The aquathermolysis of heavy oil from Riphean-Vendian complex with iron-based catalyst: FT-IR spectroscopy data

In this paper, we investigated the influence of steam treatment on structural group composition of resins and asphaltenes of heavy oil. The object of investigation was oil-saturated rocks from Riphean-Vendian complex. The extracted crude oil was determined as a high-viscous fluid. The resins and asphaltenes destructed in a small extent due to thermal treatment. The oil-soluble iron-based catalyst intensified the destructive processes. The content of sulfur compounds (-SO) in resins and asphaltenes drastically decreased due to reduction reaction of sulfoxide to sulfide and hydrogen sulfide. The results showed that catalytic aquathermolysis, even at low temperature ranges, promoted the cracking reaction of most macromolecular components and increased the content of light fractions of heavy oil. Consequently, it reduced its viscosity.     

Governing the dynamics of multi-stage production systems subject to learning and forgetting effects: A simulation study

Managing production systems where production rates change over time due to learning and forgetting effects poses a major challenge to researchers and practitioners alike. This task becomes especially difficult if learning and forgetting effects interact across different stages in multi-stage production systems as rigid production management rules are unable to capture the dynamic character of constantly changing production rates. In a comprehensive simulation study, this paper first investigates to which extent typical key performance indicators (KPIs), such as the number of setups, in-process inventory, or cycle time, are affected by learning and forgetting effects in serial multi-stage production systems. The paper then analyses which parameters of such production systems are the main drivers of these KPIs when learning and forgetting occur. Lastly, it evaluates how flexible production control based on Goldratt’s Optimised Production Technology can maximise the benefits learning offers in such systems. The results of the paper indicate that learning and forgetting only have a minor influence on the number of setups in serial multi-stage production systems. The influence of learning and forgetting on in-process inventory and cycle time, in contrast, is significant, but ambiguous in case of in-process inventory. The proposed buffer management rules are shown to effectively counteract this ambiguity.     

Correction to: How the analysis of transitionary references in knowledge networks and their centrality characteristics helps in understanding the genesis of growing technology areas

Scientometrics - In the original publication of the article, the project ID was published incorrectly in the Acknowledgements section. The correct Acknowledgement is given in this correction.     

Fatigue life prediction of structural steel using acoustic birefringence and characteristics of persistent slip bands

Nondestructive evaluation methods provide additional information about the material fatigue behavior and enhance the comprehension of damage evolution thanks to relationship between microstructure and physical properties. This paper deals with optical and ultrasonic investigations of structural steel specimens tested for low-cycle fatigue. The development of persistent slip bands observed on the surface with an optical microscope was quantified using a previously trained neural network and fractal analysis. A surface damage parameter was defined as the ratio of total area of detected slip bands to the area of observed surface. Relationships between the rate of change and critical value of the damage parameter, the strain range, and the fatigue life were established. A single square relationship between relative number of cycles and ratio of the surface damage parameter to its critical value was obtained. Acoustic birefringence was measured by the echo method. The effect of the strain range on the rate of change in acoustic birefringence was investigated. A single linear relationship between relative number of cycles and change in acoustic birefringence was established. An algorithm for predicting the material remaining life, combining optical and ultrasonic data, was proposed.     

Gamblified digital product offerings: an experimental study of loot box menu designs

Electronic Markets - To augment traditional monetization strategies, digital platform providers increasingly draw on gamblification (i.e., the use of gambling design elements). By means of gambling...     

Automated reference-free detection of motion artifacts in magnetic resonance images

Objectives

Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture.

Materials and methods

T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation. Using these patches as input data, a convolutional neural network (CNN) was trained to derive probability maps for the presence of motion artifacts. A deep visualization offers a human-interpretable quality control of the trained CNN. Results were visually assessed on probability maps and as classification accuracy on a per-patch, per-slice and per-volunteer basis.

Results

On visual assessment, a clear difference of probability maps was observed between data sets with and without motion. The overall accuracy of motion detection on a per-patch/per-volunteer basis reached 97%/100% in the head and 75%/100% in the abdomen, respectively.

Conclusion

Automated detection of motion artifacts in MRI is feasible with good accuracy in the head and abdomen. The proposed method provides quantification and localization of artifacts as well as a visualization of the learned content. It may be extended to other anatomic areas and used for quality assurance of MR images.

     

Maternal inhalation of carbon black nanoparticles induces neurodevelopmental changes in mouse offspring

Background

Engineered nanoparticles are smaller than 100 nm and designed to improve or creating even new physico-chemical properties. Consequently, toxicological properties of materials may change as size reaches the nm size-range. We examined outcomes related to the central nervous system in the offspring following maternal inhalation exposure to nanosized carbon black particles (Printex 90).

Methods

Time-mated mice (NMRI) were exposed by inhalation, for 45 min/day to 0, 4.6 or 37 mg/m³ aerosolized carbon black on gestation days 4–18, i.e. for a total of 15 days. Outcomes included maternal lung inflammation (differential cell count in bronchoalveolar lavage fluid and Saa3 mRNA expression in lung tissue), offspring neurohistopathology and behaviour in the open field test.

Results

Carbon black exposure did not cause lung inflammation in the exposed females, measured 11 or 28–29 days post-exposure. Glial fibrillary acidic protein (GFAP) expression levels were dose-dependently increased in astrocytes around blood vessels in the cerebral cortex and hippocampus in six weeks old offspring, indicative of reactive astrogliosis. Also enlarged lysosomal granules were observed in brain perivascular macrophages (PVMs) in the prenatally exposed offspring. The number of parvalbumin-positive interneurons and the expression levels of parvalbumin were decreased in the motor and prefrontal cortices at weaning and 120 days of age in the prenatally exposed offspring. In the open field test, behaviour was dose-dependently altered following maternal exposure to Printex 90, at 90 days of age. Prenatally exposed female offspring moved a longer total distance, and especially males spent significantly longer time in the central zone of the maze. In the offspring, the described effects were long-lasting as they were present at all time points investigated.

Conclusion

The present study reports for the first time that maternal inhalation exposure to Printex 90 carbon black induced dose-dependent denaturation of PVM and reactive astrocytes, similarly to the findings observed following maternal exposure to Printex 90 by airway instillation. Of note, some of the observed effects have striking similarities with those observed in mouse models of neurodevelopmental disorders.

     

Vacuum compatible sample positioning device for matrix assisted laser desorption∕ionization Fourier transform ion cyclotron resonance mass spectrometry imaging

The high mass accuracy and resolving power of Fourier transform ion cyclotron resonance mass spectrometers (FT-ICR MS) make them ideal mass detectors for mass spectrometry imaging (MSI), promising to provide unmatched molecular resolution capabilities. The intrinsic low tolerance of FT-ICR MS to RF interference, however, along with typically vertical positioning of the sample, and MSI acquisition speed requirements present numerous engineering challenges in creating robotics capable of achieving the spatial resolution to match. This work discusses a two-dimensional positioning stage designed to address these issues. The stage is capable of operating in ～1 × 10(-8) mbar vacuum. The range of motion is set to 100 mm × 100 mm to accommodate large samples, while the positioning accuracy is demonstrated to be less than 0.4 micron in both directions under vertical load over the entire range. This device was integrated into three different matrix assisted laser desorption∕ionization (MALDI) FT-ICR instruments and showed no detectable RF noise. The "oversampling" MALDI-MSI experiments, under which the sample is completely ablated at each position, followed by the target movement of the distance smaller than the laser beam, conducted on the custom-built 7T FT-ICR MS demonstrate the stability and positional accuracy of the stage robotics which delivers high spatial resolution mass spectral images at a fraction of the laser spot diameter.     

Exchange reactions control for selective separation of glyoxylic acid in technological mixtures of glyoxal oxidation

Separation of glyoxylic acid from unpurified multicomponent technological mixtures, resulting in the process of direct oxidation of glyoxal, and preparation of sodium glyoxylate are developed. The mixtures are treated with an optimal amount of CaCO_3, which has to be prespecified by acidic–basic titration of the technological mixtures. Both separation of glyoxylic acid and preparation of sodium glyoxylate take place owing to ionic exchange reactions: calcium glyoxylate is easily converted into glyoxylic acid by action of oxalic acid. Reaction with Na₂CO₃ leads to the formation of sodium glyoxylate.     

Radiation-Induced Fault Simulation of SOI/SOS CMOS LSI’s Using Universal Rad-SPICE MOSFET Model

The methodology of modeling and simulation of environmentally induced faults in radiation hardened SOI/SOS CMOS IC’s is presented. It is realized at three levels: CMOS devices – typical analog or digital circuit fragments – complete IC’s. For this purpose, a universal compact SOI/SOS MOSFET model for SPICE simulation software with account for TID, dose rate and single event effects is developed. The model parameters extraction procedure is described in great depth taking into consideration radiation effects and peculiarities of novel radiation-hardened (RH) SOI/SOS MOS structures. Examples of radiation-induced fault simulation in analog and digital SOI/SOS CMOS LSI’s are presented for different types of radiation influence. The simulation results show the difference with experimental data not larger than 10–20% for all types of radiation.