the models for density (rho, g/cm(3)) and kinematic viscosity (nu, mm(2)/s) were designed, refined and analyzed using modeling and design tool MODDE, Equation 1 for density and 2 for kinematic viscosity: rho = 1.03473 + 0.00216707 [Cu] + 0.000535362 [H2SO4] + 0.00234682 [Ni] - 0.000713461 TPeer reviewe

Modelling the effect of temperature and free acid, silver, copper and lead concentrations on silver electrorefining electrolyte conductivity

Conductivity is one of the key physico-chemical properties of electrolyte in silver electrorefining since it affects the energy consumption of the process. As electrorefining process development trends towards high current density operation, having electrolytes with high conductivities will greatly reduce the energy consumption of the process. This study outlines investigations into silver electrorefining electrolyte conductivity as a function of silver, free acid, copper and lead concentration at different temperatures via a full factorial design comprising of 246 individual measurements. Regression analysis of the model was used to determine the goodness of fit R2, goodness of prediction Q2, model validity and reproducibility. Conductivity was shown to be enhanced by increases in free acid, copper, silver and lead, with free acid having the highest impact on conductivity. Temperature also increased conductivity in two ways: both as a single factor and as a combined effect with free acid, silver and copper concentration. Overall, this work produced a model of high accuracy that allows conductivity of a range of industrial silver electrorefining conditions to be calculated.Peer reviewe

Industrial validation of conductivity and viscosity models for copper electrolysis processes

Funding Information: This research was performed within the SIMP (System Integrated Metal Production) project (grant number 2140/31/2013) of DIMECC (Digital, Internet, Materials & Engineering Co-Creation (Tampere, Finland)) and BATCircle project (grant number 4853/31/2018) supported by Business Finland. In addition, Taina Kalliomäki would like to thank the Emil Aaltonen Foundation and Arif T. Aji the LPDP, Indonesian Endowment Fund for Education, (grant number S-1440/LPDP.3/2015) for additional funding. The RawMatTERS Finland Infrastructure (RAMI) based at Aalto University and supported by Academy of Finland is also greatly acknowledged. Finally, the authors would like to acknowledge the personnel in Glencore Nikkelverk AS, Reference Tankhouses 2 and 3, and Boliden Harjavalta Oy for their assistance and for permission to publish the results. Publisher Copyright: © 2021 The Author(s)In copper electrorefining and electrowinning, the conductivity and viscosity of the electrolyte affect the energy consumption, and for electrorefining the purity of cathode copper. Consequently, accurate models for predicting these properties are highly important. Although the modeling of conductivity and viscosity of synthetic copper electrolytes has been previously studied, only a few models have been validated with actual industrial electrolytes. The conductivity and viscosity models outlined in this study were developed using conductivity and viscosity measurements from both synthetic and industrial solutions. The synthetic electrolytes were investigated over a temperature range between 50–70 °C and typical concentrations of Cu (40–90 g/dm3), Ni (0–30 g/dm3), Fe (0–10 g/dm3), Co (0–5 g/dm3), As (0–63.8 g/dm3), H2SO4 (50–223 g/dm3) as well as other solution impurities like Sb in some cases. Validation of the synthetic electrolyte models was performed through industrial measurements at three copper plants across Europe. Generally, the developed models predicted the conductivities and viscosities of industrial solutions with high accuracy. The viscosity models covered extended ranges of both [H2SO4] and [Cu] with percentage errors of only (2.08 ± 0.59) - (2.48 ± 0.61). For conductivity, two different models for low (142 g/dm3) [H2SO4] electrolytes were utilized. Their error margins were (−1.96 ± 0.84) - (−1.44 ± 0.35) and (1.17 ± 0.27) - (2.52 ± 0.28), respectively. In the case of high [H2SO4] electrolytes, the validations focused on conductivity, and the highest level of accuracy was obtained when the effects of Sb and other minor impurities were considered.Peer reviewe