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Most drugs are no longer produced in their own countries by the pharmaceutical companies, but by contract manufacturers or at manufacturing sites in countries that can produce more cheaply. This not only makes it difficult to trace them back but also leaves room for criminal organizations to fake them unnoticed. For these reasons, it is becoming increasingly difficult to determine the exact origin of drugs. The goal of this work was to investigate how exactly this is possible by using different spectroscopic methods like nuclear magnetic resonance and near- and mid-infrared spectroscopy in combination with multivariate data analysis. As an example, 56 out of 64 different paracetamol preparations, collected from 19 countries around the world, were chosen to investigate whether it is possible to determine the pharmaceutical company, manufacturing site, or country of origin. By means of suitable pre-processing of the spectra and the different information contained in each method, principal component analysis was able to evaluate manufacturing relationships between individual companies and to differentiate between production sites or formulations. Linear discriminant analysis showed different results depending on the spectral method and purpose. For all spectroscopic methods, it was found that the classification of the preparations to their manufacturer achieves better results than the classification to their pharmaceutical company. The best results were obtained with nuclear magnetic resonance and near-infrared data, with 94.6%/99.6% and 98.7/100% of the spectra of the preparations correctly assigned to their pharmaceutical company or manufacturer.
How different diversity factors affect the perception of first-year requirements in higher education
(2021)
In the light of growing university entry rates, higher education institutions not only serve larger numbers of students, but also seek to meet first-year students’ ever more diverse needs. Yet to inform universities how to support the transition to higher education, research only offers limited insights. Current studies tend to either focus on the individual factors that affect student success or they highlight students’ social background and their educational biography in order to examine the achievement of selected, non-traditional groups of students. Both lines of research appear to lack integration and often fail to take organisational diversity into account, such as different types of higher education institutions or degree programmes. For a more comprehensive understanding of student diversity, the present study includes individual, social and organisational factors. To gain insights into their role for the transition to higher education, we examine how the different factors affect the students’ perception of the formal and informal requirements of the first year as more or less difficult to cope with. As the perceived requirements result from both the characteristics of the students and the institutional context, they allow to investigate transition at the interface of the micro and the meso level of higher education. Latent profile analyses revealed that there are no profiles with complex patterns of perception of the first-year requirements, but the identified groups rather differ in the overall level of perceived challenges. Moreover, SEM indicates that the differences in the perception largely depend on the individual factors self-efficacy and volition.
Stretch-shortening type actions are characterized by lengthening of the pre-activated muscle-tendon unit (MTU) in the eccentric phase immediately followed by muscle shortening. Under 1 g, pre-activity before and muscle activity after ground contact, scale muscle stiffness, which is crucial for the recoil properties of the MTU in the subsequent push-off. This study aimed to examine the neuro-mechanical coupling of the stretch-shortening cycle in response to gravity levels ranging from 0.1 to 2 g. During parabolic flights, 17 subjects performed drop jumps while electromyography (EMG) of the lower limb muscles was combined with ultrasound images of the gastrocnemius medialis, 2D kinematics and kinetics to depict changes in energy management and performance. Neuro-mechanical coupling in 1 g was characterized by high magnitudes of pre-activity and eccentric muscle activity allowing an isometric muscle behavior during ground contact. EMG during pre-activity and the concentric phase systematically increased from 0.1 to 1 g. Below 1 g the EMG in the eccentric phase was diminished, leading to muscle lengthening and reduced MTU stretches. Kinetic energy at take-off and performance were decreased compared to 1 g. Above 1 g, reduced EMG in the eccentric phase was accompanied by large MTU and muscle stretch, increased joint flexion amplitudes, energy loss and reduced performance. The energy outcome function established by linear mixed model reveals that the central nervous system regulates the extensor muscles phase- and load-specifically. In conclusion, neuro-mechanical coupling appears to be optimized in 1 g. Below 1 g, the energy outcome is compromised by reduced muscle stiffness. Above 1 g, loading progressively induces muscle lengthening, thus facilitating energy dissipation.
Glucose oxidase (GOx) is an enzyme frequently used in glucose biosensors. As increased temperatures can enhance the performance of electrochemical sensors, we investigated the impact of temperature pulses on GOx that was drop-coated on flattened Pt microwires. The wires were heated by an alternating current. The sensitivity towards glucose and the temperature stability of GOx was investigated by amperometry. An up to 22-fold increase of sensitivity was observed. Spatially resolved enzyme activity changes were investigated via scanning electrochemical microscopy. The application of short (<100 ms) heat pulses was associated with less thermal inactivation of the immobilized GOx than long-term heating.
Nacre-mimetic nanocomposites based on high fractions of synthetic high-aspect-ratio nanoclays in combination with polymers are continuously pushing boundaries for advanced material properties, such as high barrier against oxygen, extraordinary mechanical behavior, fire shielding, and glass-like transparency. Additionally, they provide interesting model systems to study polymers under nanoconfinement due to the well-defined layered nanocomposite arrangement. Although the general behavior in terms of forming such layered nanocomposite materials using evaporative self-assembly and controlling the nanoclay gallery spacing by the nanoclay/polymer ratio is understood, some combinations of polymer matrices and nanoclay reinforcement do not comply with the established models. Here, we demonstrate a thorough characterization and analysis of such an unusual polymer/nanoclay pair that falls outside of the general behavior. Poly(ethylene oxide) (PEO) and sodium fluorohectorite form nacre-mimetic, lamellar nanocomposites that are completely transparent and show high mechanical stiffness and high gas barrier, but there is only limited expansion of the nanoclay gallery spacing when adding increasing amounts of polymer. This behavior is maintained for molecular weights of PEO varied over four orders of magnitude and can be traced back to depletion forces. By careful investigation via X-ray diffraction and proton low-resolution solid-state NMR, we are able to quantify the amount of mobile and immobilized polymer species in between the nanoclay galleries and around proposed tactoid stacks embedded in a PEO matrix. We further elucidate the unusual confined polymer dynamics, indicating a relevant role of specific surface interactions.
As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: β-O-4 linkage, B: phenylcoumaran, C: resinol, D: β-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70% and significantly lower in stem and mixture lignins at around 60% and almost 65%. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20% or more (maximum is M. sinensis Sin2 with over 30%). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27%. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.
This paper presents a novel numerical procedure for computing limit and shakedown loads of structures using a node-based smoothed FEM in combination with a primal–dual algorithm. An associated primal–dual form based on the von Mises yield criterion is adopted. The primal-dual algorithm together with a Newton-like iteration are then used to solve this associated primal–dual form to determine simultaneously both approximate upper and quasi-lower bounds of the plastic collapse limit and the shakedown limit. The present formulation uses only linear approximations and its implementation into finite element programs is quite simple. Several numerical examples are given to show the reliability, accuracy, and generality of the present formulation compared with other available methods.
The utilization of phase change material (PCM) for latent heat storage and thermal control of spacecraft has been demonstrated in the past in few missions only. One limiting factor was the fact that all concepts developed so far envisioned the PCM to be applied as an additional capacitor, encapsulated in its own housing, leading to mass, efficiency and accommodation challenges. Recently, the application of PCM within the scan cavity of a GEOS type satellite has been suggested, in order to tackle thermal issues due to direct sun intrusion (Choi, M., 2014). However, the application of PCM in such complex mechanical structures is extremely challenging. A new concept to tackle this issue is currently under development at the FH Aachen University of Applied Sciences. The concept "Infused Thermal Solutions (ITS)" is based on the idea to 3D print metallic structures in their regular functional shape, but double walled with internal lattice support structures, allowing the infusion of a PCM layer directly into the voids and eliminating the need for additional parts and interfaces. Together with OHB System, FH Aachen theoretically studied the application of this technology to the Meteosat Third Generation (MTG) Infra-Red Sounder (IRS) instrument. The study focuses on the scan cavity and entrance baffling assembly (EBA) of the IRS. It consists of thermal analyses, 3D-redesign and bread boarding of a scaled and PCM infused EBA version. In the thermal design of the alternative EBA, PCM was applied directly into the EBA, simulating the worst hot case sun intrusion of the mission. By applying 4kg of PCM (to a 60kg baffle) the EBA temperature excursions during sun intrusion were limited from 140K to 30K, leading to a significant thermo-opto-elastic performance gain. This paper introduces the ITS concept development status.
Bitcoin is a cryptocurrency and is considered a high-risk asset
class whose price changes are difficult to predict. Current research focusses
on daily price movements with a limited number of predictors. The paper at
hand aims at identifying measurable indicators for Bitcoin price movement s
and the development of a suitable forecasting model for hourly changes. The
paper provides three research contributions. First, a set of significant
indicators for predicting the Bitcoin price is identified. Second, the results of
a trained Long Short-term Memory (LSTM) neural network that predicts
price changes on an hourly basis is presented and compared with other
algorithms. Third, the results foster discussions of the applicability of neural
nets for stock price predictions. In total, 47 input features for a period of
over 10 months could be retrieved to train a neural net that predicts the
Bitcoin price movements with an error rate of 3.52 %.
Combined with the use of renewable energy sources for
its production, Hydrogen represents a possible alternative gas
turbine fuel for future low emission power generation. Due to
its different physical properties compared to other fuels such
as natural gas, well established gas turbine combustion
systems cannot be directly applied for Dry Low NOx (DLN)
Hydrogen combustion. This makes the development of new
combustion technologies an essential and challenging task
for the future of hydrogen fueled gas turbines.
The newly developed and successfully tested “DLN
Micromix” combustion technology offers a great potential to
burn hydrogen in gas turbines at very low NOx emissions.
Aiming to further develop an existing burner design in terms
of increased energy density, a redesign is required in order to
stabilise the flames at higher mass flows and to maintain low
emission levels.
For this purpose, a systematic design exploration has
been carried out with the support of CFD and optimisation
tools to identify the interactions of geometrical and design
parameters on the combustor performance. Aerodynamic
effects as well as flame and emission formation are observed
and understood time- and cost-efficiently. Correlations
between single geometric values, the pressure drop of the
burner and NOx production have been identified as a result.
This numeric methodology helps to reduce the effort of
manufacturing and testing to few designs for single
validation campaigns, in order to confirm the flame stability
and NOx emissions in a wider operating condition field.