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This report examines the strength of young and early age concrete that has been systematically exposed to horizontal, sinusoidal vibrations with varying vibration parameters. Specimens were subjected to vibrations of predefined vibration times (4–14 h) and the compressive strength was determined after a period of 28 days. It was found that the different parameters have no critical influence on compressive strength and that vibration prior to initial setting of the concrete can increase its strength. Additional information to examine the reasons for this increase was obtained by further investigations (nuclear magnetic resonance, x-ray diffraction, and thermogravimetric analysis).
Background. Ketone bodies are a highly relevant topic in nutrition and medicine. -e influence of medium-chain triglycerides (MCT) on ketogenesis is well known and has been successfully used in ketogenic diets for many years. Nevertheless, the effects of MCTs and coconut oil on the production of ketone bodies have only partially been investigated. Furthermore, the increased mobilisation of free fatty acids and release of catabolic hormones by caffeine suggest an influence of caffeine on ketogenesis.
Methods. In a controlled, double-blind intervention study, seven young healthy subjects received 10mL of tricaprylin (C8), tricaprin (C10), C8/C10 (50% C8, 50% C10), or coconut oil with or without 150 mg of caffeine, in 250mL of decaffeinated coffee, over ten interventions. At baseline and after every 40 minutes, for 4 h, ßHB and glucose in capillary blood as well as caffeine in saliva were measured. Furthermore, questionnaires were used to survey sensory properties, side effects, and awareness of hunger and satiety. Results. -e interventions with caffeine caused an increase in ßHB levels—in particular, the interventions with C8 highly impacted ketogenesis. -e effect decreased with increased chain lengths. All interventions showed a continuous increase in hunger and diminishing satiety. Mild side effects (total � 12) occurred during the interventions. Conclusions. -e present study demonstrated an influence of caffeine and MCTon ketogenesis. -eaddition of caffeine showed an additive effect on the ketogenic potential of MCT and coconut oil. C8 showed the highest ketogenicity.
This study investigates the role of individual differences in channel choice and switching behavior in a multichannel environment using latent class analysis on data from 1512 customers. Psychographic variables from five domains (risk attitudes, cognitive ability, motivation, personality, and decision-making style) serve as covariates for multichannel customer behavior. We identify six segments that differ significantly on six psychographic variables (readiness to take risks, need for cognition, autotelic and instrumental need for touch, and rational and intuitive decision-making styles). The results advance the theory-building of multichannel customer behavior and present insights for proactively managing customer journeys of distinct segments.
Organic food quality is based on processing. While the EU organic production regulation focuses on agricultural production, private standards provide more detailed information about further processing. For the development of organic processing, practitioner perspectives can provide valuable input. To get insight into practitioner perspectives, we conducted semi-structured expert interviews with nine employees of seven partly organic juice processing companies from Germany and Austria. Interview topics were (i) quality of organic juice processing in general, (ii) assessment of specific processing techniques, (iii) product quality of organic juice and (iv) flow of information between producer and consumer. We conducted a thematic analysis. We found that the experts’ understanding of process quality mostly includes more aspects than the EU organic production regulation. It covers the whole food chain plus aspects of social and environmental sustainability. The experts prefer directly bottled juice of local raw materials but chiefly accept juice made from concentrate of exotic raw materials because of environmental concerns. Organic juice is preferred when it is cloudy and natural fluctuations are interpreted as an indicator of natural quality. The experts report that consumer information is challenging because of low food literacy. Raising this might help reduce the number of processed juices on the market.
Purpose: Organic food processing must include organic principles to be authentic. This qualitative study aims to understand the processors' understanding of organic food processing quality.
Design/methodology/approach: This study is based on semi-structured expert interviews with eight employees of six purely or partly organic dairies from Germany and Switzerland. Interview themes are (1) quality of organic milk processing in general, (2) assessment of specific processing techniques, (3) product quality of organic milk and (4) flow of information between producer and consumer. The interviews have been audio-recorded, transcribed verbatim and thematically analysed.
Findings: (1) Experts prefer minimal processing; some prefer artisanal processing, whilst others stress the advantages of mechanisation. (2) High temperature short time (HTST) pasteurisation and mechanical processing techniques are accepted; ultra-high-temperature (UHT) milk processing is partly rejected. (3) Traditional taste and valuable ingredients should be present in the final product. Natural variances are judged positively. (4) Consumers' low level of food technology literacy is challenging for communication.
Research limitations/implications: The results cannot be generalised due to the qualitative study design. Further studies, e.g. qualitative case analyses and studies with a quantitative design, are necessary to deepen the results.
Practical implications: The paper shows which processing technologies experts consider suitable or unsuitable for organic milk. The paper also identifies opportunities to bridge the perceived gap between processors' and consumers' demands.
Originality/value: The study shows the challenges of processors in expressing the processors' understanding of process quality.
Meanwhile, renewable energy sources such as hydropower, solar and wind energy and biomass are increasingly being used to reduce dependence on fossil fuels and thus counteract the ongoing global warming. However, these are also associated with environmental impacts. To that effect, this article takes a closer look at tidal power plants, which are classified as hydroelectric power plants, by conducting a systematic literature review. The results show that the strength and form of the environmental impact depends on the specific location and type of plant. Tidal power plants have an impact on the habitats of marine animals and thus influence their behavior and population. In addition, the operation of tidal power plants changes the sediment distribution, causes a reduction in current velocities and a change in current direction in the surrounding area and leads to a change in wave height. The construction of the power plants is associated with noise, which primarily causes changes in the behavior of some species. Furthermore, the electromagnetic fields generated can also affect marine life. In order to assess the environmental impact of tidal power plants in comparison to other renewable energies, further studies should focus on the environmental impact of the different technologies in relation to the energy yield.
This article discusses the use of artificial intelligence
in the wind energy industry, particularly in addressing
challenges and optimizing the expansion of renewable
energies in Germany. It highlights the application
of artificial intelligence in wind forecasts and yield
predictions, bird detection, wind turbine and farm
design, condition monitoring, and predictive maintenance.
Additionally, it introduces the “WindGISKI”
research project, which aims to use artificial intelligence
to identify new areas for wind turbines. The
project utilizes a neural network to analyze and predict
flight routes, potentially reducing bird mortality.
The document also emphasizes the potential broader
applications of “WindGISKI” in other fields of activity,
such as land use planning and city development.
Overall, it underscores the significant role of artificial
intelligence in addressing challenges in wind energy
and outlines the potential for artificial intelligence
to drive the expansion of renewable energies while
addressing key obstacles.
A new approach to determine the elements carbon, hydrogen, nitrogen and oxygen (CHNO) in polymers by wavelength-dispersive X-ray fluorescence analysis (WDXRF) in combination with partial least squares (PLS) regression was explored. The quantification of CHNO was achieved by using the Rayleigh and Compton scattering spectra of an Rh X-ray tube from 84 different polymers. Concealed differences of the corresponding scattering spectra could be utilized to quantify CHNO in a multivariate manner. It was shown that the developed model was capable of determining these commonly non-measurable matrix elements in polymers using WDXRF. Furthermore, the influence of spectral resolution, which is given by the collimator and the crystal, on the prediction of CHNO was explored in this study. It was found that minimal spectral resolution led to the most accurate CHNO predictions. Information about matrix composition could be used to improve so-called semi-quantitative XRF methods based on fundamental parameters (FP) for the analysis of plastics, soil or other samples with high organic content.
Wind turbine structures take a major role in the
modern conversion to renewable energy sources and
contribute to the creation of a greener world. In recent
years, the development and installation of wind
turbines have seen rapid growth. However, with the
increasing capacity and size of wind farms worldwide,
there are growing concerns about the safety and reliability
of these installations. Therefore, structural
health monitoring and the detection of damage to
wind turbines have gained considerable importance in
research. Wind turbine blades are particularly susceptible
to various types of damage due to environmental
influences. This article provides an overview of signal
responses, sensors used and non-destructive testing
techniques in the field of damage detection on wind
turbine blades. The intention of the article is to give
an insight into the possibilities of structural health
monitoring and at the same time to point out unsolved
problems in this field.